ISSN:2320-9186
Impact Factor:4.1
ISSN:2320-9186 Impact Factor:4.1
"Water is one of the most important resources for all life on Earth. However, with industrialization, urbanization, and climate change, water bodies around the world are in danger. An important component of water is the amount of oxygen present in it (also known as Dissolved Oxygen). Predicting DO levels can be difficult, espe- cially due to the non-linear nature of its factors, ranging from photosynthesis and respiration to temperature-dependent solubility. Previous models span mechanistic DO–BOD formulations and data-driven methods (SVR, tree ensembles, LSTM), yet inconsistent datasets, non-temporal splits, and missing persistence baselines hinder fair comparison. Thus, this paper explores how various Traditional and Ma- chine Learning Models (Ridge Regression, Random Forest, HistGradientBoosting Regressor, LSTM, GRU and TCN) compare in predicting Dissolved Oxygen."
This study proposes a novel theoretical formulation of a multifunctional nano-fertilizer spray, integrating nano-struvite (MgNH4PO4•6H2O), ammonium sulfate (NH4)2SO4, and calcium sulfate (gypsum, CaSO4•2H2O), stabilized with food-grade additives including potassium sorbate (preservative) and polysorbate-20 (spray adjuvant). Unlike conventional fertilizers, this formulation is designed to function as a slow-release nutrient source of nitrogen (N), phosphorus (P), sulfur (S), and calcium (Ca), while simultaneously acting as a protective spray against pathogens and enhancing soil and plant resilience. The present paper provides a complete theoretical synthesis pathway, chemical interactions, formulation design, potential benefits, applications in agriculture, anticipated challenges, and proposed solutions. This research contributes to the growing field of sustainable nanotechnology in agriculture, providing a new perspective on integrating multifunctionality into fertilizer systems.
Abstract Most people believe that mathematics is a closed field where original mathematical research has been abandoned for decades, which is completely false. The author believes that there are thousands of new mathematical rules and formulas still hidden, waiting to be discovered or generated [1,2,3]. The question arises: how to generate such new mathematics? The author believes that there are three most common methods for generating new mathematics, the choice between them depends on the user's taste, knowledge and experience, namely: i- Use existing mathematics, composed of a nearly infinite number of axioms and theories, to generate new mathematics. Mathematics can generate new mathematics. ii - Use of four-dimensional topology to describe and analyze quantum mechanical systems, based on the 1927 Schrödinger equation, to generate new expressions and formulas describing vacuum dynamics. Fundamental questions about the nature of cosmic space related to the universal laws of thermodynamics, such as the entropy of free space, the density and temperature of dark matter, etc., remain unanswered. iii - Application of the theory of everything, derived from the statistics of B-matrix chains, to the physical control volume currently under study. The third theory iii which is the subject of this article, operates in the most recent and promising space, discovered by the author only in 2020, and yet successfully applied to generate new mathematical and physical rules and theorems, such as: 1 - Generation of a new complex quantum transition matrix Q for the Schrödinger PDE and definition of a complex transfer matrix for the time-independent steady-state solution for the complex ES introduced in 1927. It should be noted that the statistical theory of Cairo techniques (2020) does not apply the FDM techniques, but rather uses the theory and practice of the 4D control volume previously explained in several previous articles. 2 - Generation of a new theory of special and general relativity, other than Einstein's. 3 - Numerical resolution of all types of time-dependent PDEs in their most general form, without resorting to FDM techniques. Finally, it should be noted that the purpose of this article is not to underestimate the great achievements of the great physicists Einstein, Schrödinger, Heisenberg, Minkowski, Hilbert, Rieman, among others, but to address the main flaws in their theories, if any.
This work introduces a new modular end effector design for robotic arms that is capable of autonomous in-field environmental inspection. In contrast to traditional single-purpose end effectors, the design incorporates a microscope, a miniaturized spectrometer, and a set of environmental sensors-all combined in a single portable, reconfigurable module. The platform is capable of real-time sample characterization, in-flight contaminant detection, and surface-level imaging, facilitating intelligent unstructured environment interaction. The innovation is in the architecture's capability to attain faultless sensor fusion and task adaptability without the need for external reprogramming or mechanical adjustment. Autonomous mode switching among inspection, scanning, and analysis is facilitated through a custom control layer based on sensor-provoked triggers. Preprocessing within, real-time data classification, and closed loop control facilitate local decision-making, lessening reliance on external computing resources. To demonstrate robustness, the system is deployed in a dual-mode task: autonomous material handling and warehousing, contaminant detection in materials. The proposed work paves the way for deploying multifunctional robotic manipulators in field robotics, smart manufacturing, and hazardous environment inspection-while offering a unified control framework for adaptive sensing and analysis at the end-effector level.
This study empirically examines the effect of employee motivation on organizational performance within the context of Ivory Coast organizations. Grounded in motivation and performance theory, the research focuses on three critical dimensions of motivation recognition by supervisors, appreciation for performance, and job satisfaction to evaluate their collective and individual influence on organizational outcomes. Adopting a descriptive and explanatory survey design, data were collected from 1,500 employees across public and private sector institutions, encompassing diverse industries such as banking, telecommunications, manufacturing, and public administration. Quantitative data analysis was conducted using EViews 2025, employing multiple linear regression to assess the strength and significance of the relationships between motivational factors and organizational performance. The findings reveal that appreciation for performance (R² = 0.7109) and recognition by supervisors (R² = 0.6684) exert the most substantial positive impact on organizational performance, while job satisfaction (R² = 0.4357) demonstrates a moderate yet significant effect. These results underscore the pivotal role of both intrinsic and extrinsic motivation in enhancing organizational efficiency and productivity. The study concludes that organizations that systematically cultivate recognition and appreciation mechanisms are more likely to achieve superior performance outcomes. Theoretically, this research enriches the discourse on employee motivation by reinforcing the empirical link between motivational practices and performance optimization in developing economies; practically, it provides actionable insights for managers and policymakers aiming to strengthen human capital performance through evidence-based motivational strategies. Keywords: Employee Motivation; Organizational Performance; Human Resource Management; Ivory Coast; Workplace Productivity; Employee Engagement.
ABSTRACT Wild plants play an important role in the diet of most rural dwellers in Nigeria. Medicinal plants are gifts of nature to cure limitless number of diseases. This study aimed to determine the phytochemical contents of the aqueous leaf extract of Senna tora and also to determine the proximate nutritional composition of S. tora leaves. Chemical test for the screening and identification of bioactive chemical constituents in the aqueous leaf extract of S. tora was carried out using the standard procedures as well as the quantity of some of them. Also the proximate composition determination was carried out by different procedures which determine the percentage. The qualitative phytochemical screening of the aqueous leaf of S. tora indicates the presence of alkaloids, tannins, phytosterols, glycosides, flavonoids, phenols, proteins and carbohydrates while saponins and diterpenes are absent. The result shows that flavonoids (0.28mg/100g) constitute the highest concentration and is significantly different with alkaloids (0.72mg/100g), tannins (0.58mg/100g) and phenols (0.26mg/100g) values at P<0.05. The proximate analysis of the leaf shows that the carbohydrate (37.8%) has the highest percentage yield as the nutrient, followed by fibre (20.8%). While fat (6.3%) has the lowest percentage yield. Thus, the leaves of S. tora are of nutritional value (composition) and pharmacological importance as it shows the presence of some vital chemical constituents. KEY WORDS: Senna tora, Phytochemicals, Proximate, Leaf, Pharmacology.
This paper explores the emerging field of solid-state lithium metal anode batteries for electric vehicles (EVs), comparing them with current lithium-ion battery technologies such as LFP, NMC, and NCA. It focuses on how solid-state batteries work and highlights their key advantages: improved safety due to the absence of flammable liquid electrolytes, dramatically higher energy density from pure lithium metal anodes, ultra-fast charging capabilities, and potentially quicker, more efficient production processes. The paper also identifies major technological drawbacks: persistent stability problems (chemical, electrochemical, mechanical, and thermal), performance issues at lower temperatures, short life cycles compared to established chemistries, and high manufacturing costs arising from limited scale. The core of this research examines why these problems arise and reviews cutting-edge solutions—such as interfacial coatings, gradient doping, multi-layer electrolyte designs, composite electrolytes, and advanced cell and thermal management strategies—pointing the way toward more stable, commercially viable solid-state batteries.
This study, entitled “The Impact of AI-Powered Study Applications on Study Efficiency Among Junior High School Students,” aimed to determine how AI-powered study applications influence study efficiency among junior high school students. The research employed a descriptive quantitative method using a structured questionnaire as the main data-gathering instrument. The respondents consisted of ninety-six (96) students from the junior high school population of Bulan National High School. The collected data were analyzed and interpreted through statistical methods to identify usage patterns, purposes, and effects of AI-powered study applications on students’ learning efficiency and academic habits. The findings revealed that most respondents were early adolescents aged 12–14 years, predominantly female, and fairly distributed across Grades 7 to 10, with many achieving high academic performance ranging from 95–97%. A significant 95% of students reported using AI-powered study applications such as ChatGPT, Grammarly, Socratic, or Quizlet AI. Half of the students (50%) used these applications a few times a week, while smaller groups used them daily (10%), occasionally (13%), rarely (23%), or never (4%). Students primarily used AI-powered applications for homework assistance (25%), writing and grammar checking (23%), exam review (19%), summarizing lessons (17%), and solving math problems (15%), with minimal use for research or translation tasks. From these findings, it was concluded that AI-powered study applications positively contributed to students’ learning efficiency and academic engagement. The respondents showed active use of these tools for academic tasks but required guidance to avoid overreliance. Structured training, purposeful use, and alignment with learning objectives were identified as essential to maximizing the benefits of these tools. The study recommended that schools integrate AI-powered study applications into the curriculum, train educators and students on responsible use, and encourage balanced usage to improve academic performance while fostering independent study habits.
Introduction: In sub Saharan Africa, most purchased milk and milk products are obtained from informal, traditional markets which are not rigorously inspected and therefore may expose consumers to harmful pathogens. In Tanzania, only a small amount goes to formal markets and in the processing plants. Purpose: This cross-sectional study was carried out along the smallholder dairy value chain in two districts of Tanzania to collect evidence on the potential risks to consumers from contaminated milk. Specifically, we intended to (1) evaluate the practices of actors that may compromise milk quality, (2) estimate the microbial load in the milk samples, in particular, assess levels of mesophilic aerobes, coliforms and Staphylococcus coagulase positive (SA), as well as (3) identify priority pathogens in the dairy value chain in the study sites. Methodology: We surveyed 114 value chain actors using a questionnaire and observation checklist. Subsequently, milk samples were collected at each site where the survey was conducted. Conventional laboratory methods following standard ISO procedures for food microbial analyses were used. Findings: We found very few actors implementing proper handling and hygienic practices during and post milking practices. Contamination was detected in over 90% of samples for total plate count (TPC) and coliform plate count (CPC) at levels below standard (Grade 2) acceptable in the Eastern Africa countries (EAC) of not more than 2.0x105 and 5.0 x 104 CFU/mL in the raw milk, respectively. There was a significant higher contamination in the household (producer) samples than in the supplier node for TPC and in the household compared to street vendor for CPC (p<0.05). Also, there was a strange high recontamination in boiled milk samples. SA count of 5.1x105 CFU/mL estimated in one sample indicates a possible risk to Staphylococcal poisoning in the milk. Bacteria identified were Enterobacteriaceae, Escherichia coli, Staphylococcus aureus, Listeria innocua, L. ivanovii, L. monocytogenes, coagulase-negative staphylococci, Klebsiella spp., Proteus spp. and Bacillus cereus. Unique contribution to theory, practice and policy: This study was conducted to evaluate the status of milk handling along the dairy value chain and to establish how this can contribute to microbial contamination, which could serve as a basis of stringent hygienic control measures along milking and handling practice from production to consumption to enhance quality of milk.
The general objective of this study was to determine the Influence of Facebook in Promoting Peace to the First Year College Students of MSU – Maguindanao. Specifically, the study aimed to answer the following questions: 1. What is the profile of the respondents in terms of: 1.1) Age, 1.2) Gender, 1.3) Colleges?; 2. To what extent is the influence of Facebook to the respondents in terms of:2.1. Academic Influence; 2.2. Social Influence; 2.3. Personal Influence; 2.4. Environmental Influence?; 3.What are the contributions of Facebook in promoting peace to the first year college students of MSU – Maguindanao?; 4. What are the challenges encountered among the first year college students of MSU – Maguindanao on using Facebook as a source of information? Based on the data gathered, the following were the major findings of the study: 1. Majority of the respondents were female, most of them were between the ages of 19 – 20. Most of the respondents were from the College of Public Affairs and Governance with a frequency of 20 or 32.79 %; 2. The first year college students from the different colleges had an average knowledge or awareness on extent of the Influence of Facebook to the respondents in terms of academic influence, social influence, personal influence and environmental influence an over – all mean of 2.79 for academic influence, 3.26 for social influence, 2.70 for personal influence and 2.94 for environmental influence; 3. The respondents were aware about the contributions of Facebook in promoting peace to the academe; and 4. Generally, the first year college students of MSU – Maguindanao had an average knowledge or awareness about the challenges encountered by them with an over – all mean of 2.87. As they said, ‘they really gained information through Facebook”. Based on the findings it showed and concluded that majority, if not, all of the first year students studying from Mindanao State University – Maguindanao were using Facebook as their medium to gather information that concerns their education, environmental protection, peace advocating and self – satisfaction. Throughout the collation of the result of the study, it was clearly shown that the students, as respondents, were aware of the different usage or importance of Facebook. Also, to conclude, the students, as respondents, were obscure of their responsibilities as a students and as millennials as well, who, in one way or another, balanced their time as academic striving students, environmental and peace advocates, and also as typical adolescents who used social networking sites. Keywords: Facebook, Promoting Peace, MSU-Maguindanao
Africa, although relatively responsible for global greenhouse gas emissions, remains one of the continent’s most vulnerable to the effects of climate change. Droughts, floods, agricultural losses, and population displacements generate not only humanitarian crises but also profound repercussions on mental health. In this context, climate anxiety, defined as persistent emotional distress linked to awareness and anticipation of climate threats, constitutes an emerging phenomenon that remains understudied on the African continent. This literature review aims to critically analyse current knowledge on the psychological impacts of climate change in Africa and to explore the psychological coping mechanisms developed by individuals and communities. The methodology is based on a narrative review of academic and grey literature published between 2000 and 2025, including studies in mental health, environmental psychology, and the social sciences. The results reveal three main themes: (1) a growing prevalence of emotional distress and fear related to environmental losses and climate uncertainty; (2) the importance of collective resilience factors, such as community support, faith, and local ecological knowledge; (3) significant gaps in empirical research, including the absence of culturally appropriate measurement tools and the lack of longitudinal studies on mental health in the face of climate change. This review highlights the urgent need to develop public policies that integrate mental health into climate action and to encourage interdisciplinary African research on psychological adaptation strategies. Ultimately, understanding and supporting the psychological resilience of African populations is essential for a socially just and sustainable ecological transition. Keywords: Africa, Climate anxiety, Climate change, Adaptation, Resilience