Relevant Information Research Articles

Balancing Innovation and Regulation: A Comprehensive Analysis and Neural Network Approach to AI Copyright Challenges

This article explores emerging issues surrounding artificial intelligence (AI) and copyright through a two-pronged approach. First, it provides an extensive literature review analyzing government and industry strategies for addressing AI copyright concerns and evaluates their rationality. Second, it details experiments conducted using neural networks to examine relevant information and investigate image copyright challenges, assessing mainstream large language models’ efficacy in handling copyright matters.
 The literature review explores AI copyright perspectives of the United Kingdom, China, the European Union, and the United States. It finds that countries emphasize balanced regulation and innovation (UK), ethical content creation (China), regulating high-risk applications (EU), or principles like non-discrimination and privacy (US). However, comprehensive governance frameworks are needed to navigate AI’s ethical, social, and legal intricacies.
 The experimental portion trains a convolutional neural network on a dataset of 41 infringing and non-infringing image sets to identify copyright infringement. While achieving over 80% accuracy, enhancements through expanded training data, segmentation, and multi-domain detection could improve generalization. The paper concludes with an analysis advocating copyright adaptation for AI creations, measured protections for standalone AI works, and constructive policies from interdisciplinary dialogue.

Clinical retrospective analysis of peri-implant oral malignancies

PurposeComplications of implant prostheses have direct correlation with the increased use of implants for dental rehabilitation. In this study, we present cases of peri-implant oral malignancies (PIOM) around dental implants and a retrospective analysis of patients treated for PIOM.MethodsThe retrospective analysis was performed with patients treated for PIOM at the Department of Oral and Maxillofacial Surgery of the Seoul National University Dental Hospital between 2006 and 2014. The patient records were thoroughly screened for previous medical issues, human papilloma virus infections, and other clinical data with a focus on relevant information such as localization, time from implant insertion to the development of the carcinoma, implant type and prosthetic rehabilitation.ResultsTwenty-one patients were diagnosed with PIOM. The male-to-female ratio was 1.625. The mean age of the patients was 60.42 ± 9.35 years old. Three patients reported ongoing alcohol/tobacco consumption. Five patients had a history of previous oral cancer surgery or exhibited mucosal lesions. The time from implant placement until carcinoma diagnosis was 49.13 ± 33.63 months on average. Most PIOM patients (95.2%) were diagnosed with SCC. All patients had previously been treated for peri-implantitis. In 85.7% of the patients, prostheses were observed on the opposing teeth where PIOM occurred.ConclusionBased on the review of these cases, it can be deduced that there is a possibility that implant treatment and galvanic currents between prosthesis may constitute an irritant and/or inflammatory cofactor which contributes to the formation and/or development of malignant tumors. Patients at potential risk may benefit from individualized recall intervals and careful evaluations.

The communication of artificial intelligence and deep learning in computer tomography image recognition of epidemic pulmonary infectious diseases.

The objectives are to improve the diagnostic efficiency and accuracy of epidemic pulmonary infectious diseases and to study the application of artificial intelligence (AI) in pulmonary infectious disease diagnosis and public health management. The computer tomography (CT) images of 200 patients with pulmonary infectious disease are collected and input into the AI-assisted diagnosis software based on the deep learning (DL) model, "UAI, pulmonary infectious disease intelligent auxiliary analysis system", for lesion detection. By analyzing the principles of convolutional neural networks (CNN) in deep learning (DL), the study selects the AlexNet model for the recognition and classification of pulmonary infection CT images. The software automatically detects the pneumonia lesions, marks them in batches, and calculates the lesion volume. The result shows that the CT manifestations of the patients are mainly involved in multiple lobes and density, the most common shadow is the ground-glass opacity. The detection rate of the manual method is 95.30%, the misdetection rate is 0.20% and missed diagnosis rate is 4.50%; the detection rate of the DL-based AI-assisted lesion method is 99.76%, the misdetection rate is 0.08%, and the missed diagnosis rate is 0.08%. Therefore, the proposed model can effectively identify pulmonary infectious disease lesions and provide relevant data information to objectively diagnose pulmonary infectious disease and manage public health.

Readability of postoperative discharge instructions is associated with complication rate in companion animals undergoing sterilisation.

Readability of client communications is a commonly overlooked topic in veterinary medical education. In human medicine, it has been advised that the readability of patient materials should be at USA schooling sixth-grade level or below. We hypothesised that student written discharge instructions would be of an inappropriate readability level, and discharges scored with higher reading grade levels would be associated with more complications. The cohort comprised 149 dogs and cats presenting for sterilisation. The readability of discharge instructions was assessed using the Flesch Reading Ease (FRE) and Flesch-Kincaid Grade Level (FKGL) formulas. Records were examined for evidence of postoperative complications. The mean FRE score of the discharge instructions was 61.97, with 30.87% being classified as 'difficult' or 'fairly difficult', 60.4% as 'standard' and 8.72% as 'fairly easy'. The mean FKGL was 8.64, with 98% being above reading level 6. Overall, there was an association between FKGL and complication occurrence (p = 0.005). Stratification by species demonstrated FRE and FKGL to be associated with complication occurrence in dogs (FRE score, p = 0.038; FKGL, p = 0.002), but not cats (FRE score, p = 0.964; FKGL, p = 0.679). Due to the retrospective nature of the study, there were difficulties associated with extracting relevant complication information from the medical records. Only 2% of owner-directed discharge instructions were written at readability levels aligning with the recommendations set forth in the human guidelines.

Novel Prognostic Model Construction of Tongue Squamous Cell Carcinoma Based on Apigenin-Associated Genes.

Clinical indexes are often selected as relevant factors for constructing prognostic models of tongue squamous cell carcinoma (TSCC) patients, while factors related to therapeutic targets are less frequently included. As Apigenin (API) shows anti-tumor properties in many tumors, in this study, we construct a novel prognostic model for TSCC patients based on Apigenin-associated genes through transcriptomic analysis. The effect of Apigenin (API) on the cell characteristics of TSCC cells was measured by several phenotype experiments. RNA-seq was executed to ensure differentially expressed genes (DEGs) in squamous cell carcinoma-9 (SCC-9) cells after API treatment. Furthermore, reverse transcription quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry were performed to verify the expression of API-related genes. Then, combined with the gene expression data and relevant individual information of TSCC samples acquired from The Cancer Genome Atlas (TCGA), an API-related model was built through Lasso regression and multivariate Cox regression. A receiver operating characteristic (ROC) curve and a nomogram and calibration curve were created to forecast patient outcomes to improve the clinical suitability of the API-related signature. The relationships between the two risk groups and function enrichment, immune infiltration characteristics, and drug susceptibility were analyzed. We demonstrated that API could inhibit the malignant behavior of TSCC cells. Among API-related genes, TSCC cells treated with API, compared to the control group, have higher levels of transmembrane protein 213 (TMEM213) and G protein-coupled receptor 158 (GPR158), and lower levels of caspase 14 (CASP14) and integrin subunit alpha 5 (ITGA5). An 7 API-associated gene model was built through Lasso regression and multivariate Cox regression that could direct TSCC prognostic status and tumor immune cell infiltration. In addition, we acquired 6 potential therapeutic agents for TSCC based on the prognostic model. Our research suggested the inhibition effect of API on TSCC cells and provided a novel prognostic model combined with therapeutic factors that can guide the prognosis of TSCC and clinical decision-making in TSCC.

Biological treatment of pesticide-containing wastewater from coffee crops: selection and optimization of a biomixture and biobed design.

The biopurification systems (BPS) or biobeds are employed for the treatment of pesticide-containing wastewater of agricultural origin. The use of these devices for pesticide removal requires the proper optimization of the composition of biomixtures (BPS active matrix) according to the target pesticides applied on a specific crop and the available materials used in their elaboration. This work aims to design a biomixture for the simultaneous treatment of several pesticides applied in coffee crops, according to local practices in Costa Rica. Three biomixtures containing either coffee husk, coconut fiber or rice husk (as the lignocellulosic substrate) were applied for the removal of 12 pesticides. The profiles of pesticide elimination and the mineralization of radiolabeled chlorpyrifos (14C-chlorpyrifos) revealed that the best performance was achieved with the coconut fiber biomixture, even though similar detoxification patterns were determined in every biomixture (according to immobilization in Daphnia magna and germination tests in Lactuca sativa). The optimization of this biomixture's composition by means of a central composite design permitted the definition of two optimal compositions (compost:soil:coconut fiber, % v/v) that maximized pesticide removal: i. 29:7.3:63.7 and ii. 11:7.3:81.7. The validation of these optimized compositions also included the use of an alternative soil from another coffee farm and resulted in overall DT50 values of 7.8-9.0 d for the pesticide mixture. Considering the removal kinetics in the optimized biomixture, a 1 m3 BPS prototype was dimensioned to be eventually used in local coffee farms. This work provides relevant information for the design and implementation of BPS at on-farm conditions for the treatment of pesticide-containing wastewater of a major crop.

MANAGING THE SPREAD OF COVID-19 PANDEMIC IN INDONESIAN SEA TRANSPORTATION

COVID-19 has been pandemic since the early 2020 and many efforts have been carried out worldwide. Among others, managing the spread of pandemic has been focused on air transportation since the mobility of people has been more actively using aeroplane hence the possibility of infecting people is much higher. Despite less intense, efforts to minimise the blow-out of COVID-19 in sea transportation have also been conducted. The International Maritime Organization (IMO) released guidance such pretravel information to crews and customers The types of guidance include the following items, namely pre-departure, social distancing, the use of masks, personal hygiene, environmental hygiene, and training. In the case of Indonesia, similar direction is introduced and implemented to cargo and passenger vessels. The current paper discusses the Indonesian regulation of managing COVID-19, which is based on IMO/WHO guidance, together with its implementation in the daily activities of people in sea transportation. A survey questionnaire is made out to collect the relevant information. The discussion covers the implementation of such guidance to Indonesian cargo and passenger vessels difficulties in applying the regulation on those ships and the related solutions.

MSE FINDR: A Shiny R Application to Estimate Mean Square Error Using Treatment Means and Post-hoc Test Results.

Research synthesis methods such as meta-analysis rely primarily on appropriate summary statistics (i.e., means and variance) of a response of interest for implementation to draw general conclusions from a body of research. A commonly encountered problem arises when a measure of variability of a response across a study is not explicitly provided in the summary statistics of primary studies. Typically, these otherwise credible studies, are omitted in research synthesis leading to potential small-study effects and loss of statistical power. We present MSE FINDR, a user-friendly Shiny R application for estimating the mean square error (i.e., within-study residual variance, σ2) for continuous outcomes from ANOVA-type studies, with specific experimental designs and treatment structures (Latin square, completely randomized, randomized complete block, two-way factorial, and split-plot designs). MSE FINDR accomplishes this by using commonly reported information on treatment means, significance level (α), number of replicates and post-hoc mean separation tests (Fisher's LSD, Tukey's HSD, Bonferroni, Šidák and Scheffé). Users upload a CSV file containing the relevant information reported in the study, then specify the experimental design and post-hoc test that was applied in the analysis of the underlying data. MSE FINDR then proceeds to recover σ2, based on user-provided study information. The recovered within-study variance can be downloaded and exported as a CSV file. Simulations of trials with variable number of treatments and treatment effects showed that the MSE FINDR-recovered σ2 was an accurate predictor of the actual ANOVA σ2 for one-way experimental designs when summary statistics (i.e., means, variance and post-hoc results) were available for the single factor. Similarly, σ2 recovered by application accurately predicted the actual σ2 for two-way experimental designs when summary statistics were available for both factors and the sub-plot factor in split-plot designs, irrespective of the post-hoc mean separation test. The MSE FINDR Shiny application, documentation and an accompanying tutorial are hosted at https://garnica.shinyapps.io/MSE_FindR/ and https://github.com/vcgarnica/MSE_FindR/. With this tool, researchers can now easily estimate the within-study variance absent in published reports that nonetheless provide appropriate summary statistics, thus enabling the inclusion of such studies that would have otherwise been excluded in meta-analyses involving estimates of effect sizes based on a continuous response.

(324) History of Priapism Treatment in the 20th Century

Abstract Introduction Priapism, defined as a prolonged erection in the absence of sexual arousal, leads to decreased quality of life, physical health, and increased erectile dysfunction. The modern priapism treatments of vasoconstriction and cavernous aspiration stem from strides made throughout the last century. Objective As a result, we seek to chronicle the history of priapism treatment throughout the 20th century. Methods We reviewed over two dozen academic articles and medical textbooks from 1872 to 1990 with relevant information on priapism treatment. Results In the 19th century, treatment of priapism solely involved symptomatic management with morphine and medicinal leeches. In 1928, Dr. Robert McKay and Dr. John Colston discovered that a thrombotic condition is sufficient to sustain an erection and that removing clots from the penis is sufficient to alleviate the erection. They recommended the newly-discovered anticoagulant heparin as a potential remedy. Dr. Rita Franklin then established in 1940 a positive association between testosterone propionate levels and priapism in eunuchoid men. Priapism therapies improved exponentially beginning in the late 1950s. Dr. H. Stephen Brody conducted the first successful penile aspiration in 1957 by aspirating blood from the base of each corpus cavernosum in a hypotensive patient. This groundbreaking procedure is conducted to this day for patients who do not respond effectively to medication management. Nine years after Dr. Brody’s study in 1966, Dr. Robert Garrett and Dr. Donald Rhamy reported penile flaccidity and sexual satisfaction in five patients who underwent a corpus-saphenous shunt to improve venous drainage. In 1997, Dr. Pierre Bondil and colleagues conducted a novel experiment demonstrating the efficacy of vasoconstrictive alpha agonist agents in decreasing penile blood flow to decrease erections and preserve erectile function. Conclusions The last one hundred years has shown significant innovation in the treatment of priapism. Some of the major developments in the first half of the 20th century included the use of heparin and the establishment of a relationship between testosterone and priapism. The second half of the 20th included treatment still in use today, such as carvenoglandular shunts and vasoconstrictive agents. Therapies from the 20th century will continue to play a vital role in the treatment and research of priapism management. Disclosure No.

(372) Clinical Understanding Through Real-World Data to Validate Effectiveness of Treatments in Peyronie’s Disease (CURVE-PD): Registry Design

Abstract Introduction Limited information is available on the treatment modalities, treatment choices and outcomes of patients with Peyronie’s disease (PD). Clinical Understanding through Real-world data to Validate Effectiveness of treatments in Peyronie’s Disease (CURVE-PD) is a prospective longitudinal, multi-center, web-based PD registry, built on the healthie™ platform, that collects relevant real-world information from treating sites, and individuals with PD and their partners and clinicians. Objective The overarching primary objective is two-fold. First, the registry aims to collect real-world data on treatments used for PD (including injectables and any surgical techniques) to understand treatment choice and variability in treatment delivery, and to assess treatment effectiveness. Secondly, to understand the impact of treatments on patient-reported outcomes (PROs) and their partners’ satisfaction as well. Furthermore, the registry also recognizes the importance of evaluating the natural progression of Peyronie’s disease (PD) in men who choose not to pursue active treatment and instead opt for observational approaches. Methods Eligible adults (≥18 years of age) with a confirmed clinical diagnosis of PD who received PD treatment starting at or within 2 weeks before enrollment (“treated”) or have never received PD treatment (“untreated”) are invited to participate by registry site personnel or their treating physician. Untreated patients who initiate PD treatment after enrollment may crossover into the treated group. Using a web-based portal, which is part of the registry, participants complete surveys at enrollment, and, for those who are treated, longitudinally at treatment initiation and at 3- 6-, 9- and 12-months post treatment initiation. Participant surveys include validated PROs such as the Peyronie’s disease questionnaire (PDQ) scale, Peyronie’s disease questionnaire for female sexual partners (PDQ-FSP), international index of erectile function (IIEF) for participants and male sexual partners, patient health questionnaire-9 (PHQ-9), and the Beck anxiety index (BAI). Additionally, participants are asked to provide details on sexual function, and reasons for treatment start and satisfaction with treatment. Designated site staff use the clinician web-based portal to enter information on demographics, medical history, and treatment history for up to 12 months before enrollment. Prospective data collected include information on PD treatments and clinical assessments as performed in routine clinical care (e.g., pre-treatment and post-treatment penile characteristics and PD symptoms) at enrollment, baseline, and each clinical visit. Currently, 15 sites in the United States are planned, with a possible future expansion to additional sites. The target for enrollment in the treated group is a minimum of 1,000 patients with PD. Results CURVE-PD enrollment opened in June 2023, with an anticipated 15 U.S. sites being enrolled over the next few months. Initial data for analysis are anticipated to be available in 2024. Conclusions CURVE-PD is a novel registry where participants with PD and their partners can provide information on quality-of-life impacts in a secure and private evidence generation web-based environment, that links both patient and clinician-reported treatments and assessments. This registry will provide the means for investigating real-world data (RWD) to attain real-world evidence (RWE) for more comprehensive knowledge and evaluation of the natural history, treatment patterns and modalities, and the comparative effectiveness of treatments for PD. Disclosure Yes, this is sponsored by industry/sponsor: Endo Pharmaceuticals Inc. Clarification: Industry funding only - investigator initiated and executed study Any of the authors act as a consultant, employee or shareholder of an industry for: Endo Pharmaceuticals Inc.

Information extraction from automotive reports for ontology population

In this paper, we showcase our research on the use of ontologies and information extraction for the purpose of modeling damages incurred on car bodies. With the increasing use of technology in the automotive industry, it is important to have a standardized and efficient way of documenting and analyzing car damage reports. Most existing reports are unstructured, and there is a lack of standardization in describing the damage. To address this issue, we have developed a domain ontology for car damage modeling (OCD),11 industryportal.enit.fr/ontologies/OCD,22 github.com/OntologyCarDamage/OCD and proposed an end-to-end system to extract information from French automotive reports. The information extraction process involves using named entity recognition (NER) and relationship extraction (RE) techniques to identify and extract relevant information from the reports. Then, the extracted information is used to populate the OCD ontology, allowing a structured and standardized representation of the damage information. The proposed system was tested on a real dataset of automotive reports and showed promising results.

Pyelocaliceal diverticula in a ferret (Mustela furo)

AbstractThrough uro‐computed tomography in a female ferret sterilised with Deslorelin Acetate implant, it was possible to discriminate the presence of a pyelocaliceal diverticula, differentiating it from a simple cyst. This method made it possible to obtain relevant information that cannot be acquired with ultrasound. Clearly, in animals such as ferrets, in which the incidence of diagnosed renal cysts is conspicuous, lesions that currently appear to be less common should be excluded through advanced diagnostics to understand the real incidence.

The investigation related to the influence of dimension manipulation on regret performance based on the upper confidence bound algorithm

This paper aims to investigate the effects of dimension manipulation on the performance of a recommendation algorithm applied to a dataset of restaurant reviews. In this paper, the Zomato dataset which contains restaurant reviews and other relevant information in Bangalore City was used. This paper extracted ratings that each user gave for each restaurant from the list of user feedback for each restaurant. These different ratings were stored as a core feature that was used for the restaurant recommendation algorithm to estimate the true mean rating of each restaurant. Upper Confidence Bound bandit algorithm was used as the restaurant recommendation algorithm to find the restaurant with the highest average rating in the dataset. Dimension raising and dimension reduction were used as ways to manipulate dimension in this paper. Principal Component Analysis was used as the technique to reduce feature dimension in the dataset. It reduced features into two principal components and the first principal component was used in place of the original core feature. Dimension raising was implemented based on the original core feature and another feature that correlated with it the most. The product of these two features was used in place of the original core feature. The experimental results suggest that dimension manipulation leads to decreased regret performance when employing the Upper Confidence Bound algorithm for recommendation. Intriguingly, within the realm of dimension manipulation, dimension reduction exhibited a more adverse impact on regret performance compared to dimension raising.

An Interprofessional Approach to Aural Rehabilitation for Adults with Hearing Loss and Cognitive Concerns.

Individuals with hearing loss are at risk for cognitive decline. The traditional approach to audiological care does not typically involve a team approach that addresses cognitive concerns. While cognitive screening is within the scope of practice in audiology, audiologists are not typically trained in interpreting screening results or providing rehabilitation that supports cognitive health. However, as growing evidence shows that hearing loss is tied to cognitive decline, a team approach is required to support whole-person care. Speech-language pathologists, who specialize in optimizing communication, are best situated to collaborate with audiologists to provide holistic aural rehabilitation. Audiologists and speech-language pathologists who partner to support a client's communication skills and social relationships play an important role in the life of an individual with hearing loss. In this perspective, we describe relevant background information about hearing loss and cognition and present an interprofessional approach to aural rehabilitation for adults with hearing loss who have cognitive concerns. We also discuss implications for future research.

Lost life expectancy following a hypothetical urban radiological incident

The consequences of mass radiological events, particularly those involving the activation of a radiological dispersion device (RDD), have been extensively studied by scientific groups. However, the critical initial period of such an event, usually spanning the first 100 h, can be characterized by a scarcity of information, potentially leading to delays in mitigating strategies. In response, a research group utilized computer simulations to generate solid, conservative analytical details that can aid decision-making and guide the prioritization of initial care based on variables such as age, sex, location, and local atmospheric stability conditions. The study estimates the Lost Life Expectancy (LLE) and provides relevant information to increase support for decision-making and allow evaluation of data closer to the lay public. The research team behind the study has been granted funding by the Brazilian National Council for Scientific and Technological Development (CNPq), and further simulations will be conducted utilizing codes that implement numerical models, specifically in atmospheric data forecasting. The methodology used to evaluate the LLE can be applied to any location, provided that the relevant variables are updated accordingly. Overall, this study offers critical insights into the impact of mass radiological events and enhances simulations' predictive capacity and precision.

Implemented classification techniques for osteoporosis using deep learning from the perspective of healthcare analytics.

Osteoporosis is a medical disorder that causes bone tissue to deteriorate and lose density, increasing the risk of fractures. Applying Neural Networks (NN) to analyze medical imaging data and detect the presence or severity of osteoporosis in patients is known as osteoporosis classification using Deep Learning (DL) algorithms. DL algorithms can extract relevant information from bone images and discover intricate patterns that could indicate osteoporosis. DCNN biases must be initialized carefully, much like their weights. Biases that are initialized incorrectly might affect the network's learning dynamics and hinder the model's ability to converge to an ideal solution. In this research, Deep Convolutional Neural Networks (DCNNs) are used, which have several benefits over conventional ML techniques for image processing. One of the key benefits of DCNNs is the ability to automatically Feature Extraction (FE) from raw data. Feature learning is a time-consuming procedure in conventional ML algorithms. During the training phase of DCNNs, the network learns to recognize relevant characteristics straight from the data. The Squirrel Search Algorithm (SSA) makes use of a combination of Local Search (LS) and Random Search (RS) techniques that are inspired by the foraging habits of squirrels. The method made it possible to efficiently explore the search space to find prospective values while using promising areas to refine and improve the solutions. Effectively recognizing optimum or nearly optimal solutions depends on balancing exploration and exploitation. The weight in the DCNN is optimized with the help of SSA, which enhances the performance of the classification. The comparative analysis with state-of-the-art techniques shows that the proposed SSA-based DCNN is highly accurate, with 96.57% accuracy.

NeoTCR: an immunoinformatic database of experimentally-supported functional neoantigen-specific TCR sequences

Abstract Neoantigen-based immunotherapy has demonstrated long-lasting antitumor activity. The recognition of neoantigens by T cell receptors (TCRs) is considered a trigger for antitumor responses. Due to the overwhelming number of TCR repertoires in the human genome, pinpointing neoantigen-specific TCRs is a formidable challenge. Recent studies have identified a number of functional neoantigen-specific TCRs, but the corresponding information is scattered across published literature and is difficult to retrieve. To improve access to these data, we developed an immunoinformatic database (NeoTCR) containing a unified description of publicly available neoantigen-specific TCR sequences, as well as relevant information on targeted neoantigens, from experimentally supported studies across 18 cancer subtypes. A user-friendly web interface allows interactive browsing and running of complex database queries. To facilitate rapid identification of neoantigen-specific TCRs from raw sequencing data, NeoTCR offers a one-stop analysis for annotation and visualization of TCR clonotypes, discovery of existing neoantigen-specific TCRs, and exclusion of bystander viral-associated TCRs. NeoTCR represents a unique tool to expedite future studies of neoantigen-specific TCRs and the development of neoantigen-based immunotherapy. NeoTCR is available at http://neotcrdb.bioaimed.com/ and https://github.com/lyotvincent/NeoTCR.

Differential effects of prior outcomes and pauses on the speed and quality of risky choices

AbstractFailures to obtain rewards influence what people choose to do next and how quickly they execute a chosen action, which are two components of motivated behavior. For instance, in risky decisions, losses can induce faster responses and sometimes increase risk‐taking, which may lead to detrimental consequences in some situations (such as gambling). Pauses might reduce these motivational influences of prior outcomes. To examine this question, participants alternated between a guess game, in which they won or lost money, and a choice game, in which they chose between a high probability of winning a small amount of money and a low probability of winning a large amount of money. The pause between a guess and a choice game was made either short (0 or 300 ms) or long (3000 ms). In four experiments, prior outcomes consistently influenced decision speed, such that people chose faster after a loss than after a win. However, prior outcomes did not consistently influence people's choices. In contrast, pauses increased decision quality, such that participants chose the option with a higher expected value more often, without substantially reducing decision speed. Pauses may improve decision quality by influencing predecisional attention allocation to relevant information, as its effect was absent when the overall task attention was high (Experiment 3). These findings have implications for both safer gambling and risky decision research. Future work can examine the underlying computational and cognitive processes and the generalizability of these findings to other contexts and populations.

First national reference of microplastic contamination of French soils

The recent emergence of studies on plastic contamination of terrestrial environments has revealed the presence of microplastics (MP) in a variety of soil types, from the most densely populated areas to the most remote ones. However, the concentrations and chemical natures of MP in soils vary between studies, and only a few ones have focused on this issue in France.The MICROSOF project aimed to establish the first national references for French soil contamination by microplastics. 33 soil samples randomly chosen on the French soil quality-monitoring network were analyzed. The study collected data on the abundance of microplastics in the [315–5000] μm range, their chemical nature and size, as well as mass abundance estimates and other relevant information. Results demonstrated that 76 % of the soil samples contained microplastics, in concentrations ranging from <6.7 to 80 MP.kg−1 (dry soil). Most samples from croplands, grasslands and vineyards and orchards were contaminated, whereas only one sample from forest contained MP, suggesting an increased risk of microplastic contamination in soils exposed to agricultural practices. The MP abundances are not statistically different from similar studies, indicating an intermediate level of contamination in French soils. Despite intervention reports and surveys, the sources remain unclear at this stage. For the first time, an overview of the state of soil contamination in France, as well as the potential risks is provided.

Addressing the care and information needs of people living with advanced multiple sclerosis

It is estimated that around 40000 people in the UK live with advanced multiple sclerosis (MS). These individuals experience a range of symptoms, and can often have moderate to severe impairment, with extensive care needs. In this article, the MS Trust provides relevant information on how to care for people with advanced MS, provides advice on future planning, and signposts individuals with the advanced MS, as well as their family and carers, to accessible online resources.