European Journal of Theoretical and Applied Sciences
European Journal of Theoretical and Applied SciencesNot a member yet
1144 research outputs found
Sort by
The Electromagnetic Unification of Four Forces: Supporting Planck and Rectifying Einstein
Get PDFIt was Zi-Jian Cai and the satellite operators from China, India and USA who led the world people in television to make the electromagnetic unification of four forces, and altogether achieved many important progressions, such as the spatially localized electromagnetic mass structure, the electromagnetic orienting force, the electromagnetic multi-hairy structure, the non-relativity of ideal time and space, the electromagnetic curve and red-shift for gravity, the stable strong force from electromagnetic multi-hairy hybrid, the weak processes from hybrid split and oscillatory pair of bound electrical fields of neutrino, and so on. Especially, it was an important supplement to general relativity of Einstein by the spatially localized electromagnetic mass structure and electromagnetic orienting force, unifying the gravitational force with electromagnetic force, while explaining the neutrino of small mass moving at light speed. Due to the mistake of Einstein in explaining the essence of mass, it would in turn mislead the mathematical field unification later in physics related to mass. Besides, it was unfortunately also a mistake of Einstein on concept of relativity for ideal time and space, which was proven to manifest as non-relativity. On the other hand, it was explained the Planck quantum as the dependence of photo energy only on frequency due to the identical strength of electrical hair of electron and emitted photo, supporting the classical quantum theory. It was herein accomplished the electromagnetic unification of four forces, supporting Planck and rectifying Einstein. 
Oil Exploitation in the Niger Delta: A Case Study of Environmental Costs and Responsibilities
Get PDFThis article delves into scientific research on the intricate topic of the environmental consequences of oil exploration in developing nations, particularly honing in on the Niger Delta area of Nigeria. It assesses the moral responsibilities of multinational oil companies (MOCs) regarding environmental preservation and their societal duties toward local communities. The study presents an examination of the environmental deterioration resulting from oil spills, gas flaring, deforestation, and other activities linked to oil extraction. It also discusses the limitations of environmental regulations and policies in developing countries, which often lack the resources and expertise to enforce them effectively. Additionally, this research article highlights the challenges of holding MOCs accountable for their actions, given their significant economic and political influence. Through a case study of the Niger Delta, this article sheds light on the extent of the environmental crisis in the region and the suffering of local communities. In this paper we discuss the impact of gas flaring, which releases harmful pollutants into the air and contributes to climate change. Furthermore, the report examines the effects of deforestation, which is often linked to oil exploration, and its impact on biodiversity and local livelihoods. The conclusion emphasizes the urgent need for stricter environmental regulations, improved corporate governance, and community engagement to achieve sustainable development in the oil industry. It highlights the importance of a novel framework in decision-making processes by all Stakeholders in this sector. Ultimately, the report calls for a collaborative effort by all stakeholders to address the environmental and social challenges of oil exploration in developing countries. 
Review of Mining and Sanitation Waste Water Management and Their Contribution to Water Contamination in Zambia
Get PDFThis research digs into the convoluted topography of water contamination in Zambia's Copperbelt Province, with an emphasis on the important contributions of mining and sewage effluent. This report provides major conclusions about the origins, types, and effects of contaminants in the region's water bodies based on a thorough review of current research and empirical evidence. Mining activities emerge as a major source of water pollution, with effluent contaminated with heavy metals, sulphates, and other compounds that pose serious hazards to aquatic ecosystems and public health. Despite efforts to improve wastewater treatment, shortcomings persist, resulting in the leakage of toxic effluent into neighboring waterways. Similarly, sewage wastewater contributes to contamination by including faecal coliforms, nutrients, oils, and heavy metals. The effects of water contamination are far-reaching, as indicated by increasing pollutant concentrations in stream sediments and downstream bodies. Aquatic life suffers from habitat destruction, diminished biodiversity, and negative health effects, while communities relying on these water supplies face increased health risks. Given these issues, the paper analyses potential solutions and recommendations for effective wastewater management, with a focus on interdisciplinary collaboration, technical innovation, and regulatory enforcement. Initiatives fostering recycling, resource recovery, and the implementation of advanced treatment technology hold promise for minimizing water pollution and maintaining sustainable water management practices in the Copperbelt Province
Predictive Analysis of the Principal Components that Configure Autistic Spectrum Disorder
Get PDFAt currently, developments regarding to autism spectrum disorder have enabled its diagnostic group to be defined as a multilateral neurodevelopmental disorder characterised by peculiarities in the procedural functioning of perceptual-cognitive parameters, derived from a characteristic connexional form in the pathway of interconnection between intrinsic information and contextual stimuli. In this characteristic process, neuronal networks are involved a fundamental processing task for working memory to be able to perform the set of executive functions with a certain degree of stability, which is severely limited in people diagnosed with this disorder. In this study, the reports of 403 participants diagnosed with the disorder were analysed with the following basic goals: 1) to analyse the relationship between relational deficits and the elaboration of semantic content, 2) to analyse the etiological attribution of the GABAergic pathway responsible for the limitations in these connections and, consequently, 3) to conclude the main predictive-explanatory level of this disorder. The data have been found by means of different statistical tests, both initial correlational tests, statistical calculation processes, univariate one-factor ANOVA tests and final consequential ordinal multinomial logit regression tests. Data found allow us to delimit that the regression equation of the model fitting information explaining the disorder shows a final logit model chi-square: 217.23, with a significant associated critical level (sig: .00), which are complemented by the significantly positive Pearson and Deviance data significantly related to the logit level (sig: .00), which confirms the importance of the predictive-explicative level of the neuronal and semantic variables derived from the GABAergic limitations in order to be able to be converted into the main propositional components of autism as a highly related neurocognitive systemic process. At currently, developments regarding to autism spectrum disorder have enabled its diagnostic group to be defined as a multilateral neurodevelopmental disorder characterised by peculiarities in the procedural functioning of perceptual-cognitive parameters, derived from a characteristic connexional form in the pathway of interconnection between intrinsic information and contextual stimuli. In this characteristic process, neuronal networks are involved a fundamental processing task for working memory to be able to perform the set of executive functions with a certain degree of stability, which is severely limited in people diagnosed with this disorder. In this study, the reports of 403 participants diagnosed with the disorder were analysed with the following basic goals: 1) to analyse the relationship between relational deficits and the elaboration of semantic content, 2) to analyse the etiological attribution of the GABAergic pathway responsible for the limitations in these connections and, consequently, 3) to conclude the main predictive-explanatory level of this disorder. The data have been found by means of different statistical tests, both initial correlational tests, statistical calculation processes, univariate one-factor ANOVA tests and final consequential ordinal multinomial logit regression tests. Data found allow us to delimit that the regression equation of the model fitting information explaining the disorder shows a final logit model chi-square: 217.23, with a significant associated critical level (sig: .00), which are complemented by the significantly positive Pearson and Deviance data significantly related to the logit level (sig: .00), which confirms the importance of the predictive-explicative level of the neuronal and semantic variables derived from the GABAergic limitations in order to be able to be converted into the main propositional components of autism as a highly related neurocognitive systemic process. 
Antibacterial Activity of Eruca sativa Mill Leaves Against Some Pathogenic Bacteria Isolated from Prostatitis Samples
Get PDFThis study was conducted in Hillah city, Babil province in Iraq, to know the extent of the effects of the secondary metabolites, such as flavonoids and terpenoids extract from Eruca sativa Mill leaves, against some bacterial species isolated Prostatitis Samples represented by Escherichia coli, Staphylococcus aureus, streptococcus pyogenes, Pseudomonas aeruginosa, and Klebsiella pneumonieae. An ability of antibacterial was totally completed by utilizing the method of agar well diffusion by preparing three concentrations 25, 50 &100mg/ml. sterile distal water was utilized as a negative control. Flavonoid extract at 50 and 100 mg/ml exhibited significant supremacy at Probability ≤ 0.05 over the negative control when applied to Escherichia coli. Staphylococcus aureus was sensitive to flavonoids and terpenoid compounds at all concentrations under study P≤ 0.05 in comparison with the negative control. Whereas streptococcus pyogenes, Pseudomonas aeruginosa, and Klebsiella pneumonieae are totally resistant to all concentrations of flavonoid compounds and Escherichia coli, Klebsiella pneumonieae, and Pseudomonas aeruginosa fully resistance to all concentration of terpenoid compounds. Lastly, flavonoids and terpenoid compounds in leaves of Eruca sativa respected a good source for controlling some bacterial species isolated from Prostatitis samples, especially against Staphylococcus aureus. 
Shaping the Paradox of Somaliland Talks with Somalia
Get PDFPolitical rigidities created by Somaliland secessionism within Somalia are unsettled, three decades after the failed proclamation of independence in May 1991. Somaliland’s unilateral discourse in search for international recognition encountered significant challenges with no single country officially recognized. Somaliland’s talks with Somalia from 2012 to 2015 collapsed with key issues addressed have not been implemented despite attempts of diplomatic efforts by international facilitators. given the current political landscape in Somaliland's existing political grievances (power arrangements) in the peripherals, recurrent electoral disputes, and the war with Las Anod further exacerbated the political crisis in Somaliland. Despite their protracted and unsuccessful venture, Somaliland should allow internal dialogue with different political actors/stakeholders to debate and discuss the common issues amid future talks through a more inclusive and participatory approach. Consequently, reviving the collapsed talks between Somalia and Somaliland in a situation where Somaliland is facing an internal crisis will weaken Somaliland’s political stand. Yet, both sides should deliberate on the interests of their people. This paper concludes by reshaping the dialogue process by reviewing the factors that led to the collapse of successful dialogue, as well as proposals for future fruitful talks and how to decide the future merger or the relationships between the two sides. 
Human Rights in Nepal's Democracy: Achieving Best Practices
Get PDFThis article outlines the status of human rights practices and provisions within Nepal, a democratic nation where democracy, progress, and the rule of law are interconnected with the preservation of human rights and fundamental freedoms. Nepal, as a democracy, ensures the protection of human rights for its citizens. Over the past few decades, significant strides have been made in enhancing these practices and provisions, particularly in granting rights to marginalized groups as per the 2015 Constitution. However, despite these advancements, the Nepalese government has consistently overlooked recommendations from the Commission to investigate and prosecute human rights violations, as mandated by the Constitution. There is a need for the Nepalese government to prioritize the human rights movement, which faces numerous challenges from activities that contradict the principles of the constitution, democratic norms, and the Universal Declaration of Human Rights. The paper highlights progress in human rights provisions and practices, alongside suggestions to actively ratify the Rome Statute to enhance Nepal's international reputation. 
Pavement Crack Detection and Solution with Artificial Intelligence
Get PDFDetecting and repairing pavement cracks is essential to ensure road safety and longevity. Traditional inspection and maintenance methods are time-consuming, expensive and often inaccurate. In recent years, there has been a growing trend to use artificial intelligence (AI) to automate the process of pavement crack detection and repair. The article focuses on using AI techniques to detect pavement cracks and provide solutions to repair them. The proposed solution is based on using deep learning algorithms to analyze high-resolution images of the road surface. Photos are taken with a vehicle camera or a drone. The deep learning algorithm is trained using a large data set of tagged sidewalk crack images. Once trained, the algorithm can accurately detect and classify the type of cracks on the pavement surface, including longitudinal, transverse, block and crocodile cracks. The algorithm can also determine the severity of each crack and help prioritize repairs. When cracks are detected, the AI system can make recommendations for repair solutions. This includes identifying the appropriate caulk or filler material to use depending on the type and severity of the crack. The AI system can also recommend the most efficient and cost-effective repair method, such as B. Crack sealing, crack filling or deep repair. Overall, using AI to detect and repair cracks in sidewalks offers a more accurate, efficient, and cost-effective solution to keep roads safe and sustainable. By automating the inspection and repair process, this technology can help prevent accidents, reduce maintenance costs, and improve overall road safety. 
Development of a Predictive Modeling Framework for Athlete Injury Risk Assessment and Prevention: A Machine Learning Approach
Get PDFAthlete injuries are a pervasive issue in sports, resulting in significant consequences for athletic performance, career longevity, and overall well-being. To address this challenge, we developed a predictive modeling framework that leverages machine learning techniques to identify athletes at high risk of injury. Our approach integrates a range of athlete-specific data, including demographic, training, and performance metrics, to generate personalized injury risk profiles. A random forest classifier was employed to identify key predictors and classify athletes into high- or low-risk categories. Our results demonstrate a substantial improvement in injury prediction accuracy compared to traditional methods, highlighting the potential of machine learning in athlete injury prevention. This framework has important implications for coaches, trainers, and medical professionals, enabling targeted interventions and optimized athlete performance. Our study contributes to the growing body of research in sports analytics and machine learning, underscoring the importance of data-driven approaches in promoting athlete health and performance. 
Role of Staphylococcus aureus Biofilm in Teeth Plague and Mouth Infection in Al-Rifai District
Get PDFStaphylococcus aureus is one of the furthermost common microbes that can cause opportunistic infections, capable of inflicting potential life-threatening infections such as pneumonia, urinary tract infection, bloodstream infection, and infectious endocarditis. Biofilms are considered the common bacterial mode in the environment and are also, considered the Main cause of clinical and dental infections in our population. A total of 150 swabs from patients who have oral infections and plague from local hospitals and private clinics, then the specimens treated with microbiological and biochemical procedures are done to identify S. aureus. Three methods are used for biofilms to be detected, CRA (Congo Red Agar method), TM (Tube method), and MtP(Microtiter plate method ) the results of CRA can be shown by the appearance of colonies in 82% of the colonies' biofilm producers (slime) and 17.5% non-biofilm producer. In the TM and MtP methods, the results can shower by weak, moderate, and strong adhesive biofilm bacteria. antibiotics susceptibility was accomplished by disc distribution technique on sensitivity (Mulare Hinton) agar and observed High resistance to many antibiotics resulted in biofilm-forming and High sensitivity to other antibiotics.