Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Deep Quantized Compressed Sensing Coding Framework of Natural Images

Traditional image compressed sensing (CS) coding frameworks solve an inverse problem that is based on the measurement coding tools (prediction, quantization, entropy coding, etc.) and the optimization based image reconstruction method. These CS coding frameworks face the challenges of improving the coding efficiency at the encoder, while also suffering from high computational complexity at the decoder. In this paper, we move forward a step and propose a novel deep network based CS coding framework of natural images, which consists of three sub-networks: sampling sub-network, offset sub-network and reconstruction sub-network that responsible for sampling, quantization and reconstruction, respectively. By cooperatively utilizing these sub-networks, it can be trained in the form of an end-to-end metric with a proposed rate-distortion optimization loss function. The proposed framework not only improves the coding performance, but also reduces the computational cost of the image reconstruction dramatically. Experimental results on benchmark datasets demonstrate that the proposed method is capable of achieving superior rate-distortion performance against state-of-the-art methods.
Optimizing Generalized Linear Models with Billions of Variables

The use of large-scale machine learning~(ML) is becoming ubiquitous in various domains ranging from business intelligence to self-driving cars. Many companies are building ML pipelines in a unified data processing environment, and leveraging well-tuned numerical optimization packages for obtaining model parameters. However, most existing optimization tools are specifically designed for a single machine setup, and cannot handle vast volume of data. In this work, we build a distributed computing framework towards optimizing generalized linear models with billions of variables. We at first design a new distributed vector to represent data points from extremely large feature space. Then, we introduce an efficient and scalable approach to compute the second order derivatives of loss function, and optimizes model parameters with limited memory requirement. Experiments on real-world datasets demonstrate that our proposed techniques can scale up for ML models with billions of variables, and achieves better performance than state-of-the-art systems on a wide range of applications, e.g., ad CTR prediction and rideshare price bidding.
Multi-modality Hierarchical Recall based on GBDTs for Bipolar Disorder Classification

In this paper, we propose a novel hierarchical recall model fusing multiple modality (including audio, video and text) for bipolar disorder classification, where patients with different mania level are recalled layer-by-layer. To address the complex distribution on the challenge data, the proposed framework utilizes multi-model, multi-modality and multi-layer to perform domain adaptation for each patient and hard sample mining for special patients. The experimental results show that our framework achieves competitive performance with Unweighed Average Recall (UAR) of 57.41% on the test set, and 86.77% on the development set.
Novel CSF biomarkers to discriminate FTLD and its pathological subtypes

Frontotemporal lobar degeneration (FTLD) is the second most prevalent dementia in young patients and is characterized by the presence of two main protein aggregates in the brain, tau (FTLD‐Tau) or TDP43 (FTLD‐TDP), which likely require distinct pharmacological therapy. However, specific diagnosis of FTLD and its subtypes remains challenging due to largely overlapping clinical phenotypes. Here, we aimed to assess the clinical performance of novel cerebrospinal fluid (CSF) biomarkers for discrimination of FTLD and its pathological subtypes.
Point Symmetry-based Deep Clustering

Clustering is a central task in unsupervised learning. Recent advances that perform clustering into learned deep features (such as DEC[14], IDEC [6] or VaDe [10]) have shown improvements over classical algorithms, but most of them are based on the Euclidean distance. Moreover, symmetry-based distances have shown to be a powerful tool to distinguish symmetric shapes -- such as circles, ellipses, squares, etc. This paper presents an adaptation of symmetry-based distances into deep clustering algorithms, named SymDEC. Our results show that the proposed strategy outperforms significantly the existing Euclidean-based deep clustering as well as recent symmetry-based algorithms in several of the synthetic symmetric and UCI studied datasets.
Re-evaluating Embedding-Based Knowledge Graph Completion Methods

Incompleteness of large knowledge graphs (KG) has motivated many researchers to propose methods to automatically find missing edges in KGs. A promising approach for KG completion (link prediction) is embedding a KG into a continuous vector space. There are different methods in the literature that learn a continuous representation of KG (latent features of KG). The benchmark dataset FB15k has been widely employed to evaluate these methods. However, It has been noted that FB15k contains many pairs of edges in which a pair represents the same relationship in reverse directions. Therefore, the inverse of numerous test triples occurs in the training set. To address this problem, FB15k-237, a subset of FB15k, was created by removing those inverse-duplicate relations to form a more challenging, realistic dataset. There is not any study that investigates how the aforementioned bias in this widely used benchmark dataset affects the results of embedding-based knowledge graph completion methods and whether their promising results are largely due to the bias. Motivated by this question, we conducted extensive experiments and report the link prediction results on FB15K and FB15k-237 using several embedding-based methods. We compare the results of different methods to see how their performances change in absence of inverse relations. Our experiment results demonstrate that the performance of embedding models in link prediction task diminishes tremendously when the inverse relationships do not exist anymore.
SOURCERY: User Driven Multi-Criteria Source Selection

Data scientists are usually interested in a subset of sources with properties that are most aligned to intended data use. The SOURCERY system supports interactive multi-criteria user-driven source selection. SOURCERY allows a user to identify criteria they consider of importance and indicate their relative importance, and seeks a source selection result aligned to the user-supplied criteria preferences. The user is given an overview of the properties of the sources that are selected along with visual analyses contextualizing the result in relation to what is theoretically possible and what is possible given the set of available sources. The system also enables a user to interactively perform iterative fine-tuning to explore how changes to preferences may impact results.
Estimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods

Estimates of the worldwide incidence and mortality from 36 cancers and for all cancers combined for the year 2018 are now available in the GLOBOCAN 2018 database, compiled and disseminated by the International Agency for Research on Cancer (IARC). This paper reviews the sources and methods used in compiling the cancer statistics in 185 countries. The validity of the national estimates depends upon the representativeness of the source information, and to take into account possible sources of bias, uncertainty intervals are now provided for the estimated sex‐ and site‐specific all‐ages number of new cancer cases and cancer deaths. We briefly describe the key results globally and by world region. There were an estimated 18.1 million (95% UI: 17.5–18.7 million) new cases of cancer (17 million excluding non‐melanoma skin cancer) and 9.6 million (95% UI: 9.3–9.8 million) deaths from cancer (9.5 million excluding non‐melanoma skin cancer) worldwide in 2018.
Traditional Chinese Medicine as a Potential Source for HSV-1 Therapy by Acting on Virus or the Susceptibility of Host

Herpes simplex virus type 1 (HSV-1) is the most common virus, with an estimated infection rate of 60–95% among the adult population. Once infected, HSV-1 can remain latent in the host for a lifetime and be reactivated in patients with a compromised immune system. Reactivation of latent HSV-1 can also be achieved by other stimuli. Though acyclovir (ACV) is a classic drug for HSV-1 infection, ACV-resistant strains have been found in immune-compromised patients and drug toxicity has also been commonly reported. Therefore, there is an urge to search for new anti-HSV-1 agents. Natural products with potential anti-HSV-1 activity have the advantages of minimal side effects, reduced toxicity, and they exert their effect by various mechanisms. This paper will not only provide a reference for the safe dose of these agents if they are to be used in humans, referring to the interrelated data obtained from in vitro experiments, but also introduce the main pharmacodynamic mechanisms of traditional Chinese medicine (TCM) against HSV-1. Taken together, TCM functions as a potential source for HSV-1 therapy by direct (blocking viral attachment/absorption/penetration/replication) or indirect (reducing the susceptibility to HSV-1 or regulating autophagy) antiviral activities. The potential of these active components in the development of anti-HSV-1 drugs will also be described.
Trimethylamine N-Oxide: A Link among Diet, Gut Microbiota, Gene Regulation of Liver and Intestine Cholesterol Homeostasis and HDL Function

Recent evidence, including massive gene-expression analysis and a wide-variety of other multi-omics approaches, demonstrates an interplay between gut microbiota and the regulation of plasma lipids. Gut microbial metabolism of choline and l-carnitine results in the formation of trimethylamine (TMA) and concomitant conversion into trimethylamine-N-oxide (TMAO) by liver flavin monooxygenase 3 (FMO3). The plasma level of TMAO is determined by the genetic variation, diet and composition of gut microbiota. Multiple studies have demonstrated an association between TMAO plasma levels and the risk of atherothrombotic cardiovascular disease (CVD). We aimed to review the molecular pathways by which TMAO production and FMO3 exert their proatherogenic effects. TMAO may promote foam cell formation by upregulating macrophage scavenger receptors, deregulating enterohepatic cholesterol and bile acid metabolism and impairing macrophage reverse cholesterol transport (RCT). Furthermore, FMO3 may promote dyslipidemia by regulating multiple genes involved in hepatic lipogenesis and gluconeogenesis. FMO3 also impairs multiple aspects of cholesterol homeostasis, including transintestinal cholesterol export and macrophage-specific RCT. At least part of these FMO3-mediated effects on lipid metabolism and atherogenesis seem to be independent of the TMA/TMAO formation. Overall, these findings have the potential to open a new era for the therapeutic manipulation of the gut microbiota to improve CVD risk.
Group Re-Identification: Leveraging and Integrating Multi-Grain Information

This paper addresses an important yet less-studied problem: re-identifying groups of people in different camera views. Group re-identification (Re-ID) is very challenging since it is not only interfered by view-point and human pose variations in the traditional single-object Re-ID tasks, but also suffers from group layout and group member variations. To handle these issues, we propose to leverage the information of multi-grain objects: individual person and subgroups of two and three people inside a group image. We compute multi-grain representations to characterize the appearance and spatial features of multi-grain objects and evaluate the importance weight of each object for group Re-ID, so as to handle the interferences from group dynamics. We compute the optimal group-wise matching by using a multi-order matching process based on the multi-grain representation and importance weights. Furthermore, we dynamically update the importance weights according to the current matching results and then compute a new optimal group-wise matching. The two steps are iteratively conducted, yielding the final matching results.Experimental results on various datasets demonstrate the effectiveness of our approach.
Mediterranean Lifestyle in Relation to Cognitive Health: Results from the HELIAD Study

Many lifestyle factors have been linked to cognitive function but little is known about their combined effect. An overall lifestyle pattern for people living in the Mediterranean basin has been proposed, including diet, but also physical activity, sleep and daily living activities with social/intellectual aspects. We aimed to examine the associations between a combination of these lifestyle factors and detailed cognitive performance. A total of 1716 participants from the Hellenic Longitudinal Investigation of Ageing and Diet (HELIAD), a population-based study of participants ≥65 years, were included in this analysis. Lifestyle factors were evaluated using standard, validated questionnaires and a Total Lifestyle Index (TLI) was constructed. Cognitive outcomes included mild cognitive impairment (MCI) diagnosis, a composite z-score (either continuous or with a threshold at the 25th percentile) and z-scores for five cognitive domains. A higher TLI was associated with 65% reduced odds for MCI in the non-demented individuals and 43% reduced odds for low global cognition when MCI participants were excluded, a risk reduction equivalent to 9 and 2.7 fewer years of ageing, respectively. Each lifestyle factor was differentially associated with domain-specific cognitive performance. Our results suggest that a TLI, more so than single lifestyle parameters, may be related to cognitive performance.
A Tumor-Promoting Phorbol Ester Causes a Large Increase in APOBEC3A Expression and a Moderate Increase in APOBEC3B Expression in a Normal Human Keratinocyte Cell Line without Increasing Genomic Uracils

Phorbol 12-myristate 13-acetate (PMA) promotes skin cancer in rodents. The mutations found in murine tumors are similar to those found in human skin cancers, and PMA promotes proliferation of human skin cells. ABSTRACT Phorbol 12-myristate 13-acetate (PMA) promotes skin cancer in rodents. The mutations found in murine tumors are similar to those found in human skin cancers, and PMA promotes proliferation of human skin cells. PMA treatment of human keratinocytes increases the synthesis of APOBEC3A, an enzyme that converts cytosines in single-stranded DNA to uracil, and mutations in a variety of human cancers are attributed to APOBEC3A or APOBEC3B expression. We tested here the possibility that induction of APOBEC3A by PMA causes genomic accumulation of uracils that may lead to such mutations. When a human keratinocyte cell line was treated with PMA, both APOBEC3A and APOBEC3B gene expression increased, anti-APOBEC3A/APOBEC3B antibody bound a protein(s) in the nucleus, and nuclear extracts displayed cytosine deamination activity. Surprisingly, there was little increase in genomic uracils in PMA-treated wild-type or uracil repair-defective cells. In contrast, cells transfected with a plasmid expressing APOBEC3A acquired more genomic uracils. Unexpectedly, PMA treatment, but not APOBEC3A plasmid transfection, caused a cessation in cell growth. Hence, a reduction in single-stranded DNA at replication forks may explain the inability of PMA-induced APOBEC3A/APOBEC3B to increase genomic uracils. These results suggest that the proinflammatory PMA is unlikely to promote extensive APOBEC3A/APOBEC3B-mediated cytosine deaminations in human keratinocytes.
The Cytokine Profile in Acute Chikungunya Infection is Predictive of Chronic Arthritis 20 Months Post Infection

The cytokine profile during acute chikungunya infection that predicts future chronic arthritis has not yet been investigated. We conducted a nested case-control study comparing serum cytokine concentrations during acute chikungunya infection in cases (n = 121) that reported the presence of chronic joint pain versus age- and gender-matched controls (n = 121) who reported recovery at 20 months post infection. We observed that a robust cytokine response during acute infection was correlated with a decreased incidence of chronic joint pain and that low TNFα, IL-13, IL-2, and IL-4 during acute infection was predictive of chronic joint pain. These data suggest that a robust cytokine response is necessary for viral clearance and cytokines that are related to immune tolerance during acute infection may be protective for chronic arthritis pathogenesis.
Pulsed electromagnetic fields prevented the decrease of bone formation in hindlimb‐suspended rats by activating sAC/cAMP/PKA/CREB signaling pathway

Microgravity is one of the main threats to the health of astronauts. Pulsed electromagnetic fields (PEMFs) have been considered as one of the potential countermeasures for bone loss induced by space flight. However, the optimal therapeutic parameters of PEMFs have not been obtained and the action mechanism is still largely unknown. In this study, a set of optimal therapeutic parameters for PEMFs (50 Hz, 0.6 mT 50% duty cycle and 90 min/day) selected based on high‐throughput screening with cultured osteoblasts was used to prevent bone loss in rats induced by hindlimb suspension, a commonly accepted animal model to simulate the space environment. It was found that hindlimb suspension for 4 weeks led to significant decreases in femoral and vertebral bone mineral density (BMD) and their maximal loads, severe deterioration in bone micro‐structure, and decreases in levels of bone formation markers and increases in bone resorption markers. PEMF treatment prevented about 50% of the decreased BMD and maximal loads, preserved the microstructure of cancellous bone and thickness of cortical bone, and inhibited decreases in bone formation markers. Histological analyses revealed that PEMFs significantly alleviated the reduction in osteoblast number and inhibited the increase in adipocyte number in the bone marrow. PEMFs also blocked decreases in serum levels of parathyroid hormone and its downstream signal molecule cAMP, and maintained the phosphorylation levels of protein kinase A (PKA) and cAMP response element‐binding protein (CREB). The expression level of soluble adenylyl cyclases (sAC) was also maintained. It therefore can be concluded that PEMFs partially prevented the bone loss induced by weightless environment by maintaining bone formation through signaling of the sAC/cAMP/PKA/CREB pathway. Bioelectromagnetics. 39:569–584, 2018. © 2018 Wiley Periodicals, Inc.
Learning Optimal Scheduling Policy for Remote State Estimation Under Uncertain Channel Condition

We consider optimal sensor scheduling with unknown communication channel statistics. We formulate two types of scheduling problems with the communication rate being a soft or hard constraint, respectively. We first present some structural results on the optimal scheduling policy using dynamic programming and assuming that the channel statistics is known. We prove that the <inline-formula><tex-math notation="LaTeX">$Q$</tex-math></inline-formula>-factor is monotonic and submodular, which leads to thresholdlike structures in both problems. Then, we develop a stochastic approximation and parameter learning frameworks to deal with the two scheduling problems with unknown channel statistics. We utilize their structures to design specialized learning algorithms. We, then prove the convergence of these algorithms. Performance improvement compared with the standard <inline-formula><tex-math notation="LaTeX">$Q$</tex-math></inline-formula>-learning algorithm is shown through numerical examples, which will also discuss an alternative method based on recursive estimation of the channel quality.
Axonal Stimulations With a Higher Frequency Generate More Randomness in Neuronal Firing Rather Than Increase Firing Rates in Rat Hippocampus

Deep brain stimulation (DBS) has been used for treating many brain disorders. Clinical applications of DBS commonly require high-frequency stimulations (HFS, ∼100 Hz) of electrical pulses to obtain therapeutic efficacy. It is not clear whether the electrical energy of HFS functions other than generating firing of action potentials in neuronal elements. To address the question, we investigated the reactions of downstream neurons to pulse sequences with a frequency in the range 50–200 Hz at afferent axon fibers in the hippocampal CA1 region of anesthetized rats. The results show that the mean rates of neuronal firing induced by axonal HFS were similar even for an up to fourfold difference (200:50) in the number and thereby in the energy of electrical pulses delivered. However, HFS with a higher pulse frequency (100 or 200 Hz) generated more randomness in the firing pattern of neurons than a lower pulse frequency (50 Hz), which were quantitatively evaluated by the significant changes of two indexes, namely, the peak coefficients and the duty ratios of excitatory phase of neuronal firing, induced by different frequencies (50–200 Hz). The findings indicate that a large portion of the HFS energy might function to generate a desynchronization effect through a possible mechanism of intermittent depolarization block of neuronal membranes. The present study addresses the demand of high frequency for generating HFS-induced desynchronization in neuronal activity, which may play important roles in DBS therapy.
Pharmacokinetics and Pharmacodynamics of the BACE1 Inhibitor Verubecestat (MK‐8931) in Healthy Japanese Adults: A Randomized, Placebo‐Controlled Study

β‐site amyloid precursor protein cleaving enzyme 1 (BACE1) is required for the production of β‐amyloid (Aβ) peptides and is considered a potential treatment target for Alzheimer's disease (AD). To support Japan's participation in the global clinical development program, we characterized the safety, pharmacokinetics (PKs), and pharmacodynamics of the BACE1 inhibitor verubecestat (MK‐8931) in 24 healthy Japanese adults in a two‐part, single‐center, randomized, placebo‐controlled phase I trial (protocol MK‐8931‐007) and compared the results with historical data from non‐Japanese subjects. Both single (20, 100, and 450 mg) and multiple (80 and 150 mg once daily for 14 days) doses of verubecestat were well tolerated. Verubecestat's PK profile was similar in Japanese and non‐Japanese subjects. Verubecestat also reduced mean cerebrospinal fluid concentrations of the Aβ proteins Aβ40, Aβ42, and soluble β fragment of amyloid precursor protein; the level of reduction was comparable between Japanese and non‐Japanese subjects. These results support the continued global development of verubecestat as a potential disease‐modifying agent for Japanese and non‐Japanese subjects who are at risk for developing AD.