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703 result(s) for "Kumar, Adarsh"
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An Overview of IoT Sensor Data Processing, Fusion, and Analysis Techniques
In the recent era of the Internet of Things, the dominant role of sensors and the Internet provides a solution to a wide variety of real-life problems. Such applications include smart city, smart healthcare systems, smart building, smart transport and smart environment. However, the real-time IoT sensor data include several challenges, such as a deluge of unclean sensor data and a high resource-consumption cost. As such, this paper addresses how to process IoT sensor data, fusion with other data sources, and analyses to produce knowledgeable insight into hidden data patterns for rapid decision-making. This paper addresses the data processing techniques such as data denoising, data outlier detection, missing data imputation and data aggregation. Further, it elaborates on the necessity of data fusion and various data fusion methods such as direct fusion, associated feature extraction, and identity declaration data fusion. This paper also aims to address data analysis integration with emerging technologies, such as cloud computing, fog computing and edge computing, towards various challenges in IoT sensor network and sensor data analysis. In summary, this paper is the first of its kind to present a complete overview of IoT sensor data processing, fusion and analysis techniques.
Nitrogen Containing Heterocycles as Anticancer Agents: A Medicinal Chemistry Perspective
Cancer is one of the major healthcare challenges across the globe. Several anticancer drugs are available on the market but they either lack specificity or have poor safety, severe side effects, and suffer from resistance. So, there is a dire need to develop safer and target-specific anticancer drugs. More than 85% of all physiologically active pharmaceuticals are heterocycles or contain at least one heteroatom. Nitrogen heterocycles constituting the most common heterocyclic framework. In this study, we have compiled the FDA approved heterocyclic drugs with nitrogen atoms and their pharmacological properties. Moreover, we have reported nitrogen containing heterocycles, including pyrimidine, quinolone, carbazole, pyridine, imidazole, benzimidazole, triazole, β-lactam, indole, pyrazole, quinazoline, quinoxaline, isatin, pyrrolo-benzodiazepines, and pyrido[2,3-d]pyrimidines, which are used in the treatment of different types of cancer, concurrently covering the biochemical mechanisms of action and cellular targets.
ROS generated from biotic stress: Effects on plants and alleviation by endophytic microbes
Aerobic living is thought to generate reactive oxygen species (ROS), which are an inevitable chemical component. They are produced exclusively in cellular compartments in aerobic metabolism involving significant energy transfer and are regarded as by-products. ROS have a significant role in plant response to pathogenic stress, but the pattern varies between necrotrophs and biotrophs. A fine-tuned systemic induction system is involved in ROS-mediated disease development in plants. In regulated concentrations, ROS act as a signaling molecule and activate different pathways to suppress the pathogens. However, an excess of these ROS is deleterious to the plant system. Along with altering cell structure, ROS cause a variety of physiological reactions in plants that lower plant yield. ROS also degrade proteins, enzymes, nucleic acids, and other substances. Plants have their own mechanisms to overcome excess ROS and maintain homeostasis. Microbes, especially endophytes, have been reported to maintain ROS homeostasis in both biotic and abiotic stresses by multiple mechanisms. Endophytes themselves produce antioxidant compounds and also induce host plant machinery to supplement ROS scavenging. The structured reviews on how endophytes play a role in ROS homeostasis under biotic stress were very meager, so an attempt was made to compile the recent developments in ROS homeostasis using endophytes. This review deals with ROS production, mechanisms involved in ROS signaling, host plant mechanisms in alleviating oxidative stress, and the roles of endophytes in maintaining ROS homeostasis under biotic stress.
Regulation of thymidylate synthase: an approach to overcome 5-FU resistance in colorectal cancer
Thymidylate synthase is the rate-limiting enzyme required for DNA synthesis and overexpression of this enzyme causes resistance to cancer cells. Long treatments with 5-FU cause resistance to Thymidylate synthase targeting drugs. We have also compiled different mechanisms of drug resistance including autophagy and apoptosis, drug detoxification and ABC transporters, drug efflux, signaling pathways (AKT/PI3K, RAS-MAPK, WNT/β catenin, mTOR, NFKB, and Notch1 and FOXM1) and different genes associated with resistance in colorectal cancer. We can overcome 5-FU resistance in cancer cells by regulating thymidylate synthase by natural products ( Coptidis rhizoma) , HDAC inhibitors, mTOR inhibitors, Folate antagonists, and several other drugs which have been used in combination with TS inhibitors. This review is a compilation of different approaches reported for the regulation of thymidylate synthase to overcome resistance in colorectal cancer cells. Graphical abstract
Concept of Hybrid Drugs and Recent Advancements in Anticancer Hybrids
Cancer is a complex disease, and its treatment is a big challenge, with variable efficacy of conventional anticancer drugs. A two-drug cocktail hybrid approach is a potential strategy in recent drug discovery that involves the combination of two drug pharmacophores into a single molecule. The hybrid molecule acts through distinct modes of action on several targets at a given time with more efficacy and less susceptibility to resistance. Thus, there is a huge scope for using hybrid compounds to tackle the present difficulties in cancer medicine. Recent work has applied this technique to uncover some interesting molecules with substantial anticancer properties. In this study, we report data on numerous promising hybrid anti-proliferative/anti-tumor agents developed over the previous 10 years (2011–2021). It includes quinazoline, indole, carbazole, pyrimidine, quinoline, quinone, imidazole, selenium, platinum, hydroxamic acid, ferrocene, curcumin, triazole, benzimidazole, isatin, pyrrolo benzodiazepine (PBD), chalcone, coumarin, nitrogen mustard, pyrazole, and pyridine-based anticancer hybrids produced via molecular hybridization techniques. Overall, this review offers a clear indication of the potential benefits of merging pharmacophoric subunits from multiple different known chemical prototypes to produce more potent and precise hybrid compounds. This provides valuable knowledge for researchers working on complex diseases such as cancer.
Role of biostimulants in mitigating the effects of climate change on crop performance
Climate change is a critical yield–limiting factor that has threatened the entire global crop production system in the present scenario. The use of biostimulants in agriculture has shown tremendous potential in combating climate change–induced stresses such as drought, salinity, temperature stress, etc. Biostimulants are organic compounds, microbes, or amalgamation of both that could regulate plant growth behavior through molecular alteration and physiological, biochemical, and anatomical modulations. Their nature is diverse due to the varying composition of bioactive compounds, and they function through various modes of action. To generate a successful biostimulatory action on crops under different parameters, a multi– omics approach would be beneficial to identify or predict its outcome comprehensively. The ‘ omics’ approach has greatly helped us to understand the mode of action of biostimulants on plants at cellular levels. Biostimulants acting as a messenger in signal transduction resembling phytohormones and other chemical compounds and their cross–talk in various abiotic stresses help us design future crop management under changing climate, thus, sustaining food security with finite natural resources. This review article elucidates the strategic potential and prospects of biostimulants in mitigating the adverse impacts of harsh environmental conditions on plants.
Reclamation of coal mine spoil and its effect on Technosol quality and carbon sequestration: a case study from India
A field study was carried out to assess the impact of revegetation on Technosol quality in the post-mining sites (Central Coalfield Limited, India). The study evaluated community structure, biodiversity, Technosol quality, and carbon (C) dynamics in the post-mining ecosystem (PME). The multivariate statistical tool was used to identify the key soil properties, and soil quality was evaluated by using Technosol quality index (TQI). One unreclaimed site (0 years) and four chronosequences revegetated coal mine sites (3, 7, 10, and 15 years) were studied and compared with an undisturbed forest as a reference site. Plant biodiversity indices [Shannon index of diversity (2.42) and Pielou’s evenness (0.97) and Patric richness (12)] were highest in 15-year-old revegetated sites. Soil physicochemical and biological properties were recovered with the revegetation age. Soil organic C (SOC) stock significantly increased from 0.75 Mg C ha −1 in 3 years to 7.60 Mg C ha −1 after 15 years of revegetation in top 15 cm of soils. Ecosystem C pool increased at a rate of 5.38 Mg C ha −1  year −1 . Soil CO 2 flux was significantly increased from 0.27 μmol CO 2  m −2  s −1 in unreclaimed sites to 3.19 μmol CO 2  m −2  s −1 in 15-year-old revegetated site. Principal component analysis (PCA) showed that dehydrogenase activity (DHA), available nitrogen (N), and silt content were the key soil parameters that were affected by reclamation. A 15-year-old Technosol had a greater TQI (0.78) compared to the control forest soils (0.64) that indicated the suitability of revegetation to recuperate soil quality in mining-degraded land and to increase C sequestration potential.
Chasmophyte associated stress tolerant bacteria confer drought resilience to chickpea through efficient nutrient mining and modulation of stress response
In the present study, ten (10) selected bacteria isolated from chasmophytic wild Chenopodium were evaluated for alleviation of drought stress in chickpea. All the bacterial cultures were potential P, K and Zn solubilizer. About 50% of the bacteria could produce Indole-3-acetic acid (IAA) and 1-aminocyclopropane-1-carboxylate (ACC) deaminase. The bacteria showed wide range of tolerance towards pH, salinity, temperature and osmotic stress. Bacillus paralicheniformis L38, Pseudomonas sp. LN75, Enterobacter hormachei subsp. xiangfengensis LJ89, B. paramycoides L17 and Micrococcus luteus LA9 significantly improved growth and nutrient (N, P, K, Fe and Zn) content in chickpea under water stress during a green house experiment conducted following a completely randomized design (CRD). Application of Microbacterium imperiale LJ10, B. stercoris LN74, Pseudomonas sp. LN75, B. paralicheniformis L38 and E. hormachei subsp. xiangfengensis LJ89 reduced the antioxidant enzymes under water stress. During field experiments conducted following randomized block design (RBD), all the bacterial inoculations improved chickpea yield under water stress. Highest yield (1363 kg ha −1 ) was obtained in plants inoculated with Pseudomonas sp. LN75. Pseudomonas sp. LN75, B. paralicheniformis L38 and E. hormachei subsp. xiangfengensis LJ89 have potential as microbial stimulants to alleviate the water stress in chickpea. To the best of our knowledge this is the first report of using chasmophyte associated bacteria for alleviation of water stress in a crop plant.
Resource Efficiency-Driven Consensus (REDC): A Machine Learning-Based Blockchain Framework for Healthcare IoT Systems
The increasing adoption of Internet of Things (IoT) devices in smart healthcare systems has revolutionized real-time data collection and processing, substantially improving healthcare delivery and operational efficiency. However, the sensitivity of medical data and the resource limitations of IoT devices demand blockchain solutions that are secure, lightweight, and scalable. This paper presents two core contributions: (1) Resource Efficiency-Driven Consensus (REDC), a machine learning–enhanced consensus protocol tailored for healthcare IoT networks, and (2) Dynamic Lightweight Hashing (DLH), a cryptographic algorithm designed for energy-constrained environments. REDC achieves up to 70% higher throughput, 43% Energy Efficiency (EE), and 25% lower latency compared to Proof of Elapsed Work and Luck (PoEWAL) in networks up to 100 nodes. DLH further enhances performance by reducing hash attempts and energy use while maintaining strong collision resistance across 100,000 trials. Together, REDC and DLH form a scalable and secure blockchain framework tailored for healthcare IoT.
Lightweight Proof of Game (LPoG): A Proof of Work (PoW)’s Extended Lightweight Consensus Algorithm for Wearable Kidneys
In healthcare, interoperability is widely adopted in the case of cross-departmental or specialization cases. As the human body demands multiple specialized and cross-disciplined medical experiments, interoperability of business entities like different departments, different specializations, the involvement of legal and government monitoring issues etc. are not sufficient to reduce the active medical cases. A patient-centric system with high capability to collect, retrieve, store or exchange data is the demand for present and future times. Such data-centric health processes would bring automated patient medication, or patient self-driven trusted and high satisfaction capabilities. However, data-centric processes are having a huge set of challenges such as security, technology, governance, adoption, deployment, integration etc. This work has explored the feasibility to integrate resource-constrained devices-based wearable kidney systems in the Industry 4.0 network and facilitates data collection, liquidity, storage, retrieval and exchange systems. Thereafter, a Healthcare 4.0 processes-based wearable kidney system is proposed that is having the blockchain technology advantages. Further, game theory-based consensus algorithms are proposed for resource-constrained devices in the kidney system. The overall system design would bring an example for the transition from the specialization or departmental-centric approach to data and patient-centric approach that would bring more transparency, trust and healthy practices in the healthcare sector. Results show a variation of 0.10 million GH/s to 0.18 million GH/s hash rate for the proposed approach. The chances of a majority attack in the proposed scheme are statistically proved to be minimum. Further Average Packet Delivery Rate (ADPR) lies between 95% to 97%, approximately, without the presence of outliers. In the presence of outliers, network performance decreases below 80% APDR (to a minimum of 41.3%) and this indicates that there are outliers present in the network. Simulation results show that the Average Throughput (AT) value lies between 120 Kbps to 250 Kbps.