The foundation for talent development as a framework for gifted education can be found in a synthesis of the psychological literature on creativity, eminence, giftedness, and high performance. The talent development framework acknowledges the contrib...
Background/Objectives: Risk taking, a crucial component of decision-making, is domain-specific. However, most literature has focused on financial risk-taking in relation to cognitive functioning. The current study investigated the association between...
Although childhood is a critical period of development during which all children begin a lifelong process of self-discovery that shapes their identities, few studies have focused on the self-concept and self-esteem of young, gifted children. This stu...
Need for Cognition (NFC) is an investment trait reflecting interindividual differences in intrinsically motivated engagement in cognitive endeavors. While other motivational constructs like the ability self-concept are typically conceptualized domain...
Ontology engineering (OE) plays a critical role in modeling and managing structured knowledge across various domains. This study examines the performance of fine-tuned large language models (LLMs), specifically GPT-4 and Mistral 7B, in efficiently au...
Research suggests that performance on cognitive tasks resembling daily challenges (i.e., everyday problem-solving tasks) may be a better indicator of functional ability in old age compared to traditional measures of cognitive ability. Findings demons...
Research on intelligence and competence has developed widely independent of each other. The present paper aims at relating these traditions and at integrating the dominant models to fill gaps in the respective theories. We test the structural models...
Previous work has shown relations between domain-general processes, domain-specific processes, and mathematical ability. However, the underlying neurophysiological effects of mathematical ability are less clear. Recent evidence highlighted the potent...
This study investigates the effects of an epistemological sensitization on domain-specific epistemological beliefs. An epistemological sensitization is a short-term intervention that presents a domain’s epistemological features to elicit episte...
Scientists routinely analyse and share data for others to use. Successful data (re)use relies on having metadata describing the context of analysis of data. In many disciplines the creation of contextual metadata is referred to as reporting. One meth...
Image inpainting for indoor environments presents unique challenges due to complex spatial relationships, diverse lighting conditions, and domain-specific object configurations. This paper introduces a resource-efficient post-processing framework tha...
Large language models (LLMs) have shown impressive general-purpose language capabilities, but their application in specialized domains such as healthcare and law remains limited due to two major challenges, namely, a lack of deep domain-specific know...
This paper represents initial research with the aim to establishes a baseline for subsequent research into AI-based construction monitoring, building upon the NORMENG project in Croatia, which previously integrated photogrammetry, laser scanning, and...
This study investigates the ability of six pre-trained sentence transformers to organize medical knowledge by performing unsupervised clustering on 70 high-level Medical Subject Headings (MeSH) terms across seven medical specialties. We evaluated mod...
Domain adaptation of pre-trained language models remains challenging, especially for specialized text collections that include distinct vocabularies and unique semantic structures. Existing contrastive learning methods frequently rely on generic mask...
The detection and localization of the ball in sport videos is crucial to better understand events and actions occurring in those sports. Despite recent advances in the field of object detection, the automatic detection of balls remains a challenging...
Carbon neutrality is a critical global objective in the fight against climate change. As relevant knowledge and technologies advance rapidly, there is an escalating demand for sophisticated intelligent services. While large language models (LLMs) hav...
Phenotypic variations in Charcot-Marie-Tooth disease type 2A (CMT2A) result from the many mutations in the mitochondrial fusion protein, mitofusin 2 (MFN2). While the GTPase domain mutations of MFN2 lack the ability to hydrolyze GTP and complete mito...
In actual industry applications, the failure categories of practical equipment are usually a subset of laboratory conditions failure categories. Due to the strict constraints, partial transfer learning can address a more practical diagnostic scenario...
Wheat seed classification is a critical task for ensuring crop quality and yield. However, the characteristics of wheat seeds can vary due to variations in climate, soil, and other environmental factors across different years. Consequently, the prese...
Giftedness is an increasingly important research topic in educational sciences and mathematics education in particular. In this paper, we contribute to further theorizing mathematical giftedness through illustrating how networking processes can be co...
There are limited studies on the impact of domain-specific self-efficacy on academic achievements. The geospatial thinking ability is paramount to understand the relationship between geographical self-efficacy and academic achievements in geography....
There is still much debate about the exact nature and frequency of developmental dyscalculia, and about how it should be defined. This article examines several key questions in turn: Is developmental dyscalculia a distinct disorder, or should it be s...
Process-Overlap Theory (POT) suggests that measures of cognitive abilities sample from sets of independent cognitive processes. These cognitive processes can be separated into domain-general executive processes, sampled by the majority of cognitive a...
The current study investigated whether a domain-specific intervention of ExeFun-Mat targeting math and executive functions in primary school children with a Roma background would be effective in improving their scholastic performance and executive fu...
One important internal factor influencing reading comprehension is a child’s executive functioning. The primary objective of this paper is to evaluate the effectiveness of a cognitive stimulation program, ExeFun-READ (a program focusing on exec...
Background: Math achievement is an important predictor of academic success. While many studies have examined math achievement in young children, studies with older children are scarce. This study focused on primary- and middle-school students, examin...
Background: Health-related quality of life (HRQoL) is an important patient-reported outcome for all cancer patients, including adult patients with rare solid cancers. However, current knowledge of HRQoL in this population is limited, which hinders th...
As the core automated execution components of blockchain technology, smart contracts enable programmatic control over digital assets; however, their immutable characteristics and inherent logical vulnerabilities give rise to substantial security risk...
As IoT environments continue to grow in scale and complexity, the increasing number of interconnected sensors and devices makes end-to-end system behaviour progressively harder to understand. Process mining offers strong potential to address this cha...
21 March 2024
The present study describes the Italian adaptation of the Academic Stressors Scale (E-CEA) of the Academic Stress Questionnaire, evaluating the relationships with general and domain-specific well-being and verifying the significant predictors and the...
Background/Objectives: Low-carbohydrate (LCD) and ketogenic diets (KD) are increasingly adopted by athletes due to their ability to enhance fat oxidation and induce metabolic adaptations. While their effects on aerobic power and capacity have been wi...
The ability to accurately judge others’ personality and the ability to accurately recognize others’ emotions are both part of the broader construct of interpersonal accuracy (IPA). However, little research has examined the association bet...
The article proposes a universal dual-axis intelligent systems assessment scale. The scale considers the properties of intelligent systems within the environmental context, which develops over time. In contrast to the frequent consideration of the &l...
Emerging deep learning-based fault diagnosis methods have advanced in the current industrial scenarios of various working conditions. However, the prerequisite of obtaining target data in advance limits the application of these models to practical en...
Medical coding plays an essential role in medical billing, health resource planning, clinical research and quality assessment. Automated coding systems offer promising solutions to streamline the coding process, improve accuracy and reduce the burden...
The ability to inhibit conflicting information is pivotal in the dynamic and high-speed context of fast-ball sports. However, the behavioral and electrophysiological characteristics underlying the cognitive inhibition processes associated with table...
Background: Neurocognitive functioning in transgender adults remains understudied and is predominantly derived from Western samples, often treated as universally applicable. Evidence from non-Western contexts is limited, despite the potential influen...
Background/Objectives: Identifying consistent patterns across empathy domains can help clinicians understand how empathy relates to burnout, covert narcissism, and other personality traits, thereby enhancing the effectiveness of clinical training. We...
In recent years, Natural Language Processing (NLP) has become increasingly important for extracting new insights from unstructured text data, and pre-trained language models now have the ability to perform state-of-the-art tasks like topic modeling,...
5 November 2016
Health research suggests that findings on young-old adults cannot be generalized to old-old adults and thus that old-old age seems not a simple continuation of young-old age due to qualitative changes that result in a discontinuity in old age. Specif...
Semantic matching is essential for understanding natural language, but traditional models like BERT face challenges with random masking strategies, limiting their ability to capture key information. Additionally, BERT’s sentence vectors may &ld...
Self-supervised monocular depth estimation (MDE) has emerged as a cost-effective alternative to traditional depth sensing approaches, which often require expensive equipment or complex configurations. However, these models often fail to maintain high...
In industrial quality control, especially in the field of manufacturing defect detection, deep learning plays an increasingly critical role. However, the efficacy of these advanced models is often hindered by their need for large-scale, annotated dat...
Feature-based approaches have been profusely used in the last decades to incorporate domain-specific knowledge in the design and development of technical systems that, according to the new Concurrent Engineering approaches, involves not only the defi...
Objective. Consumer-grade EEG devices have the potential for widespread brain–computer interface deployment but pose significant challenges for emotion recognition due to reduced spatial coverage and the variable signal quality encountered in u...
In application, training data and test data collected via indoor positioning algorithms usually do not come from the same ideal conditions. Changes in various environmental conditions and signal drift can cause different probability distributions bet...
The proliferation of fake news poses a significant challenge in today’s information landscape, spanning diverse domains and topics and undermining traditional detection methods confined to specific domains. In response, there is a growing inter...
We assessed the relational abilities of two state-of-the-art large language models (LLMs) and two large reasoning models (LRMs) using a new battery of several thousand syllogistic problems, similar to those used in behavior-analytic tasks for relatio...
Multimodal learning has gained attention in recent years due to its ability to effectively utilize data features from various modalities. Diagnosing the vulnerability of atherosclerotic plaques directly from carotid 3D MRI images is challenging for b...
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