Relevant Tasks Research Articles

أهمية التأثير البشري في تقييم الحالة البيئية للمدن في أوزبكستان (منطقة نافوي كحالة للدراسة)

يعتبر إنشاء سلسلة من الخرائط ، وتجميع المؤشرات البيئية ، وتقييم الحالة البيئية للمدن من المهام البحثية وثيقة الصلة بالموضوع. إن تزايد عدد السكان في المدن ، وإنشاء العديد من المؤسسات الصناعية والإنتاجية ، واستخدام المركبات ، كلها عوامل تساهم في تدهور البيئة. منطقة نافوي هي وحدة إدارية شابة تقع في وسط أوزبكستان. أما فيما يتعلق بالتنمية الصناعية فمنطقة نافوي هي الأولى بين الوحدات الإدارية في الجمهورية. يشكل الإنتاج في مدنها ، وخاصة الإنتاجية العالية للمؤسسات الصناعية الثقيلة ، والمشاكل البيئية بأشكال مختلفة بسبب الضغط البشري على البيئة الطبيعية ، وصحة السكان - الأمهات والأطفال وكبار السن - تهديدًا خطيرًا. نتيجة للضغط البشري المرتفع ، تتناقص المساحات الخضراء النظيفة بيئيًا. تحتل حصة صغيرة جدًا مقارنة بالمساحة الإجمالية. وهذا بدوره يمكن أن يسبب ضغوطًا بيئية في المدن الإقليمية الواقعة في المناطق القاحلة ، ويسبب فقدان المساحات الخضراء. إن توقع مثل هذه العواقب ومكافحتها أمر مهم بشكل خاص اليوم. تحلل هذه المقالة الظروف البيئية في منطقة نافوي ومدنها ، بالإضافة إلى العامل الأكثر أهمية الذي يؤثر عليها ، التأثيرات البشرية. تم تصنيف الأراضي لمنطقة المدينة بالإضافة إلى الاقتراحات والتوصيات. لهذا ، قمنا بتحليل وتجميع التصنيف الهيكلي لمنطقة المدن الإقليمية. نتيجة لأبحاثنا ، يمكننا أن نرى أن المخاطر البيئية عالية. في هذه المقالة ، تتم تغطية المعلمات الرئيسية للدراسة بحسابات دقيقة.

Improving Students’ Creative Thinking Skills Assisted by GeoGebra Software

This study aims to improve students’ creative thinking skills in problem-based, ill-structured, open-ended learning through stimulus. This study used learning strategies that simultaneously develop problem-solving strategies and knowledge discipline. This learning can be achieved if educational activities are focused on authentic, contextual, and relevant tasks or problems so that students can gather the necessary information, evaluate alternative solutions, and present solutions they believe in. Moreover, the ability to generate uncommon or extraordinary ideas must be raised from the problems that exist in learning. The ability to think creatively in mathematics in education using the Problem-Based Learning (PBL) approach assisted by GeoGebra is expected to be a practical approach to educating students in increasing their intellectual potential and familiarizing them to deal with non-routine problems and applying it in their daily life to become a student who can think creatively. This study used a quasi-experimental research method with a quantitative approach conducted at SMA Negeri 2 Cimalaka. The instruments used in this study were questionnaires and tests. This study's approach, which was integrated with GeoGebra, can be used as an alternative to learning mathematics in schools. It can be developed with other approaches according to problems in mathematics.

Re-evaluating GPT-4’s bar exam performance

AbstractPerhaps the most widely touted of GPT-4’s at-launch, zero-shot capabilities has been its reported 90th-percentile performance on the Uniform Bar Exam. This paper begins by investigating the methodological challenges in documenting and verifying the 90th-percentile claim, presenting four sets of findings that indicate that OpenAI’s estimates of GPT-4’s UBE percentile are overinflated. First, although GPT-4’s UBE score nears the 90th percentile when examining approximate conversions from February administrations of the Illinois Bar Exam, these estimates are heavily skewed towards repeat test-takers who failed the July administration and score significantly lower than the general test-taking population. Second, data from a recent July administration of the same exam suggests GPT-4’s overall UBE percentile was below the 69th percentile, and $$\sim$$ ∼ 48th percentile on essays. Third, examining official NCBE data and using several conservative statistical assumptions, GPT-4’s performance against first-time test takers is estimated to be $$\sim$$ ∼ 62nd percentile, including $$\sim$$ ∼ 42nd percentile on essays. Fourth, when examining only those who passed the exam (i.e. licensed or license-pending attorneys), GPT-4’s performance is estimated to drop to $$\sim$$ ∼ 48th percentile overall, and $$\sim$$ ∼ 15th percentile on essays. In addition to investigating the validity of the percentile claim, the paper also investigates the validity of GPT-4’s reported scaled UBE score of 298. The paper successfully replicates the MBE score, but highlights several methodological issues in the grading of the MPT + MEE components of the exam, which call into question the validity of the reported essay score. Finally, the paper investigates the effect of different hyperparameter combinations on GPT-4’s MBE performance, finding no significant effect of adjusting temperature settings, and a significant effect of few-shot chain-of-thought prompting over basic zero-shot prompting. Taken together, these findings carry timely insights for the desirability and feasibility of outsourcing legally relevant tasks to AI models, as well as for the importance for AI developers to implement rigorous and transparent capabilities evaluations to help secure safe and trustworthy AI.

Анализ доказательной базы эффективности моделей ранней помощи DIRFloortime и ESDM. Часть 2. Модель ESDM

<p style="text-align: justify;"><strong>Objectives</strong>. Describing empirically proven algorithms of the Early Start Denver Model (ESDM) is a relevant task to compare variants of the model practically presented in the correctional space and the empirically proven variant. The basic empirical studies of the effectiveness of the ESDM model are analyzed.</p> <p style="text-align: justify;"><strong>Methods</strong>. The review considers 9 English-language sources, 5 articles in Russian, and a textbook on the Denver Early Intervention Model, which describe evaluations mainly in the format of randomized and controlled trials of the effectiveness of the ESDM model.</p> <p style="text-align: justify;"><strong>Results. </strong>The results of the analysis of the cited studies indicate a significantly greater effectiveness of the ESDM approach for children with autism spectrum disorders (ASD) compared to standard available care options on such parameters as: receptive and expressive speech, socialization, daily living skills, communication, motor skills, reduction of the main symptoms of autism, and reduction of parental stress.</p> <p style="text-align: justify;"><strong>Conclusions</strong>. The basic evidence-based applications of the ESDM model are described, which include: writing an individualized care plan, intensive sessions with the child for approximately 15 hours per week, regular parent training, independent interaction with children for approximately 2—3 hours per day, and age of onset of care between 18 and 30 months. The conclusion has been made that the Early Start Denver Model (EDSM) is appropriate for working with early age children showing signs of ASD.</p>

КЛИНИЧЕСКИЕ ПОКАЗАТЕЛИ КРОВИ КРЫС С ХРОНИЧЕСКИМ ВОСПАЛЕНИЕМ МЯГКИХ ТКАНЕЙ СПИНЫ ПРИ КУРСОВОМ ВНУТРИМЫШЕЧНОМ ВВЕДЕНИИ РАСТВОРОВ ЯДА ГЮРЗЫ ЗАКАВКАЗСКОЙ (MACROVIPERA LEBETINA OBTUSA)

An relevant task of modern pharmacology is the search for drugs for the treatment of chronic inflammatory processes. The use of nonsteroidal anti-inflammatory drugs and drugs of the glucocorticoid group has a number of limitations due to pronounced negative effects. The use of herbal anti-inflammatory drugs often has a delayed effect. In this case, the anti-inflammatory effect is manifested in the later stages of the pathological process. For this reason, it seems interesting to us to use a solution of poison obtained from gyurza (Macrovipera lebetina obtusa) as an alternative therapy for chronic inflammatory processes. Earlier in our work, the ability of solutions of these poisons to reduce inflammation was shown. This effect was found both in native venom solutions and in those heated to 55оС. In this work, the effect of venom solutions was studied after a course of intramuscular administration. The criteria for anti-inflammatory action were blood counts in experimental chronic inflammation caused by acetic acid. Inflammation was modeled by injecting 0.5 ml of 9% acetic acid solution under the skin of the back and intraperitoneal administration of 1 ml of 10% Rheopolyglukin solution to white outbred male rats. Diclofenac in injections was chosen as a comparison drug. The assessment of clinical blood parameters was carried out on an automatic hematology analyzer BC 2800vet (Mindray). The positive dynamics of the course of the chronic aseptic inflammatory process has been revealed. A more positive dynamics of the course of the chronic aseptic inflammatory process was revealed in groups of animals receiving solutions of native venom.

Accurate and interpretable drug-drug interaction prediction enabled by knowledge subgraph learning

BackgroundDiscovering potential drug-drug interactions (DDIs) is a long-standing challenge in clinical treatments and drug developments. Recently, deep learning techniques have been developed for DDI prediction. However, they generally require a huge number of samples, while known DDIs are rare.MethodsIn this work, we present KnowDDI, a graph neural network-based method that addresses the above challenge. KnowDDI enhances drug representations by adaptively leveraging rich neighborhood information from large biomedical knowledge graphs. Then, it learns a knowledge subgraph for each drug-pair to interpret the predicted DDI, where each of the edges is associated with a connection strength indicating the importance of a known DDI or resembling strength between a drug-pair whose connection is unknown. Thus, the lack of DDIs is implicitly compensated by the enriched drug representations and propagated drug similarities.ResultsHere we show the evaluation results of KnowDDI on two benchmark DDI datasets. Results show that KnowDDI obtains the state-of-the-art prediction performance with better interpretability. We also find that KnowDDI suffers less than existing works given a sparser knowledge graph. This indicates that the propagated drug similarities play a more important role in compensating for the lack of DDIs when the drug representations are less enriched.ConclusionsKnowDDI nicely combines the efficiency of deep learning techniques and the rich prior knowledge in biomedical knowledge graphs. As an original open-source tool, KnowDDI can help detect possible interactions in a broad range of relevant interaction prediction tasks, such as protein-protein interactions, drug-target interactions and disease-gene interactions, eventually promoting the development of biomedicine and healthcare.

A model-based framework for controlling activated sludge plants

This work presents a general framework for the advanced control of a common class of activated sludge plants (ASPs). Based on a dynamic model of the process and plant sensors and actuators, we design and configure a highly customisable Output Model-Predictive Controller (Output MPC) for the flexible operation of ASPs as water resource recovery facilities. The controller consists of a i) Moving-Horizon Estimator for determining the state of the process, from plant measurements, and ii) a Model-Predictive Controller for determining the optimal actions to attain high-level operational goals. The Output MPC can be configured to satisfy the technological limits of the plant equipment, as well as operational desiderata defined by plant personnel. We consider exemplary problems and show that the framework is able to control ASPs for tasks of practical relevance, ranging from wastewater treatment subject to normative limits, to the production of an effluent with varying nitrogen content, and energy recovery.

THE IMPACT OF THE KOSHTEPA CANAL IN AFGHANISTAN ON THE HYDROPOLITICS OF CENTRAL ASIA

ABSTRACT
 This article discusses the formation and construction of the Qosh Tepa Canal in Afghanistan, its hydro-political influence on Central Asian countries, its problems, risks, consequences, and solutions. The majority of available freshwater is used for agricultural purposes. This continues to be the main source of income for almost all Central Asian countries. However, there are cases of wasteful water usage, with old methods still being employed instead of modern technologies. To prevent this situation, the direct application of the experience of developed countries and the implementation of new innovative irrigation methods are among the relevant tasks for each country in the region. In general, everyone should preserve nature, treat it carefully, and use water resources efficiently. States should also pursue policies of mutual agreement, taking into account the interests of other countries.

Your Prompt Is My Command: On Assessing the Human-Centred Generality of Multimodal Models (Abstract Reprint)

Even with obvious deficiencies, large prompt-commanded multimodal models are proving to be flexible cognitive tools representing an unprecedented generality. But the directness, diversity, and degree of user interaction create a distinctive “human-centred generality” (HCG), rather than a fully autonomous one. HCG implies that —for a specific user— a system is only as general as it is effective for the user’s relevant tasks and their prevalent ways of prompting. A human-centred evaluation of general-purpose AI systems therefore needs to reflect the personal nature of interaction, tasks and cognition. We argue that the best way to understand these systems is as highly-coupled cognitive extenders, and to analyse the bidirectional cognitive adaptations between them and humans. In this paper, we give a formulation of HCG, as well as a high-level overview of the elements and trade-offs involved in the prompting process. We end the paper by outlining some essential research questions and suggestions for improving evaluation practices, which we envision as characteristic for the evaluation of general artificial intelligence in the future.

Prediction uncertainty estimates elucidate the limitation of current NSCLC subtype classification in representing mutational heterogeneity

The heterogeneous pathogenesis and treatment response of non-small cell lung cancer (NSCLC) has led clinical treatment decisions to be guided by NSCLC subtypes, with lung adenocarcinoma and lung squamous cell carcinoma being the most common subtypes. While histology-based subtyping remains challenging, NSCLC subtypes were found to be distinct at the transcriptomic level. However, unlike genomic alterations, gene expression is generally not assessed in clinical routine. Since subtyping of NSCLC has remained elusive using mutational data, we aimed at developing a neural network model that simultaneously learns from adenocarcinoma and squamous cell carcinoma samples of other tissue types and is regularized using a neural network model trained from gene expression data. While substructures of the expression-based manifold were captured in the mutation-based manifold, NSCLC classification accuracy did not significantly improve. However, performance was increased when rejecting inconclusive samples using an ensemble-based approach capturing prediction uncertainty. Importantly, SHAP analysis of misclassified samples identified co-occurring mutations indicative of both NSCLC subtypes, questioning the current NSCLC subtype classification to adequately represent inherent mutational heterogeneity. Since our model captures mutational patterns linked to clinical heterogeneity, we anticipate it to be suited as foundational model of genomic data for clinically relevant prognostic or predictive downstream tasks.

The effect of inherent and incidental constraints on bimanual force control in simulated Martian gravity

The ability to coordinate actions between the limbs is important for many operationally relevant tasks associated with space exploration. A future milestone in space exploration is sending humans to Mars. Therefore, an experiment was designed to examine the influence of inherent and incidental constraints on the stability characteristics associated with the bimanual control of force in simulated Martian gravity. A head-up tilt (HUT)/head-down tilt (HDT) paradigm was used to simulate gravity on Mars (22.3° HUT). Right limb dominant participants (N = 11) were required to rhythmically coordinate patterns of isometric forces in 1:1 in-phase and 1:2 multifrequency patterns by exerting force with their right and left limbs. Lissajous displays were provided to guide task performance. Participants performed 14 twenty-second practice trials at 90° HUT (Earth). Following a 30-min rest period, participants performed 2 test trials for each coordination pattern in both Earth and Mars conditions. Performance during the test trials were compared. Results indicated very effective temporal performance of the goal coordination tasks in both gravity conditions. However, results indicated differences associated with the production of force between Earth and Mars. In general, participants produced less force in simulated Martian gravity than in the Earth condition. In addition, force production was more harmonic in Martian gravity than Earth gravity for both limbs, indicating that less force distortions (adjustments, hesitations, and/or perturbations) occurred in the Mars condition than in the Earth condition. The force coherence analysis indicated significantly higher coherence in the 1:1 task than in the 1:2 task for all force frequency bands, with the highest level of coherence in the 1–4 Hz frequency band for both gravity conditions. High coherence in the 1–4 Hz frequency band is associated with a common neural drive that activates the two arms simultaneously and is consistent with the requirements of the two tasks. The results also support the notion that neural crosstalk stabilizes the performance of the 1:1 in-phase task. In addition, significantly higher coherence in the 8–12 Hz frequency bands were observed for the Earth condition than the Mars condition. Force coherence in the 8–12 Hz bands is associated with the processing of sensorimotor information, suggesting that participants were better at integrating visual, proprioceptive, and/or tactile feedback in Earth than for the Mars condition. Overall, the results indicate less neural interference in Martian gravity; however, participants appear to be more effective at using the Lissajous displays to guide performance under Earth's gravity.

TacticAI: an AI assistant for football tactics

Identifying key patterns of tactics implemented by rival teams, and developing effective responses, lies at the heart of modern football. However, doing so algorithmically remains an open research challenge. To address this unmet need, we propose TacticAI, an AI football tactics assistant developed and evaluated in close collaboration with domain experts from Liverpool FC. We focus on analysing corner kicks, as they offer coaches the most direct opportunities for interventions and improvements. TacticAI incorporates both a predictive and a generative component, allowing the coaches to effectively sample and explore alternative player setups for each corner kick routine and to select those with the highest predicted likelihood of success. We validate TacticAI on a number of relevant benchmark tasks: predicting receivers and shot attempts and recommending player position adjustments. The utility of TacticAI is validated by a qualitative study conducted with football domain experts at Liverpool FC. We show that TacticAI’s model suggestions are not only indistinguishable from real tactics, but also favoured over existing tactics 90% of the time, and that TacticAI offers an effective corner kick retrieval system. TacticAI achieves these results despite the limited availability of gold-standard data, achieving data efficiency through geometric deep learning.

Regulatory and legal regulation of the healtcare sector in Ukraine and Hungary: general and special

This article conducts a comparative analysis of the current state of legal regulation in the healthcare sector in Ukraine and Hungary. The significance of healthcare issues has elevated them to the level of one of the most important state tasks and an internal function of the modern state. This necessitates not only the execution of effective state governance but also the formation and implementation of state policy in this sphere. The article is dedicated to the formation and implementation of state policy concerning the legal regulation of the healthcare sector in Ukraine and Hungary, which underscores its relevance.
 During the writing process, the author researched the system of legal relations and state bodies responsible for performing relevant functions and tasks in the formation and implementation of healthcare policy. It analyzes the legislative system regulating these areas and the practice of its application in both countries. The article identifies the roles and places of the Verkhovna Rada (Supreme Council) of Ukraine and the Hungarian National Assembly, as well as the Cabinets of Ministers and the executive branch systems in both countries in the realization of healthcare policy.
 Like most contemporary scientific developments in this field, the article covers problems of three scientific disciplines – medicine, management, and law. In preparing this article, the author reviewed a considerable amount of medical literature, particularly in social medicine and healthcare organization, thoroughly exploring their scientific issues in both Ukraine and Hungary. However, it aims to illuminate the issues and problems arising in this context, specifically from the legal standpoint, particularly administrative law. Therefore, the focus of this work is primarily on legal categories and concepts – the legal mechanisms for implementing state medical and health improvement programs, ensuring the constitutionally guaranteed right of individuals in Ukraine and the Fundamental Law of Hungary to medical care, healthcare, and medical insurance, particularly the guaranteed level of free qualified medical aid.

Determining the Largest Overlap between Tables

Both on the Web and in data lakes, it is possible to detect much redundant data in the form of largely overlapping pairs of tables. In many cases, this overlap is not accidental and provides significant information about the relatedness of the tables. Unfortunately, efficiently quantifying the overlap between two tables is not trivial. In particular, detecting their largest overlap, i.e., their largest common subtable, is a computationally challenging problem. As the information overlap may not occur in contiguous portions of the tables, only the ability to permute columns and rows can reveal it. The detection of the largest overlap can help us in relevant tasks such as the discovery of multiple coexisting versions of the same table, which can present differences in the completeness and correctness of the conveyed information. Automatically detecting these highly similar, matching tables would allow us to guarantee their consistency through data cleaning or change propagation, but also to eliminate redundancy to free up storage space or to save additional work for the editors. We present the first formal definition of this problem, and with it Sloth, our solution to efficiently detect the largest overlap between two tables. We experimentally demonstrate on real-world datasets its efficacy in solving this task, analyzing its performance and showing its impact on multiple use cases.

Characterization and classification of oleogels and edible oil using vibrational spectroscopy in tandem with one-class and multiclass chemometric methods

Oleogel represents a promising healthier alternative to act as a substitute for conventional fat in various food products. Oil selection is a crucial factor in determining the technological properties and applications of oleogels due to their distinct fatty acid composition, molecular weight, and thermal properties, as well as the presence of antioxidants and oxidative stability. Hence, the relevance of monitoring oleogel properties by non-destructive, eco-friendly, portable, fast, and effective techniques is a relevant task and constitutes an advance in the evaluation of oleogels quality. Thus, the present study aims to classify oleogels rapidly and reliably, without the use of chemicals, comparing two handheld near infrared (NIR) spectrometers and one portable Raman device. Furthermore, two different multivariate methods are compared for oleogel classification according to oil type. Three types of oleogels were prepared, containing 95 % oil (sunflower, soy, olive) and 5 % beeswax as a structuring agent, melted at 90 °C. Polarized light microscopy (PLM) images were acquired, and fatty acid composition, peroxide index and free fatty acid content were determined using official methods. A total of 240 oleogel and 92 oil spectra were obtained for each instrument. After spectra pretreatment, Principal Component Analysis (PCA) was performed, and two classification methods were investigated. The Data Driven - Soft Independent Modelling of Class Analogy (DD-SIMCA) and Partial Least Squares Discriminant Analysis (PLS-DA) models demonstrated 95 % to 100 % of accuracy for the external test set. In conclusion, the use of vibrational spectroscopy using handheld and portable instruments in tandem with chemometrics showed to be an efficient alternative for classifying oils and oleogels and could be extended to other food samples. Although the classification of vegetable oils by NIR is widely used and known, this work proposes the classification of different types of oil in oleogel matrices, which has not yet been explored in the literature.

Ensuring metrological traceability of reference materials of gas mixtures composition

The modern concept of metrological assurance for gas analytical measuring instruments with the use of reference materials of gas mixtures composition in cylinders under pressure is presented. The reference materials of gas mixtures composition of approved type in cylinders under pressure, which are the most often means of mole fraction and mass concentration units transfer in gas analytical measurements, are considered. The certified value in these reference materials is the content of the target component (or components) in the gas medium (analytical matrix). All the produced reference materials of gas mixtures composition, which are used for ensuring the uniformity of measurements are traceable to the State primary standard of units of mole fraction, mass fraction and mass concentration of components in gas and gas condensate media GET 154-2019, which characteristics are confirmed on the international level by the results of about 90 international comparisons. The paper presents a methodology for ensuring metrological traceability of reference materials of gas mixtures composition using GET 154-2019, taking into account the constantly increasing park of gas analytical instruments and the emergence of new measuring tasks in various fields of industry and environmental control. Currently, a park of secondary and working standards has been created at enterprises producing reference materials of gas mixtures composition, and their traceability to GET 154-2019 has been implemented according to the state verification scheme. The paper presents the results of international comparisons with participation of GET 154-2019, confirming the comparability of the obtained and reference value of the target component content in reference gas mixtures at the international level. The variety and large number of relevant gas analytical measurement tasks in various industries and the social sphere determines the need to choose priority areas for improving the existing reference base, including the structure of the GET 154 Standard and the nomenclature of reference gas mixtures. The strategic program of the Gas Analysis working group of the Consultative Committee of the Amount of Substance of the International Bureau of Weights and Measures developed for the period up to 2030 has been analysed and a review of the long-term tasks of gas analytical measurements is given. The currently existing GET 154-2019 Standard of the latest generation provides reproduction, storage and transfer of the components’ mole fraction units in gas and gas condensate media in the range from 1.5·10 –8 to 99.99999 %, and mass concentration units in the range from 1.0·10–6 to 2.0·105 mg/m3, what is confirmed by the results of participation in international comparisons and published CMC positions in the International database of calibration and measurement capabilities (about 400 CMCs positions).

Praktisk yrkesopplæring på nett: En case-studie av yrkesfaglæreres undervisningspraksis under covid-19-pandemien

The purpose of this article is to develop knowledge about the experiences of technical vocational education and training teachers in Norway during the covid-19 school closures in the spring and autumn of 2020. Data has been obtained through an electronic questionnaire with open, text-based answers. 18 vocational teachers participated in the survey, which shows that the closure had major consequences for vocational students in the technological education programs. The home school’s narrow framework conditions made it difficult to replace the school’s practical workshop and hands-on training. The study shows that the closure has triggered major differences in how vocational training was carried out. While some students only participated in digital home school, other students were able to have more practice in firms and enterprises than in ordinary school life. Excluded from school, training firms, and leisure activities, many students felt lonely and passive and some were eventually in danger of dropping out of school. The study shows that the vocational teachers took extensive responsibility and worked hard to find relevant and practical tasks for their students in the crisis that arose. One-to-one conversations between teacher and student as well as a close school-home collaboration became decisive for the students' experience of social and professional belonging.

Neurocognitive Errors and Noncontact Anterior Cruciate Ligament Injuries in Professional Male Soccer Players.

Evidence is emerging that core neurocognitive functions such as working memory and inhibitory control (ie, motor-response and attentional inhibition) are linked to the anterior cruciate ligament (ACL) injury risk. Research has been conducted in laboratory settings, but the contribution of neurocognition to actual ACL injuries under real-world conditions is unknown. To describe the possible neurocognitive errors involved in noncontact ACL injury mechanisms. Case series. Soccer matches. A total of 47 professional male soccer players. Three independent reviewers evaluated 47 videos of players sustaining noncontact ACL injuries. Neurocognitive errors in inhibitory control were operationalized as follows: (1) motor-response inhibition was scored when a player demonstrated poor decision-making and approached the opponent with high speed that reduced the ability to stop or change the intended action and (2) an attentional error was scored when a player shifted his selective attention away from the relevant task to irrelevant stimuli. Of 47 noncontact ACL injuries, 26 (55%) were related to a pressing-type injury, 19 (73%) of which involved a deceiving action made by the opponent, suggesting poor inhibitory control of the defender. Of the remaining 21 noncontact ACL injuries (45%), 16 (76%) could be attributed to attentional errors. Agreement among the 3 raters was very good for all items except poor decision-making, which showed fair to good agreement (Fleiss κ = 0.71). Interrater reliability was excellent (intraclass correlation coefficient = 0.99-1.00). Errors in motor-response inhibitory control and attentional inhibition were common during noncontact ACL injury events in professional male soccer players. The interrater agreement in detecting neurocognitive errors in general was very good.

Transparency materialised: how registers can regulate access to documents?

AbstractProactive transparency in the form of electronic provision of documents is required by law in the EU. It has long been acknowledged in law and technology studies that digital technology can have legal consequences when implemented to perform a legal function. Consequently, the technological design of document registers has the ability to limit as well as enhance access to documents. When technology can have such regulatory powers, incorporating it into a legal function requires closer attention as to how or why it is so. This article will provide a close analysis of the European Commission’s main Register of Documents (RegDoc) to study the implications of technological design for access to documents. Transparency is approached through a procedural view, highlighting its mechanisms. The article uses a HCI based walkthrough method for the case-study artefact critique of the RegDoc. The main findings suggest that there are two specific affordances of the RegDoc that limit access, especially for users who do not have pre-existing knowledge of the documents they are searching for. These affordances are, first, the scope of the dataset and, second, searchability. Overall, designing technology for legally relevant functions should take into account the wider legal framework that the technology aims to cater for. Attention should be paid to the affordances that can make a legal difference in a technology created to perform a legally relevant task.

Distinct and common mechanisms of cross-model semantic conflict and response conflict in an auditory relevant task.

The mechanisms of semantic conflict and response conflict in the Stroop task have mainly been investigated in the visual modality. However, the understanding of these mechanisms in cross-modal modalities remains limited. In this electroencephalography (EEG) study, an audiovisual 2-1 mapping Stroop task was utilized to investigate whether distinct and/or common neural mechanisms underlie cross-modal semantic conflict and response conflict. The response time data showed significant effects on both cross-modal semantic and response conflicts. Interestingly, the magnitude of semantic conflict was found to be smaller in the fast response time bins than in the slow response time bins, whereas no such difference was observed for response conflict. The EEG data demonstrated that cross-modal semantic conflict specifically increased the N450 amplitude. However, cross-modal response conflict specifically enhanced theta band power and theta phase synchronization between the medial frontal cortex (MFC) and lateral prefrontal electrodes as well as between the MFC and motor electrodes. In addition, both cross-modal semantic conflict and response conflict led to a decrease in P3 amplitude. Taken together, these findings provide cross-modal evidence for domain-specific mechanism in conflict detection and suggest both domain-specific and domain-general mechanisms exist in conflict resolution.