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Resetting, in which a system is regularly returned to a given state after a fixed or random duration, has become a useful strategy to optimize the search performance of a system. While earlier theoretical frameworks focused on instantaneous resetting, wherein the system is directly teleported to a given state, there is a growing interest in physical resetting mechanisms that involve a finite return time. However employing such a mechanism involves cost and the effect of this cost on the search time remains largely unexplored. Yet answering this is important in order to design cost-efficient resetting strategies. Motivated from this, we present a thermodynamic analysis of a diffusing particle whose position is intermittently reset to a specific site by employing a stochastic return protocol with external confining trap. We show for a family of potentials U R ( x ) ∼ | x | m with m  > 0, it is possible to find optimal potential shape that minimises the expected first-passage time for a given value of the thermodynamic cost, i.e. mean work. By varying this value, we then obtain the Pareto optimal front, and demonstrate a trade-off relation between the first-passage time and the work done.

In typical turbulent flow problems, detailed heat transfer coefficient (h) maps obtained through short-duration experiments are based on inverse heat transfer methods that take the wall temperatures measured via liquid crystals or infrared thermography as input, and an error minimization routine is adopted to determine the best value of h that satisfies the wall temperature temporal evolution under a certain change in fluid temperature. A common practice involves modeling the solid as a one-dimensional semi-infinite medium by selecting the solid material that has low thermal conductivity and low thermal diffusivity. However, in certain flow scenarios, the neglection of the lateral heat diffusion may lead to significant errors in the deduced h values. It is imperative to understand the reasons behind large errors that may be incurred by using the 1D heat conduction assumption in order to accurately determine high-resolution h maps for better heat exchanger designs in a wide range of thermal management applications. This paper presents a computational heat transfer study on different jet impingement scenarios to demonstrate the errors incurred in the determination of h when calculated under the assumption of one-dimensional (1-d) heat conduction into a solid. To this end, three different cases are studied: (a) single jet, (b) array jet (theoretical distribution), (c) array jet (experimental distribution), along with three different mainstream temperature evolution profiles representing step change, moderately fast transient and slow transient nature of flow driving the heat transfer in the solid. A known distribution of heat transfer coefficient (“true h”) for each of the three cases is considered, and three-dimensional transient heat diffusion equations were solved to populate temperatures of each node in the solid at every time step. It is found that stagnation zones’ h1d calculations were lower than the “true h” while the low heat transfer zones exhibited significantly higher h1d compared to the “true h”. For the array jet (experimental distribution) case, it was observed that errors can be as high as 10% in certain low heat transfer zones. Different data reduction procedures, configurations, and conditions explored in this study indicate that a suitable balance can be achieved if shorter time durations in transient experiments are used as a reference for tracking in h1d calculations to keep the deviations from the “true h” low.

Although child immunization is regarded as a highly cost-effective lifesaver, about fifty percent of the eligible children aged 12-23 months in India are without essential immunization coverage. Despite several programmatic initiatives, urban-rural and gender difference in child immunization pose an intimidating challenge to India's public health agenda. This study assesses the urban-rural and gender difference in child immunization coverage during 1992-2006 across six major geographical regions in India. Three rounds of the National Family Health Survey (NFHS) conducted during 1992-93, 1998-99 and 2005-06 were analyzed. Bivariate analyses, urban-rural and gender inequality ratios, and the multivariate-pooled logistic regression model were applied to examine the trends and patterns of inequalities over time. The analysis of change over one and half decades (1992-2006) shows considerable variations in child immunization coverage across six geographical regions in India. Despite a decline in urban-rural and gender differences over time, children residing in rural areas and girls remained disadvantaged. Moreover, northeast, west and south regions, which had the lowest gender inequality in 1992 observed an increase in gender difference over time. Similarly, urban-rural inequality increased in the west region during 1992-2006. This study suggests periodic evaluation of the health care system is vital to assess the between and within group difference beyond average improvement. It is essential to integrate strong immunization systems with broad health systems and coordinate with other primary health care delivery programs to augment immunization coverage.

Vast stretches of India comes under meteorological drought this year or the other. A huge population base in rural India are rendered highly vulnerable to this drought because of their primary dependency on agriculture and in turn they may respond through temporary migration out of the drought affected rural areas in search of alternative livelihoods. This study aims to investigate the association between drought and temporary migration in rural India by fitting binary logistic regression models on a cross-sectional dataset involving both National Sample Survey Organization (NSSO) 64 th round data and India Meteorological Department (IMD) rainfall data. The paper also examines whether this association varies across the different socio-economic groups. Out of the total temporary migrants generated in rural India in the study period, 99.46% migrated internally and 67.12% were rural to urban migrants. The study finds that there is a positive association between drought instances and probability of a household to have at least one temporary migrant member in rural India (OR 1.64 with p<0.001) while controlling all other covariates. The study also concludes that the probability of temporary migration on account of drought is more severe among the socio-economically marginalised sections of the rural population compared to their better-off counterparts.

Software and Programming Tools in Pharmaceutical Research is a detailed primer on the use for computer programs in the design and development of new drugs. Chapters offer information about different programs and computational techniques in pharmacology. The book will help readers to harness computer technologies in pharmaceutical investigations. Readers will also appreciate the pivotal role that software applications and programming tools play in revolutionizing the pharmaceutical industry. The book includes nine structured chapters, each addressing a critical aspect of pharmaceutical research and software utilization. From an introduction to pharmaceutical informatics and computational chemistry to advanced topics like molecular modeling, data mining, and high-throughput screening, this book covers a wide range of topics. Key Features: · Practical Insights: Presents practical knowledge on how to effectively utilize software tools in pharmaceutical research. · Interdisciplinary Approach: Bridges the gap between pharmaceutical science and computer science · Cutting-Edge Topics: Covers the latest advancements in computational drug development, including data analysis and visualization techniques, drug repurposing, pharmacokinetic modelling and screening. · Recommendations for Tools: Includes informative tables for software tools · Referenced content: Includes scientific references for advanced readers The book is an ideal primer for students and educators in pharmaceutical science and computational biology, providing a comprehensive foundation for this rapidly evolving field. It is also an essential resource for pharmaceutical researchers, scientists, and professionals looking to enhance their understanding of software tools and programming in drug development. Readership Pharmaceutical researchers, scientists, and professionals; students and educators in pharmacology and computational biology.

Coupled with the largest number of maternal deaths, adolescent pregnancy in India has received paramount importance due to early age at marriage and low contraceptive use. The factors associated with the utilization of maternal healthcare services among married adolescents in rural India are poorly discussed. Using the data from third wave of National Family Health Survey (2005-06), available in public domain for the use by researchers, this paper examines the factors associated with the utilization of maternal healthcare services among married adolescent women (aged 15-19 years) in rural India. Three components of maternal healthcare service utilization were measured: full antenatal care, safe delivery, and postnatal care within 42 days of delivery for the women who gave births in the last five years preceding the survey. Considering the framework on causes of maternal mortality proposed by Thaddeus and Maine (1994), selected socioeconomic, demographic, and cultural factors influencing outcome events were included as the predictor variables. Bi-variate analyses including chi-square test to determine the difference in proportion, and logistic regression to understand the net effect of predictor variables on selected outcomes were applied. Findings indicate the significant differences in the use of selected maternal healthcare utilization by educational attainment, economic status and region of residence. Muslim women, and women belonged to Scheduled Castes, Scheduled Tribes, and Other Backward Classes are less likely to avail safe delivery services. Additionally, adolescent women from the southern region utilizing the highest maternal healthcare services than the other regions. The present study documents several socioeconomic and cultural factors affecting the utilization of maternal healthcare services among rural adolescent women in India. The ongoing healthcare programs should start targeting household with married adolescent women belonging to poor and specific sub-groups of the population in rural areas to address the unmet need for maternal healthcare service utilization.

The flagellar motor supports bacterial chemotaxis, a process that allows bacteria to move in response to their environment. A central feature of this motor is the MS-ring, which is composed entirely of repeats of the FliF subunit. This MS-ring is critical for the assembly and stability of the flagellar switch and the entire flagellum. Despite multiple independent cryoEM structures of the MS-ring, there remains a debate about the stoichiometry and organization of the ring-building motifs (RBMs). Here, we report the cryoEM structure of a Salmonella MS-ring that was purified from the assembled flagellar switch complex (MSC-ring). We term this the ‘post-assembly’ state. Using 2D class averages, we show that under these conditions, the post-assembly MS-ring can contain 32, 33, or 34 FliF subunits, with 33 being the most common. RBM3 has a single location with C32, C33, or C34 symmetry. RBM2 is found in two locations with RBM2 inner having C21 or C22 symmetry and an RBM2 outer -RBM1 having C11 symmetry. Comparison to previously reported structures identifies several differences. Most strikingly, we find that the membrane domain forms 11 regions of discrete density at the base of the structure rather than a contiguous ring, although density could not be unambiguously interpreted. We further find density in some previously unresolved areas, and we assigned amino acids to those regions. Finally, we find differences in interdomain angles in RBM3 that affect the diameter of the ring. Together, these investigations support a model of the flagellum with structural plasticity, which may be important for flagellar assembly and function.

Impingement heat transfer is considered one of the most effective cooling technologies that yield high localized convective heat transfer coefficients. This paper studies different configurable parameters involved in jet impingement cooling such as, exit orifice shape, crossflow regulation, target surface modification, spent air reuse, impingement channel modification, jet pulsation, and other techniques to understand which of them are critical and how these heat-transfer-enhancement concepts work. The aim of this paper is to excite the thermal sciences community of this efficient cooling technique and instill some thoughts for future innovations. New orifice shapes are becoming feasible due to innovative 3D printing technologies. However, the orifice shape variations show that it is hard to beat a sharp-edged round orifice in heat transfer coefficient, but it comes with a higher pressure drop across the orifice. Any attempt to streamline the hole shape indicated a drop in the Nusselt number, thus giving the designer some control over thermal budgeting of a component. Reduction in crossflow has been attempted with channel modifications. The use of high-porosity conductive foam in the impingement space has shown marked improvement in heat transfer performance. A list of possible research topics based on this discussion is provided in the conclusion.

Nanomaterials have shown immense potential for their versatile applications in various sectors like medicine, healthcare, food sector, environment, agriculture, electronics, and pharmaceutics due to their unique and tunable physicochemical properties attributed to their small sizes. Recently nanomaterials have garnered foremost interest in agricultural applications due to constructive results of various studies showing significantly better crops growth/yield as compared to traditional fertilizers and pesticides. Besides, nanomaterials have shown encouraging results to deal with problems associated with conventional fertilizers, such as low nutrient usage efficiency and unregulated nutrient release with no precise control on the nutrients delivery. Moreover, nanomaterials have positively impacted plants growth attributing to higher chlorophyll content in leaves, increased root/shoot lengths, and better stress tolerance. Furthermore, nanomaterials are extremely capable of disease detection in plants and soil remediation. In this review, we have attempted to provide the readers with a complete overview of nanomaterials in agriculture by implementing the ideas of precision farming. Hereby, we have deliberated the development of nanomaterials in agriculture in the form of nanofertilizers, nanopesticides and nanosensors for sustainable growth in crops productivity, quality and protection. We have also illuminated the possibility of integrated farm management via soil remediation using nanotechnology. Finally, we have explicated limitations and possible improvements of nanomaterials for sustainable agricultural applications.

With the outbreak of the Coronavirus Disease in 2019, life seemed to be had come to a standstill. To combat the transmission of the virus, World Health Organization (WHO) announced wearing of face mask as an imperative way to limit the spread of the virus. However, manually ensuring whether people are wearing face masks or not in a public area is a cumbersome task. The exigency of monitoring people wearing face masks necessitated building an automatic system. Currently, distinct methods using machine learning and deep learning can be used effectively. In this paper, all the essential requirements for such a model have been reviewed. The need and the structural outline of the proposed model have been discussed extensively, followed by a comprehensive study of various available techniques and their respective comparative performance analysis. Further, the pros and cons of each method have been analyzed in depth. Subsequently, sources to multiple datasets are mentioned. The several software needed for the implementation are also discussed. And discussions have been organized on the various use cases, limitations, and observations for the system, and the conclusion of this paper with several directions for future research.