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Attention Allocation for Dysphoric Information in Adults with Depression Symptoms Using Eye-tracking and Mouse-tracking
Biased attention for dysphoric stimuli is thought to maintain depression, but poor measurement has limited prior tests of this hypothesis. The current study examined the association between biased attention for dysphoric information and depression using a novel free viewing attention bias task combined with measuring line of visual gaze via eye tracking or a behavioral proxy for line of visual gaze via mouse tracking in three samples of college students using in-person eye-tracking (Experiment 1, N = 129) and remotely collected mouse-tracking (Experiment 2, N = 79; Experiment 3, N = 154). Mixed effects regression analyses revealed that depression severity was significantly associated with greater attention for dysphoric stimuli in Experiments 1 and 2, but not Experiment 3. Results suggest that depression severity is associated with attention for dysphoric information (although findings from Experiment 3 temper this conclusion) and that eye- and mouse-tracking may be good options for measuring attention bias in depression. Additional work using longitudinal research designs seems warranted to further examine the relationship between attention bias for dysphoric information and the maintenance of depression.
Spatial monitoring of open caissons via computer vision approach
Sustainable hydrophobic bio-based adsorbent from modified sphagnum moss for efficient oil-water separation
Separation of thoracic and abdominal measurements in neonatal vital sign monitoring using radar vision fusion system
Research on intelligent identification of microscopic substances in shale scanning electron microscope images based on deep learning theory
Association between organophosphate esters exposure and the prevalence of hyperuricemia in US adults from NHANES 2011–2016
Magnetic properties and entanglement in antiferromagnetic interactions in copper(II) dinuclear and trinuclear complexes
Theoretical research and system design of ship navigation guidance for local temporary prohibited navigation area
Exploring the injury severity of unlicensed powered two- and three-wheeler drivers in two-vehicle crashes in China
Abstract Large presence of unlicensed powered two- and three-wheeler (PTW) drivers in China pose a significant threat to road safety. In this study, a customized Deep Forest Model (DF-ptw) is constructed to investigate the effect of unlicensed PTW drivers on crash severity in two-vehicle crashes, using a recent 3-year historical crash data. SHapley Additive explanation (SHAP) and Partial Dependence Plot (PDP) analysis reveal that unlicensed motorcyclists are significantly more likely to suffer serious injuries in two-vehicle crashes compared to unlicensed auto-rickshaw drivers. Additionally, factors such as drunk driving, fatigued driving, and being an unlicensed driver over the age of 53 notably elevate the risk of serious injury or death, with unlicensed motorcyclists being disproportionately affected. Moreover, self-employed unlicensed PTW drivers face a higher probability of serious injury or fatality in crashes compared to farmers, blue-collar, and white-collar workers. Unlicensed PTW drivers are also more susceptible to severe or fatal injuries on national and provincial roads, in low visibility conditions, during late-night hours, on non-separated roads, and at dusk or dawn. Based on these findings, this study proposes to reduce the frequency and severity of crashes involving unlicensed PTW drivers by focusing on more stringent eligibility checks, increasing safety awareness, and implementing advanced safety measures.
Experimental investigation of the role of hexamethylenediamine in controlling fine migration in clay-rich sandstones
Htra4 promotes vascular endothelial cell injury and is associated with the early-onset of preeclampsia
ICRL: independent causality representation learning for domain generalization
Computational insights into exploring the potential effects of environmental contaminants on human health
Active regulatory elements recruit cohesin to establish cell specific chromatin domains
Abstract As the 3D structure of the genome is analysed at ever increasing resolution it is clear that there is considerable variation in the 3D chromatin architecture across different cell types. It has been proposed that this may, in part, be due to increased recruitment of cohesin to activated cis-elements (enhancers and promoters) leading to cell-type specific loop extrusion underlying the formation of new sub-TADs. Here we show that cohesin correlates well with the presence of active enhancers and that this varies in an allele-specific manner with the presence or absence of polymorphic enhancers which vary from one individual to another. Using the alpha globin cluster as a model, we show that when all enhancers are removed, peaks of cohesin disappear from these regions and the erythroid specific sub-TAD is no longer formed. Re-insertion of the major alpha globin enhancer (R2) is associated with re-establishment of recruitment and increased interactions. In complementary experiments insertion of the R2 enhancer element into a “neutral” region of the genome recruits cohesin, induces transcription and creates a new large (75 kb) erythroid-specific domain. Together these findings support the proposal that active enhancers recruit cohesin, stimulate loop extrusion and promote the formation of cell specific sub-TADs.
Selenomethionine inhibits the proliferation of hypoxia-induced pulmonary artery smooth muscle cells by inhibiting ROS and HIF-1α-ACE-AngII axis
Using artificial intelligence system for assisting the classification of breast ultrasound glandular tissue components in dense breast tissue
Deep learning for simultaneous phase and amplitude identification in coherent beam combination
Abstract Coherent beam combination has emerged as a promising strategy for overcoming the power limitations of individual fibre lasers. This approach relies on maintaining precise phase difference between the constituent beamlets, which are typically established using phase retrieval algorithms. However, phase locking is often studied under the assumption that the power levels of the beamlets remain stable, an idealisation that does not hold always in practical applications. Over the operational lifetime of fibre lasers, power degradation inevitably occurs, introducing additional challenges to phase retrieval. To address this, we propose a deep learning algorithm for single-step simultaneous phase and amplitude identification, directly from a single camera observation of the intensity distribution of the combined beam. By leveraging its ability to detect and interpret subtle variations in intensity interference patterns, the deep learning approach can accurately disentangle phase and power contributions, even in the presence of significant power fluctuations. Using a spatial light modulator, we systematically investigate the impact of power-level fluctuations on phase retrieval within a simulated coherent beam combination system. Furthermore, we explore the scalability of this deep learning approach by evaluating its ability to achieve the required phase and amplitude precision as the number of beamlets increases.
Hybrid vision GNNs based early detection and protection against pest diseases in coffee plants
Taper wear in total joint arthroplasty can be reliably assessed with various coordinate measuring systems
Abstract In total joint arthroplasty, wear and corrosion at modular taper junctions is an issue with clinical implications, as ions and wear debris can lead to adverse tissue reactions. The quantification of the generated wear is, therefore, an important measure to judge the performance of such modular junctions. This applies to pre-clinical in vitro investigations as well as to retrospective investigations of retrieved implants. The volume of the worn material can be determined with coordinate measuring machines (CMMs), which can generally be classified as tactile and optical systems. The study aims on the comparison of a tactile with two optical CMM systems for the determination of taper wear. To do so, four taper samples—three trunnions and one bore taper—with different amounts of known volumetric wear (range 1.5 mm3 to 8.3 mm3) were fabricated. Wear volume, linear deviation and taper angle were determined with the different CMM systems. The tactile system yielded the highest deviation from the gravimetric reference values of about 0.3 mm3, while the optical systems exhibited deviations of about 0.1 mm3 and 0.2 mm3. Clinically relevant taper wear, however, is well measurable with all investigated systems.