Problematic mobile phone use and Shyness: A network perspective on User differences.

Problematic mobile phone use (PMPU) has become increasingly prevalent among young adults, raising concerns about its psychological underpinnings. While shyness has been linked to PMPU, few studies have explored the symptom-level mechanisms that differentiate problematic from non-problematic users. This study employed psychological network analysis to examine the structure and central symptoms of PMPU in two groups: problematic and non-problematic mobile phone users.

X-FASNet: cross-scale feature-aware with self-attention network for cognitive decline assessment in Alzheimer's disease.

Early diagnosis of Alzheimer's disease is critical for effective therapeutic intervention. The progressive nature of cognitive decline requires precise computational methods to detect subtle neuroanatomical changes in prodromal stages. Current multi-scale neural networks have limited cross-scale feature integration capabilities, which constrain their effectiveness in identifying early neurodegenerative markers.

Integrated pH-responsive three-phase system: Time- and solvent-efficient biorefining of waste into multifunctional saponins.

seed cake (COSC), an agricultural byproduct, offers untapped potential as a biosurfactant source but suffers from inefficient extraction. We developed a pH-responsive platform integrating ultrasound-assisted alkaline three-phase partitioning (-butanol/ammonium sulfate, pH 10) and acid-triggered precipitation (pH 4.5).

Arginine Maillard reaction products recovered damaged immune cells.

Instant noodle has been an initiating point for food industry in many countries, and it continues to be a beloved convenient food in the world. However, some products cause discomfort after consumption despite full compliance in both ingredients and processing methods. It has not only resulted in serious consumer misunderstanding but also affect the industry as well.

Evidence synthesis of effective e-cigarette prevention messages for adolescents and young adults: A scoping review.

Introduction: This scoping review aims to examine existing evidence regarding information design for youth e-cigarette prevention, identify research gaps, and provide recommendations for future research and practice.

Methods: A comprehensive literature search was conducted from the inception of databases to April 2024 across six databases: Web of Science Core Collection (including MEDLINE), PubMed, Embase, Scopus, PsycINFO, and CNKI. Peer-reviewed articles related to information design for youth e-cigarette prevention were included based on eligibility criteria.

Effects of Salinity on the Growth Performance and Docosahexaenoic Acid Positional Distribution in Triacylglycerols of the Newly Isolated sp. FJ-1.

-derived omega-3 polyunsaturated fatty acids (e.g., docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA)) are proven to be health-beneficial bioactive substances that have been widely applied in the pharmaceutical, nutraceutical, and food industries.

Insights Into Proliferation Effects of Low-Dose Glyphosate on Phytoplankton Communities.

Glyphosate-based herbicides are among the most widely used agricultural chemicals globally, and their widespread application presents risks to environmental health and aquatic ecosystems. Continuous glyphosate inputs disrupt phytoplankton communities, potentially triggering harmful algal blooms. This study examines the proliferation of microalgal species exposed to low glyphosate concentrations (0.

The Relationship Between Envy and Problematic Social Media Use: Evidence From Longitudinal Study and Daily Diary Investigation.

Social media is widely used worldwide, and previous research has established a link between envy and social media use. However, the dynamic association between envy and problematic social media use has rarely been explored. Based on Social Comparison Theory and Innovation Adoption Framework, the study examined the relationship between envy and problematic social media use.

Induction of Strong Magneto-Optical Effect and High Compatibility with Si of BiFeO Thin Film by Sr and Ti Co-Doping.

The poor magnetic and magneto-optical properties of BiFeO, along with its significant lattice mismatch with silicon, have limited its application in silicon-based integrated magneto-optical devices. In this study, co-doping with Sr and Ti ions effectively transformed the trigonal structure of BiFeO into a cubic phase, thereby reducing the lattice mismatch with silicon to 2.8%.

The Electrocortical Effects of Repurposing and Reconstrual on the Regulation of Disgust.

Cognitive reappraisal serves as a pivotal strategy in emotion regulation, encompassing techniques such as repurposing and reconstrual. However, the behavioral and temporal disparities between these two reappraisal subtypes remain underexplored. This study aims to delineate these differences by comparing the psychophysiological impacts of repurposing versus reconstrual on disgust emotion regulation, employing event-related potentials (ERPs) as the primary neurophysiological indicator.

Deep Learning in Antimicrobial Peptide Prediction.

Antimicrobial peptides (AMPs) have garnered significant attention from researchers as effective alternatives to antibiotics. In recent years, deep learning has demonstrated unique advantages in AMP prediction, surpassing traditional machine learning methods and offering new avenues to address the issue of antibiotic resistance. This review introduces the research foundations of deep learning in AMP prediction, covering data set status, processing methods, and representation learning approaches.

Interdisciplinary perspective-based behavioral prediction of e-cigarette use: A population-based study among Chinese college students.

Introduction: E-cigarette use is rising among young adults globally, and college students are particularly vulnerable due to high social media engagement and targeted promotions. Understanding which factors predispose this population to initiate vaping is critical for designing effective prevention strategies.

Methods: We conducted a cross-sectional survey of 303 never-smoking, never-vaping Chinese college students (aged 18-24 years) recruited via online platforms and referrals.

Media representation of tobacco control in China: A comparative analysis of agenda-setting across different policy contexts during 2017-2022.

Introduction: While media play a crucial role in tobacco control policy advancement, little is known about how different policy contexts shape media coverage of tobacco control, particularly in China's unique political and administrative systems. This study innovatively compares tobacco control news coverage across three regions with distinct tobacco control policy environments: mainland China, Guangdong Province, and Macao SAR, examining how policy contexts influence media agenda-setting before and during the COVID-19 pandemic.

Methods: Using the WisersOne database, we analyzed 749 tobacco control news articles from three influential newspapers () from 2017-2022.

Effective features of e-cigarette prevention videos: A qualitative study with primary school students.

Introduction: While video-based prevention campaigns show promise in addressing the rising e-cigarette use among youth, little is known about what makes such videos effective from children's perspectives, particularly in China's cultural context. This study aimed to investigate which video content elements could be effective in preventing e-cigarette use among children, providing evidence-based guidance for developing e-cigarette prevention materials and information design targeting children.

Methods: Using purposive sampling, we conducted four gender-stratified focus groups with 35 primary school students (aged 12-13 years) in Beijing and Yunnan.

Subtypes I and II of O.F. Müller: Dominant Green Tide Species in the Southern Yellow Sea and Their Responses to Natural Light and Temperature Conditions.

This study systematically investigated two ecotypes of , the dominant species responsible for green tides in the Yellow Sea, classified as Subtype I (strain ) and Subtype II (strain ). Both subtypes produce positively phototactic biflagellate gametes with oval/pear-shaped morphology but exhibit distinct cellular dimensions. Subtype I gametes demonstrated significantly larger cell sizes, with long and short axes measuring 6.

The Effect of Hawthorn Red Pigment on Meridian Voltage: An Experimental Study on Traditional Efficacy and Modern Application Value.

Objective: To observe the effect of hawthorn red pigment (HRP) on meridian voltage in 20 volunteers over a period of 90 days.

Methods: The characteristic absorption peak of HRP was determined by ultraviolet-visible spectroscopy full-wavelength absorption analysis scanning, and its solution particle size was measured by Nano-ZS Malvern laser particle size analyzer. Volunteers were required to take a 100 mL HRP solution containing 4.

Polysaccharide-based beads and water purification: A review.

Polysaccharide-based beads have attracted considerable interest as efficient materials for remediation of water contamination because of their excellent adsorption capability and eco-friendly properties. This review analyzes recent progress in developing biopolymeric magnetic hydrogels deduced from polysaccharides like cellulose, starch, alginate, chitosan, lignin, pectin, guar gum, carrageenan, and agar. It emphasizes their use in eliminating heavy metals, dyes, oil, and antibiotics from polluted water.

Extreme Heat Event Alters BVOC Responses to Elevated Ozone: From Physiology to Emission Patterns.

Extreme heat and elevated ozone (O) significantly affect plant growth and secondary metabolism, including biogenic volatile organic compound (BVOC) emissions. However, the impact of the extreme heat events (EHs) on the O-induced BVOC emissions remains unclear. Here, (an isoprene emitter) and (a monoterpene emitter) were exposed to five O treatments for three months and subjected to a two-week EH.

Effect of gel ageing and electrode corrosion on the performance of direct laser writing carbonization-enabled hydrogel-based moist-electric generators.

The combined use of hydrogel active materials and porous and asymmetric electrodes enables the development of high-performance and high-power output moist-electric generators (MEGs). Herein, we report a direct laser writing carbonization (DLWc)-enabled approach for cost-effectively manufacturing the porous carbon electrode that can be easily integrated and assembled with the hydrogel active material for the scalable fabrication of MEGs. With the hydrogel active material composed of poly(vinyl alcohol) (PVA), poly(acrylic acid) (PAA), phytic acid (PA), glycerol and water, the best performing DLWc-enabled PVA/PAA/PA hydrogel-based MEG exhibited an open-circuit voltage of ∼0.

A review of the application of machine learning in carbon emission assessment studies: prediction optimization and driving factor selection.

With growing global concerns over the greenhouse effect and its impacts, developing effective carbon emission prediction models has become an imperative for addressing climate change. Machine learning (ML) excels at extracting potential patterns and correlations from a wide range of datasets, playing an indispensable role in this research field. This study conducted a systematic literature review of 126 peer-reviewed papers applying machine learning to carbon accounting, aiming to synthesize research progress, identify knowledge gaps and propose future directions.

The analysis of motion recognition model for badminton player movements using machine learning.

This study aims to comprehensively analyze and classify the badminton players' swing actions by combining the theoretical frameworks of quantum mechanics and machine learning. A badminton stroke recognition method based on Quantum Convolutional Neural Network (QCNN) is proposed. It is then compared with traditional Support Vector Machines (SVM) and Convolutional Neural Network (CNN).

ATDMNet: Multi-Head Agent Attention and Top-k Dynamic Mask for Camouflaged Object Detection.

Camouflaged object detection (COD) encounters substantial difficulties owing to the visual resemblance between targets and their environments, together with discrepancies in multiscale representation of features. Current methodologies confront obstacles with feature distraction, modeling far-reaching dependencies, fusing multiple-scale details, and extracting boundary specifics. Consequently, we propose ATDMNet, an amalgamated architecture combining CNN and transformer within a numerous phases feature extraction framework.

Community Characteristics and Potential Risk of Nekton in Waters Adjacent to Ningde Nuclear Power Plant in Fujian, China.

The impact of bio-invasions and abnormal aggregations of marine life on the safety of cooling water systems in coastal nuclear power plants (NPPs) is significant and cannot be overlooked. In this study, we conducted 12 consecutive monthly surveys from September 2022 to August 2023 in the waters near Ningde NPP in Fujian, China, focusing on nekton species composition, dominant species, abundance, biomass, and diversity indices. We conducted statistical analyses to examine potential correlations between the community structure of these organisms and environmental factors.

Harsh Parenting and Problematic Smartphone Use: The Chain Mediating Effects of Attention to Negative Information and Social Anxiety.

Harsh parenting has been shown to be associated with problematic smartphone use among adolescents. However, few studies have explored the relationship between harsh parenting and problematic smartphone use through a dual-system framework that integrates both emotional and cognitive processing. We aim to investigate the serial mediation effects of attention to negative information and social anxiety in the relationship between harsh parenting and problematic smartphone use among adolescents.

Exploring Predictors of Bullying Perpetration Among Adolescents Using Machine Learning Approach.

This study used machine learning methods to detect risk and protective factors for bullying perpetration in adolescents. The study sample consisted of 777 students with an age range of 11 to 16 years old. Multidimensional data covering both individual and environmental levels were collected.