European Journal of Theoretical and Applied Sciences
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Autism Perceptual – Behavioural Precision Scale
Get PDFThe Perceptual-Cognitive-Behavioural Diagnostic Precision Scale for Autism Spectrum Disorder allows to complement the analysis of the autism diagnosis through the measurement of variables the neuropsychological processing of human information to avoid high errors over ASD diagnosis currently existing, derived from unilateral analysis of the behaviour criteria component of the actual Scales. The empirical scoring of the Scale has been verified to N= 75, being 38 participants belonging to the TEA-1 level, 24 to TEA-2 and 13 to TEA-3, has allowed find a statistical reliability of Cronbach's Alpha average greater to .91 in the ten dimensions of the Scale: 1) comprehension, 2) significant, 3) categories, 4) intercategorical 5) relationships-neural-nodes, 6) semantic recovery, 7) social interaction, 8) social communication, 9) stereotyped behaviours, and 10) restrictive behaviours. These ten dimensions have been statistically grouped around three great categories to analysis: 1) perceptual-cognitive processing, 2) social interaction, and 3) behaviour. The conclusive statistical analyses indicate that perceptual-cognitive process category explains 88.52% of total accumulated explicative variance, social category: 10.19% and behaviour: 1.28%; which shows the importance of the perceptual-cognitive dimensional factor analysis, in order to conclude with the mean percentiles of the diagnostic conclusion regarding each ASD´ level, according to International Classification of the American Psychiatric Association DSM-5 (APA, 2023). 
Determinants of Goods/Services Procurement Fraud with Performance Accountability as Moderation in Central Lombok Regency Government
Get PDFThe purpose of this study is to examine the effects of competence and opportunity, as well as organizational commitment to PBJ fraud, directly or with performance accountability as a moderation variable. The study was conducted on a sample of goods and services procurement actors in Central Lombok Regency, with as many as 120 respondents. Data analysis was done using SmartPLS. The results showed the correlation of variables in Goods/Services Procurement Fraud (PBJ) with the principles of agency theory and the fraud triangle. The competence of PBJ implementers has a negative influence on PBJ fraud, in line with agency theory, which emphasizes the importance of highly competent individuals in reducing opportunities for unethical behavior in public agencies. Strong organizational commitment also shows a negative influence on PBJ fraud, confirming agency principles that emphasize adherence to procurement processes. On the other hand, the finding that opportunity has a positive effect on PBJ fraud is in line with the fraud triangle theory, which highlights that opportunity in the procurement system can facilitate fraudulent practices. The role of performance accountability that strengthens the influence of competence and commitment to PBJ fraud is in line with the fraud triangle theory, affirming the importance of accountability in controlling fraud opportunities. These findings consistently support the principles of agency theory and the fraud triangle in the context of the procurement of goods and services in the public sector. 
Beyond Accuracy: Building Trustworthy Extreme Events Predictions Through Explainable Machine Learning
Get PDFExtreme events, despite their rarity, pose a significant threat due to their immense impact. While machine learning has emerged as a game-changer for predicting these events, the crucial challenge lies in trusting these predictions. Existing studies primarily focus on improving accuracy, neglecting the crucial aspect of model explainability. This gap hinders the integration of these solutions into decision-making processes. Addressing this critical issue, this paper investigates the explainability of extreme event forecasting using a hybrid forecasting and classification approach. By focusing on two economic indicators, Business Confidence Index (BCI) and Consumer Confidence Index (CCI), the study aims to understand why and when extreme event predictions can be trusted, especially in the context of imbalanced classes (normal vs. extreme events). Machine learning models are comparatively analysed, exploring their explainability through dedicated tools. Additionally, various class balancing methods are assessed for their effectiveness. This combined approach delves into the factors influencing extreme event prediction accuracy, offering valuable insights for building trustworthy forecasting models. 
Heavy Metal Contamination in Urban Soils: Health Impacts on Humans and Plants: A Review
Get PDFThis research looks at how the growth of cities and industries affects the levels of heavy metals in the soil, which can impact people's health. We find out where the pollution comes from, such as factories, car fumes, and improper waste disposal, by reviewing existing studies. We use different methods to test the soil for heavy metals and study how exposure to these metals in urban areas affects people's health. The evidence shows a connection between high levels of heavy metals in city soil and health problems like breathing issues, brain disorders, and overall toxicity in the body. We also explore how these metals get into the human body, highlighting the importance of understanding how they are available and the ways people are exposed. To deal with polluted city soils, we look at different ways to manage the soil and suggest sustainable methods to reduce heavy metal pollution. Our discoveries add to what we know about urban environmental health, emphasizing the need for actions to protect city residents. Ultimately, this study aims to give important information and insights to policymakers, city planners, and public health officials for managing and lessening the health risks linked to heavy metal contamination in urban soils. 
Application of Weibull Distribution to Hidden Markov Model for Non-Negative Factorization Matrix
Get PDFProbabilistic Nonnegative Matrix Factorizations (NMFs) are very useful in statistics when dealing with stochastic signals such as wave fronts, share prices, and volatility as a Nonnegative Matrix Factorization (NMF) approach. Little attention has been made in the literature to developing NMF algorithms that use moving average to exploit data's temporal dependencies. A hidden Markov model (HMM) using a Weibull distribution as the output density function was created in this study. The Weibull HMM was then reformulated as a probabilistic NMF. This demonstrates the connection between the proposed HMM and NMF, and will lead to a novel probabilistic NMF approach in which the model captures temporal dependencies inherently utilizing moving average. Furthermore, the model parameters were estimated using maximum likelihood estimation (MLE). The model's adaptability was compared to the existing probabilistic NMFs models of gamma and lognormal. Our trials with US COVID-19 data revealed that the proposed technique achieves a superior balance of sparsity, the goodness of fit, and temporal modeling than gamma and lognormal models. 
Transformative Precision: Investigative Summary of PET/CT-Guided Radiation Therapy Simulation in Comprehensive Cancer Management
Get PDFPositron Emission Tomography/Computed Tomography (PET/CT)-guided radiation therapy simulation has transformed cancer treatment, ushering in enhanced precision and individualization. This discussion delves into clinical indications, applications, procedures, and limitations, providing a comprehensive overview across cancer types.
Clinical indications underscore PET/CT's role in accurate staging, target volume delineation, treatment response assessment, and post-treatment recurrence detection. Accurate staging is crucial for tailored treatment plans, while target volume delineation benefits from PET's identification of metabolic patterns. Ongoing treatment response assessment enables dynamic adjustments, and post-treatment, PET/CT aids in detecting recurrent disease.
Applications highlight PET/CT's treatment planning optimization by combining anatomical and functional information. Fusion of PET
and CT images customizes radiation plans, identifying active regions for targeted delivery while sparing healthy tissues. This fusion facilitates tailored strategies, minimizing radiation exposure and enabling dynamic adaptations.
Procedural aspects detail imaging acquisition, image fusion, target delineation, treatment planning, and ongoing monitoring. Starting with radiotracer administration, typically fluorodeoxyglucose (FDG), PET/CT captures functional and anatomical data. Image fusion aids in target delineation and optimizing plans. Ongoing monitoring allows real-time adjustments.
Specific clinical applications across cancers demonstrate PET/CT's versatility. In head and neck cancers, it ensures precise delineation while avoiding critical structures. In lung cancer, it improves tumor extent identification. Similar advantages apply to lymphomas, sarcomas, brain tumors, metastatic disease, and esophageal, gastrointestinal, breast, prostate, gynecological, and pediatric cancers.
Limitations include spatial resolution challenges, false positives, cumulative radiation exposure, lesion size, histology, and standardization issues. Ongoing research targets spatial resolution enhancement, radiomics and AI integration, novel tracers, hybrid imaging, patient-specific dosimetry, clinical trials, multimodal workflows, cost-effectiveness, accessibility, and education.
PET/CT-guided radiation therapy simulation is transformative. Ongoing advancements promise a more precise and individualized approach, enhancing patient outcomes in cancer management
The Potential Role of Chromophiles (Absorbtion) Fungi from Polluted Landfill by Tannery Effluent Challawa Industrial Estates Kano State of Nigeria
Get PDFThe release of unprecedented tannery effluents into the environment as industrial wastes is one of the major causes of environmental pollution. Tannery waste containing heavy metals are usually disposed in landfills and streams in Challawa industrial estate Kano. In the present study tannery effluent discharge soil (polluted landfill), undischarged soil (control) were collected from the surrounding areas of tannery industry. The soil and physicochemical properties were examined in-situ. A total of eleven fungi species were found in the soil. The most common fungal strains viz., Aspergillus niger, Aspergillus sp, Rhizopus nigricans and Penicillium sp were tested for tolerance against chromium sulphate. The degree of tolerance was measured by their mycelia growth length of each respective culture colony and it was compared with control containing no chromium sulphate. Among the isolated fungal strains of all locations, Aspergillus niger was the most tolerant against chromium sulphate. It exhibit strong radial mycelia growth length from 0-4.0% followed by Rhizopus nigricans and the least was obtain by Penicillium sp. Effect of pH and temperature on tolerance of fungal isolates at 1% chromium concentration using different substrates tested were so effective at pH 4-5 and 32oC respectively. These fungi have shown a high level of tolerance to chromium sulphate tested which makes them so attracted and potentially candidate for further investigations regarding their ability to remove metals from contaminated waste waters. 
Online Shopping in India: A Cross-Cultural Study of Paradigm Shift in Tier II Cities
Get PDFOnline merchandizing environment has become fiercely competitive aiming for profoundly understanding consumers’ persona that fascinates them to shop online. The current study has been construed to comprehend this. First, differential role of consumer demographics in creating awareness and affecting online shopping on cross-cultural design is scrutinized. Then, relationships between consumer satisfaction and factors affecting consumer buying behaviour have been explored. After conducting KMO and Bartlett’s Test of Sphericity, bivariate analysis has examined the effect of factors affecting online shopping on consumer behaviour of 400 respondents belonging to four urbanized cities of India, through t-test and one way ANOVA. Subsequently, the impact of factors affecting consumer buying behaviour on consumer satisfaction has been investigated by linear regression analysis. Findings suggest age affects online consumer awareness with no differential role of consumer demographics in the effect of factors affecting online shopping cross-culturally. Next part highlights two factors- family influence (motivational factor) and trend (perceptional factor) establishing strong relationships with online consumer satisfaction. This study aids marketing managers and researchers to scrutinize how age affects present-day online consumer awareness. The non-effective differential role of online consumer demographics on a cross-cultural design can aid in marketing strategy formulation for investigating novel relationships between factors affecting consumer satisfaction. It is striking that age affects present-day online consumer awareness without any differential role of consumer demographics, cross-culturally. Moreover, the impact of family influence and trend on consumer satisfaction is leading towards transformational consumer buying behaviour patterns needing recognition which is the researchers’ contribution to extant literature. 
The Fundamental Underpinning of Biological Theory of Spontaneous Generation in Biology
Get PDFThe concept of spontaneous generation, originating from ancient philosophical and theological debates, has persisted through scientific inquiry and paradigm shifts. This article explores the historical trajectory of spontaneous generation theory from its roots in Aristotelian philosophy to its refutation by pivotal experiments in the seventeenth and nineteenth centuries. Through an examination of key figures such as Louis Pasteur and Francesco Redi, the evolution of scientific understanding regarding the origin of life is elucidated. Pasteur's contributions to germ theory and experimental microbiology, including his famous swan-neck flask experiment, played a decisive role in discrediting the notion of spontaneous generation. Moreover, Redi's controlled experiments with meat and flies provided empirical evidence against the spontaneous generation of maggots. The article also delves into the broader socio-political context surrounding these scientific debates, highlighting the influence of societal authorities and shifting scientific paradigms on the acceptance of new ideas. Additionally, it discusses the role of advancements in microbiology and biochemistry in shaping contemporary perspectives on the origin of life, emphasizing the interdisciplinary nature of scientific inquiry in this field. Ultimately, the narrative underscores the pivotal role of empirical evidence and scientific rigor in overturning long-standing beliefs, illuminating the complex interplay between social context, scientific progress, and the quest for understanding life's fundamental processes. Investigations into the spontaneous production of hydrogen peroxide from pure water micro droplets highlight the complexity of spontaneous chemical reactions. Historical perspectives on spontaneous generation, offer valuable insights into the evolution of scientific thought. Synthesizing recent findings with historical context provides a comprehensive understanding of spontaneous generation's implications across diverse research fields. 
A Review of Stackelberg Game Theory Model on Trade Credit
Get PDFOver the years, game theory has been used extensively to study interactions between the supplier and the retailer in business environment. Recently, a number of researchers have applied Stackelberg game theory on trade credit in centralized and decentralized channels. In this work, we reviewed the assumptions of the Stackelberg game theory model, its solution, its limitations and further extensions were also considered. Furthermore, how the Stackelberg game model applies to trade credit has been analyzed.