Miracle-dz/UniFAR-FTUs huggingface dataset:
Measurement of the 
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The $^{18}$Ne($\alpha,p$)$^{21}$Na reaction plays a significant role in Type-I X-ray bursts. It is a major path in the breakout from the hot-CNO cycles to the synthesis of heavier elements in the $\alpha p$-- and $rp$-processes. An experiment to determine the cross section of this reaction was performed with the ANASEN active-target detector system, determining the cross section at energies between 2.5 and 4 MeV in the center-of-mass frame. The measured cross sections for reactions populating the ground state in $^{21}$Na are consistent with results obtained from the time-inverse reaction, but significantly lower than the previously published experimental data of direct measurements. The total cross sections are also compared with those derived from indirect methods and statistical-model calculations. This experiment establishes a new experimental data set on the excitation function of the $^{18}$Ne($\alpha,p$)$^{21}$Na reaction, revealing the significance of the excited states' contributions to the total reaction cross section and allowing to separate the contribution of the $(\alpha,2p)$ reaction. The impact of the measured cross section on thermal reaction rates is discussed.
On the Evidence for a Common-spectrum Process in the Search for the Nanohertz Gravitational-wave Background with the Parkes Pulsar Timing Array

A nanohertz-frequency stochastic gravitational-wave background can potentially be detected through the precise timing of an array of millisecond pulsars. This background produces low-frequency noise in the pulse arrival times that would have a characteristic spectrum common to all pulsars and a well-defined spatial correlation. Recently the North American Nanohertz Observatory for Gravitational Waves collaboration (NANOGrav) found evidence for the common-spectrum component in their 12.5 yr data set. Here we report on a search for the background using the second data release of the Parkes Pulsar Timing Array. If we are forced to choose between the two NANOGrav models—one with a common-spectrum process and one without—we find strong support for the common-spectrum process. However, in this paper, we consider the possibility that the analysis suffers from model misspecification. In particular, we present simulated data sets that contain noise with distinctive spectra but show strong evidence for a common-spectrum process under the standard assumptions. The Parkes data show no significant evidence for, or against, the spatially correlated Hellings–Downs signature of the gravitational-wave background. Assuming we did observe the process underlying the spatially uncorrelated component of the background, we infer its amplitude to be A=2.2−0.3+0.4×10−15 in units of gravitational-wave strain at a frequency of 1 yr−1. Extensions and combinations of existing and new data sets will improve the prospects of identifying spatial correlations that are necessary to claim a detection of the gravitational-wave background.
Changes in Preferential Flow Path Distribution and Its Affecting Factors in Southwest China

Abstract Preferential flow is important in solute transport in the soil, and it indirectly affects the quality of the groundwater. The objectives of the present study were to investigate the distribution characteristics of preferential flow paths under different land-use types (forestland, shrubland, and farmland) and to determine the factors that affect the formation of these paths. Dye tracer experiments were conducted at six sites covering the three land-use types. The relationship of the preferential flow paths to the properties of the soil, root length per soil volume, root holes, and root surface area was analyzed using a partial correlation method. The results show dye coverage of greater than 50% at a soil depth of 0 to 10 cm and dye coverage of less than 30% below a depth of 20 cm in all of the land-use types. The vertical distribution differed widely in the various land-use types. Shrubland and farmland had more preferential flow paths in the topsoil compared with forestland, in contrast to the conditions in the deeper soil layers. The soil chemical properties and the saturated hydraulic conductivity in the preferential flow paths were quite different from those in the soil matrix. The soil organic matter content was approximately 5% to 20% higher in the preferential flow paths than in the soil matrix. The average value of the saturated hydraulic conductivity was 41.3 mm min−1 in the preferential flow paths compared with 21.4 mm min−1 in the soil matrix. The percentage of preferential flow paths in the soil was significantly affected by roots with a diameter of less than 5 mm, root holes, and the root surface area. These findings suggest that land use is significant in the distribution of preferential flow paths, and root characteristics are important in the formation of preferential flow paths.
Operator spectrum of nonrelativistic CFTs at large charge

We extend and clarify the large-charge expansion of the conformal dimension $\Delta_Q$ of the lowest operator of charge $Q$ in nonrelativistic CFTs using the state-operator correspondence. The latter requires coupling the theory to an external harmonic trap that confines the particles to a spherical cloud, at the edge of which the effective theory breaks down and leads to divergences. Only recently has this issue been overcome by constructing appropriate counterterms at the edge of the cloud in arXiv:2010.07967. In this note, we extend these results by systematically analyzing the degree of divergence of operators in the effective action and show that there always exist appropriate edge counterterms that make the final contributions to $\Delta_Q$ finite. On the other side of the correspondence, this also provides new corrections to the Thomas-Fermi approximation of the unitary Fermi gas, and we comment on their relevance for ultracold atom physics.
Contextual Transformer Networks for Visual Recognition

Transformer with self-attention has led to the revolutionizing of NLP field, and recently inspires the emergence of Transformer-style architecture design with competitive results in numerous CV tasks. Nevertheless, most of existing designs directly employ self-attention over a 2D feature map to obtain the attention matrix based on pairs of isolated queries and keys, but leave the rich contexts among neighbor keys under-exploited. Here we design a novel Transformer-style module, i.e., Contextual Transformer (CoT) block, for visual recognition. It fully capitalizes on the contextual information among input keys to guide the learning of dynamic attention matrix and thus strengthens the capacity of visual representation. Technically, CoT block first contextually encodes input keys via $3\times3$ convolution, leading to a static contextual representation. We further concatenate the encoded keys with input queries to learn the dynamic multi-head attention matrix through two consecutive $1\times1$ convolutions. The learnt attention matrix is multiplied by values to achieve the dynamic contextual representation. The fusion of static and dynamic contextual representations are finally taken as outputs. Our CoT block can readily replace each $3\times3$ convolution in ResNet architectures, yielding a Transformer-style backbone named as Contextual Transformer Networks (CoTNet). Through extensive experiments over a wide range of applications, we validate the superiority of CoTNet as a stronger backbone.
Self-Repairing Neural Networks: Provable Safety for Deep Networks via Dynamic Repair

Neural networks are increasingly being deployed in contexts where safety is a critical concern. In this work, we propose a way to construct neural network classifiers that dynamically repair violations of non-relational safety constraints called safe ordering properties. Safe ordering properties relate requirements on the ordering of a network’s output indices to conditions on their input, and are sufficient to express most useful notions of non-relational safety for classifiers. Our approach is based on a novel self-repairing layer, which provably yields safe outputs regardless of the characteristics of its input. We compose this layer with an existing network to construct a self-repairing network (SR-Net), and show that in addition to providing safe outputs, the SR-Net is guaranteed to preserve the accuracy of the original network. Notably, our approach is independent of the size and architecture of the network being repaired, depending only on the specified property and the dimension of the network’s output; thus it is scalable to large state-of-the-art networks. We show that our approach can be implemented using vectorized computations that execute efficiently on a GPU, introducing run-time overhead of less than one millisecond on current hardware—even on large, widely-used networks containing hundreds of thousands of neurons and millions of parameters.
Co-Optimization of Design and Fabrication Plans for Carpentry

Past work on optimizing fabrication plans given a carpentry design can provide Pareto-optimal plans trading off between material waste, fabrication time, precision, and other considerations. However, when developing fabrication plans, experts rarely restrict to a single design, instead considering families of design variations, sometimes adjusting designs to simplify fabrication. Jointly exploring the design and fabrication plan spaces for each design is intractable using current techniques. We present a new approach to jointly optimize design and fabrication plans for carpentered objects. To make this bi-level optimization tractable, we adapt recent work from program synthesis based on equality graphs (e-graphs), which encode sets of equivalent programs. Our insight is that subproblems within our bi-level problem share significant substructures. By representing both designs and fabrication plans in a new bag of parts (BOP) e-graph, we amortize the cost of optimizing design components shared among multiple candidates. Even using BOP e-graphs, the optimization space grows quickly in practice. Hence, we also show how a feedback-guided search strategy dubbed Iterative Contraction and Expansion on E-graphs (ICEE) can keep the size of the e-graph manageable and direct the search towards promising candidates. We illustrate the advantages of our pipeline through examples from the carpentry domain.
Going Deeper into Semi-supervised Person Re-identification

Person re-identification is the challenging task of identifying a person across different camera views. Training a convolutional neural network (CNN) for this task requires annotating a large dataset, and hence, it involves the time-consuming manual matching of people across cameras. To reduce the need for labeled data, we focus on a semi-supervised approach that requires only a subset of the training data to be labeled. We conduct a comprehensive survey in the area of person re-identification with limited labels. Existing works in this realm are limited in the sense that they utilize features from multiple CNNs and require the number of identities in the unlabeled data to be known. To overcome these limitations, we propose to employ part-based features from a single CNN without requiring the knowledge of the label space (i.e., the number of identities). This makes our approach more suitable for practical scenarios, and it significantly reduces the need for computational resources. We also propose a PartMixUp loss that improves the discriminative ability of learned part-based features for pseudo-labeling in semi-supervised settings. Our method outperforms the state-of-the-art results on three large-scale person re-id datasets and achieves the same level of performance as fully supervised methods with only one-third of labeled identities.
Are in-person lectures beneﬁcial for all students? A Study of a Large Statistics Class

Over 1000 students over four semesters were given the option of taking an introductory statistics class either by in-person attendance in lectures, augmented by online recorded lectures, or by taking the same class without the in-person lectures. The all-online students did slightly better on computer-graded exams. The causal eﬀect of choosing only online lectures was estimated by adjusting for potential confounders using four methods. The four nearly identical point estimates remained positive but were small and not statistically signiﬁcant. No statistically signiﬁcant diﬀerences were found in prelimi-nary comparisons of eﬀects on females/males, U.S./non-U.S. citizens, freshmen/non-freshman, and lower-scoring/higher-scoring math ACT groups.
On the power of conditional independence testing under model-X

For testing conditional independence (CI) of a response Y and a predictor X given covariates Z , the recently introduced model-X (MX) framework has been the subject of active methodological research, especially in the context of MX knockoﬀs and their successful application to genome-wide association studies. In this paper, we study the power of MX CI tests, yielding quantitative explanations for empiri-cally observed phenomena and novel insights to guide the design of MX methodology. We show that any valid MX CI test must also be valid conditionally on Y, Z ; this conditioning allows us to reformulate the problem as testing a point null hypothesis involving the conditional distribution of X . The Neyman-Pearson lemma then implies that the conditional randomization test (CRT) based on a likelihood statistic is the most powerful MX CI test against a point alternative. We also obtain a related optimality result for MX knockoﬀs. Switching to an asymptotic framework with arbitrarily growing covariate dimension, we derive an expression for the limiting power of the CRT against local semiparametric alternatives in terms of the prediction error of the machine learning algorithm on which its test statistic is based. Finally, we exhibit a resampling-free test with uniform asymptotic Type-I error control under the assumption that only the ﬁrst two moments of X given Z are known , a signiﬁcant relaxation of the MX assumption.
Genetic, biochemical and histopathological evaluations of thymoquinone on male reproduction system damaged by paclitaxel in Wistar rats

This study was aimed to evaluate therapeutic effects of thymoquinone on male reproductive damages induced by paclitaxel. Forty‐eight male rats were divided; control, paclitaxel (4 mg/kg), paclitaxel + thymoquinone (1.25, 2.5 and 5 mg/kg) and thymoquinone (1.25, 2.5 and 5 mg/kg). Paclitaxel and thymoquinone were administrated intraperitoneally for 4 and 14 days respectively. Then, the testes were removed for H&E staining, sperm parameters and apoptotic genes expression assessments. Serum levels of nitric oxide, total antioxidant capacity and testosterone were evaluated, and sperm DNA fragmentation was assessed. Paclitaxel significantly (p < .05) increased nitric oxide, decreased total antioxidant capacity and reduced testosterone levels than control group. Sperm motility, viability and count were significantly (p < .05) reduced in paclitaxel group than control. Co‐administration of thymoquinone + paclitaxel caused decreased levels of nitric oxide and increased total antioxidant capacity, testosterone levels and reproductive parameters than paclitaxel group significantly (p < .05). Paclitaxel significantly (p < .05) increased caspase‐3 and p‐53 and decreased Bcl‐2 genes expression than control. Sperm DNA fragmentation index was also increased significantly (p < .05) in paclitaxel group than control, and this value was decreased in whole doses of paclitaxel + thymoquinone groups than paclitaxel. Thymoquinone can alleviate the side effects of paclitaxel on the male reproductive system.
A quinoxaline-based compound ameliorates bone loss in ovariectomized mice

DMB (6,7-dichloro-2-methylsulfonyl-3-Ntert-butylaminoquinoxaline) is a quinoxaline-based compound that has been investigated as a glucagon-like peptide-1 receptor (GLP-1R) agonist. To clarify anti-osteoporosis effect of DMB, an osteoporotic mice model was established by ovariectomy (OVX) operation. The OVX mice were given intraperitoneally DMB, exendin-4 (EX-4), or 17β-estradiol (E2) for two months. Then bone mass and structure, and bone morphometric parameters were examined by micro-CT. Weight gain and food consumption, bone turnover markers, and biomechanical strength of the femur were tested, and bone histomorphometry was analyzed. The food intake and weight gain was obviously reduced by E2 or EX-4, but not DMB. However, DMB or EX-4 treatment obviously inhibited skeletal deterioration and enhanced bone strength. The improvement involved in the increased osteoblast number and level of bone formation markers, and reduced osteoclasts number and level of bone resorption markers. In addition, DMB was found to stimulate osteoblastogenesis-related marker gene expression. These results demonstrated that DMB ameliorated bone loss mainly via induction of bone formation, which suggests that the small molecule compound might be applied to the management of postmenopausal osteoporosis.
Predictors of adverse pregnancy outcome in a cohort of women with systemic lupus erythematosus in Malaysia.

INTRODUCTION Pregnancy in women with systemic lupus erythematosus (SLE) is known to be associated with adverse pregnancy outcomes (APO). We aimed to determine the frequency of APO, the associated variables and predictors. MATERIALS AND METHODS This retrospective study included all pregnancies seen at the SLE Clinic, Kuala Lumpur Hospital from January 2008 to May 2020. Maternal outcomes included SLE flare during pregnancy, preeclampsia and eclampsia. Foetal outcomes included foetal loss, preterm birth and small-for-gestational age (SGA) neonates. Clinical and laboratory variables were examined. Variables from univariate analysis were entered into logistic regression model. Odds ratio and 95% confidence interval were reported. RESULTS Of the 131 pregnancies, 106 (80.9%) were live births. Twenty-six (24.5%) babies were born preterm and 35 (33%) neonates were SGA. Twenty-four (18.3%) women had disease flare during pregnancy, with the majority (22/24) being mild to moderate flares. Four women experienced preeclampsia while none had eclampsia. Predictors of adverse maternal outcomes included high SLEDAI-2K score, proteinuria and hypocomplementemia within 6 months before conception and during pregnancy; history of lupus nephritis (LN), pre-existing hypertension, antiphospholipid syndrome (APS), antiphospholipid antibodies, anti-Ro antibody and anti-RNP antibody. Predictors of adverse foetal outcomes comprised APS, preeclampsia, anti-Sm antibody, history of neuropsychiatric systemic lupus erythematosus (NPSLE) and azathioprine use. CONCLUSION Pregnancy in SLE women is best deferred until disease activity is in remission for at least 6 months before conception. A history of LN is associated with a 3-fold risk of renal flare during pregnancy. Haematological abnormalities are rare in disease flare during pregnancy.
Repositioning Chairs in the Diagnosis and Treatment of Benign Paroxysmal Positional Vertigo - A Systematic Review

Multi-axial repositioning chairs such as the TRV chair and the Epley Omniax Rotator (EO) are newer alternatives in the treatment of complex and recurrent cases of the common peripheral vertigo disorder, benign paroxysmal positional vertigo (BPPV). The objective of this systematic review is to collect and synthesize current knowledge on the clinical characteristics of repositioning chairs for treatment of BPPV. A systematic search of the PubMed and EmBase databases was conducted and data regarding clinical characteristics were extracted from both retrospective and prospective studies, and a qualitative synthesis was made. Of 36 unique publications, 9 studies were considered eligible, containing data from 3383 subjects. No randomized controlled trials were found. The included studies were found to have a high risk of bias and the overall quality of evidence was low. The type of referred patients and follow-up periods varied. Recurrence rates varied between 11% and 27.9%. Incidence of rarer types of BPPV was higher in the included studies than previous estimates. The rate of symptom relief was high, and clinical outcomes were similar between posterior canal BPPV (p-BPPV) and non-P BPPV. The included studies show repositioning chairs to be a safe and effective treatment for BPPV, especially for rarer forms and in patients unable to perform manual treatment. However, data from randomized controlled trials are needed to compare with conventional methods to examine their efficacy, to determine indications for treatment, and to decide whether they should be used as first-line treatment.
Selective Photocoagulation of Capillary Macroaneurysms by Navigated Focal Laser.

BACKGROUND AND OBJECTIVE To evaluate the anatomical and functional outcome of selective photocoagulation of capillary macroaneurysms (CMAs) by navigated focal laser. PATIENTS AND METHODS Consecutive patients with solitary or secondary CMAs greater than 150 mm in diameter were included in this analysis. All patients were treated with navigated focal laser and received multimodal imaging. RESULTS Seventeen eyes of 17 patients were retrospectively analyzed. Navigated laser photocoagulation of the CMAs successfully occluded 100% of the CMAs, inducing significative improvement in best-corrected visual acuity at 3 (P = .002) and 6 months (P = .001) and a decrease in central macular thickness (CMT) at 3 (P = .0004) and 6 months (P = .0004). CONCLUSIONS Solitary or secondary CMAs arising from retinal capillaries are candidates for navigated laser treatment. Navigated focal treatment was able to close all CMAs in this series with an improvement in vision and CMT. [Ophthalmic Surg Lasers Imaging Retina. 2021;52:366-373. ].
Genome‐environment association methods comparison supports omnigenic adaptation to ecological niche in malaria vector mosquitoes

The concept of a fundamental ecological niche is central to questions of geographic distribution, population demography, species conservation, and evolutionary potential. However, robust inference of genomic regions associated with evolutionary adaptation to particular environmental conditions remains difficult due to the myriad of potential confounding processes that can generate heterogeneous patterns of variation across the genome. Here, we interrogate the potential role of genome environment association (GEA) testing as an initial step in building an understanding of the genetic basis of ecological niche. We leverage publicly available genomic data from the Anopheles gambiae 1000 Genomes (Ag1000g) Consortium to test the ability of multiple analytically unique GEA methods to handle confounding patterns of genetic variation, control false positive rates, and discern associations with broadly relevant climate variables from random allele frequency patterns throughout the genome. We found evidence supporting the ability of commonly implemented GEA methods to account for confounding patterns of spatial and genetic variation, and control false positive rates. However, we fail to find evidence supporting the ability of GEA tests to reject signals of adaptation to randomly simulated environmental variables, indicating that discerning between true signals of genome environment adaptation and genome environment correlations resulting from alternative evolutionary processes, remains challenging. Because signals of environmental adaptation are so diffuse and confounded throughout the genome, we argue that genomic adaptation to ecological niche is likely best understood under an omnigenic model wherein highly interconnected, genome‐wide gene regulatory networks shape genomic adaptation to key environmental conditions.