Miracle-dz/UniFAR-FTUs huggingface dataset:
Neural mechanisms of intertemporal and risky decision-making in individuals with internet use disorder: A perspective from directed functional connectivity

Abstract Background and aims The intertemporal and risk decision-making impairments are vital cognitive mechanisms in internet use disorder (IUD). However, the underlying neural mechanisms for these two decision-making dysfunctions in individuals with IUD remain unclear. Methods This study employed Functional Near-Infrared Spectroscopy (fNIRS) to record changes in blood oxygen concentration in the prefrontal cortex of individuals with IUD during intertemporal and risk decision-making tasks. Results The findings revealed that the intertemporal decision-making deficits in IUD group were primarily associated with reduced activation in the left dorsolateral prefrontal cortex (dlPFC) and orbitofrontal cortex (OFC) and FC from the left dlPFC to the right dlPFC. On the other hand, risk decision-making impairments were linked to decreased OFC activation and weakened functional connectivity from the left dlPFC to the right dlPFC and OFC. Discussions and Conslusions These results suggested that while there were common neural mechanisms underlying intertemporal and risk decision-making impairments in individuals with IUD, specific neural foundations existed for each type of dysfunction.
AGREEMENT BETWEEN SINGLE RATERS AND TEAM RATING WHEN APPLYING THE INTERNATIONAL CLASSIFICATION OF FUNCTIONING, DISABILITY AND HEALTH’S REHABILITATION SET

Objective To quantify the agreement between functional assessments by a single rater and a team using the Chinese version of the International Classification of Functioning, Disability and Health Rehabilitation Set in a clinical situation. Design Inter-rater, multi-centre agreement study. Subjects A total of 193 adult inpatients admitted to 5 rehabilitation centres at 5 hospitals in China Methods The Chinese version of the International Classification of Functioning, Disability and Health Rehabilitation Set was used by either a single rater or a team to assess 193 patients at 5 Chinese hospitals. Percentage of agreement and quadratic-weighted kappa coefficients were computed. Evaluation times were compared with paired t-tests. Results The mean team and individual evaluation times were not significantly different. The percentage of agreement ranged from 46.1% to 94.2% depending on the item, and the quadratic-weighted kappas ranged from 0.43 to 0.92. Eight categories (26.6%) showed a weighted kappa exceeding 0.4, 11 others (36.7%) exceeded 0.6, and another 11 (36.7%) produced kappas of more than 0.8. Conclusion Either a single rater or a team of raters can produce valid and consistent ratings when using the Chinese version of the International Classification of Functioning, Disability and Health Rehabilitation Set to assess patients in a rehabilitation department. The team rating approach is suitable for clinical application. LAY ABSTRACT A new team evaluation approach to implementing the rehabilitation measures of the World Health Organization’s International Classification of Functioning, Disability and Health was tested by asking teams including a physician, a nurse, and a physiotherapist or an occupational therapist to evaluate 193 adult inpatients admitted to the rehabilitation departments of 5 hospitals in China. The teams’ ratings were compared with those of single physicians and therapists. The agreement of the assessment results and the time taken by a single rater and a team were compared. There was moderate to high consistency in the ratings, and the mean times taken by the teams and the individual raters were not significantly different. In conclusion, team and single rating can both produce consistent assessments.
Active Fault‐Related Folding beneath an Alluvial Terrace in the Southern Longmen Shan Range Front, Sichuan Basin, China: Implications for Seismic Hazard

Abstract The devastating 2008 M w 7.9 Wenchuan earthquake, China, demonstrates that the central and northern parts of the Longmen Shan are currently active. Evidence for active faulting and folding in the southern Longmen Shan, however, remains poorly documented. In this paper, we define the structural geometry, fault kinematics, and seismic hazard of the Qiongxi thrust fault system (QTF) along the southern Longmen Shan range front by integrating deep and shallow seismic‐reflection data and geomorphic observations. The QTF is a 50 km long, north–south‐trending set of faults and associated folds that exhibit geomorphic evidence of Quaternary surface deformation. Geomorphic observations and seismic‐reflection data reveal that these faults dip steeply to the east and merge at depth with a blind, west‐dipping thrust ramp. The trend and reverse sense of slip along the QTF indicates that the structure accommodates east–west crustal shortening. Based on uplift of stratigraphic horizons across the fault zone, we define a Late Pliocene–to–Early Pleistocene fault slip rate of 0.2–0.3 mm/yr and a Middle Pleistocene–to–present rate of 0.4–1.2 mm/yr on the west‐dipping thrust ramp. This ramp soles to a basal detachment in the Triassic section at a depth of 4.5–5.5 km. To the west, this detachment steps down onto a blind, northwest‐dipping thrust termed the Range Front thrust. A rupture of the QTF in combination with the Range Front thrust could generate an M w 7.8 earthquake with average displacement of 5.7 m. This type of earthquake source poses significant hazards to the adjacent, highly populated Sichuan basin. Online Material: Figures detailing cross sections and 3D surfaces, additional reflection profiles, and dating information.
Biofuel production by two green microalgae utilizing wastewater and recycled nutrients for growth

Microalgae have received considerable attention in recent years as a viable feedstock for biofuel production. In order for algal biofuel to displace a significant amount of traditional fossil-based fuel, non-potable water must be used to avoid additional stress on dwindling freshwater supplies. Additionally, adequate nutrient sources must be available, and productive, robust strains need to be utilized. The work performed towards this thesis aims to determine the ability of two green microalgae and one diatom to grow and produce biofuel and biofuel precursors in untreated wastewater. Scenedesmus sp. strain WC-1 (WC-1), Chlorella sp. strain SLA-04 (SLA-04) and Navicula sp. strain RGd-1 (RGd-1) were initially screened for growth in untreated primary clarifier effluent and diluted anaerobic digestate. WC-1 and SLA-04 were able to grow in each condition, but RGd-1 was unable to sustain growth. After WC-1 and SLA-04 displayed successful growth, experiments were performed attempting to increase the lipid content in WC-1 and SLA-04 by varying the form and concentration of dissolved inorganic carbon present in the cultures. The addition of supplementary inorganic carbon did not increase cellular triacylglyceride (TAG) content as expected, but WC-1 and SLA-04 were able to achieve considerable fatty acid methyl ester (FAME) content. The final experiments conducted toward this thesis involved the use of recycled harvest water amended with anaerobic digestate for nutrients. WC-1 grew without inhibition during the first two generations of growth in recycled harvest water, but high ammonium concentrations due to an error during the addition of anaerobic digestate in the third generation caused reduced growth rates. SLA-04 was able to grow without inhibition during each of the three generations of growth in recycled harvest water. The results of this work may strengthen the outlook of microalgae’s potential as a biofuel feedstock. Identifying robust algae that can utilize low-cost nutrients while requiring minimal supplies of freshwater is a large step towards the commercialization of algal biofuels.
Platelet-Derived Apoptotic Vesicles Promote Bone Regeneration via Golgi Phosphoprotein 2 (GOLPH2)-AKT Signaling Axis

Apoptotic vesicles (apoVs) are apoptotic-cell-derived nanosized vesicles that take on dominant roles in regulating bone homeostasis. We have demonstrated that mesenchymal stem cell (MSC)-derived apoVs are promising therapeutic agents for bone regeneration. However, clinical translation of MSC-derived apoVs has been hindered due to cell expansion and nuclear substance. As another appealing source for apoV therapy, blood cells could potentially eliminate these limitations. However, whether blood cells can release apoVs during apoptosis is uncertain, and the detailed characteristics and biological properties of respective apoVs are not elucidated. In this study, we showed that platelets (PLTs) could rapidly release abundant apoVs during apoptosis in a short time. To recognize the different protein expressions between PLT-derived apoVs and PLTs, we established their precise protein landscape. Furthermore, we identified six proteins specifically enriched in PLT-derived apoVs, which could be considered as specific biomarkers. More importantly, PLT-derived apoVs promoted osteogenesis of MSCs and rescued bone loss via Golgi phosphoprotein 2 (GOLPH2)-induced AKT phosphorylation, therefore, leading to the emergence of their potential in bone regeneration. In summary, we comprehensively determined characteristics of PLT-derived apoVs and confirmed their roles in bone metabolism through previously unrecognized GOPLH2-dependent AKT signaling, providing more understanding for exploring apoV-based therapy in bone tissue engineering.
SLC25A48 is a human mitochondrial choline transporter

Choline has important physiological functions as a precursor for essential cell components and signaling molecules including phospholipids and the neurotransmitter acetylcholine. Choline is a water-soluble charged molecule and therefore requires transport proteins to cross biological membranes. Membrane transport of choline is incompletely understood. Here we show that SLC25A48 is a human mitochondrial choline transporter. Loss-of-function mutations in SLC25A48 are associated with elevated urine and plasma choline levels resulting from impaired choline transport into mitochondria.
Male Hypogonadism After Recovery from Acute COVID-19 Infection: A Prospective Observational Study

Abstract Background The severe acute respiratory syndrome coronavirus 2 can affect the hypothalamic-pituitary-gonadal axis (HPG) due to the expression of the angiotensin-converting enzyme 2 receptor. Objectives To assess the prevalence of hypogonadism and Sertoli cell dysfunction in coronavirus disease 2019 (COVID-19) male survivors. Method Male subjects recovered from acute COVID-19 infection were prospectively observed. The primary outcomes included the proportion of hypogonadism, defined biochemically as serum testosterone<230 ng/dL or CFT of<6.4 ng/mL if the total testosterone is between 230–320 ng/m. Sertoli cell dysfunction was defined as inhibin-B level<54.5 pg/mL. Subjects with hypogonadism were followed up at 12 months to assess the recovery of the HPG axis. Results Eighty-three subjects aged≥18 years were evaluated at a median of 120 (±35) days post-recovery. Their mean age was 49.50±12.73 years, and the mean BMI was 26.84±5.62 kg/m 2 . Low testosterone was detected in 21 (24.71%) and low inhibin-B was detected in 14 (19.71%) out of 71 subjects at 3 months. Subjects with low testosterone were younger, with a mean age of 43.29±12.03 years (P-0.08) and higher BMI (P-0.012). The severity of COVID-19 infection, duration of hospitalization, and other factors were not significantly associated with low testosterone. At 12 months, 18 out of 21 subjects came for follow-up, of which 9 (50%) showed persistently low testosterone, suggestive of hypogonadism. Conclusion Following COVID-19 infection, testosterone levels recovered over time; however, a significant proportion of subjects had low levels at 12-month follow-up. These findings have long-term implications for the management of COVID-19 subjects.
Low Temperature Hot Press Forming of a Zinc Coated Third Generation Advanced High Strength Steel

A 7 wt. % Mn steel was designed and was cast and processed to 1.5 mm sheets. The sheets were continuous annealed and coated with a Zn alloy by hot dip galvanizing before subjecting them to hot press forming cycles. The final microstructure was characterized by ultrafine ferrite grains and a high fraction of retained austenite. Excellent combinations of in-service strength-ductility-bendability were achieved for hot forming in the temperature range of 530-675 °C. The use of the low temperature hot forming minimized the liquid metal embrittlement induced cracking with Zn coating during hot forming and spot welding. Various application properties such as oxidation resistance, corrosion resistance, and springback were found at optimum levels for hot forming at 675 °C.
Impact of Ultra-Flash Tempering Treatment on the Microstructure and Mechanical Properties of High-Strength Carbon Steel

A novel high-frequency induction technology was successfully developed to carry out ultra-flash tempering treatment (UFTT) of high-strength carbon steel (HS-CS) with a heating rate of 1000 °C/s. The as-received HS-CS is a fully martensitic structure with low toughness. UFTT strategy at various temperatures is proposed to produce a tempered martensitic lath structure with promoting carbide precipitates in this structure. Microstructure evolution during UFTT was characterized using secondary electron imaging and electron backscatter diffraction technique in a scanning electron microscope. Micro-indentation hardness tests were measured through the cross-section of the steel to analyze the impact extent of UFTT. The mechanical properties were measured by uniaxial tensile tests. The results revealed that UFTT at various temperatures (550-650 °C) significantly affected the microstructure and the mechanical strength of the steel. A fully tempered martensitic microstructure with various types of carbide precipitates was promoted. Although, the microhardness and tensile strength of flash-tempered steel decreased owing to the breakdown of lath and dislocation structure in the achieved microstructure by UFTT. Hence, it is expected that the promoted microstructure during UFTT in the tested steel will result in a superior strength-toughness synergy. Based on the achieved results, the UFTT technique provides an alternative route for the conventional processing to tailor the microstructure of microalloyed HS-CS, consequently, optimizing the mechanical performance. Meanwhile, Economically, it is a cost-effective route to manufacture advanced high-strength steel.
Alternative meat in the diets of young children

Alternative meat is designed to address concerns about the impact of traditional meat on the environment, animal welfare, foodborne illnesses and human health. The availability, market share and variety of substitute meat products have exploded in recent years. This review will discuss the different types of alternative meat available, the benefits and challenges associated with their production as well as the regulatory and consumer acceptance issues that must be addressed to ensure their success. Cultivated or lab-grown meat is discussed as a separate category from all plant-based meat products because its nutritional composition is much closer to traditional meat. There is limited information about specific alternative meat products in the diets of children under five and the possible role meat substitutes can play in vegetarian and omnivorous diets. When planning a diet for a young child, parents and nutritionists will need to consider the consumption of each alternative meat product in the context of the child’s age, nutritional requirements, health status and the composition of their overall diet.
Towards Mitigating Perceived Unfairness in Contracts from a Non-Legal Stakeholder’s Perspective

Commercial contracts are known to be a valuable source for deriving project-specific requirements. However, contract negotiations mainly occur among the legal counsel of the parties involved. The participation of non-legal stakeholders, including requirement analysts, engineers, and solution architects, whose primary responsibility lies in ensuring the seamless implementation of contractual terms, is often indirect and inadequate. Consequently, a significant number of sentences in contractual clauses, though legally accurate, can appear unfair from an implementation perspective to non-legal stakeholders. This perception poses a problem since requirements indicated in the clauses are obligatory and can involve punitive measures and penalties if not implemented as committed in the contract. Therefore, the identification of potentially unfair clauses in contracts becomes crucial. In this work, we conduct an empirical study to analyze the perspectives of different stakeholders regarding contractual fairness. We then investigate the ability of Pre-trained Language Models (PLMs) to identify unfairness in contractual sentences by comparing chain of thought prompting and semi-supervised fine-tuning approaches. Using BERT-based fine-tuning, we achieved an accuracy of 84% on a dataset consisting of proprietary contracts. It outperformed chain of thought prompting using Vicuna-13B by a margin of 9%.
Political dogwhistles and community divergence in semantic change

We test whether the development of political dogwhistles can be observed using language change measures; specifically, does the development of a “hidden” message in a dogwhistle show up as differences in semantic change between communities over time? We take Swedish-language dogwhistles related to the on-going immigration debate and measure differences over time in their rate of semantic change between two Swedish-language community forums, Flashback and Familjeliv, the former representing an in-group for understanding the “hidden” meaning of the dogwhistles. We find that multiple measures are sensitive enough to detect differences over time, in that the meaning changes in Flashback over the relevant time period but not in Familjeliv. We also examine the sensitivity of multiple modeling approaches to semantic change in the matter of community divergence.
KnowTellConvince at ArAIEval Shared Task: Disinformation and Persuasion Detection in Arabic using Similar and Contrastive Representation Alignment

In an era of widespread digital communication, the challenge of identifying and countering disinformation has become increasingly critical. However, compared to the solutions available in the English language, the resources and strategies for tackling this multifaceted problem in Arabic are relatively scarce. To address this issue, this paper presents our solutions to tasks in ArAIEval 2023. Task 1 focuses on detecting persuasion techniques, while Task 2 centers on disinformation detection within Arabic text. Leveraging a multi-head model architecture, fine-tuning techniques, sequential learning, and innovative activation functions, our contributions significantly enhance persuasion techniques and disinformation detection accuracy. Beyond improving performance, our work fills a critical research gap in content analysis for Arabic, empowering individuals, communities, and digital platforms to combat deceptive content effectively and preserve the credibility of information sources within the Arabic-speaking world.
Team_Syrax at BLP-2023 Task 1: Data Augmentation and Ensemble Based Approach for Violence Inciting Text Detection in Bangla

This paper describes our participation in Task1 (VITD) of BLP Workshop 1 at EMNLP 2023,focused on the detection and categorizationof threats linked to violence, which could po-tentially encourage more violent actions. Ourapproach involves fine-tuning of pre-trainedtransformer models and employing techniqueslike self-training with external data, data aug-mentation through back-translation, and en-semble learning (bagging and majority voting). Notably, self-training improves performancewhen applied to data from external source butnot when applied to the test-set. Our anal-ysis highlights the effectiveness of ensemblemethods and data augmentation techniques inBangla Text Classification. Our system ini-tially scored 0.70450 and ranked 19th amongthe participants but post-competition experi-ments boosted our score to 0.72740.
Results of WMT23 Metrics Shared Task: Metrics Might Be Guilty but References Are Not Innocent

This paper presents the results of the WMT23 Metrics Shared Task. Participants submitting automatic MT evaluation metrics were asked to score the outputs of the translation systems competing in the WMT23 News Translation Task. All metrics were evaluated on how well they correlate with human ratings at the system and segment level. Similar to last year, we acquired our own human ratings based on expert-based human evaluation via Multidimensional Quality Metrics (MQM). Following last year’s success, we also included a challenge set subtask, where participants had to create contrastive test suites for evaluating metrics’ ability to capture and penalise specific types of translation errors. Furthermore, we improved our meta-evaluation procedure by considering fewer tasks and calculating a global score by weighted averaging across the various tasks. We present an extensive analysis on how well metrics perform on three language pairs: Chinese-English, Hebrew-English on the sentence-level and English-German on the paragraph-level. The results strongly confirm the results reported last year, that neural-based metrics are significantly better than non-neural metrics in their levels of correlation with human judgments. Further, we investigate the impact of bad reference translations on the correlations of metrics with human judgment. We present a novel approach for generating synthetic reference translations based on the collection of MT system outputs and their corresponding MQM ratings, which has the potential to mitigate bad reference issues we observed this year for some language pairs. Finally, we also study the connections between the magnitude of metric differences and their expected significance in human evaluation, which should help the community to better understand and adopt new metrics.
Pretrained Language Models v. Court Ruling Predictions: A Case Study on a Small Dataset of French Court of Appeal Rulings

NLP systems are increasingly used in the law domain, either by legal institutions or by the industry. As a result there is a pressing need to characterize their strengths and weaknesses and understand their inner workings. This article presents a case study on the task of judicial decision prediction, on a small dataset from French Courts of Appeal. Specifically, our dataset of around 1000 decisions is about the habitual place of residency of children from divorced parents. The task consists in predicting, from the facts and reasons of the documents, whether the court rules that children should live with their mother or their father. Instead of feeding the whole document to a classifier, we carefully construct the dataset to make sure that the input to the classifier does not contain any ‘spoilers’ (it is often the case in court rulings that information all along the document mentions the final decision). Our results are mostly negative: even classifiers based on French pretrained language models (Flaubert, JuriBERT) do not classify the decisions with a reasonable accuracy. However, they can extract the decision when it is part of the input. With regards to these results, we argue that there is a strong caveat when constructing legal NLP datasets automatically.