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Transition zone-based prostate-specific antigen density for differentiating clinically significant prostate cancer in PI-RADS score 3 lesions
Optical band gap modulation in functionalized chitosan biopolymer hybrids using absorption and derivative spectrum fitting methods: A spectroscopic analysis
Overexpression of PLCG2 and TMEM38A inhibit tumor progression in clear cell renal cell carcinoma
The myometrial transcriptome changes in mares with endometrosis
A quantum-optimized approach for breast cancer detection using SqueezeNet-SVM
Subclinical depressive symptoms and job stress differentially impact memory in working and retired older adults
Abstract Retirement has been associated with cognitive decline beyond normal age-related decline. However, there are many individual differences in retirement that can influence cognition. Subclinical depressive symptoms are common in late life and are associated with general memory decline and a bias towards remembering negative events (i.e., better memory for negative vs. positive or neutral stimuli), in opposition to a reported positivity bias (i.e., better memory for positive vs. negative or neutral stimuli) in aging. Furthermore, job stress is often a major contributor to retirement decisions and may impact cognition post-retirement. Here, we aimed to examine how subclinical depressive symptoms and job stress in working and retired older adults impacted emotional memory. We found that retired, but not working, older adults with greater depressive symptoms showed enhanced negative and impaired positive memory. Second, working older adults with moderately high current job stress showed better memory overall but a weaker positivity bias, while retired older adults with moderately high retrospective job stress showed worse memory overall and a stronger positivity bias. These findings suggest that subclinical depressive symptoms and job stress have differing impacts on emotional memory in late life depending on retirement status.
Enhancing lane detection in autonomous vehicles with multi-armed bandit ensemble learning
Abstract This study introduces a novel ensemble learning technique namely Multi-Armed Bandit Ensemble (MAB-Ensemble), designed for lane detection in road images intended for autonomous vehicles. The foundation of the proposed MAB-Ensemble technique is inspired in terms of Multi-Armed bandit optimization to facilitate efficient model selection for lane segmentation. The benchmarking dataset namely TuSimple is used for training, validating and testing the proposed and existing lane detection techniques. Convolutional Neural Networks (CNNs) architecture which includes ENet, PINet, ResNet-50, ResNet-101, SqueezeNet, and VGG16Net are employed in lane detection problems to construct segmentation models and demonstrate proficiency in distinct road conditions. However, the proposed MAB-Ensemble technique overcomes the limitations of individual models by dynamically selecting the most suitable CNN model based on prevailing environmental factors. The proposed technique optimizes the segmentation accuracy and treats the attained accuracy as a reward signal in the context of reinforcement learning by interacting with the environment through CNN model selection. The MAB-Ensemble achieved an overall accuracy of 90.28% in different road conditions. The results overcome the performance of the individual CNN models and state-of-the-art ensemble techniques. Also, it demonstrates superior performance which includes daytime, night-time, and abnormal road conditions. The MAB-Ensemble technique offers a promising solution for robust lane detection by harnessing the collective strengths of diverse CNN models.
Enhanced optical properties of chitosan polymer doped with orange peel dye investigated via UV–Vis and FTIR analysis
Heart rate variability biofeedback in a global study of the most common coherence frequencies and the impact of emotional states
Age group classification based on optical measurement of brain pulsation using machine learning
Biocompatibility of variable thicknesses of a novel directly printed aligner in orthodontics
Abstract Direct printed aligners (DPAs) offer benefits like the ability to vary layer thickness within a single DPA and to 3D print custom-made removable orthodontic appliances. The biocompatibility of appliances made from Tera Harz TA-28 (Graphy Inc., Seoul, South Korea) depends on strict adherence to a standardized production and post-production protocol, including UV curing. Our aim was to evaluate whether design modifications that increase layer thickness require a longer UV curing time to ensure biocompatibility. Specimens with varying layer thickness were printed to high accuracy using Tera Harz TA-28 and the Asiga MAX 3D printer (Asiga SPS ™ technology, Sydney, Australia). UV curing durations were set at 20, 30 and 60 min. Cytotoxicity was evaluated using the AlamarBlue assay on human gingival fibroblasts. Cell viability decreased with increasing specimen thickness (significant for 2 mm [p < 0.001], 4 mm [p < 0.0001], and 6 mm [p < 0.01]) under the manufacturer-recommended 20-min UV curing. Extending the curing time did not improve cell viability. However, cell viability never decreased by more than 30%, meeting EN ISO 10993-5 standards for non-cytotoxicity. The standard 20-minute UV curing protocol ensures the biocompatibility and patient safety of Tera Harz TA-28 for material thicknesses up to 6 mm.
Therapeutic alternatives for sporotrichosis induced by wild-type and non-wild-type Sporothrix schenckii through in vitro and in vivo assessment of enilconazole, isavuconazole, posaconazole, and terbinafine
Proteomic analysis of Trichoderma harzianum secretome and their role in the biosynthesis of zinc/iron oxide nanoparticles
Evaluating physician concordance in interpretation of tracheobronchomalacia diagnosis and phenotyping using dynamic expiratory chest computed tomography
Temporal transcriptional profiling of host cells infected by a veterinary alphaherpesvirus using nanopore sequencing
Abstract In our research, we performed temporal transcriptomic profiling of host cells infected with Equid alphaherpesvirus 1 (EHV-1) by utilizing direct cDNA sequencing based on nanopore MinION technology. The sequencing reads were harnessed for transcript quantification at various time points. Viral infection-induced differential gene expression was identified through the edgeR package. The identified genes were segmented into six groups based on their kinetic characteristics. The initial three clusters encompass immediate-early response genes, typically transcription factors and elements of antiviral signaling pathways. These genes were either upregulated (cluster 1) or downregulated (clusters 2 and 3) during the early infection phase. The remaining three clusters include late response genes. In these categories, it is challenging to determine whether changes in gene expression are directly connected to the viral infection or merely side effects of the infection. A study of gene associations using the STRINGDB software revealed several gene networks that might be directly impacted by the virus. We also explored whether gene co-expression could be a result of their collective regulation by upstream transcription factors using the Gene Regulatory Network database. Finally, our differential transcript usage (DTU) analysis identified a number of genes that exhibited altered proportions of transcript isoforms in comparison to non-infected cells. Thus, our analysis revealed that EHV-1 infection not only alters host gene expression but also leads to differential use of transcript isoforms, particularly splice variants.
Mechanism of microscopic behind the influence of stress loading on gas adsorption by coal
A high-speed MPPT based horse herd optimization algorithm with dynamic linear active disturbance rejection control for PV battery charging system
Clinical value of quantitative echocardiographic features in preterm infants with necrotizing enterocolitis
Asymptomatic female softball pitchers have altered hip morphology and cartilage composition
Abstract Few studies have explored hip morphology and cartilage composition in female athletes or the impact of asymmetric repetitive loading, such as occurs during softball pitching. The current cross-sectional study assessed bilateral bony hip morphology on computed tomography imaging in collegiate-level softball pitchers (‘Pitch1’, n = 25) and cross-country runners (‘Run’, n = 13). Magnetic resonance imaging was used to assess cartilage relaxation times in a second cohort of pitchers (‘Pitch2’, n = 10) and non-athletic controls (‘Con’, n = 4). Pitch1 had 52% greater maximum alpha angle than Run (p < 0.001) and were 21.3 (95% CI 2.4 to 192.0) times more likely to have an alpha angle ≥ 60° within at least one hip. Pitch2 had longer T2 relaxation times in the superior femoral cartilage of the drive leg (same side as the throwing arm) and stride leg than Con (all p < 0.02). The drive leg in Pitch2 had longer T1ρ and T2 relaxation times in the superior femoral cartilage compared to the stride leg (all p ≤ 0.03). Asymptomatic softball pitchers exhibit altered bony hip morphology and cartilage composition compared to cross-country runners and non-athletic controls, respectively. They also exhibit asymmetry in cartilage composition. Further studies with larger sample sizes are warranted and any potential long-term consequences of the changes in terms of symptom and osteoarthritis development requires investigation.