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Abstract Regional weather and climate are generally impacted by global climatic phenomenon′s. Understanding the impact of global climate phenomenon′s on an atmospheric branch of the hydrological cycle is crucial to make advances in skillful precipitation forecast. The present study adopts a multiscale approach based on wavelets for unravelling the linkages between teleconnections and atmospheric moisture transport over homogeneous regions of Indian sub-continent. We investigated linkages between atmospheric moisture transport quantified as monthly integrated water vapor transport (IVT) during 1951–2022 over selected homogeneous regions and eight large scale climate oscillations using wavelet and global wavelet coherence. Our results indicate significant heterogeneity in linkages across different regions and across multiple timescales. In particular, the Indian Ocean Dipole (IOD) influence monthly IVT at intra-annual to inter-annual scale over all regions. The El Niño–Southern Oscillation (ENSO) have strong connection to monthly IVT at inter-annual scale whereas over west central region both IOD and ENSO strongly influence IVT at inter-decadal scale. While the Atlantic Multi-Decadal Oscillation and Pacific Decadal Oscillation have an impact on IVT in the north-east and southern regions, the Arctic Oscillation and North Atlantic oscillation have a strong inter-annual connection to IVT, majorly in the northwest and hilly regions. Overall, the methodology offers an effective approach for capturing the dynamics of atmospheric moisture transport in time–frequency space and provide a practical reference for prediction of atmospheric moisture transport linked precipitation over different regions of Indian subcontinent.

Objective: We developed and evaluated a training program for Accredited Social Health Activists (ASHAs), female community health workers (CHWs) in India, on non-communicable diseases (NCDs). Methods: A 5-day training program, developed using government-approved manuals, was tested in a randomised controlled trial in the Tehri-Garhwal district. Quantitative comparisons were undertaken using Student's t-test and two-way ANOVA. ASHAs in the intervention group were asked questions about new skills learnt. Results: Thirty-six ASHAs (20 intervention, 16 controls) participated (response rate 75.0%). Mean pre-test knowledge score was 43.3/100 points (95% CI 36.7–49.9) for the intervention group and 44.4 (38.9–49.9) for controls. The mean post-test knowledge score increased more in the intervention group (48.5-point increase; P

Photoresists are fundamental materials in photolithography and are crucial for precise patterning in microelectronic devices, MEMS, and nanostructures. This paper provides an in-depth review of recent advancements in positive photoresist research and development, focusing on discussion regarding the underlying mechanisms governing their behavior, exploring innovative fabrication techniques, and highlighting the advantages of the photoresist classes discussed. The paper begins by discussing the need for the development of new photoresist technologies, highlighting issues associated with adopting extreme ultraviolet photolithography and addressing these challenges through the development of advanced positive-tone resist materials with improved patterning features, resolution, and sensitivity. Subsequently, it discusses the working mechanisms and synthesis methods of different types and subtypes of photoresists, starting from non-chemically amplified, organic, and inorganic–organic hybrid photoresists and progressing to dry film resists, with an emphasis on the upsides of each. The paper concludes by discussing how future research in the field of lithography—prioritizing concerns related to environmental impacts, improved photoresist material and properties, and utilization of advanced quantum technology—can assist with revolutionizing lithography techniques.

Enhancement of wear resistance of components used in fast reactors is necessary for long service life of the components. Plasma nitriding is a promising surface modification technology to impart high hardness and improved wear resistance of various steel components. This study discusses the characterization of chrome nitrided SS316L casing ring used in secondary sodium pump of fast breeder reactor and its stability under long term sodium exposure. Microstructural and hardness analysis showed that stress relieved component could be chrome nitrided successfully to a thickness of about 100 μm. Assessment of in-sodium performance of the chrome nitrided casing ring subjected to long term exposure up to 5000h at 550°C, showed retention of chrome nitrided layer with a case depth almost similar to that before sodium exposure. A slight decrease in the hardness was observed due to prolonged high temperature sodium exposure. Tribological studies indicate very low coefficient of friction indicating the retention of good wear resistance of the coating even after long term sodium exposure.

Abstract In this article, we study the finite temperature properties of a 10-D version of a hardwall model for QCD. Introducing fundamental matter via probe D7-branes and separate cutoffs r m and r g for the branes and the bulk, we present a detailed exploration of the phases for varying temperature and quark mass. Finite thermodynamic quantities are calculated using the procedure of holographic renormalization and used to characterize the phases. Finally, by fitting glueball and vector meson masses, we show how a unique phase diagram can be isolated.

A modelling study is under way in preparation for a planned upgrade of the capacity of the kwaMashu WWTP in eThekwini, South Africa, from 50 to 80 ML/d. When the configuration of an existing plant is to be changed, the most critical part of the model calibration is the influent wastewater fractionation. However, the constantly varying characteristics of wastewater make experimental determination of an adequately representative set of components difficult, time-consuming and expensive, which constitutes significant barriers to the adoption of modelling by many municipalities. Compliance and process monitoring generate large sets of influent measurements of chemical oxygen demand (COD), free and saline ammonia (FSA), total suspended solids (TSS), etc., but these are insufficient for modelling purposes. In particular, biodegradability is not routinely measured. However, since influent fractionation is designed to predict the fate of material in the wastewater treatment process, it should be possible to infer the fractionation from a combination of influent and plant measurements. This case study demonstrates the application of a pair of modelling tools, a probabilistic influent fractionator and a simplified steady‑state plant‑wide model, to estimate the influent fractionation, together with certain unmeasured or unreliable operational parameters. HIGHLIGHTS Estimation of influent COD fractionation from routine plant measurements.; Data reconciliation using a simplified steady-state plant-wide model.; Estimation of unmeasured or unreliable operational parameters.; Methodology for improving a plant monitoring programme.;

Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by the destruction of pancreatic β-cells, leading to insulin deficiency. Insulin replacement therapy is the current standard of care for T1D, but it has significant limitations. However, stem cell-based replacement therapy has the potential to restore β-cell function and achieve glycaemic control eradicating the necessity for drugs or injecting insulin externally. While significant progress has been made in preclinical studies, the clinical translation of stem cell therapy for T1D is still in its early stages. In continuation, further research is essentially required to determine the safety and efficacy of stem cell therapies and to develop strategies to prevent immune rejection of stem cell-derived β-cells. The current review highlights the current state of cellular therapies for T1D including, different types of stem cell therapies, gene therapy, immunotherapy, artificial pancreas, and cell encapsulation being investigated, and their potential for clinical translation.

Snake-like modular robots (MRs) are highly flexible, but, to traverse a challenging terrain or explore a region of interest, MR needs to attain efficient locomotion depending on a tradeoff between objectives like forward velocity and power consumption of the robot. The objectives can vary with different weights depending upon the situation, reflecting relative objective importance. This study developed a multiobjective reinforcement learning algorithm based on a fuzzy inference system (FI-MORL) to select the most appropriate gait parameters of snake-like MRs according to the objective weights. The developed algorithm employs a fuzzy inference system to reduce the number of states in an environment, which results in faster learning. The proposed approach uses the previously learned experience to rapidly achieve the best objective values in response to a change in weights. While setting equal importance to the objectives, FI-MORL delivers superior performance than single-objective reinforcement learning algorithms by consuming 2% less power and gaining 2.5% higher velocity since it mitigates the effect of weight change, similar performance found comparing an actor-critic algorithm. Likewise, the proposed method outperforms by consuming 14% less power and achieving 11% higher velocity than traditional methods like proximal policy optimization, deep Q-network, and vanilla policy gradient. Even after weight change, FI-MORL achieved a 14% higher reward than the above methods. The proposed FI-MORL framework can effectively converge quicker and efficiently handle the changes in objective weights.

In the current paper, the authors are intended to manufacture the aluminum based metal matrix composite (MMC) employing the stir casting process. Further, the fabricated composite sample is investigated for machining characteristics during the die sink electrical discharge machining process (EDM). EDM is most commonly employed to satisfy the special needs of industry such as developing deep holes and complex contours from high strength materials such as composites, alloys, smart materials, and functionally graded materials. In the current study A356 and 4%, tungsten carbide (WC) powder are considered as matrix and strengthening materials respectively to fabricate the MMCs. During the machining activity, the input factors like discharge current (Ip), Voltage (Vg), Pulse On-Time (Ton), and flushing pressure (P) are optimized for achieving optimum surface roughness (SR), Tool Wear Rate (TWR) and Material Removal Rate (MRR). To estimate the ideal set of process factors grey regression analysis (GRA) is used. From the results, it was observed that the GRA is found to perform better than the RSM.

Objectives Gastric varices (GV) have been classified by the Sarin classification for over two decades. However, a subset of these varices does not fit into this classification. We share our experience on GV in past 20 years and propose a modification. Materials and Methods Consecutive patients with portal hypertension (PHT) posted for esophagogastroduodenoscopy were screened for GV between 1996 and 2016 at a tertiary-care hospital. GV were categorized as gastroesophageal varices (GOV1, GOV2) and isolated gastric varices (IGV1, IGV2) by Sarin’s classification. Patients with varices in esophagogastric region as well as distally in the stomach or duodenum, thus having efferent drainage into the superior as well as inferior vena cava simultaneously, remain unclassified and were coined as GOV3. Statistical Analysis Descriptive data was represented as mean (standard deviation) or median (interquartile range) or number (percentage). Chi-squared test, t-test, and logistic regression were done to compare groups and identify outcomes of interest. Results GV were recognized in 400 (11.5%) of 3,476 patients with PHT. Underlying disease was cirrhosis in 301 (75.2%), extrahepatic portal venous obstruction in 78 (19.5%), noncirrhotic portal fibrosis in 18 (4.5%) and Budd–Chiari syndrome in 3 (0.75%) patients with GV. GOV1, GOV2, IGV1, IGV2, and combined GOV1 with GOV2 were seen in 170 (42.5%), 154 (38.5%), 17 (4.3%), 5 (1.3%), and 12 (3.0%) patients; respectively. GOV3 were identified in 42 (10.5%) patients. Ninety-three patients with GV presented with gastrointestinal bleed and frequency of GOV2 was higher and GOV1 and GOV3 were lower among bleeders than non-bleeders. Conclusions A significant proportion of patients with GV remain uncategorized by current classification among PHT patients. Addition of GOV3 in Sarin’s classification will make it more comprehensive, uniform, and reproducible for future studies.

Transportation is one of the critical functions in any business, and its cost depends on many constraints, including driver behavior, weather, distance, and demand in the market. This study proposes a novel approach for multi-criteria decision-making problems using the analytical hierarchy process (AHP) with the trapezoidal neutrosophic fuzzy numbers to produce the best criteria for evaluating total transportation cost. The proposed trapezoidal neutrosophic fuzzy analytical hierarchy process (TNF-AHP) determines the most significant criteria to be considered for further investigation in ANN training. In this study on the transportation problem (TP), the demands at different destination points and the distances between source and demand cities were determined. An artificial neural network (ANN) model has been proposed for the collected data of the TP to investigate the prediction of total transportation cost. The proposed ANN model predicts the total transportation cost with two input which were chosen by the TNF-AHP. Collected data are trained from 2 to 25 neurons with a logsig activation function, and the ideal model for ANN has been observed by Levenberg-Marquardt’s feed-forward back-propagation (trainlm) learning algorithm with a single hidden layer (6-9-1) topology. It is found that the ANN model can predict the total transportation cost with high efficiency as the R values indicate a high degree of correlation. The recommended ANN model, mean absolute percentage error, Pearson product-moment correlation coefficient (R), and mean square error have been obtained adequately. The ANN model validation has been conducted, and its results are compared with the collected data.

The classical transportation problem and the solid transportation problem are special types of linear programming problems which are very important in Operations Research. In this paper, a solid transportation model is described, where the total supply of goods is insufficient to fulfil the total demand of goods, due to which the supplier company tries to obtain the required remaining goods from another source. An expression is derived to determine the import plan. The parameters of the model are considered to be uncertain and imprecise and are taken as trapezoidal neutrosophic numbers. The paper gives a general formulation of such a model and an algorithm is proposed to solve the model. The main objective function of the model present in the manuscript is to minimize the total cost. A formula is provided to check the degree of sufficiency of such a solution. The model is elucidated with a numerical example and its solution shows its efficiency and optimality in practical aspect. Finally, the paper provides a brief discussion about the computational time and some relative points of research.

According to the World Health Organization, between 8% and 38% of health workers suffer physical violence at some point in their careers. This multicentric study was conducted to find the prevalence, perceived risk factors, and measures to prevent workplace violence among doctors. The sample consisted of all 2nd- and 3rd-year resident doctors (n = 305) from three colleges in Uttar Pradesh. An anonymous, pretested in a similar setting, self-administered questionnaire was used. 69.5% of doctors reported to have experienced violence in one or other form in the past 1 year. In most incidents, relatives and attendants (69.3%) were involved in violence. No action was taken immediately in regard to violence in 35.3% of instances; 60.3% of study participants reported that they had repeated disturbing memories, thoughts, or images of the attack. Nonavailability of medicines (38.6%) and less staff (36.7%) were cited as top reasons behind violence.

Background/Aims: The aim of the study was to evaluate the safety of non-anesthesia provider (NAPP) administered propofol sedation in patients undergoing non-advanced gastrointestinal (GI) endoscopic procedures. Materials and Methods: Pubmed, Embase, Cochrane central register of controlled trials, Scopus, and Web of Science databases were searched for prospective observational trials involving non-advanced endoscopic procedures. From a total of 608 publications, 25 [colonoscopy (9), upper GI endoscopy (5), and combined procedures (11)] were identified to meet inclusion criteria and were analyzed. Data was analyzed for hypoxia rates, airway intervention rates, and airway complication rates. Results: A total of 137,087 patients were involved. A total of 2931 hypoxia episodes (defined as an oxygen saturation below 90%) were reported with a pooled hypoxia rate of 0.014 (95% CI being 0.008-0.023). Similarly, pooled airway intervention rates and pooled airway complication rates were 0.002 (95% CI being 0.006–0.001) and 0.001 (95% CI being 0.000–0.001), respectively. Conclusions: The rates of adverse events in patients undergoing non-advanced GI endoscopic procedures with NAPP sedation are extremely small. Similar data for anesthesia providers is not available. It is prudent for anesthesia providers to demonstrate their superiority in prospective randomized controlled trials, if they like to retain exclusive ownership over propofol sedation in patients undergoing GI endoscopy.

In the last decade, video games became a common vehicle for citizen science initiatives in life science, allowing participants to contribute to real scientific data analysis while learning about it. Since 2010, our scientific discovery game (SDG) Phylo enlists participants in comparative genomic data analysis. It is frequently used as a learning tool, but the activities were difficult to aggregate to build a coherent teaching activity. Here, we describe a strategy and series of recipes to facilitate the integration of SDGs in courses and implement this approach in Phylo. We developed new roles and functionalities enabling instructors to create assignments and monitor the progress of students. A story mode progressively introduces comparative genomics concepts, allowing users to learn and contribute to the analysis of real genomic sequences. Preliminary results from a user study suggest this framework may help to boost user motivation and clarify pedagogical objectives.