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Abstract Background A significant overlap in the pathophysiological features of polycystic ovary syndrome (PCOS) and type 2 diabetes mellitus (T2DM) has been reported; and insulin resistance is considered a central driver in both. The expression and hepatic clearance of insulin and subsequent glucose homeostasis are mediated by TCF7L2 via Wnt signaling. Studies have persistently associated TCF7L2 genetic variations with T2DM, however, its results on PCOS are sparse and inconsistent. Methods We performed a comprehensive literature review of the data published till June 2024, on rs7903146, rs12255372, and PCOS in PubMed, Medline, the Cochrane Library, Google Scholar, Science Direct, Scopus, and Web of Science, followed by a meta-analysis to evaluate the association between these genetic variations and the PCOS risk. Using a random effects model, the pooled odds ratio (OR) and confidence intervals (95%CI) were computed using STATA statistical software. Results The genotypic data from 3052 controls and 2291 women with PCOS from ten published studies were analysed. The results indicated no cumulative association between the rs7903146 variant and PCOS risk in either the allelic (C vs. T: OR = 1.21; 95% CI: 0.96–1.47, p > 0.05) or genotypic models (CC vs. CT + TT: OR = 1.06; 95% CI: 0.90–1.23, p > 0.05). Similarly, the genetic variant rs12255372 was not associated with PCOS risk both in the allelic and the dominant inheritance model(p > 0.05). Unlike East Asians (MAF

Automatic voltage regulators (AVR) are designed to manipulate a synchronous generator’s voltage level automatically. Proportional integral derivative (PID) controllers are typically used in AVR systems to regulate voltage. Although advanced PID tuning methods have been proposed, the actual voltage response differs from the theoretical predictions due to modeling errors and system uncertainties. This requires continuous fine tuning of the PID parameters. However, manual adjustment of these parameters can compromise the stability and robustness of the AVR system. This study focuses on the online self-tuning of PID controllers called indirect design approach-2 (IDA-2) in AVR systems while preserving robustness. In particular, we indirectly tune the PID controller by shifting the frequency response. The new PID parameters depend on the frequency-shifting constant and the previously optimized PID parameters. Adjusting the frequency-shifting constant modifies all the PID parameters simultaneously, thereby improving the control performance and robustness. We evaluate the robustness of the proposed online PID tuning method by comparing the gain margins (GMs) and phase margins (PMs) with previously optimized PID parameters during parameter uncertainties. The proposed method is further evaluated in terms of disturbance rejection, measurement noise, and frequency response analysis during parameter uncertainty calculations against existing methods. Simulations show that the proposed method significantly improves the robustness of the controller in the AVR system. In summary, online self-tuning enables automated PID parameter adjustment in an AVR system, while maintaining stability and robustness.

Abstract A 37-year-old male patient with a past history of fluctuating hypertension and insulin-treated diabetes mellitus presented to our clinic with a 1-year history of sudden-onset cough, dyspnea, and frank hemoptysis. Examination showed asthenia, moderate anemia, uncontrolled blood pressure, and a past history of one admission for management of hemoptysis and cardiac failure. The evaluation showed mild anemia, azotemia, low ejection fraction, contrast-enhanced computed tomography (CECT) of the chest, and sputum suggestive of pulmonary hemorrhage. Investigation during current admission revealed proteinuria, left suprarenal mass on USG, and clear lung parenchyma on chest X-ray and CECT. Autoimmune workup for vasculitis was negative and 24-h urinary catecholamine levels were elevated with CECT abdomen confirming pheochromocytoma. His blood pressure was controlled and he underwent laparoscopic left adrenalectomy with confirmation on histopathology. Postoperatively he is doing well with minimal requirement of antihypertensive, and diabetes is controlled with diet and exercise only. This case highlights diffuse alveolar hemorrhage as a rare presentation of pheochromocytoma. This case also highlights that secondary cause of hypertension should always be ruled out in case of uncontrolled hypertension in young patients to prevent devastating complications.

Abstract Ginger, Zingiber officinale, is a medicinal herb widely used for its distinct flavor and medicinal properties. It contains various bioactive compounds, including zingerone, shogaols, gingerol saponin, polyphenols, and flavonoids, which confer anti‐inflammatory, antioxidant, and immunomodulatory effects. Ginger and its derivatives such as powder, essential oil, and active ginger extracts have been used as natural functional ingredients with health‐promoting and disease‐preventing properties. In recent studies, ginger derivatives have been tested in aquafeeds for their potential as safe herbal medicines. They have shown several benefits, acting as growth promoters and modulators of physiological and biochemical functions. Ginger has been found to improve growth performance, modulate immunity, and enhance disease resistance in fish. Its organic constituents exhibit potent anti‐stress, antibacterial, antiviral, and antiparasitic activities, thereby boosting the specific and nonspecific immunity of aquaculture fish. This review provides a comphrensive summary of studies exploring the effects of dietary ginger on various aspects of fish health including growth performance, blood parameters, immunity, disease resistance, gut morphology, antioxidant status, and molecular mechanisms. Furthermore, the review emphasizes the necessity of elucidating the specific bioactive compounds in ginger responsible for its biological functions and their mechanisms of action against infectious diseases in different fish species.

This research introduces the improved Archimedes optimization algorithm (IAOA) for data-driven modeling of continuous-time Hammerstein models with missing data. It addresses the limitations of the original Archimedes optimization algorithm (AOA) through two key modifications: rebalancing the exploration and exploitation phases and mitigating local optima trapping issues. The primary focus is on developing a novel data-driven approach for modeling continuous-time Hammerstein models, particularly in the presence of missing output data. Four levels of missing measurement data (5 %, 15 %, 35 %, and 50 %) were considered, with data points randomly replaced with zeros. Models were tested with both complete and missing output data to evaluate the robustness of the IAOA-based method. The proposed based method identified linear and nonlinear subsystem variables in a continuous-time Hammerstein model leveraging input and output data, validated through two practical experiments: a Twin Rotor System and an Electromechanical Positioning System. The performance was assessed by examining various factors, including the convergence curve of the fitness function and its statistical analysis, responses in the frequency and time domains, Wilcoxon's rank-sum test, and computational time. Across all experiments, the IAOA-based method demonstrated superior performance compared to AOA and other methods, including a hybrid approach combining the average multi-verse optimizer and sine cosine algorithm, particle swarm optimizer, the sine cosine algorithm, multi-verse optimizer and grey wolf optimizer. The findings showed that the proposed IAOA-based method delivered highly accurate and consistent solutions, proving it to be the most effective and reliable method compared to the others assessed.

In the face of growing global challenges in food security and increasing demand for sustainable protein sources, the aquaculture industry is undergoing a transformative shift through the integration of nanotechnology. This review paper explores the profound role of nanotechnology in aquaculture, addressing critical issues such as efficient feed utilization, disease management, and environmental sustainability. Nanomaterials are used to enhance nutritional content and digestibility of aquafeed, optimize fish growth and health, and improve disease prevention. Nanoparticle-based vaccines and drug delivery systems reduce antibiotic reliance, while nano sensors monitor water quality in real-time. Furthermore, nanotechnology has revolutionized infrastructure design, contributing to smart, self-regulating aquaculture systems. Despite its vast potential, challenges such as ethical considerations and long-term safety must be addressed. This paper highlights nanotechnology's transformative role in aquaculture, underscoring its potential to contribute significantly to global food security through enhanced productivity and sustainability.

The widespread use of dynamic systems has greatly simplified various human-operated tasks. However, the complex and nonlinear nature of these systems has posed challenges in determining their structure due to heavy reliance on modeling for theoretical and empirical purposes in academic and practical contexts. This challenge is particularly evident in the Hammerstein model, which is well-known for its recognition of structural nonlinearity. To address the limitations of uncovering an optimized continuous-time Hammerstein model, researchers have explored the practical application of the Augmented Sine Cosine Algorithm-Game Theoretic (ASCA-GT). By combining the Game Theoretic (GT) and Sine Cosine Algorithm (SCA), this hybrid approach aims to achieve a nonlinear position-updated process for improved exploration and exploitation, while effectively overcoming issues like local optima trapping. The performance of ASCA-GT was evaluated using 13 benchmark functions and mathematical scenarios, as well as the Twin-Rotor System (TRS) and Electro-Mechanical Positioning System (EMPS). The effectiveness of the proposed technique was assessed using Wilcoxon's rank test, which confirmed the superior performance of ASCA-GT compared to other metaheuristic optimization methods in determining the continuous-time Hammerstein model.

This paper sets pioneering research which investigates the parametric identification of thermoelectric modules (TEMs) through the employment of enhanced slime mould algorithm (ESMA). The proposed method incorporates a pair of modifications to the standard slime mould algorithm (SMA). Primary modification encloses computation of random average position between the slimes' current individual position and best individual position towards resolution of local optima issue. Subsequent modification then involves substitution of an exponential function to the existing tangent hyperbolic function within formula p of the standard SMA in enabling improved probability variants via the selection of updated equations. Competency of the proposed algorithm in generating the optimal parameters for TEMs was appraised based on 21 benchmarked design parameters, following the objective of root mean square error (RMSE) minimization between the temperature of both actual and estimated models. Acquired results which demonstrate lower values of RMSE and parameter deviation index against the standard SMA and other preceding algorithms such as particle swarm optimization, sine cosine algorithm, moth flame optimizer and ant lion optimizer ultimately verified ESMA’s efficacy as an effective approach for accurate model identification.

Abstract In the present study, the effect of mild to high-temperature regimes on the quasi-static and dynamic tensile behaviours of Barakar sandstone from the Jharia coal mine fire region has been experimentally investigated. The experimental work has been performed on Brazilian disk specimens of Barakar sandstone, which are thermally treated up to 800 °C. The quasi-static and dynamic split tensile strength tests were carried out on a servo-controlled universal testing machine and Split Hopkinson Pressure Bar (SHPB), respectively. Microscopic and mineralogical changes were studied through a petrographic investigation. The experimental results suggest the prevalence of both, static and dynamic loading scenarios after 400 °C. Up to 400 °C, the quasi-static and dynamic tensile strengths increased due to the evaporation of water, which suggests a strengthening effect. However, beyond 400 °C, both strengths decreased significantly as newly formed thermal microcracks became prevalent. The dynamic tensile strength exhibits strain rate sensitivity up to 400 °C, although it shows a marginal decline in this sensitivity beyond this temperature threshold. The Dynamic Increase Factor (DIF) remained constant up to 400 °C and slightly increased after 400 °C. Furthermore, the characteristic strain rate at which the dynamic strength becomes twice the quasi-static strength remains consistent until reaching 400 °C but steadily decreases beyond this temperature. This experimental study represents the first attempt to validate the Kimberley model specifically for thermally treated rocks. Interestingly, the presence of water did not have a significant impact on the failure modes up to 400 °C, as the samples exhibited a dominant tensile failure mode, breaking into two halves with fewer fragments. However, as temperature increased, the failure behaviours became more complex due to the combined influence of thermally induced microcracks and the applied impact load. Cracks initially formed at the centre and subsequently, multiple shear cracks emerged and propagated in the loading direction, resulting in a high degree of fragmentation. This study also demonstrates that shear failure is not solely dependent on the loading rate but can also be influenced by temperature, further affecting the failure mode of the sandstone.

IntroductionIndian senna (Senna alexandrina Mill.) (formerly Cassia angustifolia Vahl.) is an important medicinal plant of the family Fabaceae. The leaves and pods of Indian senna yield sennosides and rhein-based laxative. Adulteration of Indian senna is a serious issue as with most of the medicinal plants used in the Indian systems of traditional medicine. The bulk of dried leaves and pods of morphologically related species, such as Cassia fistula, Senna occidentalis, Senna sophera, and Senna tora, is usually mixed with those of the Indian senna, and the admixture is used in laxative-based formulations. The present investigation is a modest attempt at developing species-specific start codon targeted (SCoT) polymorphism- and CAAT-box-derived polymorphism (CBDP)-based sequence-characterized amplified region (SCAR) markers for the identification and authentication of Indian senna and four adulterant species (C. fistula, S. occidentalis, S. sophera, and S. tora species).MethodsIn this study, genomic DNA extracted from 44 accessions of Indian senna and four adulterant species was subjected to SCoT and CBDP PCR. The polymorphic amplicons were identified, eluted, ligated, and transformed into Escherichia coli DH5 α strain. PCR, restriction analysis, and DNA sequencing confirmed the transformed recombinant plasmid clones.ResultsPost-sequencing, the sequence of the primary SCoT and CBDP primers was analyzed and extended into the unique signature sequence of the concerned accessions. This resulted in development of one SCoT-44- and two CBDP-25-based SCARs. SCoT-44 SCAR produced a signature amplicon of 287 bp for accession DCA120, and CBDP-25 SCAR yielded signature amplicons of 575 and 345 bp for accessions DCA13 and DCA119, respectively. The developed SCAR markers were validated across 48 samples (44 accessions of Indian senna and 4 adulterant species) and produced distinct amplicons in Indian senna only, while no such amplicon was observed in the other four adulterant species.DiscussionThe information generated using these markers have been faithfully converted to single-locus, unequivocal, highly reproducible, and informative sequence-based SCAR markers. These markers will enable discrimination of individual plants on the basis of unique sequence-specific amplicons, which could be used as diagnostic markers to settle issues pertaining to the true identity of Indian senna.

Reproductive processes in fishes are regulated by the hypothalamic-pituitary-gonadal (HPG) axis, much like in tetrapods. Within this system, Gonadotropin-Releasing Hormone (GnRH) is released by the hypothalamus, binding to GnRH receptors in the pituitary gland and stimulating the secretion of gonadotropin hormones. The current study aimed to analyze the GnRH receptor in Oncorhynchus mykiss (rainbow trout) using a computational and structural biology approach. The GnRH receptor gene of O. mykiss comprises a nucleotide sequence of 1707 base pairs with an open reading frame of 1251 base pairs, which is responsible for encoding 416 amino acids. It was found that the GnRH receptor contains leucine (L) as the most abundant amino acid. The secondary structure revealed that alpha helices constitute the largest percentage (36 %) with 153 residues, followed by extended strands with 77 residues (17.51 %). The GnRH receptor contains 26 negatively charged and 37 positively charged amino acid residues. The highest hydrophilicity was observed for lysine (K) at position 310, with a value of −3.900, while the highest hydrophobicity was found for leucine (L) at position 290, with a value of 3.80. Molecular docking analysis showed that the most favorable binding energy was observed for Gestrinone (−7.8 kcal/mol). Gestrinone was found to form hydrogen bonds with MET160, LUE245, LUE62, TYR216, and GLN209 residues of GnRH. Moreover, molecular dynamics revealed that the complexes form robust and enduring connections, indicating their structural integrity throughout the simulation. The results of this study provide insights into the protein modeling, molecular docking, and virtual screening of antagonist ligands against the GnRH receptor. Additionally, they may significantly aid in the advancement and improvement of therapeutic strategies targeted at treating various fish reproductive dysfunctions.

The increasing global population drives a rising demand for food, particularly fish as a preferred protein source, straining capture fisheries. Overfishing has depleted wild stocks, emphasizing the need for advanced aquaculture technologies. Unlike agriculture, aquaculture has not seen substantial technological advancements. Artificial Intelligence (AI) tools like Internet of Things (IoT), machine learning, cameras, and algorithms offer solutions to reduce human intervention, enhance productivity, and monitor fish health, feed optimization, and water resource management. However, challenges such as data collection, standardization, model accuracy, interpretability, and integration with existing aquaculture systems persist. This review explores the adoption of AI techniques and tools to advance the aquaculture industry and bridge the gap between food supply and demand.

Enhancing the root traits through selection and breeding efforts can significantly improve the acquisition of soil resources, consequently boosting crop production in marginal environments. Cowpea is one of the important legume crops in arid and semi-arid regions, grown mostly in marginal environments under drought conditions. The roots play a crucial role in plant's ability to survive and adapt under such water stressed conditions. The understanding of cowpea genetic architecture related to root system architecture (RSA) remains limited due to difficulties in accurately measuring root traits. In the present study, a set 110 diverse mini-core collection of cowpea from IITA, Nigeria was evaluated for thirteen (13) different root-shoot traits under controlled conditions in the green house. Significant variation was recorded for all the root traits in the mini-core set. Most promising genotype for most of the root traits, viz., root volume, dry root weight, root biomass density and tap root diameter were identified. The correlation analysis revealed significant positive association (p < 0.001) of root weight with shoot weight (0.85), root volume (r = 0.61), and tap root diameter (0.56). In the principal component analysis (PCA), first three principal components explained the variance of 64.31%, with PC1 contributing 44.43%, PC2 10% and PC3 9.88%. All the root-shoot traits contribute positive variation to PC1especially dry root weight and dry shoot weight that had high component loading and in PC2 root shoot ratio had high loading. The root-shoot trait data was used with 6,574 good quality SNP data for discovery of genes/QTLs/marker-trait associations for root traits. The analysis of results of genome wide association study (GWAS) led to the identification of 52 unique SNPs associated significantly (p < 10−4) with thirteen root-shoot traits. Highest number of SNPs was found associated with root weight and chromosome 5 was identified as SNP hotspot for harboring majority of significant SNPs. We further delve candidate genes within 50 kb around the identified SNP that led to the identification of several important candidate genes underlying genomic regions responsible for root-shoot traits in cowpea. The promising cowpea genotypes for root traits and promising MTAs/candidate genes will prove useful in cowpea improvement programs including improvement of drought tolerance in cowpea.

Although various optimization algorithms have been widely employed in multiple applications, the traditional Archimedes optimization algorithm (AOA) has presented imbalanced exploration with exploitation phases and the propensity for local optima entrapment. Therefore, this article identified various continuous-time Hammerstein models based on an improved Archimedes optimization algorithm (IAOA) to address these concerns. The proposed algorithm employed two principal modifications to mitigate these issues and enhance identification accuracy: (i) exploration and exploitation phase recalibrations using a revised density decreasing factor and (ii) local optima entrapment alleviation utilizing safe experimentation dynamics. Various advantages were observed with this proposed algorithm, including a lower number of coefficient criteria, improved accuracy in Hammerstein model identification, and diminished processing demands by reducing gain redundancy between nonlinear and linear subsystems. This proposed algorithm also discerned linear and nonlinear subsystem variables within a continuous-time Hammerstein model utilizing input and output data. The process was evaluated using a numerical example and two practical experiments [twin-rotor system (TRS) and electro-mechanical positioning system (EMPS)]. Several parameters were then analyzed, such as the convergence curve of the fitness function, frequency and time domain-related responses, variable deviation index, and Wilcoxon's rank-sum test. Consequently, the proposed algorithm reliably determined the most optimal design variables during numerical trials, demonstrating 54.74 % mean fitness function and 75.34 % variable deviation indices enchantments compared to the traditional AOA. Improved mean fitness function values were also revealed in the TRS (11.63 %) and EMPS (69.63 %) assessments, surpassing the conventional algorithm. This proposed algorithm produced solutions with superior accuracy and consistency compared to various established metaheuristic strategies, including particle swarm optimizer, grey wolf optimizer, multi-verse optimizer, AOA, and a hybrid optimizer (average multi-verse optimizer-sine-cosine algorithm).

Abstract The cloning and characterization of the complete coding sequence of the Clarias magur SRD5A1 (CmSRD5A1) gene, which encodes an enzyme responsible for regulating steroid levels by converting testosterone into 5α-dihydrotestosterone (DHT), have been successfully achieved. DHT plays a vital role in enabling the complete expression of testosterone's actions in neuroendocrine tissues. The ORF of the full-length cDNA sequence of SRD5A1 was 795 bp, translating into 265 amino acids, with a total length of 836 bp including UTRs. Like other vertebrates, the signal peptide analysis revealed that SRD5A1 is a non-secretory protein, and hydropathy profiles indicated that it is hydrophobic in nature. The 3D structure of CmSRD5A1 sequence generated above was predicted using highly accurate AlphaFold 2 in Google Colab online platform. CmSRD5A1 contains seven transmembrane helices connected by six loops, with the N-termini located on the periplasmic side and C-termini on the cytosolic side. Structural superimposition with known bacterial and human SRD5As showed very high structural similarity. The electrostatic potential calculation and surface analysis of CmSRD5A1 revealed the presence of a large cavity with two openings one highly electropositive towards the cytosolic side and another relatively neutral towards the transmembrane region. The structural comparison revealed that the electropositive side of the cavity should bind to NADPH and the steroid hormone in the hydrophobic environment. Polar residues binding to NADPH are highly conserved and the same as known strictures. The conserved residues involved in hydrogen bonding with the ketone group at C-3 in the steroids hence fevering Δ4 double-bond reduction are identified as E66 and Y101. Our findings showed that SRD5A1 expression was lower during the spawning phase than the preparatory phase in female fish, while the administration of Ovatide (a GnRH analogue) resulted in up-regulation of expression after 6 h of injection in the ovary. In males, the lowest expression was observed during the preparatory phase and peaked at 16 h post- Ovatide injection in the testis. The expression of SRD5A1 in the brain of female fish was slightly higher during the Ovatide stimulation phase than the spawning phase. This study represents the first report on the cloning and characterization of the full-length cDNA of SRD5A1 in Indian catfish.

Background: Organophosphorus insecticides are considered one of the commonest causes of morbidity and mortality due to poisoning worldwide. Severe organophosphorus poisoning can lead to multiple sometimes lethal metabolic and haematological abnormalities. METHODS: A total of 141 OP poisoning patients were admitted during the study period and their blood samples were collected on admission and analysed for the biochemical abnormalities. RESULTS: Out of 141 patients 76 were males (53.9%) and 65 were females (46.1%). Bradycardia with Pulse rate of less than 60 was seen in in 21 patients (14.7). Hypoxemia with oxygen saturation of less than 94% was seen in 32 (22.7%). leucocytosis with TLC o 11000 or more was seen in 19 patients (13.5%).101 patients (83.5%) had low serum choline esterase levels less than 1.5kU/L. Hypokalaemia with K+ of less than 3.5 was seen in 16 patients (9.9%). Five patients died out of 141 (3.5%). Hypoxemia Spo2 of less than 90% was seen in 3 (60%) patients who died and hypoglycaemia with blood glucose of less than 70mg/dl was seen in 2 out of 5 Patients (40%) CONCLUSIONS: low choline esterase levels less than 1.5kU/L was the most common abnormality indicating severe poisoning followed by hypoxemia. Both Hypoxemia and low acetylcholine esterase levels are bad prognostic signs and result in high mortality in organophosphorus poisoning. Keywords: Organophosphorus Poisoning, Hypoxemia, choline esterase, Hypokalaemia, Hypoglycaemia.

The fractional-order proportional-integral-derivative (FOPID) controller stands as a widely embraced choice for the task of automatic voltage regulation (AVR) when it comes to maintaining the voltage output of synchronous generators. Nevertheless, fine-tuning the FOPID controller presents a formidable challenge, mainly because it possesses five tuning gains, in contrast to the conventional PID controller, which has three gains. Consequently, this paper introduces a novel tuning tool tailored to the AVR system by utilizing the marine predators algorithm (MPA). To gauge the effectiveness of the proposed approach, two key evaluation criteria are employed: step response analysis and trajectory tracking analysis. The results of this research reveal that the MPA-FOPID controller demonstrates exceptional performance criteria, notably enhancing the AVR transient response in comparison to other FOPID controllers optimized through recent metaheuristic algorithms.

The integration of photovoltaic (PV) systems into traditional power grids introduces significant challenges in maintaining system stability, particularly in multi-area power systems. This study proposes a novel approach to load frequency control (LFC) in a two-area power system, where one area is powered by a PV grid and the other by a thermal generator. To enhance system performance, a cascaded control strategy combining a fractional-order proportional–integral (FOPI) controller and a proportional–derivative with filter (PDN) controller, FOPI(1+PDN), is introduced. The controller parameters are optimized using the spider wasp optimizer (SWO). Extensive simulations are conducted to validate the effectiveness of the SWO-tuned FOPI(1+PDN) controller. The proposed method demonstrates superior performance in reducing frequency deviations and tie-line power fluctuations under various disturbances. The results are compared against other advanced optimization algorithms, each applied to the FOPI(1+PDN) controller. Additionally, this study benchmarks the SWO-tuned controller against recently reported control strategies that were optimized using different algorithms. The SWO-tuned FOPI(1+PDN) controller demonstrates superior performance in terms of faster response, reduced overshoot and undershoot, and better error minimization.

The integration of sensor technology and automated analytics in wearable devices marks a significant advancement in sports science, aiming to proactively prevent injuries and optimize athletic performance. This paper delves into the application of advanced sensor systems and automated data analysis tools in the realm of athletics. These wearables, equipped with a multitude of sensors, continuously monitor an athlete's physiological and biomechanical data, including heart rate, muscle activity, and movement dynamics. The automated processing of this data through machine learning algorithms enables real-time insights and predictive analytics, offering a novel approach to injury prevention. By analyzing the intricate patterns of an athlete's performance metrics, these sensor-augmented wearables facilitate a data-driven strategy for reducing risks of soft-tissue and heat-related injuries. This technology empowers coaches and athletes with actionable insights, fostering a safer and more efficient training environment. Our exploration showcases the transformative impact of sensor-enhanced wearables and automated analytics in elevating the standards of injury prevention and performance optimization in sports.

In this study, we discuss how Wireless Sensor Networks (WSN) are susceptible to malicious assaults from malfunctioning nodes, which jeopardise the security of data transmission in crucial applications. We use a Convolutional Neural Network coupled with Fuzzy Logic (CNN-FL) for improved deep learning, introducing a unique method, effectively identifying and categorizing trustworthy and malicious nodes. This is combined with a routing strategy enhanced by the Neuro Genetic Optimizer (NGO), built on the LEACH routing protocol and based on a Roulette wheel selection mechanism. The WSN's lifetime is increased by our suggested routing method, which not only provides safe data transmission but also dramatically reduces latency and energy consumption. Simulation findings show that our technique outperforms current protocols as ASNGSRA, DMCNN, and FRCSROD in terms of packet delivery ratio, energy economy, and latency analysis.

This paper presents an improved Sine Cosine Algorithm (ISCA) towards optimization of a DC-DC buck converter with employment of the proportional-integral-derivative (PID) controller. Limitations of the conventional Sine Cosine Algorithm (SCA) was hereby overcome through two separate alterations which pioneered a synergized employment of nonlinear equation to instrumental mechanism in revising the average location. Primary alteration tackled the issue of local optima by proposed instrumental function towards revision of average location. Secondary alteration then coordinated disproportional exploration and exploitation phases of the conventional SCA by application of a nonlinear equation against the algorithm's decreasing position-updated mechanism. Robustness of the proposed ISCA-PID approach was studied against preceding algorithm-based PID for DC-DC buck converter with respect to their step response, statistics regarding the analyzed objective function, time-domain integral-error performance, reaction to frequency, and resistance to disturbance and parametric uncertainties. Generated findings subsequently uncovered overshadowing efficacy of the proposed method over its algorithmic predecessors towards exceptionally enhanced transitory response of the DC-DC buck converter.

Conventionally, researchers have favored the model-based control scheme for controlling gantry crane systems. However, this method necessitates a substantial investment of time and resources in order to develop an accurate mathematical model of the complex crane system. Recognizing this challenge, the current paper introduces a novel data-driven control scheme that relies exclusively on input and output data. Undertaking a couple of modifications to the conventional marine predators algorithm (MPA), random average marine predators algorithm (RAMPA) with tunable adaptive coefficient to control the step size ( CF ) has been proposed in this paper as an enhanced alternative towards fine-tuning data-driven multiple-node hormone regulation neuroendocrine-PID (MnHR-NEPID) controller parameters for the multi-input–multi-output (MIMO) gantry crane system. First modification involved a random average location calculation within the algorithm’s updating mechanism to solve the local optima issue. The second modification then introduced tunable CF that enhanced search capacity by enabling users’ resilience towards attaining an offsetting level of exploration and exploitation phases. Effectiveness of the proposed method is evaluated based on the convergence curve and statistical analysis of the fitness function, the total norms of error and input, Wilcoxon’s rank test, time response analysis, and robustness analysis under the influence of external disturbance. Comparative findings alongside other existing metaheuristic-based algorithms confirmed excellence of the proposed method through its superior performance against the conventional MPA, particle swarm optimization (PSO), grey wolf optimizer (GWO), moth-flame optimization (MFO), multi-verse optimizer (MVO), sine-cosine algorithm (SCA), salp-swarm algorithm (SSA), slime mould algorithm (SMA), flow direction algorithm (FDA), and the formally published adaptive safe experimentation dynamics (ASED)-based methods.

Aquaculture, a rapidly expanding global food sector faces challenges like pathogenic infections, water quality management and sustainability. Silver nanoparticles (AgNPs) have emerged as promising tools in aquaculture due to their antimicrobial, antiviral and antifungal properties. AgNPs offer alternatives to traditional antimicrobial agents. Their small size and unique physicochemical properties enhance antimicrobial activity, effectively inhibiting pathogen growth and reducing disease incidence in aquatic organisms. Additionally, AgNPs can improve water quality by catalyzing the removal of pollutants, heavy metals and nutrients, reducing environmental impacts. Despite their potential benefits, several challenges and knowledge gaps exist in the utilization of AgNPs in aquaculture. Addressing challenges related to regulation, sustainability and environmental impact will be crucial for realizing their full potential in the industry. Therefore, the present review aims to provide insight into the role of AgNPs, its challenges in aquaculture and also highlights key areas for future research.

The current study reports the potential of chitosan nanoparticles for the efficient delivery of hypothalamic hormonal analogue in Labeo rohita, aiming to improve reproductive performance. Here salmon gonadotropin-releasing hormone analogue (sGnRH-a) was conjugated with chitosan nanoparticles (ChN-sGnRH-a) to evaluate its efficiency in enhancing the reproductive gene expression, hormones as well as the overall reproductive output in L. rohita. A total of 54 pairs of brooders were selected and divided into six treatments viz; C0: Negative Control (fish injected with bare chitosan nanoparticles), C: Positive Control (fish injected with Gonopro-FH®, a commercially available inducing hormone, at a dose of 0.2 ml/kg body weight of fish), T1: fish injected with ChN-sGnRH-a at a dose of 0.2 ml/kg, T2: T1 + 10 mg/ml domperidone, T3: fish injected with ChN-sGnRH-a at a dose of 0.1 ml/kg, T4: T3 + 10 mg/ml domperidone. In T2 and T4 treatments, serum hormones, Testosterone (T); Estradiol (E2); Vitellogenin (Vtg); and 17α, 20β-dihydroxyprogesterone (17α, 20β-DHP) showed the sustained elevation. The means of reproductive traits like fecundity, fertilization rate, pseudo-gonadosomatic index and spawning rate were significantly (P

Understanding the role of the mitogen-activated protein kinases (MAPKs) signalling pathway is essential in advancing treatments for neurodegenerative disorders like Alzheimer's. In this study, we investigate in-silico techniques involving computer-based methods to extract the MAPK1 sequence. Our applied methods enable us to analyze the protein's structure, evaluate its properties, establish its evolutionary relationships, and assess its prevalence in populations. We also predict epitopes, assess their ability to trigger immune responses, and check for allergenicity using advanced computational tools to understand their immunological properties comprehensively. We apply virtual screening, docking, and structure modelling to identify promising drug candidates, analyze their interactions, and enhance drug design processes. We identified a total of 30 cell-targeting molecules against the MAPK1 protein, where we selected top 10 CTL epitopes (PAGGGPNPG, GGGPNPGSG, SAPAGGGPN, AVSAPAGGG, AGGGPNPGS, ATAAVSAPA, TAAVSAPAG, ENIIGINDI, INDIIRTPT, and NDIIRTPTI) for further evaluation to determine their potential efficacy, safety, and suitability for vaccine design based on strong binding potential. The potential to cover a large portion of the world's population with these vaccines is substantial—88.5 % for one type and 99.99 % for another. In exploring the molecular docking analyses, we examined a library of compounds from the ZINC database. Among them, we identified twelve compounds with the lowest binding energy. Critical residues in the MAPK1 protein, such as VAL48, LYS63, CYS175, ASP176, LYS160, ALA61, LEU165, TYR45, SER162, ARG33, PRO365, PHE363, ILE40, ASN163, and GLU42, are pivotal for interactions with these compounds. Our result suggests that these compounds could influence the protein's behaviour. Moreover, our docking analyses revealed that the predicted peptides have a strong affinity for the MAPK1 protein. These peptides form stable complexes, indicating their potential as potent inhibitors. This study contributes to the identification of new drug compounds and the screening of their desired properties. These compounds could potentially help reduce the excessive activity of MAPK1, which is linked to Alzheimer's disease.

Background: Vitamin D has important role in regulating various metabolic processes in the body including calcium metabolism. Fetuses and neonates are dependent on their mothers to get adequate supply of Vitamin D. Maintaining adequate maternal Vitamin D levels may be highly beneficial for their fetuses and the babies. Aims and Objectives: The aim of the study was to find a correlation, if any, between maternal Vitamin D status and neonatal Vitamin D levels and delayed neonatal hypocalcemia. Materials and Methods: Fifty mother infant pairs with neonatal late onset hypocalcemia were included in the study. Detailed clinical history along with simultaneous maternal and neonatal blood samples were taken for estimation of calcium, phosphorus, parathormone (intact), and Vitamin D levels. Results: Mean maternal and neonatal serum Vitamin D (25-OH Vitamin D) levels were 19.5±7.5 and 15±8.5, respectively. There was a statistically significant correlation between maternal and neonatal Vitamin D levels (P=0.001). There was also a direct correlation between low maternal Vitamin D levels and delayed hypocalcemia in neonates (P=0.048). Mean maternal and neonatal serum calcium levels were 9±1.5 mg/dl and 6.2±0.4 mg/dl, respectively. There was no significant statistical correlation between the two (P>0.05). Conclusion: Maternal Vitamin D level appears to be an important determinant of neonatal Vitamin D and serum calcium levels.

Background: Unlike COVID 19 lockdown, very little is known about the impact of non-COVID 19 lockdown and two lockdowns (post abrogation of article 370 and post COVID 19) in series on health-care delivery system. Aims and Objectives: The aim of the study was to look for the impact of two lockdowns, separately and in combination, on health-care delivery system. Materials and Methods: Data of patients visiting the pediatric outpatient department, pattern of hospital admissions and patient outcomes 1 month and 6 months before and after two lockdowns were recorded and compared within a lockdown and with each other. Results: Fall in Outpatient visits and its persistence even after 6 months was more pronounced for post COVID 19 Lockdown or lockdown 2 (–73%VS–43% and +195VS–61%). There was a statistically significant difference between admissions rates 1 month before and after lockdown 1 (post article 370 abrogation) as well as 1 month before and after lockdown 2 (P= 0.001; P< 0.0001). For the same time period, admission rates were significantly different for respiratory and gastrointestinal illnesses during the two lockdowns (

This study analyses the local microclimate information to discover the ideal Agrivoltaic system tilt-orientation angles and the influence of crops on energy production. The study’s objectives are twofold: (1) to provide a comprehensive method for determining the ideal tilt-orientation angles of PV modules that would both match the demands of crop-light requirements and optimize the energy output, and (2) to develop a mathematical model that considers the integration of crops within the AVS when projecting energy output. The simulation utilized a mix of PV tilt angle 0°-90° with orientation 0°-359° and hourly local meteorological data over one year. The study’s findings showed that local microclimate data can be used to anticipate the tilt-orientation angle of PV modules to fulfil crop-light demand. The maximum solar irradiance collected on the PV module is 1819 kW/m2/year at a tilt angle of 8° and orientation of 187°. In comparison, 40.92% of light reduction is observed below the same combination. Furthermore, it was discovered that cultivation of Andrographis paniculata using the same combination produced higher yields than cultivation in open areas. Next, AVS installation also reduces the temperature of the PV module by 1.28 °C and increases the efficiency of the PV module by approximately 0.82%. Following that, the LER value for AVS recorded at 2.17. In conclusion, this AVS model offers enormous potential to predict ideal PV tilt-orientation and assessing the effect of crops on energy output.

BackgroundA clear understanding of the anthropometric and sociodemographic risk factors related to BMI and hypertension categories is essential for more effective disease prevention, particularly in India. There is a paucity of nationally representative data on the dynamics of these risk factors, which have not been assessed among healthy reproductive-age Indian women. ObjectiveThis cross-sectional polycystic ovary syndrome (PCOS) task force study aimed to assess the anthropometric and sociodemographic characteristics of healthy reproductive-age Indian women and explore the association of these characteristics with various noncommunicable diseases. MethodsWe conducted a nationwide cross-sectional survey from 2018 to 2022 as part of the Indian Council of Medical Research–PCOS National Task Force study, with the primary aim of estimating the national prevalence of PCOS and regional phenotypic variations among women with PCOS. A multistage random sampling technique was adopted, and 7107 healthy women (aged 18-40 years) from 6 representative geographical zones of India were included in the study. The anthropometric indices and sociodemographic characteristics of these women were analyzed. Statistical analysis was performed to assess the association between exposure and outcome variables. ResultsOf the 7107 study participants, 3585 (50.44%) were from rural areas and 3522 (49.56%) were from urban areas. The prevalence of obesity increased from 8.1% using World Health Organization criteria to 40% using the revised consensus guidelines for Asian Indian populations. Women from urban areas showed higher proportions of overweight (524/1908, 27.46%), obesity (775/1908, 40.62%), and prehypertension (1008/1908, 52.83%) categories. A rising trend of obesity was observed with an increase in age. Women aged 18 to 23 years were healthy (314/724, 43.4%) and overweight (140/724, 19.3%) compared with women aged 36 to 40 years with obesity (448/911, 49.2%) and overweight (216/911, 23.7%). The proportion of obesity was high among South Indian women, with 49.53% (531/1072) and 66.14% (709/1072), using both World Health Organization criteria and the revised Indian guidelines for BMI, respectively. BMI with waist circumference and waist-to-height ratio had a statistically significant linear relationship (r=0.417; P

Summary: Background: The hormonal profile varies considerably with age, gender, ethnicity, diet or physiological state of an individual. Limited population-specific studies have studied the variations in hormonal parameters among apparently healthy women. We aimed to analyse the biological reference interval for various hormonal parameters in the reproductive-aged healthy Indian women. Methods: Out of 3877 participants that were clinically evaluated, 1441 subjects were subjected to laboratory investigations. All participants underwent a detailed clinical, biochemical and hormonal profiling. The hormone analysis was carried out at a single centre using a uniform methodology. Among the participants evaluated for biochemical and hormonal parameters, subjects that presented any abnormal profile or had incomplete investigations (n = 593) were excluded for further analysis. Findings: The mean age (±SD) of the subjects retained in the final analysis (n = 848) was 29.9 (±6.3) years. In the present study, the biological reference interval (2.5th–97.5th centile) observed were: serum T4: μg/dL (5.23–12.31), TSH: μg/mL (0.52–4.16) and serum prolactin: ng/mL (5.13–37.35), LH: mIU/mL (2.75–20.68), FSH: mIU/mL 2.59–15.12), serum total testosterone: ng/mL (0.06–0.68), fasting insulin: mIU/mL (1.92–39.72), morning cortisol: μg/dL (4.71–19.64), DHEAS:μg/dL (50.61–342.6) and SHBG: nmol/L (21.37–117.54). Unlike T4, TSH, LH, and E2, the biological reference interval for prolactin, FSH, testosterone, C-peptide insulin and DHEAS varied when the subjects were stratified by age (p

Abstract Chickpea is the most important nutrient-rich grain legume crop in the world. A diverse core set of 147 chickpea genotypes was genotyped with a Axiom(®)50K CicerSNP array and trait phenotyped in two different environments for four seed micronutrients (Zn, Cu, Fe and Mn). The trait data and high-throughput 50K SNP genotypic data were used for the genome-wide association study (GWAS). The study led to the discovery of genes/QTLs for seed Zn, Cu, Fe and Mn, concentrations in chickpea. The analysis of seed micronutrient data revealed significant differences for all four micronutrient concentrations (P ≤ 0.05). The mean concentrations of seed Zn, Cu, Fe and Mn pooled over the 2 years were 45.9 ppm, 63.8 ppm 146.1 ppm, and 27.0 ppm, respectively. The analysis of results led to the identification of 35 SNPs significantly associated with seed Zn, Cu, Fe and Mn concentrations. Among these 35 marker-trait associations (MTAs), 5 were stable (consistently identified in different environments), 6 were major (explaining more than 15% of the phenotypic variation for an individual trait) and 3 were both major and stable MTAs. A set of 6 MTAs, MTAs (3 for Mn, 2 for Fe, and 1 for Cu) reported by us during the present study have been also reported in the same/almost same genomic regions in earlier studies and therefore declared as validated MTAs. The stable, major and validated MTAs identified during the present study will prove useful in future chickpea molecular breeding programs aimed at enhancing the seed nutrient density of chickpea.

Background: With the rapid development of the genomic sequence data for the Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its variants Delta (B.1.617.2) and Omicron (B.1.1.529), it is vital to successfully identify mutations within the genome. Objective: The main objective of the study is to investigate the full-length genome mutation analysis of 157 SARS-CoV-2 and its variant Delta and Omicron isolates. This study also provides possible effects at the structural level to understand the role of mutations and new insights into the evolution of COVID-19 and evaluates the differential level analysis in viral genome sequence among different nations. We have also tried to offer a mutation snapshot for these differences that could help in vaccine formulation. This study utilizes a unique and efficient method of targeting the stable genes for the drug discovery approach. Methods: Complete genome sequence information of SARS-CoV-2, Delta, and Omicron from online resources were used to predict structure domain identification, data mining, and screening; employing different bioinformatics tools. BioEdit software was used to perform their genomic alignments across countries and a phylogenetic tree as per the confidence of 500 bootstrapping values was constructed. Heterozygosity ratios were determined in-silico. A minimum spanning network (MSN) of selected populations was determined by Bruvo's distance role-based framework. Results: Out of all 157 different strains of SARS-CoV-2 and its variants, and their complete genome sequences from different countries, Corona nucleoca and DUF5515 were observed to be the most conserved domains. All genomes obtained changes in comparison to the Wuhan-Hu-1 strain, mainly in the TRS region (CUAAAC or ACGAAC). We discovered 596 mutations in all genes, with the highest number (321) found in ORF1ab (QHD43415.1), or TRS site mutations found only in ORF7a (1) and ORF10 (2). The Omicron variant has 30 mutations in the Spike protein and has a higher alpha-helix shape (23.46%) than the Delta version (22.03%). T478 was also discovered to be a prevalent polymorphism in Delta and Omicron variations, as well as genomic gaps ranging from 45 to 65aa. All 157 sequences contained variations and conformed to Nei's Genetic distance. We discovered heterozygosity (Hs) 0.01, mean anticipated Hs 0.32, the genetic diversity index (GDI) 0.01943989, and GD within population 0.01266951. The Hedrick value was 0.52324978, the GD coefficient was 0.52324978, the average Hs was 0.01371452, and the GD coefficient was 0.52324978. Among other countries, Brazil has the highest standard error (SE) rate (1.398), whereas Japan has the highest ratio of Nei's gene diversity (0.01). Conclusions: The study's findings will assist in comprehending the shape and kind of complete genome, their streaming genomic sequences, and mutations in various additions of SARS-CoV-2, as well as its different variant strains like Omicron. These results will provide a scientific basis to design the vaccines and understand the genomic study of these viruses.

Small-scale third-party accessories vendors face numerous challenges such as (i) warranty period covered for sensitive product, (ii) malicious induction, and (iii) extract root cause of product failure after customer experienced in the real time usage. Therefore, an advanced industrial environment is necessary to resolve these limitations. It offers strong security levels as well as intelligent root cause detection over failure. In this work, propose a blockchain-based internet of things (IoT) architecture for industry 4.0, which includes a voting decision mechanism for IoT device authentication and fault classification based on device and product trust values, respectively. These values are regularly updated in the historical trust value and machinery database for every successful product transaction and identify a new failure cause to set feature for next iteration set from the defective industrial cloud database. The analytical model and simulation results for correct authentication ensure that the proposed architecture achieves 86% eligibility of accuracy across a high ratio of malicious attacks in less converged time.

Abstract Root rot of pea caused by Fusarium spp. is one of the important diseases of pea (Pisum sativum L.). The causal fungus of the disease isolated from naturally infected pea plants was identified as Fusarium solani f. sp. pisi (Jones). Evaluation of four bio agents and nine fungicides was done in vitro against Fusarium solani. Trichoderma harzianum was the most effective bio agent in inhibiting the mycelial growth of F. solani by (82.62%). Carbendazim 50 WP was the most effective fungicide in inhibiting the mycelial growth of F. solani by (91.06%). Carbendazim at the rate of 0.1% and T. harzianum at concentration of 109 cfu when used as seed treatment under field conditions were evaluated along with three planting techniques v.i.z, raised beds, ridges and flat beds. It was found that Carbendazim at the rate of 0.1% when given as seed treatment in raised beds exhibited the lowest disease incidence (10.97%), intensity (2.89%) and the maximum pod yield (89.63 q ha−1) as compared to control.

Abstract Background The emerging viral pandemic worldwide is associated with a novel coronavirus, SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2). This virus is said to emerge from its epidemic center in Wuhan, China, in 2019. Coronaviruses (CoVs) are single-stranded, giant, enveloped RNA viruses that come under the family of coronaviridae and order Nidovirales which are the crucial pathogens for humans and other vertebrates. Main body Coronaviruses are divided into several subfamilies and genera based on the genomic structure and phylogenetic relationship. The name corona is raised due to the presence of spike protein on the envelope of the virus. The structural and genomic study revealed that the total genome size of SARS-CoV-2 is from 29.8 kb to 29.9 kb. The spike protein (S) is a glycoprotein that attaches to the receptor of host cells for entry into the host cell, followed by the attachment of virus RNA to the host ribosome for translation. The phylogenetic analysis of SARS-CoV-2 revealed the similarity (75–88%) with bat SARS-like coronavirus. Conclusion The sign and symptoms of novel severe acute respiratory syndrome coronavirus 2 are also discussed in this paper. The worldwide outbreak and prevention from severe acute respiratory syndrome coronavirus 2 are overviewed in the present article. The latest variant of coronavirus and the status of vaccines are also overviewed in the present article.

IntroductionPolycystic Ovary syndrome (PCOS) affects the health of many women around the world. Apart from fundamental metabolic problems connected to PCOS, focus of our study is on the role of quercetin on genes relevant to steroidogenesis and folliculogenesis.MethodsEighteen mature parkes strain mice (4-5 weeks old) weighing 18–21 g were randomly divided into three groups of six each as follows: Group I serves as the control and was given water and a regular chow diet ad lib for 66 days; group II was given oral gavage administration of letrozole (LETZ) (6 mg/kg bw) for 21 days to induce PCOS and was left untreated for 45 days; For three weeks, Group III received oral gavage dose of LETZ (6 mg/kg), after which it received Quercetin (QUER) (125 mg/kg bw orally daily) for 45 days.ResultsIn our study we observed that mice with PCOS had irregular estrous cycle with increased LH/FSH ratio, decreased estrogen level and decline in expression of Kitl, Bmp1, Cyp11a1, Cyp19a1, Ar, lhr, Fshr and Esr1 in ovary. Moreover, we observed increase in the expression of CYP17a1, as well as increase in cholesterol, triglycerides, testosterone, vascular endothelial growth factor VEGF and insulin levels. All these changes were reversed after the administration of quercetin in PCOS mice.DiscussionQuercetin treatment reversed the molecular, functional and morphological abnormalities brought on due to letrozole in pathological and physiological setting, particularly the issues of reproduction connected to PCOS. Quercetin doesn’t act locally only but it acts systematically as it works on Pituitary (LH/FSH)- Ovary (gonad hormones) axis. the Side effects of Quercetin have to be targeted in future researches. Quercetin may act as a promising candidate for medical management of human PCOS.

Weathering degree is one of the key criteria used to determine tunnel support with the main difficulty is in assessing the weathering grade of the tunnel face. This study applied CIEL*a*b colour space and image analysis to a rock mass tunnel face. The authors used the Japanese Highway (JH) Rock Mass Classification System to classify the rock mass tunnel face. JudGeo converted the RGB photographs to L*a*b values. This study compared the quantitative evaluation system's performance to manual tunnel face mapping by geologists using six JH Rock Mass Classification samples (Class B, CI, CII, DI, DII, and E). The analysis showed good correlations between four (B; CI; CII; DI) of six rock mass classes. The tunnel face mapping showed two rock mass classes above grade (DII and E). This technique can effectively identify the degree of weathering grades of the tunnel face, especially for fresh to moderately weathered tunnel faces.

Background: Obstructive sleep apnea (OSA) occurs in both obese and nonobese individuals. This study was designed to compare clinical, metabolic profile, and polysomnographic parameters among obese and nonobese OSA patients. Material and Methods: This cross-sectional retro-prospective study involved 148 OSA patients. OSA patients were classified as nonobese (body mass index [BMI]

SARS CoV-2 is a β-coronavirus responsible for the current COVID-19 pandemic. Although there is increase severity and mortality described in the elderly population and people with co-morbidities, all age groups are susceptible to COVID-19. Recent data showed that obesity has also emerged as a significant risk factor for COVID-19 mortality. As per the WHO, most of the world's population lives in countries where obesity is highly prevalent. In this context, we aimed to review various studies that showed obesity as an independent risk factor for mortality in SARS CoV-2 infection. We followed the PRISMA guidelines to search for two databases including PubMed and Google Scholar using the key terms “COVID-19, OBES* and MORTALITY,” SARS CoV-2, OBES* and MORTALITY” “COVID-19, OBESITY, and MORTALITY,” SARS Cov-2, OBESITY and MORTALITY,” respectively, up to August 3, 2020. Twelve studies were finally included in this review after applying inclusion and exclusion criteria. All 12 studies included in the review consistently showed that obesity is a risk factor for mortality in patients with SARS CoV-2 infection. These studies have also shown evidence that obesity leads to increased hospitalization, ICU admission, increased need for mechanical ventilation, and poor prognosis among patients with SARS CoV-2 infection. Obesity is an independent risk factor for mortality in patients infected with this novel coronavirus. Appropriate triage, monitoring, and vigilance are required while dealing with individuals with obesity with SARS CoV2 infection, especially in the young obese population. More epidemiological studies need to be done taking BMI also into consideration in COVID-19 patients to find the exact cause of increased severity and mortality and develop appropriate preventive and therapeutic strategies.

The aim of this paper is to explore the influence of training and development on employee’s performance through different dimensions. Moreover, this study proposes a model in the area of human resource development to be used for testing and improving the performance of employees in the Indian travel and tourism sector. An integrated model was developed highlighting the relationship between the training and development and employee performance. Using the sample of 146 employees, structural equation modelling (SEM) was employed to validate the hypothesized relationship by evaluating the responses of employees working in the Indian travel agencies. The findings of this study demonstrate a strong relationship between training and development and employee performance in the travel industry and also can be used by managers and HR professionals for organizing exclusive training programs for improving employee's performance based on the dimensions used in this paper. The present study provides an empirical and theoretical explanation of different dimensions associated with training and development and employee performance, especially in the Indian tourism industry.

Background: Neonatal severe primary hyperparathyroidism (NSPHPT) is disorder characterized by severe hypercalcemia and severe hyperparathyroidism resulting from a loss of function of the calcium-sensing receptor (CaSR), encoded by a gene located on the long arm of chromosome 3 (3q-13.3-21). It can be fatal if timely management is not initiated. Clinical Description: A 10-day-old exclusively breastfed girl presented with poor feeding, constipation, and lethargy for 2–3 days before admission. She was born of third-degree consanguinity to a primiparous woman with normal gestation. Born at term, with a birth weight of 3.1 kg, she was discharged uneventfully on day 3 of life. At admission, she was hemodynamically stable and normothermic but exhibited tachypnea, dehydrated with 15% weight loss as compared to birth weight, lethargy, and hypotonia. Salient investigations showed euglycemia, no dyselectrolytemia, and negative sepsis screen, but severe hypercalcemia and hyperparathyroidism. A final diagnosis of NSPHPT was made. Clinical exome sequencing showed homozygous CaSR gene frameshift mutation on chromosome 3. Management: Hypercalcemia was managed initially by standard protocol, including furosemide, hyperhydration, bisphosphonates, and cinacalcet. Subsequently, parathyroidectomy was performed at 2 months of age. Postoperatively, the infant is 5 months old and thriving well. Conclusion: NSPHPT should be considered in the presence of features of clinical sepsis, failure to timely regain birth weight, and a profile suggesting atypical calcium homeostasis.

Voltage regulation in automatic voltage regulator (AVR) system has been one of the most challenging engineering problem due to the uncertain load condition. Therefore, the control of AVR system by using PID based controller is one of the essential approach to maintain the performance of the AVR system. Subsequently, the application of FOPID controller in AVR system is gaining more attention recently. This is because the FOPID has additional control parameters at the derivative and integral parts than the PID controller, which has the advantage to improve the output response of AVR system while retaining the robustness and simple construction as the PID controller. Nevertheless, many existing optimization tools for tuning the FOPID controller, which are based on multi-agent based optimization, require large number of function evaluation in their algorithm that could lead to high computational burden. Therefore, this study proposes a modified smoothed function algorithm (MSFA) based method to tune the FOPID controller of AVR system since it requires fewer number of function evaluation per iteration. Moreover, the proposed MSFA based method also can solve the unstable convergence issue in the original smoothed function algorithm (SFA), thus able to provide better convergence accuracy. The simulations of step response analysis, Bode plot analysis, trajectory tracking analysis, disturbance rejection analysis, and parameter variation analysis are conducted to evaluate the effectiveness of the proposed MSFA-FOPID controller of AVR system. Consequently, the results obtained from the simulations revealed that the proposed method is highly effective and significantly improved as compared to the other existing FOPID controllers.

The capabilities of pure bacterial strains and their consortia isolated from agricultural soil were evaluated during a bioremediation process of the organophosphate pesticide malathion. The pure bacterial strains efficiently degraded 50.16–68.47% of the pesticide within 15 days of incubation, and metabolites were observed to accumulate in the soil. The consortia of three bacterial species [Micrococcus aloeverae (MAGK3) + Bacillus cereus (AGB3) + Bacillus paramycoides (AGM5)] degraded the malathion more effectively, and complete malathion removal was observed by the 15th day in soils inoculated with that consortium. In contrast, the combined activity of any two of these strains was lower than the mixed consortium of all of the strains. Individual mixed consortia of Micrococcus aloeverae (MAGK3) + Bacillus cereus (AGB3); Micrococcus aloeverae (MAGK3) + Bacillus paramycoides (AGM5); and Bacillus cereus (AGB3) + Bacillus paramycoides (AGM5) caused 76.58%, 70.95%, and 88.61% malathion degradation in soil, respectively. Several intermediate metabolites like malaoxon, malathion monocarboxylic acid, diethyl fumarate, and trimethyl thiophosphate were found to accumulate and be successively degraded during the bioremediation process via GC–MS detection. Thus, inoculating with a highly potent bacterial consortium isolated from in situ soil may result in the most effective pesticide degradation to significantly relieve soils from pesticide residues, and could be considered a prospective approach for the degradation and detoxification of environments contaminated with malathion and other organophosphate pesticides. This study reports the use of a mixed culture of Indigenous bacterial species for successful malathion degradation.

Objective: Cancer is the second biggest cause of death in humans. Rapid advancements in clinical bioinformatics and high-throughput proteomics technology are essential tools and methodologies for cancer research. Medicinal plants are considered operative therapeutic agents that are utilized for novel drug discovery and development, using computer-aided drug design (CAAD). The AKT-1 Serine/Threonine Kinase family was chosen as the target protein because it is implicated in the mediation of the cancer process. In this work, phytocompounds that target AKT-1 in cancer were recognized and were used to identify their binding relationship with the nominated receptor. Methods: A dried extraction of Fenugreek (Trigonella foenum-graecum) seeds in solid form was obtained using an evaporation technique and phytochemicals present in it were tested using qualitative tests. Fenugreek and its natural components were evaluated against AKT-1 because chemical agents acquired from natural sources appear to be particularly appealing alternatives to synthetic compounds. Different bioinformatics computational methods were used for protein structural analysis, interactive comparison, alignment, and superposition of AKT-1 protein structures in 3D. By using molecular docking and molecular dynamic (MD) simulation experiments, the binding interaction of the selected compounds with AKT-1 was investigated. Results: Fenugreek seeds yielded by phytochemicals screening and crude extractions of tannins, saponin, steroids, and cardiac glycosides were found to have very high antioxidant activity. After virtual screening hits, the top three phytocompounds (Compound-1 tannins, Compound-2 saponins, and Compound-3 steroids) were selected against AKT-1 on the basis of their strong binding energy (−10.9 to −9.2 Kcal/mol). Compound-1 showed the highest pharmacophore fit score (43.91) among all compounds. In molecular interactions, some crucial residues (Gln-79, Trp-80, Thr-82, Val-270, Tyr-272, Asp-274, and Asp-292) were observed at binding pockets of AKT-1. MD simulations at 100 ns revealed that the ligand was bound to the protein with some major conformational changes in the protein structure. Conclusions: In-silico studies report new dimensions for novel drug design targeting AKT-1. The three leading hits inhibit the cancer cell's inflammation activity in the AKT-1 pathway. In the future, these three compounds might be tested for the drug discovery of inflammatory disorders.

Background: Immunoglobulin A vasculitis (IgAV) also known as Henoch-Schonlein purpura is a common form of primary vasculitis, characterized clinically by palpable skin rash and one or more gastrointestinal, musculoskeletal, and/or renal system(s) involvement. It is more common in less than 10 years, with overall good prognosis. Half of the IgAV patients do have kidney involvement, with very small percentage progress to end stage kidney disease (ESKD). Objective: To know the incidence, clinical profile and outcome of IgAV (Henoch-Schonlein purpura) among hospitalized children in Kashmir province. Methods: This retrospective study, analysed the case records of all hospitalized patients between 1-18 years, diagnosed with IgAV over the last three years (April, 2017- March 2020). Data on clinical profile, laboratory abnormalities and outcomes were extracted. Results: Out of 40681 hospitalised children, 40 had IgAV, where 37 (92.5%) were between 3-10 years, with male female ratio of 1.8:1. Skin rash was observed in 38 (95%) children, gastrointestinal (GI) symptoms in 27 (67.5%), musculoskeletal symptoms in 18(45%) children, while as 11 (27.5%) had renal involvement. Two girls each of 6 and 7 years, and one 7-year boy presented as nephrotic syndrome with hematuria, who underwent renal biopsy, received prolonged immunosuppression, and are doing well with preserved renal functions till last follow up. Conclusion: Boys between 3-10 years were the commonest IgAV affected age group, where 95% had skin, 67.5% had GIT, 45% had musculoskeletal and 27.5% children had renal involvement.

Abstract Polycystic ovary syndrome (PCOS) is the most common reproductive endocrine disorder in pre-menopausal women having complex pathophysiology. Several candidate genes have been shown to have association with PCOS. CYP19 gene encodes a key steroidogenic enzyme involved in conversion of androgens into estrogens. Previous studies have reported contradictory results with regard to association of SNP rs2414096 in CYP19 gene with PCOS and hyperandrogenism in different ethnic populations. Present study was aimed to investigate the impact of SNP rs2414096 polymorphism of CYP19 gene on susceptibility of PCOS and hyperandrogenism in Kashmiri women. Further we also studied the genotypic-phenotypic association for various clinical and biochemical parameters of this polymorphism. Case control study. 394 PCOS cases diagnosed on the basis of Rotterdam criteria and age matched 306 healthy women. We found a significant differences in genotypic frequency (χ2 = 18.91, p

One of the most popular controllers for the automatic voltage regulator (AVR) in maintaining the voltage level of a synchronous generator is the fractional-order proportional–integral-derivative (FOPID) controller. Unfortunately, tuning the FOPID controller is challenging since there are five gains compared to the three gains of a conventional proportional–integral–derivative (PID) controller. Therefore, this research work presents a variant of the marine predators algorithm (MPA) for tuning the FOPID controller of the AVR system. Here, two modifications are applied to the existing MPA: the hybridization between MPA and the safe experimentation dynamics algorithm (SEDA) in the updating mechanism to solve the local optima issue, and the introduction of a tunable step size adaptive coefficient (CF) to improve the searching capability. The effectiveness of the proposed method in tuning the FOPID controller of the AVR system was assessed in terms of the convergence curve of the objective function, the statistical analysis of the objective function, Wilcoxon’s rank test, the step response analysis, stability analyses, and robustness analyses where the AVR system was subjected to noise, disturbance, and parameter uncertainties. We have shown that our proposed controller has improved the AVR system’s transient response and also produced about two times better results for objective function compared with other recent metaheuristic optimization-tuned FOPID controllers.

Abstract Globally hypertension in adults is among the leading preventable cause of premature death, where a graded association from the childhood hypertension is well recognised. With the concurrent rise in obesity and pediatric hypertension (HTN) during the past decade in developed countries, a parallel trend is emerging in developing countries that has a potential for exponential rise in cardiovascular, cerebrovascular and renal tragedies. A cumulative incidence of pediatric HTN in China and India is 50–70 and 23% respectively, is quite disturbing. New guidelines for the detection, evaluation and management of hypertension in children and adolescents published in 2017, where a jump in prevalence of pediatric HTN is observed, rings a call to address this under-attended burning problem; for which a review in pediatric hypertension and its management is warranted.