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Exposure-based therapy is effective in treating anxiety, but a return of fear in the form of relapse is common. Exposure is based on the extinction of Pavlovian fear conditioning. Both animal and human studies point to increased arousal during immediate compared to delayed extinction (>+24 h), which presumably impairs extinction learning and increases the subsequent return of fear. Impaired extinction learning under arousal might interfere with psychotherapeutic interventions. The aim of the present study was to investigate whether arousal before extinction differs between extinction groups and whether arousal before extinction predicts the return of fear in a later (retention) test...

In this work we seek to enhance the frameworks practitioners in asset management and wealth management may adopt to asses how different screening rules may influence the diversification benefits of portfolios. The problem arises naturally in the area of Environmental, Social, and Governance (ESG) based investing practices as practitioners often need to select subsets of the total available assets based on some ESG screening rule. Once a screening rule is identified, one constructs a dynamic portfolio which is usually compared with another dynamic portfolio to check if it satisfies or outperforms the risk and return profile set by the company...

BACKGROUND AND PURPOSE: With the growing interest for physical therapists to incorporate musculoskeletal (MSK) ultrasound comes a need to understand how to organize training to promote the transfer of training to clinical practice. A common training strategy blends asynchronous learning through online modules and virtual simulations with synchronous practice on live simulated participants. However, few physical therapists who attend MSK ultrasound continuing education courses integrate ultrasound into clinical practice...

Introduction Artificial intelligence (AI) models using large language models (LLMs) and non-specific domains have gained attention for their innovative information processing. As AI advances, it's essential to regularly evaluate these tools' competency to maintain high standards, prevent errors or biases, and avoid flawed reasoning or misinformation that could harm patients or spread inaccuracies. Our study aimed to determine the performance of Chat Generative Pre-trained Transformer (ChatGPT) by OpenAI and Google BARD (BARD) in orthopedic surgery, assess performance based on question types, contrast performance between different AIs and compare AI performance to orthopedic residents...

Memory for inherently neutral elements of emotional events is often enhanced on delayed tests - an effect that has been attributed to noradrenergic arousal. Reactivation of a memory is thought to return its corresponding neural ensemble to a state that is similar to when it was originally experienced. Therefore, we hypothesized that neutral elements of memories, too, can be enhanced through reactivation concurrent with heightened arousal. Participants (n = 94) visited the lab for three sessions...

Modern machine learning approaches have led to performant diagnostic models for a variety of health conditions. Several machine learning approaches, such as decision trees and deep neural networks, can, in principle, approximate any function. However, this power can be considered to be both a gift and a curse, as the propensity toward overfitting is magnified when the input data are heterogeneous and high dimensional and the output class is highly nonlinear. This issue can especially plague diagnostic systems that predict behavioral and psychiatric conditions that are diagnosed with subjective criteria...

BACKGROUND: Informal caregivers are key support for patients with progressive incurable diseases. However, their own needs often remain unmet. Therefore, we developed, manualised and implemented the intervention "Being an informal caregiver - strengthening resources" aiming to support and empower informal caregivers by addressing relevant information-related, physical, psychological and social needs. METHODS: In this pilot study, we evaluated the acceptance and experiences with this psychoeducational intervention...

Anxiety and depressive disorders are highly prevalent and a leading cause of disability. Understanding how symptoms develop could lead to new preventive and clinical interventions. This pilot study examined whether systematically restricting specific behaviours (target actions) associated with good psychological health would increase psychological symptoms in healthy participants, and whether resuming those actions would reduce symptoms to baseline levels. Twelve adults participated in a series of N-of-1 trials comprising baseline (A), restriction (B) and recovery (C) phases...

Opponent modeling has proven effective in enhancing the decision-making of the controlled agent by constructing models of opponent agents. However, existing methods often rely on access to the observations and actions of opponents, a requirement that is infeasible when such information is either unobservable or challenging to obtain. To address this issue, we introduce distributional opponent-aided multiagent actor-critic (DOMAC), the first speculative opponent modeling algorithm that relies solely on local information (i...

In areas of machine learning such as cognitive modeling or recommendation, user feedback is usually context-dependent. For instance, a website might provide a user with a set of recommendations and observe which (if any) of the links were clicked by the user. Similarly, there is growing interest in the so-called "odd-one-out" learning setting, where human participants are provided with a basket of items and asked which is the most dissimilar to the others. In both of those cases, the presence of all the items in the basket can influence the final decision...

Grouping gene expression into gene set activity scores (GSAS) provides better biological insights than studying individual genes. However, existing gene set projection methods cannot return representative, robust, and interpretable GSAS. We developed NetActivity, a machine learning framework that generates GSAS based on a sparsely-connected autoencoder, where each neuron in the inner layer represents a gene set. We proposed a three-tier training that yielded representative, robust, and interpretable GSAS. NetActivity model was trained with 1518 GO biological processes terms and KEGG pathways and all GTEx samples...

Anxiety among nursing students documented during the COVID-19 pandemic reflected their fear of contracting infections, adhering to the mandatory use of masks in public, engaging in the new experience of distance learning, having financial problems, and so on. The purpose of this study was to examine the mediating role of emotional intelligence (EI) on nursing students' coping strategies and anxiety during the pandemic. This cross-sectional correlational study was conducted in a university in Jordan. An online survey was used to obtain data from a sample of 282 nursing students who had returned to on-campus learning during the summer semester of 2019/2020...

This paper reviews current knowledge on minimally invasive spine surgery (MISS). Although it has significant advantages, such as less postoperative pain, short hospital stay, quick return to work, better cosmetics, and less infection rate, there are also disadvantages. The long learning curve, the need for special instruments and types of equipment, high costs, lack of tactile sensation and biplanar imaging, some complications that are hard to treat, and more radiation to the surgeon and surgical team are the disadvantages...

Wire-arc additive manufacturing (WAAM) is a promising industrial production technique. Without optimization, inherent temperature gradients can cause powerful residual stresses and microstructural defects. There is therefore a need for data-driven methods allowing real-time process optimization for WAAM. This study focuses on machine learning (ML)-based prediction of temperature history for WAAM-produced aluminum bars with different geometries and process parameters, including bar length, number of deposition layers, and heat source movement speed...

While earthquakes are well-known to trigger surface hazards and initiate hazard cascades, whether surface hazards can instead trigger earthquakes remains underexplored. In 2018, two landslides on the Tibetan plateau created landslide-dammed lakes which subsequently breached and caused catastrophic outburst floods. Here we build an earthquake catalog using machine-learning and cross-correlation-based methods which shows there was a statistically significant increase in earthquake activity (local magnitude ≤ 2...

With the aging of the population, the quality of life and happiness of the elderly are increasingly becoming concerns of society. Smart senior care (SSC) products are an important tool to improve the quality of life of the elderly, and their application has been widely discussed. However, due to differences in cognitive characteristics and habits of the elderly, they may face difficulties when using smart products. Therefore, how to design a suitable SSC product APP interface for the elderly has become an urgent problem to be solved...

Foraging theory has been a remarkably successful approach to understanding the behavior of animals in many contexts. In patch-based foraging contexts, the marginal value theorem (MVT) shows that the optimal strategy is to leave a patch when the marginal rate of return declines to the average for the environment. However, the MVT is only valid in deterministic environments whose statistics are known to the forager; naturalistic environments seldom meet these strict requirements. As a result, the strategies used by foragers in naturalistic environments must be empirically investigated...

INTRODUCTION: The research in consumer neuroscience has identified computational methods, particularly artificial intelligence (AI) and machine learning, as a significant frontier for advancement. Previously, we utilized functional magnetic resonance imaging (fMRI) and artificial neural networks (ANNs) to model brain processes related to brand preferences in a paradigm exempted from motor actions. In the current study, we revisit this data, introducing recent advancements in explainable artificial intelligence (xAI) to gain insights into this domain...

Ulnar collateral ligaments (UCL) tears have moved from a career ending injury to one where success is almost expected from reconstruction. In reality, though, success from a UCL reconstruction is not guaranteed. As we have attempted to assess the true success rate of UCL reconstructions we have also learned the difficulties of this assessment. Rates of return to sport after ulnar collateral ligament reconstruction vary by level of play, the primary or revision status of the repair along with the specific surgical techniques performed, the chronicity of the tear, the rehab protocols associated with the surgery, and more...

BACKGROUND: Early diagnosis is key to reducing the morbi-mortality associated with P. falciparum malaria among international travellers. However, access to microbiological tests can be challenging for some healthcare settings. Artificial Intelligence could improve the management of febrile travellers. METHODS: Data from a multicentric prospective study of febrile travellers was obtained to build a machine-learning model to predict malaria cases among travellers presenting with fever...