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Resisting obsessive-compulsive disorder (OCD) compulsions is a key predictor of exposure and response prevention (ERP) effectiveness, yet trauma-exposed individuals with OCD endorse more severe compulsions and are more likely to be labelled 'treatment resistant.' Among trauma-exposed individuals, compulsions are theorised to function to prevent future trauma and cope with trauma-related responses.

OBJECTIVE: To investigate a recently developed MRI technique for mapping the Mean Diffusivity of Tissue (MDT), which improves diffusion MRI imaging of the cerebral cortex by reducing partial volume effects from cerebrospinal fluid (CSF). As cortical lesions are common in patients with focal epilepsy, we explored the clinical value of MDT imaging in patients with drug resistant epilepsy and low-gra

Aims ECG monitoring is often required during critical phases of illness. To evaluate the role of modern technology and advanced analytical algorithms artificial intelligence compared with standard-of care, we undertook a prospective, head-to-head comparison of a novel, cable-free, patch-based, and AI-enhanced electrocardiography system (CardioSenseSystem) with standard of care (SOC) ECG monitoring

This paper firstly proposes a simple yet efficient generalized approach to apply differential privacy to text representation (i.e., word embedding). Based on it, we propose a user-level approach to learn personalized differentially private word embedding model on user generated contents (UGC). To our best knowledge, this is the first work of learning user-level differentially private word embeddin

Background Parenthood is consistently identified as a protective factor for suicidal behavior. However, it remains unclear whether this relationship varies as a function of sex, age, time since birth, number of children, and other risk/protective factors. Methods We used Cox proportional hazards models to describe the relationship between the birth of up to four children and suicide attempt (SA) r

A major challenge hampering the industrial and biological exploitation of lipases is the self-limiting effect of the lipolytic reaction. Defying sustained attention throughout history, the influence of lipase catalysed lipolysis on the internal structure of thin triglyceride films has proved elusive. An in-depth understanding of the lipolysis process at the triglycerides/aqueous interface will ass

Aqueous zinc-ion batteries have emerged as strong contenders for sustainable energy storage; however, their widespread adoption is constrained by sluggish Zn2+ transport and suboptimal cathode performance. A rapid, energy-efficient solvothermal synthesis of Na2V6O16 is reported, and introduces cation vacancies via initial electrochemical engineering. This electrochemical pre-treatment generate

The diffusion of water and the cross relaxation between water and cellulose in a hydrated paper system were followed with the Goldman-Shen and the pulsed-field-gradient stimulated-echo NMR pulse sequences as a function of moisture content. The diffusion coefficient measured along the plane of the paper sheet is very sensitive to the moisture content; more water leads to faster diffusion. The cress

The first measurement of the polarisation of coherently photoproduced J/ψ mesons in ultra-peripheral Pb–Pb collisions, using data at sNN=5.02 TeV, is presented. The J/ψ meson is measured via its dimuon decay channel in the forward rapidity interval −4.0

Large language models (LLMs) and their applications in low-resource languages (such as in Vietnamese) are limited due to lack of training data and benchmarking datasets. This paper introduces a practical real-world implementation of a question answering system for Vietnamese, called ViGPTQA, leveraging the power of LLM. Since there is no effective LLM in Vietnamese to date, we also propose, evalua

Characterizing the effect of pesticides on pollinators is essential in the strive to protect biodiversity while maintaining efficient food production. Metabolomics offers detailed insight into the physiological response to pesticides. The impact of pre-dissection and dissection methodology on the metabolic response remains largely unknown, as does their possible effect on the measured metabolic re

SARS-CoV-2 breakthrough infections (BTIs) are relatively common, but little is known in terms of differentiating responses associated with asymptomatic BTI (ABTI) versus symptomatic BTI (SBTI). Here, we investigated the impact of ABTI and SBTI on antibody and T-cell responses toward Spike. SBTI donors had significantly higher plasma anti-Spike RBD IgG titers compared to both ABTI and SARS-CoV-2 va

BACKGROUND: The Leiden group and the Assessment of Spondyloarthritis International Society (ASAS)-MRI study group have proposed definitions for structural (SL) and active (AL) lesions typical for axial spondyloarthritis (axSpA) on MRI of the sacroiliac joints (MRI-SIJ).OBJECTIVES: To analyse the predictive validity of proposed SL and AL MRI-SIJ definitions in early axSpA and compare proposed AL wi

Given the increasing number of heterogeneous data stored in relational databases, file systems or cloud environment, it needs to be easily accessed and semantically connected for further data analytic. The potential of data federation is largely untapped, this paper presents an interactive data federation system (https://vimeo.com/319473546) by applying large-scale techniques including heterogeneo

Rhesus macaques (RMs) are a vital model for studying human disease and are invaluable to preclinical vaccine research, particularly for the study of broadly neutralizing antibody responses. Such studies require robust genetic resources for antibody-encoding genes within the immunoglobulin (IG) loci. The complexity of the IG loci has historically made them challenging to characterize accurately. To

Automatic voice pathology detection is promising for non-invasive screening and early intervention using sound signals. Nevertheless, existing methods are susceptible to covariate shifts due to background noises, human voice variations, and data selection biases leading to severe performance degradation in real-world scenarios. Hence, we propose a non-invasive framework that contrastively learns p