Miracle-dz/UniFAR-FTUs huggingface dataset:
The neurodevelopmental and mental health outcomes in children with single ventricle physiology and Fontan circulation: a state-ofthe-art review and future directions

The survival of pa5ents with single ventricle circula5on undergoing Fontan opera5on has signiﬁcantly improved in the last decades. However, the neurodevelopmental outcome of this pa5ents is s5ll not sa5sfying and far below the healthy controls. The ae5ology of neurodevelopment disability and mental health disorders is mul5factorial and has a cumula5ve and synergic trend over the years. Gene5c factors, abnormal fetal circula5on, peri and intra-opera5ve care, mul5ple hospitaliza5ons and socioeconomic status play a crucial role in this process. Due to the heterogeneity of anatomies and diﬀerent treatment possibili5es there is a need for a personalized, mul5disciplinary and transla5onal approach focused on the pa5ent. The introduc5on of new technologies driven by ar5ﬁcial intelligence and the con5nuous integra5on of in vivo data and biomedical simula5ons into medicine promises signiﬁcant improvements in pathologies diagnosis and treatment thus enhancing the quality of life of pa5ents and their families.
A Benchmark for Text Classification in News Recommendations

Text classification is an important task in natural language processing. In the current era, people mainly obtain information from online news resources. It is then important to have an automatic and accurate news classifier to categorize every day’s news stories such that readers can find articles of interested more easily. We use news story data from the McClatchy organization to establish benchmarks on how accurately stories can be classified by multiple existing deep learning classifiers. Among the models we evaluated, Bidirectional Encoder Representations from Transformers (BERT) provides the best accuracy, macro-averaging precision, micro-averaging precision, macro-averaging recall and micro-averaging recall. Different from many other benchmark news data set, McClatchy provides both headline and full-text for each news story. We compare the performance of every deep learning-based classifier using headlines versus full-texts—the top three predicted categories include the labeled value 95% of the time with full-texts training and 92% with headlines only. Furthermore, the defined topics in McClatchy are not mutually exclusive. Some predictions identified as inaccurate are in fact classified into reasonable topics. We further provide a visualization of stories from various defined topics. The predicted results and the visualization of news stories illustrate the untrustworthiness of labeled classes and the intrinsic difficulty of categorizing news stories.
The Effect of Relative Advantage, Top Management Support and IT Infrastructure on E-Filing Adoption

Electronic filing (e-filing) adoption for tax income purposes is limited in developing countries as the practices of financial accounting and reporting, as well as digitalization in accounting systems, are more prevalent in developed countries. This paper investigates the determinants of e-filing usage in the context of emerging economies such as Jordan. Building on the Technology–Organization–Environment framework (TOE), the study proposes that the effects of relative advantage, top management support, and IT infrastructure as new variables on e-filing adoption and trust in the e-filing systems are positive. The study also proposes that trust in the e-filing system affects e-filing adoption and mediates the influence of relative advantage, top management support, and IT infrastructure on e-filing adoption. Data were collected from 315 respondents and analyzed via Smart PLS. Relative advantage and top management were found to affect the adoption of and trust in e-filing. In addition, trust in the e-filing system affects e-filing adoption and mediates the impact of relative advantage and top management support for e-filing. Therefore, decision-makers should develop a mechanism to increase trust and the benefits of using e-filing for income tax purposes.
An Evaluation of the Anti-Inflammatory Effects of a Thai Traditional Polyherbal Recipe TPDM6315 in LPS-Induced RAW264.7 Macrophages and TNF-α-Induced 3T3-L1 Adipocytes

TPDM6315 is an antipyretic Thai herbal recipe that contains several herbs with anti-inflammatory and anti-obesity activities. This study aimed to investigate the anti-inflammatory effects of TPDM6315 extracts in lipopolysaccharide (LPS)-induced RAW264.7 macrophages and TNF-α-induced 3T3-L1 adipocytes, and the effects of TPDM6315 extracts on lipid accumulation in 3T3-L1 adipocytes. The results showed that the TPDM6315 extracts reduced the nitric oxide production and downregulated the iNOS, IL-6, PGE2, and TNF-α genes regulating fever in LPS-stimulated RAW264.7 macrophages. The treatment of 3T3-L1 pre-adipocytes with TPDM6315 extracts during a differentiation to the adipocytes resulted in the decreasing of the cellular lipid accumulation in adipocytes. The ethanolic extract (10 µg/mL) increased the mRNA level of adiponectin (the anti-inflammatory adipokine) and upregulated the PPAR-γ in the TNF-α induced adipocytes. These findings provide evidence-based support for the traditional use of TPDM6315 as an anti-pyretic for fever originating from inflammation. The anti-obesity and anti-inflammatory actions of TPDM6315 in TNF-α induced adipocytes suggest that this herbal recipe could be useful for the treatment of metabolic syndrome disorders caused by obesity. Further investigations into the modes of action of TPDM6315 are needed for developing health products to prevent or regulate disorders resulting from inflammation.
A First Record of Lower Jurassic (Toarcian) Coleoid Jaws in Siberia

In the present paper, we describe several coleoid jaws discovered in the lower Toarcian black shales, cropping out along the Vilyui River (Yakutia, Russia). This is the first record of a Lower Jurassic coleoid jaw outside Europe and the first report of such a finding from the Mesozoic of Siberia. The described coleoid jaws demonstrate the same mode of preservation and morphology as the coeval jaws previously reported from Europe. Their preservation in Siberia became possible due to the widespread occurrence of black shale facies associated with the early Toarcian oceanic anoxic event (TOAE).
A Tighter Problem-Dependent Regret Bound for Risk-Sensitive Reinforcement Learning

We study the regret for risk-sensitive reinforcement learning (RL) with the exponential utility in the episodic MDP. Recent works establish both a lower bound Ω(( e | β | ( H − 1) / 2 − 1) √ SAT/ | β | ) and the best known (upper) bound ˜ O (( e | β | H − 1) √ H 2 SAT/ | β | ) , where H is the length of the episode, S the size of state space, A the size of action space, T the total number of timesteps, and β the risk parameter. The gap between the upper and the lower bound is exponential and hence is unsatisfactory. In this paper, we show that a variant of UCB-A DVANTAGE algorithm reduces a factor of √ H from the best previously known bound in any arbitrary MDP. To further sharpen the regret bound, we introduce a brand new mechanism of regret analysis and derive a problem-dependent regret bound without prior knowledge of the MDP from the algorithm. This bound is much tighter in MDPs with special structures. Particularly, we show that a regret that matches the information-theoretic lower bound up to logarithmic factors can be attained within a rich class of MDPs, which improves an exponential factor over the best previously known bound. Further, we derive a novel information-theoretic lower bound of Ω(max h ∈ [ H ] c ∗ v,h +1 √ SAT/ | β | ) , where max h ∈ [ H ] c ∗ v,h +1 is a problem-dependent statistic. This lower bound shows that the problem-dependent regret bound achieved by the algorithm is optimal in its dependence on max h ∈ [ H ] c ∗ v,h +1 .
Extracting Toponyms from OpenStreetMap: A Cross-linguistic Perspective

In this paper we discuss three studies in which we performed toponym extraction from OpenStreetMap. The studies operated at three different levels of geographical resolution: city level (Macao), national level (Italy and its regions), and province level (Geneva and its district). We present a single algorithm that we used in each study to extract toponyms from the text database associated to the corresponding OSM map. For each study, we provide a summary of the results, some observations on the language-specific methodological and theoretical aspects, and language-general/cross-linguistic considerations. We conclude by analyzing the reliability of OSM for toponym extraction and linguistic theory.
Learning a Sparse Representation Model for Neural CLIR

In monolingual retrieval, sparse representations learned atop BERT-style models offer a complementary approach to the unsupervised BM25 model. Inspired by this line of work, we explore adapting such models to the Cross-Language Information Retrieval (CLIR) setting, in which queries and documents are in different languages. The lack of lexical match between queries and documents inhibits a naive replication of these monolingual models for CLIR. We propose SPLADE-X, a cross-language expansion model for CLIR that performs complementary to a strong PSQ baseline. We further identify the challenges in developing such models, make connections to existing CLIR models and highlight future directions that pave the way for learning sparse representations feasible for CLIR.
Cutting Corners in Theory of Mind

Theory of Mind (ToM) research is concerned with the fundamental social ability of cognitively repre-senting other people’s mental states. In the context of designing intuitive, human-like, and collaborative artificial intelligence (AI), ToM is becoming increasingly relevant to AI researchers. However, there is a missing link between the theoretical and empirical approaches to ToM in Psychology and the applied but theory- and evidence-distant work in Computer Science. This work aims to connect the understandings and aims of both fields. A dual-process theory driven framework was adopted, distinguishing between higher-level and lower-level processes. Participants saw a virtual agent’s movement in a maze with either a full egocentric cue, a partial egocentric cue, or no egocentric cue. They were asked to predict the agent’s next actions and give verbal explanations for their predictions. Results show a strong sensitivity to egocentric information. Moreover, the qualitative responses show large individual differences not reflected in the recordings of participants’ decisions. The mechanisms contributing to efficient and flexible ToM and their implications for applied ToM in AI are considered and discussed. The value of qualitative research in this subject area is highlighted.
Influence of toroidal rotation on resistive tearing modes in tokamaks

Influence of toroidal equilibrium plasma rotation on m/n = 2/1 resistive tearing modes is studied numerically using a 3D toroidal MHD code (CLT). It is found that the toroidal rotation with or without shear can suppress the tearing instability and the Coriolis effect in the toroidal geometry plays a dominant role on the rotation induced stabilization. For a high viscosity plasma (τR/τV ≫ 1, where τR and τV represent resistive and viscous diffusion time, respectively), the effect of the rotation shear combined with the viscosity appears to be stabilizing. For a low viscosity plasmas (τR/τV ≪ 1), the rotation shear shows a destabilizing effect when the rotation is large.
Observer Effect in Social Media Use

Research has revealed the potential of social media as a source of large-scale, verbal, and naturalistic data for human behavior both in real-time and longitudinally. However, the in-practice utility of social media to assess and support wellbeing will only be realized when we account for extraneous factors. One such factor that might confound our ability to make inferences is the phenomenon of the “observer effect”—that individuals may deviate from their otherwise typical social media use because of the awareness of being monitored. This paper conducts a causal study to measure the observer effect in longitudinal social media use. We operationalized the observer effect in two dimensions of social media (Facebook) use—behavioral and linguistic changes. Participants consented to Facebook data collection over an average retrospective period of 82 months and an average prospective period of 5 months around the enrollment date to our study. We measured how they deviated from their expected social media use after enrollment. We obtained expected use by extrapolating from historical use using time-series (ARIMA) forecasting. We ﬁnd that the deviation in social media use varies across individuals based on their psychological traits. Individuals with high cognitive ability and low neuroticism immediately decreased posting after enrollment, and those with high openness signiﬁcantly increased posting. Linguistically, most individuals decreased the use of ﬁrst-person pronouns, reﬂecting lowered sharing of intimate and self-attentional content. While some increased posting about public-facing events, others increased posting about family and social gatherings. We validate the observed changes with respect to psychological traits drawing from psychology and behavioral science theories, such as self-monitoring, public self-consciousness, and self-presentation. The ﬁndings provide recommendations to correct observer effects in social media data-driven assessments of human behavior.
Developing Critical Thinking in Technical and Vocational Education and Training

Critical thinking has been difficult to develop in technical and vocational education and training, where acquiring practical skills is often the priority. This study looks at whether tried-and-tested methods for developing critical thinking in higher education are also effective in this educational context. To test this, an intervention was carried out as part of a compulsory, semester-long “Basic Communication Skills” class for 149 first year engineering students. This involved linking the expected learning outcomes for the course to a series of sub-skills comprising an updated definition of critical thinking. Furthermore, a set of strategies promoting active participation among students was also implemented. The proposed methodology led to improved levels of critical thinking when compared to traditional teaching methods. It was found that lessons characterized as interactive, dynamic, and encouraging active student participation facilitate the teacher’s job in the classroom and improve the development of critical thinking in a specific technical and vocational education context.
Open Research

α-Dystrobrevin (α-DB) is a major component of the dystrophin-associated protein complex (DAPC). Knockout (KO) of α-DB in the brain is associated with astrocytic abnormalities and loss of neuronal GABA receptor clustering. Mutations in DAPC proteins are associated with altered dopamine signaling and cognitive and psychiatric disorders, including schizophrenia. This study tested the hypothesis that motivation and associated underlying biological pathways are altered in the absence of α-DB expression. Male wildtype and α-DB KO mice were tested for measures of motivation, executive function and extinction in the rodent touchscreen apparatus. Subsequently, brain tissues were evaluated for mRNA and/or protein levels of dysbindin-1, dopamine transporter and receptor 1 and 2, mu opioid receptor 1 (mOR1) and cannabinoid receptor 1 (CB1). α-DB KO mice had significantly increased motivation for the appetitive reward, while measures of executive function and extinction were unaffected. No differences were observed between wildtype and KO animals on mRNA levels of dysbindin-1 or any of the dopamine markers. mRNA levels of mOR1were significantly decreased in the caudate-putamen and nucleus accumbens of α-DB KO compared to WT animals, but protein levels were unaltered. However, CB1 protein levels were significantly increased in the prefrontal cortex and decreased in the nucleus accumbens of α-DB KO mice. Triple-labelling immunohistochemistry confirmed that changes in CB1 were not specific to astrocytes. These results highlight a novel role for α-DB in the regulation of appetitive motivation that may have implications for other behaviours that involve the dopaminergic and endocannabinoid systems
A new concept of focusing antennas using plane-parallel Fabry-Perot cavities with nonuniform mirrors

An original configuration of low-profile directive antennas is presented in V-band. The focusing effect is performed by a plane-parallel Fabry-Perot (FP) resonator illuminated by a printed antenna. Both reflecting mirrors are made of metal strip gratings. The dimensions of the strips and slots of the nonperiodic output mirror are much smaller than the working wavelength; they are computed locally so that this mirror behaves as a spherical equiphase surface. Theoretical and experimental results show that the radiation patterns are symmetric and have low sidelobes. The antenna directivity is controlled by the value of the synthesized radius of curvature, that is to say by the nonperiodic distribution of the metal strips. It typically varies between 15 and 23.5 dB at 60 GHz. This new radiating structure is much more compact than substrate lenses and is compatible with low-cost multilayer technologies at millimeter wave frequencies. This is a possible candidate for user mobile-stations of indoor broadband communication systems.
Learning English vocabulary through playing games: the gamification design of vocabulary learning applications and learner evaluations

ABSTRACT Mobile-assisted language learning is a growing feature of contemporary language learning, and their distinct gamification design produces new and increasingly popular contexts for language learning. This paper explores the gamification features of the two most popular EFL vocabulary learning applications widely used by Asian learners – BaiCiZhan and Perfect Lingo. Their gamified designs are analysed based on the ‘mechanics, dynamics and aesthetics’ (MDA) model developed by Hunicke, LeBlanc, and Zubek [2004. MDA: A formal approach to game design and game research. Proceedings of the Game Developers Conference, San Jose, CA, USA, 23 November 2004. https://users.cs. northwestern.edu/∼hunicke/MDA.pdf] and Ruhi’s [2015. Level up your strategy: towards a descriptive framework for meaningful enterprise gamification. Technology Innovation Management Review 5, no. 8: 5–16. do:10.22215/timreview/918] descriptive framework for gamification applications. It further explores learners’ attitudes towards features of the gamified designs via observations and interviews. The research concludes that such mobile vocabulary learning applications are found more helpful when they present words in a multimodal way, contain more meaningful practice, adopt social interaction and reward learners with in-kind incentives. It is hoped that the study will contribute to the improvement of educational gamified applications for EFL vocabulary learning and language learning in general.
Effect of Acupoint Stimulation on Controlling Pain from Heel Lance in Neonates: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

To evaluate the effect of acupoint stimulation compared to other interventions on pain control in neonates who underwent heel lance, we searched for randomized controlled trials across six databases (CINAHL, Cochrane Library, EMBASE, Medline, PubMed, and Web of Science) published up to January 2023. Studies comparing acupoint stimulation and other interventions for controlling heel lance pain in neonates were included. These reports measured at least one of the following variables: pain score, crying time, oxygenation saturation, heart rate, respiration rate, and duration of the procedure. The data were independently extracted by two authors, and the PRISMA guidelines for study selection were followed. A total of 79 articles were screened, and 10 studies, with results on 813 neonates, were included in the final selection. The pain scores recorded during the heel lance procedure were not significantly different between the acupoint stimulation cohort and the control cohort (SMD of −0.26, 95% confidence interval (CI) from −0.52 to 0.01; p = 0.06; I2 = 68%). After processing the subgroup analyses, significant differences were found in the comparisons of acupuncture vs. usual care (SMD of −1.25, 95% CI from −2.23 to 0.27) and acupressure vs. usual care (SMD of −0.62, 95% CI from −0.96 to −0.28); nonsignificant differences were found in other comparisons. Our results demonstrate that acupoint stimulation may improve pain score during the heel lance procedure.
Significance of Type II Collagen Posttranslational Modifications: From Autoantigenesis to Improved Diagnosis and Treatment of Rheumatoid Arthritis

Collagen type II (COL2), the main structural protein of hyaline cartilage, is considerably affected by autoimmune responses associated with the pathogenesis of rheumatoid arthritis (RA). Posttranslational modifications (PTMs) play a significant role in the formation of the COL2 molecule and supramolecular fibril organization, and thus, support COL2 function, which is crucial for normal cartilage structure and physiology. Conversely, the specific PTMs of the protein (carbamylation, glycosylation, citrullination, oxidative modifications and others) have been implicated in RA autoimmunity. The discovery of the anti-citrullinated protein response in RA, which includes anti-citrullinated COL2 reactivity, has led to the development of improved diagnostic assays and classification criteria for the disease. The induction of immunological tolerance using modified COL2 peptides has been highlighted as a potentially effective strategy for RA therapy. Therefore, the aim of this review is to summarize the recent knowledge on COL2 posttranslational modifications with relevance to RA pathophysiology, diagnosis and treatment. The significance of COL2 PTMs as a source of neo-antigens that activate immunity leading to or sustaining RA autoimmunity is discussed.
On Divergent Barotropic and Inertial Instability in Zonal-Mean Flow Profiles

Abstract Impacts of atmospheric mean zonal flows on equatorial and subequatorial waves are examined using the generalized Laplace tidal equation, a horizontal structure equation that explicitly includes the effect of horizontal divergence on disturbances via the Lamb parameter e = (2Ωa)2/(ghe). Two important consequences of the mean zonal flow profile are the excitation of barotropically unstable waves associated with a reversed meridional gradient of potential vorticity and the excitation of inertially unstable waves related to anomalous potential vorticity values. Investigations show that both types of instabilities occur in realistic wind fields of the upper troposphere around 200 hPa. The barotropically unstable waves are divided into weakly divergent waves located in the middle latitudes and the more important class of strongly divergent waves located at the equatorward flank of the jet stream in the subtropics. The strongly divergent inertially unstable waves are identified by equatorially trapped w.