Browse Articles
Discover research articles across all indexed journals
Screening of advanced fibrosis and metabolic dysfunction-associated steatotic liver disease using transient elastography in vulnerable population
Enhancing indoor activity recognition for disabled persons using multi head self attention recurrent neural network with improved pelican algorithm
Psychiatric symptoms and their predictors in aging parents of adults with autism spectrum disorder
Abstract Parenting an individual with Autism Spectrum Disorder (ASD) affects the mental health of both mothers and fathers. A chronic disorder, ASD, has devastating effects on parental mental health as the affected individual moves from childhood to adulthood. While the effects of ASD on parental mental health during childhood have been studied extensively, there is limited information regarding the mental health of aging parents of the expanding adult ASD population. In this context, we aimed to determine the psychiatric symptoms (PS) levels of parents of adult with ASD, to compare the PS level between mothers and fathers, to investigate the relationship between parental PS and variables related to the individuals with ASD and their parents. To assess the parents’ PS, the Brief Symptom Inventory was administered to 77 parents of adults with ASD. ASD severity was evaluated with the Childhood Autism Rating Scale, behavioral problems were assessed with the Aberrant Behavior Checklist, independence level (IL) of the cases was measured with the Lawton Instrumental Activities of Daily Living Scale, and social functioning level (SFL) of the cases was evaluated using the Social Functioning Scale. At all ages from childhood to adulthood, the most common primary caregiver was mother. Mothers’ labor force participation rate was significantly lower than fathers’ (p < 0.05). Mothers’ somatization (p = 0.028) and depression (p = 0.002) levels were significantly higher than fathers’. The somatization score of the mothers of cases with comorbid medical diagnosis and intellectual disability (ID) was significantly higher than those without. The depression score of fathers of cases with ID and illiteracy was significantly higher (p < 0.05). The negative self-concept score of fathers of cases with ID, illiteracy, and dependent self-care and toileting was significantly higher (p < 0.05). As IL increased, paternal depression and negative self-concept levels decreased significantly (p < 0.05). When SFL increased, maternal anxiety, depression, and somatization and paternal negative self-concept levels decreased significantly (p < 0.05). In regression analyses, maternal anxiety was significantly associated with irritability, depression with hyperactivity, negative self-concept with irritability; somatization with irritability and the presence of medical diease in mother and patient; hostility with hyperactivity. Paternal anxiety, depression, somatization, and hostility were associated with irritability; negative self-concept with irritability and social withdrawal. It is hoped these results contribute to a better understanding of the protective and risk factors of the psychopathology of parents of adults with ASD, a topic relatively poorly studied.
Diversity and characterization of the ammonia-oxidizing bacteria responsible for nitrification in tea field soils
Machine learning models for predicting rural residential carbon emissions and optimising spatial forms
Protective role of Karanjin against bisphenol A-Induced cognitive deficits and oxidative damage in a zebrafish model
Improved first arrival picking of microseismic P-waves in coal mines using multi-denoising and adaptive characteristic functions
Abstract Microseismic monitoring is a critical technology for mine safety monitoring, but existing microseismic picking methods exhibit instability and limitations when dealing with high-noise data in coal mine environments. This paper proposes a method for improving the picking of high-noise microseismic P-wave first arrivals, called IWTSE-MSDACF-AIC. The method first uses the improved complete ensemble empirical mode decomposition with adaptive noise to decompose the microseismic signal into a series of intrinsic mode functions (IMFs). Then, the sample entropy of the IMFs is calculated, and an appropriate threshold is set to perform wavelet denoising on the IMFs. The signals are then reconstructed to distinguish noise from useful signals. Finally, the denoised signal’s P-wave first arrival is automatically determined using the proposed picking method based on the moving standard deviation-adaptive characteristic function and Akaike information criterion, which incorporates the relative energy coefficient and relative energy time series. Tests using synthetic seismic records with different signal-to-noise ratios and validation on real coal mine seismic datasets show that the proposed denoising strategy and picking method achieve high accuracy and robustness. In practical data tests, 90.01% of data errors fell within the range of 0s to 0.06s, demonstrating excellent picking performance. Furthermore, in grid search localization using five calibration blasts at the Dongtan coal mine, the localization results based on the proposed method significantly outperformed those based on traditional methods and PhaseNet.
Comparison of low pressure cold plasma and chemical elicitors as two approaches for enrichment of lentil sprouts with bioactive compounds
An improved feature extraction algorithm for EEG-based driving fatigue recognition
Enhancing developmental potential of vitrified in vitro matured bovine oocytes using extracellular vesicles from large follicles
Elevated ApoB/A1 ratio predicts enhanced short-term efficacy of anti-VEGF therapy in diabetic macular edema
Research on the contact characteristics of rocker arm gears in shearer under lubrication containing coal powder impurities
Cathepsin B in human peripheral blood lymphocytes as a peripheral biomarker for cardiac hypertrophy
Long-term outcomes according to birth weight after full-term pregnancy: a nationwide cohort study
LIMK1 is a prognosis and treatment biomarker in hepatocellular carcinoma
The gut microbial composition is different in chronic fatigue syndrome than in healthy controls
Cuticular hydrocarbon profiles in plump bush crickets vary according to species, sex and mating status
Abstract Cuticular hydrocarbons (CHCs) serve critical roles in insect communication and desiccation resistance and are increasingly recognized as valuable taxonomic characters. This study investigates inter- and intraspecific variation in CHC profiles across ten Isophya species representing three distinct species groups (zernovi, rectipennis, and staneki), focusing on how these profiles vary by species identity, sex, and mating status. A total of 829 individuals (411 females, 418 males) were sampled and analyzed via GC–MS to quantify CHC composition. Multivariate analyses revealed strong effects of species and sex, as well as significant species × sex × mating status interactions. In both males and females, species in the zernovi group displayed tightly clustered CHC profiles, whereas members of the rectipennis group exhibited broader within-group dispersion, with I. rectipennis forming a distinct cluster. I. staneki was clearly differentiated from all other taxa. CHCs were categorized into six structural classes, with n-alkanes being the most dominant across all taxa. Linear mixed-effects models confirmed that CHC class composition was significantly affected by sex and mating status, particularly for alkenes and methyl-branched alkanes. Notably, nonvirgin individuals showed greater CHC variability, suggesting reproductive condition influences chemical expression. While the study remains descriptive, these findings highlight the potential utility of CHCs in taxonomic resolution, sexual communication, and ecological adaptation in Isophya. The integrative use of CHC data, in combination with morphological and acoustic traits, provides a promising framework for understanding species boundaries and evolutionary divergence in Orthoptera.
Biobased self healing waterborne polyurethane with vanillin derived dynamic Imine bonds for enhanced mechanical strength and performance
Abstract Rising global interest in environmentally friendly, high-performance polymeric materials has accelerated the innovation of next-generation polyurethane systems. This research introduces a novel bio-based waterborne polyurethane, synthesized with a vanillin-derived green polyol chain extender featuring dynamic imine linkages. Vanillin diol (VAN-OH) was synthesized using a straightforward one-step condensation of vanillin and ethylenediamine, incorporating dynamic Schiff base functionality into the compound. The waterborne polyurethane (WPU) formulation was synthesized by combining the chain extender VAN-OH, dimethylolpropionic acid (DMPA), polytetrahydrofuran (PTHF), and isophorone diisocyanate (IPDI) in the proper molar ratios. The synthesis parameters were improved through a Design of Experiments (DoE) methodology to enhance mechanical characteristics. The WPU incorporating a vanillin-derived diol chain extender (WPU-VAN-OH) films exhibited a tensile strength of 12.8 MPa, three times greater than that of standard WPU at 4.3 MPa, and showed exceptional self-healing capabilities, completely mending surface scratches within 30 min at 80 °C by dynamic imine bond exchange. The material exhibited higher thermal stability, less water absorption (22.8% compared to 32.2% for WPU after 7 days), and superior adhesion to stainless steel (18.17 kgf/cm² versus 8.23 kgf/cm² for WPU). WPU-VAN-OH films presents a sustainable and efficient methodology for formulating polyurethanes characterized by high strength, self-healing properties, and environmental compatibility, appropriate for uses including protective coatings, advanced adhesives, and flexible elastomers.