Miracle-dz/UniFAR-FTUs huggingface dataset:
Causal Associations Between Lifestyle Habits and Risk of Benign Prostatic Hyperplasia: A Two-Sample Mendelian Randomization Study

Abstract Background Benign prostatic hyperplasia (BPH) most often occurs in older men; previous studies and clinical experience suggest a potential link between lifestyle habits such as sleep habits, sedentary behavior, exercise levels, and BPH, but whether they have a clear causal relationship and the direction of that causality is unclear. We aimed to investigate the causal relationship between lifestyle habits and BPH using 2-sample Mendelian randomization (MR) analysis. Methods Instrumental genetic independent variables strongly associated with the selected exposure factors were filtered from published genome-wide association studies (GWAS) consisting primarily of European ancestry samples. GWAS from BPH was analyzed as an MR outcome with the inverse-variance weighted method, maximum likelihood, weighted median method, MR–Egger regression, and several sensitivity analyses, including Cochran’s Q test, intercept of MR–Egger, and MR pleiotropy residual sum and outlier test. Results MR analysis showed a significant causal risk relationship between sleep duration and BPH, with an odds ratio of 0.42 (95% confidence interval, 0.25–0.69, p = .001) for BPH when sleep duration was increased by 1 standard deviation, but we did not find a causal relationship between the 2 when we performed a reverse analysis. However, sedentary behavior and different levels of exercise did not significantly affect the risk of BPH. Conclusions This study showed a strong causal relationship between sleep levels and BPH, with adequate sleep duration being a protective factor for BPH.
Adaptive leader‐following state consensus of multiagent systems with switching topology

In this paper, an adaptive leader‐following consensus problem of multiagent systems with possibly persistent switching topology is solved. The control goal is to achieve state consensus of multiagent systems with switching topology in the presence of system parameter uncertainties. After introducing an indicator function, a new uniform nominal controller structure is developed to ensure consensus for multiagent systems with switching topology for the case of known system parameters, which provides the a priori knowledge for the adaptive control design. Then, an adaptive state consensus control scheme is developed for dealing with unknown dynamics of both the leader and the followers, for multiagent systems with switching topology. Complete stability and asymptotic state consensus analysis is shown to guarantee the desired consensus performance despite possibly persistent topology switches. A simulation study with several different cases is conducted to evaluate the effectiveness of the proposed adaptive consensus control scheme.
Skeletal muscle‐enriched miRNAs are highly unstable in vivo and may be regulated in a Dicer‐independent manner

MicroRNAs (miRNAs) are small noncoding RNAs that control essential cellular processes. For several decades, the molecular mechanisms underlying the functions and biogenesis of miRNAs have been clarified, whereas the molecular dynamics of miRNAs are poorly understood. We recently found that muscle‐enriched miRNAs were reduced by only 20 ~ 50% in the skeletal muscles even 4 weeks after the suppression of miRNA processing through an inducible depletion of Dicer1 gene. These data suggest that miRNAs are stably expressed in skeletal muscle. In this study, we investigated the half‐lives of those miRNAs in adult skeletal muscle with an in vivo metabolic labeling strategy and a genetic mouse model. In contrast to the hypothesis, in vivo metabolic labeling revealed that the half‐lives of skeletal‐muscle‐enriched miRNAs were approximately 11–20 h. Furthermore, the levels of mature miR‐23a decreased rapidly in the skeletal muscle of mice lacking miR‐23 clusters in a tamoxifen‐inducible manner. These data suggest that skeletal‐muscle‐enriched miRNAs are not highly stable in vivo. We also observed that the transfer of miR‐150 into Dicer1‐deficient muscle increased the miR‐150 level to the same as that in control muscle. Taken together, our data demonstrate that miRNAs are degraded within a few days in adult skeletal muscle and that a Dicer‐independent biogenetic pathway may produce mature miRNAs.
Spectral Descriptors for Data Clustering and Classification

Spectral descriptors have received much attention in recent years due in large part to their versatility as well as their ability to capture either local or global geometric information of data. While the overwhelming majority of work on spectral descriptors has concentrated primarily on image/shape retrieval and object recognition, the goal of this work is to introduce efficient algorithms for data classification and clustering in the spectral graph-theoretic setting. In addition to exploiting the dependence among the features of spectral descriptors, we perform clustering and classification on sparse codes, thereby seamlessly capturing the similarity between these features. Unlike classification in which objects are assigned to predefined classes, clustering is different in the sense that the number (and labels) of clusters or the cluster structure are not known in advance. In this thesis, we propose a spectral graph-theoretic clustering and classification framework, called GraphFDD, which uses the Fermi density descriptor (FDD) in conjunction with graph regularized sparse coding. We also propose a unified framework for data clustering using the spectral graph wavelet descriptor, which has a strong discriminative power and good performance in capturing neighborhood information. To further enhance the effectiveness of the proposed algorithms, we not only optimize the parameters, but also determine the proper matching normalization technique. To assess the performance of the proposed algorithms, we use several validity measures and indices, including the average clustering accuracy, normalized mutual information, confusion matrix and classification accuracy. Our experiments on different standard benchmarks not only show that the proposed approaches outperform state-of-the-art methods, but also provide attractive scalability and robustness in terms of computational efficiency.
Molecular subtypes of endometrial cancer: Implications for adjuvant treatment strategies

When determining adjuvant treatment for endometrial cancer, the decision typically relies on factors such as cancer stage, histologic grade, subtype, and a few histopathologic markers. The Cancer Genome Atlas revealed molecular subtyping of endometrial cancer, which can provide more accurate prognostic information and guide personalized treatment plans.
Subcortico-amygdala pathway processes innate and learned threats

Behavioral flexibility and timely reactions to salient stimuli are essential for survival. The subcortical thalamic-basolateral amygdala (BLA) pathway serves as a shortcut for salient stimuli ensuring rapid processing. Here, we show that BLA neuronal and thalamic axonal activity in mice mirror the defensive behavior evoked by an innate visual threat as well as an auditory learned threat. Importantly, perturbing this pathway compromises defensive responses to both forms of threats, in that animals fail to switch from exploratory to defensive behavior. Despite the shared pathway between the two forms of threat processing, we observed noticeable differences. Blocking β-adrenergic receptors impairs the defensive response to the innate but not the learned threats. This reduced defensive response, surprisingly, is reflected in the suppression of the activity exclusively in the BLA as the thalamic input response remains intact. Our side-by-side examination highlights the similarities and differences between innate and learned threat-processing, thus providing new fundamental insights.
Recombination from polar InGaN/GaN quantum well structures at high excitation carrier densities

In this paper we report on the emergence of a high energy band at high optically excited carrier densities in the low temperature photoluminescence spectra from polar InGaN/GaN single quantum well structures. This high energy band emerges at carrier densities when the emission from the localized ground states begins to saturate. We attribute this high energy band to recombination involving higher energy less strongly localized electron and hole states that are populated once the localized ground states become saturated; this assignment is supported by the results from an atomistic tight-binding model. A particular characteristic of the recombination at the high carrier densities is that the overall forms of the photoluminescence decay curves bear great similarity to those from semiconductor quantum dots. The decay curves consist of plateaus where the photoluminescence intensity is constant with time as a result of Pauli state blocking in the high energy localized states followed by a rapid decrease in intensity once the carrier density is sufficiently low that the states involved are no longer saturated.
Busulfan for Allogeneic Hematopoietic Stem Cell Transplantation in Children with Severe Aplastic Anemia: A Retrospective Study

Introduction: This retrospective study aimed to compare a range of conditioning regimens in children with severe aplastic anemia (SAA) undergoing allogeneic hematopoietic stem cell transplantation (allo-HSCT) at the Seventh Medical Center of PLA General Hospital between January 2008 and June 2017. Methods: Patients were categorized into the Bu (Bu + Flu + Cy + ATG-F regimen) and control (Flu + Cy + ATG-F) groups, with a median follow-up time after HSCT of 3.5 (range, 3.1–6.2) and 3.7 (3.2–5.9) years in the Bu and control groups, respectively. Results: No differences were observed between the two groups regarding the median time of peripheral blood neutrophil and platelet engraftment (p = 0.538 and p = 0.491); the 28-day engraftment rates of neutrophils were similar (p = 0.199), although higher for platelets with Bu (p = 0.044). Additionally, graft failure was 0% and 20.0% in the Bu and control groups, respectively (p = 0.004). In both groups, the incidence of grades III–IV (or grades II–IV) acute graft-versus-host disease (GVHD) and chronic GVHD was not significantly different (p > 0.05). Moreover, the 3-year overall survival and failure-free survival did not show significant differences (p = 0.670 and p = 0.908). Discussion: In children with SAA undergoing allo-HSCT, conditioning regimen with Bu + Flu + Cy + ATG-F is capable of enhancing the myeloablation effect, promoting donor hematopoietic stem cell engraftment, and reducing the graft failure rate. Furthermore, it does not increase the incidence of complications, including GVHD.
TMEM120A/TACAN: A putative regulator of ion channels, mechanosensation, and lipid metabolism

ABSTRACT TMEM120A (TACAN) is an enigmatic protein with several seemingly unconnected functions. It was proposed to be an ion channel involved in sensing mechanical stimuli, and knockdown/knockout experiments have implicated that TMEM120A may be necessary for sensing mechanical pain. TMEM120A’s ion channel function has subsequently been challenged, as attempts to replicate electrophysiological experiments have largely been unsuccessful. Several cryo-EM structures revealed TMEM120A is structurally homologous to a lipid modifying enzyme called Elongation of Very Long Chain Fatty Acids 7 (ELOVL7). Although TMEM120A’s channel function is debated, it still seems to affect mechanosensation by inhibiting PIEZO2 channels and by modifying tactile pain responses in animal models. TMEM120A was also shown to inhibit polycystin-2 (PKD2) channels through direct physical interaction. Additionally, TMEM120A has been implicated in adipocyte regulation and in innate immune response against Zika virus. The way TMEM120A is proposed to alter each of these processes ranges from regulating gene expression, acting as a lipid modifying enzyme, and controlling subcellular localization of other proteins through direct binding. Here, we examine TMEM120A’s structure and proposed functions in diverse physiological contexts.
A psychometric evaluation of a new social subscale for the Common Misconceptions about Traumatic Brain Injury (CM-TBI) questionnaire: toward the CM-TBI-II

ABSTRACT Objective Existing TBI misconception measures are critiqued for failing to measure postinjury social experiences. This study developed a social subscale for the Common Misconceptions about TBI (CM-TBI) questionnaire for use in the general public. Methods Seven experts independently review items drawn from the literature. Shortlisted items were administered online to 158 adults (aged ≥18 years; 51% postschool educated; 60% no TBI experience), the CM-TBI, and a measure of construct validity (a published TBI-adaptation of the Community Attitudes Towards the Mentally Ill; CAMI-TBI). One week later, the new items were redeployed (n = 46). Results Expert review and iterative correlations identified a 10-item social subscale (internal consistency, test-retest reliability, α’s>.80). When added to the CM-TBI (ie. CM-TBI-II), the internal consistency was . 71. The social subscale was significantly correlated with CAMI-TBI measures (p’s <.05, r’s > .3). There was no significant difference on the social subscale for education subgroups (school vs post-school, p = 0.056) or previous TBI experience; but there was a difference for the CM-TBI-II (post-school>school; Cohen’s d = 7.83, large effect). Conclusion This study found strong preliminary psychometric support for a new social subscale, administered as the CM-TBI-II. This subscale shows promise as a measure of misconceptions about social functioning post-TBI. The CM-TBI-II could support evaluations of programs aiming to improve social engagement and community participation for people with TBI.
Electron pairing across a band intersection may create a highly conductive state

Electrons in metals form a Fermi surface separating occupied from unoccupied states in momentum space at zero temperature. Interactions between electrons are usually accounted for by the Landau theory of Fermi liquids; however, little is known about the stability of the Fermi liquid when the Fermi level intercepts the crossing point between two bands, shrinking the Fermi surface to a set of points known as conical intersections. Here we consider the possibility of pairing electronic states across conical intersections that results in a Bardeen-Cooper-Schrieffer-like state restricted to a finite range of energies around the crossing point, hence,"floating"over an ordinary Fermi sea of occupied states in the lower band. Although this state is not superconducting in the usual sense and does not exhibit a gap in its excitation spectrum, it is nevertheless immune to elastic scattering caused by any kind of disorder, and is therefore expected to exhibit high electric conductivity at low temperature, similar to a real superconductor. The stability of this correlated state requires high density of electronic states in the vicinity of the crossing point -- a feature that may occur in twisted multilayer graphene structures, which are experimentally available. Our findings thus open an exciting opportunity for creating a new class of highly conductive materials.
Development of low-dissipative projection method framework integrating various high-order time integration schemes using OpenFOAM

A low-dissipative solution framework integrating various types of high-order time scheme is proposed and implemented based on the open-source C++ library OpenFOAM. This framework aims to introduce different categories of low-dissipative time integration schemes into a unified solver convenient for comparison of scheme performance in finite volume computational fluid dynamics code, contributing to the development of low dissipation scheme appropriate for scale-resolving turbulence simulation. To demonstrate this general framework's ability of including a wide range of time integration method, in addition to typical Runge--Kutta family schemes of linear single-step method, two more complex linear multi-step method, Adams--Bashforth family and Adams--Bashforth--Moutton family schemes, are implemented with the projection algorithm, which increase the options of time discretization. The unified solver obtained by the solution framework select the specified time scheme from a variety of alternatives in runtime rather than maintaining multiple solvers with each compiled for a single scheme, while new scheme can be easily added according to the basic idea of this universal framework. Further research on the stability of the explicit scheme indicates that a multi-step method with an appropriate order may be an optimal choice when taking both the prediction accuracy and computational efficiency into account in unstable problems.
Safety Control of Uncertain MIMO Systems Using Dynamic Output Feedback Barrier Pairs

Safety control of dynamical systems using barrier functions relies on knowing the full state information. This paper introduces a novel approach for safety control in uncertain MIMO systems with partial state information. The proposed method combines the synthesis of a vector norm barrier function and a dynamic output feedback safety controller to ensure robust safety enforcement. The safety controller guarantees the invariance of the barrier function under uncertain dynamics and disturbances. To address the challenges associated with safety verification using partial state information, a barrier function estimator is developed. This estimator employs an identifier-based state estimator to obtain a state estimate that is affine in the uncertain model parameters of the system. By incorporating a priori knowledge of the limits of the uncertain model parameters and disturbances, the state estimate provides a robust upper bound for the barrier function. Comparative analysis with existing control barrier function based methods shows the advantage of the proposed approach in enforcing safety constraints under tight input constraints and the utilization of estimated state information.
The Infrared Extinction Law in the Ophiuchus Molecular Cloud Based on the UKIDSS and Spitzer c2d Surveys

Investigating the extinction properties in dense molecular clouds is of significant importance for understanding the behavior of interstellar dust and its impact on observations. In this study, we comprehensively examined the extinction law in the Ophiuchus cloud across a wavelength range from 0.8 μm to 8 μm. To achieve this, we analyzed NIR and MIR data obtained from the UKIDSS GCS and the Spitzer c2d survey, respectively. By fitting a series of color–color diagrams, we determined color-excess ratios EJ−λ/EJ−K for seven passbands. These ratios were then directly converted to derive the relative extinction law Aλ/AK. Our findings demonstrate that the Ophiuchus cloud exhibits a characteristic of flat MIR extinction, consistent with previous studies. Additionally, our results reveal variations in the extinction law with extinction depth, indicating a flatter trend from the NIR to MIR bands as extinction increases. Notably, our analysis reveals no significant difference in the MIR extinction law among the four dark clouds: L1712, L1689, L1709, and L1688. However, distinct variations were observed in the extinction law for regions outside the dark clouds, specifically L1688N and L1688W. These regions displayed lower color-excess ratios EJ−λ/EJ−K in the Spitzer/IRAC bands. This observation lends support to the dust growth occurring in the dense regions of the Ophiuchus cloud.
Efficient Quantum Counting and Quantum Content-Addressable Memory for DNA Similarity

We present QCAM, a quantum analogue of Content-Addressable Memory (CAM), useful for finding matches in two sequences of bit-strings. Our QCAM implementation takes advantage of Grover's search algorithm and proposes a highly-optimized quantum circuit implementation of the QCAM oracle. Our circuit construction uses the parallel uniformly controlled rotation gates, which were used in previous work to generate QBArt encodings. These circuits have a high degree of quantum parallelism which reduces their critical depth. The optimal number of repetitions of the Grover iterator used in QCAM depends on the number of true matches and hence is input dependent. We additionally propose a hardware-efficient implementation of the quantum counting algorithm (HEQC) that can infer the optimal number of Grover iterations from the measurement of a single observable. We demonstrate the QCAM application for computing the Jaccard similarity between two sets of k-mers obtained from two DNA sequences.
Comparability of Automated Vehicle Crash Databases

Advanced driving assistance systems are available on many late-model vehicles, and automated driving systems are testing on public roads. Regulators and developers continue to assess the safety of these vehicles by comparing automated vehicle crash rates to baseline, human-driven crash rates. While there are several widely-cited automated vehicle and conventional vehicle crash databases, these databases have different underlying assumptions and inclusion criteria. Crash rates among databases may be directly comparable only with significant filtering and normalization, if at all. This paper reviews current automated vehicle and baseline human-driven crash databases and evaluates their comparability. Recommendations are presented to improve their comparability, both in terms of normalization and contextualization, as well as additional data fields that can be incorporated into existing databases. These findings may assist researchers, regulators, and automated vehicle developers attempting to evaluate the safety of driving automation systems.
The dynamical magnetic-induced quark spin polarization at the early stage in heavy-ion collisions

There has been significant interest in recent years in studying the spin polarization of hyperons in heavy-ion collisions. However, describing the dynamic spin polarization of quarks in quark-gluon plasma fireballs in detail presents a significant challenge. In this study, we conducted a phenomenological investigation of the dynamical spin polarization of quarks induced by the magnetic field at the pre-thermal stage in heavy-ion collisions using the recently developed theoretical tool of chiral kinetic theory. This study presents a comprehensive analysis of the dynamic process of quark spin polarization induced by magnetic fields. Our findings demonstrate that the spin polarization of quarks is highly sensitive to the interactions between quarks. These interactions can delay the decay of the early spin polarization vector while accelerating the decay of the later spin polarization vector. Specifically, our simulations model the detailed process of how magnetic fields polarize quarks within the fireball by the average spin vector and reveal that quark interactions lead to an acceleration effect on the average spin, causing it to rapidly increase from zero before being rapidly destroyed. Notably, the induced magnetic field in the fireball has an incomplete electromagnetic response effect, and its increase in the opposite direction of the external magnetic field decaying has a delay effect.
Two-pion interferometry for partially coherent sources in relativistic heavy-ion collisions in a multiphase transport model

We perform two-pion Hanbury Brown-Twiss (HBT) interferometry for the partially coherent pion-emitting sources in relativistic heavy-ion collisions, using a multi-phase transport (AMPT) model. A longitudinal coherent emission length, as well as a transverse coherent emission length, are introduced to the pion generation coordinates in calculating the HBT correlation functions of the partially coherent sources. We compare the model results with and without coherent emission conditions with experimental data in Au-Au collisions at center-of-mass energy $\sqrt{s_{NN}}=$200 GeV, and in Pb-Pb collisions at center-of-mass energy $\sqrt{s_{NN}}=$2.76 TeV, and find that the HBT results of the partially coherent sources are closer to the experimental data than those of chaotic sources.