Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy-dependent Analyses of the Gamma-Ray Emission from HESS J1857+026 with Fermi-LAT

We report the discovery of the energy-dependent morphology of the GeV gamma-ray emission from HESS J1857+026 with more than 13 yr of Fermi Large Area Telescope data. The GeV gamma-ray emission from this region is composed of two extended components. The hard component with an index of 1.74 ± 0.07 in the energy range of 0.5–500 GeV is spatially coincident with HESS J1857+026, and its 68% containment radius varies from ∼0. °44 below 40 GeV to ∼0. °30 above 140 GeV. The hard GeV gamma-ray spectrum and the energy-dependent morphology of HESS J1857+026 make it favor a pulsar wind nebula origin, which is associated with the energetic pulsar PSR J1856+0245. The soft component with an index of 2.70 ± 0.16 and another extended gamma-ray source detected in this region, 4FGL J1857.9+0313e, with an index of 2.55 ± 0.07, are spatially coincident with two molecular clumps in the northeast and southwest of HESS J1857+026, which favors the hadronic process, and the protons could be accelerated by the hypothetical supernova remnant associated with PSR J1856+0245.
Frequency Spectrum is More Effective for Multimodal Representation and Fusion: A Multimodal Spectrum Rumor Detector

Multimodal content, such as mixing text with images, presents significant challenges to rumor detection in social media. Existing multimodal rumor detection has focused on mixing tokens among spatial and sequential locations for unimodal representation or fusing clues of rumor veracity across modalities. However, they suffer from less discriminative unimodal representation and are vulnerable to intricate location dependencies in the time-consuming fusion of spatial and sequential tokens. This work makes the first attempt at multimodal rumor detection in the frequency domain, which efficiently transforms spatial features into the frequency spectrum and obtains highly discriminative spectrum features for multimodal representation and fusion. A novel Frequency Spectrum Representation and fUsion network (FSRU) with dual contrastive learning reveals the frequency spectrum is more effective for multimodal representation and fusion, extracting the informative components for rumor detection. FSRU involves three novel mechanisms: utilizing the Fourier transform to convert features in the spatial domain to the frequency domain, the unimodal spectrum compression, and the cross-modal spectrum co-selection module in the frequency domain. Substantial experiments show that FSRU achieves satisfactory multimodal rumor detection performance.
Model Stealing Attack against Graph Classification with Authenticity, Uncertainty and Diversity

Recent research demonstrates that GNNs are vulnerable to the model stealing attack, a nefarious endeavor geared towards duplicating the target model via query permissions. However, they mainly focus on node classification tasks, neglecting the potential threats entailed within the domain of graph classification tasks. Furthermore, their practicality is questionable due to unreasonable assumptions, specifically concerning the large data requirements and extensive model knowledge. To this end, we advocate following strict settings with limited real data and hard-label awareness to generate synthetic data, thereby facilitating the stealing of the target model. Specifically, following important data generation principles, we introduce three model stealing attacks to adapt to different actual scenarios: MSA-AU is inspired by active learning and emphasizes the uncertainty to enhance query value of generated samples; MSA-AD introduces diversity based on Mixup augmentation strategy to alleviate the query inefficiency issue caused by over-similar samples generated by MSA-AU; MSA-AUD combines the above two strategies to seamlessly integrate the authenticity, uncertainty, and diversity of the generated samples. Finally, extensive experiments consistently demonstrate the superiority of the proposed methods in terms of concealment, query efficiency, and stealing performance.
Cross-Domain Robustness of Transformer-based Keyphrase Generation

Modern models for text generation show state-of-the-art results in many natural language processing tasks. In this work, we explore the effectiveness of abstractive text summarization models for keyphrase selection. A list of keyphrases is an important element of a text in databases and repositories of electronic documents. In our experiments, abstractive text summarization models fine-tuned for keyphrase generation show quite high results for a target text corpus. However, in most cases, the zero-shot performance on other corpora and domains is significantly lower. We investigate cross-domain limitations of abstractive text summarization models for keyphrase generation. We present an evaluation of the fine-tuned BART models for the keyphrase selection task across six benchmark corpora for keyphrase extraction including scientific texts from two domains and news texts. We explore the role of transfer learning between different domains to improve the BART model performance on small text corpora. Our experiments show that preliminary fine-tuning on out-of-domain corpora can be effective under conditions of a limited number of samples.
Self-interacting Vectorial Dark Matter in a SM-like Dark Sector

A $SU(2)_D \times U(1)_D$ gauge-Higgs sector, an exact dark copy of the Standard Model (SM) one, is proposed. It is demonstrated that the dark gauge bosons ${\cal W}^{(p,m)}$, in analogous to the SM $W^\pm$, can fulfill the role as a self-interacting vector dark matter candidate, solving the core versus cusp and missing satellites problems faced by the conventional paradigm of collisionless weakly interacting massive particle. Constraints from collider, astroparticle and cosmology on such a self-interacting vector dark matter candidate are scrutinized. Implications for the future searches of ${\cal W}^{(p,m)}$ in direct detection experiments are discussed.
The Metacognitive Demands and Opportunities of Generative AI

Generative AI (GenAI) systems offer unprecedented opportunities for transforming professional and personal work, yet present challenges around prompting, evaluating and relying on outputs, and optimizing workflows. We argue that metacognition$\unicode{x2013}$the psychological ability to monitor and control one's thoughts and behavior$\unicode{x2013}$offers a valuable lens to understand and design for these usability challenges. Drawing on research in psychology and cognitive science, and recent GenAI user studies, we illustrate how GenAI systems impose metacognitive demands on users, requiring a high degree of metacognitive monitoring and control. We propose these demands could be addressed by integrating metacognitive support strategies into GenAI systems, and by designing GenAI systems to reduce their metacognitive demand by targeting explainability and customizability. Metacognition offers a coherent framework for understanding the usability challenges posed by GenAI, and provides novel research and design directions to advance human-AI interaction.
Low‐frequency nonlinearity and regime behavior in the Northern Hemisphere extratropical atmosphere

The extratropical atmosphere is characterized by robust circulations which have time scales longer than that associated with developing baroclinic systems but shorter than a season. Such low‐frequency variability is governed to a large extent by nonlinear dynamics and, hence, is chaotic. A useful aspect of this low‐frequency circulation is that it can often be described by just a few quasi‐stationary regime states, broadly defined as recurrent or persistent large‐scale structures, that exert a significant impact on the probability of experiencing extreme surface weather conditions. We review a variety of techniques for identifying circulation regimes from reanalysis and numerical model output. While various techniques often yield similar regime circulation patterns, they offer different perspectives on the regimes. The regimes themselves are manifest in planetary scale patterns. They affect the structure of synoptic scale patterns. Extratropical flow regimes have been identified in simplified atmospheric models and comprehensive coupled climate models and in reanalysis data sets. It is an ongoing challenge to accurately model these regime states, and high horizontal resolutions are often needed to accurately reproduce them. The regime paradigm helps to understand the response to external forcing on a variety of time scales, has been helpful in categorizing a large number of weather types and their effect on local conditions, and is useful in downscaling. Despite their usefulness, there is a debate on the “nonequivocal” and systematic existence of these nonlinear circulation regimes. We review our current understanding of the nonlinear and regime paradigms and suggest future research.
Nuclear localization of Argonaute 2 is affected by cell density and may relieve repression by microRNAs

Abstract Argonaute protein is associated with post-transcriptional control of cytoplasmic gene expression through miRNA-induced silencing complexes (miRISC). Specific cellular and environmental conditions can trigger AGO protein to accumulate in the nucleus. Localization of AGO is central to understanding miRNA action, yet the consequences of AGO being in the nucleus are undefined. We show nuclear enrichment of AGO2 in HCT116 cells grown in two-dimensional culture to high density, HCT116 cells grown in three-dimensional tumor spheroid culture, and human colon tumors. The shift in localization of AGO2 from cytoplasm to nucleus de-represses cytoplasmic AGO2-eCLIP targets that were candidates for canonical regulation by miRISC. Constitutive nuclear localization of AGO2 using an engineered nuclear localization signal increases cell migration. Critical RNAi factors also affect the localization of AGO2. Knocking out an enzyme essential for miRNA biogenesis, DROSHA, depletes mature miRNAs and restricts AGO2 localization to the cytoplasm, while knocking out the miRISC scaffolding protein, TNRC6, results in nuclear localization of AGO2. These data suggest that AGO2 localization and miRNA activity can be regulated depending on environmental conditions, expression of mature miRNAs, and expression of miRISC cofactors. Localization and expression of core miRISC protein machinery should be considered when investigating the roles of miRNAs.
Initial validation of the Mass. General Neuropathy Exam Tool (MAGNET) for evaluation of distal small‐fiber neuropathy

Diagnosis of small‐fiber neuropathy (SFN) is hampered by its subjective symptoms and signs. Confirmatory testing is insufficiently available and expensive, so predictive examinations have value. However, few support the 2020 SFN consensus‐case‐definition requirements or were validated for non‐diabetes neuropathies. Thus we developed the Massachusetts General Hospital Neuropathy Exam Tool (MAGNET) and measured diagnostic performance in 160 symptomatic patients evaluated for length‐dependent SFN from any cause and 37 healthy volunteers.
Bayesian inference for prediction of survival probability in prime‐boost vaccination regimes

We focus on Bayesian inference for survival probabilities in a prime‐boost vaccination regime in the development of an Ebola vaccine. We are interested in the heterologous prime‐boost regimen (unmatched vaccine deliverys using the same antigen) due to its demonstrated durable immunity, well‐tolerated safety profile, and suitability as a population vaccination strategy. Our research is motivated by the need to estimate the survival probability given the administered dosage. To do so, we establish two key relationships. Firstly, we model the connection between the designed dose concentration and the induced antibody count using a Bayesian response surface model. Secondly, we model the association between the antibody count and the probability of survival when experimental subjects are exposed to the Ebola virus in a controlled setting using a Bayesian probability of survival model. Finally, we employ a combination of the two models with dose concentration as the predictor of the survival probability for a future vaccinated population. We implement our two‐level Bayesian model in Stan, and illustrate its use with simulated and real‐world data. Performance of this model is evaluated via simulation. Our work offers a new application of drug synergy models to examine prime‐boost vaccine efficacy, and does so using a hierarchical Bayesian framework that allows us to use dose concentration to predict survival probability.
Refractive Predictability between Standard and Total Keratometry during the Femtosecond Laser-Assisted Cataract Surgery with Monofocal Intraocular Lens with Enhanced Intermediate Function

Purpose We aimed to compare the accuracy of the intraocular lens (IOL) calculation formula using the standard keratometry (K) and total K (TK) during the femtosecond laser-assisted cataract surgery (FLACS) with a monofocal IOL with enhanced intermediate function using currently used formulas. Methods A retrospective review of 125 eyes from 125 patients who had undergone FLACS with implantation of monofocal IOL with enhanced intermediate function was conducted. The predicted refractive power was calculated using an optical biometer (IOLmaster 700) according to the K and TK in the Barrett Universal II, SRK/T, Haigis, and Holladay 2 formulas. Absolute prediction error (APE) obtained from the actual postoperative refractive outcomes and the refractive error predicted in each formula was compared one month after surgery. Results Mean APE ranged between 0.29 and 0.39 diopters (D) regardless of the calculation formula and the method of measuring corneal curvature. Significant differences were observed in the APE from the four formulas and the two keratometric measurements (p = 0.014). In a total of 125 eyes from 125 patients, the mean APE was lowest with the Barrett Universal II formula. Across all formulas, both the mean APE and the median APE tended to be lower for K than for TK, although there was no significant difference. Approximately 70% to 80% of the patients were included within 0.5 D of the refractive error across all formulas. The percentage of eyes within 0.5 D of APE outcomes was not statistically different between the K and TK data when using each formula. Conclusions Keratometric measurements considering the poster corneal curvature did not show any additional advantages when implanting the monofocal IOL with enhanced intermediate function during the FLACS.
A Polycrystalline Pd Surface Studied by Two-Dimensional Surface Optical Reflectance during CO Oxidation: Bridging the Materials Gap

Industrial catalysts are complex materials systems operating in harsh environments. The active parts of the catalysts are nanoparticles that expose different facets with different surface orientations at which the catalytic reactions occur. However, these facets are close to impossible to study in detail under industrially relevant operating conditions. Instead, simpler model systems, such as single crystals with a well-defined surface orientation, have been successfully used to study gas–surface interactions such as adsorption and desorption, surface oxidation, and oxidation/reduction reactions. To more closely mimic the many facets exhibited by nanoparticles and thereby close the so-called materials gap, there has also been a recent move toward using polycrystalline surfaces and curved crystals. However, these studies are limited either by the pressure or spatial resolution at realistic pressures or by the number of surfaces studied simultaneously. In this work, we demonstrate the use of reflectance microscopy to study a vast number of catalytically active surfaces simultaneously under realistic and identical reaction conditions. As a proof of concept, we have conducted an operando experiment to study CO oxidation over a Pd polycrystal, where the polycrystalline surface acts as a collection of many single-crystal surfaces. Finally, we visualized the resulting data by plotting the reflectivity as a function of surface orientation. We think the techniques and visualization methods introduced in this work will be key toward bridging the materials gap in catalysis.
High expression of SLC38A1 predicts poor prognosis in patients with de novo acute myeloid leukemia

The glutamine amino acid transporter solute carrier family 38 member 1 (SLC38A1) is associated with the occurrence and progression of solid tumors. However, it has not yet been assessed in patients with hematologic malignancy. Herein, we investigated SLC38A1 expression and explored its clinical implications in acute myeloid leukemia (AML). The results showed that patients with high SLC38A1 expression had a lower mutation rate of NPM1 gene and higher incidence of adverse‐risk karyotype (p = 0.0010 and 0.0051, respectively). Patients with a high level of SLC38A1 expression presented significantly shorter overall survival in whole‐cohort, chemotherapy‐only, and non‐inv(16) AML (p = 0.0049, 0.0247, and 0.0005 respectively). Moreover, both univariate and multivariate analyses showed that high SLC38A1 expression was an independent unfavorable prognostic biomarker for AML (p = 0.0057 and 0.0483, respectively). In summary, our study revealed SLC38A1 as a valuable prognostic and predictive marker for AML. Further, glutamine transporter SLC38A1 might serve as a potential target for the development of novel therapeutic drugs in the treatment of AML.
cLD: Rare-variant linkage disequilibrium between genomic regions identifies novel genomic interactions

Linkage disequilibrium (LD) is a fundamental concept in genetics; critical for studying genetic associations and molecular evolution. However, LD measurements are only reliable for common genetic variants, leaving low-frequency variants unanalyzed. In this work, we introduce cumulative LD (cLD), a stable statistic that captures the rare-variant LD between genetic regions, which reflects more biological interactions between variants, in addition to lack of recombination. We derived the theoretical variance of cLD using delta methods to demonstrate its higher stability than LD for rare variants. This property is also verified by bootstrapped simulations using real data. In application, we find cLD reveals an increased genetic association between genes in 3D chromatin interactions, a phenomenon recently reported negatively by calculating standard LD between common variants. Additionally, we show that cLD is higher between gene pairs reported in interaction databases, identifies unreported protein-protein interactions, and reveals interacting genes distinguishing case/control samples in association studies.
Perceptions of personal control and treatment efficacy of sport-related concussions in collegiate athletes

ABSTRACT Objective The purpose of this study was to examine healthy collegiate athletes’ perceptions of personal control and beliefs regarding the treatment efficacy related to sport-related concussion (SRC) along with identifying factors that may be associated with these perceptions. Methods This cross-sectional study included collegiate athletes (n = 956) between the age of 18–26 years. Participants completed a 10- to 15-min survey regarding their demographics, diagnosed SRC history, SRC knowledge, and Perceptions of Concussion Inventory for Athletes (PCI-A). Chi-squared analysis and multivariable logistic regressions were conducted to identify factors associated with the PCI-A outcomes of personal control and treatment efficacy perceptions. Results 24.2% of respondents reported higher perceptions of personal control, while 77.3% reported higher perceptions of treatment efficacy. The multivariable logistic regression revealed males had higher odds of greater perceptions of personal control (OR = 1.50; 95% CI: 1.10–2.03), while those with a history of diagnosed SRC had lower odds of having favorable treatment efficacy beliefs (OR: 0.69; 95% CI: 0.50–0.96). Conclusions This study established that collegiate athletes generally have lower perceptions of personal control and higher perceptions of treatment efficacy related to SRC recovery. Comprehensive SRC education should be expanded for individuals to understand that they have power over their own health outcomes and that SRC is a treatable injury.
Raynaud’s phenomenon in the feet of Arctic open-pit miners

ABSTRACT The literature on Raynaud’s phenomenon (RP) in the feet is scarce, especially in the occupational setting. The primary aim of our study was to investigate the occurrence of RP in the feet of miners. As part of the MineHealth project, written surveys and clinical examinations were completed by 260 Arctic open-pit miners working in northern Sweden and Norway (participation rate 53.6%). Data on RP were collected using standardised colour charts and questionnaire items. Clinical examination included assessing the perception of vibration and pain in both feet. There were eight women and three men who reported RP in the feet. Four also had RP in their hands but none acknowledged any first-degree relatives with the condition. Nine reported exposure to foot-transmitted vibration and one to hand-arm vibration. Seven showed signs of neurosensory injury in the feet. To conclude, the occurrence of RP in the feet of miners was 4.4%. Most cases with RP in the feet did not report the condition in the hands and were exposed to vibration transmitted directly to the feet. There were no reports of a hereditary component. Most cases with RP in the feet also had clinical findings suggestive of peripheral neuropathy in the feet.
Bactericidal killing of meningococcal W strains isolated in Argentina by the sera of adolescents and infants immunized with 4-component meningococcal serogroup B vaccine (4CMenB)

ABSTRACT Invasive meningococcal disease (IMD) is a life-threatening disease caused by meningococcal serogroups A, B, C, W, X, and Y, of which B and W are most common in Argentina. The 4-component meningococcal serogroup B (4CMenB) vaccine contains three purified recombinant protein antigens (Neisseria adhesin A [NadA], factor H binding protein [fHbp], and Neisserial Heparin Binding Antigen [NHBA]) and outer membrane vesicles (OMV), which is derived from the New Zealand epidemic strain and contains Porin A 1.4. These antigens are present and conserved in strains that belong to other serogroups. In this study, we show that 10/11 (91%) meningococcal serogroup W (MenW) strains selected to be representative of MenW isolates that caused IMD in Argentina during 2010–2011 were killed in bactericidal assays by the sera of adolescents and infants who had been immunized with the 4CMenB vaccine. We also show that MenW strains that caused IMD in Argentina during 2018–2021 were genetically similar to the earlier strains, indicating that the 4CMenB vaccine would likely still provide protection against current MenW strains. These data highlight the potential of 4CMenB vaccination to protect adolescents and infants against MenW strains that are endemic in Argentina.