Miracle-dz/UniFAR-FTUs huggingface dataset:
Audio-Visual Attention Networks for Emotion Recognition

We present a spatiotemporal attention based multimodal deep neu- ral networks for dimensional emotion recognition in multimodal audio-visual video sequence. To learn the temporal attention that discriminatively focuses on emotional sailient parts within speech audios, we formulate the temporal attention network using deep neural networks (DNNs). In addition, to learn the spatiotemporal attention that selectively focuses on emotional sailient parts within facial videos, the spatiotemporal encoder-decoder network is formu- lated using Convolutional LSTM (ConvLSTM) modules, and learned implicitly without any pixel-level annotations. By leveraging the spatiotemporal attention, the 3D convolutional neural networks (3D-CNNs) is also formulated to robustly recognize the dimensional emotion in facial videos. Furthermore, to exploit multimodal infor- mation, we fuse the audio and video features to emotion regression model. The experimental results show that our method can achieve the state-of-the-art results in dimensional emotion recognition with the highest concordance correlation coefficient (CCC) on AV+EC 2017 dataset.
Monocular Camera Based Real-Time Dense Mapping Using Generative Adversarial Network

Monocular simultaneous localization and mapping (SLAM) is a key enabling technique for many computer vision and robotics applications. However, existing methods either can obtain only sparse or semi-dense maps in highly-textured image areas or fail to achieve a satisfactory reconstruction accuracy. In this paper, we present a new method based on a generative adversarial network,named DM-GAN, for real-time dense mapping based on a monocular camera. Specifcally, our depth generator network takes a semidense map obtained from motion stereo matching as a guidance to supervise dense depth prediction of a single RGB image. The depth generator is trained based on a combination of two loss functions, i.e. an adversarial loss for enforcing the generated depth maps to reside on the manifold of the true depth maps and a pixel-wise mean square error (MSE) for ensuring the correct absolute depth values. Extensive experiments on three public datasets demonstrate that our DM-GAN signifcantly outperforms the state-of-the-art methods in terms of greater reconstruction accuracy and higher depth completeness.
New Feature-level Video Classification via Temporal Attention Model

CoVieW 2018 is a new challenge which aims at simultaneous scene and action recognition for untrimmed video [1]. In the challenge, frame-level video features extracted by pre-trained deep convolutional neural network (CNN) are provided for video-level classification. In this paper, a new approach for the video-level classification method is proposed. The proposed method focuses on the analysis in temporal domain and the temporal attention model is developed. To compensate for the differences in the lengths of various videos, temporal padding method is also developed to unify the lengths of videos. Further, data augmentation is performed to enhance some validation accuracy. Finally, for the train/validation in CoView 2018 dataset we recorded the performance of 95.53% accuracy in the scene and 87.17% accuracy in the action using temporal attention model, nonzero padding and data augmentation. The top-1 hamming score is the standard metric in the CoVieW 2018 challenge and 91.35% is obtained by the proposed method.
Transcription Factor ANAC074 Binds to NRS1, NRS2, or MybSt1 Element in Addition to the NACRS to Regulate Gene Expression

NAC (NAM, ATAF1/2, and CUC2) transcription factors play important roles in many biological processes, and mainly bind to the NACRS with core sequences “CACG” or “CATGTG” to regulate gene expression. However, whether NAC proteins can bind to other motifs without these core sequences remains unknown. In this study, we employed a Transcription Factor-Centered Yeast one Hybrid (TF-Centered Y1H) screen to study the motifs recognized by ANAC074. In addition to the NACRS core cis-element, we identified that ANAC074 could bind to MybSt1, NRS1, and NRS2. Y1H and GUS assays showed that ANAC074 could bind the promoters of ethylene responsive genes and stress responsive genes via the NRS1, NRS2, or MybSt1 element. ChIP study further confirmed that the bindings of ANAC074 to MybSt1, NRS1, and NRS2 actually occurred in Arabidopsis. Furthermore, ten NAC proteins from different NAC subfamilies in Arabidopsis thaliana were selected and confirmed to bind to the MybSt1, NRS1, and NRS2 motifs, indicating that they are recognized commonly by NACs. These findings will help us to further reveal the functions of NAC proteins.
Insights into the antibacterial mechanism of PEGylated nano-bacitracin A against Streptococcus pneumonia: both penicillin-sensitive and penicillin-resistant strains

Background Multidrug-resistant (MDR) Streptococcus pneumonia constitute a major worldwide public health concern. Materials and methods In our preliminary study, PEGylated nano-self-assemblies of bacitracin A (PEGylated Nano-BA12K) showed strong antibacterial potency against reference S. pneumonia strain (ATCC 49619). In this study, the possibility of applying PEGylated Nano-BA12K against penicillin-resistant S. pneumonia was further investigated. In addition, the underlying antibacterial mechanism of PEGylated Nano-BA12K against both sensitive and resistant S. pneumonia was also clarified systematically, since S. pneumonia was naturally resistant to its unassembled counterpart bacitracin A (BA). Results PEGylated Nano-BA12K showed strong antibacterial potency against 13 clinical isolates of S. pneumonia, including five penicillin-resistant strains. Structural changes, partial collapse, and even lysis of both penicillin-sensitive and penicillin-resistant bacteria were observed after incubation with PEGylated Nano-BA12K via transmission electron microscopy and atomic force microscopy. Thus, the cell wall or/and cell membrane might be the main target of PEGylated Nano-BA12K against S. pneumonia. PEGylated Nano-BA12K exhibited limited effect on the permeabilization and peptidoglycan content of cell wall. Surface pressure measurement suggested that PEGylated Nano-BA12K was much more tensioactive than BA, which was usually translated into a good membranolytic effect, and is helpful to permeabilize the cell membrane and damage membrane integrity, as evidenced by depolarization of the membrane potential, permeabilization of membrane and leakage of calcein from liposomes. Conclusion Collectively, great cell membrane permeability and formidable membrane disruption may work together for the strong antibacterial activity of PEGylated Nano-BA12K against S. pneumonia. Taken together, PEGylated Nano-BA12K has excellent potential against both penicillin-sensitive and penicillin-resistant S. pneumonia and might be suitable for the treatment of S. pneumonia infectious diseases.
A Human Gonadal Cell Model From Induced Pluripotent Stem Cells

Sertoli cells are main players in the male gonads development and their study may shed light on 46,XY disorders of sex development (DSD). Mature primary Sertoli cells are incapable of proliferating in prolonged in vitro cultures and the available Sertoli cell models have several limitations since they derive from mouse or human cancer tissues. We differentiated human fibroblasts (HFs)-derived induced pluripotent stem cells into Sertoli-like cells (SLC) and, in order to characterize this new Sertoli cell model, we performed gene expression analyses by NextGeneration Sequencing techniques. This approach revealed that our putative SLC have reduced expression of pluripotency markers and expressed Sertoli cell markers such as SRY-Related HMG-Box 9 (SOX9), vimentin (VIM), and claudin-11 (CLDN-11). More in detail, the transcriptional profile analysis suggested that these cells are in an early stage of Sertoli cells maturation. Harnessing the power of induced pluripotent stem cells, we were able to generate SLC that show genetic and functional similarities to human Sertoli cells (HSerCs). SLC could become an excellent source of patient-specific Sertoli cells that could be of paramount benefit for both basic research and personalized medicine in sex development and reproductive medicine.
Performance Comparison of CUDA and OpenACC Based on Optimizations

Based on various optimizations, this paper presents a performance comparison between CUDA and OpenACC using 19 kernels in 10 benchmarks. The performance analysis focuses on programming models, optimization technologies and underlying compilers. It measures and compares kernel execution times and data transfer times to/from the GPU. In addition, it utilizes a Performance Ratio metric to conduct an objective comparison. The experimental results show that in general the PGI compiler is able to translate OpenACC kernels into object code that is slightly slower than hand-written CUDA codes for benchmarks that solve the same problem. Also, the data transfer time in OpenACC programs tends to be much faster than in CUDA, while the number of memcpy calls tends to be higher than in CUDA. Overall conclusions were found that OpenACC is a very reliable programming model and a good alternative to CUDA for accelerator devices. For the programs in our test corpus, OpenACC performs as well as CUDA, and in general, OpenACC is better for novices and for programmers targeting multiple platforms.
Shensong Yangxin capsule reduces atrial fibrillation susceptibility by inhibiting atrial fibrosis in rats with post-myocardial infarction heart failure

Purpose Shensong Yangxin (SSYX) capsule is a traditional Chinese medicine that has been used widely to treat cardiac arrhythmia. This study aimed to assess whether SSYX prevents atrial fibrillation (AF) after chronic myocardial infarction (MI)-induced heart failure and to determine the underlying mechanisms. Materials and methods The study included 45 male Sprague Dawley rats. The rats underwent MI induction or sham surgery. One week after MI induction surgery, we performed serial echocardiography and administered SSYX capsule to some rats that experienced MI. After 4 weeks of treatment, AF inducibility was assessed with transesophageal programmed electrical stimulation technology. Additionally, multielectrode array assessment, histological analysis, and Western blot analysis were performed. Results AF inducibility was significantly lower in SSYX rats than in MI rats (33.3% vs 73.3%, P<0.05). Additionally, conduction velocities in the left atrium were greater in SSYX rats than in MI rats. Moreover, SSYX decreased left atrial fibrosis, downregulated TGF-β1, MMP-9, TIMP-I, and type I and III collagen expressions, and inhibited the differentiation of cardiac fibroblasts to myofibroblasts. Conclusion SSYX reduces AF inducibility after MI by improving left atrial conduction function via the inhibition of left atrial fibrosis. It prevents the development of an MI-induced vulnerable substrate for AF.
GREB1‐CTNNB1 fusion transcript detected by RNA‐sequencing in a uterine tumor resembling ovarian sex cord tumor (UTROSCT): A novel CTNNB1 rearrangement

Mutations of CTNNB1 have been implicated in tumorigenesis in many organs. However, tumors harboring a CTNNB1 translocation are extremely rare and this translocation has never been reported in a uterine mesenchymal neoplasm. We report a novel translocation t(2;3)(p25;p22) involving the GREB1 (intron 8) and CTNNB1 (exon 3) in a uterine tumor resembling ovarian sex cord tumor (UTROSCT), which exhibited extrauterine metastasis. The translocation detected by RNA‐sequencing was validated by RT‐PCR, and resulted in nuclear expression of β‐catenin. Juxtapositioning with GREB1, which is overexpressed in response to estrogens, resulted in overexpression of a truncated and hypophosphorylated nuclear β‐catenin in the primary and recurrent tumors. This accumulation of nuclear β‐catenin results in a constitutive activation of the Wnt/β‐catenin signaling pathway with a major oncogenic effect. The CTNNB1 gene fusion, promoted by an estrogen‐responsive gene (GREB1), could be a potential driver of tumorigenesis in this case and a therapeutic target with adapted inhibitors. RT‐PCR and immunohistochemistry performed on 11 additional UTROSCTs showed no CTNNB1 fusion transcript or nuclear β‐catenin immunoreactivity.
Sex-related response to bivalirudin and unfractionated heparin in patients with acute myocardial infarction undergoing percutaneous coronary intervention: A subgroup analysis of the VALIDATE-SWEDEHEART trial

Aims: Our aim was to study the impact of sex on anticoagulant treatment outcomes during percutaneous coronary intervention in acute myocardial infarction patients. Methods: This study was a prespecified analysis of the Bivalirudin versus Heparin in ST-Segment and Non ST-Segment Elevation Myocardial Infarction in Patients on Modern Antiplatelet Therapy in the Swedish Web System for Enhancement and Development of Evidence-based Care in Heart Disease Evaluated according to Recommended Therapies Registry Trial (VALIDATE-SWEDEHEART) trial, in which patients with myocardial infarction were randomised to bivalirudin or unfractionated heparin during percutaneous coronary intervention. The primary outcome was the composite of death, myocardial infarction or major bleeding at 180 days. Results: There was a lower risk of the primary outcome in women assigned to bivalirudin than to unfractionated heparin (13.6% vs 17.1%, hazard ratio 0.78, 95% confidence interval (0.60–1.00)) with no significant difference in men (11.8% vs 11.2%, hazard ratio 1.06 (0.89–1.26), p for interaction 0.05). The observed difference was primarily due to lower risk of major bleeding (Bleeding Academic Research Consortium definition 2, 3 or 5) associated with bivalirudin in women (8.9% vs 11.8%, hazard ratio 0.74 (0.54–1.01)) but not in men (8.5% vs 7.3%, hazard ratio 1.16 (0.94–1.43) in men, p for interaction 0.02). Conversely, no significant difference in the risk of Bleeding Academic Research Consortium 3 or 5 bleeding, associated with bivalirudin, was found in women 4.5% vs 5.4% (hazard ratio 0.84 (0.54–1.31)) or men 2.9% vs 2.1% (hazard ratio 1.36 (0.93–1.99)). Bleeding Academic Research Consortium 2 bleeding occurred significantly less often in women assigned to bivalirudin than to unfractionated heparin. The risk of death or myocardial infarction did not significantly differ between randomised treatments in men or women. Conclusion: In women, bivalirudin was associated with a lower risk of adverse outcomes, compared to unfractionated heparin, primarily due to a significant reduction in Bleeding Academic Research Consortium 2 bleeds.
Enhancing Visual Question Answering Using Dropout

Using dropout in Visual Question Answering (VQA) is a common practice to prevent overfitting. However, in multi-path networks, the current way to use dropout may cause two problems: the co-adaptations of neurons and the explosion of output variance. In this paper, we propose the coherent dropout and the siamese dropouy to solve the two problems, respectively. Specifically, in coherent dropout, all relevant dropout layers in multiple paths are forced to work coherently to maximize the ability of preventing neuron co-adaptations. We show that the coherent dropout is simple in implementation but very effective to overcome overfitting. As for the explosion of output variance, we develop a siamese dropout mechanism to explicitly minimize the difference between the two output vectors produced from the same input data during training phase. Such mechanism can reduce the gap between training and inference phases and make the VQA model more robust. Extensive experiments are conducted to verify the effectiveness of coherent dropout and siamese dropout. And the results also show that our methods can bring additional improvements on the state-of-the-art VQA models.
Computation Offloading for Mobile-Edge Computing with Maximum Flow Minimum Cut

Due1 to the constraints of size and weight, mobile terminals are limited by processing power, memory capacity, network connectivity and battery capacity. Therefore, how to expand the resources of mobile terminals has become an urgent problem. The mobile-edge computation offloading is an effective way to extend the battery life of mobile intelligent terminals by performing some application calculations on remote servers. However, the segmentation of computing programs is a precondition for mobile-edge computation offloading. In this paper, we discuss the segmentation problem of computation offloading based on maximum flow minimum cut and propose an optimal segmentation algorithm for mobile applications. First, the network flow graph model of application is defined. Based on the label propagation theory, the sub-graphs are divided and the network graph is simplified by compression and merge. Finally, the optimal solution is obtained according to the maximum flow algorithm. Experiments show that the algorithm have a better effect on programs with high degree of function coupling.
Characteristic analysis of TCR β-chain CDR3 repertoire for pre- and post-liver transplantation

Liver cirrhosis of hepatitis B is an immune-related disease in which liver cells die during the body’s immune system activation to clear the virus, and the progress is closely related to T lymphocytes. T lymphocyte cells recognise antigens, specifically by major histocompatibility complex (MHC), through a membrane protein T cell receptor (TCR). Here, we used high throughput immune repertoire sequencing technique to study the characteristics and diversity of the TCR repertoire between patients who underwent liver transplantation and healthy controls (NC). We sequenced the TCR β-chain complementary-determining region 3 (CDR3) repertoire in peripheral blood mononuclear cells (PBMCs) from 6 liver transplantation patients before transplantation (Pre) and on the first (Post1) and seventh days (Post7) after transplantation along with 6 NC. We observed that the distributions of CDR3, VD indel, and DJ indel lengths were similar among the Pre, Post1, Post7 and NC groups. We found that the TCR repertoire diversity of transplantation groups was relatively lower compared to NC group. The Pre-group had more highly expanded T cell clones compared to Post1, Post7 and NC groups, and the diversity of the T cell repertoire of the Post7 group was significantly decreased compared to the Pre, Post1 and NC groups. In addition, we found our results also show that various TRBV expression increased and some public sequences at different time points after liver transplantation, and the expression levels of 3 TRBV segments and 2 TRBJ segments were also significantly different in Pre, Post1, Post7 and NC groups. Moreover, 1 aa sequence shared by all liver transplantation patients and 2 aa sequences shared by at least two groups, which may serve as biomarkers to monitor the immune status of liver transplant patients.
Enhancing Graph Kernels via Successive Embeddings

Graph kernels have recently emerged as a promising approach to perform machine learning on graph-structured data. A graph kernel implicitly embedds graphs in a Hilbert space and computes the inner product between these representations. However, the inner product operation greatly limits the representational power of kernels between graphs. In this paper, we propose to perform a series of successive embeddings in order to improve the performance of existing graph kernels and derive more expressive kernels. We first embed the input graphs in a Hilbert space using a graph kernel and then we embed them into another space by employing popular kernels for vector data (e.g., gaussian kernel). Our experiments on several datasets show that by composing kernels, we can achieve significant improvements in classification accuracy.
Randomized Method for Robust Principal Component Analysis

This1 paper proposes two fast randomized algorithms for solving the robust PCA problem. Alternating direction method is a popular technique to solve robust PCA problem, its dominant cost is SVD in each iteration. As randomized SVD methods have advantages in computing singular values of large-scale matrix, we combine ADM with randomized SVD methods and obtain two randomized ADM algorithms, named Randomized ADM and Extend Randomized ADM, the former of which is faster while later is more precise. We apply our algorithms to background modeling. Experimental results show that the computational time has been reduced significantly by both algorithms while the accuracy of the model is guaranteed.
Positive metacognitions about alcohol mediate the relationship between FKBP5 variability and problematic drinking in a sample of young women

Background Previous research has shown that polymorphisms in the FKBP5 gene are related to some psychiatric conditions, including alcohol dependence. These relationships are moderated by the level of adverse childhood experiences that one has undergone. Maladaptive metacognition, associated with symptoms of psychiatric disorders and disturbed emotional self-regulation, is also a strong predictor of problematic alcohol use. Recent studies suggest that maladaptive metacognitions may be part of the developmental pathway from childhood abuse to drinking problems. This study attempted to identify relationships between FKBP5 polymorphisms and metacognitions about the positive effects of alcohol use and problematic drinking in a group differing in levels of childhood trauma. Methods The sample studied was composed of 502 female participants aged 18–25 years (M=21.78; SD=1.84). Positive metacognitions about alcohol use were measured with the Positive Alcohol Metacognitions Scale (PAMS) and problematic drinking was gauged using the WHO Alcohol Use Disorders Identification Test. Levels of childhood adverse experiences were determined with the use of the Childhood Questionnaire. A total of 18 single-nucleotide polymorphisms (SNPs) in the FKBP5 gene were genotyped. Results We did not find any interaction between the gene and childhood trauma on problematic drinking or metacognitions. However we identified a strong main effect of two SNPs of the FKBP5 gene – rs755658 and rs1334894 – on the PAMS subscale measuring positive metacognitive beliefs about emotional self-regulation. We also found nominally significant relations of several other SNPs with metacognitions and problematic drinking. Additionally, we showed that positive alcohol metacognitions mediate the relationship between problematic drinking and both rs755658 and rs1334894. Conclusion Our results may shed some light on the biological underpinnings of the developmental pathway leading to problematic drinking through maladaptive metacognitions.