Automatic detection of problem-gambling signs from online texts using large language models.

Problem gambling is a major public health concern and is associated with profound psychological distress and economic problems. There are numerous gambling communities on the internet where users exchange information about games, gambling tactics, as well as gambling-related problems. Individuals exhibiting higher levels of problem gambling engage more in such communities.

Pharmacological Enhancement of Dopamine Neurotransmission Does Not Affect Illusory Pattern Perception.

Psychotic symptoms and delusional beliefs have been linked to dopamine transmission in both healthy and clinical samples and are assumed to result at least in part from perceiving illusory patterns in noise. However, the existing literature on the role of dopamine in detecting patterns in noise is inconclusive. To address this issue, we assessed the effect of manipulating dopaminergic neurotransmission on illusory pattern perception in healthy individuals (= 48, = 19 female) in a double-blind placebo-controlled within-subjects design (see preregistration at https://osf.

Decomposition of Reinforcement Learning Deficits in Disordered Gambling via Drift Diffusion Modeling and Functional Magnetic Resonance Imaging.

Gambling disorder is associated with deficits in reward-based learning, but the underlying computational mechanisms are still poorly understood. Here, we examined this issue using a stationary reinforcement learning task in combination with computational modeling and functional resonance imaging (fMRI) in individuals that regular participate in gambling (n = 23, seven fulfilled one to three DSM 5 criteria for gambling disorder, sixteen fulfilled four or more) and matched controls (n = 23). As predicted, the gambling group exhibited substantially reduced accuracy, whereas overall response times (RTs) were not reliably different between groups.

Corrigendum: Individuals under voluntary treatment with sexual interest in minors: what risk do they pose?

[This corrects the article DOI: 10.3389/fpsyt.2023.

Active afforestation of drained peatlands is not a viable option under the EU Nature Restoration Law.

The EU Nature Restoration Law (NRL) is critical for the restoration of degraded ecosystems and active afforestation of degraded peatlands has been suggested as a restoration measure under the NRL. Here, we discuss the current state of scientific evidence on the climate mitigation effects of peatlands under forestry. Afforestation of drained peatlands without restoring their hydrology does not fully restore ecosystem functions.

Acceptance and Usability of a Soft Robotic, Haptic Feedback Seat for Autonomy Level Transitions in Highly Automated Vehicles.

Fully autonomous vehicles, capable of completing entire end-to-end journeys without the interference of a human driver, will be one of the biggest transforming technologies of the next decades. As the journey towards fully autonomous vehicles progresses, there will be an increase in the number of highly automated vehicles on the roads, requiring the human driver to take back control in situations, which cannot be handled by the vehicle autonomously. These human-robot take-over requests can lead to safety risks, in particular in scenarios when the driver fails to understand the take-over request and, hence, lacks situational awareness.

On the Benefit of Optimal Transport for Curriculum Reinforcement Learning.

Curriculum reinforcement learning (CRL) allows solving complex tasks by generating a tailored sequence of learning tasks, starting from easy ones and subsequently increasing their difficulty. Although the potential of curricula in RL has been clearly shown in various works, it is less clear how to generate them for a given learning environment, resulting in various methods aiming to automate this task. In this work, we focus on framing curricula as interpolations between task distributions, which has previously been shown to be a viable approach to CRL.

Identification, semi-quantification and risk assessment of contaminants of emerging concern in Flemish indoor dust through high-resolution mass spectrometry.

Indoor dust can contribute substantially to human exposure to known and contaminants of emerging concern (CECs). Novel compounds with high structural variability and different homologues are frequently discovered through screening of the indoor environment, implying that constant monitoring is required. The present study aimed at the identification and semi-quantification of CECs in 46 indoor dust samples collected in Belgium by liquid chromatography high-resolution mass spectrometry.

Individuals under voluntary treatment with sexual interest in minors: what risk do they pose?

Child Sexual Abuse (CSA) and the production, use, and distribution of Child Sexual Abuse Material (CSAM) are key threats to children's mental health. From the perspective of indicated prevention, it can be assumed that some persons with a sexual interest in children commit such unreported crimes. Accordingly, the German Network (meaning ) has implemented a confidential treatment service for persons with a sexual interest in minors who voluntarily seek therapy, might or might not have offended but have not yet been detected or have fulfilled all legal requirements (here referred to as non-forensic individuals).

A human-centered safe robot reinforcement learning framework with interactive behaviors.

Deployment of Reinforcement Learning (RL) algorithms for robotics applications in the real world requires ensuring the safety of the robot and its environment. Safe Robot RL (SRRL) is a crucial step toward achieving human-robot coexistence. In this paper, we envision a human-centered SRRL framework consisting of three stages: safe exploration, safety value alignment, and safe collaboration.

Variational Hierarchical Mixtures for Probabilistic Learning of Inverse Dynamics.

Well-calibrated probabilistic regression models are a crucial learning component in robotics applications as datasets grow rapidly and tasks become more complex. Unfortunately, classical regression models are usually either probabilistic kernel machines with a flexible structure that does not scale gracefully with data or deterministic and vastly scalable automata, albeit with a restrictive parametric form and poor regularization. In this paper, we consider a probabilistic hierarchical modeling paradigm that combines the benefits of both worlds to deliver computationally efficient representations with inherent complexity regularization.

Chronic Deep Brain Stimulation of the Human Nucleus Accumbens Region Disrupts the Stability of Intertemporal Preferences.

When choosing between rewards that differ in temporal proximity (intertemporal choice), human preferences are typically stable, constituting a clinically relevant transdiagnostic trait. Here we show, in female and male human patients undergoing deep brain stimulation (DBS) of the anterior limb of the internal capsule/NAcc region for treatment-resistant obsessive-compulsive disorder, that long-term chronic (but not phasic) DBS disrupts intertemporal preferences. Hierarchical Bayesian modeling accounting for temporal discounting behavior across multiple time points allowed us to assess both short-term and long-term reliability of intertemporal choice.

Dopamine regulates decision thresholds in human reinforcement learning in males.

Dopamine fundamentally contributes to reinforcement learning, but recent accounts also suggest a contribution to specific action selection mechanisms and the regulation of response vigour. Here, we examine dopaminergic mechanisms underlying human reinforcement learning and action selection via a combined pharmacological neuroimaging approach in male human volunteers (n = 31, within-subjects; Placebo, 150 mg of the dopamine precursor L-dopa, 2 mg of the D2 receptor antagonist Haloperidol). We found little credible evidence for previously reported beneficial effects of L-dopa vs.

PAC-Bayes Bounds for Bandit Problems: A Survey and Experimental Comparison.

PAC-Bayes has recently re-emerged as an effective theory with which one can derive principled learning algorithms with tight performance guarantees. However, applications of PAC-Bayes to bandit problems are relatively rare, which is a great misfortune. Many decision-making problems in healthcare, finance and natural sciences can be modelled as bandit problems.

Die Neustrukturierung der Notaufnahme gemäß dem G-BA-Beschluss zu einem gestuften System von Notfallstrukturen.

Background: There is no assessment of the effects regarding the decision of the Federal Joint Committee from April 19th, 2018 which demands a central and interdisciplinary emergency room system under the control of a professionally and organizationally independent administration. The aim of this study was to solicit the current opinion of leading orthopedic surgeons regarding the above-mentioned decision.

Material And Methods: An online questionnaire was sent to all 731 members of the Verband Leitender Orthopäden und Unfallchirurgen (www.

Erotic cue exposure increases physiological arousal, biases choices toward immediate rewards, and attenuates model-based reinforcement learning.

Computational psychiatry focuses on identifying core cognitive processes that appear altered across distinct psychiatric disorders. Temporal discounting of future rewards and model-based control during reinforcement learning have proven as two promising candidates. Despite its trait-like stability, temporal discounting may be at least partly under contextual control.

SensEURCity: A multi-city air quality dataset collected for 2020/2021 using open low-cost sensor systems.

Low-cost air quality sensor systems can be deployed at high density, making them a significant candidate of complementary tools for improved air quality assessment. However, they still suffer from poor or unknown data quality. In this paper, we report on a unique dataset including the raw sensor data of quality-controlled sensor networks along with co-located reference data sets.

Whether cycling around the city is in fact healthy in the light of air quality - Results of black carbon.

Studying the air quality and exposure of the inhabitants of urban agglomerations to pollution is the basis for the creation and development of more sustainable cities. Although research on black carbon (BC) has not yet reached the official acceptable levels and guidelines, the World Health Organization clearly indicates the need to measure and control the level of this pollutant. In Poland, monitoring of the level of BC concentration is not included in the air quality monitoring network.

[Proximal femoral fracture with bony ankylosis of the hip joint : Case report of difficult surgical treatment].

A 78-year-old female patient sustained a left-sided proximal femoral fracture due to a fall. Since childhood the patient had suffered from ankylosis of unknown origin in the ipsilateral hip joint. The recommended intramedullary osteosynthesis could restore the original status quo before the fracture.

Large-Scale Web Scraping for Problem Gambling Research: A Case Study of COVID-19 Lockdown Effects in Germany.

The COVID-19 pandemic and the measures to prevent its spread have had a negative impact on substance use behaviour. It is likely that social distancing and lockdown measures have also altered gambling behaviour, for instance shifting from land-based to online gambling. We used large-scale web scraping to analyse posting behaviour on a major German online gambling forum, gathering a database of more than 200k posts.

Mobile measurements of black carbon: Comparison of normal traffic with reduced traffic conditions during COVID-19 lock-down.

A mobile monitoring campaign was conducted (by bicycle) to assess the black carbon (BC) concentrations in Cluj-Napoca city, Romania, in 2020, before, during and after COVID-19 lock-down. Over the entire study period, the BC concentrations ranged between 1.0 and 25.

The catecholamine precursor Tyrosine reduces autonomic arousal and decreases decision thresholds in reinforcement learning and temporal discounting.

Supplementation with the catecholamine precursor L-Tyrosine might enhance cognitive performance, but overall findings are mixed. Here, we investigate the effect of a single dose of tyrosine (2g) vs. placebo on two catecholamine-dependent trans-diagnostic traits: model-based control during reinforcement learning (2-step task) and temporal discounting, using a double-blind, placebo-controlled, within-subject design (n = 28 healthy male participants).