Browse Items (7684 total)
Sort by:
-
FEATURE SELECTION AND CLASSIFICATION OF LEUKEMIC CELLS USING IOT AND MACHINE LEARNING
Machine learning and the Internet of Things (IoT) have affected every step of the leukemia process, from diagnosis to understanding to therapy. Consequently, this study delves into the planning of an innovative system that employs IoT and machine learning techniques to precisely differentiate leukemic cells. Depending on the patient's samples, the system uses different ways to feature selection and cell classification. To pick the most informative collection of features that enables stable and accurate cell categorization into suitable categories, the offered research relies on strong machine-learning approaches for feature selection. Next, a classification model is used to classify cells based on their properties using the attributes that have been chosen. There is evidence that the suggested approach can classify leukemic cells with an identification rate of up to 99%, which is greater than the current methods. As a novel strategy for managing massive volumes of biological and medical samples, the suggested method will be an invaluable tool for doctors treating leukemia patients. The system's ability to process data from various Internet of Things (IoT) sources should aid its ability to learn and adapt to real-world clinical settings. With the results of this study in hand, we may be able to detect leukemia sooner, with greater precision, and maybe use more tailored treatments for each patient, leading to better results while reducing healthcare expenditures. 2025, Institute of Mechanics of Continua and Mathematical Sciences. All rights reserved. -
Understanding the drivers of intermittent fasting adoption in middle adulthood
Over the past decade, intermittent fasting has gained into the mainstream limelight as a prevalent method for weight management and to maintain metabolic health. However, the number of studies exploring the determinants affecting its approval, especially among individuals in middle adulthood, is still comparatively under-examined. Hence, the present study has been conducted to gain better insights about the factors influencing the adoption of intermittent fasting among middle-aged adults. By employing snowball sampling, a sample of 260 respondents was surveyed to comprehend the drivers of intermittent fasting, challenges faced in adhering to it and its impact on physiological and psychological health. Factor analysis was employed to group the factors influencing the respondents adherence to intermittent fasting into three categories: longevity-enhancing incentives for intermittent fasting, wellness incentives for intermittent fasting and cognitive enhancement incentives for intermittent fasting. In order to examine the significant differences among the ages of the respondents among the three factors, ANOVA and post-hoc test were conducted. The post-hoc test results provide insight into how motivational factors for intermittent fasting vary across different age groups. For respondents in the age group between 35 to 45 years, the post-hoc results show statistically significant differences in the first factor with the group aged 18-25 and 25-35 years, respectively at 5 % level of significance. The insights garnered from this research are contributory in understanding the factors influencing how and why individuals in middle adulthood embrace intermittent fasting practices. 2025 The Authors. -
BRICS VS. G7: A COMPARATIVE ANALYSIS OF ECONOMIC AND POLITICAL EFFICIENCY IN SHAPING GLOBAL ORDER
The global distribution of power is increasingly shaped by the competing influences of two major blocs: BRICS (Brazil, Russia, India, China, and South Africa) and the G7 (Canada, France, Germany, Italy, Japan, the United Kingdom, and the United States). This paper investigates how BRICS and the G7 shape the emerging multipolar global order. Using comparative analysis of key indicators: GDP, trade flows, investment patterns, diplomatic engagement, and strategic alliances. The paper examines each blocs structure and internal cohesion. The analysis underscores the G7's historical supremacy, which stems from its economic strength and political unity, in contrast to BRICS rising role as a representative for the Global South and a platform for alternative governance models. Important metrics include trade flows, investment trends, diplomatic efforts, and strategic alliances. The research also assesses the internal dynamics within each bloc, including challenges to cohesion and the effectiveness of decision-making. By comparing the advantages and drawbacks of BRICS and G7, this paper provides insights into their respective functions in a multipolar world order, evaluating their ability to promote transformative global agendas. Lastly, the paper concludes that both alliances embody divergent approaches to global governance, reflecting deeper shifts in international collaboration, competition, and the balance of power. 2025, Observare. All rights reserved. -
Impact of Ionic Liquids on the Crystal Growth and Surface Morphology of Ruthenium-doped TiO2 Nano Heterojunction Structures for Improved Photocatalytic Degradation of Evans Blue Dye and the Associated Antibacterial Activities
Novel Ru-doped TiO2 nanocomposites (Ru/TiO2 NCs) were synthesized at a 130 C temperature and 24-h incubation period using hydrothermal methods with and without ionic liquids (ILs). NCs were synthesized using 1-butyl-2,3-dimethylimidazolium tetrafluoroborate as the ILs and titanium(IV) isopropoxide and ruthenium(III) nitrate as the precursors. The presence of Ru in the NCs was analyzed using different characterization techniques. Powder X-ray diffraction and transmission electron microscopy confirmed the presence of anatase and rutile phases as well as the nanocrystalline texture of the prepared Ru/TiO2 NCs. The presence of Ru, Ti, and O was confirmed via energy-dispersive X-ray spectroscopy and X-ray photoelectron spectroscopy. The optical properties and bandgap energies of Ru/TiO2 NCs were determined via ultraviolet (UV)visible (Vis) diffuse reflectance spectroscopy; the optical properties exhibited a redshift in the optical response toward the visible region owing to the reduced bandgap energy of Ru/TiO2 NCs in the visible region after doping Ru into the TiO2 nanocrystalline structure. Scanning electron microscopy images revealed a highly voluminous and porous network of Ru/TiO2 NCs. Moreover, different concentrations of Ru were doped into the TiO2 matrix to investigate the photocatalytic and antibacterial activities. Among all the synthesized NCs, 0.3-wt% Ru/TiO2 NCs exhibited high photocatalytic degradation efficiency and was therefore considered the optimum concentration. Moreover, it exhibited the highest BET surface area and quantum efficiency compared with other Ru/TiO2 NCs. Results revealed that Ru/TiO2 NCs synthesized via IL-assisted hydrothermal method, i.e., R3TL, exhibited considerably enhanced photocatalytic and antibacterial activities compared to the NCs synthesized without the ILs, i.e., R3TH. The inhibition pattern showed an excellent zone of inhibition (p < 0.001) in several strains with both NCs (R3TL and R3TH). However, Gram-positive Staphylococcusaureus exhibited a remarkably increased zone of inhibition (35 mm) compared with all the other strains used for R3TH. In contrast, Bacillus sp. exhibited the second largest zone of inhibition (21 mm) for R3TL after S. aureus (34 mm). In summary, this study emphasized the role of ILs and reaction mechanisms. The author(s) 2025. -
Fuzzy Computational Intelligence in Personalized Medicine and Diagnosis
The development of fuzzy computational intelligence (FCI) has emerged as an effective method for personalized medicine and diagnosis. FCI effectively handles uncertainty and imprecision in medical data, facilitating patient-specific treatment recommendations. Conventional diagnostic and treatment methods typically rely on fixed threshold-based approaches, which fail to account for individual variations in patient responses, leading to suboptimal treatment outcomes. This study proposes the personalized treatment recommendation using fuzzy logic (PTR-FC) framework for diabetes (DB) patients to address these challenges. The framework integrates patient-specific data such as blood glucose levels, diet, exercise, and medication history into the fuzzy inference system (FIS), supporting personalized treatment recommendations. The treatment plans are dynamically adapted based on individual patient outcomes using linguistic factors and fuzzy rules (FR). The proposed method dynamically adjusts recommendations in real time, potentially enhancing personalized treatment and improving decision-making in DB management. Additionally, it promotes lifestyle modifications while reducing the risk of medication-induced complications. The effectiveness of the proposed method was compared to conventional methods, demonstrating improved treatment accuracy, increased patient adherence, and reduced adverse health risks. The PTR-FC framework offers a more adaptive and effective approach to DB management, ensuring better patient outcomes. 2009 Tsinghua University Press. -
An Efficient Fuzzy Logic-Integrated Hybrid Deep Learning Framework for Medical Diagnosis
Medical diagnosis involves analyzing symptoms, test results, and patient histories, but uncertainty from vague symptoms and incomplete records complicates the process. Fuzzy logic-based systems address this issue but often depend on manual rule creation, which is time-consuming. This research proposes a hybrid approach integrating fuzzy logic with deep learning techniques (FL-DLT) for intelligent diagnosis. The framework combines adaptive neuro-fuzzy inference system (ANFIS) for handling uncertainty with convolutional neural networks (CNNs) for extracting features from medical images like X-rays and MRIs. ANFIS models relationships between symptoms, results, and diagnoses, while CNNs analyze medical images. Experimental results show high accuracy and reliability, even with noisy or incomplete data. The proposed approach can improve diagnostic accuracy and efficiency, supporting clinicians in decision-making. Key contributions include the development of the FL-DLT framework and its evaluation using a large dataset of patient records and medical images. Additionally, the research offers insights into the application of fuzzy logic and deep learning in medical diagnosis, highlighting their potential to enhance diagnostic outcomes and efficiency in clinical practice. 2009 Tsinghua University Press. -
COSMOLOGICAL DIAGNOSTICS OF BIANCHI TYPE-II BARROW HOLOGRAPHIC DARK ENERGY UNIVERSE; [????????I??? ?I????????? ????????I???? ?????? ?????I? ?????I?? ?????? ???? ?I???I-II]
In this paper, we investigate a Bianchi type II anisotropic cosmological model in the framework of Barrow holographic dark energy, considering both the Hubble horizon and GrandaOliveros scale as infrared cutoffs. To obtain exact solutions of the Einstein field equations, we assume a suitable relation between the metric potentials. Using Hubble cosmic chronometer data, we constrain the model parameters and obtain the best-fit values b4= ?0.091+0.013 ?0.012and H0= 72.32.7 km s?1Mpc?1The H(z) fit shows excellent agreement with observational data and overlaps with ?CDM at low redshifts, with mild deviations at higher z. The physical behaviour of the model is examined through a detailed analysis of cosmological parameters. The deceleration parameter q(z) reveals a smooth transition from an early decelerating phase to the present accelerating epoch. The equation of state parameter ?deshows quintom-like dynamics, evolving across the cosmological constant boundary and entering the phantom regime, consistent with late-time acceleration. Stability is tested using the squared sound speed vs2, which remains positive in the recent Universe, ensuring classical stability. The ?de?dephase plane indicates that both models lie in the freezing region, corresponding to faster acceleration. The statefinder diagnostics (r,s) and (r,q) further confirm the transition from the standard cold dark matter dominated phase to a de Sitter-like attractor, with trajectories showing clear deviations from ACDM. U.Y.D. Prasanthi, D. Tejeswararao, Diddi Srinivasa Rao, Y. Aditya, D. Ram Babu, 2026. -
Precise cervical cancer cell boundary denoising and segmentation with adaptive wavelet-spectral enhancement
Accurate segmentation of cell nuclei in cervical cytology images is crucial for automated cervical cancer screening, yet existing methods struggle with blurred boundaries, noise-induced degradation, and topologically implausible predictions. The current research proposes Cell-Seg Tool, a novel triplet-branch diffusion AI tool that synergistically integrates three innovations to address these limitations. The Wavelet-Enhanced Contour Refinement Branch employs a learnable multi-scale discrete wavelet transform with adaptive coefficient attention to dynamically enhance boundary features across horizontal, vertical, and diagonal orientations. The Adaptive Spectral Noise Suppression module performs dual-domain processing using DCT-based filtering and uncertainty-guided fusion, coupled with bidirectional anchor semantic feedback to couple cross-branch information. The Topology-Aware Hybrid Loss integrates a focal Tversky loss, a persistent homology loss, a directional boundary loss, a skeleton completeness loss, and a diffusion-noise MSE loss for multi-objective optimization. Comprehensive experiments on multiple datasets demonstrate superior performance, achieving 94.45% Dice coefficient and 19.2% reduction in boundary localization error compared to state-of-the-art methods. Unlike prior work that applies these techniques independently, this work demonstrates that their adaptive, synergistic integration within a diffusion-based framework yields substantial improvements in boundary accuracy and topological correctness. 2026 The Author(s). -
BERT-Enhanced Bi-LSTM with weighted cross-entropy for multilingual sentiment classification
With the increasing volume of multilingual user-generated content across social media platforms, effective sentiment analysis (SA) becomes crucial, especially for low-resource languages. However, traditional models relying on context-independent embeddings, such as Word2Vec, GloVe, and fastText, struggle to handle the complexity of multilingual sentiment classification. To address this, we propose an Automatic Multilingual Sentiment Detection (AMSD) framework that leverages the contextual capabilities of BERT for feature extraction and a Bidirectional Long Short-Term Memory (Bi-LSTM) network for classification. Our method, termed Elite Opposition Cross-Entropy Weighted Bi-LSTM (EOCEWBi-LSTM), integrates elite opposition-based learning to optimize hyperparameters and enhance classification accuracy. A weighted cross-entropy loss function further refines the model's sensitivity to class imbalance, thereby improving its performance. The model is trained and evaluated on the NEP_EDUSET corpus, comprising 45,434 tweets in English, Hindi, and Tamil. Experimental results demonstrate notable improvements in precision, recall, F1-score, and accuracy, highlighting the effectiveness of EOCEWBi-LSTM in multilingual sentiment analysis, especially across both high-resource and low-resource languages. The experimental results show that the proposed EOCEWBi-LSTM achieves a high F1-score ratio of 93.83% and an accuracy ratio of 93.83% compared to other existing methods. EOCEWBi-LSTM provides an effective solution for multilingual sentiment analysis, especially for languages with limited resources. 2025 The Author(s). -
Edge criticality in signed graphs admitting a Roman dominating function
A Roman dominating function(RDF) on a signed graph S = (G, ?) is a function f: V (S) ? {0, 1, 2} such that f(N[v]) ? 1 for every vertex v ? V (S) and any vertex v with f(v) = 0 has a neighbour u ? N + P (v) having f(u) = 2, where f(N[v]) = f(v) + ?u?N(v) ?(uv)f(u). The weight of an RDF is ?(f) = ?v?V f(v) and the minimum weight among all the RDFs on S is called the Roman domination number, ?R(S). In this article we explore the concept of edge criticality in signed graphs admitting an RDF by examining the signed graphs S such that ?R(S+uv) < ?R(S), for any pair of non-adjacent vertices u and v of S, such that the edge uv is positive. This work is licensed under https://creativecommons.org/licenses/by/4.0/ -
EXPLORING THE REGULATION OF CHARACTER STRENGTHS: A SCOPING REVIEW ON BALANCING UNDERUSE, OVERUSE, AND OPTIMAL USE FOR WELL-BEING AND PERFORMANCE
Character strengths play a fundamental role in psychological well-being, resilience, and personal development. Traditionally, research in positive psychology has focused on the benefits of character strengths, emphasizing their role in enhancing life satisfaction, fostering positive relationships, and promoting professional success. However, recent studies highlight the critical importance of balance in strength utilization. Specifically, underuse, overuse, and optimal use of strengths can lead to varying consequences across different life domains. This scoping review systematically examined the imbalance of character strengths and its impact on mental health, leadership, and social interactions. A systematic search was conducted across Google Scholar, PubMed, Scopus, and Web of Science, following PRISMA-SCR guidelines. The findings revealed that underuse of strengths is associated with low engagement, passivity, and decreased motivation, while overuse can lead to rigidity, interpersonal conflicts, and burnout. The review further identified contextual moderators (e.g., personality traits, cultural factors, and situational demands) that influence how strengths are applied in everyday life. Based on the findings, this review proposes the Balanced Strength Utilization Model (BSUM), integrating theoretical perspectives and empirical evidence to offer a comprehensive framework for character strength regulation. Future research should focus on longitudinal studies and intervention-based approaches to help individuals optimize strength balance and apply their strengths effectively across different domains. The Author(s). All articles are licensed under the terms and conditions of the Creative Commons Attribution 4.0 International License (CC-BY 4.0 http://creativecommons.org/licenses/by/4.0/). -
SIGNIFICANCE OF NURTURING PERMA FLOURISHING IN HIGHER EDUCATION: AN INTEGRATIVE REVIEW
This integrated review explored the significance of PERMA, a multidimensional well-being framework, and PERMA-based interventions in promoting student well-being within higher education contexts. The literature search resulted in 16 studies, and the synthesizing of key research findings supports the effectiveness of PERMA-based intervention on students overall well-being. The interventions centered on cultivating PERMA (positive emotions, engagement, relationship, meaning, accomplishment) offered as semester courses, classroom-based curricula, or intervention programs were found successful in improving wellbeing, happiness, life satisfaction, motivation, relationship building, engagement in learning, and reducing negative emotions, stress, academic boredom, anxiety, depression. Overall, the review findings demonstrate that embedding a PERMA-based well-being program as a holistic approach in education would foster a supportive learning environment and social connection in promoting individual and collective well-being among the students. Future studies could strengthen the present findings and respond to the limitations of the existing studies, which would provide a better understanding of the application and effects of PERMA-based programs. Copyright: The Author(s). -
Development of a Thin Layer Chromatography method to detect the presence of spiked Steroid drugs in Herbal Crude extracts
This study aimed to develop a better, faster and more efficient TLC method for detecting steroids in the herbal samples. The steroid drugs dexamethasone and prednisolone were considered possible adulterants and were spiked into herbal extracts of neem and amla. Optimization of the TLC mobile phases for better resolution for prominent visualisation of spots was performed with several combinations of solventsnamely, methanol, chloroform, ethyl acetate, toluene, ethanol, isopropyl alcohol, acetic acid and petroleum ether and, spray reagents such as iodine, potassium permanganate, sulphuric acid and, methanol. The optimal result was obtained using chloroform and methanol (9:1, v/v) as the mobile phase and methanol-sulphuric acid (9:1, v/v) as the spraying agent. The method was also able to separate a mixture of dexamethasone and prednisolone in the ratio of 1:1. The retention factors (Rf) for the steroids dexamethasone and prednisolone were within the range of 0.50-0.55 and 0.73-0.83 respectively. The lowest detection limit for the steroid drugs when mixed with herbal samples (neem and amla) was 0.1 g/ml. The developed TLC method is robust and can be conveniently utilised for detecting steroid adulterants in herbal samples. 2026, World Researchers Associations. All rights reserved. -
Isolation and Screening of Chromium-Tolerant Bacteria from Wetland Rhizosphere for use in Sustainable Bioremediation
Heavy metal contamination by hexavalent chromium [Cr(VI)] remains a major ecological threat due to its toxicity and persistence. This study investigated chromium-tolerant rhizospheric bacteria associated with Typha domingensis collected from Doddagubbi Lake, Bengaluru. Twelve isolates were obtained and exhibited diverse colony morphologies, where Gram staining classified the isolates into six Gram-positive and six Gram-negative strains. Physiological screening revealed broad adaptability with several isolates (DL4, DL6, DL11) tolerating up to 7.5% NaCl and DL11 showing thermotolerance up to 50C. pH profiling indicated that multiple strains (DL2, DL4, DL6, DL7, DL8) sustained growth up to pH 10. Biochemical tests showed widespread catalase activity and notable proteolysis, citrate utilisation and amylase production. Molecular identification grouped the isolates into eight taxa, including Brevibacillus brevis, Bacillus subtilis, Paenibacillus cookii, Kocuria rhizophila and several Pseudomonas species. Chromium tolerance assays demonstrated clear differentiation between highly tolerant isolates (DL1, DL2, DL8, DL9), which showed uninterrupted growth from 10100 mg/L Cr(VI) and moderately tolerant isolates that declined beyond 60 mg/L. Quantitative OD??? measurements further confirmed that the highly tolerant group retained OD values >0.55 at 80100 mg/L, whereas sensitive strains dropped below 0.05. These results highlight the strong bioremediation potential of T. domingensisassociated rhizobacteria for Cr(VI)-contaminated environments. 2026, World Researchers Associations. All rights reserved. -
Phytochemicals in Lemongrass (Cymbopogon citratus) Contributing to Growth and Disease Resistance in Goldfish (Carassius auratus Linn. 1758): Integration of Molecular Docking and Statistical Analyses
The ornamental fish industry has experienced significant growth with species like goldfish (Carassius auratus) gaining popularity for their vibrant appearance and ease of care. However, bacterial infections, particularly those caused by Aeromonas hydrophila, pose a significant threat to fish health and market value. In this study, visibly diseased goldfish exhibiting symptoms such as fin rot, black spots, tail rotting and skin lesions were divided into control and treated groups. The treated group was fed lemongrass (Cymbopogon citratus)-coated pellets, while the control group received standard feed. Over a three-week trial, visual improvements, including the healing of fin rot were documented, demonstrating the effectiveness of lemongrass-enhanced feed in promoting recovery and growth. GC-MS analysis of fresh lemongrass leaves identified key bioactive compounds, including citral, tetra decanoic acid, trans-verbenol and 1-undecanol, known for their antimicrobial properties. These findings confirmed the presence of phytochemicals with potential therapeutic applications against bacterial infections. Molecular docking studies further evaluated the interactions of prominent lemongrass phytochemicals: Procyanidin B2, Diosmin, Catechin and Tricin, with A. hydrophila outer membrane protein (3OD9). The results demonstrated strong binding affinities with Procyanidin B2 showing the highest (-8.0 kcal/mol), followed by Diosmin (-7.8 kcal/mol), Catechin (-7.6 kcal/mol) and Tricin (-7.6 kcal/mol), indicating their potential to inhibit bacterial pathogenicity. This study highlights the dual role of lemongrass as a natural growth promoter and antibacterial agent, emphasizing its potential as a sustainable and eco-friendly alternative to antibiotics in aquaculture. By effectively managing bacterial infections and improving fish health, lemongrass offers a promising solution for enhancing sustainability in aquaculture. 2026, World Researchers Associations. All rights reserved. -
Pediococcus pentaceous-mediated fermentation of Gracilaria corticate: A sustainable reutilisation of renewable resource to enhance its nutritional profile, optimised through response surface methodology for improved growth and pathogenic resistance in Oreochromis niloticus
Seaweed, as a functional food and a sustainable alternative to synthetic additives, is gaining attention. It can enhance the nutritive value, improve antioxidant properties and mitigate oxidative stress induced by pathogens. This study investigates the utilisation of fermented seaweeds in feed formulations to reduce oxidative stress, improve fish health and enhance disease resistance. Seaweeds Gracilaria corticate, rich in bioactive compounds such as polyphenols and antioxidants, were fermented using probiotic Pediococcus pentosaceus MK459540. Nile tilapia (Oreochromis niloticus) was fed a diet supplemented with fermented seaweed, which indicates lower levels of Superoxide Dismutase (SOD), Glutathione (GSH) and Glutathione-S-Transferase (GST) activities compared to control and non-fermented seaweeds when challenged with Vibrio harveyi, Aeromonas hydrophila and a mixture of both pathogens. These findings highlight the potential of seaweed, a sustainable and renewable marine resource in advancing aquaculture practices by promoting fish health and immunity. 2026, World Researchers Associations. All rights reserved. -
Study of cognitive adaptiveness of isolated Plant Growth Promoting Bacteria in nutritionally stress condition
The biological processes behind bacterial memory in different species are still under terra incognita. Additionally, the ability of learning through association in prokaryotes is still unknown. Cross-fertilization between the study of multicellular creatures' cognitive capacities and that of bacteria is possible. Therefore, Plant Growth Promoting Bacteria (PGPB) can be used to analyze this cognitive adaptation of bacteria under stress because PGPB is crucial to the maintenance of plant physiology and growth under a variety of stress scenarios. This study focuses on analyzing preliminary evidence of cognitive adaptability in PGPB under nutritional stress conditions. The isolated PGPB were treated with nutritional deprivation in both periodical and non-periodical manners and their performance was compared with the control group. The characteristics of PGPB, such as ammonia production, siderophore production, phosphate solubilization and indole-3-acetic acid, as well as anti-oxidant activities such as DPPH activity, hydroxyl radical scavenging activity and hydrogen peroxide scavenging activities, were analysed and compared to periodically and non-periodically stressed PGPB with control. In the isolated PGPB post-nutrition deprivation treatment, it was evident that the periodically stressed performed better than the non-periodically stress-exposed PGPB compared to the control wherein the isolates produced as high as 2.5510 mol mL-1 ammonia, 23.0406 mgL?1 indole-3-acetic acid, 69.16 0.71 psu siderophore and 123.5780.429mgL-1 phosphate solubilised. Out of the four isolated PGPB, the two novel strains, Paenibacillus alvei SJ6 and Paenibacillus alvei SJ8, have shown to possess the supreme ability to adapt to periodic nutritional stress compared to the other isolates in our study. 2025 World Researchers Associations. All rights reserved. -
Isolation and characterization of plant growth promoting bacteria (PGPB) from the rhizosphere of Spinacea oleracea L.
As the years pass by, there is an increase in abiotic stress conditions around the environment that directly or indirectly affect agriculture around the world. Therefore, there is a dire need to increase the sustainability of plants. Plant Growth Promoting Bacteria (PGPB) play an important role in maintaining the physiology and growth of plants under various stress conditions. This study looks into the isolation and characterization of different PGPB from Spinacia oleracea L. and their tolerance against salinity and commonly used commercial pesticides against the Spinacia family. The techniques used are isolation by serial dilution, 16sRna sequencing, characterization of different PGPB assays for confirmation such as ammonia production, catalase test, phosphate solubilisation, potassium solubilization, siderophore production, indole-3-acetic acid production, biofilm formation assay, halotolerance and tolerance study using Minimal Inhibitory Concentration (MIC). PGPB were isolated and characterized from Spinacia oleracea L., which was under an abiotic stress environment. Isolates were Bacillus clarus, Bacillus licheniformis, Paenibacillus alvei SJ6 and Paenibacillus alvei SJ8, having quantities as high as 78.10.004 mgL-1 phosphate solubilization, 43.8 mgL?1 of indole-3-acetic acid production, 14.5660.011 psu of siderophore production and 0.62 0.027 mol mL?1 of ammonia production. All isolates also had considerable amounts of halotolerance up to 10%, whereas Bacillus licheniformis had 12.5% halotolerance. The bacterial isolates had considerable tolerance against commonly used commercial pesticides against green leafy vegetables such as chlorpyriphos + cypermethrin combination and fungicides such as mancozeb. Therefore, this study looks into the isolation of potential plant growth promoting bacteria that have considerable amount of halotolerance and pesticide tolerance. 2025 World Researchers Associations. All rights reserved. -
Enterococcus faecalis CGz3 alleviating steatosis via BSH-mediated modulation in HepG2 cell-lines
The study aimed to evaluate the therapeutic potential of bile salt hydrolase (BSH)-producing probiotic Enterococcus faecalis CGz3 in alleviating steatosis in HepG2 hepatocarcinoma cells, with non-alcoholic fatty liver disease (NAFLD) induced by cholesterol and oleic acid (OA), focusing on its effects on lipid accumulation, metabolic gene expression and, inflammatory pathways. HepG2 cells were treated with cholesterol and OA to induce lipid accumulation, mimicking non-alcoholic fatty liver disease (NAFLD) conditions. Cells were then incubated with E. faecalis CGz3 for 6 hours at 37C and 5% CO2. Lipid levels were quantified using Oil Red O staining and cholesterol uptake assays, while gene expression of lipogenic, inflammatory and metabolic markers was assessed via quantitative real-time polymerase chain reaction (qRT-PCR). Treatment with E. faecalis CGz3 significantly reduced lipid accumulation from 42.961.35 mg/mL in NAFLD-induced cells to 29.731.26 mg/mL. It down regulated lipogenic genes (SREBP-1c, FAS and ACC) and inflammatory markers (TNF-?, IL-6, CRP, TLR4, TLR9, NF-?B, JNK, ERK) while upregulating PPAR? and AMPK, promoting fatty acid oxidation. No significant cytotoxicity was observed at 6 hours, though prolonged exposure (1224 hours) reduced cell viability. This study introduces E. faecalis CGz3, a novel BSH-producing probiotic isolated from chicken gizzard, as a promising candidate for NAFLD intervention. Its selective modulation of lipid metabolism and inflammation via BSH activity offers a new perspective on probiotic-based therapies for NAFLD, warranting further in vivo and clinical exploration. 2025, World Researchers Associations. All rights reserved. -
Novel Ovate Antenna for Wireless Communication: Characteristic Mode and Time Domain Analyses
In this article, a novel ovate-shaped microstrip antenna (OMSA) is presented for the application in wireless communication. It covers the evolution of a new shape and delves deeper into the resonance mechanism of the proposed design using characteristic mode analysis (CMA). The OMSA resonates at 2.45 GHz and 2.69 GHz with the return loss of ?18.82 dB and ?31.84 dB, respectively. It offers an ultra-wideband performance with 91.46% measured bandwidth. The characteristic impedance and VSWR at 2.4 GHz are 49 ? and 1.3, respectively. By introducing performance enhancement techniques such as ground truncation and a notch in the patch, the antenna resonance characteristics have been enhanced. A prototype of the proposed OMSA has been fabricated and validated experimentally. The time domain characteristics of the proposed OMSA have been simulated for both face-to-face (FtF) and side-by-side (SbS) configurations. The FtF configuration offers better performance, showcasing the group delay of the OMSA < 2 ns and minimal variation along the operating band. The phase linearity is also maintained, minimizing any distortions. The time domain results demonstrate a maximum fidelity factor of 90.62%, reaffirming the suitability of the antenna for wireless communication. The suitability of the proposed OMSA for wireless applications is also validated experimentally by analyzing the group delay and S21 phase linearity of the received signal. 2026, Electromagnetics Academy. All rights reserved.