Mengyao Shi

Agricultural mechanization and custom machine services have developed rapidly in China, which can influence rice production efficiency in the future. We calculate technical efficiency, allocative efficiency, and scale efficiency using data collected in 2015 from a face-to-face interview survey of 450 households that cultivated 3096 plots located in the five major rice-producing provinces of China. We use a one-step stochastic frontier model to calculate technical efficiency and regress the efficiency scores on socio-demographic and physical land characteristics to find the influencing variables. Variables influencing technical efficiency are compared at three different phases of rice cultivation. We also calculate technical efficiency by using the Heckman Selection Model, which addresses technological heterogeneity and self-selection bias. Results indicate that: (1) the average value of technical efficiency using a one-step stochastic frontier model was found to be 0.74. When self-selection bias is accounted for using the Heckman Selection Model, the average value of the technical efficiency increases to 0.80; (2) mechanization at the chemical application phase has a positive effect on technical efficiency, but mechanization does not affect efficiency at the plowing and harvesting phases; (3) machines are overused relative to both land and labor, and high machine input use on the small size of landholding has resulted in allocative inefficiency; (4) rice farmers are overwhelmingly operating at a sub-optimal scale. Future policies should focus on encouraging farmland transfer in rural areas to achieve scale efficiency and allocative efficiency while promoting mechanization at the chemical application phase of rice cultivation to improve technical efficiency.

Electrocatalytic nitrogen reduction reaction (NRR) is an environmentally friendly method for sustainable ammonia synthesis under ambient conditions. Searching for efficient NRR electrocatalysts with high activity and selectivity is currently urgent but remains great challenge. Herein, we systematically investigate the NRR catalytic activities of single and double transition metal atoms (TM = Fe, Co, Ni and Mo) anchored on g-C6N6 monolayers by performing first-principles calculation. Based on the stability, activity, and selectivity analysis, Mo2@g-C6N6 monolayer is screened out as the most promising candidate for NRR. Further exploration of the reaction mechanism demonstrates that the Mo dimer anchored on g-C6N6 can sufficiently activate and efficiently reduce the inert nitrogen molecule to ammonia through a preferred distal pathway with a particularly low limiting potential of -0.06 V. In addition, we find that Mo2@g-C6N6 has excellent NRR selectivity over the competing hydrogen evolution reaction, with the Faradaic efficiency being 100%. Our work not only predicts a kind of ideal NRR electrocatalyst but also encouraging more experimental and theoretical efforts to develop novel double-atom catalysts (DACs) for NRR.

Reduced graphene oxide (RGO) was translocated into leaves and inhibited the activity of photosystem II by damaging the oxygen-evolving-complex on the donor side.

Photocatalytic water splitting utilizing solar energy is considered as one of the most ideal strategies for solving the energy and environmental issues. Recently, two-dimensional (2D) materials with an intrinsic dipole show great chance to achieve excellent photocatalytic performance. In this work, blue-phase monolayer carbon monochalcogenides (CX, X = S, Se) are constructed and systematically studied as photocatalysts for water splitting by performing first-principles calculations based on density functional theory. After confirming the great dynamical, thermal, and mechanical stability of CX monolayers, we observe that they possess moderate band gaps (2.41 eV for CS and 2.46 eV for CSe) and high carrier mobility (3.23 × 104 cm2 V−1 s−1 for CS and 4.27 × 103 cm2 V−1 s−1 for CSe), comparable to those of many recently reported 2D photocatalysts. Moreover, these two monolayer materials are found to have large intrinsic dipole (0.43 D for CS and 0.51 D for CSe), thus the build-in internal electric field can be self-introduced, which can effectively drive the separation of photongenerated carriers. More importantly, the well-aligned band edge as well as rather pronounced optical absorption in the visible-light and ultraviolet regions further ensure that our proposed CX monolayers can be used as high efficient photocatalysts for water splitting. Additionally, the effects of external strain on the electronic, optical and photocatalytic properties of CX monolayers are also evaluated. These theoretical predictions will stimulate further work to open up the energy-related applications of CX monolayers.

Graphene adsorbents have been applied to remove diverse pollutants from aqueous systems. However, the mechanical strength of most graphene adsorbents is low and the fragile graphene sheets are released into the environment. In this study, we prepared carboxylated graphene oxide/chitosan/cellulose (GCCSC) composite beads with good mechanical strength for the immobilization of Cu2+ from both water and soil. The proportional limit of GCCSC beads was 3.2 N, a much larger value than graphene oxide beads (0.2 N). The largest pressure for GCCSC beads recorded before brittle failure was 26 N. The Cu2+ adsorption capacity of GCCSC beads was 22.4 mg/g in aqueous systems at initial Cu2+ concentration of 40 μg/mL, which is competitive with many efficient adsorbents. The partition coefficient (PC) for the Cu2+ adsorption onto GCCSC beads was 1.12 mg/g/μM at Ce of 0.83 mg/L and qe of 14.3 mg/g. The PC decreased to 0.055 mg/g/μM at Ce of 26.0 mg/L and qe of 22.4 mg/g. The adsorption kinetics of Cu2+ on GCCSC beads were moderately fast and required approximately 3 h to reach equilibrium with a k2 of 0.0021 g/(mg·min). A lower temperature and higher pH slightly increased the adsorption capacity of GCCSC beads. The ionic strength did not influence the adsorption. The porous structure of GCCSC beads blocked the direct contact between soil and the graphene surface; thus, a high Cu2+ immobilization efficiency was achieved by GCCSC beads applied to soil. The implications for the design of high-performance graphene adsorbents for water and soil remediation are discussed.

Nanodiamonds (NDs) are produced with large scale and applied in many areas, thus the environmental impacts and hazards of NDs should be systematically investigated. In this study, we evaluated the interaction between detonation NDs and white rot fungus Phanerochaete chrysosporium and the impact on the fungus decompositions activities. NDs did not influence the biomass gain of P. chrysosporium and the culture medium pH values. The mycelia of P. chrysosporium were destroyed upon the direct contact with NDs, while the rest retained the fibrous structure. Ultrastructural observations suggested that small aggregates of NDs seldom entered the fungus cells, but the break of cell wall and the loss of cytoplasm were induced by NDs. Under both optical and electron microscopes, the aggregation of colloidal ND particles was observed, which was the possible reason of low toxicity. High concentrations of NDs inhibited the laccase activity and manganese peroxidase activity of P. chrysosporium, which led to the decrease of decomposition activity for pollutants. Colloidal ND particles were not well dispersed in sawdust degradation evaluations, so no inhibitive effect was observed for wood degradation. The toxicological mechanism of NDs was assigned to oxidative stress. The results collectively suggested that NDs had low toxicity to white rot fungi and could be applied safely. The colloid dispersion/aggregation of nanoparticles in biological systems should be carefully considered during the design of safe nanomaterials.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), a respiratory illness that poses a serious threat to global public health. In an essential step during infection, SARS-CoV-2 uses the receptor-binding domain (RBD) of the spike (S) protein to engage with angiotensin-converting enzyme 2 (ACE2) in host cells. Chinese herbal medicines and their active components exhibit antiviral activity, with luteolin being a flavonoid that can significantly inhibit SARS-CoV infection. However, whether it can block the interaction between the S-protein RBD of SARS-CoV-2 and ACE2 has not yet been elucidated. Here, we investigated the effects of luteolin on the binding of the S-protein RBD to ACE2. By employing a competitive binding assay in vitro, we found that luteolin significantly blocked the binding of S-protein RBD to ACE2 with IC50 values of 0.61 mM, which was confirmed by the neutralized infection with SARS-CoV-2 pseudovirus in vivo. A surface plasmon resonance-based competition assay revealed that luteolin significantly affects the binding of the S-protein RBD to the ACE2 receptor. Molecular docking was performed to predict the binding sites of luteolin to the S-protein RBD-ACE2 complex. The active binding sites were defined based on published literature, and we found that luteolin might interfere with the mixture at residues including LYS353, ASP30, and TYR83 in the cellular ACE2 receptor and GLY496, GLN498, TYR505, LEU455, GLN493, and GLU484 in the S-protein RBD. These residues may together form attractive charges and destroy the stable interaction of S-protein RBD-ACE2. Luteolin also inhibits SARS-CoV-2 spike protein-induced platelet spreading, thereby inhibiting the binding of the spike protein to ACE2. Our results are the first to provide evidence that luteolin is an anti-SARS-CoV-2 agent associated with interference between viral S-protein RBD-ACE2 interactions.

Nitrogen is an essential element and 80% of nitrogen fixation from atmosphere is achieved by biological nitrogen fixation. When graphene enters the environment, it would inevitably interact with nitrogen-fixing bacteria and might disturb the nitrogen cycle. Herein, the interaction between graphene oxide (GO) and nitrogen-fixing bacterium Azotobacter chroococcum was studied to reveal the potential impact of graphene materials on biological nitrogen fixation. After incubation with A. chroococcum, GO was separated, washed and characterized by different techniques. The toxicity of GO to A. chroococcum was monitored by colony-forming unit (CFU) counting, growth curve, live/dead staining and ultrastructural observations. The nitrogen fixation activity of A. chroococcum was measured by acetylene reduction assay and the soil nitrogen contents were measured. GO was immediately reduced by cell secretions and kept stable thereafter. GO stimulated A. chroococcum growth at low concentrations and showed inhibitive effect at high concentrations. GO induced cell death and cell wall break at high concentration. The toxicological mechanism was assigned to membrane damage and oxidative stress. In the presence of soil, GO showed similar concentration-dependent but alleviated toxicity, while the soil nitrogen contents slightly increased at high concentrations. Our results collectively indicated that GO was bio-reduced and toxic to nitrogen-fixation bacteria.

NITRATE TRANSPORTER 1 (NRT1)/PEPTIDE TRANSPORTER (PTR) family (NPF) proteins can transport various substrates, and play crucial roles in governing plant nitrogen (N) uptake and distribution. However, little is known about the NPF genes in Brassica napus. Here, a comprehensive genome-wide systematic characterization of the NPF family led to the identification of 193 NPF genes in the whole genome of B. napus. The BnaNPF family exhibited high levels of genetic diversity among sub-families but this was conserved within each subfamily. Whole-genome duplication and segmental duplication played a major role in BnaNPF evolution. The expression analysis indicated that a broad range of expression patterns for individual gene occurred in response to multiple nutrient stresses, including N, phosphorus (P) and potassium (K) deficiencies, as well as ammonium toxicity. Furthermore, 10 core BnaNPF genes in response to N stress were identified. These genes contained 6–13 transmembrane domains, located in plasma membrane, that respond discrepantly to N deficiency in different tissues. Robust cis-regulatory elements were identified within the promoter regions of the core genes. Taken together, our results suggest that BnaNPFs are versatile transporters that might evolve new functions in B. napus. Our findings benefit future research on this gene family.

The systemic toxicity, reduced cellular internalization, and uncontrollable intracellular drug release of smart nanoparticles (NPs) still need to be overcome for effective cancer therapy.

Today, graphene nanomaterials are produced on a large-scale and applied in various areas. The toxicity and hazards of graphene materials have aroused great concerns, in which the detection and quantification of graphene are essential for environmental risk evaluations. In this study, we developed a fast identification and quantification method for graphene oxide (GO) in aqueous environments using Raman spectroscopy. GO was chemically reduced by hydrazine hydrate to form partially reduced GO (PRGO), where the fluorescence from GO was largely reduced, and the Raman signals (G band and D band) were dominating. According to the Raman characteristics, GO was easily be distinguished from other carbon nanomaterials in aqueous environments, such as carbon nanotubes, fullerene and carbon nanoparticles. The GO concentration was quantified in the range of 0.001-0.6 mg/mL with good linearity. Using our technique, we did not find any GO in local water samples. The transport of GO dispersion in quartz sands was successfully quantified. Our results indicated that GO was conveniently quantified by Raman spectroscopy after partial reduction. The potential applications of our technique in the environmental risk evaluations of graphene materials are discussed further.

Hydrophilic surface modification enhanced the interaction between fullerene and lysozyme to induce more protein conformational changes and enzyme activity loss.

Generative adversarial networks heavily rely on large datasets and carefully chosen model parameters to avoid model overfitting or mode collapse. Cutout with patch-loss augmentation, a dataset augmentation designed for generative adversarial networks that applies cutout to both the discriminator and the generator with a patch-loss structure and a new loss function, is proposed as a solution to the issue. It can enhance the performance of generative adversarial networks on full datasets and promote better convergence and stability on limited datasets. Additionally, the tensor value clamp is proposed, accelerating training speed without compromising quality. The proposed method can be successfully used with various generative adversarial networks, according to experiments. The performance of generative adversarial networks trained with full data on CIFAR-10 is matched by our method with only 20% of the training data. Finally, combined with our approach, StyleGAN2-ADA's Fréchet Inception Distance (FID) results on the CIFAR-10, LSUN-CAT, and FFHQ-256 datasets can be further enhanced.

Metal-organic framework (MOF) materials are emerging materials for various applications because of their unique structures and properties. The hazards and environmental safety of MOF should be carefully evaluated before their large-scale production. Herein, we studied the toxicity and its mechanisms of MOF-199 to Gram-negative bacterium (Escherichia coli) and Gram-positive bacterium (Staphylococcus aureus). MOF-199 was synthesized from Cu(NO3)2 and 1,3,5-benzenetricarboxylic acid by hydrothermal method and well characterized before toxicological evaluations. MOF-199 was nontoxic to bacteria at low concentrations, and the bacterium growths were completely inhibited at high concentrations (900 mg/L for E. coli; 1200 mg/L for S. aureus). Cell deaths occurred at high MOF-199 concentrations associated with the loss of cytoplasm and flagella. The toxicological mechanisms of MOF-199 were attributed to oxidative stress, which further led to the membrane damage and DNA damage. The chemical origin of MOF-199 toxicity should be partially attributed to the released Cu2+ in culture medium, because Cu(NO3)2 was much more toxic than 1,3,5-benzenetricarboxylic acid. Our results indicated that MOF-199 was of low toxicity and environmental risks to bacteria.

Carbon nanomaterials are widely studied and applied nowadays, with annual production increasing. After entering the environment, the complete degradation of these carbon nanomaterials by microorganisms is proposed as an effective approach for detoxification and remediation. In this study, we evaluated the degradation of pristine multiwalled carbon nanotubes (p-MWCNTs) and oxidized multiwalled carbon nanotubes (o-MWCNTs) by the white rot fungus Phanerochaete chrysosporium, which is a powerful decomposer in the carbon cycle and environmental remediation. Both p-MWCNTs and o-MWCNTs were partially oxidized by P. chrysosporium as indicated by the addition of oxygen atoms to the carbon skeleton in the forms of C=O and O–H bonds. The fungal oxidation led to the shortening of MWCNTs, where precipitated o-MWCNTs showed more short tubes. During the transformation, the defects on the tubes became detached from the carbon skeleton, resulting in decreases of the ID/IG (intensity of D-band/ intensity of G-band) values in Raman spectra. The transformation mechanism was attributed to the enzymatic degradation by laccase and manganese peroxidase excreted by P. chrysosporium. The results collectively indicated that MWCNTs could be transformed by P. chrysosporium, but complete degradation could not be achieved in a short time period. The implications on the environmental risks of carbon nanomaterials are discussed.

Tumor drainage lymph node imaging is crucial for oncological surgery, where the complete dissection of sentinel lymph nodes could largely prevent/delay recurrence. However, current commercially used imaging reagents distinguish the lymph nodes by staining them dark, which might be seriously interfered with by blood and other tissues. Herein, we reported fluorescent Ag–In–S/ZnS quantum dots (AIS/ZnS QDs) with red emission for fast tumor drainage lymph node imaging. AIS/ZnS QDs were synthesized by solution reaction and then dispersed in poly(vinyl pyrrolidone) for in vivo applications. AIS/ZnS QDs were well dispersed in water with hydrodynamic radii of 295 nm, suitable for lymph node imaging. The fluorescent imaging capability of AIS/ZnS QDs was first established after subcutaneous injection in mice. AIS/ZnS QDs could migrate to sentinel lymph nodes after the interdermal injection to the extremities. Tumor drainage lymph node imaging was achieved within 10 min upon intratumoral injection to H460 tumor-bearing mice. However, intravenous injection did not lead to tumor uptake of AIS/ZnS QDs. The fast and efficient migration of AIS/ZnS QDs into tumor drainage lymph nodes resulted in AIS/ZnS QDs being a high-performance imaging reagent for tumor drainage lymph nodes in vivo.

The widespread antibiotic use is accompanied by antibiotic resistance. A large number of antibiotic pollutants enter the water, seriously endangering the ecological environment and human health. In this study, cobalt-based materials are used to activate persulfate to treat antibiotics in wastewater based on advanced oxidation. Co3O4 is obtained at different temperatures by the one-step roasting method, eliminating the complicated preparation of traditional materials which require a large amount of reagents, generating a large amount of wastewater, and complex large-scale preparation. XRD and Raman results indicate the materials’ good crystallinity and purity. XPS and SEM indicated that the appropriate calcination temperature promoted the formation of Co2+, which was conducive to the activation of PMS for the oxidation of TCH. The catalytic activity of the materials is evaluated using tetracycline (TCH). Results suggest that 90.01% of TCH is removed after 30 min using 0.8 g/L Co3O4-350 °C, 0.4 g/L persulfate (PMS), 25 °C, and initial pH. Moreover, pH, cyclic, and ion interference experiments indicate that the Co3O4-350 °C/PMS system exhibits a wide potential application range. Free radical scavenging experiments show that ·O2− is the main active oxygen species. Co3O4-350 °C as a PMS activator is a catalytic material with large-scale practical applications.

Two-dimensional MXene membranes have garnered significant attention in the field of water treatment. Nevertheless, achieving a balance between permeability and selectivity remains a fundamental challenge in MXene membrane separation. Herein, a novel electrically active nanofiltration (NF) membrane (CNT/MXene-PEI) with an ultra-thin separation layer was prepared through vacuum filtration of MXene and cross-linking of polyethyleneimine (PEI) on the CNT substrate. By controlling the thickness of the MXene separation layer to reduce mass transfer resistance and applying a negative voltage to enhance the electrostatic effect between the conductive membrane and charged pollutants, the dye rejection rate and anti-pollution performance were improved. At an optimal MXene loading of 15.625 mg/m2, the thickness of the separation layer was about ∼47 nm. Under these conditions, the pure water flux achieved was 156.11 LMH/bar. The rejection rate of methylene blue (MLB) increased from 26.2 % to 97.9 % under an applied voltage of −2 V, while the rejection rate for inorganic salts was 9 %. The dye/salt separation factor was approximately 11. Furthermore, the flux recovery rate of the CNT/MXene-PEI membrane was at 90 % after 12 h of operation with applied voltage of −2 V, indicating excellent anti-pollution performance and long-term operational stability. These results demonstrate the combined effect of structural regulation and electric field enhancement in the membrane's filtration performance. This study offers a new approach for overcoming the trade-off effect between permeability and selectivity in dye/salt separation processes.

In observational studies, covariates with substantial missing data are often omitted, despite their strong predictive capabilities. These excluded covariates are generally believed not to simultaneously affect both treatment and outcome, indicating that they are not genuine confounders and do not impact the identification of the average treatment effect (ATE). In this paper, we introduce an alternative doubly robust (DR) estimator that fully leverages non-confounding predictive covariates to enhance efficiency, while also allowing missing values in such covariates. Beyond the double robustness property, our proposed estimator is designed to be more efficient than the standard DR estimator. Specifically, when the propensity score model is correctly specified, it achieves the smallest asymptotic variance among the class of DR estimators, and brings additional efficiency gains by further integrating predictive covariates. Simulation studies demonstrate the notable performance of the proposed estimator over current popular methods. An illustrative example is provided to assess the effectiveness of right heart catheterization (RHC) for critically ill patients.

Acoustic topological insulators, as a type of acoustic metamaterial, possess special acoustic wave manipulation capabilities. However, an acoustic topological insulator based on Bragg scattering requires its lattice constant to be equivalent to the wavelength. This means that constructing acoustic topological insulators efficiently in the low-frequency range is a challenge. To this end, this paper proposes a method to construct sub-wavelength acoustic topological insulators by adding spatially folded resonant cavities at symmetric locations. It can easily reduce unidirectional transmission frequency bands with topological protection to subwavelength scales. On this basis, it is even possible to realize effective control of the unidirectional transmission band over a great range by adjusting the length parameter of the folded resonant cavity. The control range can reach more than 4000Hz. Experimental results from finite element simulations further verify that this approach does not affect the topologically protected edge states and the topologically unidirectional acoustic transmission properties. This work provides a method for the construction of low-frequency acoustic topological insulators, as well as an efficient method for the accurate regulation of unidirectional transmission frequency bands over a wide range of frequencies.

Diffuse radiation, which is modulated by cloud and aerosol conditions, can have varied impacts on gross primary production (GPP), with the specific impacts depending on vegetation density, environmental conditions, and the specific physiological characteristics of plants. To quantify the sensitivity of GPP variation to changes in diffuse radiation at the global scale, we use several reanalysis datasets and a satellite-derived products with distinct characterizations of the division between direct beam and diffuse radiation, to force the Energy Exascale Earth System Model Land Model (herein ELM). We find large variations in the range of GPP due to the change in ratio of diffuse radiation to the total downward shortwave radiation (or diffuse fraction). The research implies substantial control of diffuse radiation on atmosphere–biosphere interaction, and demonstrates the importance of thoroughly and systematically validating the simulated diffuse radiation by atmosphere modules, along with assessing the ecosystem responses to the diffuse radiation variations within global land models.

NELIBS using an Ag NP paper substrate achieves effective spectral enhancement, enabling serum analysis with limited sample preparation.

Abstract The acquisition and recognition of ultrasonic signals are essential forms of dynamic monitoring of bat species. In this work, a portable terminal of bat ultrasonic monitoring and online recognition based on an embedded platform and AudioMoth is presented. Depending on the significant differences in the typical characteristics of echolocation signals among different bat species, as well as their spectrogram features, a voiceprint recognition method of bat species by combining Convolutional Neural Network (CNN) with Long Short-Term Memory network (LSTM) was developed and then ported to the terminal. Furthermore, Majority Vote Algorithm (MVA) was employed to improve the recognition accuracy. The test results in a bat laboratory show that the terminal can achieve real-time collection and online recognition of bat ultrasonic signals, with a recognition accuracy of 99.18%, which is higher than those of the general four deep learning models. This research provides a practical case for bat acoustic monitoring and recognition and can be extended to wildlife diversity investigations.

Forest fires constitute a widespread and impactful natural disaster, annually ravaging millions of hectares of forests and posing a severe threat to human life and property.Accurate quantitative prediction of forest fire spread is essential for devising swift risk management strategies and implementing effective firefighting approaches.In response to this imperative, this study introduces a Forest Fire Spread Behavior Prediction (FFSBP) model, encompassing two integral components: the Forest Fire Spread Process Prediction (FFSPP) model and the Forest Fire Spread Results Prediction (FFSRP) model.The FFSPP model involves the prediction of the direction and speed of forest fire spread, achieved through a fusion of the Cellular Automata model and the Wang Zhengfei model.On the other hand, the FFSRP model focuses on forecasting the extent of the burned area, leveraging machine learning methods.To validate the efficacy of the proposed models, a real case study is undertaken using the "3.29 Forest Fire" incident in China.The FFSPP model is validated against this case, while the FFSRP model is assessed using a real fire dataset obtained from Montesinho National Forest Park in Portugal.Results from the validation process reveal that during the natural development period of the "3.29 Forest Fire," the FFSPP model predicts a burned area of 286.81 hm 2 , with an associated relative error of 28.94%.This relative error is notably smaller than those observed in the Farsite and Prometheus fire behavior simulation models.Additionally, the FFSRP model demonstrates commendable predictive performance, particularly in the context of small and medium-sized fire scenarios.These findings underscore the potential of the FFSBP model as a valuable tool in enhancing forest fire prediction accuracy and facilitating more robust risk mitigation and firefighting strategies.

Inflammatory bowel disease (IBD) is a chronic and relapsing inflammatory disorder of the gastrointestinal tract for which treatment options remain limited. In this study, we used a dual-luciferase-based screening of an FDA-approved drug library, identifying Bazedoxifene (BZA) as an inhibitor of the NF-κB pathway. We further investigated its therapeutic effects in a dextran sodium sulfate (DSS)-induced colitis model and explored its impact on gut microbiota regulation and the underlying molecular mechanisms. Our results showed that BZA significantly reduced DSS-induced colitis symptoms in mice, evidenced by decreased colon length shortening, lower histological scores, and increased expression of intestinal mucosal barrier-associated proteins, such as Claudin 1, Occludin, Zo-1, Mucin 2 (Muc2), and E-cadherin. Used independently, BZA showed therapeutic effects comparable to those of infliximab (IFX). In addition, BZA modulated the abundance of gut microbiota especially Bifidobacterium pseudolongum, and influenced microbial metabolite production. Crucially, BZA's alleviation of DSS-induced colitis in mice was linked to change in gut microbiota composition, as evidenced by in vivo gut microbiota depletion and fecal microbiota transplantation (FMT) mice model. Molecularly, BZA inhibited STAT3 and NF-κB activation in DSS-induced colitis in mice. In general, BZA significantly reduced DSS-induced colitis in mice through modulating the gut microbiota and inhibiting STAT3 and NF-κB activation, and its independent use demonstrated a therapeutic potential comparable to IFX. This study highlights gut microbiota's role in IBD drug development, offering insights for BZA's future development and its clinical applications.

In order to optimize the extraction of gigantol from Dendrobium officinale, the influence of methanol concentration, ultrasonic temperature, and liquid ratio on extraction efficiency was analysed by the response surface analysis method. The results show that the extraction rate reached a maximum when the methanol concentration was 92.98%, the solid-liquid ratio was 27.2 mL/g, and the extraction temperature was 41.41 °C. The content of gigantol of Dendrobium officinale in leaves was significantly higher than that in stems, reaching 4.7942 μg/g. The content of gigantol in Dendrobium huoshanensis Fengdou was significantly higher than that of other species of Fengdou. This experiment has practical significance for improving the utilization rate of Dendrobium officinale, and provides a reference for the study of the pharmacological and biological activity of gigantol.

The 20-inch MCP-PMT employs microchannel plates (MCP) as the electron multiplier unlike the traditional photomultiplier tubes (PMTs) with the dynode structure. According to the performance requirements for 20-inch PMTs to be used in the Hyper-Kamiokande (Hyper-K) project, North Night Vision Technology Co., Ltd. (NNVT) developed a novel 20-inch MCP-PMT based on the modification of the 20-inch MCP-PMT used for the Jiangmen Underground Neutrino Observatory by optimizing the design of the focusing electrode structure, the fabrication of the photocathode, and the other processes. The performance of the new NNVT 20-inch MCP-PMTs was evaluated and compared with respect to time resolution and noise. It was found that the transit time spread of the novel type is lower than 4 ns and the dark count rate is lower than 15 kHz. Compared to the previous model, the novel 20-inch MCP-PMT presents enhanced performance for time resolution and noise that is promising for its use in high-energy physics applications such as neutrino detection.

Developing high-performance electrocatalysts with low overpotential and high selectivity for nitrogen reduction reaction (NRR) is vital to the sustainable production of ammonia (NH3) at mild conditions. Recently, various B interstitial doped porous graphitic carbon nitride have been identified as efficient electrocatalysts for NRR, while the B substitutional doping has been rarely explored. In this work, three B doped C9N4 monolayers have been designed (BC, BN, and Bint), and their efficiencies toward NRR are evaluated by performing comprehensive first-principles calculations. Our results clearly reveal that N2 can be sufficiently activated on the BN and Bint monolayers due to the ”acceptance-donation” interaction, and prefers to be reduced to NH3 via the alternating mechanism. Particularly, BN monolayer shows superior catalytic activity with a rather low overpotential of 0.12 V comparing to Bint monolayer (0.56 V). Moreover, we find that this proposed BN monolayer has not only great thermal and dynamic stabilities but also excellent suppression effect on the competitive hydrogen evolution reaction. These theoretical findings suggest that B substitutional doping strategy might be another direction for the design of high-performance B-based NRR eletrocatalysts.

The dental arch plays an important role in generation of maxillofacial panoramic imaging and is beneficial to orthodontic treatment. However, it is hard to detect dental arches accurately and employ all them to reconstruct a panoramic image. In this paper, we propose a dental arch detection procedure based on radials from a configured center on each axial slice and can detect the dental arch on each axial slice. The program will first remove spines and those tissues above hard palate. Then, on each axial slice, it will search the inner and outer intersection points of the jaw with each radial at equal spaced interval based on large intensity variation. With these detected points, we can construct the dental arch through selection of feature points, spline interpolation, curving fitting processes. The results demonstrated that our method can accurately detect dental arches, and further, it performed well when the dental arch is lack in the mouth open on the axial slice.

The 20-inch photomultiplier tube has been extensively applied in neutrino detection, for example, in the Super-K, Daya Bay, and JUNO detectors. In order to achieve a high quantum efficiency, two types of structures, namely variably-doped and uniformly-doped structures, are proposed in this study. It is found that the maximum QE of the variably-doped K-Cs-Sb cathode is about 33%, as compared to the maximum QE of 25% for the uniformly-doped cathode. These high QE bialkali photocathodes of the 20-inch photomultiplier tubes were delivered to JUNO, and the average detection efficiency (410 nm) of 6384 mass-produced PMTs is found to be 30.1%.

• Cr 3+ /Pr 3+ -doped zinc gallogermanate nanoparticles emitted persistent luminescence at 700 nm. • Persistent luminescent nanoparticles (PLNPs) migrated into sentinel lymph nodes within 5 min. • The tumor drainage lymph node imaging of high contrast was achieved by PLNPs. • PLNPs were nontoxic to mice after intravenous injection. Tumor drainage lymph node identification and dissection are crucial for the oncological surgery to prevent/delay the recurrence. However, commercial imaging reagents distinguish the lymph nodes by staining them dark, which would be seriously interfered by blood and surrounding tissues. In this study, we reported the Cr 3+ /Pr 3+ -doped zinc gallogermanate persistent luminescent nanoparticles (PLNPs) for fast tumor drainage lymph node imaging with high contrast. PLNPs were synthesized by citrate sol-gel method and dispersed in Tween 80 for in vivo applications. PLNPs were well dispersed in water with hydrodynamic radii of 5 nm and emitted strong persistent luminescence at 696 nm upon the irradiation of UV light. The advantage of afterglow imaging over fluorescent imaging of PLNPs was first established after subcutaneous injection to mice with much higher contrast and less interference of autofluorescence. PLNPs quickly migrated to sentinel lymph nodes after the interdermal injection to extremity of mice. The tumor drainage lymph node imaging was achieved within 5 min upon the intratumoral injection to H460 tumor bearing mice and the signal to noise ratio was 462. Due to the lack of targeting moieties, the intravenous injected PLNPs mainly accumulated in liver. There were no statistical changes in serum biochemistry and abnormal histopathological characteristic, indicating the low toxicity of PLNPs. These findings highlighted the great potential of PLNPs as high-performance imaging reagent for lymph node identification.

The excitation power and temperature dependence of the photoluminescence (PL) and electroluminescence (EL) spectra were studied in green InGaN/GaN multiple quantum well (MQW)-based light-emitting diodes (LED). An examination of the PL-325, PL-405, and EL spectra at identical optical or electrical generation rates at room temperature showed that the normalized spectra exhibited different characteristic peaks. In addition, the temperature behavior of the peak energy was S-shaped for the PL-405 spectrum, while it was V-shaped for the EL spectrum. These measurement results demonstrate that the excitation source can affect the carrier dynamics about the generation (injection), transfer, and distribution of carriers.

Future collider detectors, including silicon tracking detectors planned for the High Luminosity LHC, will require components and mechanical structures providing unprecedented strength-to-mass ratios, thermal conductivity, and radiation tolerance. This paper studies carbon foam used in conjunction with thermally conductive epoxy and thermally conductive tape for such applications. Thermal performance and tensile strength measurements of aluminum-carbon foam-adhesive stacks are reported, along with initial radiation damage test results.

CBCT images have been widely used in digital orthodontics. In CBCT images, there are some tooth boundaries of blurriness and disappearance, and the teeth are of intensity inhomogeneity. In order to identify these boundaries and segment teeth, this paper develops an approach of alternate level set evolutions with controlled switch via slice-by-slice tooth segmentation: the user selects a voxel inside a tooth to initialize a small circle encircling the voxel, and the curve is automatically expanded until the tooth surface is formed. In each slice, the curve is expanded by two level set evolutions: the first level set evolution handles the intensity inhomogeneity and the second level set evolution solves the boundary blurriness and disappearance of the teeth. Experiments showed that the proposed method successfully segmented 12 CBCT datasets of 356 teeth and outperformed the geodesic active contour method and the popular method and the state-of-the-art method.

In order to meet the requirement of JUNO, 20-inch microchannel plate photomultiplier (MCP-PMT) was researched by the MCP-PMT collaboration, which was established by Institute of High Energy Physics (IHEP) and North Night Vision Technology Co., Ltd (NNVT) in 2012.By the breakthrough of the key technology, such as the electronic optics structure design, the high quantum efficiency photocathode process, and so on, the 20-inch MCP-PMT was developed successfully by 2015.The collection efficiency was about 98% and the detection efficiency (DE) was about 26%.At the same year, NNVT successfully bided for the 15000 PMTs of JUNO.In order to finish the contract of MCP-PMTs, the production line of 20-inch MCP-PMT was built on the 25 th Nov of 2016.The production line was the domestic advanced photomultiplier production line with capable of 7500 pieces 20-inch MCP-PMTs a year.By building the batch test system, the charge performance of 32 pieces PMTs could be tested at the same time.Recently, NNVT had delivered JUNO total 7000 pieces 20-inch MCP-PMTs.The average DE was increased to 30% from 27% since June 2018, and the average dark count rate was about 30 kHz.Based on the research finding of 20-inch MCP-PMT for JUNO, the 20-inch MCP-PMT with good time response was researched to meet the requirement of Hyper-K project, and developed successfully.The new 20-inch MCP-PMT had a flower-like focusing electrode.The transit time spread was about 5 ns, namely FWHM, better than the one of the original 20-inch MCP-PMT with 14ns.

In this work, we propose practical side-channel attacks for message recovery in post-quantum key encapsulation mechanisms (KEM). As a target scheme, Kyber is a standardized algorithm in the ongoing NIST standardization process. Notably, this work is the first one that implements message recovery by exploiting the information leaked on computational operations during Kyber decoding. The main findings include 1. analyzing computational operations during decoding by power consumption information to effectively recover message; 2. recovering message by analyzing the time differences existing in decoding single bits; 3. by way of simple power analysis, using incremental storage leakage to recover the message.

The large surface area and porous structure of MOF materials could provide binding sites for fluorescent moieties for bioimaging. Herein, we reported the preparation of fluorescent MOF material Zn(BDC) by 8-hydroquinoline modification [Zn(BDC)-8HQ]. Zn(BDC)-8HQ emitted strong fluorescence at 507 nm. The fluorescent Zn(BDC)-8HQ had a hydrodynamic radius of 255 nm, suitable for lymph node tracing. After subcutaneous injection, a bright spot could be distinguished at the injection site. The injections to front extremities resulted in sentinel lymph node accumulations. The low toxicity of Zn(BDC)-8HQ was evidenced by serum biochemical index and histopathological observations.

金顶铅锌矿床位于中国西南中新生代兰坪盆地,是亚洲第二大铅锌矿床,其巨大的储量和复杂的地质成矿史吸引了众多学者的研究,但在矿床成因和矿化过程的精细描述等方面仍存在较大争议。本文通过详细的野外地质调查并结合硫化物的LA-(MC)ICP-MS微量元素和硫、铅同位素分析对该矿床进行了详细解剖。金顶铅锌矿床的含矿地层为景星组砂岩、云龙组含砾砂岩及灰岩角砾岩。成矿过程可分为2个主要阶段:第Ⅰ阶段早期为浸染状的黄铁矿-白铁矿-闪锌矿-方铅矿,晚期硫化物呈块状且出现天青石;第Ⅱ阶段为闪锌矿-方铅矿-黄铁矿-天青石-重晶石-方解石-石膏阶段。成矿过程中硫化物的原位微量元素和S-Pb同位素表现出规律演化特征。主要金属元素除了以简单的类质同象形式赋存于闪锌矿中,Zn²⁺与微量元素存在4Zn²⁺&#8652;2Fe²⁺+Ge⁴⁺、2Zn²⁺&#8652;Fe²⁺+Mn²⁺、3Zn²⁺&#8652;In³⁺+Sn³⁺等复杂的替代关系。综合微量元素和S-Pb同位素演化规律,本文认为金顶铅锌矿的成矿流体早阶段与富含金属的盆地卤水和富含H₂S的流体有关,晚阶段则与大气水的混入有关。在后一过程中,大气水萃取了区域上富含Fe、Mn、Tl的红层碎屑岩,进而导致Fe、Mn、Tl等元素含量的升高,同时闪锌矿也表现出更宽范围的微量元素特征和更窄范围的²⁰⁸Pb/²⁰⁴Pb、²⁰⁷Pb/²⁰⁴Pb和<i>δ</i>³⁴S值的特征。由此推断,超大型金顶铅锌矿床是由多来源流体相互叠加而形成,其成矿物质主要来源于兰坪盆地沉积地层。此外,BSR作用在硫酸盐还原过程中起着重要作用,西部矿段还原硫可能还有少量TSR作用的贡献。最后,本文讨论了金顶铅锌矿床的矿床成因和精细矿化过程,综合分析认为它是一个受层间构造控制的、富Cd和Ge等多种分散元素的后生碎屑岩容矿型MVT铅锌矿床。

Abstract Low temperature plasma technology shows promise in sewage treatment with its advantages of high degradation efficiency, simple operation, and fewer by-products. In this study, a self-built Dielectric Barrier Discharge (DBD) plasma degradation experimental platform was utilized to simulate polymer-containing wastewater from an oilfield using a polyacrylamide (PAM) solution. The PAM solution was treated with low temperature plasma generated by dielectric barrier discharge combined with H 2 O 2 and a Mn + Cu/AC composite catalyst. The effects of different catalyst dosage, H 2 O 2 addition amount, DBD voltage on the degradation rate of polyacrylamide, molecular weight of solution, PH value of solution and solution viscosity were studied. The characterization of the polyacrylamide and composite catalyst before and after degradation was also conducted. The optimal conditions for the oxidation degradation of a PAM solution using low temperature plasma-H 2 O 2 -Mn + Cu/AC were determined as follows:: initial concentration 1000 mg/L, discharge voltage 18 kV, H 2 O 2 addition of 2% and catalyst addition of 810 mg. Increasing the catalyst dosage resulted in higher degradation rates, as well as decreased dynamic viscosity, pH value, and molecular weight of the solution. Under these conditions, the degradation rates of 60 min, 180 min and 300 min were 71.4%, 97.6% and 98.6%, respectively.

Abstract The effect of water deficit on grapevine fruit ripening has most often been addressed under the assumption that individual berries behave identically to their blend in the future harvest, both kinetically and metabolically. However, mixing unsynchronized berries, whose water and sucrose import pathways critically change according to their own developmental stages, intrinsically blurs the physiological and phenological effects of stress. We investigated the consequences of water deprivation on berry growth and primary metabolites content (glucose, fructose, tartaric and malic acids) on sixteen genetically distant genotypes of Vitis vinifera and fungus-tolerant hybrids submitted to 10 watering regimes, from well-watered to partial leaf shedding. Then, six genotypes were selected for comprehensive single berry analyses. Own-rooted potted plants bearing berries at the late herbaceous plateau stage were subjected to the different water treatments for four weeks in a greenhouse with automated regulation of soil water content. Berry and cluster growth were monitored by image analysis, before performing a final destructive sampling to determine berry weight and composition. Grape phenology was highly dependent on water availability. In some cultivars, ripening was considerably delayed or even prevented under well-watered conditions. These cultivars required an intermediate water deficit to trigger the second berry growth period along with sugar accumulation and malate breakdown, typical of the ripening process. Ripening still occurred in all genotypes upon severe water deprivation, although sugar accumulation and concentration were dramatically impaired, and the second growth period was annihilated or even replaced by shrivelling. Water deficit increased malate breakdown, uncoupling it from sugar accumulation. Single berry analyses suggest that although asynchronicity in berry ripening was reduced upon stress, individual fruits within the same cluster may undergo heterogeneous water budgets, expansion or shrivelling.

The random fluctuation caused by the high percentage of new energy makes the operation of the distribution network face severe challenges. With the purpose of improving the economy of the distribution net, this paper puts forward an economic operation strategy based on two-layer optimal dispatching with multi-microgrids lease shared energy storage. Firstly, the architecture of distribution network partitioning system with multi-microgrid shared energy accumulation is introduced, and establishes the shared energy accumulation power interaction model. Secondly, for the given shared energy storage capacity, a quantitative apportion model of the initial capacity of shared energy reservation is established from the perspective of wind and solar absorption of microgrid. With that, a two-layer optimization model for distribution network with multi-microgrid lease shared energy accumulation is recommended, in which the upper goal is to optimize the load flow of the distribution network, and the lower target is to cut down the operating cost of multi-microgrid and abandon wind and discard light. The results show that the strategy of numerous microgrids leasing shared energy reservation for the economy of distribution network, can achieve the co-ordination of supply and demand of source and load.

With the explosive growth of network information, demands for hardware implementation of cryptographic algorithms is increasing rapidly in recent years. However, the greatest limitation impeding extensive data encryption lies in that, there lack of efficient and lightweight cryptography implementations adaptable for ubiquitous smart devices, especially for those IoT devices, whose power and computations are both limited. In that case, a well-designed processing unit for cryptography computations is the critical way to boost ubiquitous usages of cryptography-based data protections. In this paper, we take SM2/SM3 algorithms as an example, to propose a brand new RISC-V compatible coprocessor design, named as ZigZag, aiming at easy usages in IoT environments. More specifically, we adopt two-fold optimizations for both SM2/3 computations on paralleled calculations in ZigZag, one is the paralleled double point multiplication design for SM2 computation acceleration, and the other is the optimization of SM3 in terms of message extension and compression functions. To justify the correctness and efficiency of the proposed ZigZag architecture, we implement a coprocessor prototype on the basis of RISC-V compatible development toolchains, running on Xilinx FPGA VCU118 when testing the prototype's performance. Our experiments show that, the ZigZag prototype takes 0.106 ms for a 256-bit point multiplication operation with 29.2k LUTs + 128 DSP hardware consumptions, which is 3.49 times faster in FPGA implementations than the state-of-the-art design.

Cooperative multi-agent reinforcement learning (CMARL) has shown promise in solving real-world scenarios. The interaction information between agents contains rich global information, which is easily neglected after perceiving other agents' behavior. To tackle this problem, we propose Collaboration Interaction Information Modelling via Hypergraph (CIIMH), which first perceives the behavior of other agents by mutual information optimization and constructs the dynamic interaction information via hypergraph. Perceived behavioral features of other agents are further aggregated in the hypergraph convolutional network to obtain interaction information. We compare our method with three existing baselines on StarCraft II micromanagement tasks (SMAC), Level-based Foraging (LBF), and Hallway. Empirical results show that our method outperforms baseline methods on all maps.

Ancient glass is extremely susceptible to environmental influences and thus weathering, and after the original elements of the glass are exchanged with the environmental elements, the original chemical composition of the glass will also change and thus pose an obstacle to the determination of the type of glass (high potassium or lead-barium). In this paper, firstly, independent samples MannWhitney U test is conducted on the data. In this paper, the independent samples MannWhitney U-test is performed on the data to obtain the chemical compositions of high-potassium and lead-barium with significant differences; and then the CART decision tree algorithm is used to realize the classification of high-potassium and lead-barium glasses. Classification rule: Distinguish high potassium and lead-barium glasses by lead oxide, barium oxide and silica. For the subclassification problem. We choose suitable chemical components for each type of glass and perform K-means clustering, and find that lead oxide and silicon dioxide can be used to classify lead-barium glass into subclasses, and potassium oxide and calcium oxide can be used to classify high-potassium glass into subclasses.

GaN-based green light-emitting diodes (LEDs) with different thicknesses of the low-temperature (LT) p-GaN layer between the last GaN barriers and p-AlGaN electron blocking layer were characterized by photoluminescence (PL) and electroluminescence (EL) spectroscopic methods in the temperature range of 6-300 K and injection current range of 0.01-350 mA. Based on the results, we suggest that a 20 nm-thick LT p-GaN layer can effectively prevent indium (In) re-evaporation, improve the quantum-confined Stark effect in the last quantum well (QW) of the active region, and finally reduce the efficiency droop by about 7%.

본 논문은 다기능 학습 커뮤니티 시스템의 설계와 구현에 대한 내용을 다룬다. 본 논문은 다양한 기능을 갖고 있는 온라인 학습 커뮤니티 시스템의 최신동향 및 관련 연구를 분석하였다. 본 시스템의 설계는 시스템 작업 흐름, 시스템 설계 단계의 기능 구분, 데이터베이스 테이블 설계, 시스템 인터페이스 설계를 하였다. 본 시스템은 관리자 모드와 사용자 모드를 구성하여 구현하였으며, 다른 학습 커뮤니티와 기능을 비교 검토하였다. This paper describes the design and implementation of the multi-function learning community system. Recent trends and related researches regarding the learning community system are surveyed and analyzed. The function sections, data flows, database tables and system interface are designed. Manager and user's modes are implemented and we compare the system functions with other learning communities.

In this paper, we give a framework to select food suppliers.The proposed framework is divided into three stages.During the first stage, we construct an index system that include quality, ability, management, service and R&D.In the second stage, we use entropy and Analytic Hierarchy Process(AHP) to determine weights.The third stage is associated with the application of Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to rank food suppliers and select the best one.In the end, we give an example to prove the method is validity and fessibility.

Conditional random field (CRF) is a spatial state model proposed by the probability graph school of thought, and it belongs to the undirected probability inference model in the area of probability graph model. CRF combines the advantages of several classical models in machine learning (ML) and plays an important role in solving the model parameters of ML algorithms which describe unconstrained optimization problems. However, CRF also have its own defects, for some functions, such as multi-modal non convex smooth objective functions, it is difficult for it to find the global optimal solution by using gradient dependent methods, and the solution process is easy to fall into local optimal solution. At present, many scholars have studied CRF related issues, but most of them have just tried to use CRF algorithm to solve specific application problems in various industries, there are few reports on the optimization of CRF algorithm itself, especially its solution process. Thus, in this paper, a derivative free optimization swarm intelligence method, namely Neiderreit sequence initialized eagle percolating optimizer (NSIEPO) has been proposed to replace the gradient dependent method in finding the global optimal solution. By numerical analysis, the effectiveness of the proposed algorithm has been verified.

The attack graph model is an effective method for analyzing multi-step attacks. Most existing related works only focus on networks with static topology and are unsuitable for the satellite Internet, whose backbone network periodically changes in topology. They are inefficient in path retrieval and unreasonable in attack path inference. To improve the retrieval efficiency of attack paths, we first propose a network logical attack graph with periodic changes. It can reduce retrieval space while preserving the exploitation relationship among hosts in a period. Then we design a hierarchical parallel search algorithm to quickly retrieve attack paths by dividing the path retrieval space into independent subspaces that can compute in parallel. To reasonably infer the attack paths, considering the impact of attack moment and topological connection duration on the selection probability of the attack path, we calculate it in combination with the basic exploitability probability, the total attack duration intention, the asset value, the time-based PageRank centrality, and the attack completion ratio. The experimental results demonstrate the effectiveness of our method.

Multi-wall carbon nanotubes (MWCNTs) are widely used in various fields due to their superior properties. Due to its wide-ranging research and application, the biosafety of MWCNTs should be carefully considered. In the study, we reported that the toxicity of MWCNTs and the influence on the reproductive ability to strawberry. The growth status and reproductive ability of strawberry were monitored after 60 days of soil culture in the presence of MWCNTs. MWCNTs showed adverse effects on the photosynthesis of strawberry leaves and the reproductive capacity of strawberry has been suppressed. Our results collectively suggested that the biosafety of MWCNTs should be highly concerned.

The purpose of our project is to greatly increase the moderation efficiency of high energy positrons (several hundred keV) to low energy positrons (a few eV). We will attempt to do this by first efficiently premoderating almost all of the positrons emitted from the radioactive source to energies less than 10 keV. These positrons will be injected in a solid neon moderator which has been shown to have a moderation efficiency of ∼50% at these energies. The immediate objective is to show that confining and guiding electromagnetic fields together with repeated slowing down traversals through a thin solid foil leads to a high efficiency in the premoderation of much of the entire β+ spectrum. We have performed computational simulation of the trajectories of positrons in the premoderation stage, and the point has now been reached where test experiments can be carried out. These will be done in the spring of 1993. We are presently evaluating different positron emitting radioactive sources, and simultaneously considering various extraction mechanisms for removing positrons from a high magnetic field region to a field free space in addition to the originally proposed phase space shifter. Besides a status report of the project, which emphasizes specific research and development work, a discussion will be given of the future steps and their time schedules, and of the planned initial beam experiments.

A discussion will be given of the magnetic and electrostatic confinement which will be used in the premoderation stage in the PSI positron beam project [1]. An analysis of the positron trajectories based upon various computer codes and Monte Carlo calculations has given us the angular and energy distribution of positrons slowing down in a carbon foil at the center of the confinement. These analyses will be compared with the planned experimental measurements to optimize the efficiency of our system to premoderate positrons from several hundreds of keV to 5–10 keV.