Browse Articles
Discover research articles across all indexed journals
Artificial intelligence, green transition and green total factor productivity in enterprises
Development of novel filament production setup of continuous fiber reinforced composite filament for additive manufacturing applications
Time of urine sampling may influence the association between urine specific gravity and body composition
Urine specific gravity (USG) is frequently utilized in sports practice and research to assess hydration status. Prior research suggests that individuals with large amounts of fat-free mass (FFM) and muscle have elevated USG, but little is known about whether the time of collection (first-morning vs. spot sampling) and various nutritional factors influence these relationships. This cross-sectional, observational study assessed fasted first-morning (n = 55) and non-fasted spot USG (n = 51) samples in adults and evaluated relationships of USG with body composition and nutrition intake. The InBody 770 was used to estimate FFM, skeletal muscle mass (SMM), and total body water (TBW). Protein, water, and sodium intakes from the 24-hour period before USG assessments were generated based on the Automated Self-Administered 24-hour Recall. Median USG was higher for fasted first-morning samples than non-fasted spot samples (1.018 vs. 1.011, Z = −5.2, p < 0.001). Based on fasted first-morning samples, 41.8% of participants had a USG ≥ 1.020 while the prevalence of USG ≥ 1.020 was 21.6% using non-fasted spot samples. None of the body composition variables (FFM, SMM, TBW) significantly associated with fasted first-morning USG (Spearman ρ < 0.10), while all three variables showed significant, positive associations with non-fasted spot USG (Spearman ρ = 0.32–0.36, p < 0.05). None of the dietary variables were significantly associated with either fasted first-morning or non-fasted spot USG. Although previous research has shown the FFM positively associates with USG, this investigation provides evidence that this relationship could depend on sampling time. Non-fasted spot samples, in comparison to fasted first-morning samples, may be impacted by FFM to a greater degree.
Targeting ATF6 reduces pathological neovascularization and improves visual outcomes in retinal disease models
Abstract Pathological retinal neovascularization is a cause of vision loss in diseases including retinopathy of prematurity (ROP), wet age-related macular degeneration (AMD), and diabetic retinopathy. The Unfolded Protein Response (UPR) is an intracellular signal transduction mechanism that is activated by ER stress and upregulates many proteins, including angiogenesis factors like VEGF and HIF-1α. This suggests that UPR genes and pathways may drive retinal angiogenesis. Here, we tested the role of the UPR regulator Activating Transcription Factor 6 (ATF6) in pathological and developmental retinal angiogenesis. We induced pathological retinal neovascularization in Atf6 −/− mice using the oxygen-induced retinopathy (OIR) model and found significantly preserved visual function, accompanied by decreased retinal neovascularization, endothelial cell proliferation, and UPR transcriptional program induction. When we chemically blocked ATF6 signaling by intraocular injection of the small molecule Ceapin-A7, we also saw suppressed retinal expression of UPR genes. Additionally, in postnatal day 7 Atf6 −/− mice when the retinal vasculature is developing in response to physiologic intraocular hypoxia, there was a transient but significant defect in pruning and retinal blood vessel extension. Together, our results demonstrate ATF6’s causal role in developmental and pathological retinal angiogenesis and highlight its potential as a therapeutic target to preserve vision in retinal neovascularization diseases.
Surface and in vitro corrosion properties of spark plasma sintered Ti–Zr–Nb–Ta–Ag high entropy alloy for dental implant applications
Enhanced Bézier curve-based trajectory planning for high-altitude autonomous trucks
Highway freight transport is the backbone of Tibet’s logistics network, accounting for 76.4% of regional freight movement (Tibet Bureau of Statistics, 2024). Challenging alpine road conditions—characterized by steep grades, sharp curves, and narrow lanes—combine with the substantial dimensions of heavy trucks to create significant operational difficulties. Autonomous truck development offers a potential solution; however, their trajectory planning algorithms exhibit limitations in high-altitude environments. To address these challenges, we propose a novel trajectory planning method using quartic Bézier curves. These 4th-order parametric curves provide G² continuity. Our approach integrates speed profiles into a three-dimensional curve representation and employs a two-phase optimization process to ensure safety and efficiency. Simulation results demonstrate the method’s effectiveness in maintaining truck stability while enabling responsive maneuvering under Tibet’s demanding road conditions.
Chaos and bifurcations of a discretized Holling-II prey-predator model including prey refuge and Allee effect
iTRAQ-based quantitative proteomics reveals reduced expression of KRT19, KRT7, and PTGDS in cutaneous specimens after kidney transplantation
Tunable single- and dual-wavelength lasers around 1.4 μm in Nd:LuGdAG crystal
We present the first diode-pumped tunable single- and dual-wavelength (DW) laser operation near 1.4 μm spectral region in Nd:LuGdAG (Nd:LGAG) crystal on the 4F3/2 → 4I13/2 transition. Three distinct lasing wavelengths at 1414 nm, 1426 nm and 1437 nm were generated by adjusting a Lyot filter (LF) in the cavity, respectively. The maximum continuous-wave (CW) power output of 3.64 W at 1414 nm was attained under an absorbed pump power of 18.7 W, exhibiting a slope efficiency of 23.7% and optical conversion efficiency of 19.5%. Further, three pairs of DW lasers operating at 1414 nm and 1426 nm, 1414 nm and 1437 nm, 1426 nm and 1437 nm were also achieved, respectively. The DW operation at 1414 nm and 1437 nm yielded 2.82 W total CW output power, attaining 15.1% total optical conversion efficiency. Single- and DW lasers in the 1410–1440 nm spectral range have important application in fields such as optical communication and medicine.
Assessing the link between cerebellar volume and cognitive function in Alzheimer’s disease: a pilot study
Investigating the role of the ALPK1 signaling pathway in the pathogenesis of diabetic retinopathy
Stochastic modeling of intra- and inter-hospital transmission in Middle East respiratory syndrome outbreak
Middle East Respiratory Syndrome (MERS) is an endemic disease that presents a significant global health challenge characterized by a high risk of transmission within healthcare settings. Understanding both intra- and inter-hospital spread of MERS is crucial for effective disease control and prevention. This study utilized stochastic modeling simulations to capture inherent randomness and unpredictability in disease transmission. This approach provides a comprehensive understanding of potential future MERS outbreaks under various scenarios in Korea. Our simulation results revealed a broad distribution of case number, with a mean of 70 and a prediction interval of [0, 315]. Additionally, we assessed the risks associated with delayed outbreak detection and investigated the preventive impact of mask mandates within hospitals. Our findings emphasize the critical role of early detection and the implementation of preventive measures in curbing the spread of infectious diseases. Specifically, even under the worst-case scenario of late detection, if mask mandates achieve a reduction effect exceeding 55%, the peak number of isolated cases would remain below 50. The findings derived from this study offer valuable guidance for policy decisions and healthcare practices, ultimately contributing to the mitigation of future outbreaks. Our research underscores the critical role of mathematical modeling in comprehending and predicting disease dynamics, thereby enhancing ongoing efforts to prepare for and respond to MERS or other comparable infectious diseases.
Optimized extreme learning machines with deep learning for high-performance network traffic classification
Identification of small molecule dimethyoxyphenyl piperazine inhibitors of alpha-synuclein fibril growth
Prediction of subjective well-being level in residents of Dali City: Where modern tourism meets traditional ethnic culture
Objective Dali is a city rich in tourism resources and cultural heritage, where residents’ subjective well-being (SWB) varies in response to the dynamics of local tourism culture. Few studies have examined the distribution of SWB levels and their influencing factors in areas where modern tourism economies and traditional cultures coexist. The study aims to explore the relationship between multiple variables and SWB, and rank the importance of key well-being factors. Methods This study employed a convenience sampling method to survey permanent residents of Dali City, resulting in a final dataset of 483 valid samples. Our study selected a wide range of predictors, including sociodemographic characteristics, leisure activities, social class identification, and preferences in socialization interaction patterns. Eight common ML algorithms were utilized to construct prediction models. The model’s performance was evaluated using the area under the curve (AUC) metric. Generalized additive models (GAMs) were used in sensitivity analyses to assess potential nonlinear relationships between predictors and SWB. Results The probability of high SWB in Dali City was 48.9%. RF demonstrated the highest predictive accuracy (AUC = 0.82). By ranking the importance of variables in the best model RF, we obtain the top five predictors of SWB as: frequency of health issues affecting daily activities, family economic status, age, income, and weekly family face-to-face communication. GAMs explained 55.2% of the variance in SWB (R2 = 0.552, N = 483). Fewer health issues affecting daily life were strongly associated with higher SWB (B = 4.83–6.39, p < 0.001). Better family economic status (B = 1.37–2.24, p < 0.001) and greater trust in society (B = 0.92–1.39, p < 0.01) also predicted higher SWB. Age showed a positive association with SWB scores (EDF = 1.00, p < 0.001). Conclusions This study shifts the focus from economic outcomes to residents’ SWB in a culturally diverse tourism setting. Using machine learning and GAMs, health issues emerged as the strongest predictors of SWB. Findings support health-oriented tourism strategies and highlight the need to integrate socio-cultural factors into sustainable tourism planning.
AI acceptance and Chinese EFL learners’ behavioral engagement with mediating effects of motivation
The use of Hückel and Onsager equation to derive stimulating voltage for a cell
The common structure of mentalizing
The primary goal of this research was to investigate the common factor structure of mentalizing by combining items from pre-existing validated tools, cross-validating the resulting structure, and exploring its associations with relevant constructs. Three sequential studies were conducted using community-dwelling samples (total N = 947). Study 1 used exploratory factor analysis on a merged item pool derived from eight measures of mentalizing. Study 2 utilized exploratory structural equation modeling to replicate the extracted structure and investigated its association with psychological dysfunction. Study 3 performed cross-validation of the factor structure and provided criterion-related validity by examining relations with markers of psychopathology and well-being. Factor analyses provided a 10-factor solution that covered distinct facets of mentalizing. Some factors, especially Nonmentalizing-Self and Emotion/Impulse Dysregulation, were strong predictors of dysfunction and psychopathology. Notably, after controlling for positive self-evaluation, individuals reporting greater confidence in understanding others’ minds (Mindreading Self-Concept) showed poorer psychological functioning (β = 0.157, p = .001), in line with theoretical emphasis on humility as a component of genuine mentalizing. The resulting 10-factor structure provides a framework to potentially differentiate between adaptive and maladaptive mentalizing, distinguish its components along the self–other continuum, and discriminate authentic mentalizing processes from subjective assessments of one’s mentalizing capacity.