Browse Articles

Adverse childhood experiences and elder abuse victimization nexus: A systematic review and meta-analysis

Adverse childhood experiences (ACEs) are important life course events that can influence elder abuse victimisation (EAV) among older adults. This systematic review and meta-analysis aimed to provide synthesised and consolidated evidence on the existing associations between ACEs and EAV. A systematic search was conducted across six databases, including PubMed, PsycINFO, CINAHL Complete, Scopus, Google Scholar, and the Web of Science. All studies that addressed associations between ACEs, in singular or multiple form, and EAV were included in the review. Meta-analysis of the extracted odds ratios (ORs) and confidence intervals (CIs) was conducted using the common-effect inverse-variance model. Nine studies (cross-sectional design = 7; cohort design = 2) met the inclusion criteria. Included studies examined multiple ACEs and multiple EAVs associations (N = 3); at least single ACE and multiple EAVs (N = 3); any single form of ACE and multiple EAVs (N = 3); multiple ACEs–any single form of EAV nexus (N = 2); multiple ACEs–financial elder abuse association (N = 2); and multiple ACEs–physical elder abuse nexus (N = 2). Pooled ORs and CIs showed statistically significant results for all ACEs and EAVs associations whether in singular or multiple form. The results indicate that interventions designed to reduce ACEs, in singular or multiple form, early in life targeting residential and community-dwelling older adults may be relevant in reducing the incidence of EAV. The life course perspective s be integrated into the planning for support services for children, families, and older adults to prevent EAV in singular or multiple forms in later life.

Influence of injection angles on flow structures and mixing properties in a supersonic combustor at low Mach supersonic crossflow

Effects of Iron Impurities and Content on Electrochemical Performance and Oxygen Evolution Selectivity of Nickel Catalysts for Ethanol Oxidation

Research on the mechanism of digital drive economy enhancing quality and efficiency

This paper, based on unstructured data, examines the outcomes and impact mechanisms of digitalization from the perspective of technological advancement and institutional evolution, providing empirical evidence for the role of digitalization in promoting economic quality and efficiency. The study finds that digitalization contributes to the improvement of regional economic development efficiency. Its economic impact primarily manifests in the transformation of traditional value creation models and the enhancement of marketization levels. The digital economy, by activating digital platforms, alleviates the problem of information asymmetry, thereby enhancing the standardization of market transactions and improving economic efficiency.

Impact of host physiology and external stressors on the bacterial community of Schmidtea mediterranea

Abstract To fully comprehend host-microorganism interactions, it is crucial to understand the composition and diversity of the microbiome, as well as the factors that shape these characteristics. We investigated microbiome variation using the freshwater planarian Schmidtea mediterranea, an invertebrate model in regeneration biology and (eco-)toxicology, by exposing the organisms to various controlled conditions. The microbiome composition exhibited high variability, with most of the bacteria belonging to the Betaproteobacteria. Among the diverse microbial communities, a few genera, such as Curvibacter, were consistently present, but exhibited significant alterations in response to changing conditions. The relative abundance of Curvibacter fluctuated during the regeneration process, initially increasing before returning to a composition similar to the beginning situation. After applying external stress, the relative abundance of Curvibacter and other genera decreased. Variation over time, between different origin laboratories and between individuals, showed that additional, yet to-be-identified, factors of variation are present. Taking all results together, our study provides a solid basis for future research focusing on bacterial functionality in planarians and other invertebrates.

High-Pressure Neutron Diffraction Study on ε-FeOOH: The Spin-Reorientation Transition and Hydrogen-Bond Symmetrization

Analysis of vehicle carbon emission characteristics on expressways in mountainous plateau areas based on the coupled simulation of CarSim/TruckSim and MOVES

Expressways in mountainous plateau areas exhibit complex driving conditions and harsh climatic characteristics that continuously impact vehicle carbon emissions throughout their entire lifecycle and determine the carbon emission levels of expressways during the operational period. To study the carbon emission characteristics of expressways in the western Sichuan Plateau mountainous area, a coupling simulation analysis method combining CarSim/TruckSim simulation software and the Motor Vehicle Emissions Simulator (MOVES) was employed to analyze the spatial distribution characteristics of vehicle-specific power (VSP). This analysis was based on the alignment data and operational environment of the Wenchuan‒Barkam Expressway in the mountainous area of the western Sichuan Plateau. A conversion formula was established to calculate the cumulative VSP per second and total carbon emissions of each unit. Statistical analysis was conducted on the distribution of carbon emissions equivalent per kilometer across the different alignment units. Distribution ranges of carbon emissions equivalent per kilometer for light-duty vehicles (LDVs) and heavy-duty vehicles (HDVs) at each alignment unit were 60‒240 g and 100‒1600 g, respectively. The grey relational analysis method was used to quantify the relationship between the carbon emissions equivalent per kilometer of alignment units, circular curves radius, and average grade. Based on the vertical variations in climatic changes with altitude in the mountainous plateau area, a comparative analysis was performed on the trends in the effects of altitude, season, and vehicle starting frequency on carbon emissions. Frequent vehicle starts significantly impacted carbon emissions, and this impact was significantly higher in winter than in summer. Carbon emissions equivalent of the LDV and HDV starting twice on average in summer were approximately 1.09- and 1.04-times higher, respectively, than that when vehicles were started 0.5 times; whereas, in winter, they were 1.17- and 1.07-times higher, respectively.

Amyloids in bladder cancer hijack cancer-related proteins and are positive correlated to tumor stage

Steering the Absorption Configuration of Intermediates over Pd-Based Electrocatalysts toward Efficient and Stable CO₂ Reduction

Impact of morphological traits and irrigation levels on fresh herbage yield of sorghum x sudangrass hybrid: Modelling data mining techniques

In this study, the effect of morphological traits on fresh herbage yield of sorghum x sudangrass hybrid plant grown in Konya province, which is the largest cereal production area in Turkey, was analyzed with some data mining methods. For this purpose, Artificial Neural Networks (ANN), Automatic Linear Model (ALM), Random Forest (RF) Algorithm and Multivariate Adaptive Regression Spline (MARS) Algorithm were used, and the prediction performances of these methods were compared. Plant height of 251.22 cm, stem diameter of 7.03 mm, fresh herbage yield of 8010.69 kg da-1, crude protein ratio of 9.09%, acid detergent fiber 33.23%, neutral detergent fiber 57.44%, acid detergent lignin 7.43%, dry matter digestibility of 63.01%, dry matter intake 2.11%, and relative feed value of 103.02 were the descriptive statistical values that were computed. Model fit statistics, including coefficient of determination (R2), adjusted R2, root of mean square error (RMSE), mean absolute percentage error (MAPE), standard deviation ratio (SD ratio), Mean Absolution Error (MAE) and Relative Absolution Error (RAE), were used to evaluate the prediction abilities of the fitted models. The MARS method was shown to be the best model for describing fresh herbage yield, with the lowest values of RMSE, MAPE, SD ratio, MAE and RAE (137.7, 1.488, 0.072, 109.718 and 0.017, respectively), as well as the highest R2 value (0.995) and adjusted R2 value (0.991). The experimental results show that the MARS algorithm is the most suitable model for predicting fresh herbage yield in sorghum x sudangrass hybrid, providing a good alternative to other data mining algorithms.

Different behavior of electrosurgical currents between air and saline immersion therapeutic endoscopy

Radical <i>S</i>-Adenosylmethionine Sulfurtransferase MybB Catalyzed Formation of the 4-Thiazolidinone Core in Mycobacidin Represents an Intersection between Primary and Secondary Metabolism

Assessing the application of adapted theory of planned behaviour in predicting postpartum family planning intentions in a pragmatic randomized control trial in Western Kenya

Introduction In developing countries like Kenya, addressing the high population growth rate necessitates a focus on early Postpartum Family Planning (PPFP) use. Despite the critical need for PPFP, few researchers explore the application of health behaviour change theories to enhance FP use among postpartum women. This study assesses the application of adapted Theory of Planned Behaviour (TPB) in predicting intention for early PPFP in postpartum women in Western Kenya. Methods This randomized control trial included pregnant women aged 15 to 49 attending Antenatal Care (ANC) clinics, randomly assigned to the "Nurses’ arm," "Community arm," or "Control arm." The intervention provided family planning (FP) counseling. Trained nurses and Community Health Workers (CHW) delivered counseling in their respective arms, while the control arm received routine care. Adapted TPB was integrated into client exit interviews to identify constructs influencing early PPFP intentions. Structural equation modeling (SEM) was used to predict the intention for early PPFP in the adapted TPB. Results The SEM was optimized with the removal of client knowledge on early PPFP. The final model retained satisfaction with PPFP counseling, perceived normative beliefs, attitude towards PPFP, behaviour control of PPFP choice, and perceived risk of early postpartum pregnancy. Only satisfaction with counseling (P = 0.001), perceived normative beliefs (P&lt;0.0001), attitude towards PPFP (P&lt;0.0001), and behaviour control of PPFP choice (P = 0.018) significantly influenced early PPFP intention. Conclusion The study demonstrates a viable application of the adapted TPB model in predicting early PPFP intention in an interventional study. Trial registration The study was registered by the Pan African Clinical Trial Registry on 03 July 2021 with a Trial Registration Number PACTR202107891858045. The trial was prospectively registered.

Multiphoton imaging-based quantifiable collagen signatures for predicting outcomes in patients with pancreatic ductal adenocarcinoma

Directed Evolution and Unusual Protonation Mechanism of Pyridoxal Radical C–C Coupling Enzymes for the Enantiodivergent Photobiocatalytic Synthesis of Noncanonical Amino Acids

Image-Based Phenotypic Profiling Enables Rapid and Accurate Assessment of EGFR-Activating Mutations in Tissues from Lung Cancer Patients

Neuroimaging findings and balance problems after mild traumatic brain injury: A systematic review protocol

Objective To systematically review studies relating neuroimaging findings to balance problems resulting from a history of mTBI. Introduction Mild traumatic brain injury affects 55.9 million people worldwide every year. These injuries can have persistent symptoms such as maintaining balance which can be life-altering. Difficulties maintaining balance persist months or years after a mild traumatic brain injury in &gt;30% of patients. Neuroimaging modalities, including magnetic resonance imaging, diffusion-weighted imaging, functional magnetic resonance imaging, electroencephalography, and magnetoencephalography, have been associated with presentation or persistence of balance difficulties, but no clinical guidelines are currently in place. Inclusion criteria Studies will include participants of any age or sex who were diagnosed as having mild traumatic brain injury by a medical professional, excluding studies which by design included patients with other conditions diagnosed using neuroimaging findings. There must be at least one post-injury scan from at one or more of the included neuroimaging modalities, and assessment of balance problems. A comparator must be present in the form of either a control group or longitudinal design. Methods A search will be conducted in Elsevier (Embase), MEDLINE (PubMed), Google Scholar, SportDiscus (EBSCOhost) and ProQuest for studies meeting the inclusion criteria, published 2013-2024, and available in English. Reviews will not be included. The process of study selection, critical assessment, data extraction, and summarizing findings will be conducted by two independent reviewers, with disagreements resolved by a third. The meta-analysis will summarize the strength of association between specific findings related to brain regions using various neuroimaging modalities and the presentation or persistence of balance difficulties. Evidence related to each neuroimaging modality will summarized using the GRADE approach. Trial registration Systematic review registration number: CRD42024476988 .

Integrative analysis of anoikis-related prognostic signature to evaluate the immune landscape and predict therapeutic response in stomach adenocarcinoma

Observation of Robust Compressed CuO₆ Octahedra and Exotic Spin Structure in CaCuFe₂O₅

Surface defect detection on industrial drum rollers: Using enhanced YOLOv8n and structured light for accurate inspection

Drum roller surface defect detection is of great research significance for control production quality. Aiming at solving the problems that the traditional light source visual imaging system, which does not clearly reflect defect features, the defect detection efficiency is low, and the accuracy is not enough, this paper designs an image acquisition system based on line fringe structured light and proposes an improved deep learning network model based on YOLOv8n to achieve efficient detection of defects on the rolling surface of a drum roller. In the aspect of image acquisition, this paper selected the line fringe structured light as the system light source, which made up for the problem that the traditional light source does not reflect the defect characteristics. In terms of algorithms, firstly, using deformable convolution instead of standard convolution to enhance the feature extraction ability of the backbone network. Then, a new feature fusion module was proposed to enable the fusion network to learn additional original information. Finally, Wise-IoU was applied to replace CIoU in the loss function, so that the network pays more attention to the high-quality samples. The experimental results show that the improved YOLOv8n algorithm has a certain improvement in detection accuracy. The main average accuracy (mAP) is 97.2%, and the detection time is 4.3ms. The system and algorithm designed in this paper can better ensure the production quality of drum rollers. While effective, the model’s standard rectangular bounding boxes may limit precision for elongated defects. Future work could explore rotated bounding boxes and broader dataset diversity to enhance generalization in real-world applications.