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Background and Aims: Autism in children is known to affect brain systems implicated in cognitive, communication, social functioning and intelligence. Although autism is a neurobiological disorder, behavioral interventi...

The rapid expansion of conversational artificial intelligence (AI) usage in healthcare, nutrition, and digital health education has made prompting a routine part of professional and personal practice. However, each AI pr...

Abstract Financial institutions continue to face a significant challenge with money laundering and need intelligent, scalable ways to detect illegal financial activity. This paper introduces a machine learning-driven pla...

Introductions: Mental retardation can be defined as a significant and direct lack of overall intellectual functioning that causes social maladaptation, a condition due to below-average intelligence. The lack of intellect...

Early intensive behavioral intervention (EIBI) is one of the most widely used treatments for children with autism spectrum disorder (ASD). The purpose of this Campbell systematic review was to examine the research on EIB...

Consolidating extensive pedagogical knowledge is essential in preservice teacher education as a foundation for developing future professional competences. While mobile learning has emerged as a promising approach for sup...

Abstract What is the fundamental economic function of the firm under radical uncertainty? This paper advances a theory of the firm centered on economies of cognition: the systematic reduction in the costs of perception, ...

While V2X-based vehicle communication and intersection management have been widely studied, most existing approaches remain limited to simulation-based environments or constrained testbeds. Furthermore, standardized mess...

Dairy farms increasingly deploy sensor networks that generate high-frequency behavioral and spatial data, yet translating these multimodal streams into actionable welfare insights remains a key challenge. This study pres...

IntroductionThe COVID-19 pandemic has reduced system resilience, caused economic welfare loss, and widened disparities in healthcare access. This study aims to identify the macro-level factors contributing to COVID-19 va...

The aim of this article is to evaluate the effectiveness of gamification marketing strategies in territory branding and to determine their impact on consumer behavior. It has been established that one of the key challeng...

Abstract The entry into elementary education - EE - represents an important transition in child development. The study aimed to assess stability and change in indicators of academic achievement, general intelligence, soc...

Background/objectivesNeurofibromatosis type 1 (NF1) is a common genetic disorder often accompanied by cognitive, behavioral, and neurodevelopmental disorders. While tumor-related manifestations are well-documented, less ...

Abstract BackgroundDepression affects more than 300 million people worldwide and is a leading contributor to the global disease burden. Traditional diagnostic methods, such as structured clinical interviews, ...

Currently, the clinical assessment of autism spectrum disorder (ASD) mainly relies on behavioral scales and structured interviews, lacking objective, repeatable, and easily trackable quantitative indicators. This review ...

The main aim of the present study was two-wise: first, to assess the presence of behavioral and intellectual disturbances in high-risk 7-year-old children, compared to healthy controls; and, second, and most importantly,...

Amid the convergence of technological, macroevolutionary, and demographic singularities, conventional approaches to analyzing and forecasting economic growth are increasingly losing relevance and predictive power. The su...

Abstract Alzheimer’s disease, a progressive neurodegenerative disorder, presents a growing global health challenge due to its increasing prevalence and lack of accessible early diagnostic methods. Even though it has en...

This study provides a quantitative framework for wellbeing outcome prediction through intentional cognitive pattern alteration. We demonstrated 81.67% accurate prediction of wellbeing states, in a three-level classificat...

Abstract Financial time series forecasting is traditionally based on historical price patterns, often overlooking exogenous and behavioral variables that can significantly affect market movements. In this study, we enhan...

This work presents a hybrid deep learning approach for identifying students who are likely to experience academic difficulties in virtual learning environments. The proposed framework is evaluated on the Open University ...

The use of Large Language Models (LLMs) in education has expanded rapidly, with LLM tutors increasingly proposed to support learning through individualized explanations and interactions. However, empirical evidence for t...

Various language domains have undergone remarkable changes in recent years; these shifts are largely attributed to the advent of Large Language Models and their misalignment with natural language usage. These misalignmen...

Multiagent systems and online communities rely on rating systems to infer the reputation given to an individual within a particular context. The notion of reputation is essential for helping a given individual to trust i...