Miracle-dz/UniFAR-FTUs huggingface dataset:
Network analysis of suicide ideation and depressive-anxiety symptoms among adolescents

Background: The co-occurrence of depression and anxiety in adolescents is common and associated with suicide ideation. This study aimed to investigate the symptom-level relationship between suicide ideation and comorbidity of depression and anxiety. Methods: R was used for network analysis of depressive and anxiety symptoms from 716 adolescents (PHQ-9 ≥ 5 and GAD-7 ≥ 5). Participants were grouped into the suicide ideation group and the non-suicide ideation group. Network differences were compared between these two groups. Results: “Restlessness”, “Sad mood”, and “Trouble relaxing” were the most prominent central symptoms in this depressive-anxiety symptom network. “Restlessness”, “Nervousness”, and “Motor” were the bridge symptoms in this network. “Sad Mood” directly related to “Suicide Ideation” and explained the highest variance. The network structure was signi�cantly different in network properties between adolescents who had suicide ideation and those who did not. “Restlessness” was the most central symptom in adolescents with suicide ideation. “Sad Mood” was the central and bridge symptom in adolescents with suicide ideation. Conclusion: “Restlessness” and “Sad Mood” might be interesting avenues for reducing depression and anxiety symptoms in adolescents with suicide ideation.
Finger Dexterity and Attention in the Elderly

Based on Rabinowitz et al. pointed out that there is an association exists between ﬁnger tapping and attention. The proposal study was based on the previous study and increased the speed of ﬁnger tapping to test the effect of ﬁnger dexterity on the attention of older adults. In this work, we tested whether ﬁnger exercise will be able to improve the attention span of the older person by the way of increase the speed of ﬁnger taps. We also tested whether the faster the tapping of the ﬁngers, the better the attention span of the older person.
Rapid and widespread vegetation responses to past climate change in the North Atlantic region

Ongoing anthropogenic perturbations to the atmosphere and biosphere increase the risk of future abrupt changes in the climate system and generate concern about the ability of natural ecosystems to respond to rapid climate change. Study of past climatic events and biotic responses can inform us about potential future change. Qualitatively fast local responses of plant taxa to abrupt late glacial climate oscillations have been reported from individual records and attributed to short migration distances in areas of high topographic relief. By using quantitative time-series analyses, we show that vegetation responses to late glacial climate change around the North Atlantic were rapid and widespread and occurred in areas of differing relief. Cross-correlation analysis of 11 high-resolution lacustrine records in eastern North America and Europe indicates vegetation-response times consistently of ,200 yr and often ,100 yr, despite regional differences in physiography and species composition. Vegetation lags of ,200 yr confirm theoretical predictions, and the apparently tight coupling between vegetation and atmosphere suggests that recent climatic trends may already have begun to affect plant population abundances and distributions.
Geochemical and boron isotopic compositions of tourmalines from selected gold-mineralised and barren rocks in SW Finland

Tourmaline-bearing rocks and a number of gold occurrences coexist in southwestern Finland, in a region where extensive magmatism and hydrothermal systems occurred during the Svecofennian orogeny, 1.9–1.8 Ga ago. Tourmalines investigated for this study were sampled from late-orogenic granite pegmatites (Erajarvi, Kietyonmaki), quartztourmaline veins from gold occurrences (Kutemajarvi, Riukka), and the tourmalinised contact between a synorogenic intrusion and supracrustal rocks (Lepomaki Au occurrence, Ylojarvi Cu-W-As-Ag-Au deposit). Major element compositions of the tourmalines are controlled by their host lithologies, whereas their boron isotopic compositions reflect the B reservoir(s) and the magmatichydrothermal processes of the B-bearing systems. The obtained δ 11 B values for granite pegmatite, vein, and intrusion-country rock contact-related tourmalines range between -10.2 ‰ and -13.2 ‰, -10.2 ‰ and -11.6 ‰, and -9.6 ‰ and -8.7 ‰, respectively, and are similar to tourmalines worldwide. The lighter B isotopic composition at Lepomaki gold and Ylojarvi polymetallic occurrences indicate different B reservoirs and magmatic-hydrothermal processes between synand late-orogenic tourmalines. Geological observations and geochemical data on tourmalines also suggest that B was a constituent in hydrothermal fluids at all localities, including the gold-mineralising fluids at Lepomaki, Ylojarvi and Riukka.
That's Interesting! Towards a Phenomenology of Sociology and a Sociology of Phenomenology

Summary Question: How do theories that are generally considered interesting differ from theories that are generally considered non-interesting? Answer: Interesting theories deny certain assumptions of their audience, while non-interesting theories affirm certain assumptions of their audience. This answer was arrived at through the examination of a number of famous social, and especially sociological, theories. That examination also generated a systematic index of the variety of propositional forms that interesting and non-interesting theories may take. The fertility of this approach suggested a new field be established called the Sociology of the Interesting, which is intended to supplement the Sociology of Knowledge. This new field will be phenomenologically oriented in so far as it will focus on the movement of the audience's mind from one accepted theory to another. It will be sociologically oriented in so far as it will focus on the dissimilar base-line theories of the various sociological categories that compose the audience. In addition to its value in interpreting the social impact of theories, the Sociology of the Interesting can contribute to our understanding of both the common sense and scientific perspectives on reality.
Object-level ranking: bringing order to Web objects

In contrast with the current Web search methods that essentially do document-level ranking and retrieval, we are exploring a new paradigm to enable Web search at the object level. We collect Web information for objects relevant for a specific application domain and rank these objects in terms of their relevance and popularity to answer user queries. Traditional PageRank model is no longer valid for object popularity calculation because of the existence of heterogeneous relationships between objects. This paper introduces PopRank, a domain-independent object-level link analysis model to rank the objects within a specific domain. Specifically we assign a popularity propagation factor to each type of object relationship, study how different popularity propagation factors for these heterogeneous relationships could affect the popularity ranking, and propose efficient approaches to automatically decide these factors. Our experiments are done using 1 million CS papers, and the experimental results show that PopRank can achieve significantly better ranking results than naively applying PageRank on the object graph.
Anisotropy in the subducting slab: Observations from Philippine Sea plate events in Taiwan

In the southernmost Ryukyu subduction zone, slab‐guiding behavior from intermediate‐depth earthquakes is well documented with a low‐frequency (<2 Hz) first P arrival followed by sustained high‐frequency (3–10 Hz) wave trains. Such waves developed by propagating along a long path within the slab are expected to have high sensitivity to anisotropy within the slab. We determine shear wave splitting parameters from 178 intraplate events that are deeper than 100 km. The possible slab‐anisotropy‐associated polarization pattern shows the fast direction at N65°E and delay time of 0.13–0.45 s. This is stronger than the previously documented crust effect (<0.1 s), similar to the mantle wedge effect (0.28 s in average), but weaker than the upper mantle effect (1.3 s in average) in Taiwan. The fast axis reflects the fossil spreading direction of Philippine Sea plate with minor clockwise rotation due to the collision to Eurasian plate.
COMPARISON OF KETAMINE-XYLAZINE, BUTORPHANOL-AZAPERONE-MEDETOMIDINE, AND NALBUPHINE-MEDETOMIDINE-AZAPERONE FOR RACCOON (PROCYON LOTOR) IMMOBILIZATION

Abstract: Raccoons (Procyon lotor) are frequently handled using chemical immobilization in North America for management and research. In a controlled environment, we compared three drug combinations: ketamine-xylazine (KX), butorphanol-azaperone-medetomidine (BAM), and nalbuphine-medetomidine-azaperone (NalMed-A) for raccoon immobilization. In crossover comparisons, raccoons received a mean of the following: 8.66 mg/kg ketamine and 1.74 mg/kg xylazine (0.104 mL/kg KX); 0.464 mg/kg butorphanol, 0.155 mg/kg azaperone, and 0.185 mg/kg medetomidine (0.017 mL/kg BAM); and 0.800 mg/kg nalbuphine, 0.200 mg/kg azaperone, and 0.200 mg/kg medetomidine (0.020 mL/kg NalMed-A). Induction time was shortest with KX (mean±SE, 10.0±0.7 min) and longest with NalMed-A (13.0±1.3 min). A sampling procedure was completed on 89% (16/18), 72% (13/18), and 89% (16/18) of the raccoons administered KX, BAM, and NalMed-A, respectively. Reasons for incomplete sampling included inadequate immobilization (one KX and one NalMed-A), responsive behaviors (one each with KX, BAM, NalMed-A), or animal safety (four BAM). Mean recovery time for KX was 32.8±7.1 min without antagonizing and 28.6±5.2 min following delivery of an antagonist. Mean recovery time was 6.2±0.8 min for BAM and 5.1±0.5 min for NalMed-A after antagonizing. Only with KX were raccoons observed to recover without use of an antagonist. Supplemental oxygen was provided to 23% (3/13), 72% (13/18), and 71% (12/17) of raccoons immobilized with KX, BAM, and NalMed-A, respectively. Hypoxemia at <80% oxygen saturation occurred in 0% (0/17), 27% (4/15), and 6% (1/16) of the raccoons administered KX, BAM, and NalMed-A, respectively; all raccoons fully recovered from chemical immobilization. All combinations could be used for raccoon immobilization; however, the need for delivery of supplemental oxygen to a majority of raccoons immobilized with BAM and NalMed-A may limit broader use of these agents for certain field studies involving capture, sample, and release of free-ranging animals from a practical standpoint.
The use of remote sensing to develop a site history for restoration planning in an arid landscape

Developing a site history and ecological site description is one of the critical steps in restoration planning for arid landscapes. This study focuses on Umm Nigga, Northeast of Kuwait, which was damaged by various human activities. The northern portion of Umm Nigga falls within the boundaries of the demilitarized zone (DMZ) adjacent to Iraq, and was fenced off to restrict public access since 1994. The central objective of this project was to use remote sensing, field assessment, and Geographical Information System (GIS) spatial data to develop a site history for restoration planning of Umm Nigga. Field observation and GIS analysis indicated that the landscape could be divided into three units along a gradient ranging from the coast to inland locations, based on geology, soil properties, and dominant vegetation. Reference sites in the DMZ were also matched for each unit. Remote sensing was used to compare vegetation cover between damaged and reference sites at selected units. Results showed that vegetation cover increased in the unfenced damaged site after the 1991 Gulf War from 2% in 1988 to 37% in 1998, but then it decreased to 23% in 2013. In the DMZ reference site, the vegetation cover also increased from 0% in 1988 to 40% in 1998, but it continued increasing through 2013 to 64%. We conclude that overgrazing and destructive camping are the major source of disturbance in the damaged areas.
Comparison of short-term outcomes between robotic and laparoscopic liver resection: a meta-analysis of propensity score-matched studies

Objective: This meta-analysis aimed to compare short-term outcomes between robotic liver resection (RLR) and laparoscopic liver resection (LLR) using data collected from propensity score-matched studies. Methods: The PubMed, Cochrane Library, and Embase databases were searched to collect propensity score-matched studies comparing RLR and LLR. Relevant data were extracted and analyzed. Odds ratios (ORs) and standardized mean differences (SMDs) with 95% confidence intervals (CIs) were calculated using fixed-effect or random-effect models. Meta-regression analysis was performed for primary outcome measures. Subgroup analyses and sensitivity analyses were performed for outcomes exhibiting high heterogeneity. Quality of evidence was evaluated using the Grading of Recommendations, Assessment, Development and Evaluation framework. Results: Twenty-two propensity score-matched studies were included to comprise 5272 patients (RLR group, 2422 cases; LLR group, 2850 cases). Intraoperative blood loss (SMD=−0.31 ml, 95% CI −0.48 to −0.14; P=0.0005), open conversion (OR=0.46, 95% CI 0.37–0.58; P <0.0001), and severe complications (OR=0.76, 95% CI 0.61–0.95; P=0.02) were significantly lower in the RLR group. Operation time, odds of use, and duration of Pringle maneuver, length of hospital stay, and odds of intraoperative blood transfusion, overall complications, R0 resection, reoperation, 30-day readmission, 30-day mortality, and 90-day mortality did not significantly differ between the groups. Further subgroup and sensitivity analyses suggested that the results were stable. Meta-regression analysis did not suggest a correlation between primary outcomes and study characteristics. The quality of evidence for the primary outcomes was medium or low, while that for the secondary outcomes was medium, low, or very low. Conclusion: Although some short-term outcomes are similar between RLR and LLR, RLR is superior in terms of less blood loss and lower odds of open conversion and severe complications. In the future, RLR may become a safe and effective replacement for LLR.
Noninvasive prediction of perineural invasion in intrahepatic cholangiocarcinoma by clinicoradiological features and computed tomography radiomics based on interpretable machine learning: a multicenter cohort study

Background: Perineural invasion (PNI) of intrahepatic cholangiocarcinoma (ICC) is a strong independent risk factor for tumour recurrence and long-term patient survival. However, there is a lack of noninvasive tools for accurately predicting the PNI status. The authors develop and validate a combined model incorporating radiomics signature and clinicoradiological features based on machine learning for predicting PNI in ICC, and used the Shapley Additive explanation (SHAP) to visualize the prediction process for clinical application. Methods: This retrospective and prospective study included 243 patients with pathologically diagnosed ICC (training, n=136; external validation, n=81; prospective, n=26, respectively) who underwent preoperative contrast-enhanced computed tomography between January 2012 and May 2023 at three institutions (three tertiary referral centres in Guangdong Province, China). The ElasticNet was applied to select radiomics features and construct signature derived from computed tomography images, and univariate and multivariate analyses by logistic regression were used to identify the significant clinical and radiological variables with PNI. A robust combined model incorporating radiomics signature and clinicoradiological features based on machine learning was developed and the SHAP was used to visualize the prediction process. A Kaplan–Meier survival analysis was performed to compare prognostic differences between PNI-positive and PNI-negative groups and was conducted to explore the prognostic information of the combined model. Results: Among 243 patients (mean age, 61.2 years ± 11.0 (SD); 152 men and 91 women), 108 (44.4%) were diagnosed as PNI-positive. The radiomics signature was constructed by seven radiomics features, with areas under the curves of 0.792, 0.748, and 0.729 in the training, external validation, and prospective cohorts, respectively. Three significant clinicoradiological features were selected and combined with radiomics signature to construct a combined model using machine learning. The eXtreme Gradient Boosting exhibited improved accuracy and robustness (areas under the curves of 0.884, 0.831, and 0.831, respectively). Survival analysis showed the construction combined model could be used to stratify relapse-free survival (hazard ratio, 1.933; 95% CI: 1.093–3.418; P=0.021). Conclusions: We developed and validated a robust combined model incorporating radiomics signature and clinicoradiological features based on machine learning to accurately identify the PNI statuses of ICC, and visualize the prediction process through SHAP for clinical application.
Finding Integral Points of Elliptic Curves over Imaginary Quadratic Fields

We determine the set of integral points on elliptic curves of rank $2$ defined over imaginary quadratic fields using quadratic Chabauty. This builds on the work of Balakrishnan, Bianchi, Besser and M\"uller, and gives the first example of quadratic Chabauty used to determine the integral points on a curve which is not a base change from $\mathbb{Q}$.
Medical Image Segmentation with Domain Adaptation: A Survey

Deep learning (DL) has shown remarkable success in various medical imaging data analysis applications. However, it remains challenging for DL models to achieve good generalization, especially when the training and testing datasets are collected at sites with different scanners, due to domain shift caused by differences in data distributions. Domain adaptation has emerged as an effective means to address this challenge by mitigating domain gaps in medical imaging applications. In this review, we specifically focus on domain adaptation approaches for DL-based medical image segmentation. We first present the motivation and background knowledge underlying domain adaptations, then provide a comprehensive review of domain adaptation applications in medical image segmentations, and finally discuss the challenges, limitations, and future research trends in the field to promote the methodology development of domain adaptation in the context of medical image segmentation. Our goal was to provide researchers with up-to-date references on the applications of domain adaptation in medical image segmentation studies.
Correlation between spin state and activity for hydrogen evolution of PtN2 monolayer

Spin plays a key role in physical and chemical reactions, such as oxygen evolution and hydrogen evolution reactions (OER/HER), but the spin–activity correlation has remained unclear. Based on a transition metal (TM)-doped PtN2 monolayer model with a well-defined spin center as an adsorption site, we here reveal that only an active spin state can enhance the strength of hydrogen adsorption, while an inert spin state offers very little influence. Specifically, the an unpaired electron along the out-of-plane direction such as in the dz2 orbital, acting as an active spin state, will strongly hybridize with hydrogen, resulting in enhanced hydrogen binding energy because the dz2 orbital is just enough to accommodate two electrons to form a bonding orbital. While the in-plane unpaired electron such as in the dx2−y2 orbital plays a negligible role in an adsorbing hydrogen atom. This is verified by a series of single atom catalysts comprising of PtN2 monolayer by replacing a Pt atom with a TM (Fe, Co, Ni, Ru, Rh, Pd, Os, or Ir) atom or subsequent adsorbing a Cl atom. One of the most promising materials is Pd@PtN2-Cl that offers superior HER activity, even better than pure Pt. This work uncovers the nature of spin–activity correlation, thus paving the way for the design of high-performance catalysts through spin-engineering.
Evidence for fluid migration as the source of deformation at Campi Flegrei caldera (Italy)

We model the location, geometry and density of the source of the recent geological unrest at Campi Flegrei caldera (Italy) by inverting levelling, trilateration and gravity measurements collected between 1980 and 1995. The best fitting source for the 1980–84 inflation is a horizontal penny‐shaped crack with a density 142 to 1115 kg/m3. The source best fitting the deflation period (1990–95) is a vertical spheroid with density between 902 and 1015 kg/m3. These results exclude the intrusion of magma, and indicate the migration of fluid to and from the caldera hydrothermal system as the cause of ground deformation and consequent unrest.
Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula

Robustness against adversarial attacks and distribution shifts is a long-standing goal of Reinforcement Learning (RL). To this end, Robust Adversarial Reinforcement Learning (RARL) trains a protagonist against destabilizing forces exercised by an adversary in a competitive zero-sum Markov game, whose optimal solution, i.e., rational strategy, corresponds to a Nash equilibrium. However, finding Nash equilibria requires facing complex saddle point optimization problems, which can be prohibitive to solve, especially for high-dimensional control. In this paper, we propose a novel approach for adversarial RL based on entropy regularization to ease the complexity of the saddle point optimization problem. We show that the solution of this entropy-regularized problem corresponds to a Quantal Response Equilibrium (QRE), a generalization of Nash equilibria that accounts for bounded rationality, i.e., agents sometimes play random actions instead of optimal ones. Crucially, the connection between the entropy-regularized objective and QRE enables free modulation of the rationality of the agents by simply tuning the temperature coefficient. We leverage this insight to propose our novel algorithm, Quantal Adversarial RL (QARL), which gradually increases the rationality of the adversary in a curriculum fashion until it is fully rational, easing the complexity of the optimization problem while retaining robustness. We provide extensive evidence of QARL outperforming RARL and recent baselines across several MuJoCo locomotion and navigation problems in overall performance and robustness.
An explanation of GRB Fermi-LAT flares and high-energy photons in stratified afterglows

The second Fermi/LAT gamma-ray burst (GRB) Catalogue (2FLGC) spanning the first decade of operations by the Large Area Telescope (LAT) collaboration was recently released. The closure relations of the synchrotron forward shock (FS) model are not able to reproduce a sizeable portion of the afterglow-phase light curves in this collection, indicating that there may be a large contribution from some other mechanism. Recently, synchrotron self-Compton (SSC) light curves from the reverse shock (RS) regions were derived in the thick- and thin-shell regimes for a constant-density medium, and it was demonstrated that analytical light curves could explain the GeV flare observed in several bursts from 2FLGC, including GRB 160509A. Here, we generalize the SSC RS scenario from the constant density to a stratified medium, and show that this contribution helps to describe the early light curves exhibited in some Fermi/LAT-detected bursts. As a particular case, we model a sample of eight bursts that exhibited a short-lasting emission with the synchrotron and SSC model from FS and RS regions, evolving in a stellar-wind environment, constraining the microphysical parameters, the circumburst density, the bulk Lorentz factor, and the fraction of shock-accelerated electrons. We demonstrate that the highest energy photons can only be described by the SSC from the FS region.