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This article addresses the crucial challenge of maintaining a reliable power supply in integrated electric systems that combine solar power and energy storage. It focuses on optimizing key parameters for remote photovoltaic, wind, and battery energy storage within the grid, with a primary goal of sustaining 24-hour load demand. The study introduces a comprehensive approach that integrates fuel price dynamics and battery depletion costs into the optimization model for hybrid grids. This approach seeks a delicate balance between sustainable energy usage and cost-effectiveness. To achieve this balance, the research employs genetic algorithms, a robust computational technique. These algorithms play a vital role in calculating discharge-charge cycles and assessing battery health, addressing concerns about battery longevity and performance. Additionally, the study explores a machine learning framework, specifically nested learning, to further enhance the optimization process. Nested learning allows for the development of a sophisticated target function that considers various grid operation parameters and constraints. This machine learning approach enhances the system's ability to dynamically monitor power consumption and generation. Within this machine learning framework, the TD Lambda learning algorithm takes a prominent role in identifying the optimal function. This algorithm is well-known for its efficiency, particularly in non-Markovian scenarios. Its quick convergence enhances the overall performance of the hybrid grid, ensuring efficiency in changing conditions. The research also evaluates the impact of weight factors on various aspects, including battery charging status, algorithmic decisions, and their consequences on optimal energy pricing within the hybrid grid. This comprehensive assessment deepens the understanding of how these weight factors influence grid performance and economic viability.

Background: Acute pulmonary embolism (APE) is the third most common cause of vascular death. Data on APE from India and other low-and middle-income countries is sparse. Objectives: Study the clinical characteristics, prognostic factors, in-hospital mortality (IMH) and 12 months mortality of patients with APE in India. Methods: We prospectively enrolled 186 consecutive patients diagnosed with APE between November 2016 and November 2021 in Madras Medical College Pulmonary Embolism Registry (M-PER). All patients had electrocardiography and echocardiography. High risk patients and selected intermediate risk patients underwent fibrinolysis. Results: 75 % of our patients were below 50 years of age. 35 % were women. The mean time to presentation from symptom onset was 6.04 ± 10.01 days. 92 % had CT pulmonary angiography. Intermediate risk category (61.3 %) was the more common presentation followed by high risk (26.9 %). Electrocardiography showed S1Q3T3 pattern in 56 %. 76 % had right ventricular dysfunction and 12.4 % had right heart thrombi(RHT) by echocardiography. 50.5 % received fibrinolysis. Patients with RHT received fibrinolysis more frequently (78.3 % vs 46.6 %; p = 0.007). In-hospital mortality (IHM) was 15.6 %. Systemic arterial desaturation and need for mechanical ventilation independently predicted IHM. Ten patients (5.3 %) were lost to follow up. One year mortality was 26.7 % (47/176). One year mortality of patients discharged alive was similar among high, intermediate and low risk groups(14.8 % vs 1.9 % vs 10.5 %; p = 0.891). Conclusions: Patients with PE are often young and present late in India. The in-hospital and 12 months mortality were high. Low and intermediate risk groups had a high post discharge mortality similar to high risk patients.

BackgroundPediatric tuberculous meningitis (TBM) commonly causes death or disability. In adults, high-dose rifampicin may reduce mortality. The role of fluoroquinolones remains unclear. There have been no antimicrobial treatment trials for pediatric TBM.MethodsTBM-KIDS was a phase 2 open-label randomized trial among children with TBM in India and Malawi. Participants received isoniazid and pyrazinamide plus: (i) high-dose rifampicin (30 mg/kg) and ethambutol (R30HZE, arm 1); (ii) high-dose rifampicin and levofloxacin (R30HZL, arm 2); or (iii) standard-dose rifampicin and ethambutol (R15HZE, arm 3) for 8 weeks, followed by 10 months of standard treatment. Functional and neurocognitive outcomes were measured longitudinally using Modified Rankin Scale (MRS) and Mullen Scales of Early Learning (MSEL).ResultsOf 2487 children prescreened, 79 were screened and 37 enrolled. Median age was 72 months; 49%, 43%, and 8% had stage I, II, and III disease, respectively. Grade 3 or higher adverse events occurred in 58%, 55%, and 36% of children in arms 1, 2, and 3, with 1 death (arm 1) and 6 early treatment discontinuations (4 in arm 1, 1 each in arms 2 and 3). By week 8, all children recovered to MRS score of 0 or 1. Average MSEL scores were significantly better in arm 1 than arm 3 in fine motor, receptive language, and expressive language domains (P

Abstract A Wireless Sensor Network (WSN) aided by the Internet of Things (IoT) is a collaborative system of WSN systems and IoT networks are work to exchange, gather, and handle data. The primary objective of this collaboration is to enhance data analysis and automation to facilitate improved decision-making. Securing IoT with the assistance of WSN necessitates the implementation of protective measures to confirm the safety and reliability of the interconnected WSN and IoT components. This research significantly advances the current state of the art in IoT and WSN security by synergistically harnessing the potential of machine learning and the Firefly Algorithm. The contributions of this work are twofold: firstly, the proposed FA-ML technique exhibits an exceptional capability to enhance intrusion detection accuracy within the WSN-IoT landscape. Secondly, the amalgamation of the Firefly Algorithm and machine learning introduces a novel dimension to the domain of security-oriented optimization techniques. The implications of this research resonate across various sectors, ranging from critical infrastructure protection to industrial automation and beyond, where safeguarding the integrity of interconnected systems are of paramount importance. The amalgamation of cutting-edge machine learning and bio-inspired algorithms marks a pivotal step forward in crafting robust and intelligent security measures for the evolving landscape of IoT-driven technologies. For intrusion detection in the WSN-IoT, the FA-ML method employs a support vector machine (SVM) machine model for classification with parameter tuning accomplished using a Grey Wolf Optimizer (GWO) algorithm. The experimental evaluation is simulated using NSL-KDD Dataset, revealing the remarkable enhancement of the FA-ML technique, achieving a maximum accuracy of 99.34%. In comparison, the KNN-PSO and XGBoost models achieved lower accuracies of 96.42% and 95.36%, respectively. The findings validate the potential of the FA-ML technique as an active security solution for WSN-IoT systems, harnessing the power of machine learning and the Firefly Algorithm to bolster intrusion detection capabilities.

Introduction: Follow-up of the mothers and their offspring recruited to a randomized controlled trial comparing neonatal outcomes in women with gestational diabetes treated with metformin or glibenclamide was conducted 9 years ago. A significant decrease in neonatal hypoglycemia in the group treated with metformin was seen in the original study. Methodology: Results of clinical examination, blood sample collection, and dual-energy X-ray absorptiometry (DEXA) scan not published in a brief communication are described in this study. The nutritional status was assessed using a 3-day recall method using the Indian Food Composition Table 2017. The physical activity of offspring was assessed using the Global Physical Activity Questionnaire. Results: The overall follow-up rate of the cohort was 49% and similar in both the groups. The anthropometric details, blood tests, and DEXA in the women and their offspring were similar except that the offspring of the group on metformin had higher triglyceride values than the offspring of the women treated with glibenclamide. The average body mass index of the offspring was similar and was 18. Currently, women who were treated with glibenclamide 9 years ago had higher fasting plasma glucose levels (9.2 [7.3, 12.6]) than the metformin group (7.2 [6.1, 8.4] median [interquartile range]), P = 0.02. They also had significantly higher diastolic blood pressure readings 77.1mmHg (8.9) and 72.1mmHg (11.7) mean (SD), P = 0.035. (Information from the previously published brief communication). Conclusion: No significant adverse outcome was seen in women treated with metformin and the offspring 9 years later.

One can understand the period and the customs of the people through the literature of that time. The theory of feminism arose in the context of modernism in the late 19th century in the English speaking world. Feminism has been put forward in society as an intellectual principle and as a tool of mitigating the struggle suffered for ages. Feminism arose out of seeking freedom and emancipation for women as an alternative and remedy to oppression, violence and social exclusion, to uncover many forms of female oppression. Despite having all the virtues of family responsibilities, bearing children, love and affection, the woman is pushed to the point of curtailing her needs and desires for the benefit of others. Such servitude is more prevalent among women in Sangha literature. But today's women are capable and capable of working in all fields. In that way, the purpose of this article is to compare and analyze Samgam literary women and contemporary women.

Prof. Na. Subbu Reddiar has been published texts in various contexts. He has written hundreds of books in the fields of religion, philosophy, literature, grammar, sociology, science and children's literature and has made great contributions to Tamil Society. The majority of the texts written by the professor are religious. Prof. Na. Subbu Reddiar's book, “Introduction to Saiva Sidhantham”, explains the basic tenets of Saivam. In this book, he explains the philosophy of Saiva Sidhantham in a deep logical approach. Although the philosophical principles in Tamil have been developed through epics since the Sangam period, only “Panniru Thirumurai” form the basic texts of Tamil Saivam philosophy. Saiva Sidhantham has a unique place in the Indian philosophical tradition and is the basis for cultural heritage. Saiva Sidhantham is a philosophy that arose based on three facts. They are Pathi, Pasu, Paasam. This is called a triplet. In the introduction of this book, Prof. Subbu Reddiar has created based on the data on these ideals from Tamil spiritual texts. Prof. P. Krishnan mentions and records “Saiva Sidhantham Or Arimugam” as the first study book on Saiva Siddhanta. In the book, the professor writes logically on the three-dimensional interpretation of two thousand years of philosophical philosophies based on enlightenment, fact-finding, and theory.

Crack development is common occurrence in concrete structural element. By the cracks, which permits the H2O and varies form of chemicals inside the concrete elements and lessen their durability characteristics, properties of strength and which make the rust on rebar when its contact with H2O, Carbon-di-oxide(CO2) including other chemicals. In the concrete structures to repair it needs usual maintenance and particular unique method of treatment but it will not be cost effective. To rectify the issue the mechanism of self-healing is induced in concrete element which assists by generating crystallization of CaCO3 to repair the cracks which helps to clog the micro nano-cracks and endopores. The literatures studies were carried and the bacteria were selected based on the condition of survive in the pH greater than 10. The mix design of M30 concrete grade was designed for the work. The Culturing or Diluting of Calcite Depositing Bacillus Subtilis Bacteria was carried. The casted specimens are to determine the mechanical characteristics of concrete without and with bacteria for different cell concentrations for the comparison. After the curing period, the concrete with bacteria improves the structural properties which were found by the strength characteristics experiments on different cell concentration specimens in comparison with normal concrete. The crack closure and micro structural analysis were carried out by using Ultrasonic pulse velocity test and SEM analysis.

Order Orthoptera is one of the largest and most important invertebrate groups for environmental monitoring and assessment. Orthoptera faunal composition was carried out at Bharathi Park, Coimbatore, Tamil Nadu, India to evaluate the present status of various species. PAST software was used to perform various statistical analyses to estimate the Orthoptera composition. Overall, 334 individuals belonging to 22 species, 19 genera, 17 tribes under 10 subfamilies, and four families of Orthoptera were recorded. Species richness (59.09%) and species abundance (70.06%) were recorded highest in the Acrididae family followed by Pyrgomorphidae, Tettigoniidae, and Gryllidae. Oedipodinae was the most species-rich (27.27%) and the most abundant subfamily, accounting for 30.24% of the total collected individuals. During the study period, 10 dominant, five intermediate dominance, four incidental, and three rare species were observed. Among these, Spathosternum prasiniferum was found to be the most dominant species (D=18.26) and the least dominant (D = 0.6) species was Euconocephalus pallidus. Based on the principal component analysis, the distribution of species along with the first two PCs (PC1= 33.87% and PC2=28.68%) accounted for the highest variance of the total variances. Cluster analysis showed that Acrotylus humbertianus and Teleogryllus mitratus, Conocephalus maculates and Gryllus bimaculatus Orthopterans were similar to each other. The value of the Shannon diversity index (2.27), Simpson index (0.87), Margalef index (2.2), and α-diversity (5.75) were higher in Acrididae when compared with other families. Value of Evenness (0.93) was highest in Gryllidae. Statistical analysis infers that the richness and abundance percentage of Orthopterans significantly varied between species to species and family to family.

Objectives: Patients with ST elevation myocardial infarction (STEMI) without standard modifiable cardiovascular risk factors (SMuRFs; dyslipidaemia, hypertension, diabetes mellitus and smoking) are reported to have a worse clinical outcome compared to those with SMuRFs. However, robust prospective data and low-and middle-income country perspective are lacking. We aimed to study the patients with first STEMI and assess the influence of SMuRFs on clinical outcomes by comparing the patients with and without SMuRFs. Methods: We included all consecutive STEMI patients without prior coronary artery disease enrolled in the Madras Medical College STEMI Registry from September 2018 to October 2019. We collected baseline clinical characteristics, revascularisation strategies and clinical outcome. We analysed suboptimal self-reported sleep duration as a 5th extended SMuRF (eSMuRF). Primary outcome was in-hospital mortality. Secondary outcomes included in-hospital complications and one-year all-cause mortality. Results: Among 2,379 patients, 605 patients (25.4%) were SMuRF-less. More women were SMuRF-less than men (27.1% vs 22.1%; P = 0.012). SMuRF-less patients were older (57.44 ± 13.95 vs 55.68 ± 11.74; P < 0.001), more often former tobacco users (10.4% vs 5.0%; P < 0.001), with more anterior wall MI (62.6% vs 52.1%; P = 0.032). The primary outcome [in-hospital mortality (10.7% vs 11.3%; P = 0.72)] and secondary outcomes [in-hospital complications (29.1% vs 31.7%; P = 0.23) and one-year all-cause mortality (22.3% vs 22.7%; P = 0.85)] were similar in both groups. Addition of suboptimal self-reported sleep duration as a 5th eSMuRF yielded similar results. Conclusions: 25% of first STEMI patients were SMuRF-less. Clinical outcomes of patients without SMuRFs were similar to those with SMuRFs. Suboptimal sleep duration did not account for the risk associated with the SMuRF-less status.

Biologically inspired synthesis of nanoparticles was found to be more attractive in metal nanoparticle synthesis. The present study reported an in-situ biogenic synthesis of silver nanoparticles (AgNPs) using Solanum trilobatum aqueous leaf extract. On this basis, the aqueous leaf extract of S. trilobatum acted as a reducing agent and stabilizing agent to synthesize highly stable AgNPs at ambient temperature. Eventually, the synthesized and stabilized AgNPs surface plasmon resonance was near 430 nm through a UV–visible (UV–vis) spectrophotometer. Here, the stability of the silver colloids monitored through zeta potential and mean particle size was evaluated through diffraction light scattering (DLF). Further, the average particle size was found to be 27.6 nm and spherical, confirmed with transmission electron microscopy (TEM). Also, colloidal AgNPs and aqueous extract are found to be rich sources of antioxidants and exhibit higher free radical scavenging ability. Thus, efficient inhibition with COX1 and COX2 enzymes and the protective effect with human red blood cell (HRBC) membrane stability showed significant results. These features are promising, suggesting the possibility of the AgNPs to be useful to disease-modifying for treating inflammatory disorders and associated complications.

Introduction: Gynura procumbens (Lorr.) Merr. (GP) displays cardio-protective effect, which may hinder atherogenesis induced by oxidized low-density lipoprotein (oxLDL) and leukocytes. The current study was undertaken to elucidate the chemical constituents of GP ethanol extract and its aqueous, chloroform, ethyl acetate, and hexane fractions, and their effects on CD4+ T cell differentiation during atherogenesis. Methods: Initially, the bioactive constituents in GP ethanol extract and its fractions were analyzed using gas chromatography-mass spectrometry (GC-MS). Generated mouse bone marrow dendritic cells (BMDC) were loaded with oxLDL and GP ethanol extract and its fractions for 24 hours and co-cultured with mouse CD4+ T cells for 72 hours. For the determination of T-bet, GATA-3, RORγt, Foxp3, DLL-3, and Jagged-1 mRNA gene expression, the floating cells (CD4+ T cells) and adherence cells (BMDC) were isolated from their total RNAs and reverse transcribed into cDNA.Results: GC-MS analysis showed that GP ethanol extract and its fractions contained various volatile compounds. GP ethanol extract and its fractions also increased the DLL-3 gene but suppressed Jagged-1 gene expression in oxLDL-treated BMDC. Furthermore, GP ethanol extract and its fractions suppressed T-bet, GATA-3, and RORγt gene expression but increased the expression of the Foxp3 gene in differentiated CD4 + T cells. Conclusion: GP ethanol extract and its fractions are composed of various bioactive chemical components that can induce anti-atherogenic effects by inhibiting pro-atherogenic cells such as Th1, Th2, and Th17 cells while increasing anti-atherogenic cells, Treg cells.

In the present work, a facile synthesis of beta-cobalt hydroxide (ß-CoOH) nanosheets from ZIF-67 structure using thermolysis method has been described. The cobalt hydroxide nanosheets grown on carbon cloth would be highly benificial for wide-ranging applications including catalysis and batteries. The XRD studies show that the crystallite sizes are below 100 nanometers for both the ZIF structure and the derived CoOH. The compositional analysis shows that cobalt contributed more to the weight percentage. FESEM images reveal that cobalt nanosheets were grown on the carbon fiber. Also, the TEM images show that nanosheets morphology has been exhibited on the surface of carbon cloth because of the CoOH coating. Further, the chemical composition and purity of the (ß-CoOH) nanosheets on CC were perceived using EDX and XPS analyses.