Miracle-dz/UniFAR-FTUs huggingface dataset:
Title: Connectome Gradient Dysfunction in Major Depression and Its Association with Gene Expression Profiles

Background: Patients with major depressive disorder (MDD) exhibit concurrent deficits in sensory processing and high-order cognitive functions such as self-awareness and rumination. Connectome mapping studies have suggested a principal primary-to-transmodal gradient in functional brain networks, supporting the spectrum from sensation to cognition. However, whether this principal connectome gradient is disrupted in patients with MDD and how this disruption is associated with gene expression profiles remain unclear. Methods: Using a large cohort of resting-state functional magnetic resonance imaging data from 2,234 participants (1,150 patients with MDD and 1,084 healthy controls) recruited at 10 sites, we investigated MDD-related alterations in the principal connectome gradient. We further used Neurosynth and postmortem gene expression data to assess the cognitive functions and transcriptional profiles related to the gradient alterations in MDD, respectively. Results: Relative to controls, patients with MDD exhibited abnormal global topography of the principal primary-to-transmodal gradient, as indicated by reduced explanation ratio, gradient range, and gradient variation (Cohen’s d = -0.16~-0.21). Focal alterations of gradient scores were mostly in the primary systems involved in sensory processing and in the transmodal systems implicated in high-order cognition. The transcriptional profiles explained 53.9% of the spatial variance in the altered gradient patterns, with the most correlated genes enriched in transsynaptic signaling and calcium ion binding. Conclusions: These results highlight the dysfunction of the core connectome hierarchy in MDD and its linkage with gene expression profiles, providing insights into the neurobiological and molecular genetic underpinnings of sensory-cognitive deficits in this disorder.
The impact of paternal obesity on serum anti-müllerian hormone level and outcome of intracytoplasmic sperm injection in infertile couples

Objectives: The goal of our study was to investigate the effect of male body mass index on serum anti-mullerian hormone (AMH) and outcome of intracytoplasmic sperm injection (ICSI) (fertilization rate, cleavage rate, embryo quality, total embryos and pregnancy rate). Patients and methods: A prospective cohort study was carried on fifty-five infertile couples who encountered inclusion criteria. Blood samples were analysed for AMH. Semen samples were collected and examined according to World Health Organization ,1999. Weight and height measurements were performed and patients were divided by BMI into normal weight (BMI 18.5-24.9 Kg/m²,n=21), overweight (BMI 25-29.9Kg/m²,n=22) and obese(BMI>30Kg/m²,n=12). Results: A negative correlation was found between BMI and serum level of AMH(r=-0.507,p=0.001). Fertilization rate, cleavage rate ,total embryo and pregnancy rate were found to be not related to BMI while the good quality embryo was a significantly high in normal weight men compared to overweight and obese men(6.47±0.96, 3.77±0.66, 2.75±0.66). Sperm concentration was found significantly high in normal weight men compared to overweight and obese men(39.90±6.06 million /ml, 24.73±6.14million/ml, 7.42±1.73 million /ml). Progressive sperm motility was also high in normal weight than overweight and obese men(47.67±4.53, 30.82±4.16, 15.67±4.01). No significant difference was found in sperm morphology among study groups. Conclusion: Our findings suggest that BMI may have a negative effect on the serum AMH level and semen parameters with no effect on ICSI outcomes except for good quality embryo.
Demystifying Unsupervised Semantic Correspondence Estimation - Supplementary Material

We perform experiments with two different types of backbones models for our feature encoder Ψ . For the CNN, unless otherwise specified, we extract features from images resized to 384×384, and use the 1024 dimensional features from the conv3 layer of a ResNet-50 [5]. We use a ResNet-50 trained on Imagenet [12] as our supervised baseline, and MoCov3 [3] as our unsupervised CNN. For the Transformer, 8×8 patches from 224×224 images with stride 8 are used as input (similar to [1]) and we extract 736 dimensional features from 9th layer. We also investigate supervised and self-supervised trained backbones. The supervised and self-supervised CNNs are from [5] and [3] and the Transformer models are from [9] and [2] respectively. During training, we upsample feature maps to 64×64 via bilinear interpolation. For our projection head ρ, a single 1×1 2D convolution is trained and the dimension of the features is reduced to 256. During training, as in [4], we freeze the feature encoder Ψ . The projection head is trained for 50 epochs using Adam [7] optimizer with learning rate of 0.001. Unless stated otherwise, we report results using the standard PCK metric with α = 0.1 for direct comparison to other methods. For EQ, DVE and LEAD we set the temperature τ to 0.05 and 0.14 for CL as in described in their papers, and set τ1 to 0.2 and τ2 to 0.4 for ASYM. We provide an evaluation of different temperature values in the supplementary material.
swTVM: Exploring the Automated Compilation for Deep Learning on Sunway Architecture

The flourish of deep learning frameworks and hardware platforms has been demanding an efficient compiler that can shield the diversity in both software and hardware in order to provide application portability. Among the exiting deep learning compilers, TVM is well known for its efficiency in code generation and optimization across diverse hardware devices. In the meanwhile, the Sunway many-core processor renders itself as a competitive candidate for its attractive computational power in both scientific and deep learning applications. This paper combines the trends in these two directions. Specifically, we propose swTVM that extends the original TVM to support ahead-of-time compilation for architecture requiring cross-compilation such as Sunway. In addition, we leverage the architecture features during the compilation such as core group for massive parallelism, DMA for high bandwidth memory transfer and local device memory for data locality, in order to generate efficient code for deep learning application on Sunway. The experimental results show the ability of swTVM to automatically generate code for various deep neural network models on Sunway. The performance of automatically generated code for AlexNet and VGG-19 by swTVM achieves 6.71x and 2.45x speedup on average than hand-optimized OpenACC implementations on convolution and fully connected layers respectively. This work is the first attempt from the compiler perspective to bridge the gap of deep learning and high performance architecture particularly with productivity and efficiency in mind. We would like to open source the implementation so that more people can embrace the power of deep learning compiler and Sunway many-core processor.
Schrödinger operators with dynamically defined potentials

In this survey we discuss spectral and quantum dynamical properties of discrete one-dimensional Schrödinger operators whose potentials are obtained by real-valued sampling along the orbits of an ergodic invertible transformation. After an introductory part explaining basic spectral concepts and fundamental results, we present the general theory of such operators, and then provide an overview of known results for specific classes of potentials. Here we focus primarily on the cases of random and almost periodic potentials.
OBSERVABLE DEVIATIONS FROM HOMOGENEITY IN AN INHOMOGENEOUS UNIVERSE

How does inhomogeneity affect our interpretation of cosmological observations? It has long been wondered to what extent the observable properties of an inhomogeneous universe differ from those of a corresponding Friedmann–Lemaître–Robertson–Walker (FLRW) model, and how the inhomogeneities affect that correspondence. Here, we use numerical relativity to study the behavior of light beams traversing an inhomogeneous universe, and construct the resulting Hubble diagrams. The universe that emerges exhibits an average FLRW behavior, but inhomogeneous structures contribute to deviations in observables across the observer’s sky. We also investigate the relationship between angular diameter distance and the angular extent of a source, finding deviations that grow with source redshift. These departures from FLRW are important path-dependent effects, with implications for using real observables in an inhomogeneous universe such as our own.
Rigidity and absence of line fields for meromorphic and Ahlfors islands maps

Abstract In this paper, we give an elementary proof of the absence of invariant line fields on the conical Julia set of an analytic function of one variable. This proof applies not only to rational and transcendental meromorphic functions (where it was previously known), but even to the extremely general setting of Ahlfors islands maps as defined by Epstein. In fact, we prove a more general result on the absence of invariant differentials, measurable with respect to a conformal measure that is supported on the (unbranched) conical Julia set. This includes the study of cohomological equations for log ∣f′∣, which are relevant to a number of well-known rigidity questions. In particular, we prove the absence of continuous line fields on the Julia set of any transcendental entire function.
Socioeconomic status does not change decision-making in the treatment of distal radius fractures at a level 1 trauma center

Abstract Objectives: To compare operative rates, total hospital charges, and length of stay between different socioeconomic cohorts in treating distal radius fractures (DRFs). Design: A retrospective cohort study. Setting: Large public level 1 trauma center. Patients: A retrospective search of all trauma activations over a 7-year period (2013–2020) yielded 816 adult patients diagnosed with DRF. Patients were separated into cohorts of socioeconomic status based on 2010 US Census data and insurance status. Intervention: DRFs were treated either nonoperatively using closed reduction and splinting or operatively using open reduction and internal fixation, closed reduction percutaneous pinning, or external fixator application. Main Outcome Measurements: Operative rates of DRF, total hospital charges, and length of stay. Results: Patients who were uninsured or in the low-income socioeconomic cohort had no significant difference in operative rates, total hospital costs, or length of stay when compared with their respective insured or standard income groups. Younger patients and those with OTA/AO type C, bilateral, or open DRFs were more likely to undergo operative intervention. Conclusions: This study demonstrates that low socioeconomic status based on annual household income and insurance status was not associated with differences in operative rates on DRFs, length of stay, or total hospital charges. These results suggest that outcome disparities between groups may be caused by postoperative differences rather than treatment decision-making. Although this study investigates access to surgical care at a publicly funded level 1 trauma center, disparities may still exist in other models of care. Level of Evidence: Prognostic Level III.
Classical limit theorems and high entropy MIXMAX random number generator

We investigate the interrelation between the distribution of stochastic fluctuations of independent random variables in probability theory and the distribution of time averages in deterministic Anosov C-systems. On the one hand, in probability theory, our interest dwells on three basic topics: the laws of large numbers, the central limit theorem and the law of the iterated logarithm for sequences of real-valued random variables. On the other hand we have chaotic, uniformly hyperbolic Anosov C-systems defined on tori which have mixing of all orders and nonzero Kolmogorov entropy. These extraordinary ergodic properties of deterministic Anosov C-systems ensure that the above classical limit theorems for sums of independent random variables in probability theory are fulfilled by the time averages for the sequences generated by the C-systems. The MIXMAX generator of pseudorandom numbers represents the C-system for which the classical limit theorems are fulfilled.
Brain Metastases in EGFR- and ALK- Positive NSCLC: Outcomes of Central Nervous System-Penetrant Tyrosine Kinase Inhibitors Alone Versus in Combination With Radiation

Introduction: Management of central nervous system (CNS) metastases in patients with driver-mutated NSCLC has traditionally incorporated both tyrosine kinase inhibitors (TKIs) and intracranial radiation. Whether next generation, CNS-penetrant TKIs can be used alone without upfront radiation, however, remains unknown. This multi-institutional retrospective analysis aimed to compare outcomes in patients with EGFR- or ALK- positive NSCLC who received CNS-penetrant TKI therapy alone versus in combination with radiation for new or progressing intracranial metastases. Methods: Data were retrospectively collected from three academic institutions. Two treatment groups (CNS-pene-trant TKI measured from the date of initiation of CNS-penetrant TKI therapy. Results: A total of 147 patients were included (EGFR n ¼ 94, ALK n ¼ 52, both n ¼ 1). In patients receiving radiation, larger metastases, neurologic symptoms, and receipt of steroids were more common. There were no signi ﬁ cant differences between TKI and CNS radiation therapy plus TKI groups for any of the study outcomes, including time to progression (8.5 versus 6.9 mo, p ¼ 0.13 [EFGR] and 11.4 versus 13.4 mo, p ¼ 0.98 [ALK]), time to intracranial progression (14.8 versus 20.5 mo, p ¼ 0.51 [EGFR] and 18.1 versus 21.8 mo, p ¼ 0.65 [ALK]), or time to treatment failure (13.8 versus 8.6 mo, p ¼ 0.26 [EGFR] and 13.5 versus 23.2 mo, p ¼ 0.95 [ALK]). Conclusions: These results provide preliminary evidence that intracranial activity of CNS-penetrant TKIs may enable local radiation to be deferred in appropriately selected patients without negatively affecting progression.
PLIN: A Persistent Learned Index for Non-Volatile Memory with High Performance and Instant Recovery

Non-Volatile Memory (NVM) has emerged as an alternative to next-generation main memories. Although many tree indices have been proposed for NVM, they generally use B+-tree-like structures. To further improve the performance of NVM-aware indices, we consider integrating learned indexes into NVM. The challenges of such an integration are two fold: (1) existing NVM indices rely on small nodes to accelerate insertions with crash consistency, but learned indices use huge nodes to obtain a flat structure. (2) the node structure of learned indices is not NVM friendly, meaning that accessing a learned node will cause multiple NVM block misses. Thus, in this paper, we propose a new persistent learned index called PLIN. The novelty of PLIN lies in four aspects: an NVM-aware data placement strategy, locally unordered and globally ordered leaf nodes, a model copy mechanism, and a hierarchical insertion strategy. In addition, PLIN is proposed for the NVM-only architecture, which can support instant recovery. We also present optimistic concurrency control and fine-grained locking mechanisms to make PLIN scalable to concurrent requests. We conduct experiments on real persistent memory with various workloads and compare PLIN with APEX, PACtree, ROART, TLBtree, and Fast&Fair. The results show that PLIN achieves 2.08x higher insertion performance and 4.42x higher query performance than its competitors on average. Meanwhile, PLIN only needs ~30 μs to recover from a system crash.
Old and young stellar populations in DustPedia galaxies and their role in dust heating

Aims. Within the framework of the DustPedia project we investigate the properties of cosmic dust and its interaction with stellar radiation (originating from different stellar populations) for 814 galaxies in the nearby Universe, all observed by the Herschel Space Observatory. Methods. We take advantage of the widely used fitting code CIGALE, properly adapted to include the state-of-the-art dust model THEMIS. For comparison purposes, an estimation of the dust properties is provided by approximating the emission at far-infrared and sub-millimeter wavelengths with a modified blackbody. Using the DustPedia photometry we determine the physical properties of the galaxies, such as the dust and stellar mass, the star-formation rate, the bolometric luminosity, the unattenuated and the absorbed by dust stellar light, for both the old (> 200 Myr) and young (≤200 Myr) stellar populations. Results. We show how the mass of stars, dust, and atomic gas, as well as the star-formation rate and the dust temperature vary between galaxies of different morphologies and provide recipes to estimate these parameters given their Hubble stage (T). We find a mild correlation between the mass fraction of the small a-C(:H) grains with the specific star-formation rate. On average, young stars are very efficient in heating the dust, with absorption fractions reaching as high as ∼77% of the total unattenuated luminosity of this population. On the other hand, the maximum absorption fraction of old stars is ∼24%. Dust heating in early-type galaxies is mainly due to old stars, up to a level of ∼90%. Young stars progressively contribute more for “typical” spiral galaxies and they become the dominant source of dust heating for Sm-type and irregular galaxies, with ∼60% of their luminosity contributing to that purpose. Finally, we find a strong correlation of the dust heating fraction by young stars with morphology and the specific star-formation rate.
Lipid abnormalities in patient with chronic kidney disease: a cross sectional study

Introduction : Chronic Kidney disease (CKD) is a public health problem with an increasing incidence and prevalence, poor outcomes, and high cost. Renal disease, in early as well as advanced stages, is associated with abnormalities in lipoprotein metabolism. Dyslipidemia appears to be independently associated with increased progression rate of CKD in patients with kidney disease and with increased risk of graft loss after renal transplantation. This study was conducted to study the lipid abnormalities in CKD patients. Methodology: A hospital-based, observational, cross-sectional study was conducted among 89 patients admitted in the ward of Bir Hospital with the diagnosis of CKD. Data was collected using the structured pro-forma. Data was analyzed using SPSS version 16. Descriptive statistics (Frequency, mean and percentage) was used. Results: In this study the average value of total cholesterol (TC), triglyceride, low density lipoprotein (LDL) & high density lipoprotein (HDL) were 246.66±53.56, 215.78±80.70, 168.61±44.73, 35.77±5.26 respectively. In this study there is significant association between HDL, LDL, triglyceride (TG) & total cholesterol with smoking with p value of 0.001, 0.003, 0.001& 0.003048 respectively. Similarly there is also significant relationship between HDL, LDL, TG& total cholesterol with age with p value of 0.001, 0.048, 0.010 & 0.048 respectively. Conclusion : Hypertriglyceridemia and low HDL and LDL
Seroprevalence and Risk Factors Associated with Leishmania Infection in Dogs from Portugal

Canine leishmaniosis (CanL) caused by Leishmania infantum is an important zoonosis in southwestern European countries where this disease is endemic, and dogs, as domestic animals in close contact with humans, are the reservoir hosts for the parasite. In Portugal, CanL is of relevant veterinary concern. The previous national study revealed an overall seroprevalence of 6.3%. Since then, new prophylactic measures, such as vaccines, have been introduced in Europe. The aim of this study was to update seroprevalence for Leishmania infection and reassess risk factors in Portugal. A cross-sectional study was conducted from January–March 2021 with 1860 client-owned dogs from continental Portugal. A questionnaire and whole blood samples on filter paper were collected and a direct agglutination test was used to calculate anti-Leishmania antibody titres. True seroprevalence was 12.5% (95% CI 10.3–13.2%). Potential risk factors associated with L. infantum infection in dogs were age ≥ 2 years (aOR = 1.68, 95% CI 1.1–2.6) and residing in the interior regions of the country (aOR = 1.92, 95% CI 1.3–2.9) and non-use of repellents (aOR = 1.75, 95% CI 1.2–2.5). The key to controlling CanL and its impact on Public Health in endemic areas lies in continuous implementation of prophylactic measures, through the correct use of repellents/insecticides and vaccines and early detection and monitoring of infected dogs.
Nuclear activity versus star formation: emission-line diagnostics at ultraviolet and optical wavelengths

In the context of observations of the rest-frame ultraviolet and optical emission from distant galaxies, we explore the emission-line properties of photoionization models of active and inactive galaxies. Our aim is to identify new line-ratio diagnostics to discriminate between gas photoionization by active galactic nuclei (AGN) and star formation. We use a standard photoionization code to compute the emission from AGN narrow-line regions and compare this with calculations of the nebular emission from star-forming galaxies achieved using the same code. We confirm the appropriateness of widely used optical spectral diagnostics of nuclear activity versus star formation and explore new diagnostics at ultraviolet wavelengths. We find that combinations of a collisionally excited metal line or line multiplet, such as CIV 1548,1551, OIII]1661,1666, NIII]1750, [SiIII]1883+[SiIII]1892 and [CIII]1907+CIII]1909, with the HeII 1640 recombination line are individually good discriminants of the nature of the ionizing source. Diagrams involving at least 3 of these lines allow an even more stringent distinction between active and inactive galaxies, as well as valuable constraints on interstellar gas parameters and the shape of the ionizing radiation. Several line ratios involving Ne-based emission lines, such as [NeIV]2424, [NeIII]3343 and [NeV]3426, are also good diagnostics of nuclear activity. Our results provide a comprehensive framework to identify the sources of photoionization and physical conditions of the ionized gas from the ultraviolet and optical nebular emission from galaxies. This will be particularly useful to interpret observations of high-redshift galaxies with future facilities, such as the James Webb Space Telescope and extremely large ground-based telescopes.
A Note on Statistical Consistency of Numerical Integrators for Multiscale Dynamics

A minimal requirement for simulating multi-scale systems is to reproduce the statistical behavior of the slow variables. In particular, a good numerical method should accurately aproximate the probability density function of the continuous-time slow variables. In this note we use results from homogenization and from backward error analysis to quantify how errors of time integrators affect the mean behavior of trajectories. We show that numerical simulations converge, not to the exact probability density function (pdf) of the homogenized multi-scale system, but rather to that of the homogenized modified equations following from backward error analysis. Using homogenization theory we find that the observed statistical bias is exacerbated for multi-scale systems driven by fast chaotic dynamics that decorrelate insufficiently rapidly. This suggests that to resolve the statistical behavior of trajectories in certain multi-scale systems solvers of sufficiently high order are necessary. Alternatively, backward error analysis suggests the form of an amended vector field that corrects the lowest order bias in Euler's method. The resulting scheme, a second order Taylor method, avoids any statistical drift bias. We corroborate our analysis with a numerical example.