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Parental Decision-Related Factors Are Associated with Discretionary Ultra-Processed Food Consumption Among Children and Adolescents Living in the Mediterranean Area
Background/Objectives: Nutrition during childhood and adolescence is a key determinant of long-term health, influencing metabolic homeostasis, neurocognitive development, and immune system maturation. Globalization and technological advances have reshaped food production and consumption, increasing the availability of ultra-processed foods (UPF) of low nutritional quality. This study aimed to investigate the relationship between parental factors, namely food literacy, perceived barriers and enablers, dietary attitudes, and healthy eating behaviors, and the consumption of discretionary UPF among children and adolescents living in 5 Mediterranean countries. Methods: This cross-sectional study was based on a survey completed by 2011 parents of children and adolescents aged 6–17 years from 5 Mediterranean countries, who reported on their children’s dietary and lifestyle habits. Adherence to the Mediterranean diet was assessed through the KIDMED index. Parental food literacy was measured using the Short Food Literacy Questionnaire (SFLQ). Perceived barriers and enablers were assessed based on the Theory of Planned Behavior, and parents’ attitudes toward their child’s diet were evaluated using the Healthy-Eating Attitudes Questionnaire (HEAQ). Finally, the Theory of Internet Use Related to Health (TIUH) questionnaire was used to assess parents’ tendencies related to health information use online. Results: Higher perceived barriers and enablers were significantly associated with lower discretionary UPF consumption across all models. Parental food literacy (SFLQ) showed a positive association with discretionary UPF consumption, remaining significant in the fully adjusted model, although with reduced magnitude. Healthy-eating attitudes (HEAQ) were initially positively associated with discretionary UPF intake but lost statistical significance after full adjustment. Regarding health-related internet use (TIUH), the Health Information dimension showed a strong positive association with discretionary UPF consumption, while other dimensions (Consciousness and Beliefs) showed inconsistent and non-significant associations in the fully adjusted model. Conclusions: Children’s consumption of discretionary UPF is shaped by several interrelated factors, such as family environment, eating patterns, and parents’ perceptions, rather than solely by knowledge or attitudes.
LwHM: lightweight hybrid classifier for SDN-attack detection using recursive feature elimination
Internet connectivity has significantly enhanced the efficiency of daily operations, information retrieval, and global communication. However, this heightened reliance on technology has also exposed us to cybersecurity threats that are often beyond our control. Consequently, securing the data, privacy, and critical systems demands essential cybersecurity measures. This study focuses on the role of artificial intelligence in strengthening security systems to thwart network breaches. The study proposes a comprehensive three-part approach for software-defined networking (SDN) security. The first is that the concentration is on assuring data integrity and reliability for an SDN intrusion dataset. This involves critical steps such as data cleaning, preprocessing, and normalization. In the second step, six popular feature selection strategies are applied, which encompass recursive feature elimination (RFE), polynomial features, artificial neural networks, SelectKBest, least absolute shrinkage and selection operator (LASSO), and correlation-based features. These techniques help identify and incorporate significant and relevant features, thereby improving the overall model performance. The third part involves the creation of a lightweight hybrid model (LwHM) that leverages the strengths of k-nearest neighbors and decision tree models, utilizing a voting classifier. The LwHM surpasses the performance of the InSDN dataset, achieved an impressive accuracy score of 99.93% with RFE features, and enhance the SDN security efficiently.
Infrared thermography to assess fatigue, injury risk factors and recovery in soccer: a systematic review of original studies
Background: Recovery after a training session or match is a key factor in injury prevention and sports performance. The purpose of this systematic review was to analyze and consolidate the available scientific evidence from the main databases on the use of infrared thermography in the assessment of fatigue, injury risk factors, and recovery in soccer players.Methods: The literature search was conducted following the PRISMA guidelines and the PICOS model until June 30, 2025, in the main scientific databases (ScienceDirect, EMBASE, Web of Science (WOS), Cochrane Library, SciELO, MEDLINE/PubMed, SPORTDiscus, and Scopus). The risk of bias and methodological quality were assessed using the Cochrane Handbook guidelines and the PEDro scale.”Results: The initial literature search yielded a total of 510 records. After applying the inclusion and exclusion criteria, the final sample consisted of 20 studies, which were of high methodological quality. The results showed the effects of infrared thermography in assessing fatigue, identifying injury risk factors, and monitoring recovery processes in soccer players. The studies also systematically reported the characterization of the population, the assessment methods used, the variables analyzed, the methodological design, the main results, and the effects of the intervention.Conclusions: Infrared thermography shows promise as a valid, reliable, and non-invasive tool for assessing skin temperature, reflecting temperature changes in response to physiological processes. It allows for the analysis of structural or metabolic fatigue and thermal asymmetries. Therefore, thermography could be used to design individualized recovery protocols.
Advanced Wafer Hotspot Detection through Image Segmentation and Stacked Model
The wafer map is a data visualization of a thin semiconductor fabric made of crystalline silicon, such as defects or test results. The wafer map is a base for creating electronic coordinate circuits and photovoltaic cells. During the wafer map production, any fault results in a product failure. The wafer map faults are undetectable to the naked eye, which is a big challenge. Hotspot detection in wafer maps is significantly important to evaluate the manufacturing process and. improve product yield. The hotspot detection in the wafer maps is the primary aim of this research. A novel wafer map hotspot detector (WHD) is proposed based on three stack fully connected conventional neural network layers and a dense layer. Data augmentation uses the segmented images of the wafers to build the proposed model. The proposed model is evaluated through several evalua-tion parameters and state-of-the-art studies comparative analysis. The proposed model achieved a 94% training and 90% testing performance accuracy for hotspot detection and shows better results than existing approaches. This study helps semiconductor engineers improve wafer manufacturing designs and efficiency in the semiconductor industry.
Liquorice alters adipocyte–breast cancer cell crosstalk by modulating oxidative stress and suppressing aromatase and renin–angiotensin signalling
Obesity is recognised to be a risk factor for breast cancer since adipose tissue influences the tumour microenvironment. This study aims to investigate the effect of the secretome of 3T3-L1 adipocytes untreated or treated with liquorice root extract (LRE), containing flavonoids, phenolic acids, and saponins on MCF-7 breast cancer cells. By treating adipocytes with LRE, the secretion of certain pro-tumorigenic factors like IGFBP-6, resistin, and VEGF was reduced. MCF-7 cells exposed to conditioned medium from LRE-treated adipocytes exhibited an increase in reactive oxygen species levels, downregulation of the Nrf2 antioxidant pathway, and increased autophagy. Those conditions reduced cell viability, migration, and colony formation. Additionally, there was downregulation of genes associated with oestrogen signalling and tumour-related processes, including CYP19A1 (aromatase), ERα, Her2, and components of the renin–angiotensin system (RAS). These findings suggest that LRE can modulate the adipocyte secretome to influence breast cancer cell behaviour under obesity-related in vitro conditions.