Miracle-dz/UniFAR-FTUs huggingface dataset:
Endovascular Treatment for Acute Basilar Artery Occlusion: A Fragility Index Meta-Analysis

Introduction: High-quality evidence regarding the use of endovascular treatment (EVT) in patients with acute basilar artery occlusion (BAO) has been provided by recently completed randomized controlled clinical trials (RCTs). Methods: We conducted a systematic review and meta-analysis including all available RCTs that investigated efficacy and safety of EVT in addition to best medical treatment (BMT) versus BMT alone for BAO. The random-effects model was used, while the fragility index (FI) was calculated for dichotomous outcomes of interest. Results: Four RCTs were included comprising a total of 988 patients with acute BAO (mean age: 65.6 years, 70% men, median NIHSS: 24, 39% pretreatment with intravenous thrombolysis). EVT was related to higher likelihood of good functional outcome (RR: 1.54; 95% CI: 1.16–2.05; I2 = 60%), functional independence (RR: 1.83; 95% CI: 1.08–3.08; I2 = 79%) and reduced disability at 3 months (adjusted common OR: 1.96; 95% CI: 1.26–3.05; I2 = 59%) compared to BMT alone. Despite that EVT was associated with a higher risk for symptomatic intracranial hemorrhage (RR: 7.78; 95% CI: 2.36–25.61; I2 = 0%) and any intracranial hemorrhage (RR: 2.85; 95% CI: 1.50–5.44; I2 = 16%), mortality at 3 months was lower among patients that received EVT plus BMT versus BMT alone (RR: 0.76; 95% CI: 0.65–0.89; I2 = 0%). However, sufficient robustness was not evident in any of the reported associations (FI < 10) including the overall effect regarding the primary outcome. The former associations were predominantly driven by RCTs with recruitment limited in China. Conclusions: EVT combined with BMT is associated with a higher likelihood of achieving good functional outcomes and a lower risk of death at 3 months compared to BMT alone, despite the higher risk of sICH. An individual-patient data meta-analysis is warranted to uncover and adjust for potential sources of heterogeneity and to provide further insight.
Dependence of Monocrystalline Sapphire Dicing on Crystal Orientation Using Picosecond Laser Bessel Beams

Dicing is a critical step in the manufacturing process for the application of sapphire. In this work, the dependence of sapphire dicing on crystal orientation using picosecond Bessel laser beam drilling combined with mechanical cleavage was studied. By using the above method, linear cleaving with on debris and zero tapers was realized for the A1, A2, C1, C2, and M1 orientations, except for the M2 orientation. The experimental results indicated that characteristics of Bessel beam-drilled microholes, fracture loads, and fracture sections of sapphire sheets were strongly dependent on crystal orientation. No cracks were generated around the micro holes when laser scanned along the A2 and M2 orientations, and the corresponding average fracture loads were large, 12.18 N and 13.57 N, respectively. While along the A1, C1, C2, and M1 orientations, laser-induced cracks extended along the laser scanning direction, resulting in a significant reduction in fracture load. Furthermore, the fracture surfaces were relatively uniform for A1, C1, and C2 orientations but uneven for A2 and M1 orientations, with a surface roughness of about 1120 nm. In addition, curvilinear dicing without debris or taper was achieved to demonstrate the feasibility of Bessel beams.
Association between Genotype and the Glycemic Response to an Oral Glucose Tolerance Test: A Systematic Review

The inter-individual variability of metabolic response to foods may be partly due to genetic variation. This systematic review aims to assess the associations between genetic variants and glucose response to an oral glucose tolerance test (OGTT). Three databases (PubMed, Web of Science, Embase) were searched for keywords in the field of genetics, OGTT, and metabolic response (PROSPERO: CRD42021231203). Inclusion criteria were available data on single nucleotide polymorphisms (SNPs) and glucose area under the curve (gAUC) in a healthy study cohort. In total, 33,219 records were identified, of which 139 reports met the inclusion criteria. This narrative synthesis focused on 49 reports describing gene loci for which several reports were available. An association between SNPs and the gAUC was described for 13 gene loci with 53 different SNPs. Three gene loci were mostly investigated: transcription factor 7 like 2 (TCF7L2), peroxisome proliferator-activated receptor gamma (PPARγ), and potassium inwardly rectifying channel subfamily J member 11 (KCNJ11). In most reports, the associations were not significant or single findings were not replicated. No robust evidence for an association between SNPs and gAUC after an OGTT in healthy persons was found across the identified studies. Future studies should investigate the effect of polygenic risk scores on postprandial glucose levels.
Antibody Response to the SARS-CoV-2 Spike and Nucleocapsid Proteins in Patients with Different COVID-19 Clinical Profiles

The first case of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), in Brazil was diagnosed on February 26, 2020. Due to the important epidemiological impact of COVID-19, the present study aimed to analyze the specificity of IgG antibody responses to the S1, S2 and N proteins of SARS-CoV-2 in different COVID-19 clinical profiles. This study enrolled 136 individuals who were diagnosed with or without COVID-19 based on clinical findings and laboratory results and classified as asymptomatic or as having mild, moderate or severe disease. Data collection was performed through a semistructured questionnaire to obtain demographic information and main clinical manifestations. IgG antibody responses to the S1 and S2 subunits of the spike (S) protein and the nucleocapsid (N) protein were evaluated using an enzyme-linked immunosorbent assay (ELISA) according to the manufacturer’s instructions. The results showed that among the participants, 87.5% (119/136) exhibited IgG responses to the S1 subunit and 88.25% (120/136) to N. Conversely, only 14.44% of the subjects (21/136) displayed S2 subunit responses. When analyzing the IgG antibody response while considering the different proteins of the virus, patients with severe disease had significantly higher antibody responses to N and S1 than asymptomatic individuals (p ≤ 0.0001), whereas most of the participants had low antibody titers against the S2 subunit. In addition, individuals with long COVID-19 showed a greater IgG response profile than those with symptomatology of a short duration. Based on the results of this study, it is concluded that levels of IgG antibodies may be related to the clinical evolution of COVID-19, with high levels of IgG antibodies against S1 and N in severe cases and in individuals with long COVID-19.
Deep-neural-network approach to solving the 
ab initio
 nuclear structure problem

Predicting the structure of quantum many-body systems from the first principles of quantum mechanics is a common challenge in physics, chemistry, and material science. Deep machine learning has proven to be a powerful tool for solving condensed matter and chemistry problems, while for atomic nuclei it is still quite challenging because of the complicated nucleon-nucleon interactions, which strongly couple the spatial, spin, and isospin degrees of freedom. By combining essential physics of the nuclear wave functions and the strong expressive power of artificial neural networks, we develop FeynmanNet, a deep-learning variational quantum Monte Carlo approach for \emph{ab initio} nuclear structure. We show that FeynmanNet can provide very accurate solutions of ground-state energies and wave functions for $^4$He, $^6$Li, and even up to $^{16}$O as emerging from the leading-order and next-to-leading-order Hamiltonians of pionless effective field theory. Compared to the conventional diffusion Monte Carlo approaches, which suffer from the severe inherent fermion-sign problem, FeynmanNet reaches such a high accuracy in a variational way and scales polynomially with the number of nucleons. Therefore, it paves the way to a highly accurate and efficient \emph{ab initio} method for predicting nuclear properties based on the realistic interactions between nucleons.
Schrödinger group on Zhidkov spaces

We consider the Cauchy problem for nonlinear Schrodinger equations on R with non zero boundary condition at infinity, a situation which occurs in stability studies of dark solitons. We prove that the Schrodinger operator generates a group on Zhidkov spaces X(R) for k > n/2, and that the Cauchy problem for NLS is locally well-posed on the same Zhidkov spaces. We justify the conservation of classical invariants which implies in some cases the global well-posedness of the Cauchy problem.
THE DISTRIBUTION OF ABSORBED ENERGY FROM A POINT BETA SOURCE

The distribution of absorbed energy/g (dose) around a point source in a homogeneous medium has been measured for a variety of beta emitters in air, argon, ethane, and expanded polystyrene. At short distances the dose falls off faster than 1/r2, contrary to the results of measurements in solids but in agreement with previous measurements in air for maximum beta energies below 1.6 MeV. Except at short distances, distributions in different media differ only by a constant scaling factor on distance (mg/cm2) that is the same within ± 1% for all beta energies considered, but that is not proportional to electron density. Except close to the end of the range, the absolute doses calculated from Spencer's numerical solutions of the transport equation agree with the measured values within about ± 4%, for maximum beta energies from 0.16 to 3.58 MeV and for a wide variety of spectral shapes. The calculations predict correctly the observed variation of attenuation with the atomic number of the medium.
Estimating Effect Size Under Publication Bias: Small Sample Properties and Robustness of a Random Effects Selection Model

When there is publication bias, studies yielding large p values, and hence small effect estimates, are less likely to be published, which leads to biased estimates of effects in meta-analysis. We investigate a selection model based on one-tailed p values in the context of a random effects model. The procedure both models the selection process and corrects for the consequences of selection on estimates of the mean and variance of effect parameters. A test of the statistical significance of selection is also provided. The small sample properties of the method are evaluated by means of simulations, and the asymptotic theory is found to be reasonably accurate under correct model specification and plausible conditions. The method substantially reduces bias due to selection when model specification is correct, but the variance of estimates is increased; thus mean squared error is reduced only when selection produces substantial bias. The robustness of the method to violations of assumptions about the form of the distribution of the random effects is also investigated via simulation, and the model-corrected estimates of the mean effect are generally found to be much less biased than the uncorrected estimates. The significance test for selection bias, however, is found to be highly nonrobust, rejecting at up to 10 times the nominal rate when there is no selection but the distribution of the effects is incorrectly specified.
Two-dimensional numerical investigation of film cooling by a cool jet injected at various angles for different blowing ratios

This paper presents the thermal and flow characteristics of a cold transverse jet, injected at five different angles (α = 30°, 45°, 60°, 75°, and 90°) into a hot crossflow with four different blowing ratios (M = 0.1, 0.3, 0.5, and 0.8). Three turbulence models, namely, standard k−∊, renormalization group (RNG) k−∊, and realizable k−∊ are tested for obtaining the accurate turbulence model to predict the effectiveness of film cooling. The tested turbulence models were compared with available experimental data in the literature. The results evinced that the RNG k−∊ turbulence model is the most appropriate among the three. It is also observed that maximum cooling efficiency is obtained at α = 30° and M = 0.8.
Predictive Bayesian Model Selection

SYNOPTIC ABSTRACT We investigate the problem of evaluating the goodness of the predictive distributions of Bayesian models. Recently, deviance information criteria (DIC) has been extensively employed in various study areas to evaluate the Bayesian models, thanks to its simplicity of calculation from the posterior simulation outputs. Unfortunately, it is known that DIC often selects overfitted models. In this paper, we develop a new criterion which can be calculated easily from posterior outputs under the model misspecification situation. The proposed criterion is developed as an estimator of the posterior mean of the expected likelihood and is robust to improper priors. Monte Carlo simulations are conducted to investigate the properties of the proposed criteria.
Promoting Recovery from Disasters, Pandemics, and Trauma: A Systematic Review of Brief Psychological Interventions to Reduce Distress in Adults, Children, and Adolescents

A substantial number of survivors of disasters, pandemics, and other severe stressors develop persistent distress that impairs mental health and well-being. However, only a few brief psychological interventions target distress or subclinical symptoms. This systematic review aimed to identify and describe brief psychological interventions to reduce distress or subclinical symptoms in survivors of disasters, pandemics, and other severe stressors. Based on a systematic literature search (MEDLINE, PsycINFO, PSYNDEX, PTSDpubs, and Web of Science), we reviewed published studies and study protocols on self-help, psychosocial support, or brief psychotherapeutic interventions to reduce distress and/or subclinical symptoms following natural hazards and man-made disasters, pandemics, or other traumatic events. We included 27 published studies or study protocols (n = 15 RCTs, n = 3 controlled pre–post studies, and n = 9 uncontrolled pre–post studies) describing 22 interventions. We found evidence for reducing psychological distress and/or subclinical symptoms in 9 out of 15 RCTs, 2 out of 3 controlled pre–post studies, and 9 out of 9 uncontrolled pre–post studies. One RCT provided evidence of increasing well-being. Innovative brief interventions have been developed to reduce distress and/or subclinical symptoms that have an emerging evidence base.
Robust stability and high-gain compensation of a two-degree-of-freedom servosystem

In order to reject the steady-state tracking error, it is common to introduce integral compensators in servosystems for constant reference signals. However, the mathematical model of the plant is exact and no disturbance input exists, the integral compensation is not necessary. From this point of view, a two-degree-of-freedom (2DOF) servosystem has been proposed, in which the integral compensation is effective only when there is a modeling error or a disturbance input. The present paper considers robust stability and high-gain compensation of this 2DOF servosystem. A condition on uncertainties in the plant model is presented, under which the servosystem is robustly stable independent of the gain of the integral compensator. This result implies that if the plant uncertainty is in the allowable set defined by the condition, a high-gain integral compensation can be carried out preserving robust stability to accelerate the tracking response. The transient behavior attainable by the limit of the high-gain compensation is calculated using a singular perturbation approach.
Making Women Visible: How Gender Quotas Shape Global Attitudes toward Women in Politics

Abstract Since the 1990s, gender quotas have been celebrated for improving women’s equality. Yet their cross-national and longitudinal impact on attitudes toward female politicians and the mechanism through which this process occurs are not well understood. Using multilevel modeling on 87 nations, we examine how different types of quotas, with varied features and levels of strength, shape beliefs about women in politics. We give particular attention to the mechanism of visibility created by quotas in impacting attitudes. Results suggest that unlike quotas with features facilitating low visibility (i.e., weak quotas), those producing high visibility (i.e., robust quotas) significantly impact public approval of women in politics. However, the direction of this effect varies by quota type. Social context also matters. Robust quota effects—both positive and negative—are especially pronounced in democracies but are insignificant in nondemocracies. Limited differences by gender (men versus women) emerge. Theoretical and policy implications are discussed.
Summer Extreme Precipitation in Southern China from the Perspective of Moisture Static Energy

The extreme precipitation (EP) in the early- and late-rainy seasons in Southern China is investigated from the perspective of moist static energy (MSE). At the synoptic timescale, the EP is accompanied by the charge-discharge paradigm of the vertically integrated MSE (); the positive anomaly reaches the peak one day before EP and decreases quickly during the event. The charge-discharge paradigm of is dominated by the horizontal and vertical advection, respectively. However, synoptic systems responsible for the charge in the early- and late-rainy seasons are different due to the different horizontal distributions of climatological MSE in the lower troposphere caused by the northward migration of solar radiation and monsoon system. At the interannual timescale, more EP in the early-/late-rainy season is associated with the higher seasonal-mean that can be caused by the anomalous anticyclone/cyclone in the western North Pacific induced by the SST anomalies in the tropical Indian Ocean and central North Pacific/the tropical Pacific. The multi-model ensemble mean of CMIP6 models reproduces well the observed -EP relationship in both the historical and SSP5-8.5 runs. Moreover, the mean state of increases in the SSP5-8.5 compared to historical runs along with more frequent occurrence of EP events. Hence, can serve as a useful metric for studying EP in Southern China at various timescales.
Partial Denaturation of Double-Stranded DNA on Pristine Graphene under Physiological-like Conditions

Interactions between DNA and graphene are paramount for a wide range of applications, such as biosensing and nanoelectronics; nonetheless, the molecular details of such interactions remain largely unexplored. We employ atomically detailed molecular dynamics simulations with an enhanced sampling technique to investigate the adsorption and mobility of double-stranded DNA along the basal plane of graphene, in an electrolytic aqueous medium. The study focuses on physiologically relevant conditions, using a buffer of [NaCl] = 134 mM. DNA physisorption is shown to be fast and irreversible, leading to deformation and partial melting of the double helix as a result of π–π stacking between the terminal nucleobases and graphene. Denaturation occurs primarily at the termini, with ensemble averaged H-bond ratios of 47.8–62%; these can, however, reach a minimum of 15%. Transition between free-energy minima occurs via a thermodynamical pathway driving the nucleic acid from a radius of gyration of 1.5 nm to 1.35 nm. Mobility along the basal plane of graphene is dominant, accounting for ~90% of all centre-of-mass translation and revealing that the DNA’s apparent diffusivity is similar to diffusion along the endohedral volume of carbon nanotubes, but one order of magnitude faster than in other 2D materials, such as BC3 and C3N.
Potential Therapeutic Value of the STING Inhibitors

The stimulator of interferon genes (STING) is a critical protein in the activation of the immune system in response to DNA. It can participate the inflammatory response process by modulating the inflammation-preferred translation program through the STING-PKR-like endoplasmic reticulum kinase (PERK)-eIF2α pathway or by inducing the secretion of type I interferons (IFNs) and a variety of proinflammatory factors through the recruitment of TANK-binding kinase 1 (TBK1) and interferon regulatory factor 3 (IRF3) or the regulation of the nuclear factor kappa-B (NF-κB) pathway. Based on the structure, location, function, genotype, and regulatory mechanism of STING, this review summarizes the potential value of STING inhibitors in the prevention and treatment of infectious diseases, psoriasis, systemic lupus erythematosus, non-alcoholic fatty liver disease, and other inflammatory and autoimmune diseases.
Numerical investigation of light-wave localization in optical Fibonacci superlattices with symmetric internal structure

We study numerically the optical transmission of one-dimensional binary quasiperiodic dielectric multilayers, which are arranged in Fibonacci sequences along two opposite directions and possess a mirror symmetry. We find that the transmission coefficient is unity for all sequences studied at the central wavelength = 0, where 0 = 4nA (B)dA (B), with nA (B) and dA (B) being the index of refraction and thickness of two kinds of layer, respectively. As the number of layers in the sequence increases, more and more perfect transmission peaks appear. We observe a scaling of the transmission spectra with increasing sequence length. These phenomena will find applications in fabrication of multiwavelength narrow-band optical filters.
Roots, Litter, and Seasonal Drought Together Inhibit Plant Growth in the Herbaceous Layer in a Subtropical Moist Forest of Southwestern China

The mechanisms of the maintenance of plant diversity in forests have been extensively studied because of their ecological importance. The study of the regeneration and growth dynamics of herbaceous understory communities in forests is relatively more common than that of woody plant overstory and understory communities. To investigate which environmental factors (plant roots, forest litter, or both) control seedling survival, growth, and production in the herbaceous layer in the context of increasingly severe seasonal drought caused by global climate change, we performed a seedling growth experiment of the herbaceous layer influenced by the interaction of plant roots and forest litter through a manipulative complete block experiment, crossed with an irrigation experiment, in a montane subtropical moist evergreen broad-leaved forest of southwestern China. Within both the control and watered plots, we established four experimental subplots with plant roots and forest litter included (R+L+); plant roots included, but forest litter excluded (R+L−); plant roots excluded, but forest litter included (R−L+); and both plant roots and forest litter excluded (R−L−). After one year, the R+L+ treatment in the control plot had statistically less species richness and plant individuals, shorter mean and maximum seedling heights, and less dry biomass of plant seedlings than those in the other seven experimental treatments. Across all the experimental replicates, the pooled data showed that plant roots, forest litter, and seasonal drought, together, inhibited all the dependent herbaceous growth variables. Our study demonstrates how plant roots, forest litter, and seasonal drought synergistically regulate seedling establishment and the growth of the herbaceous layer in tropical and subtropical forest understory. This synergistic regulation changes plant physiological responses and forest evolution through controlling plant diversity and the individual richness of the herbaceous layer in the context of sustained global climate change.