Miracle-dz/UniFAR-FTUs huggingface dataset:
Serum testosterone acts as a prognostic indicator in polycystic ovary syndrome‐associated kidney injury

Polycystic ovary syndrome (PCOS) is closely related with the onset and development of metabolic abnormalities. However, the correlation between PCOS and kidney injury has not been clarified, and the underlying mechanism remains unknown. Herein, we performed a prospective survey in 55 PCOS and 69 healthy participants. Furthermore, the correlation analyses between serum testosterone and renal functional manifestations of patients and healthy subjects, including urinary albumin to creatinine ratio (UACR), urinary κ‐light chains (KapU), urinary λ‐light chains (LamU), urinary α1‐microglobulin (α1‐MU), and urinary β2‐microglobulin (β2‐MU), were analyzed. Compared with that in normal subjects, the levels of serum testosterone and UACR were significantly higher in PCOS patients. Serum testosterone is significantly correlated with the disease severity of PCOS. Although urinary excretions of KapU, LamU, α1‐MU, and β2‐MU did not increase in PCOS patients, they had a significantly positive correlation with the extent of serum testosterone in PCOS patients. IN vitro, primary cultured human ovary granulosa cells (GCs) were isolated from the follicular fluid (FF) extracting from PCOS patients and controls. FF, especially which extracted from PCOS patients with a high expression of serum testosterone, significantly induced cell apoptosis and inflammation in human GCs. To examine the communication between PCOS and kidney injury, a human proximal tubular epithelial cell line (HKC‐8) was cultured and administered FF. Interestingly, FF from PCOS patients with a higher level of serum testosterone induced fibrotic lesions in HKC‐8 cells. These data suggest serum testosterone plays a critical role in PCOS and PCOS‐associated kidney injury. Serum testosterone may serve as a promising indicator for kidney fibrotic injury outcomes in PCOS patients.
USING LIDAR DATA TO QUANTIFY FOREST STRUCTURAL HABITAT VARIABLES IMPORTANT TO FISHERS AND MARTENS

Fishers (Pekania pennanti), martens (Martes americana), and many other wildlife species rely on three-dimensional structural habitat characteristics to provide essential resources. Spatiallycontinuous data on fine-scale structural habitat features are generally not available across large landscapes because passive remote sensing systems are not capable of measuring threedimensional characteristics and because it is financially and logistically challenging to collect field-data continuously across the landscape. Light detection and ranging (LiDAR) is an active remote sensing technology capable of providing accurate, high-resolution data on threedimensional vegetation structure across large spatial extents. Many past studies have demonstrated that LiDAR data can be used to map coarseand fine-scale habitat characteristics at the scale of individual trees, field plots, or forest stands. However, most research has focused on forestry applications, and relatively few studies have focused on modeling structural variables that serve as basic wildlife habitat indicators.
UNSUPERVISED DEEP TRANSFER LEARNING APPROACH TO PERSON RE-IDENTIFICATION 1

Person re-identification (Re-ID) aims at recognizing the same person from images taken across different cameras. To address this task, one typically requires a large amount labeled data for training an effective Re-ID model, which might not be practical for real-world applications. To alleviate this limitation, we choose to exploit a sufficient amount of pre-existing labeled data from a different (auxiliary) dataset. By jointly considering such an auxiliary dataset and the dataset of interest (but without label information), our proposed adaptation and re-identification network (ARN) performs unsupervised domain adaptation, which leverages information across datasets and derives domain-invariant features for Re-ID purposes. In our experiments, we verify that our network performs favorably against state-of-the-art unsupervised Re-ID approaches, and even outperforms a number of baseline ReID methods which require fully supervised data for training.
Rényi Differential Privacy of the Sampled Gaussian Mechanism

The Sampled Gaussian Mechanism (SGM)---a composition of subsampling and the additive Gaussian noise---has been successfully used in a number of machine learning applications. The mechanism's unexpected power is derived from privacy amplification by sampling where the privacy cost of a single evaluation diminishes quadratically, rather than linearly, with the sampling rate. Characterizing the precise privacy properties of SGM motivated development of several relaxations of the notion of differential privacy. This work unifies and fills in gaps in published results on SGM. We describe a numerically stable procedure for precise computation of SGM's Renyi Differential Privacy and prove a nearly tight (within a small constant factor) closed-form bound.
On Inferring Training Data Attributes in Machine Learning Models

A number of recent works have demonstrated that API access to machine learning models leaks information about the dataset records used to train the models. Further, the work of \cite{somesh-overfit} shows that such membership inference attacks (MIAs) may be sufficient to construct a stronger breed of attribute inference attacks (AIAs), which given a partial view of a record can guess the missing attributes. In this work, we show (to the contrary) that MIA may not be sufficient to build a successful AIA. This is because the latter requires the ability to distinguish between similar records (differing only in a few attributes), and, as we demonstrate, the current breed of MIA are unsuccessful in distinguishing member records from similar non-member records. We thus propose a relaxed notion of AIA, whose goal is to only approximately guess the missing attributes and argue that such an attack is more likely to be successful, if MIA is to be used as a subroutine for inferring training record attributes.
HERMIT in Action: Succinct Secondary Indexing Mechanism via Correlation Exploration

Database administrators construct secondary indexes on data tables to accelerate query processing in relational database management systems (RDBMSs). These indexes are built on top of the most frequently queried columns according to the data statistics. Unfortunately, maintaining multiple secondary indexes in the same database can be extremely space consuming, causing signiﬁcant performance degradation due to the potential exhaustion of memory space. However, we ﬁnd that there indeed exist many opportunities to save storage space by exploiting column correlations. We recently introduced H ERMIT , a succinct secondary indexing mechanism for modern RDBMSs. H ERMIT judiciously leverages the rich soft functional dependencies hidden among columns to prune out redundant structures for indexed key access. Instead of building a complete index that stores every single entry in the key columns, H ERMIT navigates any incoming key access queries to an existing index built on the correlated columns. This is achieved through the Tiered Regression Search Tree (TRS-T REE ), a succinct, ML-enhanced data structure that performs fast curve ﬁtting to adaptively and dynamically capture both column correlations and outliers. In this demonstration, we showcase H ERMIT ’s appealing characteristics. we not only demonstrate that H ERMIT can signiﬁcantly reduce space consumption with limited performance overhead in terms of query response time and index maintenance time, but also explain in detail the rationale behind H ERMIT ’s high efﬁciency using interactive online query processing examples.
High-dimensional quantum frequency converter

In high dimensional quantum communication networks, quantum frequency convertor (QFC) is indispensable as an interface in the frequency domain. For example, many QFCs have been built to link atomic memories and fiber channels. However, almost all of QFCs work in a two-dimensional space. It is still a pivotal challenge to construct a high-quality QFC for some complex quantum states, e.g., a high dimensional single-photon state that refers to a qudit. Here, we firstly propose a high-dimensional QFC for an orbital angular momentum qudit via sum frequency conversion with a flat top beam pump. As a proof-of-principle demonstration, we realize quantum frequency conversions for a qudit from infrared to visible range. Based on the qudit quantum state tomography, the fidelities of converted state are 98.29(95.02)\%, 97.42(91.74)\%, and 86.75(67.04)\% for a qudit without (with) dark counts in 2,3, and 5 dimensions, respectively. The demonstration is very promising for constructing a high capacity quantum communication network.
Epithelial Cells as a Transmitter of Signals From Commensal Bacteria and Host Immune Cells

Intestinal epithelial cells (IECs) are non-hematopoietic cells that form a physical barrier against external antigens. Recent studies indicate that IECs have pleiotropic functions in the regulation of luminal microbiota and the host immune system. IECs produce various immune modulatory cytokines and chemokines in response to commensal bacteria and contribute to developing the intestinal immune system. In contrast, IECs receive cytokine signals from immune cells and produce various immunological factors against luminal bacteria. This bidirectional function of IECs is critical to regulate homeostasis of microbiota and the host immune system. Disruption of the epithelial barrier leads to detrimental host diseases such as inflammatory bowel disease, colonic cancer, and pathogenic infection. This review provides an overview of the functions and physiology of IECs and highlights their bidirectional functions against luminal bacteria and immune cells, which contribute to maintaining gut homeostasis.
OpenACC Errors Classification and Static Detection Techniques

With the continued increase of usage of High-Performance Computing (HPC) in scientific fields, the need for programming models in a heterogeneous architecture with less programming effort has become important in scientific applications. OpenACC is a high-level parallel programming model used with FORTRAN, C, and C++ programming languages to accelerate the programmers’ code with fewer changes and less effort, which reduces programmer workloads and makes it easier to use and learn. Also, OpenACC has been increasingly used in many top supercomputers around the world, and three of the top five HPC applications in Intersect360 Research are currently using OpenACC. However, when programmers use OpenACC to parallelize their code without correctly understanding OpenACC directives and their usage or following OpenACC instructions, they can cause run-time errors that vary from causing wrong results, performance issues, and other undefined behaviors. In addition, building parallel systems by using a higher level programming model increase the possibility to introduce errors, and the parallel applications thus have non-determined behavior, which makes testing and detecting their run-time errors a challenging task. Although there are many testing tools that detect run-time errors, this is still inadequate for detecting errors that occur in applications implemented in high-level parallel programming models, especially OpenACC related applications. As a result, OpenACC errors that cannot be detected by compilers should be identified, and their causes should be explained. In this paper, our contribution is introducing new static techniques for detecting OpenACC errors, as well as for the first time classifying errors that can occur in OpenACC software programs. Finally, to the best of our knowledge, there is no published work to date that identifies or classifies OpenACC-related errors, nor is there a testing tool designed to test OpenACC applications and detect their run-time errors.
Interactive Deformation Simulation of Manual Girth Measurement for Limbs

The existing methods for automatic girth measurement are primarily based on 3D point cloud or its generated surfaces, without considering limbs’ elasticity and thus the interactive deformation during manual measurement. Taking human foot as example, we propose a new method to simulate manual girth measurement using 3D triangular mesh and mass-spring model. The deformation is limited in the local deformed region consisted of tape region, propagation region and compensation region, while the latter two regions are controlled with depth parameters representing the affected ranges of limb surface from external forces. We also present a novel algorithm to dynamically calculate volume change of the deforming limb, and then repair the lost volume with compensation function. Our approach has the advantages of low computational complexity and realistic volume preserved simulation for interactive deformation in manual measurement. The proposed method is tested with experimental results, which illustrate its efficiency in many applications such as custom products making.
Properties of radio-loud quasars in the Sloan Digital Sky Survey

We present a study of a sample of 223 radio-loud quasars (up to redshift < 0.3) in order to investigate their spectral properties. Twenty-six of these radio-loud quasars are identified as flat-spectrum radio quasars (FSRQs), and 54 are identified as steep-spectrum radio quasars (SSRQs) based on their radio spectral index. We study the [O III] line properties of these quasars to investigate the origin and properties of blue wings (shift of the profile toward lower wavelengths) and blue outliers (shift of the whole spectroscopic feature). Most of the quasars show blue wings with velocities of up to 420 km s−1. We find that about 17% of the quasars show outliers whose velocities span from 419 to −315 km s−1. Finally, we revisit the MBH − σ relation of our sample using the [S II]λ 6716,6731 and [O III] line widths as surrogates for stellar velocity dispersions, σ, to investigate their location on the MBH − σ relation for quiescent galaxies. Because [S II] is strongly blended with Hα, we were able to estimate σ[S II] for only 123 quasars. We find that the radio-loud quasars do not show a relationship between MBH and σ[S II]/[O III] up to a redshift of 0.3, although they cluster around the local relation. We find an overall offset of 0.12 ± 0.05 dex of our sample of radio-loud quasars from the MBH − σ relation of quiescent galaxies. Quasars in our highest redshift bin (z = 0.25 − 0.3) show a deviation of ∼0.33 ± 0.06 dex from the local relation. Implications of the results are discussed.
Kernel/User-level Collaborative Persistent Memory File System with Efficiency and Protection

Emerging high performance non-volatile memories recall the importance of efficient file system design. To avoid the virtual file system (VFS) and syscall overhead as in these kernel-based file systems, recent works deploy file systems directly in user level. Unfortunately, a userlevel file system can easily be corrupted by a buggy program with misused pointers, and is hard to scale on multi-core platforms which incorporates a centralized coordination service. In this paper, we propose KucoFS, a Kernel and user-level collaborative file system. It consists of two parts: a user-level library with direct-access interfaces, and a kernel thread, which performs metadata updates and enforces write protection by toggling the permission bits in the page table. Hence, KucoFS achieves both direct-access of user-level designs and fine-grained write protection of kernel-level ones. We further explore its scalability to multicores: For metadata scalability, KucoFS rebalances the pathname resolution overhead between the kernel and userspace, by adopting the index offloading technique. For data access efficiency, it coordinates the data allocation between kernel and userspace, and uses range-lock write and lock-free read to improve concurrency. Experiments on Optane DC persistent memory show that KucoFS significantly outperforms existing file systems and shows better scalability.
Data Civilizer 2.0: A Holistic Framework for Data Preparation and Analytics

Data scientists spend over 80% of their time (1) parameter-tuning machine learning models and (2) iterating between data cleaning and machine learning model execution. While there are existing efforts to support the first requirement, there is currently no integrated workflow system that couples data cleaning and machine learning development. The previous version of Data Civilizer was geared towards data cleaning and discovery using a set of pre-defined tools. In this paper, we introduce Data Civilizer 2.0, an end-to-end workflow system satisfying both requirements. In addition, this system also supports a sophisticated data debugger and a workflow visualization system. In this demo, we will show how we used Data Civilizer 2.0 to help scientists at the Massachusetts General Hospital build their cleaning and machine learning pipeline on their 30TB brain activity dataset.
Association Between Hormone Therapy and Muscle Mass in Postmenopausal Women

Key Points Question In postmenopausal women 50 years or older, is estrogen-based hormone therapy associated with reduced loss of lean body mass compared with no hormone therapy? Findings In this systematic review and meta-analysis of 12 studies comprising 4474 postmenopausal women, those who received estrogen-based hormone therapy lost less lean body mass compared with women who received no hormone therapy and women who received placebo, but this finding was not statistically significant. Meaning The importance of muscle retention in aging women is crucial, but these findings suggest that interventions other than hormone therapy should be explored.
Mitigation of compression based attack on TLS/SSL

—Transport Layer Security(TLS) commonly known as Secure Socket Layer (SSL) is a foundation for Internet Security. We can achieve all security services by just implementing TLS. But though it reveals plaintext information through side channels. So, In this paper, we discuss security mechanism along with their side channel info-leakage. One basic side channel is compression, so based on compression information various attacks has been developed since last few years. Later, we discuss attacks like CRIME and BREACH briefly. In the end, we proposed schema to mitigate this attacks along with result analysis.
Diet and cognitive decline: considerations for reconciling heterogeneous findings.

DOI:10.1097/MOL.0000000000000624 Findings on dietary factors in relation to cognitive decline have not been entirely consistent across epidemiologic studies [1,2 & ]. Recently, two important investigations reached opposing conclusions regarding the associations between dietary quality and cognitive function. One publication, from the Whitehall II study, found no association between the Alternative Healthy Eating Index (AHEI), a validated dietary quality score, measured in mid-life and cognitive function over a follow-up of 18 years among 6961 British civil servants. Further, no association was observed between mid-life diet and risk of dementia [3 && ]. In contrast, a prospective study from the Coronary Artery Risk Development in Young Adults (CARDIA) cohort found that greater adherence to a heathy dietary pattern, as measured by the A Priori Diet Quality Score (APDQS), during early adulthood was associated with a slower decline in cognitive function during the mid-life of 2621 participants [4 && ]. As strengths, both studies had extended followup periods, included large study populations, administered validated dietary measurements repeatedly, and assessed cognitive function through multiple standardized tests. However, common limitation, such as the observational study setting and limited generalizability of study results because of participants’ age, should be considered when interpreting the findings. In the Whitehall II study, ascertaining dementia cases via linkage to electronic health record databases may lead to biased results because of misclassification of outcomes. It is commonly accepted that electronic health records tend to capture more progressive cases as patients are less likely to seek help from physicians when the disease is mild. As dementia cases were not investigated in the CARDIA study, discussion in this commentary will focus on cognitive function as the outcome. Nevertheless, given that the same set of cognitive test batteries were administered repeatedly in both studies, the assessments of cognitive functions in both studies were prone to measurement errors from practice effects because of serial testing. Additionally, it is debatable whether the cognitive test batteries can sufficiently capture the pathological
Evaluation of a logarithmic HDR sensor for an image-based navigation system

We have evaluated a HDR (high dynamic range) CMOS image sensor with logarithmic response for an image-based navigation system which allows vehicles to autonomously drive on reference trajectories. The goal of the evaluation is to investigate how the advantages (constant image intensities under varying illumination conditions) and the disadvantages (higher noise and artifact levels) of the sensor affect the performance of image-based navigation. We recorded HDR image sequences using a vehicle to evaluate the performance of intra-frame image analysis which is used to estimate the vehicle motion and the respective trajectories, and the performance of inter-frame image analysis which is used for the alignment of a current trajectory to a reference trajectory. We have also performed a comparison with simultaneously recorded LDR image data on itineraries with scenes with high dynamic range.
Mitochondrial bioenergetic changes during development as an indicator of C. elegans health-span

Mild suppression of mitochondrial activity has beneficial effects across species. The nematode Caenorhabditis elegans is a versatile, genetically tractable model organism widely employed for aging studies, which has led to the identification of many of the known evolutionarily conserved mechanisms regulating lifespan. In C. elegans the pro-longevity effect of reducing mitochondrial function, for example by RNA interference, is only achieved if mitochondrial stress is applied during larval development. Surprisingly, a careful analysis of changes in mitochondrial functions resulting from such treatments during the developmental windows in which pro-longevity signals are programmed has never been carried out. Thus, although the powerful C. elegans genetics have led to the identification of different molecular mechanisms causally involved in mitochondrial stress control of longevity, specific functional mitochondrial biomarkers indicative or predictive of lifespan remain to be identified. To fill this gap, we systematically characterized multiple mitochondrial functional parameters at an early developmental stage in animals that are long-lived due to mild knockdown of twelve different mitochondrial proteins and correlated these parameters with animals’ lifespan. We found that basal oxygen consumption rate and ATP-linked respiration positively correlate with lifespan extension and propose the testable hypothesis that the Bioenergetic Health Index can be used as a proxy to predict health-span outcomes.