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Abstract Wireless sensor networks play a crucial role in gathering data from remote or hard-to-reach locations, enabling real-time monitoring and decision-making in a wide range of industries and applications. The mobile sink path planning (MSPP) enables mobile sinks (e.g., drones or rovers) to navigate through the environment, collecting data from different sensor nodes, ensuring comprehensive coverage, and adaptively addressing changing conditions. Still, the energy-efficient routing with minimal delay is the challenging aspect. This research focuses on improving data gathering in wireless sensor networks by introducing an efficient routing protocol. In this proposed protocol, sensor nodes are initially deployed using Voronoi diagrams to ensure uniform network coverage. The network is then divided into clusters using the low-energy adaptive clustering hierarchy (LEACH) algorithm for energy-efficient routing. To optimize the path planning of a mobile sink for data collection, we introduce the extended Aquila (ExAq) optimization algorithm, which uses a multi-objective fitness function considering factors such as delay, residual energy, link quality, priority, and distance. Simulation results demonstrate the effectiveness of the proposed ExAq-MSPP protocol in terms of reduced delay, improved network lifetime, higher packet delivery ratio, enhanced residual energy, and increased throughput compared to existing protocols with the values of 1.169, 99.857, 99.920, 0.997, and 255.306, respectively. Thus, the energy-efficient routing and optimizing path planning for mobile sinks, the proposed ExAq-MSPP protocol can extend network lifetime, increase data accuracy, and provide more robust performance under changing environmental conditions.

Objectives: To investigate the genomic differences between two extensively drug resistant, ST16 strains of Klebsiella pneumoniae recovered from patients in the same ICU, one of which was colistin resistant. Methods: Antimicrobial susceptibilities of the isolates were determined using VITEK-2. Hybrid assemblies for both strains were generated using Oxford Nanopore and Illumina technologies. The sequence type, capsule type, O-locus type, antimicrobial resistance determinants and plasmids carried by the isolates were inferred from the genome sequence. The phylogenetic placement, antimicrobial resistance, and virulence determinants of the isolates relative to a collection (n = 871) of ST16 isolates were assessed. Results: Both BC16, a colistin-resistant blood stream isolate and U23, a colistin-sensitive urinary isolate displayed near-identical antimicrobial resistance profiles and genome sequences with varying plasmid profiles. The BC16 genome only had 21 SNPs relative to U23 and belonged to the same capsule, O-antigen locus and multi-locus sequence types. The mgrB locus in BC16 was disrupted by an IS5 element. Phylogenetically, U23 and BC16 were placed on a clade with 4 strains belonging to K-type K48 and O-type O2a as opposed to majority (n = 807) of the strains (K-type K51 and O-type O3b). Conclusions: BC16 was a colistin resistant derivative of U23, which evolved colistin resistance by an IS5-mediated disruption of the mgrB locus, likely during treatment of the index patient with colistin in the ICU. The strains belong to a rare subtype of ST16 with unique capsular and O-antigen types underscoring the utility of genomic surveillance networks and open-access genomic surveillance data in tracking problem clones.

“Are we asking the right questions?” seems cliché, but for ChatGPT, it is a pivotal tool to ensure the accuracy of responses. While ChatGPT-3.5’s training on the vast database promises to revolutionize STEM education and research, this investigation shows the importance of precise communication and prompt engineering in guiding ChatGPT-3.5 toward reliable and accurate responses, particularly in chemistry. For instance, emphasizing context, clearly defining symbols, and focusing on field-specific instructions can dramatically improve its performance. Furthermore, avoiding open-ended prompts and strategically using repetition can further enhance its accuracy. The iterative prompt design, demonstrated through a series of adjustments, illustrates how seemingly minor refinements, such as substituting “least” for “lowest”, profoundly impact the output. This study highlights the essential role of human oversight, including the construction of well-crafted prompts, in guarding reliable information and nurturing a productive “Human–AI” (HAI) partnership.

Abstract Background Tuberculosis (TB) lymphadenitis is the most common form of extra-pulmonary TB, and the treatment duration is six months. This non-inferiority based randomized clinical trial in South India evaluated the efficacy and safety of a four-month ofloxacin containing regimen in tuberculosis lymphadenitis (TBL) patients. Methods New, adult, HIV-negative, microbiologically and or histopathologically confirmed superficial lymph node TB patients were randomized to either four-month oflaxacin containing test regimen [ofloxacin (O), isoniazid (H), rifampicin (R), pyrazinamide (Z) -2RHZO daily/ 2RHO thrice-weekly] or a six-month thrice-weekly control regimen (2HRZ, ethambutol/4RH). The treatment was directly observed. Clinical progress was monitored monthly during and up to 12 months post-treatment, and thereafter every three months up to 24 months. The primary outcome was determined by response at the end of treatment and TB recurrence during the 24 months post-treatment. Results Of the 302 patients randomized, 298 (98.7%) were eligible for modified intention-to-treat (ITT) analysis and 294 (97%) for per-protocol (PP) analysis. The TB recurrence-free favourable response in the PP analysis was 94.0% (95% CI: 90.1–97.8) and 94.5% (95% CI: 90.8–98.2) in the test and control regimen respectively, while in the ITT analysis, it was 92.7% and 93.2%. The TB recurrence-free favourable response in the test regimen was non-inferior to the control regimen 0.5% (95% CI: -4.8-5.9) in the PP analysis based on the 6% non-inferiority margin. Treatment was modified for drug toxicity in two patients in the test regimen, while one patient had a paradoxical reaction. Conclusion The 4-month ofloxacin containing regimen was found to be non-inferior and as safe as the 6-month thrice-weekly control regimen.

Ramya Manoharan,1 Chythra Somanathan Nair,1 Nermin Eissa,2 Hao Cheng,3 Pengliang Ge,4 Maozhi Ren,3 Abdul Jaleel1 1Department of Integrative Agriculture, College of Agriculture and Veterinary Medicine, United Arab Emirates University, Al Ain, United Arab Emirates; 2Department of Biomedical Sciences, College of Health Sciences, Abu Dhabi University, Abu Dhabi, United Arab Emirates; 3Institute of Urban Agriculture, Chinese Academy of Agricultural Sciences, Chengdu National Agricultural Science and Technology Center, Chengdu, People’s Republic of China; 4College of Plant Science & Technology, Huazhong Agricultural University, Wuhan, People’s Republic of ChinaCorrespondence: Abdul Jaleel, Department of Integrative Agriculture, College of Agriculture and Veterinary Medicine, United Arab Emirates University, Al Ain, United Arab Emirates, Tel +9713-7134558, Email abdul.jaleel@uaeu.ac.aeAbstract: Cancer has emerged as a formidable global health challenge, with treatment methods like chemotherapy and radiation often exacerbating the situation due to their associated side effects. Opting for natural sources like plants as a safer and environmentally friendly alternative seems promising. Historically, plants have served as valuable sources for treating diverse health conditions, attributable to their rich composition of therapeutic phytochemicals. Within this array of phytochemicals, alkaloids, especially those found in the Solanaceae plant family, are notably prominent. Alkaloids from Solanaceae plant family called Solanum alkaloids demonstrate noteworthy anti-tumour characteristics and exert a potent inhibitory influence on cancer cell proliferation. They trigger programmed cell death in cancerous cells through various molecular pathways, whether administered alone or combined with other medications. Solanum alkaloids act upon cancer cells via multiple mechanisms, including apoptosis induction, suppression of cell growth and migration, as well as inhibition of angiogenesis. This review provides insights into the anti-cancer attributes of Solanum alkaloids found in various Solanum plant species, along with a brief overview of their other medicinal properties.Keywords: Solanum alkaloids, anticancer, apoptosis, molecular mechanism, structure function relationship, therapeutic values

Background: Teachers are the foundation of any civilized society, as they preserve information, wisdom, and ideals. The study was conducted to analyze the Health-Related Quality Of Life among private school teachers and associate the findings with various demographic and occupational parameters. Methodology: This cross-sectional study was conducted among 300 private school teachers in Chengalpattu district from March-to May 2024.Sample size was determined by multistage random sampling technique. A semi-structured questionnaire consisting of background, occupation related details, and SF-36 to assess the HRQOL were used to collect data. Data was entered in excel and analysed using SPSS version 26. Results: Out of 300 teachers,233 were female and 152 were above the age of 40. Most affected domains were Bodily Pain and General Health Perception. In both these domains, very low mean levels of quality of life were significantly associated with teachers age more than 40 years old, those who got monthly income of more than 40k, married, teaching experience more than 20 years, those who travelled more than 60 minutes to reach school and those who had comorbidities. Conclusions: At least one variable across all domains analysed was associated with lower quality of life scores. Administrators and policymakers must provide appropriate health education or health promotion programs and comprehensive prevention strategies for improving their HRQOL.

A 15-year-old boy was admitted to the intensive care unit of our hospital with complaints of increased urination, extreme tiredness, and nausea for the past 15 days. He had also lost 6.5 kg of weight (almost 10% of total body weight) in 1 month. On admission, his plasma glucose was 780 mg/dL, glycated haemoglobin (HbA1c) 11.6%, serum ketones >10.0 mmol/L, osmolality 346 mosm/kg, arterial pH 7.28, and bicarbonate 9 mEq/L. The C-peptide report initially indicated poor pancreatic beta cell reserve (fasting: 0.41 pmol/mL and stimulated: 0.46 pmol/mL). He was diagnosed with diabetic ketoacidosis and responded well to treatment, after which time he was switched to subcutaneous insulin. Ten days later, in the outpatient clinic, his fasting blood glucose was 132 mg/dL, postprandial blood glucose was 183 mg/dL, and C-peptide had improved to fasting: 0.89 pmol/mL and stimulated: 1.42 pmol/mL. Considering the presence of acanthosis nigricans on the neck, a body mass index in the overweight range, a positive family history of diabetes, and negative tests for pancreatic autoantibodies, an early onset diagnosis of type 2 diabetes mellitus was considered. Insulin was gradually withdrawn, and he was switched to metformin. Sustained recovery of C-peptide in this case indicates that lack of insulin at admission was due to beta cell stunning, rather than a total and irreversible loss of beta cells as expected in type 1 diabetes mellitus. Beta cell stunning is often reversible, as shown in this case.

This paper delves into the increasingly complex domain of Optimal Power Flow (OPF) within modern power systems, enhanced by the integration of unpredictable renewable energy sources. The research originally integrates stochastic photovoltaic and wind energy sources, along with a suite of Flexible AC Transmission System (FACTS) components – including thyristor-controlled series compensators, static VAR compensators, and thyristor-controlled phase shifters. The primary objective is to solve the OPF problem by reducing generation costs while accommodating the variable nature of renewable energy sources and load demands. This study prioritizes the examination of both constant and fluctuating load requirements. The inherent variability of PV and wind energy, along with load demand, is captured through the modelling of probability density functions. This approach enables a more detailed optimization process, incorporating not just the cost of thermal energy generation but also the scheduling costs of renewable sources and associated penalty costs. Moreover, the study examines the strategic placement and sizing of FACTS components, an aspect essential in minimizing the overall cost of power production. Employing both single- and multi-objective optimization algorithms, the research addresses the OPF problem in a modified IEEE-30 bus system through various case studies. The application of the recently developed flow direction algorithm, including its multi-objective variant with an ε-based constraint-handling mechanism to OPF problem is the primary contributions of this work. The results, benchmarked against several advanced metaheuristic algorithms, reveal the proposed algorithm's superior performance. This comprehensive study not only underscores the potential of integrating renewable energy sources into the grid but also highlights the efficacy of intelligent optimization strategies in managing the complexities of modern power systems.

Diabetes mellitus is a chronic disease which causes complications in a large population worldwide. Traditionally, medicinal plants possess numerous bioactive compounds to treat chronic diseases. In this study, the bioactive compounds in Cucumis pubescens Willd. were screened computationally to treat diabetes. Ten ligand molecules from C. pubescens Willd. plant fruit were selected from GC-MS analysis. The target proteins like Lipase-related Protein 2 (2OXE), α – amylase (2QV4) and β – Glucosidase (2ZOX) were retrieved from the PDB databank. The proteins have been selected based on their role in anti-diabetic activity. All ten ligands were docked with all three proteins to identify the suitable ligand possessing high binding energy. The ligand (4H-Pyran-4-one, 2,3-Dihydro 3,5-Dihydroxy-6-Methyl) had a maximum binding energy of -4.3 kcal/mol and -4.4 kcal/mol with the targets 2OXE and 2ZOX respectively. The ligand molecule 1,4-dimethyl-2,3-diazabicyclo[2.2.1]hept-2-ene produced the highest binding energy of -4.7 kcal/mol with 2QV4. The predicted active phytochemicals can be used as natural drug molecules to treat diabetes mellitus in future.

Abstract This study presents the K-means clustering-based grey wolf optimizer, a new algorithm intended to improve the optimization capabilities of the conventional grey wolf optimizer in order to address the problem of data clustering. The process that groups similar items within a dataset into non-overlapping groups. Grey wolf hunting behaviour served as the model for grey wolf optimizer, however, it frequently lacks the exploration and exploitation capabilities that are essential for efficient data clustering. This work mainly focuses on enhancing the grey wolf optimizer using a new weight factor and the K-means algorithm concepts in order to increase variety and avoid premature convergence. Using a partitional clustering-inspired fitness function, the K-means clustering-based grey wolf optimizer was extensively evaluated on ten numerical functions and multiple real-world datasets with varying levels of complexity and dimensionality. The methodology is based on incorporating the K-means algorithm concept for the purpose of refining initial solutions and adding a weight factor to increase the diversity of solutions during the optimization phase. The results show that the K-means clustering-based grey wolf optimizer performs much better than the standard grey wolf optimizer in discovering optimal clustering solutions, indicating a higher capacity for effective exploration and exploitation of the solution space. The study found that the K-means clustering-based grey wolf optimizer was able to produce high-quality cluster centres in fewer iterations, demonstrating its efficacy and efficiency on various datasets. Finally, the study demonstrates the robustness and dependability of the K-means clustering-based grey wolf optimizer in resolving data clustering issues, which represents a significant advancement over conventional techniques. In addition to addressing the shortcomings of the initial algorithm, the incorporation of K-means and the innovative weight factor into the grey wolf optimizer establishes a new standard for further study in metaheuristic clustering algorithms. The performance of the K-means clustering-based grey wolf optimizer is around 34% better than the original grey wolf optimizer algorithm for both numerical test problems and data clustering problems.

Abstract The advancement of Photovoltaic (PV) systems hinges on the precise optimization of their parameters. Among the numerous optimization techniques, the effectiveness of each often rests on their inherent parameters. This research introduces a new methodology, the Reinforcement Learning-based Golden Jackal Optimizer (RL-GJO). This approach uniquely combines reinforcement learning with the Golden Jackal Optimizer to enhance its efficiency and adaptability in handling various optimization problems. Furthermore, the research incorporates an advanced non-linear hunting strategy to optimize the algorithm’s performance. The proposed algorithm is first validated using 29 CEC2017 benchmark test functions and five engineering-constrained design problems. Secondly, rigorous testing on PV parameter estimation benchmark datasets, including the single-diode model, double-diode model, three-diode model, and a representative PV module, was carried out to highlight the superiority of RL-GJO. The results were compelling: the root mean square error values achieved by RL-GJO were markedly lower than those of the original algorithm and other prevalent optimization methods. The synergy between reinforcement learning and GJO in this approach facilitates faster convergence and improved solution quality. This integration not only improves the performance metrics but also ensures a more efficient optimization process, especially in complex PV scenarios. With an average Freidman’s rank test values of 1.564 for numerical and engineering design problems and 1.742 for parameter estimation problems, the proposed RL-GJO is performing better than the original GJO and other peers. The proposed RL-GJO stands out as a reliable tool for PV parameter estimation. By seamlessly combining reinforcement learning with the golden jackal optimizer, it sets a new benchmark in PV optimization, indicating a promising avenue for future research and applications.

Background: Continuous subcutaneous insulin infusion (CSII) pump has shown good outcomes in patients with both type 1 and type 2 diabetes mellitus. Here, we present an individual with type 2 diabetes and obesity who was on a high dosage of insulin and oral hypoglycemic agents (OHA) were able to get diabetes under good control with weight reduction after using a hybrid artificial closed-loop insulin pump system along with glucagon-like peptide 1 receptor agonist (GLP-1RA) and sodium-glucose co-transporter-2 (SGLT-2) inhibitor. Case Presentation: A 60-year-old lady with type 2 diabetes presented with uncontrolled blood sugars despite high doses of insulin and a combination of OHAs. She was also depressed and frustrated due to uncontrolled blood sugars despite repeated changes made in her treatment plan using an insulin pump along with GLP-1RA (dulaglutide) and SGLT-2 inhibitor (empagliflozin). Results: After changing the treatment plan, her HbA1c levels decreased from 10.1% to 7.3% after 3 months. The microalbuminuria reverted to normoalbuminuria (59.9–12.2 µg/mg of creatinine). Improvement has been observed in the fasting C-peptide levels from 0.50 to 0.86 pmol/L and stimulated C–C-peptide levels from 1.2 to 2.05 pmol/L. As she lost nearly 7 kg of weight, she felt satisfied with a better quality of life. Even her depression settled down. Conclusion: Use of CSII pump along with dulaglutide and empagliflozin helped in controlling blood sugars, bringing down weight with an overall improvement in mental health and renal function; in this, difficult to treat the patient.

The module with multijunction solar cells (MJSC) is an excellent solution for converting solar radiation into electrical energy. Several methods are applied to extract the parameters of the multijunction solar cell. Most of them are analytical and numerical. Metaheuristic algorithms have lately been used for the parameters’ extraction. In specialized literature, only a few multijunction solar cells have been performed to extract the parameters. Therefore, two metaheuristic algorithms are proposed in this paper: the Chameleon Swarm Algorithm (CSA) and the Black Widow Optimization Algorithm (BWOA). The first algorithm (CSA) is applied for the first time to estimate the solar cell and panel parameters, and both algorithms (CSA & BWOA) are employed for the first time for the multijunction solar cell. They are applied considering two models: the single diode model (SDM) and the double diode model (DDM) for the multijunction solar cell, and three work temperatures of the multijunction solar cell. Four statistical tests are used to analyze the performance of the algorithms, the main being root mean square error (RMSE). A comparative study was performed using the other analytical and metaheuristic algorithm. The obtained RMSE is 8.9120260701E-5 for BWOA and 8.9123932518E-5 for CSA model, respectively, in the case of SDM model and 41.5°C, 1.0186359636E-4 for BWOA and 1.0088314434E-4 for CSA model, respectively, in the case of DDM model and 41.5°C. In the case of the solar panel the RMSE is 3.62E-3 for BWOA, 3.6250156794E-3 for CSA model, respectively, in the case of SDM model and 25°C. The best root mean square error results are obtained using the Black Widow Optimization Algorithm for the single-diode model. The lowest value for root mean square error is 8.9120260701E-5. The special feature and merits of the proposed algorithms are that they have better exploration and exploitation ability; thus, they provide the optimal results with reduced computational time. Further, the performance of the two algorithms (BWOA andCSA) is validated using the dataset of the CTJ 30 panel. The BWOA algorithm has a root mean square error that is two times lower than the one in the research literature. The computational time is also calculated. It is around 2 s, which is very competitive for all considered cases. CSA has the lowest computing time for all four cases considered, varying from 1.882829 s to 2.277469 s. Furthermore, variation in the temperature function is studied using the extracted parameters.

This study suggests a more accurate series-parallel hybrid electric vehicle (HEV) energy management control technique based on heuristic adaptive dynamic programming (HADP). This article provides a solution to the energy management problem of Electric Vehicle using the Stimulant Dependent Heuristic Adaptive Dynamic Programming (SDHADP) algorithm. The reinforced Q learning model along with the three-layer feed-forward neural network with backpropagation is detailed with the necessary diagrams and equations. The approach to connecting the battery of a BEV to a residential system is novel and innovative. The experimental results highlight the importance and effectiveness of the SDHADP algorithm using an electric vehicle. This is done with the help of a BV feed-forward neural network with back-propagation. In the model, which is in charge of controlling the system based on the training given by the BV network, Markov decision theory was adopted by scholars as a paradigm for posing and solving planning problems in the face of uncertainty and is in charge of the battery management system.The suggested technique uses online learning control methods to improve upon the efficiency of the traditional Q-learning method by more than 4.55% under the specified real-world driving circumstances.

Rice bean is an underutilized legume crop cultivated in Asia, and it is a good source of protein, minerals, and essential fatty acids for human consumption. Moreover, the leaves left over after harvesting rice bean seeds contain various biological constituents beneficial to humans and animals. In our study, we performed a de-novo transcriptome assembly of rice bean, characterized the WRKY transcription factors, and studied their response to aluminum stress. A total of 46.6 million clean reads, with a GC value of 43%, were generated via transcriptome sequencing. De novo assembly of the clean reads resulted in 90,933 transcripts and 74,926 unigenes, with minimum and maximum lengths of 301 bp and 24,052 bp, and N50 values of 1801 bp and 1710 bp, respectively. A total of 27,095 and 28,378 unigenes were annotated and subjected to GO and KEGG analyses. Among the unigenes, 15,593, 20,770, and 15,385 unigenes were identified in the domains of biological process, molecular function, and cellular component, respectively. A total of 16,132 unigenes were assigned to 188 pathways, including metabolic pathways (5500) and secondary metabolite biosynthesis (2858). Transcription factor analysis revealed 4860 unigenes from 98 different transcription factor families. For WRKY, a total of 95 unigenes were identified. Further analysis revealed the diverse response of WRKY transcription factors to aluminum stress. Collectively, the results of this study boost genomic resources and provide a baseline for further research on the role of WRKY transcription factors in aluminum tolerance in rice bean.

Abstract Vehicular Adhoc Networks (VANET) facilitate inter‐vehicle communication using their dedicated connection infrastructure. Numerous advantages and applications exist associated with this technology, with road safety particularly noteworthy. Ensuring the transportation and security of information is crucial in the majority of networks, similar to other contexts. The security of VANETs poses a significant challenge due to the presence of various types of attacks that threaten the communication infrastructure of mobile vehicles. This research paper introduces a new security scheme known as the Soft Computing‐based Secure Protocol for VANET Environment (SC‐SPVE) method, which aims to tackle security challenges. The SC‐SPVE technique integrates an adaptive neuro‐fuzzy inference system and particle swarm optimisation to identify different attacks in VANETs efficiently. The proposed SC‐SPVE method yielded the following average outcomes: a throughput of 148.71 kilobits per second, a delay of 23.60 ms, a packet delivery ratio of 95.62%, a precision of 92.80%, an accuracy of 99.55%, a sensitivity of 98.25%, a specificity of 99.65%, and a detection time of 6.76 ms using the Network Simulator NS2.

Patients with chronic kidney disease (CKD) are at a higher risk of cognitive impairment. Poor quality of life and decreased compliance are frequently observed with cognitive decline among CKD patients. Cognitive impairment among Stage 5 CKD patients varies with different modalities of treatment, and contradicting results have been reported. Fifty-four medically stable Stage 5 CKD patients undergoing different modalities of treatment were recruited: Patients with Stage 5 CKD on maintenance hemodialysis (HD) (n = 18), continuous ambulatory peritoneal dialysis (CAPD) (n = 18), and conservative management (CM) (n = 18). Eighteen apparently healthy participants were recruited as a control group. The cognitive functions assessed were P300 event- related potential, auditory and visual reaction times (VRTs). Kidney function was assessed by serum creatinine and estimated glomerular filtration rate. Creatinine levels were significantly higher in all three treatment groups compared with the control group. Multivariate analysis revealed a significant association between the CKD groups (n = 54) and the parameters of cognitive function. P300 latency was prolonged in all treatment groups compared with the control group and was significantly prolonged in patients on CM compared with HD and CAPD patients. The VRT of CM patients was found to be significantly higher compared with the control group. The auditory reaction time was significantly prolonged in all treatment groups compared with the control group and in the CM group compared with the CAPD group. Cognitive function was more affected in Stage 5 CKD patients on CM compared with patients undergoing HD or CAPD.

Wan Zhen Janice Ng,1,* James van Hasselt,2,* Bhumika Aggarwal,3 Anand Manoharan4 1School of Biological Sciences, Nanyang Technological University, Singapore, Singapore; 2GSK, Regional Medical Affairs, Bryanston, Gauteng, South Africa; 3Regional Respiratory Medical Affairs, GSK Plc, Singapore, Singapore; 4Infectious Diseases Medical & Scientific Affairs, GSK, Mumbai, India*These authors contributed equally to this workCorrespondence: James van Hasselt, GSK, The Campus, Flushing Meadows, 57 Sloane Street, Bryanston, Gauteng, 2021, South Africa, Tel +27-82-330-8489, Email james.d.van-hasselt@gsk.comBackground: Strong associations between early antibiotic exposure and increased risk of childhood allergies have been established. Antibiotics have the potential to induce microbial dysbiosis that may be linked to allergic conditions. This review examines the limited available evidence on the associations between adult antibiotic use, microbial dysbiosis and atopic conditions.Methods: A systematic literature search was conducted using PubMed and Embase for relevant studies, published between 01– 01– 2000 and 08– 17– 2022. We searched for associations between antibiotic use, microbial dysbiosis, and allergic conditions in adults, defined as over 13 years of age for the purposes of this review.Results: Twenty-one studies were analyzed, with the inclusion of four narrative reviews as scarce relevant literature was found when stricter selection criteria were employed. Relevant studies predominantly focused on asthma. Significant microbial differences were observed in most measures between healthy subjects and subjects with allergic conditions. However, no system-wise and strain-wise associations were evident. Notably, at the phyla level, the Bacillota and Pseudomonadota phyla were associated with asthmatics, while the Actinobacteria phylum was linked to healthy controls. Asthmatics tends to reflect upregulation in the Bacillota and Pseudomonadota phyla in both airway and gut microbiomes.Conclusion: No compelling evidence could be found between adult antibiotic exposure, consequent microbial dysbiosis, and allergic conditions in adults. Our review is limited by scarce literature and therefore remains inconclusive. However, potential implications of antibiotic use impacting on allergic conditions justify additional research and heightened pharmacovigilance in this area.Keywords: atopy, allergic, asthma, microbiome

The intermittent and stochastic nature of Renewable Energy Sources (RESs) necessitates accurate power production prediction for effective scheduling and grid management. This paper presents a comprehensive review conducted with reference to a pioneering, comprehensive, and data-driven framework proposed for solar Photovoltaic (PV) power generation prediction. The systematic and integrating framework comprises three main phases carried out by seven main comprehensive modules for addressing numerous practical difficulties of the prediction task: phase I handles the aspects related to data acquisition (module 1) and manipulation (module 2) in preparation for the development of the prediction scheme; phase II tackles the aspects associated with the development of the prediction model (module 3) and the assessment of its accuracy (module 4), including the quantification of the uncertainty (module 5); and phase III evolves towards enhancing the prediction accuracy by incorporating aspects of context change detection (module 6) and incremental learning when new data become available (module 7). This framework adeptly addresses all facets of solar PV power production prediction, bridging existing gaps and offering a comprehensive solution to inherent challenges. By seamlessly integrating these elements, our approach stands as a robust and versatile tool for enhancing the precision of solar PV power prediction in real-world applications.

It is well known that highly inbred dogs are more prone to diseases than less inbred or outbred dogs. This is because inbreeding increases the load of recessive deleterious variants. Using the genomes of 392 dogs belonging to 83 breeds, we investigated the association between the abundance of homozygous deleterious variants and dog health. We used the number of non-routine veterinary care events for each breed to assess the level of morbidity. Our results revealed a highly significant positive relationship between the number of homozygous deleterious variants located within the runs of homozygosity (RoH) tracts of the breeds and the level of morbidity. The dog breeds with low morbidity had a mean of 87 deleterious SNVs within the RoH, but those with very high morbidity had 187 SNVs. A highly significant correlation was also observed for the loss-of-function (LoF) SNVs within RoH tracts. The dog breeds that required more veterinary care had 2.3 times more homozygous LoF SNVs than those that required less veterinary care (112 vs. 50). The results of this study could be useful for understanding the disease burden on breed dogs and as a guide for dog breeding programs.

Abstract Stress and depression have been reported in gestational diabetes mellitus (GDM). Though inflammation and oxidative stress are associated with depression, there are no reports of link of cardiometabolic risks (CMR) to stress and depression in GDM. Normal pregnant women (control group, n = 164) and women with GDM (study group, n = 176) at 36th week of gestation were recruited for the study. Blood pressure (BP), body composition, heart rate variability (HRV), glycated hemoglobin (HbA1C), markers of insulin resistance, oxidative stress, inflammation and endothelial dysfunction, were assessed. Perceived stress score (PSS), quality of life (QoL) scale, Indian diabetic risk score (IDRS) and Edinburg postnatal depression score (EPDS) were assessed. Association of potential contributors to PSS and EDPS were assessed by correlation and regression analyses. There was significant increase in PSS, EPDS, IDRS scores, HbA1C, malondialdehyde (MDA) (oxidative stress marker) and high-sensitive C-reactive protein and interleukin-6 (inflammatory markers), and significant decrease in total power (TP) of HRV (marker of cardiovagal modulation), QoL and nitric oxide (endothelial dysfunction marker) in study group compared to control group. Though many cardiometabolic risk parameters were correlated with PSS and EPDS, the significant independent association was observed for TP, HbA1C, MDA and interleukin-6. However, interleukin-6 had maximum contribution to PSS (β = 0.550, p

Abstract The emergence of micro‐sources in the energy market to reduce carbon emissions and exploit more renewable generations increases the frequency oscillations of the system. Hence, this paper attempts to develop a robust nonlinear fractional order proportional integral derivative (NLFOPID) controller for frequency regulation of restructured energy systems. A hybrid atom search‐particle swarm optimization (AS‐PSO) is proposed to optimize the gain values of the NLFOPID controller. The proposed control approach enhances flexibility by providing robustness against the RE intermittency. The optimization technique is coded in MATLAB and applied for frequency regulation of a multi‐area energy system developed in Simulink. Initially, the effectiveness of the hybrid algorithm is validated for standard benchmark functions and then implemented for frequency control. The results demonstrate that the proffered AS‐PSO technique performs significantly for various types of transactions in a deregulated energy market than state‐of‐the‐art. The real‐time applicability of the proposed controller is validated using hardware‐in‐the‐loop simulation of the open energy market in OPAL‐RT. The frequency response obtained from the AS‐PSO optimized NLFOPID controller is remarkable compared to other techniques. Furthermore, the closed‐loop stability of the system is examined using bode analysis through an improved Oustaloup approximation technique.

Xanthium strumarium L. finds therapeutic applications in traditional medicines. The objective of the current study was to evaluate the antioxidant activity and to determine the total phenolic contents (TPCs) and total flavonoid contents (TFCs) of hexane, chloroform, ethyl acetate, acetone, methanol, and water extracts obtained from the leaves and stem bark of X. strumarium. Maceration and hot solvent extraction techniques were used to obtain various solvent extracts. 2,2-Diphenyl-1-picrylhydrazyl (DPPH) radical scavenging and ferric-reducing power assays were used to evaluate the antioxidant activity. Folin-Ciocalteu colorimetric and aluminum chloride colorimetric methods were used to determine the TPCs and TFCs, respectively. The extracts from the leaves and stem bark exhibited radical scavenging activity in the ranges of 18.06 ± 0.3-185.67 ± 11.54% and 9.13 ± 0.54-84.18 ± 0.92%, respectively at a concentration range of 200-3000 µg/ml. The positive control, ascorbic acid, exhibited radical scavenging activity in a range of 56.64 ± 1.26-88.98 ± 0.31% at a concentration range of 200-3000 µg/ml. Additionally, the IC50 values of all these extracts were determined. The hexane and chloroform extracts from both leaves and stem bark and methanol leaf extract were found to be the most potent extracts with an IC50 value of < 200 µg/ml for each extract. The IC50 value of positive control, ascorbic acid was determined to be < 200 µg/ml. Furthermore, in the ferric-reducing power assay, ethyl acetate extract from both leaves and stem bark exhibited the highest ferric-reducing power of 0.996 ± 0.101 and 0.947 ± 0.018 at a concentration of 100 µg/ml. Moreover, the methanol extract from the leaves showed the highest TPCs of 133.41 ± 3.23 mg GAE/g of DW of extract followed by the methanol extract from stem bark and the acetone extract from the leaves with TPCs of 121.21 ± 3.14 and 118.01 ± 1.85 mg GAE/g of DW of extract, respectively. Similarly, the methanol extract from the leaves also showed the highest TFCs of 20.61 ± 1.81 mg QE/g of DW of extract followed by the methanol extract from stem bark with TFCs of 14.90 ± 1.18 mg QE/g of DW of extract. From this study, we concluded that various extracts obtained from the leaves and stem bark of X. strumarium exhibited a moderate-to-strong radical scavenging activity and ferric-reducing power and possessed a significant amount of TPCs and TFCs.

Abstract At the end of the last ice age, several Atlantic salmon populations got caught up in the lakes and ponds of the Northern Hemisphere. Occasionally, the populations also got locked when the flow of rivers terminated from reaching the sea due to land upheaval. Therefore, the pattern of evolution shaping the landlocked salmon populations is different from the other anadromous salmons, which migrate between the sea and rivers. According to the theories of population genetics, the effect of genetic drift is expected to be more pronounced in the former compared to the latter. Here we examined this using the whole genome data of landlocked and anadromous salmon populations of Norway. Our results showed a 50–80% reduction in the genomic heterozygosity in the landlocked compared to anadromous salmon populations. The number and total size of the runs of homozygosity (RoH) segments of landlocked salmons were two to eightfold higher than those of their anadromous counterparts. We found the former had a higher ratio of nonsynonymous-to-synonymous diversities than the latter. The investigation also revealed a significant elevation of homozygous deleterious Single Nucleotide Variants (SNVs) in the landlocked salmon compared to the anadromous populations. All these results point to a significant reduction in the population size of the landlocked salmons. This process of reduction might have started recently as the phylogeny revealed a recent separation of the landlocked from the anadromous population. Previous studies on terrestrial vertebrates observed similar signatures of a bottleneck when the populations from Island and the mainland were compared. Since landlocked waterbody such as ponds and lakes are geographically analogous to Islands for fish populations, the findings of this study suggest the similarity in the patterns of evolution between the two.

Transition-metal-graphene nanoribbons (TM-GNR) exhibit unusual optoelectronic properties, however, synthetic access to such materials remains highly challenging. Here, the authors report a quantum chemical substrate design via DFT to access TM-GNR hybrid semiconductors using zwitterionic Bergman cyclization-triggered cascade polymerization.

Nodular lesions can be seen in a wide range of conditions such as infections, granulomatous conditions, neutrophilic disorders, vasculitis, benign tumours and malignant conditions. These numerous aetiologies behind the occurrence of nodular lesions signify the importance of thorough work-up of the patient to diagnose the underlying reason behind the clinical condition. Erythema elevatum diutinum (EED) is a rare vasculitis with variable clinical presentation, the diagnosis of which can be challenging. Extracutaneous signs such as arthralgias, oral and penile ulcers, involvement of the eye and neuropathy have all been linked to it. Various systemic illnesses, infectious diseases, autoimmune diseases, haematological abnormalities and plasma cell dyscrasias are also associated with EED. Such extracutaneous signs in EED patients indicate that the condition may involve several organ systems. Patients with EED should be assessed for systemic manifestations to ensure focused care, since extracutaneous forms of EED may comprise deposition of circulating immune complexes.

Palmyrah young shoot is rich in starch and fiber and provides good glycemic control. Unfortunately, the consumption rate is limited by the presence of bitter and toxic compounds. Reported literatures reveal that thermal treatment especially dry heat processes like milling the flour at more than 80 °C had an impact on toxicity reduction rather than wet heat processes like boiling. As a result, the current study was aimed to investigate the combined effect of wet (boiling) and dry (radio frequency) heat processing on the debittering of young shoot flour in comparison with tray drying. In the study the flour obtained by a combination of boiling and drying was considered as treated flour and without boiling and drying was considered as untreated flour. The combined effect of wet and dry heat processing had an impact on the nutrients but had no effect on bitterness reduction. The study found tray dried untreated flour favored the feasibility of bitterness reduction as compared to other samples. The compounds (FlabelliferinsB, Flabelliferins–II, isomers of flabelliferins, and vitamin C) responsible for bitterness and its intensity were identified by FTMS. Furthermore, the study revealed that debittering process improved the functional properties of young shoot flour compared to raw flour.

Introduction: In head and neck cancer (HNC) radiotherapy, parotid, submandibular, and minor salivary glands are often incidentally irradiated. Hence, Xerostomia is the most significant disabling side-effect, to improve the quality of life, it should be reduced. The study was to evaluate the parotid dose and PTV coverage in post operated Oral cancer patients using Volumetric Modulated Arc Therapy (VMAT) technique.Material and Methods: The authors generated VMAT plans for 14 post operated oral cancer patients, where primary disease crossed midline or nodal stage ≥ 2. The doses to the moderate high-risk volume of the clinical target volume (CTV) and planning target volume (PTV) were 60Gy in 30 fractions. The low-risk volume received a dose to the CTV and PTV of 54Gy in 30 fractions. Plans were made for each patient, and the dose to D95 and D98 of target volumes was analyzed. The mean dose of the parotid and parotid minus PTV volumes were analyzed and compared with target doses (D98 & D95). Results: Median dose to the ipsilateral parotid gland was 54.45Gy and to the ipsilateral parotid gland minus PTV was 45.60Gy while to the contralateral parotid gland median dose was 16.31Gy, (mean is ranging from 14.01 to 17.06Gy) and to the contralateral parotid gland minus PTV was 14.92 (mean is ranging from 12.42 to 15.18Gy) after achieving the 95% coverage of PTV.Conclusion: Better sparing of contralateral parotid glands with the help of VMAT technique in post-operative HNC patients is possible, which can prevent xerostomia in most patients.

Abstract The Optimal Power Flow (OPF) is a primary tool in planning and installing power systems. It attempts to minimize the operating costs associated with generating and transmitting electrical power by modifying control parameters to satisfy environmental, economic, and operational constraints. Implementing an efficient and robust optimization algorithm for the above‐said problem is critical to achieving such a typical objective. Therefore, this paper introduces and evaluates new variants of the Successive History‐based Adaptive Differential Evolutionary (SHADE) algorithm called ESHADE, SHADE‐SFS, and SHADE‐SAP to solve the OPF problems with equality and inequality constraints. Generally, the static penalty approach is widely used for eliminating infeasible solutions discovered during the search phase when searching for feasible solutions. This approach requires the accurate selection of penalty coefficients, accomplished through the trial‐and‐error method. The proposed ESHADE algorithm is formulated using Self‐Adaptive Penalty (SAP) and Superiority of Feasible Solution (SFS) mechanisms to obtain feasible solutions for OPF problems. Two IEEE bus systems are used to demonstrate the effectiveness of the proposed algorithm in handling OPF problems. The fuel cost and active power loss obtained by the proposed algorithm are better than other state‐of‐the‐art algorithms. The results reveal that the proposed framework offers significant advantages over other algorithms.

Background: The objective of study was to assess the knowledge and awareness of the management of biological waste (BMW) among undergraduate students of Dental College, Tamilnadu state. Materials and Methods: Among the students of Dental College in Tamilnadu state, India, a cross-sectional observational research was conducted. A pre-designed questionnaire was distributed to the students. Their expertise and awareness of managing biomedical waste were the variables that were investigated. Results: One hundred and eighty students were participated. The male to female ratio was 1:2, and the average age of responders was 19.76 ± 1.03 years. When it comes to information concerning the management of biomedical waste, an average of 60.33% were correct and 39.57% were incorrect. For their knowledge of the same, 81.35% were correct and 18.65% were incorrect. Conclusion: The findings indicated that students had a high degree of knowledge and understanding regarding the management of biomedical waste.

In this work PV fed Modified Resonant Voltage Multiplier Rectifier (RVMR) has been proposed for the hybrid renewable energy system. PV source energy is maximized in the modified RVMR scheme by applying the perturb and observe (P&O) based MPPT method. To incorporate modified RVMR for PV grid-connected systems and observe the improvement in dynamic response and voltage gain. In the proposed work, voltage gain and efficiency are analyzed and evaluated in the MATLAB/SIMULINK environment.

The present study deals with the extraction and characterization of untreated and silane-treated natural fibers from stems of Psidium guajava (Guava plants) for automobile brake pad applications. The extraction of fibers was done from the Psidium guajava plant stems by the retting process followed by silane treatment. The untreated and silane-treated Psidium guajava fibers were analyzed for chemical, physical, and crystalline properties. These fibers were used in the brake pad composite developed using conventional industrial processes and analyzed for various performance characteristics as per industrial standards. The tribological performance of the developed brake pads was measured using the Chase test following IS 2742 Part-4 of 1994 or SAE J661:2012. It was found that silane-treated Psidium guajava fibers had acrystalline index of 42%, while it was 27% for untreated Psidium guajava fibers. The brake pads developed using silane-treated Psidium guajava fibers showed ahigher hardness of 99, while it was 90 for untreated Psidium guajava fibers proving better results upon the usage of silane-treated Psidium guajava fibers in brake pads. Scanning Electron Microscope studies of Chase tested brake pads that elucidated the plateau formations and back transfers.

Abstract Dingoes arrived in Australia during the mid‐Holocene and are the top‐order terrestrial predator on the continent. Although dingoes subsequently spread across the continent, the initial founding population(s) could have been small. We investigated this hypothesis by sequencing the whole genomes of three dingoes and also obtaining the genome data from nine additional dingoes and 56 canines, including wolves, village dogs and breed dogs, and examined the signatures of bottlenecks and founder effects. We found that the nucleotide diversity of dingoes was low, 36% less than highly inbred breed dogs and 3.3 times lower than wolves. The number of runs of homozygosity (RoH) segments in dingoes was 1.6–4.7 times higher than in other canines. While examining deleterious mutational load, we observed that dingoes carried elevated ratios of nonsynonymous‐to‐synonymous diversities, significantly higher numbers of homozygous deleterious Single Nucleotide Variants (SNVs), and increased numbers of loss of function SNVs, compared to breed dogs, village dogs, and wolves. Our findings can be explained by bottlenecks and founder effects during the establishment of dingoes in mainland Australia. These findings highlight the need for conservation‐based management of dingoes and the need for wildlife managers to be cognisant of these findings when considering the use of lethal control measures across the landscape.

The phyto nanotechnology strategy was executed for the genesis of zinc oxide nanoparticles by applying bark aqueous extract of Acacia nilotica (AN-ZnO NPs). The AN-ZnO NPs emergence was substantiated through a distinct peak at 350 nm in the ultraviolet–visible spectroscopy. The fourier transform infrared spectroscopy exposed the phyto-organic moieties engaged as reduction and stabilization factors in fabricating nanoparticles. The crystalline trait, elemental proportions, spherical and hexagonal geometry of AN-ZnO NPs was witnessed by X-ray diffraction, energy-dispersive X-ray analysis and scanning electron microscopy. The high-resolution transmission electron microscopic technique provided the average size of 35 nm. AN-ZnO NPs presented larger inhibition zone against Candida albicans (22.7 ± 0.32 mm) at 40 µg/mL as an effectual fungicidal agent. Execution of in vitro antiradical scavenging assay of AN-ZnO NPs applying 2,2-diphenyl-1-picrylhydrazyl (DPPH), nitric oxide (NO), hydroxyl radical (OH–), 2,2′-azino-bis-(3-ethylbenzothiazoline-6-sulphonic acid) displayed radical scavenging trait with the minimum inhibitory concentration (IC50) of 34.54 µg/mL, 38.0 µg/mL, 41.34 µg/mL, and 35.41 µg/mL, respectively. Cytotoxic feature against MCF-7 cell line was in a dose-manner with IC50 value of 37.15 µg/mL in addition to apoptotic proteins expressions were displayed by AN-ZnO NPs. An appreciable larvicidal role of AN-ZnO NPs was rendered against Anopheles stephensi with LD50 (0.31 ppm) and LD90 (0.59 ppm), besides acetylcholinesterase inhibition. Further, biofilm origination was remarkably ceased by the Staphylococcus aureus and Klebsiella pneumoniae, respectively. All our experimented reports on AN-ZnO NPs attested the credible applicability of ZnO NPs in biomedical care for health troubles.

In present research, of chitosan loaded plant essential oils (CsEOs) were performed against Pseudomonas aeruginosa (P. aeruginosa), Escherichia coli (E.coli), K. pneumoniae and Staphylococci aureus (S. aureus), also the anti-cancer properties were evaluated against A549 lung cancer cells. Consequently, the CsEOs against P. aeruginosa, E.coli, K. pneumoniae and Staphylococci aureus were shown 24 mm, 22 mm, and 26 mm and 22 mm zones of inhibition respectively. In addition, 500 µg/mL of CsEOs exhibited 92, 89, 88 and 94% of inhibition against P. aeruginosa, E.coli, K. pneumoniae and S. aureus were observed respectively using micro broth dilution broth experiment. Further, cytotoxicity ability of CsEOs against A549 human lung cancer cells were monitored by 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide (MTT) assay, and result of 500 µg/mL concentration was exhibited 58% inhibition against A549 lung cancer cells. Furthermore, the microscopic evidence of 500 µg/mL concentrations of CsEOs treated A549 lung cancer cells was showed irregular morphology in phase contrast microscope. Altogether, both the invitro and morphological experiments of anti-bacterial and anti-cancer study results were conveyed that the CsEOs have excellent anti-bacterial and anti-cancer properties. Finally, the entire study was proposed, the chosen CsEOs was excellent bionanomaterial used to deliver the drugs and bioactive compounds in target sites for inhibit the infectious pathogens and cancer cells.