Volume 21 Issue 8 2026

The human microbiome of the gut has become one of the most important players in the regulation of metabolic, immune, and nutritional processes, with a wealth of studies showing how dietary intake influences microbial communities within the body. Traditional diets based on foods gathered, prepared, and fermented by women could be one explanation for the diversity of the ancestral human microbiome. Conventional fermented foods and plant-centric diets ensured that individuals were constantly exposed to microbes and their metabolic products, including short chain fatty acids, which are crucial for intestinal and immunological homeostasis. Modern research in microbiome biology, however, has added to this knowledge base the idea of the “microgenderome” to emphasize the importance of biological sex and diet-specific behaviour influenced by gender in the development of microbiology. At the same time, innovations such as shotgun metagenomics, multi-omics and machine learningdriven precision nutrition modeling have transformed studies on diet-microbiome relationships. Nevertheless, there still exists several difficulties in terms of methodology, such as high-dimensional computational noise, overfitting in machine learning models, insufficient validation by mechanisms, as well as severe population biases favouring the Western industrialized populations. This review attempts to critically analyse the connection between the traditional dietary behaviours of females and the development of their gut microbiota, as well as the use of novel technological solutions in precision nutrition.

An eco-friendly and effective approach for the preparation of dihydropyrano[2,3-c]pyrazole analogues has been devised Using a magnetically recoverable glucose-coated Fe3O4 nanocatalyst (Glu@Fe₃O₄) under mild green conditions. Ethyl acetoacetate, hydrazine hydrate, aromatic aldehydes, and malononitrile undergoes one-pot, four-component reaction in an EtOH:H2O (4:1) media at room temperature, yielding the appropriate products in good yields (up to 96%) in 15 minutes. The catalyst showed wide substrate compatibility, was magnetically extracted and used again for four successive cycles with no loss of activity and was characterized by FT-IR and XRD studies. This process is a useful and sustainable means to synthesize physiologically significant dihydropyrano[2,3-c]pyrazole analogues because of its simple operation, quick reactivity time, simple handling, catalyst recyclability, and ecologically acceptable conditions.

The study aimed to evaluate the factors that influence employees' turnover intention at Bonga University. The study employed both descriptive and explanatory research design with qualitative and quantitative approaches. The total population of the study was 1504 Academic and Administrative employees of Bonga University. To determine the actual sample, the researcher used a simple random sampling technique for employees to give them an equal chance, and close-ended, questionnaires were used for data collection. The instrument's reliability was tested using the Cronbach alpha test. Data was analyzed using descriptive and inferential statistical methods, using SPSS to estimate causal relationships between employee factors and turnover intention. The finding of the study revealed that all six independent variables have a positive and significant influence on Employee turnover intention and have negative relationship. The mean result has shown most employees in the organization were dissatisfied. Besides the independent variable has significantly explained 74.3% of the variation in Employee turnover intention whereas the remaining 25.7% of its variation may be explained by other variables that were not examined in this study. Based on the findings of the study, it was recommended that the organization must understand the needs of its employees, which will help organizations, adopt certain strategies to reduce turnover.

Certain legal aspects also require looking back to the history of origin to analyze how they are being developed slowly and gradually to reach the present stage. One of such important aspects is safeguarding interests of victims of crimes which traces its origin rooted in different cultures, traditions, systems, etc. in different countries, particularly the countries of the world including the West, through jurisprudential demonstrations over time as the humanity progresses. The perception of victims of crimes as it exists in the modern criminal justice is simply a gradual transformation and reflection of jurisprudential contributions made by jurists living in their cultures, traditions, political philosophy and set-up, and systems of administering justice as determined. The history of classical criminal law and its philosophy fundamentally regarded crime as an offence committed against the State thereby relegating victims to the periphery of criminal justice processes. However, the contemporary victimological jurisprudential discourse emphasizes that criminal justice must not only punish offenders, but also be administered to protect, compensate, rehabilitate and empower the victims. This article aims at providing a jurisprudential analysis of conceptual foundation underlying victim protection, and examines the theoretical contributions like that of natural law theory, utilitarianism, positivism, etc. towards safeguarding the interests of the victims, along with international legal developments regarding the victim-centric approaches in criminal justice systems in Indian context. In short, the article displays that the modern victim jurisprudence is a reflection of a paradigm shift from the earlier offender-centric criminal law approaches towards a balanced framework recognizing victims’ rights as stakeholders in the justice system. While dealing so, special emphasis is given in victimological jurisprudence in Indian criminal justice system. This transformation is very crucial for achieving the goals of substantive justice reinforcing the legitimacy of criminal justice institutions.

Postpartum depression (PPD) is a significant global maternal mental health issue often overlooked, particularly in Northern Nigeria, where the prevalence rate is 17.7% of mothers worldwide (LiuZarzuela et al., 2023; Carlson et al., 2024), and a total fertility rate of 7.5 in Northern Nigeria (NDHS, 2018), increasing vulnerability due to repeated childbirths at short intervals, creating physical and emotional strain. Little is known about how culturally relevant information sources and risk communication influence women’s knowledge and help-seeking behaviours in Niger State. The study seeks to address this gap in alignment with Sustainable Development Goals (SDGs) 3 and 17, which promote maternal well-being and global partnerships for health advancement. A mixed-methods design was adopted, comprising a survey (n = 384) and focus group discussions (FGD) (n = 32). Multistage and purposive sampling techniques were employed, and data were analysed using SmartPLS (Partial Least Squares), SPSS, and Yin’s thematic explanation model. Healthcare providers exerted the strongest influence on PPD knowledge (β = 0.71, p < .01). Social media and radio were other dominant sources of PPD knowledge, whereas family, friends, and television showed minimal influence on. Indigenous media, such as community radio and storytelling, also had a strong influence on knowledge about PPD. Strategic communication skills training emphasising risk communication, empathy, and culturally sensitive patient interaction for medical professionals, along with community-based risk messaging, and digital platforms integration, is recommended to improve knowledge about PPD, early help-seeking and reduce stigma.

This study examines the influence of infrastructure development, in conjunction with two control variables namely population and per capita net state domestic product on the intricate dynamics of economic growth by utilizing the comprehensive time series data spanning from 2001-2019 within the specific context of the region of Jammu & Kashmir. By using the gauge of infrastructure indicators, study uses the principal component analysis (PCA) method for constructing the composite index of infrastructure development. The investigation utilizes the augmented Dickey Fuller (ADF) test to observe the stationary nature of the data series. Additionally, Granger causality models are employed to examine the causal relationship between economic growth and the composite index of infrastructure development, as well as per capita net state domestic product and population. The application of the auto regressive distributed lag model (ARDL) has been utilized to analyze the intricate relationship between economic growth and composite index of infrastructure development along with population & net state per capita domestic product. The empirical findings elucidate compelling evidence of a pervasive positive influence exerted by the composite index of infrastructure development, population, and net state per capita domestic product on the economic growth of Jammu and Kashmir, both in the short and long run. Moreover empirical results show that composite index of infrastructure development exerted the greatest impact on economic growth than population and per capita net state domestic product in the long run. The findings also signify that the development of infrastructure plays a central role in both expediting the progression of economic growth and ensuring long run convergence in Jammu and Kashmir. Moreover the study elucidates the presence of unidirectional relationship running from composite index of infrastructure development along with population to economic growth and by-directional relationship between economic growth and per capita net state domestic product. From the policy prospective the findings of this study hold great significance to considering the extensive and inclusive economic growth in Jammu & Kashmir; care must be taken to remove bottlenecks in the creation of infrastructure development.

This synthesis examines 1,150 empirical investigations exploring how planetary ecological disruption cascades through global financial architecture. Drawing upon the theoretical heritage of Knightian uncertainty, Polanyi's double movement, and the emerging paradigm of Earth Systems Finance, we develop a unified framework for understanding climate-induced financial transformation. Our analysis reveals four fundamental insights that challenge conventional financial theory. First, the "carbon premium" manifests not as a stable risk-return tradeoff but as an emergent property of socio-ecological systems undergoing punctuated equilibrium shifts, exhibiting phase transitions that mirror thermodynamic irreversibility. Second, physical climate impacts operate through complex adaptive system dynamics wherein localized environmental perturbations propagate through financial networks via nonlinear amplification mechanisms, producing what we term "ecological contagion." Third, regulatory ambiguity generates valuation bifurcations that reflect competing temporal discounting regimes—what Keynes might recognize as "animal spirits" now channeled through climate consciousness. Fourth, institutional absorptive capacity—encompassing state effectiveness, informational transparency, and cognitive frameworks—modulates the velocity of climate risk internalization, revealing profound disparities between jurisdictions that approximate differential equations of institutional inertia. Environmental-certified instruments demonstrate countercyclical protective characteristics during ecological anxiety episodes. We identify critical lacunae concerning biodiversity collapse thresholds, systemic financial cascades, and distributional justice imperatives embedded in energy transition pathways.

Today many distinct products exists along with the configuration. Technology is advancing as well, proposed system deals with promoter system based on KNN clustering techniques. KNN along with filtering mechanism is introduced as a base mechanism to predict most likely products to be promoted through the promoter system. Simulation results indicates that the C-KNN(Content based K nearest neighbour technique is better than individual approaches of KNN and content based filtering

Passive Optical Networks (PONs) have become a popular fiber access network solution because of its service transparency, cost effectiveness, energy savings, and higher security over other access networks. This paper discusses about the evolution and basic structure of Passive Optical Networks. In this paper we discussed about the Access networks, their classifications and its types. How copper networks differs from optical network The Difference between active and passive optical networks and basic system of Passive Optical Networks. We show through analysis that Passive Optical Networks are very cheap and can provide better services as compare to copper access networks. PON is also better option for access networks because it is very cheaper than active optical networks.

In recent times one of the emerging and intelligent tool is Cloud Computing. It has developed a leadingmodel of computing and IT service delivery. Cloud Computing is characterized by three-layered basic service forms such as, Platform-as-a-Service (PaaS), Software-as-aService (SaaS) and Infrastructure-as-a Service (IaaS). Pushinginformation into the cloud extendslargercloseness since users are not necessary to be concerned about the storage capacity, storing techniques, hardware management, or data maintenance. A key problem that requiresspecificconsideration is security of clouds. Existing approaches for secured outsourcing of information and random calculations are either support on a single tamperproof hardware, or based on homomorphic encryption. To overcome existing issues a novel approach is proposed tofocus on security experiments in cloud computing and to provide solutions. To provideunfailing security to the users, the purpose of this paper is in threefolding. 1) To design a mathematical model for trust and reputation calculation. 2) To propose TR-SSalgorithm for calculation of security score. 3) To compare the security score of trust and reputation factors by Fuzzy Logic System, Neural Network.This work is focused on controlling the security issues in cloud environment by means of trust and reputation factors using mathematical model, Trust and Reputation Security Score (TRSS) algorithm, Fuzzy Logic System, Neural Network.

The Box-Jenkins approach, specifically the autoregressive integrated moving average (ARIMA) model, based on the data of the tuberculosis incidence from 2005 -2017 in Tamilnadu, we establish the single ARIMA (2,2,1) model, the combined ARIMA (2,2,1)-ARCH (1) model, and the HW model, which can be used to predict the tuberculosis incidence successfully in Tamilnadu. Comparative analyses show that the ARIMA and ARIMA-ARCH models perform reasonably well, with the ARIMA model being the best in our case. Tuberculosis (TB) remains a major global public health problem, especially for considered as high burden cities in Tamilnadu. It is considered by WHO as one of the high burden countries and tuberculosis incidence continues to be very high. Therefore, there is need to continue monitoring and predicting tuberculosis incidence in an effort to make the control of tuberculosis more effective. To the best of our knowledge, this is the First study to establish the ARIMA model and ARIMA-ARCH model for pre-diction and monitoring the yearly incidence of tuberculosis (TB) in Tamilnadu. Based on the results of this study, the ARIMA (2,2,1) and ARIMA (2,2,1) - ARCH (1) models are suggested to give tuberculosis surveillance by providing estimates on tuberculosis incidence trends in Tamilnadu.