Praveen Chandra Tiwari

The radionuclide $^{22}$Na is a target of $\gamma$-ray astronomy searches, predicted to be produced during thermonuclear runaways driving classical novae. The $^{22}$Na(p,$\gamma$)$^{23}$Mg reaction is the main destruction channel of $^{22}$Na during a nova, hence, its rate is needed to accurately predict the $^{22}$Na yield. However, experimental determinations of the resonance strengths have led to inconsistent results. In this work, we report a measurement of the branching ratios of the $^{23}$Al $\beta$-delayed protons, as a probe of the key 204--keV (center-of-mass) $^{22}$Na(p,$\gamma$)$^{23}$Mg resonance strength. We report a factor of 5 lower branching ratio compared to the most recent literature value. The variation in $^{22}$Na yield due to nuclear data inconsistencies was assessed using a series of hydrodynamic nova outburst simulations and has increased to a factor of 3.8, corresponding to a factor of $\sim$2 uncertainty in the maximum detectability distance. This is the first reported scientific measurement using the Gaseous Detector with Germanium Tagging (GADGET) system.

A Quality by Design (QbD) systematic and analytical approach was used to develop a novel and sensitive Lenvatinib stability-indicating method. The ICH Q1A(R2) and Q3 guidelines were implemented to determine Lenvatinib degradation behavior under various environmental conditions. The QbD approach implementation has screening and optimization stages.The Placket–Burman design was used to assess primary parameters, and Response Surface Design (RSD) to optimize critical factors. The drug degradation was examined under different degradation conditions, including acidic, basic, oxidative, neutral, thermal, and photolytic conditions. Separation was achieved using a Shimadzu® C18 column (250 mm × 4.6 mm, particle size 5 µ) with the mobile phase consisted of Acetonitrile: 10 mM ammonium acetate at pH 3.5 (39:61, v/v) at a flow rate 0.8 mL/min. The run time was 20 min and the wavelength used was 245 nm. The drug found sensitive toward acid and base hydrolysis, resulting in the generation of five degradation products. These products were successfully identified using the optimized LC–MS compatible analytical method. The optimized method was found to be sensitive, reproducible, specific, and robust, with a linearity range of 10 to 60 mg/mL and a correlation coefficient (R2 = 0.9993). The greenness score of the analytical method was calculated, revealing that the developed method is environmentally friendly.

The Gaseous Detector with Germanium Tagging (GADGET) is a new detection system devoted to the measurement of weak, low-energy β-delayed proton decays relevant for nuclear astrophysics studies. It is comprised of a new gaseous Proton Detector equipped with a Micromegas readout for charged particle detection, surrounded by the existing Segmented Germanium Array (SeGA) for the high-resolution detection of the prompt γ-rays. In this work we describe in detail for the first time the design, construction, and operation of the GADGET system, including performance of the Proton Detector. We present the results of a recent commissioning experiment performed with 25Si beam at the National Superconducting Cyclotron Laboratory (NSCL). GADGET provided low-background, low-energy β-delayed proton detection with efficiency above 95%, and relatively good efficiency for proton-gamma coincidences (2.7% at 1.37 MeV).

SRAM (static random-access memory) is used to store the cache memory or data in static form. Unlike DRAM (dynamic random-access memory) it needs not to be refreshed. SRAM gives faster access than DRAM and it retains data bits as long as power is being supplied. DRAM uses capacitor to store the data bits whereas SRAM uses latching circuit(flip-flop). The latching circuit consists of four transistors (two CMOS inverters which are cross coupled) act as memory part. This paper compares 6T and 7T SRAM using Tanner EDA tools on 45nm technology. For both SRAMs, all the parameters such as Read noise margin, W-rite noise margin, and Hold noise margin are calculated and compared at different cell ratios. In our simulation we found that 7T SRAM cells have a larger noise margin than 6T SRAM cells at the same cell ratio, and as the cell ratio increases noise margins also increase.

Background: Spinal anesthesia for cesarean section is not a 100% successful technique. At times, despite straightforward insertion and drug administration, intrathecal anaesthesia for cesarean section fails to obtain any sensory or motor block.Methods: This study is aimed at comparing the incidence of hypotension and the need for vasopressors in patients submitted to caesarean section under spinal anaesthesia following preload with either crystalloid or colloid. This study was carried out on 100 healthy pregnant women with single term foetus and not in labor admitted at the labor room of Gynecological department of RIMS. Blood pressure, Pulse rate, O2 Saturation and episodes of hypotension were recorded every 5 minutes from the spinal block.Results: The study showed that maximum number of caesarean sections here performed for the indication of foetal distress which is seen in 44%, 48%, 52%, and 48% in Group A, Group B, Group C and Group D respectively. This is followed by scar tenderness and obstructed labour. In Group A maximum number of patients developed hypotension during 11-20 minutes duration which is 13 (61.9%) followed by 5 (23.8%) patients during first 10 minutes.Conclusions: The study concludes that the combined use of volume preloading to compensate for vasodilatation and vasopressor to counteract arterial dilatation is a very effective method in reducing the incidence, severity and duration of spiral hypotension. The combination group with decreased volume of preload and reduced dose of vasoconstrictor provides better haemodynamic stability when compared to preloading of vasoconstrictors alone.

Background: $\ensuremath{\beta}$-decay spectroscopy provides valuable information on exotic nuclei and a stringent test for nuclear theories beyond the stability line.Purpose: To search for new $\ensuremath{\beta}$-delayed protons and $\ensuremath{\gamma}$ rays of $^{25}\mathrm{Si}$ to investigate the properties of $^{25}\mathrm{Al}$ excited states.Method: $^{25}\mathrm{Si}\phantom{\rule{4pt}{0ex}}\ensuremath{\beta}$ decays were measured by using the Gaseous Detector with Germanium Tagging system at the National Superconducting Cyclotron Laboratory. The protons and $\ensuremath{\gamma}$ rays emitted in the decay were detected simultaneously. A Monte Carlo method was used to model the Doppler broadening of $^{24}\mathrm{Mg}\phantom{\rule{4pt}{0ex}}\ensuremath{\gamma}$-ray lines caused by nuclear recoil from proton emission. Shell-model calculations using two newly developed universal sd-shell Hamiltonians were performed.Results: The most precise $^{25}\mathrm{Si}$ half-life to date has been determined. A new proton branch at 724(4) keV and new proton-$\ensuremath{\gamma}$-ray coincidences have been identified. Three $^{24}\mathrm{Mg}\phantom{\rule{4pt}{0ex}}\ensuremath{\gamma}$-ray lines and eight $^{25}\mathrm{Al}\phantom{\rule{4pt}{0ex}}\ensuremath{\gamma}$-ray lines are observed for the first time in $^{25}\mathrm{Si}$ decay. The first measurement of the $^{25}\mathrm{Si}\phantom{\rule{4pt}{0ex}}\ensuremath{\beta}$-delayed $\ensuremath{\gamma}$-ray intensities through the $^{25}\mathrm{Al}$ unbound states is reported. All the bound states of $^{25}\mathrm{Al}$ are observed to be populated in the $\ensuremath{\beta}$ decay of $^{25}\mathrm{Si}$. Several inconsistencies between the previous measurements have been resolved, and new information on the $^{25}\mathrm{Al}$ level scheme is provided. An enhanced decay scheme has been constructed and compared to the mirror decay of $^{25}\mathrm{Na}$ and the shell-model calculations.Conclusions: The measured excitation energies, $\ensuremath{\gamma}$-ray and proton branchings, log $ft$ values, and Gamow-Teller transition strengths for the states of $^{25}\mathrm{Al}$ populated in the $\ensuremath{\beta}$ decay of $^{25}\mathrm{Si}$ are in good agreement with the shell-model calculations, offering gratifyingly consistent insights into the fine nuclear structure of $^{25}\mathrm{Al}$.

Abstract Classical novae are environments which can produce heavier elements up to mass A ∼ 40. These nuclides at the endpoint of nova nucleosynthesis consist of elements such as Ar, K, and Ca. There is an order of magnitude discrepancy with the predicted and theoretical abundances of these endpoint nuclides produced in a classical nova. The uncertainty in the theoretical 38 K(p,γ) 39 Ca reaction rate has been shown to affect the abundances by an order of magnitude or more. The only direct measurement of this reaction rate was performed with the DRAGON facility at TRIUMF; however additional spectroscopic data could aid the interpretation of this data as well as motivate further study of this reaction rate. In this study, we present the preliminary results of a spectroscopic study of 39 Ca using the 40 Ca(d,t) 39 Ca reaction carried out at the Maier-Leibnitz Laboratory in Garching, Germany.

During various stages of hardware design, different types of control signals get introduced; clock, reset are specified and connected at the RTL stage whereas signals like scan enable, isolation enable, power switch enable get added to implemented devices later in the flow.

Property Specification Language (PSL) is a form of temporal logic that has been mainly used in discrete domains (e.g. formal hardware verification). In this paper, we show that by merging machine learning techniques with PSL monitors, we can extend PSL to work on continuous domains. We apply this technique in machine learning-based anomaly detection to analyze scenarios of real-time streaming events from continuous variables in order to detect abnormal behaviors of a system. By using machine learning with formal models, we leverage the strengths of both machine learning methods and formal semantics of time. On one hand, machine learning techniques can produce distributions on continuous variables, where abnormalities can be captured as deviations from the distributions. On the other hand, formal methods can characterize discrete temporal behaviors and relations that cannot be easily learned by machine learning techniques. Interestingly, the anomalies detected by machine learning and the underlying time representation used are discrete events. We implemented a temporal monitoring package (TEF) that operates in conjunction with normal data science packages for anomaly detection machine learning systems, and we show that TEF can be used to perform accurate interpretation of temporal correlation between events.

Most of the CMS studies rely on the identification of b jets (b tagging), which is important for a broad range of analyses at CMS. Identification algorithms of jets from B hadrons heavily rely on machine learning tools and are thus natural candidates for advanced tools like deep neural networks. During the past couple of years, the CMS Collaboration has proven the power of deep neural networks implementing new algorithms, which outperform previous algorithms for b jet identification. While improving b tagging, the CMS Collaboration is pushing the heavy flavor identification beyond the traditional boundaries, with the implementation of b tagging algorithms specialized to the boosted topologies, and the development of c tagging algorithms, used to identify jets originated from charm quarks. With the increased experimentally excluded mass ranges of new particles, in several cases at the TeV scale, searches need to focus more and more on very boosted regimes. Several heavy flavor identification tools specific for boosted topologies have been developed to make these searches possible, such as b tagging of subjets and a double b tagger, aiming at the identification of boosted decays of the heavy particles into pairs of b quarks.

In classical novae simulations, the uncertainty in the reaction rate of $$^{ 38 }$$ K(p, $$\gamma $$ ) has been shown to affect the abundances of endpoint nuclides significantly. To better understand the reaction rate, we have done a spectroscopic study on $$^{ 39 }$$ Ca. The reaction $$^{ 40 }$$ Ca(d,t) $$^{ 39 }$$ Ca at a beam energy of 22 MeV was used to populate excited states of $$^{ 39 }$$ Ca. Tritons were momentum analyzed using a high resolution quadrupole-dipole-dipole-dipole (Q3D) magnetic spectrograph at 4 angles. Preliminary resonance energies for $$^{ 39 }$$ Ca within the energetic region of interest for classical novae - 6.0–6.4 MeV - were determined.


 
 
 Orphan imports and lost exports refer to import and export transactions that have been reported by only one of the two trading partners.They are excluded from computations of trade mis-invoicing based on comparing partner country trade statistics. We show that India’s trade with 19 trading partners over 2000-2018 not only indicates substantial trade mis-invoicing but alsosignificant orphan and lost trade in the commodities displaying mis- invoicing. We also show that the amounts involved show an uptrend and are more pronounced in imports, with the orphan imports recorded by India being more than 15 times the orphan imports recorded by partner countries. Therefore, any conclusion on illicit flows through mis-invoicing in these commodities will be incomplete without analysing the impact of orphan and lost trade. We analyse some possible causes and discuss specific commodity-level examples to demonstrate that orphan and lost trade could not only lead to re-adjustment of computed amounts of trade mis-invoicing but, in the worst scenario, indicate serious fraud, with important implications for illicit flows. The paper’s finding that only a few commodities account for bulk of the amounts in orphan and lost trade could facilitate better analysis and mitigation measures.