Miao Hu

New data are reported from the operation of a 4.0 kg CF$_{3}$I bubble chamber in the 6800-foot-deep SNOLAB underground laboratory. The effectiveness of ultrasound analysis in discriminating alpha-decay background events from single nuclear recoils has been confirmed, with a lower bound of $>$99.3% rejection of alpha-decay events. Twenty single nuclear recoil event candidates and three multiple bubble events were observed during a total exposure of 553 kg-days distributed over three different bubble nucleation thresholds. The effective exposure for single bubble recoil-like events was 437.4 kg-days. A neutron background internal to the apparatus, of known origin, is estimated to account for five single nuclear recoil events and is consistent with the observed rate of multiple bubble events. This observation provides world best direct detection constraints on WIMP-proton spin-dependent scattering for WIMP masses $>$20 GeV/c$^{2}$ and demonstrates significant sensitivity for spin-independent interactions.

Bubble chambers were the dominant technology used for particle detection in accelerator experiments for several decades, eventually falling into disuse with the advent of other techniques. We report here on a new application for these devices. We operated an ultraclean, room-temperature bubble chamber containing 1.5 kilograms of superheated CF3I, a target maximally sensitive to spin-dependent and -independent weakly interacting massive particle (WIMP) couplings. An extreme intrinsic insensitivity to the backgrounds that commonly limit direct searches for dark matter was measured in this device under operating conditions leading to the detection of low-energy nuclear recoils like those expected from WIMPs. Improved limits on the spin-dependent WIMP-proton scattering cross section were extracted during our experiments, excluding this type of coupling as a possible explanation for a recent claim of particle dark-matter detection.

Data from the operation of a bubble chamber filled with 3.5 kg of CF3I in a shallow underground site are reported. An analysis of ultrasound signals accompanying bubble nucleations confirms that alpha decays generate a significantly louder acoustic emission than single nuclear recoils, leading to an efficient background discrimination. Three dark matter candidate events were observed during an effective exposure of 28.1 kg day, consistent with a neutron background. This observation provides strong direct detection constraints on weakly interacting massive particle (WIMP)-proton spin-dependent scattering for WIMP masses >20 GeV/c2.

Metal phosphides are superior anode materials for secondary batteries but suffer from variable volume and low electronic conductivity. In this work, chemically bonded metal [email protected] nanowire arrays with adjustable structure mounted on foam metal were synthesized via a general facile chemical vapor deposition (CVD)-like approach using an environmentally friendly, solid ionic resin as a phosphorus source. The diameter of the nanowires and thicknesses of the carbon shell could be tailored via control of the synthesis conditions. Using a Fe2[email protected] array on iron foam as an example, it was demonstrated that the new materials could be used directly as an electrode in sodium-ion batteries (SIBs) without any additives or post-processing. The Fe2[email protected] electrode delivered a significantly high area capacity of 0.40 mAh cm–2 after 1400 cycles at a current density of 3 mA cm–2, a capacity retention rate of 80.25%, which is, to the best of our knowledge, one of the most stable, high surface capacity performances achieved in SIBs at this large current density. Tests showed that the Fe2[email protected] nanowire array on a 3D foam structure provided a larger exposure area for electrolyte penetration, a shorter passage for Na+ diffusion, and faster electronic transfer. In situ TEM revealed that the carbon shell effectively alleviated volume expansion of the Fe2P and in-situ Raman and XRD verified the mechanism and high reversibility of Fe2[email protected]

Nanoporous poly(ionic liquid)s with both great porosities and high IL contents are prepared through a two-step synthetic strategy, serving as efficient heterogeneous catalysts for CO 2 cycloaddition with epoxides under mild conditions.

The caching behavior of rodents is widely considered to facilitate plant seed dispersal and seedling regeneration in forest ecosystems. Studies supporting this theory have been based mainly on experimental results from natural forests; however, whether scatter-hoarding rodents play an important role in seed dispersal and seedling regeneration in tree plantations remains unclear. In this study, we tracked 4,000 seeds over 2 years in a Pinus armandii plantation in southwest China to investigate their fate from seed removal to survival after hoarding. We found that rodents removed more than 30.0% of the released seeds in both years, 9.9% to 29.1% of the seeds were scatter-hoarded under the leaf litter or on the soil surface, and a few seeds were removed two to three times. The dispersal distance of scatter-hoarded seeds ranged from 0.4 to 14.5 m with a mean of 3.55 m, and re-caching processes increased the dispersal distance of cached seeds. Additionally, 18.9% of the removed seeds survived in the cache until the end of the observation period. Our results suggested that scatter-hoarding rodents play an important role in seed dispersal in planted forests.

Insulator is a kind of key electrical equipment in transmission line. Its long-term operation in strong electric field, high temperature sunshine, mechanical stress, humidity, dirt and other complex environment. This is likely to lead to self-detonation, pollution, flashover and leakage current and other defects, which will reduce insulation performance and seriously affect the safety of power grid. Therefore, power insulator defect detection is an important task in power system detection. How to identify insulator defects quickly and accurately has been an important problem for many scholars. Firstly, this paper reviews the insulator defect detection technology based on traditional detection algorithm. Secondly, the application and key technologies of deep learning algorithm in insulator defect detection are introduced in detail. Then it introduces the challenges and future development trend of this field; Finally, it summarizes this paper and puts forward some suggestions for the development of this field.

Wood material is the foundation of wood structure architecture, and its production technology and equipment technology decide the development and upgrading of modern wood structure architecture. Aiming at the problems of low automation degree, low material utilization rate, low production efficiency and high labor costs in the process of traditional wood processing, we explore the integration and innovation of the traditional wood processing industry and modern industrial Internet information technology on the basis of studying the properties of Betula (Betula costata) solid wood materials, wood comprehensive utilization rate, wood structure component development and processing technology requirements, and form an intelligent, automatic and industrial production mode for building materials. Through technology and methods such as mechanical design, automation technology, machine vision, deep learning, optimization algorithm, electronic design automation, computer aided manufacturing, etc., the key technologies of intelligent automatic optimization of wood materials were studied, and intelligent automatic production lines of Betula species identification, log optimization sawing, solid timber longitudinal multiblade sawing, sawn timber quality detection and solid timber optimizing cross-cuts are built. Based on the machine vision method, features are extracted; a tree species, defect classification and recognition model database is established; an image processing algorithm with high recognition accuracy, as well as fast processing speed and high robustness are studied; non-destructive testing and classification methods of machine vision are optimized; key problems of online rapid classification, detection and optimization of sawing are solved and production quality and processing efficiency are improved. Finally, the timber defect detection accuracy and Betula timber yield are analyzed, and the comprehensive utilization value of optimized sawing timber is compared with the comprehensive utilization value of manually marking sawing timber. The processing cost and efficiency of Betula sawing timber with an intelligent automatic production line are calculated. The test results show that the average detection accuracy of timber defect type, size and location is 89.69%, 89.69%, 92.25% and 82.29%, respectively, and the detection stability is high. By adopting intelligent automatic detection, classification and optimization sawing production line of wood, the comprehensive utilization value of optimized sawing timber is 14.13% higher than that of manual marking sawing timber, and 16,089.29 m3 more building materials can be processed annually. In the process of intelligent automatic wood processing, the intelligent detection system is used to detect defects, improve production performance and production efficiency and reduce labor costs. Compared with the traditional wood processing process, the method studied in this paper is improved to optimize the production line processing performance and processing technology. The research and development of an intelligent automatic production system for solid wood can promote the application and development of an automatic industrial production mode for sawn timber for the wood structure construction industry, deepen the integration of artificial intelligence technology, Internet technology and the whole wood processing industry and lead the upgrading of building materials for wood structures to an intelligent manufacturing production mode.

Since the mid-1990s, information technology, particularly the diffusion of the internet, has brought tremendous changes to communication and social participation for people in China, including older adults. At the same time, modernisation and urbanisation have transformed the way many people in China live. The traditional multigenerational household-older adults living with adult children and grandchildren-is giving way to other living arrangements, such as living alone or with a spouse only. Using wave 1 of the World Health Organization Study on Global AGEing and Adult Health collected between 2007 and 2010, we examined the extent to which home internet access might be associated with cognitive function in older adults aged 50 or over in urban China (N = 5,898), paying attention to the moderating role of living arrangements. We found that home internet access was associated with better cognitive function, and living arrangements played an essential role in such an association for different age groups. Specifically, older adults living alone benefited cognitively from internet access, particularly among those aged 50-64 and 65-74. Those living with a spouse only and those in two-generation households benefited cognitively from internet access, particularly among those aged 50-64 and 75+. Older adults age 75+ in skip-generation households benefited cognitively from internet access. Considering the trend of older adults living apart from their children, our research suggests that providing internet access to older adults in urban China, especially those living alone, could help protect their cognitive function.

Extracellular vesicles (EVs) act as multifunctional regulators of intercellular communication and are involved in diverse tumor phenotypes, including tumor angiogenesis, which is a highly regulated multi-step process for the formation of new blood vessels that contribute to tumor proliferation. EVs induce malignant transformation of distinct cells by transferring DNAs, proteins, lipids, and RNAs, including noncoding RNAs (ncRNAs). However, the functional relevance of EV-derived ncRNAs in tumor angiogenesis remains to be elucidated. In this review, we summarized current research progress on the biological functions and underlying mechanisms of EV-derived ncRNAs in tumor angiogenesis in various cancers. In addition, we comprehensively discussed the potential applications of EV-derived ncRNAs as cancer biomarkers and novel therapeutic targets to tailor anti-angiogenic therapy.

We investigate the influence of transverse mode distribution on the self-mode-locked (SML) states by employing off-axis pumping in an Nd:YVO4 laser with a linear concave-plano cavity. The higher-order transverse modes in the cavity are excited by adjusting the off-axis pumping displacement, and the dependence of the time characteristics of the SML laser on the transverse modes is analyzed. When the laser cavity length is 50 mm, and the off-axis displacement is adjusted offsets in the radial x and y directions to be (0,0) μ m, (45,58) μ m, and (80,0) μ m, the laser is operated in the longitudinal SML state with a repetition rate of 2.72 GHz, the amplitude modulation mode-locked pulse with a modulation frequency of 0.68 GHz and a repetition rate of 2.72 GHz, and the total-self-mode-locked with a repetition rate of 0.68 GHz, respectively. The corresponding transverse mode patterns are TEM00, TEM00+TEM01+TEM10 superposition, and TEM00+TEM10+TEM20 superposition. Finally, numerical simulations reconstruct the experimental mode-locked pulse and the corresponding transverse mode patterns based on the theory of coherent superposition of laser modes.

The interactions between gold nanoclusters (AuNCs) and proteins have been extensively investigated. Nevertheless, the structure-activity relationship between gold nanoclusters and proteins in terms of ligand isomerization remained unclear. Here, interactions between Au25NCs modified with para-, inter- and ortho-mercaptobenzoic acid (p/m/o-MBA-Au25NCs) and human serum albumin (HSA) were analyzed. The results of the multispectral approach showed that all three gold nanoclusters bound to the site I in dynamic modes to increase the stability of HSA. There were significant differences in the binding intensity, thermodynamic parameters, main driving forces, and binding ratios between these three gold nanoclusters and HSA, which might be related to the existence forms of the three ligands on the surface of AuNCs. Due to the different polarities of AuNCs themselves, the impact of three AuNCs on the microenvironment of amino acid residues in HSA was also different. It could be seen that ligand isomerization significantly affected the interactions between gold nanoclusters and proteins. This work will provide theoretical guidance for ligand selection and biological applications of metal nanoclusters.

Nonalcoholic fatty liver disease (NAFLD) is closely related to metabolic syndrome (MetS). Bone morphogenetic protein 9 (BMP9) is an essential factor in glucose, lipid and energy metabolism. This study aims to investigate whether BMP9 can serve as a serological marker for the severity of NAFLD or MetS. Blood samples, clinical data and FibroTouch test were collected from consecutively recruited 263 individuals in Shanghai East hospital. All the participants were divided into three groups: the healthy controls, nonalcoholic fatty liver (NAFL) group and nonalcoholic steatohepatitis (NASH) at-risk group according to the results of FibroTouch test and liver function. Serum BMP9 levels were measured by enzyme-linked immunosorbent assay. Serum BMP9 levels were positively correlated with transaminase, triglyceride, fasting plasma glucose, glycated hemoglobin (HbA1c) and uric acid while it showed a downward trend as the increasing number of MetS components. Furthermore, it differentiated NASH at-risk (58.13 ± 2.82 ng/L) from the other groups: healthy control (70.32 ± 3.70 ng/L) and NAFL (64.34 ± 4.76 ng/L) (p < 0.0001). Controlled attenuation parameter of liver fat and liver stiffness measurement were negatively correlated with BMP9 levels, while high-density lipoprotein levels were positively correlated. The risk of developing NAFLD increased along with elevated serum BMP9 and BMI, and a significantly higher risk was observed in men compared to women. BMP9 should be considered a protective factor for the onset and development of NAFLD, as well as a promising biomarker for the severity of the NAFLD and MetS.

Treatment of spine fractures may require periods of prolonged immobilization which prevents effective pulmonary toileting. We hypothesized that patients with longer time to mobilization, as measured by time to first physical therapy (PT) session, would have higher pulmonary complications.We performed a retrospective review of all trauma patients with cervical and thoracolumbar spinal fractures admitted to a level 1 trauma center over a 12-month period. Demographic data collection included age, gender, BMI, pulmonary comorbidities, concomitant rib fractures, admission GCS, Injury Severity Score (ISS), GCS at 24 h, treatment with cervical or thoracolumbar immobilization, and time to first PT evaluation. The primary outcome was the presence of any one of the following complications: unplanned intubation, pneumonia, or mortality at 30 days. Multivariable logistic regression analysis was used to assess significant predictors of pulmonary complication.In total, 491 patients were identified. In terms of overall pulmonary complications, 10% developed pneumonia, 13% had unplanned intubation, and 6% died within 30 days. In total, 19% developed one or more complication. Overall, 25% of patients were seen by PT <48 h, 33% between 48 and 96 h, 19% at 96 h to 1 week, and 7% > 1 week. Multivariable logistic regression analysis showed that time to PT session (OR 1.010, 95% CI 1.005-1.016) and ISS (OR 1.063, 95% CI 1.026-1.102) were independently associated with pulmonary complication.Time to mobility is independently associated with pulmonary complications in patients with spine fractures.

Abstract We experimentally demonstrated the phenomenon of period-multiplying pulses in the self-mode-locking Nd:YVO 4 laser. With a fixed cavity length of 50 mm and the input mirrors in the resonator with radii of curvature of 100 mm, 200 mm, and 500 mm, the mode-locked pulses with pulse periods 4 times, 6 times and 10 times the fundamental mode-locked pulse period are observed respectively. Besides, by tilting the angle of the output mirror to control the spatial distribution of transverse modes, the switching between the period-multiplication state and its harmonic self-locking state can be achieved. Numerical simulations further confirm that this period-multiplying phenomenon results from the simultaneous locking of multi-longitudinal and multi-transverse modes. This study is of great significance for understanding the complex transverse dynamics in the self-mode-locking lasers.

Optimal cache spacing theory predicts that scatter-hoarding animals cache seeds at a density that balances the gains of reducing cache pilferage with the costs of transporting seeds over larger distances. Animals cannot indefinitely reduce the density of cached seeds and should distribute seeds within a convenient range. The hypothesis is that scatter-hoarding animals can optimize cache size and distribution to reduce cache pilferage without increasing transport effort. In this study, we used artificial caches of Chinese Armand pine seeds to investigate whether cache distribution patterns and cache sizes could impact cache loss in a pine plantation in southwest China. Artificially created caches of three different sizes (one, two and four seeds) and two distribution patterns (uniform and random) were laid out and their pilferage was assessed. Cache distribution and size had an interactive effect on the survival time of caches. The cache and seed survival times for randomly distributed one- and four-seed caches were found to be longer than those for uniformly distributed caches, whereas for the two-seed caches, we detected no significant difference in cache and seed survival time between uniform and random distribution caches. Although larger randomly distributed caches were more likely to be discovered, the seeds in these caches may survive longer. In contrast, for caches with a uniform distribution, two-seed caches and their seeds were less likely to be discovered than one- and four-seed caches. Our findings in this study indicate that cache size and distribution pattern significantly affected the probability of caches and seeds being discovered. We propose that by optimizing cache size and distribution, scatter-hoarding animals can reduce the likelihood of cache pilferage.

Abstract In order to be utilized in the design of a wood building, the lumber must pass grade. Machine-vision inspection grading offers higher efficiency and accuracy than traditional manual visual grading. In this paper, a fast and accurate method for identifying defects in large-size structural lumber based on machine vision of Fujian Chinese fir (Cunninghamia lanceolata (Lamb.) Hook) constructional lumber (FCF CL) is proposed. Specifically, the grey matrix of the captured images on the surface of the sawn timber is initially scanned and the pixel weights on the edges of the image greyness variables are calculated. A matrix-valued torus was formed by fitting the knot edge profile and analyzing changes in the gradient values at the knot's edge, as well as calculating the directional derivative's rate of change. The knot three-dimensional mapping curves were projected onto the plane to form horizontal rise contours. Observe from the contour map of the whole large-size sawn timber, and extract the positional information of the knot where there is a trough (groove). The test results show that the rRMSE (Relative Root Mean Square Error) measured at the x axis position of knots is within 0.49 percent; the rRMSE measured at the y axis is 0.35 percent, which has high detection accuracy and meets the production requirements. We also investigated the effect of knots in different positions on the modulus of elasticity and the bending strength of FCF CL, with a view to establishing a link between machine-vision knot detection and mechanical properties of sawn timber in our next work.

Pulse signal detection is widely used in nuclear explosion electromagnetic pulse detection, lightning signal detection, power system partial discharge detection, electrostatic discharge detection, and other fields. The signal strength becomes weak with the increase of the detection distance and may be submerged in strong Gaussian noise for remote detection. Therefore, the detection and recovery of the weak signals, especially the weak pulse signals, have important applications in signal processing area. Some methods have been reported to detect and estimate weak pulse signals in strong background noise. Coupled Duffing oscillators are usually used in processing periodic signals, though it is still in an exploration stage for aperiodic transient signals. There remain some problems to be solved, for example, the system performance depends on some initial values, results are valid only for the period-doubling bifurcation state, the waveform time domain information cannot be accurately estimated, etc. In this paper, we explain the reasons why there exist these inherent defects in the current weakly coupled Duffing oscillators. In order to solve the above-mentioned problems, a new signal detection and recovery model is constructed, which is characterized by coupling the restoring force and damping force of the two oscillators simultaneously. A large coupling coefficient is applied to the two Duffing oscillators, and a generalized " in-well out-of-synchronization”phenomenon arises between the oscillators which conduces to detecting and recovering the weak pulse signals, and also overcoming the defects mentioned above. Using the metrics of signal-to-noise ratio improvement (SNRI) and waveform similarity, the effects of amplitude and period of periodic driving force, coupling coefficient, step size and damping coefficient on signal detection and waveform recovery are studied. Finally, experiments are performed to detect and recover the following three kinds of pulses: square wave pulses, double exponential pulses, and Gaussian derivative pulses. The input SNR thresholds of these three waveforms are –15, –12, and –16 dB, respectively, under the detection probabilities and waveform similarity all being greater than 0.9 simultaneously. The maximum error of the pulse amplitude and pulse width are both less than 5% of their corresponding true values. In summary, the strongly coupled Duffing system has advantages of being able to operate in any phase-space state and being no longer limited by the initial values. Especially, the time domain waveform of weak pulse signals can be well recovered in the low SNR case, and the error and the minimum mean square error are both very low.

As an important part of metal processing, welding is widely used in industrial manufacturing activities, and its application scenarios are very extensive. Due to technical limitations, the welding process always unavoidably leaves weld defects. Weld defects are extremely hazardous, and the work used must be guaranteed to be defect-free, regardless of the field. However, manual weld inspection has subjective factors such as inefficiency and easy missed detection, and although some automatic weld inspection methods have appeared, these traditional methods still do not meet actual demand in terms of detection time and detection accuracy. Therefore, there is a need for a higher quality weld image automatic detection method to replace the manual method and the traditional automatic detection method. In view of the above, this paper proposes a weld seam image recognition algorithm based on deep learning. The Adam adaptive moment estimation algorithm is chosen as the backpropagation optimization algorithm to accelerate the training of convolutional neural networks and design an independent adaptive learning rate. Through the simulation of the collected 4500 tube images, the adaptive threshold-based method is used for weld seam extraction. The algorithm proposed in this paper is compared with the weld seam recognition method based on image texture feature value distribution (ITFVD) and the SUSAN-based weld defect target detection method. The results show that the proposed method can identify weld defects in a short time on different sizes of weld images, and can further detect the type of weld defects. In addition, the method in this paper is better than the other two methods in the false detection rate, recall rate and overall recognition accuracy, which shows that the experimental results have achieved the expected results.

Checkpoint inhibitors are designed to rejuvenate depleted or suppressed T cells in the tumor microenvironment, relying on the immune system to control and kill tumors. However, accumulating evidence indicates that tumor-infiltrating neutrophils impede the proliferation and activation of T cells and determine the resistance to checkpoint blockade and chemotherapy. In this study, sialic acid ligand-modified colchicine derivative phospholipid complexes specifically targeted tumor-associated neutrophils in the peripheral blood, blocked neutrophil accumulation in tumors, and attenuated the inhibitory effect of infiltrating neutrophils on T cells. Neutrophil blocking therapy enhanced the immunotherapy effect of the PD-L1 antibody in S180 advanced tumors and 4T1 breast cancer. Our study found that PD-L1 antibody monotherapy increased the tumor infiltration of immunosuppressive neutrophils. Combination therapy with neutrophil blocking can greatly reduce tumor-infiltrating neutrophils and increase the proliferation of cytotoxic CD8+ T lymphocytes in the tumor. The combination therapy significantly improved the survival rate of mice with advanced S180 tumors and increased the sensitivity of immune checkpoint inhibitors to 4T1 cold tumors.

Using resonant inelastic x-ray scattering, we measure the paramagnon dispersion and damping of undoped, antiferromagnetic ${\mathrm{Ca}}_{2}{\mathrm{CuO}}_{2}{\mathrm{Cl}}_{2}$ as well as doped, superconducting ${\mathrm{Na}}_{x}{\mathrm{Ca}}_{2\text{\ensuremath{-}}x}{\mathrm{CuO}}_{2}{\mathrm{Cl}}_{2}$. Our estimation of the spin-exchange parameter and width of the paramagnon peak at the zone boundary $X=(0.5,0)$ confirms that no simple relation can be drawn between these parameters and the critical temperature ${T}_{\mathrm{c}}$. Consistently with other cuprate compounds, we show that upon doping there is a slight softening at (0.25,0) but not at the zone boundary $X$. In combination with these measurements we perform calculations of the dynamical spin structure factor of the one-band Hubbard model using cluster dynamical mean-field theory. The calculations are in excellent agreement with the experiment in the undoped case, both in terms of energy position and width. While the increase in width is also captured upon doping, the dynamical spin structure factor shows a sizable softening at $X$, which provides insightful information on the length-scale of the spin fluctuations in doped cuprates.

In this paper, we present a compact model of the spintronic memristor based on the magnetic-domain-wall motion mechanism for circuit design. Our model also takes into account the variations of material parameters and fabrication process, which significantly affects the actual electrical characteristics of a memristor in nano-scale technologies. Our proposed model can be easily implemented by Verilog-A languages and compatible to SPICE-based simulation. Based on our model, we also show some potential applications of memristor in computing system, including the detailed analysis and optimizations based on our proposed model.

An understanding of the scientific layout of surface water space is crucial for the sustainable development of human society and the ecological environment. The objective of this study was to use land-use/land-cover data to identify the spatiotemporal dynamic change processes and the influencing factors over the past three decades in Henan Province, central China. Multidisciplinary theories (landscape ecology and graph theory) and methods (GIS spatial analysis and SPSS correlation analysis) were used to quantify the dynamic changes in surface water pattern and connectivity. Our results revealed that the water area decreased significantly during the periods of 1990–2000 and 2010–2018 due to a decrease in tidal flats and linear waters, but increased significantly in 2000–2010 due to an increase in patchy waters. Human construction activities, socioeconomic development and topography were the key factors driving the dynamics of water pattern and connectivity. The use of graph metrics (node degree, betweenness centrality, and delta probability of connectivity) in combination with landscape metrics (Euclidean nearest-neighbor distance) can help establish the parameters of threshold distance between connected habitats, identify hubs and stepping stones, and determine the relatively important water patches that require priority protection or development.

The fourth fundamental passive circuit element - memristor, has received the increased attentions after a real device was demonstrated by HP Lab in 2008. The distinctive characteristic of a memristor to record the historical profile of the voltage/current through itself creates great potentials in highly integrated circuit and system design. Among all the proposed memristor structures, magnetic-based spintronic memristor becomes a promising technology for its simple structure and the compatibility to the traditional CMOS process. In this paper, we depict a compact model of the spintronic memristor based on the magnetic-domain-wall motion mechanism. Our model takes into account the variations of material parameters and fabrication process, which significantly affect the actual electrical characteristics of a memristor in nano-scale technologies. Furthermore, we present the applications of the compact model, analyze the effect of process variations on memristor electrical properties, and discuss the corresponding circuit design considerations. Our proposed compact model can be easily implemented in Verilog-A language, compatible to SPICE-based simulation, and beneficial to minimize the design margin of memristor-based circuit implementations.

Neuromorphic computing, which is inspired by the working mechanism of human brain, recently emerges as a hot research area to combat the contradiction between the limited functions of computing systems and the ever increasing variety of applications. In this work, we will introduce our research on a bio-inspired neuromorphic embedded computing engine named Centaur, which aims to achieve an ultra-high power efficiency beyond One-TeraFlops-Per-Watt by adopting the bio-inspired computation model and the advanced memristor technology. The success of Centaur design may promote the embedded system power efficiency three orders of magnitude from the current level while the small footprint and real-time re-configurability of the design allow an easy integration into MPSoCs, enabling many emerging mobile and embedded applications.

Abstract Background Portal vein thrombosis is a common complication of liver cirrhosis and hepatocellular carcinoma; however, few studies have reported its long-term clinical prognosis. This study aimed to establish and validate easy-to-use nomograms for predicting gastrointestinal bleeding, portal vein thrombosis resolution, and mortality of patients with portal vein thrombosis. Methods This multicenter retrospective cohort study included 425 patients with portal vein thrombosis who were divided into training ( n = 334) and validation ( n = 91) sets. Prediction models were developed using multivariate Cox regression analysis and evaluated using the consistency index and calibration plots. Results Predictors of gastrointestinal bleeding included a history of gastrointestinal bleeding, superior mesenteric vein thrombosis, red color sign observed during endoscopy, and hepatic encephalopathy. Meanwhile, predictors of resolution of portal vein thrombosis included a history of abdominal infection, C-reactive protein and hemoglobin levels, and intake of thrombolytics. Predictors of death included abdominal infection, abdominal surgery, aspartate aminotransferase level, hepatic encephalopathy, and ascites. All models had good discriminatory power and consistency. Anticoagulation therapy significantly increased the probability of thrombotic resolution without increasing the risk of bleeding or death. Conclusions We successfully developed and validated three prediction models that can aid in the early evaluation and treatment of portal vein thrombosis.

Electronic states within superconducting vortices hold crucial information about paring mechanisms and topology. While scanning tunneling microscopy/spectroscopy(STM/S) can image the vortices, it is difficult to isolate the intrinsic electronic states from extrinsic effects like subsurface defects and disorders. We combine STM/S with unsupervised machine learning to develop a method for screening out the vortices pinned by embedded disorder in Fe-based superconductors. The approach provides an unbiased way to reveal intrinsic vortex-core states and may address puzzles on Majorana zero modes.

We investigated the thermal transport properties of two $\alpha$-RuCl$_3$ crystals with different degrees of stacking disorder to understand the origin of the previously reported oscillatory feature in the field dependence of thermal conductivity. Crystal I shows only one magnetic order around 13\,K, which is near the highest T$_N$ for $\alpha$-RuCl$_3$ with stacking faults. Crystal II has less stacking disorder, with a dominant heat capacity at 7.6\,K along with weak anomalies at 10\,K and 13\,K. In the temperature and field dependence of thermal conductivity, no obvious anomaly was observed to be associated with the magnetic order around 13\,K for either crystal or around 10\,K for crystal II. Crystal II, with less disorder, showed clear oscillations in the field dependence of thermal conductivity, while crystal I, with more disorder, did not. For crystal I, an L-shaped region in the temperature-field space was observed where thermal Hall conductivity $\kappa_{xy}$/T is within $\pm$20\% of the half quantized thermal Hall conductivity $\kappa_{HQ}$/T. While for crystal II, $\kappa_{xy}$/T reaches $\kappa_{HQ}$/T only in the high field and high temperature regime with no indication of a plateau at $\kappa_{HQ}$/T. Our thermal conductivity data suggest the oscillatory features are inherent to the zig-zag ordered phase with T$_N$ near 7\,K. Our planar thermal Hall effect measurements highlight the sensitivity of this phenomena to stacking disorder. Overall, our results highlight the importance of understanding and controlling crystallographic disorder for obtaining and interpreting intrinsic thermal transport properties in $\alpha$-RuCl$_3$.

$\alpha$-RuCl$_3$, a well-known candidate material for Kitaev quantum spin liquid, is prone to stacking disorder due to the weak van der Waals bonding between the honeycomb layers. After a decade of intensive experimental and theoretical studies, the detailed correlation between stacking degree of freedom, structure transition, magnetic and thermal transport properties remains unresolved. In this work, we reveal the effects of a small amount of stacking disorder inherent even in high quality $\alpha$-RuCl$_3$ crystals. This small amount of stacking disorder results in the variation of the magnetic ordering temperature, suppresses the structure transition and thermal conductivity. Crystals with minimal amount of stacking disorder have a T$_N>$7.4\,K and exhibit a well-defined structure transition around 140\,K upon cooling. For those with more stacking faults and a T$_N$ below 7\,K, the structure transition occurs well below 140\,K upon cooling and is incomplete, manifested by the diffuse streaks and the coexistence of both high temperature and low temperature phases down to the lowest measurement temperature. Both types of crystals exhibit oscillatory field dependent thermal conductivity and a plateau-like feature in thermal Hall resistivity in the field-induced quantum spin liquid state. However, $\alpha$-RuCl$_3$ crystals with minimal amount of stacking disorder have a higher thermal conductivity that pushes the thermal Hall conductivity to be closer to the half-integer quantized value. These findings demonstrate a strong correlation between layer stacking, structure transition, magnetic and thermal transport properties, underscoring the importance of interlayer coupling in $\alpha$-RuCl$_3$ despite the weak van der Waals bonding.

Using Resonant Inelastic X-ray Scattering, we measure the paramagnon dispersion and damping of undoped, antiferromagnetic Ca$_2$CuO$_2$Cl$_2$ as well as doped, superconducting Na$_{x}$Ca$_{2-x}$CuO$_2$Cl$_2$. Our estimation of the spin-exchange parameter and width of the paramagnon peak at the zone boundary $X=(0.5,0)$ confirms that no simple relation can be drawn between these parameters and the critical temperature $T_\mathrm{c}$. Consistently with other cuprate compounds, we show that upon doping there is a slight softening at $(0.25,0)$, but not at the zone boundary $X$. In combination with these measurements we perform calculations of the dynamical spin structure factor of the one-band Hubbard model using cluster dynamical mean-field theory. The calculations are in excellent agreement with the experiment in the undoped case, both in terms of energy position and width. While the increase in width is also captured upon doping, the dynamical spin structure factor shows a sizable softening at $X$, which provides insightful information on the length-scale of the spin fluctuations in doped cuprates.

To propose and validate a new classification of surgical methods for patients with subaxial cervical hemivertebrae.This article reviewed cases diagnosed with subaxial cervical hemivertebrae in our hospital from January 2008 to December 2019. The results of preoperative (initial visit), postoperative and/or final follow-up were assessed using the Japanese Orthopaedic Association (JOA) score, Neck Disability Index (NDI) score, spinal balance parameters, and Scoliosis Research Society-22 Questionnaire (SRS-22). We also performed a reliability study to assess this classification.The classification includes three types. Each type can be divided into two subtypes, and a preliminary algorithm is proposed. Type I: There is an obvious appearance deformity in the neck, there are hemivertebrae in the cervical spine, and only a single hemivertebra of the subaxial cervical hemivertebra needs to be resected. Type II: There is an obvious appearance deformity in the neck, there are hemivertebrae in the cervical spine, and multiple subaxial cervical hemivertebrae need to be removed. Type III: No apparent deformity in the neck, at least one subaxial cervical hemivertebra existed or Klipper-Feil syndrome. Each type is divided into two subtypes, A and B, according to whether the upper and lower adjacent vertebral bodies of the rescected hemivertebra(e) are fused. We propose corresponding treatment methods for different types. We included a total of 121 patients and reviewed the prognosis for each type of patient. All patients achieved satisfactory results. The reliability study showed that the mean interobserver agreement was 91.8% (89.3%-93.4%), and the κ value was 0.845 (0.800-0.875). The intraobserver agreement ranged from 93.4% to 97.5%, with a mean κ value of 0.929 (0.881 to 0.954).In our study, we proposed and validated a new classification of subaxial cervical hemivertebrae and proposed corresponding treatment plans for different classifications.

Edge computing has been getting a momentum with ever-increasing data at the edge of the network. In particular, huge amounts of video data and their real-time processing requirements have been increasingly hindering the traditional cloud computing approach due to high bandwidth consumption and high latency. Edge computing in essence aims to overcome this hindrance by processing most video data making use of edge servers, such as small-scale on-premises server clusters, server-grade computing resources at mobile base stations and even mobile devices like smartphones and tablets; hence, the term edge-based video analytics. However, the actual realization of such analytics requires more than the simple, collective use of edge servers. In this paper, we survey state-of-the-art works on edge-based video analytics with respect to applications, architectures, techniques, resource management, security and privacy. We provide a comprehensive and detailed review on what works, what doesn't work and why. These findings give insights and suggestions for next generation edge-based video analytics. We also identify open issues and research directions.

In this paper, we propose an augmented subspace based adaptive proper orthogonal decomposition (POD) method for solving the time dependent partial differential equations. By augmenting the POD subspace with some auxiliary modes, we obtain an augmented subspace. We use the difference between the approximation obtained in this augmented subspace and that obtained in the original POD subspace to construct an error indicator, by which we obtain a general framework for augmented subspace based adaptive POD method. We then provide two strategies to obtain some specific augmented subspaces, the random vector based augmented subspace and the coarse-grid approximations based augmented subspace. We apply our new method to two typical 3D advection-diffusion equations with the advection being the Kolmogorov flow and the ABC flow. Numerical results show that our method is more efficient than the existing adaptive POD methods, especially for the advection dominated models.

Federated learning (FL) is a prospective distributed machine learning framework that can preserve data privacy. In particular, cross-silo FL can complete model training by making isolated data islands of different organizations collaborate with a parameter server (PS) via exchanging model parameters for multiple communication rounds. In cross-silo FL, an incentive mechanism is indispensable for motivating data owners to contribute their models to FL training. However, how to allocate the reward budget among different rounds is an essential but complicated problem largely overlooked by existing works. The challenge of this problem lies in the opaque feedback between reward budget allocation and model utility improvement of FL, making the optimal reward budget allocation complicated. To address this problem, we design an online reward budget allocation algorithm using Bayesian optimization named BARA (\underline{B}udget \underline{A}llocation for \underline{R}everse \underline{A}uction). Specifically, BARA can model the complicated relationship between reward budget allocation and final model accuracy in FL based on historical training records so that the reward budget allocated to each communication round is dynamically optimized so as to maximize the final model utility. We further incorporate the BARA algorithm into reverse auction-based incentive mechanisms to illustrate its effectiveness. Extensive experiments are conducted on real datasets to demonstrate that BARA significantly outperforms competitive baselines by improving model utility with the same amount of reward budget.

Different from conventional federated learning, personalized federated learning (PFL) is able to train a customized model for each individual client according to its unique requirement. The mainstream approach is to adopt a kind of weighted aggregation method to generate personalized models, in which weights are determined by the loss value or model parameters among different clients. However, such kinds of methods require clients to download others' models. It not only sheer increases communication traffic but also potentially infringes data privacy. In this paper, we propose a new PFL algorithm called \emph{FedDWA (Federated Learning with Dynamic Weight Adjustment)} to address the above problem, which leverages the parameter server (PS) to compute personalized aggregation weights based on collected models from clients. In this way, FedDWA can capture similarities between clients with much less communication overhead. More specifically, we formulate the PFL problem as an optimization problem by minimizing the distance between personalized models and guidance models, so as to customize aggregation weights for each client. Guidance models are obtained by the local one-step ahead adaptation on individual clients. Finally, we conduct extensive experiments using five real datasets and the results demonstrate that FedDWA can significantly reduce the communication traffic and achieve much higher model accuracy than the state-of-the-art approaches.

This paper investigates the column generation (CG) for solving cutting stock problems (CSP). Traditional CG method, which repeatedly solves a restricted master problem (RMP), often suffers from two critical issues in practice -- the loss of solution quality introduced by linear relaxation of both feasible domain and objective and the high time cost of last iterations close to convergence. We empirically find that the first issue is common in ordinary CSPs with linear cutting constraints, while the second issue is especially severe in CSPs with nonlinear cutting constraints that are often generated by approximating chance constraints. We propose an alternative approach, ensembles of multiple column generation processes. In particular, we present two methods -- \mc (multi-column) which return multiple feasible columns in each RMP iteration, and \mt (multi-path) which restarts the RMP iterations from different initialized column sets once the iteration time exceeds a given time limit. The ideas behind are same: leverage the multiple column generation pathes to compensate the loss induced by relaxation, and add earlier sub-optimal columns to accelerate convergence of RMP iterations. Besides, we give theoretical analysis on performance improvement guarantees. Experiments on cutting stock problems demonstrate that compared to traditional CG, our method achieves significant run-time reduction on CSPs with nonlinear constraints, and dramatically improves the ratio of solve-to-optimal on CSPs with linear constraints.

Building a reasonable model for predicting biodiversity using limited data is challenging. Expanding limited experimental data using a variational autoencoder generative adversarial network (VAEGAN) to improve biodiversity predictions for a region is a new strategy. Aquatic beetle diversity in a large &gt;30-year-old artificial pool that had not had human interference in Nanshe Village (Dapeng Peninsula, Shenzhen City, Guangdong Province, China) was investigated. Eight ecological factors were considered. These were water temperature, salinity, pH, water depth, proportional area of aquatic plants, proportional area of submerged plants, water area, and water level. Field sampling was performed for 1 or 2 days in the middle or late part of each month for a year. A type D net was swept 10 times in the same direction in each ~1 m × ~1 m sample square, generating 132 datasets (experimental data). In total, 39 aquatic beetle species were collected, 19 of which were assigned to Hydrophilidae, 16 to Dytiscidae, 3 to Noteridae, and 1 to Gyrinidae. A one-dimensional convolutional neural network (1-D CNN) was used to assess and predict the grade of the number of individuals and the number of aquatic beetle species. The Bayesian-optimized 1-D CNN established using 112 experimental datasets as the training set and the other 20 datasets as validation and testing sets gave a 74.0% prediction accuracy for the grade of the number of individuals and a 70.0% prediction accuracy for the number of species. The impact of insufficient sample data on the model was assessed using a VAEGAN to expand the training set from 112 to 512 samples, and then the Bayesian-optimized 1-D CNN-based VAEGAN prediction model was re-established. This improved prediction accuracy for the grade of the number of individuals to 86.0% and for the number of species to 85.0%. The grade of the number of individuals’ prediction accuracy was 88.0% and the number of species’ prediction accuracy was 85.0% when the random effects of only obtaining a single individual of a species were excluded. The results indicated that the accuracy of the 1-D CNN in predicting the aquatic beetle species number and abundance from relevant environmental factors can be improved using a VAEGAN to expand the experimental data.

Although the numerical models can estimate the significant influence of local site conditions on the seismic propagation characteristics near the surface in many studies, they cannot feasibly predict the seismic ground motion amplification in regular engineering practice or earthquake hazard assessment due to the high computational cost and their complex implementation. In this paper, the scattering problem of trapezoidal sedimentary basins, one of the representatives of local complex sites with a relatively small model size, and simplified by practice in this type of study, was selected as the basin model. A series of standard basin models were built to quantify the relationship between the site condition parameters and the site amplification parameters (the peak ground acceleration and the hazard location). In addition, the factors that influence seismic ground motion amplification, such as the basin shape ratio, the soil depth, the basin edge dip angle, the ratio of shear wave velocity between the bedrock and the soil layer, the damping coefficient, and the fundamental frequency, were selected to investigate the sensitivity. A convolutional neural network (CNN) algorithm based on deep learning replacing traditional recursive algorithms was explored to establish a prediction model of basin amplification characteristics. By the Bayesian optimization method, the structural parameters of the CNN predicting model were selected to improve the accuracy of the prediction model. The results show that the optimized CNN models could predict the amplification characteristics of the basin better than the un-optimized CNN models. Three prediction models were established with the site condition parameters as the input parameters and their output parameters were the maximum amplification value of the peak ground acceleration (PGA), the hazard location, and their combination for each basin. To analyze the CNN’s prediction ability, each CNN model used about 80% of the data from the seismic model repose results for training and the remaining data (20%) for testing. By comparing the CNN prediction results with the FE simulation results, the accuracy and rationality of each prediction model were studied. The results show that, compared to a single numerical model, the CNN prediction results of the site amplification features could be quickly obtained by inputting the relevant parameters. Compared to recursive class models, the established CNN prediction model can directly establish the relationships among multiple input and multiple output parameters. A comparison of the three kinds of CNN models shows that the prediction accuracy of the joint parameter model was slightly lower than that of the two single-output models.

Federated learning (FL) is a prospective distributed machine learning framework that can preserve data privacy. In particular, cross-silo FL can complete model training by making isolated data islands of different organizations collaborate with a parameter server (PS) via exchanging model parameters for multiple communication rounds. In cross-silo FL, an incentive mechanism is indispensable for motivating data owners to contribute their models to FL training. However, how to allocate the reward budget among different rounds is an essential but complicated problem largely overlooked by existing works. The challenge of this problem lies in the opaque feedback between reward budget allocation and model utility improvement of FL, making the optimal reward budget allocation complicated. To address this problem, we design an online reward budget allocation algorithm using Bayesian optimization named BARA (Budget Allocation for Reverse Auction). Specifically, BARA can model the complicated relationship between reward budget allocation and final model accuracy in FL based on historical training records so that the reward budget allocated to each communication round is dynamically optimized so as to maximize the final model utility. We further incorporate the BARA algorithm into reverse auction-based incentive mechanisms to illustrate its effectiveness. Extensive experiments are conducted on real datasets to demonstrate that BARA significantly outperforms competitive baselines by improving model utility with the same amount of reward budget.

RhPb was initially recognized as one of a CoSn-like compounds with $P6/mmm$ symmetry, containing an ideal kagome lattice of $d$-block atoms. However, theoretical calculations predict the realization of the phonon soft mode which leads to the kagome lattice distortion and stabilization of the structure with $P\bar{6}2m$ symmetry [A. Ptok et al., Phys. Rev. B 104, 054305 (2021)]. Here, we present the single crystal x-ray diffraction results supporting this prediction. Furthermore, we discuss the main dynamical properties of RhPb with $P\bar{6}2m$ symmetry. The bulk phononic dispersion curves contain several flattened bands, Dirac nodal lines, and triple degenerate Dirac points. As a consequence, the phononic drumhead surface state is realized for the (100) surface, terminated by the zigzag-like edge of Pb honeycomb sublattice.

Individuals' initial conceptualizations of the world are typically formed during their childhood years, a period whose influence is notably enduring. This fundamental understanding tends to reach maturation during adolescence, though it remains subject to continuous evolution and reshaping throughout adulthood, influenced by a myriad of personal experiences. The complex interplay of continuity and change in identity formation underscores the multifaceted and dynamic nature of personal identity. This recognition can enhance nuanced understanding of self and others, potentially enriching interpersonal relationships, self-development, and overall life satisfaction. By appreciating the intricate perspectives, maintaining a stable core identity and accommodating the potential for change, individuals can better navigate the complexities of life. This equilibrium provides a crucial framework for individuals to forge their unique life paths, while adjusting to various special expectations and personal growth stages.

Abstract Nonalcoholic fatty liver disease (NAFLD) is closely related to metabolic syndrome (MetS). Bone morphogenetic protein 9 (BMP9) is an essential factor in glucose, lipid and energy metabolism. This study aims to investigate whether BMP9 can serve as a serological marker for the severity of NAFLD or MetS. Total of 263 individuals were enrolled and categorized into the healthy controls, NAFL group, and non-alcoholic steatohepatitis (NASH) at-risk group by the results of FibroTouch test and liver function. Basic demographic data and blood biochemical indicators were collected, and peripheral blood BMP9 levels were detected by enzyme-linked immunosorbent assay (ELISA). Stratified analysis of population BMP9 levels was conducted according to the number of MetS components. Serum BMP9 levels differentiated NASH at-risk (58.13 ± 2.82 ng/L) from the other groups: healthy control (70.32 ± 3.70 ng/L) and NAFL (64.34 ± 4.76 ng/L). ( p &lt; 0.0001). The concentration of BMP9 was associated with transaminase, triglyceride (TG), fasting plasma glucose (FPG), glycated hemoglobin (HbA1c), uric acid (UA). Controlled attenuation parameter of liver fat (CAP) and liver stiffness measurement (LSM) were negatively correlated with BMP9 levels, while high-density lipoprotein (HDL) levels were positively correlated. The risk of developing NAFLD increased along with elevated serum BMP9 and BMI, and a significantly higher risk observed in men compared to women. Additionally, serum BMP9 levels showed a downward trend as the number of components increased. BMP9 may be a protective factor for the onset and development of NAFLD, as well as a biomarker for the severity of the NAFLD and MetS.

In the presence of external magnetic field, the Kitaev model could either hosts gapped topological anyon or gapless Majorana fermions. In $α$-RuCl$_3$, the gapped and gapless cases are only separated by a thirty-degree rotation of the in-plane magnetic field vector. The presence/absence of the spectral gap is key for understanding the thermal transport behavior in $α$-RuCl$_3$. Here, we study the anisotropy of the oscillatory features of thermal conductivity in $α$-RuCl$_3$. We examine the oscillatory features of thermal conductivities (k//a, k//b) with fixed external fields and found distinct behavior for the gapped (B//a) and gapless (B//b) scenarios. Furthermore, we track the evolution of thermal resistivity ($λ_{a}$) and its oscillatory features with the rotation of in-plane magnetic fields from B//b to B//a. The thermal resistivity $λ(B,θ)$ display distinct rotational symmetries before and after the emergence of the field induced Kitaev spin liquid phase. These experiment data suggest close correlations between the oscillatory features of thermal conductivity, the underlying Kitaev spin liquid phase and the fermionic excitation it holds.

In this paper, the investigation on the instability in parallel channel system is summarized systematically. This phenomenon in parallel channel system is very typical, interesting and challengeable. The experiment data of a twin-channel system is used as the validation. Two typical methods are adopted to simulate this phenomenon for deciding the instability boundary. One is the integral method, which is based on the model of Clausse and Lahey and developed by Lee and Pan and GUO; the other is the classical system analysis code: Relap5/MOD3.4. In the experiment the influences of inlet resistance, system pressure and nonuniform heating are obtained. The influences of system pressure and inlet resistance can be simulated by both methods. However, there are some differences between the results of two methods. And for the effects of nonuniform heating and asymmetric inlet resistances, which are very popular in the nuclear power system, the results of numerical methods cannot get a good numerical agreement with those of experiment. It should be noticed in the practical engineering design. Finally, the typical “Ledinegg” instability phenomenon may occur in the parallel channel system according to the numerical results. Sometimes it will induce the burnout before the parallel channel instability. Both methods predict the same tendency. And a detailed explanation is given. The slope of the pressure drop-mass flux curve is the key to avoid the flow excursion phenomenon in parallel channel system.

For offshore floating nuclear power system the ocean conditions, such as rolling, must be considered for safe design. The neutron kinetics decides the power distribution and variation. Both of them will change the characteristics of the core instability. In this paper the ocean condition model and multi-point reactor model are added into the parallel channel system thermal-hydraulic model. A reactor core with 121 assemblies based on QinshanII nuclear power plant is selected as research object. The inherent instability of the system is studied firstly as the basis of comparison. Then the instability boundaries under motion condition and neutron feedback are obtained separately. The joint influence of motion and neutron feedback is studied. The results indicate that ocean condition has very limited effect for such system with so many parallel channels. Neutron feedback in different inlet subcooling regions have different influence tendency. The combined effect is very powerful and should be paid more attention. At last part the spectral analysis method is used to discuss the influence of the coupling calculation method.

Welding is an important method for modern material processing. In actual processing, due to the influence of processing accuracy and welding thermal deformation, various defects often appear in the appearance of the weld. At present, visual inspection is mainly used for the appearance inspection of welds. The detection of weld defects mainly depends on the work experience of the staff. Based on the above background, the purpose of this article is to visually inspect the weld surface quality. This article uses visually obtained fringe images of weld contours as information sources to explore a visual-based weld appearance detection algorithm, including the measurement of weld formation dimensions and the detection of weld appearance defects. This algorithm overcomes manual measurements of the misjudgments and omissions caused by eye fatigue and experience differences. It improves the efficiency and accuracy of welding appearance inspection, and meets the needs of automation and intelligence of the entire welding process. In this paper, a subpixel stripe centerline extraction algorithm based on the combination of the Hessian matrix method and the center of gravity method is used; to further improve the accuracy of the extraction of the centerline of the weld seam, this article also performs the work of removing the wrong points and the compensation of the broken seam. Obtain a fringe centerline with better connectivity. Comparing the extraction algorithms of each centerline, the centerline obtained by this method has high accuracy, less time-consuming and high stability. It laid the foundation for the subsequent inspection of weld appearance. Through the training of the model, the accurate classification and recognition of surface defects of tube and plate welds have been achieved. The experimental results show that the improved vision-based welding surface defect recognition and classification proposed in this paper has better performance and accuracy. Up to 96.34%.

Dockless bikeshare systems show potential for replacing traditional dock-based systems, primarily by offering greater flexibility for bike returns. However, many cities in the US currently regulate the maximum number of bikes a dockless system can deploy due to bicycle management issues. Despite inventory management challenges, dockless systems offer two main advantages over dock-based systems: a lower (sometimes zero) membership fee, and being free-range (or, at least free-range within designated service areas). Moreover, these two advantages may help to solve existing access barriers for disadvantaged populations. To date, much of the research on micro-mobility options has focused on addressing equity issues in dock-based systems. There is limited knowledge of whether, and the extent to which dockless systems might help mitigate barriers to bikeshare for disadvantaged populations. Using San Francisco and Los Angeles as case studies, because both cities have both dock-based and dockless systems running concurrently, the research team quantified bikeshare service levels for communities of concern (CoCs) by analyzing the spatial distribution of service areas, available bikes and bike idle times, trip data, and rebalancing among the dock-based and dockless systems. They found that dockless systems can provide greater availability of bikes for CoCs than for other communities, attracting more trip demand in these communities because of a larger service area and frequent bike rebalancing practices. More importantly, they noticed that the existence of electric bikes helps mitigate the bikeshare usage gap between CoCs and other tracts. Besides the data analyses for bikeshare trips, the research team also studied the spatial distribution of online suggested station locations and find that the participants’ desired destinations for work/school purposes have not been covered to the same extent in CoCs as in other communities. The results provide policy insights to local municipalities on how to properly regulate and develop dockless bikeshare systems to improve mobility equity.View the NCST Project Webpage

Abstract The application of castor oil in various fields and the development potential in renewable energy have attracted large attention, and castor oil extraction has become a research focus. The objective of this study is to determine the relationship between important parameters during single grain extrusion and to obtain the maximum oil yield. Mechanical compression tests are conducted by a texture analyzer. Response surface methodology is used to optimize the process variables. A four‐factor three‐level Box–Behnken design is used to generate factor combinations. A quadratic mathematical model between each variable and oil yield is developed. The significance of each interaction term is assessed by analysis of variance. The model's oil yield prediction accuracy is verified by tests. The highest oil yield of 30.18% is obtained under strain 94.97%, speed 0.1 mm s −1 , dwell time 480 s, and drying at 20 °C. The determination coefficients ( R 2 = 0.9885; R 2 Adj = 0.8979; R 2 Pre = 0.8782) indicate the fitted quadratic mathematical model has a good correlation between experimental and predicted values. Lack of fit (0.9998) term is not significant and indicates the model reliability. Predicted oil yield value (30.18%) is close to experimental testing value (31.47%), which further demonstrates the mathematical model reliability. Practical applications : The extracted castor oil can be used for industrial research such as biodiesel. Castor seed is rich in oil content. Optimization of process parameters can improve oil recovery rate of castor seed. The developed model in this study provides a basic reference for improvement equipment related to the oil extraction.

Sodium-cooled reactors (SFR) have always been recognized as one of the most promising candidates for the fourth-generation nuclear systems as announced by the Generation-IV International Forum. In the design of SFR, helical wire-wrapped rod is applied to stabilize the structure of the rod bundle and enhance coolant mixing. Although there has been considerable research on SFR in computational fluid dynamics (CFD), the phenomenon of heat transfer has rarely been paid attention to. This article discovered that there exists reversed heat flux from coolant to wrapped wire, which is contrary to our usual understanding. This phenomenon has not been reported in previous CFD calculations. Hence, a solid heat conduction model is proposed to prove this phenomenon and analyze the heat transfer process. The simulation results show that the wrapping wire embedding depth, the shape of the calculation domain and the physical properties of all components have great influence on the magnitude of the reversed heat flux. The present findings will have strong influence on the temperature field and maximum value of the fuel rod as well as profound reference value for future flow calculation, especially in grid generation and treatment of the junction between the winding wire and fuel rod.

• A novel switchable fiber comb filter based on polarization beam splitter (PBS) is proposed, which can generate two different output channels selected by adjusting the polarization controllers (PC) in front of the PBS. • The two different channels’ wavelength intervals can be obtained by changing the polarization-maintaining fiber’s characteristics. • The switched wavelength interval is 0.85 nm and 0.40 nm. • The power fluctuation of the two channel interval outputs in one hour is less than 0.88 dB and 1.37 dB, and the wavelength fluctuation is less than 0.06 nm and 0.18 nm. In this paper, we proposed and demonstrated a novel switchable fiber comb filter based on polarization beam splitter (PBS). The proposed filter transmission characteristics is theoretically analyzed in detail by using the transmission matrix theory. The simulated results show that the filter can generate two different output channels selected by adjusting the polarization controllers (PC) in front of the PBS, and the two different channels’ wavelength intervals can be changed with polarization-maintaining fiber’s (PMF’s) characteristics. Different PMFs give a new switchable combination of channel intervals. A multi-wavelength fiber laser (MWFL) based on the proposed filter is experimentally demonstrated. Its wavelength interval can be switched among 0.85 nm, 0.40 nm, which is consistent with the simulated results of the filter. The power fluctuation of the two channel interval outputs in one hour is less than 0.88 dB and 1.37 dB, and the wavelength fluctuation is less than 0.06 nm and 0.18 nm, respectively.

This paper proposes a non-contact, online, rapid, and non-destructive measurement method of Pinus densiflora S.et Z. (Pinus densiflora) dimension lumber based on an algorithm of maximizing lumber recovery by minimizing the enclosure rectangle fitting area. The method takes the full influence of multiple factors, such as the difficulty in measuring large-size dimension lumber, conveying deflection, etc. into account. Image splicing, object and background segmentation, and lumber size measurements are carried out. Compared to other current algorithms, it can decrease the measurement errors and improve measurement efficiency. The problems of slow image segmentation, large-size lumber measurement, and conveying deflection are solved. Through measurement tests and error analysis, the measurement accuracy of the lumber size can reach 0.8 mm/m. This method meets the requirements of high-speed lumber production and lays the foundation for the development of a lumber detection and evaluation system.

We have completed measurements of key scintillation properties of liquid neon. We found the nuclear recoil scintillation efficiency to be 0.26 ± 0.03 for 387 keV nuclear recoils. We also measured the time dependence of scintillation light from electronic and nuclear recoils in liquid neon, finding a decay lifetime of 14.9 ± 0.3 μs for the slower component. Pulse shape discrimination was investigated as a means of identifying event type in liquid neon.

Gummy stem blight,caused by Didymella bryoniae,has resulted in an increasing loss in cucurbitacae vegetables production in China.This paper carries out systematical review on the pathogenic bacteria,occurrence rule, disease symptom,resistance identification technology, resistance resources,resistance inheritance regularity,resistance gene molecular biotechnology study and control method,etc..Aiming at the problems existing in current research,the paper also puts forward orientation and focus for future studies.

This paper presents a semantic trust modeling method and SCTM model for service composition. The idea of social network is used in modeling and the issues of trust are analyzed from the service composition perspectives. How to calculate the multidimensional trust value of a service is illustrated also. Finally the implementation framework of the corresponding modeling tool is given.

Roll – forming is through the allocation of roll the sheets for multiple successive of transverse bending deformation process of the section, to form a specific shape with high energy efficiency, uniform cross section, stable product quality, etc. Since the 19th century began to study the roll-forming process, successively completed the exploration of this kind of technology and promotion from 1938 to 1938.It has entered the rapid development of roll-forming technology at present. Began to roll-forming technology research relatively late in our country, but the trend of development of fast, such as the construction industry, automotive industry, white home appliance industry has been widely used, to specific parts such as highway anti-collision WeiDang, auto parts anticollision beam beams, before and after the threshold of the anticollision beam and a side door production, etc. Roll-forming technology belongs to the nonlinear problem of large plastic deformation, the forming theory of the present domestic scholars have researched, forming a simplified analytical method, energy analysis method, cable original research method and finite element method theory. With the development of computer aided design technology, through the computer simulation of sheet deformation and regional stress analysis, and makes the product design cycle is shortened, the product design quality was improved. At home and abroad, roll-forming equipment have developed highly efficient, the formation of the uncoiled stamping - roll-forming - welding - material such as plastic - cut – code craft route, eventually forming the results approach to the product shape, implementation process highly integrated production mode, cold-formed molding equipment of high automation intelligent design, help to realize planning of ‘Made in China 2025 strategy’ in the industry of roll-forming.

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Abstract More than half of the total natural ionizing radiation dose received by the human population is caused by radon and thoron (Rn and Tn) and their progeny. To estimate the level of radiation due to radon and thoron and their progeny, an investigation was conducted in a residential area near the world’s largest open-pit mine of Bayan Obo in Inner Mongolia, China. The concentration of Rn, Tn, and their decay products in air and soil were studied by using AlphaGUARD, RAD7, and ERS-RDM-2S for a discrete period of time in three different locations. The average indoor concentration of radon and thoron was 62.6 ± 44.6 Bq/m 3 and 108.3 ± 94.5 Bq/m3 respectively, and the outdoor concentration was 12.9 ± 6.3 Bq/m 3 and 55.8 ± 18.5 Bq/m 3 , respectively. Relatively high concentrations were recorded in the area near to the mine, with a significant increasing trend observed in indoor thoron concentration. A prominent hotspot in thoron concentration was found in a single-story house with values 747 ± 150 Bq/m 3 . The equilibrium equivalent thoron concentration (EEC Tn ) varies from 0.48 Bq/m 3 to 2.36 Bq/m 3 with an arithmetic mean of 1.37 ± 0.64 Bq/m 3 , and comparatively higher than EEC Rn . Concluding that the mining activity at Bayan Obo mine is significantly increasing the level of indoor thoron and its progeny in surroundings. It is suggested to further systematically investigate the indoor Rn and Tn progeny concentrations in the residential dwellings of the Bayan Obo mining area, and 232 Th content of the building materials, to provide a basis for calculating the radiation dose.

The East Asian winter monsoon(EAWM) is one of the most active systems in northern hemisphere during boreal winter. The EAWMexerts an essential influence on controlling winter climate over most of China, and its interannual and interdecadal variabilities are of significantimportance in predicting and inspecting winter climate over China. Based on the NCEP/NCAR reanalysis date and the 160-station observationaldata, a comparison for 12 EAWM indices and their relations to winter temperature and precipitation over eastern China have been performedin this paper. Furthermore, the stability of the relations between EAWM indices and temperature and precipitation in Ei Nino status or La Ninastatus has also been detected. The results indicate that most of the EAWM indices share the same variations year-to year, but there are somedifferences between them at the same time, which suggest that the focuses of each index in capturing the integrity or partial features are different.It was found that the intensity of the EAWM system reduced obviously during the last 60 years, especially in the latest 30 years with a trend of-0.25σ/10a averaging from the 10 EAWM indices. All of the 12 EAWM indices showed intense interannual variabilities and interdecadal variationsduring the last six decades. Although the exact periods of each index are not unified, the dominant interannual periods of ~2 to ~4a and ~8 to~9a, and the dominant interdecadal periods of ~13.3a and ~20a of the EAWM indices can be identified from a power spectrum analysis. Thereare ten(eight) EAWM indices correlated significantly (0.1%) with the first mode time series(PC1) of winter temperature(precipitation) over easternChina. Among them, the Siberian High index can explain 53.3% variance in winter temperature PC1, and the East Asian meridional windindex derived from the middle-high troposphere can explain 50.4% variance in winter precipitation PC1. The relationships between each EAWMindex and winter temperature and precipitation over eastern China during Ei Nino status and La Nina status are not consistent completely. So,the different reference significances of each EAWM index in Ei Nino status or La Nina status should be considered carefully when used in winterclimate monitoring.

Objective:To compare the effect of five different apical preparation protocols in smear layer removal.Methods:Fifty extracted single-rooted maxillary anterior teeth were randomly divided into five groups,group A:root canals were prepared to 25#(F2)by ProTaper system,and irrigated by NaOCl and EDTA;group B:root canals were prepared to 30#(F3),and the preparation and irrigation protocols were same as group A;group C:root canals were prepared to 30#(F3)by ProTaper system,and then the apical size enlarged to 35#by stainless steel K-file.The irrigation protocol was same as group A;group D:root canals were prepared to 30#(F3)by ProTaper system,and then the apical size enlarged to 40#by stainless steel K-file.The irrigation protocol was same as group A;group E:root canal preparation was same as group D,and irrigated by distilled water.The samples were examined under a thermal field emission scanning electron microscope.Results:Group B,group C and group D showed lower scores than group A(P0.05);group A,group B,group C and group D showed lower scores than group E(P0.05).Conclusion:In smear layer removal,the minimum instrumentation for proper penetration of irrigants to the apical third of the canal is a 30#file by ProTaper system.

To summarize the clinical experience of the retrograde replantation for amputated toe.Between January 2010 and August 2015, 11 cases of amputated toes (15 toes) were treated by the retrograde replantation. All patients were male, with a mean age of 31 years (range, 18-45 years). The causes included cutting injury in 6 cases (9 toes) and crush injury in 5 cases (6 toes). One case had amputated great toe and distal segment of the second toe combined with the third toe nail bed contusion; 1 case had amputated proximal great toe and middle segment of the second and third toes; 1 case had amputated proximal segment of great toe and middle segment of the second toe; 7 cases had amputated distal segment of the great toe; and 1 case had amputated middle segment of the fifth toe. The time from injury to hospital was 1-3 hours (mean, 2 hours).Thirteen toes survived completely after operation. Toe necrosis occurred in 1 toe; partial dorsal skins necrosis and nail bed necrosis occurred in 1 toe, and was cure after repaired with dorsalis pedis island flap. The rate of success for replantation of amputated toes was 93.33% (14/15). X-ray examination showed fracture healing of all survival toes at 8-12 weeks after operation (mean, 10 weeks); internal fixation was removed. Eleven cases were followed up 3-12 months (mean, 7.5 months). The survival toes had good appearance and toenail. The two point discrimination was 9-12 mm (mean, 10 mm) at last follow-up. The patients could walk and run normally.It is an ideal surgical method to use retrograde replantation to treat amputated toe, with the advantages of simple operation and high survival rate.总结采用逆行法行断趾再植术的临床经验。.2010年1月-2015年8月，采用逆行法对11例（15趾）足趾完全离断伤男性患者行断趾再植术。年龄18～45岁，平均31岁。受伤原因：切割伤6例（9趾），压砸伤5例（6趾）。其中1例趾、第2趾末节完全离断合并第3趾甲床挫裂，1例趾近节及第2、3趾中节完全离断，1例趾近节、第2趾中节完全离断，7例趾末节完全离断，1例小趾中节完全离断。受伤至入院时间1～3 h，平均2 h。.术后13趾完全成活；1趾背侧部分皮肤及甲床坏死，予以足背岛状皮瓣修复创面后趾体成活；1趾坏死。断趾再植成活率为93.33%（ 14/15）。X线片复查示，术后8～12周成活趾体骨折均愈合，平均10周，行内固定物取出术。术后患者均获随访，随访时间3～12个月，平均7.5个月。成活趾体外形饱满，趾甲生长良好。末次随访时趾端两点辨别觉为9～12 mm，平均10 mm。患足行走及跑步无影响。.采用逆行法行断趾再植术具有手术操作简便、再植成活率高的特点。.

This thesis contributes to the formulation of a theory around the implication of supplier development (SD) practices on improving supplier social performance in the context of China. The study focuses on how two social SD practices (i.e. supplier assessment and supplier incentives) affect suppliers’ social performance. In contrast to most SD literature, this study is conducted from a supplier’s perceptive. Furthermore, in this thesis, the function of buyer-supplier trust (TR) is discussed as a potential moderator when implementing SD practices to improve suppliers’ social performance.The findings of the thesis demonstrate that supplier incentives contribute to improving suppliers’ social performance, whilst TR does not moderate the effectiveness of SD practices on suppliers’ social performance.

Effective inter-vehicle communication is fundamental to a decentralized traffic information system based on Vehicular Ad Hoc Networks (VANETs). To reflect the uncertainty of the information propagation, most of the existing work was conducted by assuming the inter-vehicle distance follows some specific probability models, e.g., the lognormal or exponential distribution, while reducing the analysis complexity. Aimed at providing more generic results, a recursive modeling framework is proposed for VANETs in this paper when the vehicle spacing can be captured by a general i.i.d. distribution. With the framework, the analytical expressions for a series of commonly discussed metrics are derived respectively, including the mean, variance, probability distribution of the propagation distance, and expectation for the number of vehicles included in a propagation process, when the transmission failures are mainly caused by MAC contentions. Moreover, a discussion is also made for demonstrating the efficiency of the recursive analysis method when the impact of channel fading is also considered. All the analytical results are verified by extensive simulations. We believe that this work is able to potentially reveal a more insightful understanding of information propagation in VANETs by allowing to evaluate the effect of any vehicle headway distributions.

A control system,based on a microcontroller for a measuring instrument,was developed for formaldehyde and other volatile organic compound emissions.This article described the system hardware construction,software processing,and how to combine them in the system to realize real-time measuring and automatic controlling.The application of this system,for a 1-cubic formaldehyde measuring system,showed that the temperature and humidity control reached ±0.5% and ±1%,respectively.The cost for this micro-controlled instrument was reduced compared with that for a programmable logic controller.An intelligent man-machine interface,based on a touch screen,was also designed to make this an easily operated system.

Normalization of histogram is often required in image preprocessing stage such as multi temporal remote sensing image matching and land-use change detection.The normalization can also minimize different imaging condition effects in analysis and rectify radiometric differences derived from solar/sensors location,atmospheric effects between adjacent images in such a way as if they have been acquired at the same imaging conditions.Relative radiometric normalization which is normally applied in image preprocessing stage does not remove all unwanted effects.In this paper,a method has been developed based on regression applied on unchanged pixels.The proposed method is based on efficient selection of unchanged pixels through image difference histogram modeling using available spectral bands and calculation of relevant coefficients for dark,gray and bright pixels in each band.The coefficients are applied to produce the normalized image.The idea has been implemented on two TM image datasets.The capability of the approach in taking in to account the imaging condition differences and effectively excluding real land change pixels from the normalization process has shown better performance in the evaluation stage.

Numerical investigation was made on the cooling characteristics of micro-and mini-channel heat transfer used in liner wall of an aero-engine combustor.A one-dimensional heat-transfer model was employed to define the boundary condition of mini-channel walls.FLUENT was used to simulate the cool ing performance,involving two aspect ratio of mini-channel(20,40) at three liner pressure loss(2.0%,2.5%,and 3.0%).Results show a powerful cooling capacity of mini-channel with small cooling air,which show a significant increase of temperature and a high utilization of potential heat sink(40%).Furthermore,the flux of cooling air is strongly affected by the aspect ratio of mini-channel,and is slightly affected by pressure loss of liner.Finally,the temperature gradients of liner are remarkable.

There are few traditional literatures about the the Jun(郡,prefectures) and Xian(县,counties) of the Zhao State,so it is difficult to know all the place names of Zhao State.Fortunately,many unearthed relics of Zhao State during the Zhan Guo(Warring States period) contain records of place names of Zhao State.These relics are precious data for research on the place names of Zhao State due to the unavailability of conventional records.This paper offers,by making use of archeological findings and traditional literature,a testimony of place names in Zhao State,in the hope of making up for the vacuum of research in this regard.

This paper introduces some ponderation after Fukushima nuclear accident. Several typical disasters happened in china are introduced briefly. The nuclear accident is compared with these disasters detailed. Then the public characteristics of china near the nuclear power plant are analyzed, which have strong influence on the nuclear accident management. Later the present nuclear accident management method is explained. In the last part some suggestions especially for China are put forward. The key points of the paper are as follows: the nuclear accident is very typical and only earthquake is commensurable; the government should tell the truth to the public as soon as possible and completely, and set quick of effective measures; a numerical forecast center is necessary, which can supply numerical data to make the disaster disposal more reliable.

研究了激光二极管端面抽运的双纵模双频微片激光器的热效应对其输出频谱的影响. 通过对端面抽运Nd:YVO4微片的热传导方程求解得出晶体内部的温度场分布; 并进一步对微片晶体热致折射率变化进行分析, 由此计算出双频微片激光器的热致频谱变化. 实验结果表明: 当抽运功率较小时得到稳定的双纵模双频激光输出; 当抽运功率增大时, 晶体热效应使双频激光频谱双峰之间的频差减小, 各纵模波长频谱宽度加宽, 实验结果与理论分析相符合.

Using the three-layer impellers with big size diameter in an unbaffled elliptic bottom stirred tank，the gas holdup (ε) was studied in the systems of air-polyether polyol (PPG). The results indicate that the gas holdup in the air-PPG system is higher, it increase with the superficial gas phase velocity (Vs) and specific power input (Pm) increase, and decrease as the temperature increase. The influence is severely when the temperature is below 100°C, and is weak above 100 °C.The conclusions give reference for choosing the operation parameter and designing and scale-up of PPG polymerization reactor.

Investigating the early-warning capability for ballistic missile of land stations located in Beijing,Changchun and Shanghai respectively.Both Horizontal Photoelectric Tracking System and X-Y Photoelectric Tracking System are fixed in each station.The simulated results show the two kinds of Tracking System supplement each other,hence can cover the entire celestial sphere.At last,connecting these land stations can increase the early-warning efficiency.

In order to check satellite-based nuclear explosion detector,an opticla simulator structure was designed.Mechanical tilting altitude-azimuth structure and X-Y double-axis structure platforms were an- alyzed theoretically.Optimized double-axis structure was put forward and the tracing accurateness was estimated.It is found that the X-Y structure table can trace the satellite within the effective area (no zen- ith blind spot) very steadily as well as with high performence.The results of experiment confirm the the- oretical and mathematical models.

Water header is the most common structure in the design of flow system for energy and power system. The complex flow structure could result in some problems when CFD simulation is applied in the whole system analysis. The rapid change in velocity distribution of the flow field leads to difficulties to create suitable boundary-layer mesh, and the complex flow structure will also make residuals hard to reach convergence criteria. Large eddy simulation is promising to promote these studies, it is more accurate than RANS method and can capture many non-steady-state characteristics those RANS method cannot obtain. In this study a typical water header flow structure is investigated by RANS and large eddy simulation methods. By comparing the detailed flow structures in the results of two methods, the deficiency of RANS method was found. The results of large eddy simulation can be used to guide the establishment of meshes and the application of time-averaged turbulence models to improve efficiency in engineering. The asymmetric Reynolds stresses may induce asymmetric flow field in symmetric geometry.

Bulk charge density waves are now reported in nearly all high-temperature superconducting cuprates, with the noticeable exception of one particular family: the copper oxychlorides. Here, we used resonant inelastic X-ray scattering to reveal a bulk charge density waves in these materials. Combining resonant inelastic X-ray scattering with non-resonant inelastic X-ray scattering, we investigate the interplay between the lattice excitations and the charge density wave, and evidence the phonon anomalies of the Cu-O bond-stretching mode at the charge density wave wave-vector. We propose that such electron-phonon anomalies occur in the presence of dispersive charge excitations emanating from the charge density wave and interacting with the Cu-O bond-stretching phonon. Our results pave the way for future studies, combining both bulk and surface probes, to investigate the static and dynamical properties of the charge density wave in the copper oxychloride family.

The notion that phonons can carry pseudo-angular momentum has become popular in the last decade, with recent research efforts highlighting phonon chirality, Berry curvature of phonon band structure, and the phonon Hall effect. When a phonon is resonantly coupled to a crystal electric field excitation, a so-called vibronic bound state forms. Here, we observe angular momentum transfer of $\delta$Jz = $\pm$1$\hbar$ between phonons and an orbital state in a vibronic bound state of a candidate quantum spin liquid. This observation has profound implications for the engineering of phonon band structure topology through chiral quasiparticle interactions.

Topological materials hosting kagome lattices have drawn considerable attention due to the interplay between topology, magnetism, and electronic correlations. The (Fe$_{1-x}$Co$_x$)Sn system not only hosts a kagome lattice but has a tunable symmetry breaking magnetic moment with temperature and doping. In this study, angle resolved photoemission spectroscopy and first principles calculations are used to investigate the interplay between the topological electronic structure and varying magnetic moment from the planar to axial antiferromagnetic phases. A theoretically predicted gap at the Dirac point is revealed in the low temperature axial phase but no gap opening is observed across a temperature dependent magnetic phase transition. However, topological surface bands are observed to shift in energy as the surface magnetic moment is reduced or becomes disordered over time during experimental measurements. The shifting surface bands may preclude the determination of a temperature dependent bulk gap but highlights the intricate connections between magnetism and topology with a surface/bulk dichotomy that can affect material properties and their interrogation.

Background: The lateral spread response (LSR) is an electromyography feature of hemifacial spasm; intraoperative reduction in the LSR is associated with positive surgical outcomes. This study examined the effects of different minimum alveolar concentrations (MACs) and durations of sevoflurane inhalation on the LSR. Methods: Eighty patients undergoing microvascular decompression surgery for hemifacial spasm were randomly allocated to receive propofol-remifentanil total intravenous anesthesia alone or in combination with sevoflurane at 0.5, 0.75, or 1 MAC. The LSR and orbicularis oculi muscle wave were recorded before and at 15 and 30 minutes after the start of sevoflurane administration. Results: Sevoflurane reduced the LSR amplitude in a dose-dependent and duration-dependent manner. The curve representing the LSR amplitude preservation ratio change according to sevoflurane concentration is best fitted by regression analysis using a cubic model, as the cubic equations had the largest coefficient of determination; at 15 minutes ( R 2 =0.76, F =78.36, P &lt;0.05) and at 30 minutes ( R 2 =0.882, F =189.94, P &lt;0.05). The inhibitory effect of sevoflurane on the LSR amplitude was greater in the first 15 minutes than in the second 15 minutes of sevoflurane administration. Sevoflurane at 1 MAC for 30 minutes mildly decreased the amplitude of the orbicularis oculi muscle wave. The latencies of the LSR and the orbicularis oculi muscle wave were not affected by sevoflurane at all MACs studied. Conclusions: The combination of intravenous propofol-remifentanil anesthesia with 0.5 MAC sevoflurane allows reliable intraoperative LSR monitoring in hemifacial spasm patients. Our findings support the central rather than peripheral hypothesis of the LSR.

Abstract In crystalline materials, electron-phonon coupling (EPC) is a ubiquitous many-body interaction that drives conventional Bardeen-Cooper-Schrieffer superconductivity. Recently, in a new kagome metal CsV3Sb5, superconductivity that possibly intertwines with unconventional charge density wave order is observed. Density functional theory calculations predicted weak EPC strength, supporting an unconventional pairing mechanism in CsV3Sb5. However, experimental determination of EPC strength is still missing, hindering a microscopic understanding of the intertwined ground state of CsV3Sb5. Here, using 7-eV laser-based angle-resolved photoemission spectroscopy and Eliashberg function analysis, we determine an intermediate EPC strength, 0.45~0.6, at T=6 K for both Sb 5p and V 3d electronic bands, which can support a conventional superconducting transition temperature on the same magnitude of experimental value in CsV3Sb5. Our results support an EPC driven superconductivity in CsV3Sb5.