Indian Institute of Technology BHU

SymPy is an open source computer algebra system written in pure Python. It is built with a focus on extensibility and ease of use, through both interactive and programmatic applications. These characteristics have led SymPy to become a popular symbolic library for the scientific Python ecosystem. This paper presents the architecture of SymPy, a description of its features, and a discussion of select submodules. The supplementary material provide additional examples and further outline details of the architecture and features of SymPy.

The expansion of lithium-ion batteries from consumer electronics to larger-scale transport and energy storage applications has made understanding the many mechanisms responsible for battery degradation increasingly important. The literature in this complex topic has grown considerably; this perspective aims to distil current knowledge into a succinct form, as a reference and a guide to understanding battery degradation. Unlike other reviews, this work emphasises the coupling between the different mechanisms and the different physical and chemical approaches used to trigger, identify and monitor various mechanisms, as well as the various computational models that attempt to simulate these interactions. Degradation is separated into three levels: the actual mechanisms themselves, the observable consequences at cell level called modes and the operational effects such as capacity or power fade. Five principal and thirteen secondary mechanisms were found that are generally considered to be the cause of degradation during normal operation, which all give rise to five observable modes. A flowchart illustrates the different feedback loops that couple the various forms of degradation, whilst a table is presented to highlight the experimental conditions that are most likely to trigger specific degradation mechanisms. Together, they provide a powerful guide to designing experiments or models for investigating battery degradation.

The family of oxide glasses is very wide and it is continuously developing.

Despite learning based methods showing promising results in single view depth estimation and visual odometry, most existing approaches treat the tasks in a supervised manner. Recent approaches to single view depth estimation explore the possibility of learning without full supervision via minimizing photometric error. In this paper, we explore the use of stereo sequences for learning depth and visual odometry. The use of stereo sequences enables the use of both spatial (between left-right pairs) and temporal (forward backward) photometric warp error, and constrains the scene depth and camera motion to be in a common, real-world scale. At test time our framework is able to estimate single view depth and two-view odometry from a monocular sequence. We also show how we can improve on a standard photometric warp loss by considering a warp of deep features. We show through extensive experiments that: (i) jointly training for single view depth and visual odometry improves depth prediction because of the additional constraint imposed on depths and achieves competitive results for visual odometry; (ii) deep feature-based warping loss improves upon simple photometric warp loss for both single view depth estimation and visual odometry. Our method outperforms existing learning based methods on the KITTI driving dataset in both tasks. The source code is available at https://github.com/Huangying-Zhan/Depth-VO-Feat.

The application of nanomedicines is increasing rapidly with the promise of targeted and efficient drug delivery. Nanomedicines address the shortcomings of conventional therapy, as evidenced by several preclinical and clinical investigations indicating site-specific drug delivery, reduced side effects, and better treatment outcome. The development of suitable and biocompatible drug delivery vehicles is a prerequisite that has been successfully achieved by using simple and functionalized liposomes, nanoparticles, hydrogels, micelles, dendrimers, and mesoporous particles. A variety of drug delivery vehicles have been established for the targeted and controlled delivery of therapeutic agents in a wide range of chronic diseases, such as diabetes, cancer, atherosclerosis, myocardial ischemia, asthma, pulmonary tuberculosis, Parkinson's disease, and Alzheimer's disease. After successful outcomes in preclinical and clinical trials, many of these drugs have been marketed for human use, such as Abraxane®, Caelyx®, Mepact®, Myocet®, Emend®, and Rapamune®. Apart from drugs/compounds, novel therapeutic agents, such as peptides, nucleic acids (DNA and RNA), and genes have also shown potential to be used as nanomedicines for the treatment of several chronic ailments. However, a large number of extensive clinical trials are still needed to ensure the short-term and long-term effects of nanomedicines in humans. This review discusses the advantages of various drug delivery vehicles for better understanding of their utility in terms of current medical needs. Furthermore, the application of a wide range of nanomedicines is also described in the context of major chronic diseases.

Catalytic reforming of methane (CH₄) with carbon dioxide (CO₂), known as dry reforming of methane (DRM), produces synthesis gas, which is a mixture of hydrogen (H₂) and carbon monoxide (CO).

The bio-molecules from various plant components and microbial species have been used as potential agents for the synthesis of silver nanoparticles (AgNPs). In spite of a wide range of bio-molecules assisting in the process, synthesizing stable and widely applicable AgNPs by many researchers still poses a considerable challenge to the researchers. The biological agents for synthesizing AgNPs cover compounds produced naturally in microbes and plants. More than 100 different biological sources for synthesizing AgNPs are reported in the past decade by various authors. Reaction parameters under which the AgNPs were being synthesized hold prominent impact on their size, shape and application. Available published information on AgNPs synthesis, effects of various parameters, characterization techniques, properties and their application are summarised and critically discussed in this review.

Resveratrol is a polyphenolic nutraceutical that exhibits pleiotropic activities in human subjects. The efficacy, safety, and pharmacokinetics of resveratrol have been documented in over 244 clinical trials, with an additional 27 clinical trials currently ongoing. Resveretrol is reported to potentially improve the therapeutic outcome in patients suffering from diabetes mellitus, obesity, colorectal cancer, breast cancer, multiple myeloma, metabolic syndrome, hypertension, Alzheimer's disease, stroke, cardiovascular diseases, kidney diseases, inflammatory diseases, and rhinopharyngitis. The polyphenol is reported to be safe at doses up to 5 g/d, when used either alone or as a combination therapy. The molecular basis for the pleiotropic activities of resveratrol are based on its ability to modulate multiple cell signaling molecules such as cytokines, caspases, matrix metalloproteinases, Wnt, nuclear factor-κB, Notch, 5'-AMP-activated protein kinase, intercellular adhesion molecule, vascular cell adhesion molecule, sirtuin type 1, peroxisome proliferator-activated receptor-γ coactivator 1α, insulin-like growth factor 1, insulin-like growth factor-binding protein 3, Ras association domain family 1α, pAkt, vascular endothelial growth factor, cyclooxygenase 2, nuclear factor erythroid 2 like 2, and Kelch-like ECH-associated protein 1. Although the clinical utility of resveratrol is well documented, the rapid metabolism and poor bioavailability have limited its therapeutic use. In this regard, the recently produced micronized resveratrol formulation called SRT501, shows promise. This review discusses the currently available clinical data on resveratrol in the prevention, management, and treatment of various diseases and disorders. Based on the current evidence, the potential utility of this molecule in the clinic is discussed.

Green synthesis of silver nanoparticles makes use of plant constituents, like carbohydrates, fats, enzymes, flavonoids, terpenoids, polyphenols, and alkaloids, as reducing agents to synthesize silver nanoparticles. The present study for the first time utilized seed extract of Tectona grandis (teak) for reduction of 1 mM silver nitrate solution to silver nanoparticles. The method proved to be very simple, cost-efficient, and convenient. Synthesis of nanoparticles was confirmed by visual detection in which the colorless solution gets changed to a brown-colored solution. Further characterization was done by UV-visible spectroscopy, XRD, FTIR analysis, SEM/EDS, FESEM, and TEM. Size of silver nanoparticles was found to be 10–30 nm approximately as determined by transmission electron microscopy (TEM). Energy-dispersive spectra (EDS) revealed that nanoparticles contain silver in its pure form. Well diffusion method showed the antimicrobial effect of AgNPs on different microorganisms with the zone of inhibition of 16 mm for Staphylococcus aureus, 12 mm for Bacillus cereus, and 17 mm for E. coli when 50 μg of AgNPs was used. Minimum inhibitory concentration was found to be 5.2, 2.6, and 2.0 μg/ml for Bacillus cereus, Staphylococcus aureus, and E. coli respectively. Mode of action of antimicrobial activity of nanoparticles was investigated by determining leakage of reducing sugars and proteins, suggesting that AgNPs were able to destroy membrane permeability.

Abstract The word “textile” means to weave and was taken from the Latin word “texere.” Nowadays, textiles not only fulfill humankind's basic necessity for clothing, they also allow individuals to make fashion statements. As one of the oldest industries, the textile industry occupies a unique place in India. It is responsible for 14% of the total industrial manufacture in India. However, the textile industry is also considered to be one of the biggest threats to the environment. Pretreatment, dyeing, printing, and finishing operations are among the various stages of the industrial textile manufacturing process. These fabrication operations not only utilize huge quantities of power and water, they also generate considerable amounts of waste. The textile industry utilizes a number of dyes, chemicals, and other materials to impart the required qualities to the fabrics. These operations produce a significant amount of effluents. The quality of effluents is such that they cannot be put to other uses, and they can create environmental problems if they are disposed of without appropriate treatment. This review discusses different textile processing stages, pollution problems associated with these stages, and their eco‐friendly alternatives. Textile wet processing is described in detail, as it is the key process in the industry and it also generates the greatest amount of pollutants in textile processing. The environmental impact of textile effluents is discussed, as textile effluents not only impose negative effects on the quality of water and soil, they also imperil plant and animal health. In this paper, various methods for treating textile effluents are described. Discussion of physical, chemical, biological, and advanced treatment technologies of effluent treatment are included in this paper.

Robust, reliable, and quantitative detection of biomarkers at ultra-low concentration is of great importance in clinical settings. Biosensor, an analytical device used for sensitive and selective detection of biomarkers offers various advantages over the conventional clinical diagnosis, which is both time consuming and not suitable for point of care/onsite diagnosis. A revolution in the understanding and synthesis of nanomaterials in the last couple of decades contributed significantly to the development of the biosensors in terms of sensitivity, catalytic activity, biocompatibility, and robustness. Additionally, nanomaterials help in miniaturization of the sensing platform and helping in the commercial success of portable biosensor kits. Surface engineering equally contributed to the biosensor development by ensuring a reproducible and stable sensing surface, efficient analyte-biorecognition element interaction, and reduced fouling effect in biological solution. Due to nanomaterial integration and surface engineering, biosensors are now equally sensitive to the lab-based sophisticated instruments to detect a wide range of molecules of clinical significance. In this review, various types of biosensors, their designs, and their working principles have been discussed. A detailed account of various types of nanomaterials, their functionalization and characterization have also been discussed. The analytical performances of biosensors for both clinical validation and analyte detection have been incorporated here. The recent trends in advanced biosensors, such as smartphone interface for biosensing, nanozymes, lab-on-a-chip based detection methods have been discussed.

BACKGROUND: There is a rising incidence of chronic kidney disease that is likely to pose major problems for both healthcare and the economy in future years. In India, it has been recently estimated that the age-adjusted incidence rate of ESRD to be 229 per million population (pmp), and >100,000 new patients enter renal replacement programs annually. METHODS: We cross-sectionally screened 6120 Indian subjects from 13 academic and private medical centers all over India. We obtained personal and medical history data through a specifically designed questionnaire. Blood and urine samples were collected. RESULTS: The total cohort included in this analysis is 5588 subjects. The mean ± SD age of all participants was 45.22 ± 15.2 years (range 18-98 years) and 55.1% of them were males and 44.9% were females. The overall prevalence of CKD in the SEEK-India cohort was 17.2% with a mean eGFR of 84.27 ± 76.46 versus 116.94 ± 44.65 mL/min/1.73 m2 in non-CKD group while 79.5% in the CKD group had proteinuria. Prevalence of CKD stages 1, 2, 3, 4 and 5 was 7%, 4.3%, 4.3%, 0.8% and 0.8%, respectively. CONCLUSION: The prevalence of CKD was observed to be 17.2% with ~6% have CKD stage 3 or worse. CKD risk factors were similar to those reported in earlier studies.It should be stressed to all primary care physicians taking care of hypertensive and diabetic patients to screen for early kidney damage. Early intervention may retard the progression of kidney disease. Planning for the preventive health policies and allocation of more resources for the treatment of CKD/ESRD patients are imperative in India.

Use of waste or by-products from different industries and the agricultural sector has received increasing attention in the scientific, technology, ecological, economic and social spheres in recent years. Rice husk (RH) is a by-product of rice milling and rice husk ash (RHA) is generated by combustion in a separate boiler. Both RH and RHA are abundantly accessible in rice growing countries such as China, India, Brazil, the USA, and Southeast Asia. RH has therefore been recycled by burning it for energy production. This generates RHA, which contains a huge quantity (85–95%) of amorphous silica. Over the past two decades, RHA has been used extensively in numerous fields for manufacturing of different silicates, zeolites, catalysts, nanocomposite, cement, lightweight construction materials, insulators, and adsorbents. This paper presents a comprehensive overview on the processing of nano-silica from RH/RHA. It tries at the same time, to present a critical review of the application of RHA as an ingredient for the production of various ceramic materials, e.g. refractory, glass, whiteware, oxide and non-oxide ceramics, silica aerogel and SiO2/C composites. In summary, amorphous silica derived from RHA or RH provides a potential alternative to conventional silica sources (e.g. quartz) for the manufacture of value-added ceramics for practical applications.

Artificial intelligence (AI) encompasses a broad spectrum of techniques that have been utilized by pharmaceutical companies for decades, including machine learning, deep learning, and other advanced computational methods. These innovations have unlocked unprecedented opportunities for the acceleration of drug discovery and delivery, the optimization of treatment regimens, and the improvement of patient outcomes. AI is swiftly transforming the pharmaceutical industry, revolutionizing everything from drug development and discovery to personalized medicine, including target identification and validation, selection of excipients, prediction of the synthetic route, supply chain optimization, monitoring during continuous manufacturing processes, or predictive maintenance, among others. While the integration of AI promises to enhance efficiency, reduce costs, and improve both medicines and patient health, it also raises important questions from a regulatory point of view. In this review article, we will present a comprehensive overview of AI's applications in the pharmaceutical industry, covering areas such as drug discovery, target optimization, personalized medicine, drug safety, and more. By analyzing current research trends and case studies, we aim to shed light on AI's transformative impact on the pharmaceutical industry and its broader implications for healthcare.

Abstract The development of the Internet of Things (IoT) technology and their integration in smart cities have changed the way we work and live, and enriched our society. However, IoT technologies present several challenges such as increases in energy consumption, and produces toxic pollution as well as E-waste in smart cities. Smart city applications must be environmentally-friendly, hence require a move towards green IoT. Green IoT leads to an eco-friendly environment, which is more sustainable for smart cities. Therefore, it is essential to address the techniques and strategies for reducing pollution hazards, traffic waste, resource usage, energy consumption, providing public safety, life quality, and sustaining the environment and cost management. This survey focuses on providing a comprehensive review of the techniques and strategies for making cities smarter, sustainable, and eco-friendly. Furthermore, the survey focuses on IoT and its capabilities to merge into aspects of potential to address the needs of smart cities. Finally, we discuss challenges and opportunities for future research in smart city applications.

The study indicates that analysis of morphometric parameters with the help of geographic information system (GIS) would prove a viable method of characterizing the hydrological response behaviour of the watershed. It is also well observed that remote sensing satellite data is emerging as the most effective, time saving and accurate technique for morphometric analysis of a basin. This technique is found relevant for the extraction of river basin and its stream networks through ASTER (DEM) in conjunction with remote sensing satellite data (Landsat etm+, 2013 and georeferenced survey of Indian toposheet, 1972). In this study, Kanhar basin a tributaries of Son River has been selected for detailed morphometric analysis. Seven sub-watersheds are also delineated within this basin to calculate the selected morphometric parameters. Morphometric parameters viz; stream order, stream length, bifurcation ratio, drainage density, stream frequency, form factor, circulatory ratio, etc., are calculated. The drainage area of the basin is 5,654 km2 and shows sub-dendritic to dendritic drainage pattern. The stream order of the basin is mainly controlled by physiographic and lithological conditions of the area. The study area is designated as seventh-order basin with the drainage density value being as 1.72 km/km2. The increase in stream length ratio from lower to higher order shows that the study area has reached a mature geomorphic stage.

Recently, the Internet of Things (IoT) has attracted much interest in its wide applications, such as smart healthcare, home automation, transportation, and smart city. In these IoT-based systems, wireless sensor networks (WSNs) are highly used to gather information needed by smart environments. However, due to huge heterogeneous data coming from different sensing devices, IoT-enabled WSNs face different challenges, such as high communication delay, low throughput, and poor network lifetime. In this article, a deep-reinforcement-learning (DRL)-based intelligent routing scheme is proposed for IoT-enabled WSNs that significantly reduce delay and increase network lifetime. The proposed algorithm divides the whole network into different unequal clusters depending on the current data load present in the sensor node that significantly prevents immature death of the network. An extensive experiment on the proposed algorithm is performed using ns3. The experimental results are compared with the state-of-the-art algorithms to demonstrate the efficiency of the proposed scheme in terms of the number of alive nodes, packet delivery, energy efficiency, and communication delay in the network.

Figure (a) shows that the semi-crystalline nature of the polymer PVdF-HFP and Figure (b) shows that the polymer chain became flexible on the addition of LiTFSI salt. Furthermore, on the addition of IL in polymer electrolyte membranes, the membranes became more flexible and provide high ionic conduction (because of more availability of ions) in the system resulting in enhancement of the ionic conductivity (see Figure (c)).

Sugarcane industries are age-old industrial practices in India which contribute a significant amount of by-products as waste. Handling and management of these by-products are huge task, because those require lot of space for storage. However, it provides opportunity to utilize these by-products in agricultural crop production as organic nutrient source. Therefore, it is attempted to review the potential of sugar industries by-products, their availability, and use in agricultural production. A large number of research experiments and literatures have been surveyed and critically analyzed for the effect of sugarcane by-products on crop productivity and soil properties. Application of sugar industries by-products, such as press mud and bagasse, to soil improves the soil chemical, physical, and biological properties and enhanced the crop quality and yield. A huge possibility of sugarcane industries by-products can be used in agriculture to cut down the chemical fertilizer requirement. If all the press mud is recycled through agriculture about 32,464, 28,077, 14,038, 3434, 393, 1030, and 240 tonnes (t) of N, P, K, Fe, Zn, Mn, and Cu, respectively, can be available and that helps in saving of costly chemical fertilizers. Application of sugarcane industries by-products reduces the recommended dose of fertilizers and improves organic matter of soil during the crop production. It can also be used in combination with inorganic chemical fertilizers and can be packed and marketed along with commercial fertilizer for a particular cropping system. That helps in reduce the storage problem of sugarcane industries by-products across the India.

Concrete has a tremendous influence on the environment since the majority of its composition is cement, which is a material that emits high levels of carbon dioxide. It is possible for concrete construction to have a lower impact on the environment if the usage of cement is reduced as much as possible by the addition of mineral admixtures such as fly ash, without sacrificing the durability standards at the same time. The disposal of fly ash, which is produced by power stations that burn coal for fuel, is recognised as one of the most pressing environmental issues. When there is a simultaneous increase in the amount of fly ash and a decline in the capacity of landfills, it is much more difficult to find a solution to this problem. The research on fly ash admixed concrete is analysed and discussed in this publication. There have been many studies conducted on the topic of fly ash concrete and its beneficial effects. In this study, the fresh and hardened properties of fly ash concrete, such as mechanical properties, durability parameters, and microstructural characteristics, are studied. Additionally, the useful application case studies of fly ash concrete published by the American Coal Ash Association are also summarised.