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Abstract We investigated the potential of the transmission line model as a digital twin of aneurysmal aorta by comparatively analyzing how a uniform lossless tube-load model were fitted to the carotid and femoral artery tonometry waveforms pertaining to (i) 79 abdominal aortic aneurysm (AAA) patients vs their matched controls (CON) and (ii) 35 AAA patients before vs after endovascular aneurysm repair (EVAR). The uniform lossless tube-load model fitted the tonometry waveforms pertaining to AAA as well as CON and EVAR. In addition, the parameters in the tube-load model exhibited physiologically explainable changes: when normalized, both pulse transit time and reflection coefficient increased with AAA and decreased after EVAR, which can be explained by the increase in arterial compliance and the decrease in arterial inertance due to the aortic expansion associated with AAA. In sum, the tube-load model may have the potential as a digital twin to enable personalized AAA monitoring.

Background: Physiotherapists are health professionals who enhance mobility and quality of life (QoL) through clinical reasoning and the application of evaluation and treatment strategies. Their role is crucial in promoting health, preventing injury, and maintaining function. AIM: This paper aims to (1) share early experiences and learnings from integrating physiotherapy in rural primary health care, (2) discuss the scope and role of physiotherapists in the primary care team, (3) list the competencies of physiotherapists in rural primary care settings, and (4) advocate for a re-imagined role of physiotherapists as multi-skilled “primary care physiotherapists.” Setting and Method: Using a selection of case stories from rural primary health care settings, the paper provides insights into the integration and impact of physiotherapy within these communities. Results: The integration of physiotherapy in rural primary health care has demonstrated significant benefits in promoting comprehensive primary health care. The case stories highlight the expanded scope and essential competencies of physiotherapists as vital members of the primary care team. Conclusion: This paper emphasizes the critical role physiotherapy plays in primary health care and calls for broader recognition and support for physiotherapists. It underscores the need for a re-imagined perspective of physiotherapists in rural settings, advocating for their role as multi-skilled primary care professionals.

Abstract Multilevel thresholding image segmentation will subdivide an image into several meaningful regions or objects, which makes the image more informative and easier to analyze. Optimal multilevel thresholding approaches are extensively used for segmentation because they are easy to implement and offer low computational cost. Multilevel thresholding image segmentation is frequently performed using popular methods such as Otsu’s between-class variance and Kapur’s entropy. Numerous researchers have used evolutionary algorithms to identify the best multilevel thresholds based on the above approaches using histogram. This paper uses the Energy Curve (EC) based thresholding method instead of the histogram. Chaotic Bidirectional Smell Agent Optimization with Adaptive Control Strategy (ChBSAOACS), a powerful evolutionary algorithm, is developed and employed in this paper to create and execute an effective method for multilevel thresholding segmentation of breast thermogram images based on energy curves. The proposed algorithm was tested for viability on standard breast thermogram images. All experimental data are examined quantitatively and qualitatively to verify the suggested method’s efficacy.

Abstract This study investigates the application of the multiobjective grey wolf optimizer (MOGWO) for optimal placement of thyristor-controlled series compensator (TCSC) to minimize power loss in power systems. Two conflicting objectives are considered: (1) minimizing real and reactive power loss, and (2) minimizing real power loss and TCSC capital cost. The Pareto-optimal method is employed to generate the Pareto front for these objectives. The fuzzy set technique is used to identify the optimal trade-off solution, while the technique for order preference by similarity to the ideal solution suggests multiple optimal solutions catering to diverse utility preferences. Simulations on an IEEE 30 bus test system demonstrate the effectiveness of TCSC placement for power loss minimization using MOGWO. The superiority of MOGWO is confirmed by comparing its results with those obtained from a multiobjective particle swarm optimization algorithm. These findings can assist power system utilities in identifying optimal TCSC locations to maximize their performance.

Abstract The synthesis of metal nanoparticles through bio-reduction is environmentally benign and devoid of impurities, which is very important for biological applications. This method aims to improve ZnO nanoparticle's antibacterial and anti-biofilm activity while reducing the amount of hazardous chemicals used in nanoparticle production. The assembly of zinc oxide nanoparticles (ZnO NPs) is presented via bio-reduction of an aqueous zinc nitrate solution using Echinochloacolona (E. colona) plant aqueous leaf extract comprising various phytochemical components such as phenols, flavonoids, proteins, and sugars. The synthesized nano ZnO NPs are characterized by UV–visible spectrophotometer (UV–vis), Fourier transform infrared spectroscopy (FT-IR), X-ray diffraction (X-RD), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and elemental composition by energy-dispersive x-ray spectroscopy (EDX). The formation of biosynthesized ZnO nanoparticles was confirmed by the absorbance at 360–370 nm in the UV–vis spectrum. The average crystal size of the particles was found to be 15.8 nm, as calculated from XRD. SEM and TEM analysis of prepared ZnO NPs confirmed the spherical and hexagonal shaped nanoparticles. ZnO NPs showed antibacterial activity against Escherichia coli and Klebsiella pneumoniae with the largest zone of inhibition (ZOI) of 17 and 18 mm, respectively, from the disc diffusion method. Furthermore, ZnO NPs exhibited significant anti-biofilm activity in a dose-dependent manner against selected bacterial strains, thus suggesting that ZnO NPs can be deployed in the prevention of infectious diseases and also used in food preservation.

Abstract Simulation and implementation of a single DC-link-based three-phase inverter are investigated in this article. The primary focus is on designing a single DC-link three-phase inverter for high power applications. Unlike conventional inverters that require 600 V to generate 400 V (RMS) at the output, the proposed system achieves this with only 330 V, facilitated by a 12-terminal 1:1 transformer. The system employs Proportional Integral (PI) and Neural Network (NN) controllers to optimize performance. Various Carrier-Based Pulse Width Modulation (CB-PWM) techniques, including Phase Disposition (PD), Phase Opposition Disposition (POD), and Alternative Phase Opposition Disposition (APOD), are implemented and evaluated based on Total Harmonics Distortion (THD) concerning the Modulation Index (MI) of the inverter. The proposed inverter achieves a THD reduction to 4.8%, demonstrating superior performance compared to recent studies. The system’s performance is validated through extensive MATLAB/Simulink simulations and practical implementation using XILINX FPGA software, confirming the efficacy of the proposed design.

Abstract Transformer is a well-known power system apparatus utilized in conjunction with solid insulations such as paper and press board, as well as liquid insulations like mineral oil, a petroleum-based fluid. Despite the notable drawbacks associated with mineral oil, such as limited resources for future generations and its non-eco-friendly nature, its usage remains ubiquitous. There is a growing imperative to explore alternative fluids that surpass mineral oil in terms of environmental impact and performance. Amidst the global shift towards green energy, this study focuses on vegetable seed oils such as corn oil, soybean oil, mustard oil, and rice bran oil as potential substitutes. The research evaluates these oils based on key transformer properties including breakdown voltage, water content, interfacial tension, viscosity, acidity, flash point, and fire point. Interestingly, rice bran oil and soybean oil exhibit promising characteristics that suggest they could effectively replace petroleum-based fluids in transformers. Furthermore, the study extends to blending mineral oil with vegetable seed oils in various compositions, incorporating natural and synthetic antioxidant additives ranging from 0 to 1%. Comparative analyses between samples with and without additives reveal that the inclusion of 1% propyl gallate yields outstanding performance improvements. For instance, a blend comprising 25 ml of mineral oil and 25 ml of soybean oil, supplemented with 1% propyl gallate, demonstrates 90% higher effectiveness compared to other blends and additives tested. Moreover, the research employs statistical regression analysis to establish relationships between different parameter variables, providing deeper insights into the performance and compatibility of these blended oils in transformer applications. This comprehensive investigation underscores the potential of vegetable seed oils as viable alternatives to mineral oil, contributing to the advancement of eco-friendly solutions in power systems.

Abstract Background The gaps in healthy life expectancy (HLE) between Indigenous and non-Indigenous Australians are significant. Detailed and accurate information is required to develop strategies that will close these health disparities. This paper aims to quantify and compare the causes and their relative contributions to the life expectancy (LE) gaps between the Indigenous and non-Indigenous population in the Northern Territory (NT), Australia. Methods The age-cause decomposition was used to analyse the differences in HLE and unhealthy life expectancy (ULE), where LE = HLE + ULE. The data was sourced from the burden of disease and injury study in the NT between 2014 and 2018. Results In 2014–2018, the HLE at birth in the NT Indigenous population was estimated at 43.3 years in males and 41.4 years in females, 26.5 and 33.5 years shorter than the non-Indigenous population. This gap approximately doubled the LE gap (14.0 years in males, 16.6 years in females) at birth. In contrast to LE and HLE, ULE at birth was longer in the Indigenous than non-Indigenous population. The leading causes of the ULE gap at birth were endocrine conditions (explaining 2.9–4.4 years, 23–26%), followed by mental conditions in males and musculoskeletal conditions in females (1.92 and 1.94 years, 15% and 12% respectively), markedly different from the causes of the LE gap (cardiovascular disease, cancers and unintentional injury). Conclusions The ULE estimates offer valuable insights into the patterns of morbidity particularly useful in terms of primary and secondary prevention.

Abstract High systolic blood pressure (BP) is the most important modifiable risk factor for cardiovascular disease. Managing systolic hypertension is especially difficult in underserved populations wherein access to cuff BP devices is limited. We showed that ubiquitous smartphones without force sensing can be converted into absolute pulse pressure (PP) monitors. The concept is for the user to perform guided thumb and hand maneuvers with the phone to induce cuff-like actuation and allow built-in sensors to make cuff-like measurements for computing PP. We developed an Android smartphone PP application. The ‘app’ could be learned by volunteers and yielded PP with total error

Introduction: Expanding knowledge on tobacco use and quitting outcomes in Chhattisgarh, India, is crucial. Limited data hinder the assessment of tobacco use prevalence and quitting outcomes in the region. This household-based cross-sectional study aimed to assess smokeless tobacco (SLT) use and quit behaviour among village dwellers aged 35–44 and 65–74 years in Jamul, Chhattisgarh. Materials and Methods: A survey was conducted among 450 participants, utilising a pretested questionnaire and data analysis using IBM Statistical Package for the Social Sciences (SPSS) v23. Results: The study revealed that among the survey participants, 61.1% were males and 38.9% were females. The prevalence of SLT use was found to be 67.8%, with 59.1% of current SLT users reporting daily use. Middle-aged individuals predominantly chose gutkha, while khaini was more common among the elderly. Tobacco and paan with tobacco were also commonly used forms. Gudakhu, a popular SLT product for oral hygiene and easy defecation, was reported by 71.34% of participants. Television warnings and SLT packages proved to be successful methods for disseminating information about the dangers of SLT use. However, SLT users who attempted to quit independently reported encountering one or more withdrawal symptoms, which posed significant obstacles to quitting SLT. Conclusion: Community-based awareness programmes are implemented via regional television (TV) channels, coupled with cessation initiatives, including professional counselling, pharmaceutical interventions and support of peer. Changing attitudes against SLT use and promoting tobacco-free environments are prioritized. These strategies will effectively address SLT use and improve quitting outcomes in Jamul, Chhattisgarh, fostering a healthier community.

The emergence of diabetes mellitus (DM), one of the prevalent metabolic disorders, has increased at alarming rates around the globe in the past few decades. The early discovery of insulin paved the way for the broadened non-invasive anti-hyperglycemic drug therapies to manage and treat diabetes. Recently, insulin resistance in brain tissues has been considered a new hallmark of disease progression, leading to neurodegeneration. Tetrahydro γ-carbolines are privileged scaffolds with various activities against obesity, cancer, and central nervous system (CNS) diseases. The failure of Latrepirdine in clinical phase trials as anti-AD, prompted us to explore further the γ-Carboline derivatives with anti-diabetic activity. To address this, we have leveraged our expertise in drug design to develop tetrahydro γ-carboline derivatives and studied their effect on glucose uptake. All the compounds exhibited low cytotoxicity towards the mammalian cell line 3T3-L1. Next, we screened the 10 derivatives to identify the novel anti-diabetic activities using a fluorescent glucose analog 2-NBDG (2-(N-(7-nitrobenz-2-oxa-1, 3-diazol-4-yl)-2-deoxy-D-glucose) based on a glucose-uptake assay in differentiated 3T3-L1 adipocytes. Compound 11a has significantly increased glucose uptake at 100 µM compared to rH-Insulin. The dose optimization (1 nM-100 nM) of lead compounds for 2-NBDG-glucose uptake clearly indicated that 11a is superior compared to Insulin. The 11a is the close analog of Latrepirdine, an anti-histamine drug, reported for Alzheimer disease (AD). Further, to understand its anti-AD potential we carried out in silico docking studies with its probable targets, Acetylcholinesterase (AChE), 5-hydroxytryptamine (5HT6) receptor, Butyrylcholinesterase (BChE), and N-methyl-D-aspartate (NMDA) receptor. The docking studies revealed that 11a had stronger binding to these targets than Latrepirdine, correlating with the glucose uptake assay. Thus, 11a is a potential lead disease-modifying agent and could be considered for the management and treatment of type 2 DM and AD.

The past several decades have seen rapid advances in diagnosis and treatment of cardiovascular diseases and stroke, enabled by technological breakthroughs in imaging, genomics, and physiological monitoring, coupled with therapeutic interventions. We now face the challenge of how to (1) rapidly process large, complex multimodal and multiscale medical measurements; (2) map all available data streams to the trajectories of disease states over the patient's lifetime; and (3) apply this information for optimal clinical interventions and outcomes. Here we review new advances that may address these challenges using digital twin technology to fulfill the promise of personalized cardiovascular medical practice. Rooted in engineering mechanics and manufacturing, the digital twin is a virtual representation engineered to model and simulate its physical counterpart. Recent breakthroughs in scientific computation, artificial intelligence, and sensor technology have enabled rapid bidirectional interactions between the virtual‐physical counterparts with measurements of the physical twin that inform and improve its virtual twin, which in turn provide updated virtual projections of disease trajectories and anticipated clinical outcomes. Verification, validation, and uncertainty quantification builds confidence and trust by clinicians and patients in the digital twin and establishes boundaries for the use of simulations in cardiovascular medicine. Mechanistic physiological models form the fundamental building blocks of the personalized digital twin that continuously forecast optimal management of cardiovascular health using individualized data streams. We present exemplars from the existing body of literature pertaining to mechanistic model development for cardiovascular dynamics and summarize existing technical challenges and opportunities pertaining to the foundation of a digital twin.

Purpose: To critically review the clinical factors, dosimetry, and their correlation with early outcomes in patients with chordomas and chondrosarcomas treated with pencil beam scanning (PBS) proton beam therapy (PBT). Methods and Materials: Consecutive 64 patients diagnosed with chordoma or chondrosarcoma treated at our center were studied. Patient, tumor, and treatment-related factors including dosimetry were captured. Early and late toxicities and early outcomes were evaluated and correlated with clinical and dosimetric factors using standard statistical tools. Results: The median age of patients was 39 years (range, 4-74 years), and most common site was skull base (47%), followed by sacrum (31%) and mobile spine (22%). The median prescription dose to the high-risk clinical target volumes for chordoma and chondrosarcoma was 70.4 cobalt gray equivalent (CGE) and 66 CGE at 2.2 CGE per fraction, respectively. At presentation, 55% presented after a recurrence/progression of which 17% had received previous radiation and 32% had a significant neural compression. At the time of PBT, 25% of patients had suboptimal neural separation. Three-fourths of patients had at least an acceptable target coverage. Although 11% had a tier 1 compromise (gross tumor volume [GTV] D98 < 90%), 14% had a tier 2 compromise (GTVD98 < 59 CGE). With a median follow-up of 27.5 months, 2-year local control and progression-free survival was 86.7% and 81.8% for chordomas and 87.5% and 77.1% for chondrosarcomas, respectively. Residual GTV of >25 cm3 and a tier 2 compromise were associated with inferior local control (hazard ratio [HR], 0.19; P = .019; HR, 0.061; P = .022, respectively) and progression-free survival (HR, 0.128; P = 0.014; HR, 0.194; P =.025, respectively) on multivariate analysis. Despite multiple surgeries, a majority presented with recurrent disease and previous radiations and grade 3 acute and late toxicities were limited and comparable with others in the literature. Conclusions: Despite multiple surgeries, adequate neural separation was challenging to achieve. Severe dosimetric compromise (GTV D98 < 59 CGE) led to inferior early outcomes. Adequate neural separation is key to avoiding dosimetric compromise and achieving optimal local control.

Introduction: Community water fluoridation (CWF) is a cost-effective intervention to reduce dental caries at population level. This Australian study used a difference-in-difference (DiD) analysis to measure dental caries in children exposed to CWF in the Northern Territory (NT), Australia. Methods: Oral health data obtained from the NT Department of Health contained 64 399 person-year observations from 2008 to 2020, totalling 24 546 children aged 1-17 years. Drinking water quality data for fluoride levels, held by the Power and Water Corporation, were obtained for 50 remote communities and linked to the oral health dataset. The DiD analysis used a treatment group and two control groups to compare the effects of CWF on dental caries outcomes in children, measured using the decayed, missing and filled teeth (dmft/DMFT) index. The treatment group consisted of records from children residing in five remote NT communities that implemented CWF in 2014.The control 1 group included records of children residing in communities with naturally occurring fluoride in drinking water supplies at levels at or above the Department of Health policy threshold of 0.5 mg/L. The control 2 group included records of children residing in communities with naturally occurring fluoride in drinking water supplies below the level recommended by the Department of Health policy (

Chronic subdural hematoma (CSDH) is a great mimicker. It should be considered in anyone presenting with chronic headaches that show postural variation. Parkinsonism following CSDH, while known, is only rarely reported in the literature. Hyponatremia, rapid correction of hyponatremia, medications, and mechanical pressure are thought to be risk factors. Here, we report a case of a 61-year-old male diagnosed with bilateral CSDH managed by craniotomy and clot evacuation who developed parkinsonism. We share several learnings (clinical pearls) that emerged from the close collaboration and co-learning curve between a family physician and physiotherapist involved in home-based rehabilitation. In conclusion, while managing the postoperative course of patients with CSDH, clinicians should maintain a high index of suspicion for parkinsonism. Early recognition and appropriate management with syndopa with supportive physiotherapy results in significant improvement of function and quality of life. Notably, parkinsonism following SDH is transient and nonprogressive and may not require lifelong therapy.

Abstract The continuing emergence of new strains of antibiotic-resistant bacteria has renewed interest in phage therapy; however, there has been limited progress in applying phage therapy to multi-drug resistant Mycobacterium tuberculosis (Mtb) infections. In this study, we show that bacteriophage strains D29 and DS6A can efficiently lyse Mtb H37Rv in 7H10 agar plates. However, only phage DS6A efficiently kills H37Rv in liquid culture and in Mtb-infected human primary macrophages. We further show in subsequent experiments that, after the humanized mice were infected with aerosolized H37Rv, then treated with DS6A intravenously, the DS6A treated mice showed increased body weight and improved pulmonary function relative to control mice. Furthermore, DS6A reduces Mtb load in mouse organs with greater efficacy in the spleen. These results demonstrate the feasibility of developing phage therapy as an effective therapeutic against Mtb infection.

Abstract Cellular responses to the steroid hormones, estrogen (E2), and progesterone (P4) are governed by their cognate receptor’s transcriptional output. However, the feed-forward mechanisms that shape cell-type-specific transcriptional fulcrums for steroid receptors are unidentified. Herein, we found that a common feed-forward mechanism between GREB1 and steroid receptors regulates the differential effect of GREB1 on steroid hormones in a physiological or pathological context. In physiological (receptive) endometrium, GREB1 controls P4-responses in uterine stroma, affecting endometrial receptivity and decidualization, while not affecting E2-mediated epithelial proliferation. Of mechanism, progesterone-induced GREB1 physically interacts with the progesterone receptor, acting as a cofactor in a positive feedback mechanism to regulate P4-responsive genes. Conversely, in endometrial pathology (endometriosis), E2-induced GREB1 modulates E2-dependent gene expression to promote the growth of endometriotic lesions in mice. This differential action of GREB1 exerted by a common feed-forward mechanism with steroid receptors advances our understanding of mechanisms that underlie cell- and tissue-specific steroid hormone actions.

Intra-abdominal Cerebrospinal Fluid (CSF) pseudocysts are a well-known and potentially serious complication of Ventriculoperitoneal (VP) shunt placement. These cysts are often found within the peritoneal cavity or along the serosal surface of solid organs. Here, we present an unusual case of an intrahepatic CSF pseudocyst in a 14-year-old female patient with a VP shunt placed three years ago, following the excision of a cerebellar pilocytic astrocytoma. The child presented with complaints of right hypochondriac pain and tenderness for one month. On ultrasound of the abdomen, the right lobe of the liver showed a complex anechoic cystic collection with multiple thick internal septations. A Contrast-enhanced Computed Tomography (CECT) examination revealed a well-defined hypodense collection in segments IV and V of the liver with a VP shunt tube within. Based on clinical and imaging features, differentials of intra-axial intrahepatic CSF pseudocyst, complex hepatic cyst, peri-shunt hemorrhagic cyst, and biliary cystadenoma were considered. Aspiration of the cyst revealed clear, colourless, non purulent, non sanguineous fluid which tested positive for beta-2-transferrin, confirming the collection to be a CSF pseudocyst. An elective laparoscopic cyst excision with shunt revision was performed with no recurrence on follow-up. The present case highlights the uncommon occurrence of intrahepatic CSF pseudocysts post-VP shunt, necessitating meticulous diagnostic evaluation. Successful laparoscopic excision and shunt revision underscore the efficacy of tailored interventions. This contribution enhances the understanding of atypical complications in VP shunt recipients, guiding clinicians and radiologists in both diagnosis and management.

Abstract Accurately locating power distribution faults reduces the total outage duration and provides better system reliability. Fault location using the traditional impedance‐based method may be very challenging in an active distribution system. However, taking into consideration the ease of implementation and cost effectiveness, a novel impedance‐based method is proposed to locate the fault by using the highly accurate time‐synchronized voltage and current phasors obtained from distribution phasor measurement units. The synchrophasor measurements obtained from the substation and various feeder segments are used in a two‐step algorithm based on the apparent impedance calculation to locate the exact source of the event. The algorithm uses phasor estimates to first identify the faulted feeder sub‐region and later uses measurements from a remote end device to eliminate pseudo‐faulted points to obtain the actual fault location. The effectiveness of the proposed method is realized using IEEE 34 bus system. Based on different fault types simulated at various parts of the system, the algorithm accurately estimates fault location in the range of ±1% of the line length. The proposed method is effective in locating faults for any type of network and topologies, with as many or as few (minimum 2) phasor measurement units in the system.

Gas turbines are pivotal in electricity generation and industry, prized for their efficiency and flexibility in meeting diverse power needs. Optimizing their thermal efficiency is essential for improving energy output and sustainability. Soft computing methods such as neural networks, genetic algorithms, and fuzzy logic offer potent tools for this optimization due to their ability to handle the turbines' nonlinear and dynamic characteristics. These techniques facilitate a deeper understanding of the intricate interplay among various parameters affecting thermal performance, thereby enabling the development of intelligent and adaptive turbine systems. By leveraging soft computing, researchers can enhance gas turbine designs to align with modern energy and environmental objectives. This review emphasizes the application of soft computing approaches in analysing and improving gas turbine thermal performance. Such advancements are instrumental in achieving higher energy efficiency, reducing greenhouse gas emissions, and promoting a sustainable energy landscape. Ultimately, integrating soft computing into gas turbine operations promises to advance both technical capabilities and environmental stewardship in the detection of a more resilient and efficient energy infrastructure.

Summary: Despite some evidence indicating diverse roles of whirlin in neurons, the functional corollary of whirlin gene function and behavior has not been investigated or broadly characterized. A single nucleotide variant was identified from our recessive ENU-mutagenesis screen at a donor-splice site in whirlin, a protein critical for proper sensorineural hearing function. The mutation (head-bob, hb) led to partial intron-retention causing a frameshift and introducing a premature termination codon. Mutant mice had a head-bobbing phenotype and significant hyperactivity across several phenotyping tests. Lack of complementation of head-bob with whirler mutant mice confirmed the head-bob mutation as functionally distinct with compound mutants having a mild-moderate hearing defect. Utilizing transgenics, we demonstrate rescue of the hyperactive phenotype and combined with the expression profiling data conclude whirlin plays an essential role in activity-related behaviors. These results highlight a pleiotropic role of whirlin within the brain and implicate alternative, central mediated pathways in its function.

Nowadays green synthesis is being incorporated into various technological fields to achieve more sustainable and environmentally friendly processes. By reducing the use of hazardous chemicals, minimizing waste generation, and utilizing renewable resources, green synthesis offers potential solutions to address environmental concerns and promote sustainable development in technology sectors. Herein we demonstrate an environmentally friendly green approach for the fabrication of MgO nanoparticles by using various fruit extracts. In this current study, watermelon, Aloe vera, and Jamun fruit extracts are used as fuel for the synthesis of MgO nanomaterials. Prepared materials were characterized by various characterization techniques. Scanning electron microscopy (SEM) images demonstrate the porous nature of the material and the Diffused reflectance spectroscopy (DRS) reveals the energy gap (4.8–4.9 eV) of the material. Photocatalytic degradation of Direct Green (DG) dye was evaluated under UV light irradiation and the catalyst prepared via jamun fuel (MgO-J) exhibited excellent catalytic activity at 84% for the degradation of DG dye under UV light and better electrochemical behavior as an electrode material compared to other prepared materials. This present work demonstrates a highly efficient eco-friendly route to synthesize MgO nanoparticles for multifunctional applications and also encourages sustainable development in technology areas.

One of the most popular renewable energy sources is solar photovoltaic, so it is essential to comprehend the PV model and model it accurately. Many parameters need to be extracted from the photovoltaic to assess the performance of the PV cell. Extracting the unknown parameters from the PV cell is significantly important for the analysis of the fault diagnosis, Maximum power point tracking (MPPT), control, and efficiency of the photo-voltaic system. The unknown parameters are (Photo current, series and shunt resistances, diode ideality factor, reverse saturation current). This algorithm is applied to PV cell (R.T.C France Si.) at the standard (STC) conditions utilizing the Three Diode Model, and applied to different PV modules like PWP201, SM55 at different temperatures and irradiances. This paper presents the Chaotic War Strategy Optimization (CWSO) algorithm to further reduce the error between measured and calculated values. The primary benefit of the proposed approach is its utilization of chaotic maps to calculate and dynamically adjust the internal parameters of the optimization algorithm. The extracted parameters and RMSE are compared to those of other cutting-edge algorithms to discover the most effective one for the parameter estimation issue to assess this algorithm’s efficacy.

The synthesis of 4-aryl-NH-1,2,3-triazoles in good to excellent isolated yields (75-95%) has been achieved via a [3+2] cycloaddition of aromatic nitroolefins and sodium azide catalyzed by recyclable heterogeneous sulfated tin oxide (STO, 10 mol%) in toluene at 60 0C. Aliphatic nitrooefines proved to be unsuccessful partners in the present methodology.

Abstract Satellite data show the Earth has been greening and identify croplands in India as one of the most prominent greening hotspots. Though India’s agriculture has been dependent on irrigation enhancement to reduce crop water stress and increase production, the spatiotemporal dynamics of how irrigation influenced the satellite observed greenness remains unclear. Here, we use satellite-derived leaf area data and survey-based agricultural statistics together with results from state-of-the-art Land Surface Models (LSM) to investigate the role of irrigation in the greening of India’s croplands. We find that satellite observations provide multiple lines of evidence showing strong contributions of irrigation to significant greening during dry season and in drier environments. The national statistics support irrigation-driven yield enhancement and increased dry season cropping intensity. These suggest a continuous shift in India’s agriculture toward an irrigation-driven dry season cropping system and confirm the importance of land management in the greening phenomenon. However, the LSMs identify CO2 fertilization as a primary driver of greening whereas land use and management have marginal impacts on the simulated leaf area changes. This finding urges a closer collaboration of the modeling, Earth observation, and land system science communities to improve representation of land management in the Earth system modeling.

Wireless Sensor Networks (WSNs) were exposed to several distinct safety issues and attacks regarding gathering and sending data. In this scenario, one of the most prevalent WSN assaults that may target any tier of the protocol stack is the Denial of Service (DoS) attack. The current research suggested various strategies to find the attack in the network. However, it has classification challenges. An effective ensemble deep learning-based intrusion detection system to identify the assault in the WSN network was, therefore, suggested in this research to address this issue. The data pre-processing involves converting qualitative data into numeric data using the One-Hot Encoding technique. Following that, Normalization Process was carried out. Then Manta-Ray Foraging Optimization is suggested to choose the best subset of features. Then Synthetic Minority Oversampling Technique (SMOTE) oversampling creates a new minority sample to balance the processed dataset. Finally, CNN–SVM classifier is proposed to classify the attack kinds. The Accuracy, F-Measure, Precision, and Recall metrics were used to assess the outcomes of 99.75%, 99.21%, 100%, and 99.6%, respectively. Compared to existing approaches, the proposed method has shown to be extremely effective in detecting DoS attacks in WSNs.

The increasing interest in renewable energy-based power systems globally is driven by their abundance and environmentally friendly attributes. Islanded hybrid microgrid systems (IHMS) are a relatively new development in this field and involve the integration of two or more sustainable sources, such as wind turbines, solar photovoltaic (PV) systems, and other forms of renewable energy such as the ocean, wave, and geothermal energy. In order to ensure an uninterrupted power supply for the growing community and industrial sector of Perhentian Island, Malaysia, alternative power sources must be properly synchronized and managed through an energy management system. To this end, the main contribution of this study is the comprehensive analysis of various optimization methods in terms of net present cost (NPC) and convergence rate. The results of the analysis indicate that HOMER proved to be relatively faster in terms of convergence rate, with the NPC recorded as 387,185$ and the Levelized Cost of Energy (LCOE) recorded as 0.64$/kWh, which are the least among the other techniques evaluated. The hybrid energy system was designed to acquire the optimal quantity and size of power-generating modules, including PV systems, wind turbines, batteries, and diesel generators, while also meeting the load requirements. The optimization problem incorporated the LCOE and NPC into the cost function. Various optimization techniques were developed and tested. In addition, an advanced control method, which includes the use of Proportional–integral–derivative (PID) control and Fuzzy Logic Controller (FLC) with automated tuning, was applied to manage voltage and frequency. The control strategy was implemented in MATLAB Simulink, along with a full model of the islanded hybrid microgrid system. The simulation results demonstrate the effectiveness of the proposed FLC in maintaining the voltage and frequency within the acceptable range during various operating conditions. In conclusion, this manuscript provides a comprehensive study on the optimization and control of a solar-wind islanded hybrid microgrid. The proposed approach can be used as a valuable tool for the design and operation of solar-wind islanded hybrid microgrids in remote and islanded communities.

Sucrose constitutes a non-toxic, biodegradable, low-cost and readily available natural product. To expand its utility, we developed total synthesis for a ligand based on a sucrose scaffold for potential use as a metal chelation agent. The designed target (compound 2) has a metal-chelating functionality at both the C-6 and C-6’ positions, which can provide a first coordination sphere of eight valencies. The designed total synthesis was highly efficient. To demonstrate the utility of the ligand, we studied its complexation with Gd(III). Using potentiometric titration and high-resolution mass spectrometry, we confirmed the formation of a 1:1 complex with Gd(III), which has a respectable formation constant of ~1013.4. Further NMR relaxivity studies show that the Gd(III) complex has a relaxivity (r1) of 7.6958 mmol−1 s−1.

The practical application of plastics is as indispensable as it is problematic regarding disposal. Plastics present significant opportunities in the context of circular usage and recycling. A circular economy dictates the utilization of every side stream to minimize waste. Current waste management techniques are insufficient in reducing plastic waste entering landfills, wastewater treatment systems, and the environment. Under these circumstances, plastic biodegradation has emerged as a viable and environmentally responsible approach to plastic pollution. Methods are needed for the natural degradation of plastics using microbes that can utilize plastics as their sole carbon source. Studies to enhance the catalytic activity of plastic-degrading enzymes through protein engineering approaches are a relatively new field of research. Enzymatic degradation for product creation represents a purely biological plastic recycling method in a sustainable economy. This review builds insights derived from previous studies and provides a brief overview of plastic degradation using enzymes, improvements in plastic-degrading enzyme efficiency, and stabilization via various protein engineering strategies. In addition, recent advances in plastic waste valorization technology based on systems metabolic engineering and future directions are discussed.

Immune dysfunction is one of the central components in the development and progression of endometriosis by establishing a chronic inflammatory environment. Western-style high-fat diets (HFD) have been linked to greater systemic inflammation to cause metabolic and chronic inflammatory diseases, and are also considered an environmental risk factor for gynecologic diseases. Here, we aimed to examine how HFD cause an inflammatory environment in endometriosis and discern their contribution to endometriotic-associated hyperalgesia. Our results showed that HFD-induced obesity enhanced abdominal hyperalgesia that was induced by endometriotic lesions. Peritoneal inflammatory macrophages and cytokine levels increased by lesion induction were elevated by chronic exposure to HFD. Increased expression of pain-related mediators in the dorsal root ganglia was observed after lesion induction under the HFD condition. Although HFD did not affect inflammatory macrophages in the peritoneal cavity without lesion induction, the diversity and composition of the gut microbiota were clearly altered by HFD as a sign of low-grade systemic inflammation. Thus, HFD alone might not establish a local inflammatory environment in the pelvic cavity, but it can contribute to further enhancing chronic inflammation, leading to the exacerbation of endometriosis-associated abdominal hyperalgesia following the establishment and progression of the disease.

Summary: Background: There are limited global data on head-to-head comparisons of vaccine platforms assessing both humoral and cellular immune responses, stratified by pre-vaccination serostatus. The COVID-19 vaccination drive for the Indian population in the age group 18–45 years began in April 2021 when seropositivity rates in the general population were rising due to the delta wave of COVID-19 pandemic during April–May 2021. Methods: Between June 30, 2021, and Jan 28, 2022, we enrolled 691 participants in the age group 18–45 years across four clinical sites in India. In this non-randomised and laboratory blinded study, participants received either two doses of Covaxin® (4 weeks apart) or two doses of Covishield™ (12 weeks apart) as per the national vaccination policy. The primary outcome was the seroconversion rate and the geometric mean titre (GMT) of antibodies against the SARS-CoV-2 spike and nucleocapsid proteins post two doses. The secondary outcome was the frequency of cellular immune responses pre- and post-vaccination. Findings: When compared to pre-vaccination baseline, both vaccines elicited statistically significant seroconversion and binding antibody levels in both seronegative and seropositive individuals. In the per-protocol cohort, Covishield™ elicited higher antibody responses than Covaxin® as measured by seroconversion rate (98.3% vs 74.4%, p

Energy management in Micro Grids (MG) has become increasingly difficult as stochastic Renewable Energy Sources (RES) and Electric Vehicles (EV) have become more prevalent. Even more challenging is autonomous MG operation with RES since prompt frequency control is required. We provide an innovative Energy Management Strategy (EMS) for MG with grid support in this academic publication. By integrating RES and EV storage, we seek to decrease reliance on the grid. The EMS consists of three execution phases: Ranking for EV Recommendation (RER), Optimal Power Allocation (OPA) for Fleet, and EV Storage Allocation (OAES). The aim of slicing the time in to smaller in intervals is to update the energy and power scheduling in shorter intervals as per the changes are going on in the system. The period of 24 h is divided into 96 intervals (t) and storage requirements (kWh/t) are estimated based on the estimated load and RES together with the necessary storage volume. We employ three approaches that are frequently used for communication channel power allocation optimization to accomplish OAES. With two objectives: minimum network power loss plus voltage fluctuations, the Multi-Objective Optimization Problem (MOOP) is solved for each 't' based on OAES to provide the Optimal Power Flow (OPF). The Pareto-front is used to calculate the best amount of power from each fleet in each 't'. The data received from the fuzzy rule base is used in the third stage to train an intelligent Convolutional Neural Network (CNN), which has rank of EV as an output and four decision variables as inputs. The main goals in this stage are to minimize battery degradation and to make the most of it for MG support. With the aid of a MATLAB-based simulation setup and heterogeneous entities, the primary goal of EMS is examined and put into practice in an On-grid MG.

Abstract Understanding how we recognize objects requires unravelling the variables that govern the way we think about objects and the neural organization of object representations. A tenable hypothesis is that the organization of object knowledge follows key object-related dimensions. Here, we explored, behaviorally and neurally, the multidimensionality of object processing. We focused on within-domain object information as a proxy for the decisions we typically engage in our daily lives – e.g., identifying a hammer in the context of other tools. We extracted object-related dimensions from subjective human judgments on a set of manipulable objects. We show that the extracted dimensions are cognitively interpretable and relevant – i.e., participants are able to consistently label them, and these dimensions can guide object categorization; and are important for the neural organization of knowledge – i.e., they predict neural signals elicited by manipulable objects. This shows that multidimensionality is a hallmark of the organization of manipulable object knowledge.

Esterified nanofibrillated cellulose (eNFC) with varying degrees of substitution was prepared using fatty acid chloride. Furthermore, the effect of esterification on properties of pure NFC and its composites with polybutylene succinate (PBS) was investigated. Lauroyl chloride (LC) with 12 carbon atoms was used for esterification. An increase in the amount of LC increased the degree of substitution (DS), which significantly decreased the water contact angle and improved the hydrophobicity of NFC. The addition of fatty acid to NFCs lowered their crystallinity. However, the fatty acid increased the hydrophobicity of NFCs, thereby improving their dispersibility in nonpolar solvents. Compared with pure NFCs, eNFC exhibited enhanced compatibility with PBS, and the addition of eNFC with an appropriate DS increased the tensile strength and elastic modulus of PBS. These findings suggest the potential of NFC esterification for improving the performance of NFC-based composite materials.

Background: Thiocolchicoside and chlorzoxazone are commonly used muscle relaxants for the management of acute musculoskeletal pain. However, there is limited evidence comparing their efficacy and safety. Aims and Objectives: The aim of the study was to compare the efficacy and safety of thiocolchicoside and chlorzoxazone in patients with acute musculoskeletal pain. Materials and Methods: This was a randomized, open-label, parallel-group study conducted in a tertiary care hospital. A total of 50 patients with acute musculoskeletal pain were randomized to receive either thiocolchicoside (8 mg) or chlorzoxazone (500 mg) thrice daily for 7 days. The primary outcome measure was the change in pain intensity from baseline to Day 7, assessed using a visual analog scale (VAS). The secondary outcome measures were the percentage reduction in pain intensity and the incidence of adverse events. Results: The baseline characteristics of the patients were similar in both groups. The mean baseline pain intensity was 7.2±1.3 in the thiocolchicoside group and 7.1±1.2 in the chlorzoxazone group. After 7 days of treatment, both drugs significantly reduced pain intensity from baseline. The mean pain intensity at Day 7 was 2.9±1.1 in the thiocolchicoside group and 3.1±1.2 in the chlorzoxazone group. The percentage reduction in pain intensity was 59.7%±12.3% in the thiocolchicoside group and 56.3%±11.5% in the chlorzoxazone group. However, there was no statistically significant difference between the groups in terms of pain intensity reduction (P=0.453). Conclusion: The results of this study suggest that thiocolchicoside and chlorzoxazone are equally effective and safe in the management of acute musculoskeletal pain. The choice of drug may depend on the patient’s individual characteristics and risk factors.

Growth in the advancement of 3D printing technology has made it easy to fabricate complicated bio-inspired structures (BISs). In this paper, the sandwich structure of the beetle elytron structure (BES) hollow cylinder, influencing every corner of the honeycomb structure, is designed by considering parameters like the thickness, length, and diameter of the hollow cylinder, with the different ranges taken giving minimum and maximum values in the response surface methodology (RSM). Sandwich structures are fabricated using VAT polymerization technology. A Universal Testing Machine (UTM) tests the fabricated structures for compression, and results are recorded from the tests of each specimen. All specimens’ compressive strength (CS) and energy absorptions (EA) values are calculated. Design parameters at which the energy absorbed and the compression strength are high are evaluated and considered optimal parameters for a specific range of values.

Currently, researchers are seeking to pay more attention to lightweight designs to minimize the materials used and greatly improve the strength of designs to increase their loading capacity in engineering applications. Bio-inspired patterns are given more attention in the design of these lightweight structures. In this current study, tensile specimens are fabricated as per the ASTM D638-IV standard and through the VAT photopolymerization technique with different bio-inspired patterns like honeycomb, re-entrant, and spider web structures, with unit cell sizes of 4 mm and 6 mm, respectively. Tensile tests are conducted on all the specimens, and all the test results are compared and evaluated to determine the one with the best performance. It was concluded that the 4 mm unit cell size specimens performed well, and spider web structures were shown to have especially satisfactory performance.

Obesity is acknowledged as a significant risk factor for cardiovascular disease, often accompanied by increased inflammation and diabetes. Bioactive peptides derived from marine animal proteins show promise as safe and effective anti-obesity agents by regulating adipocyte differentiation through the AMPK signaling pathway. Therefore, this study aims to investigate the anti-obesity and anti-diabetic effects of bioactive compounds derived from a Meretrix lusoria Protamex enzymatic hydrolysate (MLP) fraction (≤1 kDa) through a 6-week treatment (150 mg/kg or 300 mg/kg, administered once daily) in leptin receptor-deficient db/db mice. The MLP treatment significantly decreased the body weight, serum total cholesterol, triglycerides, and LDL-cholesterol levels while also exhibiting a beneficial effect on hepatic and serum marker parameters in db/db mice. A histological analysis revealed a reduction in hepatic steatosis and epididymal fat following MLP treatment. Furthermore, poor glucose tolerance was improved, and hepatic antioxidant enzyme activities were elevated in MLP-treated mice compared to db/db control mice. Western blot analysis showed an increased expression of the AMPK protein after MLP treatment. In addition, the expression of lipogenic genes decreased in db/db mice. These findings indicate that bioactive peptides, which are known to regulate blood glucose levels, lipid metabolism, and adipogenesis, could be beneficial functional food additives and pharmaceuticals.