Miracle-dz/UniFAR-FTUs huggingface dataset:
A Study of Language and Classifier-independent Feature Analysis for Vocal Emotion Recognition

Every speech signal carries implicit information about the emotions, which can be extracted by speech processing methods. In this paper, we propose an algorithm for extracting features that are independent from the spoken language and the classification method to have comparatively good recognition performance on different languages independent from the employed classification methods. The proposed algorithm is composed of three stages. In the first stage, we propose a feature ranking method analyzing the state-of-the-art voice quality features. In the second stage, we propose a method for finding the subset of the common features for each language and classifier. In the third stage, we compare our approach with the recognition rate of the state-of-the-art filter methods. We use three databases with different languages, namely, Polish, Serbian and English. Also three different classifiers, namely, nearest neighbour, support vector machine and gradient descent neural network, are employed. It is shown that our method for selecting the most significant language-independent and method-independent features in many cases outperforms state-of-the-art filter methods.
Detecting Incremental Frequent Subgraph Patterns in IoT Environments

As graph stream data are continuously generated in Internet of Things (IoT) environments, many studies on the detection and analysis of changes in graphs have been conducted. In this paper, we propose a method that incrementally detects frequent subgraph patterns by using frequent subgraph pattern information generated in previous sliding window. To reduce the computation cost for subgraph patterns that occur consecutively in a graph stream, the proposed method determines whether subgraph patterns occur within a sliding window. In addition, subgraph patterns that are more meaningful can be detected by recognizing only the patterns that are connected to each other via edges as one pattern. In order to prove the superiority of the proposed method, various performance evaluations were conducted.
Super Diffusion for Salient Object Detection

One major branch of saliency object detection methods are diffusion-based which construct a graph model on a given image and diffuse seed saliency values to the whole graph by a diffusion matrix. While their performance is sensitive to specific feature spaces and scales used for the diffusion matrix definition, little work has been published to systematically promote the robustness and accuracy of salient object detection under the generic mechanism of diffusion. In this work, we firstly present a novel view of the working mechanism of the diffusion process based on mathematical analysis, which reveals that the diffusion process is actually computing the similarity of nodes with respect to the seeds based on diffusion maps. Following this analysis, we propose super diffusion, a novel inclusive learning-based framework for salient object detection, which makes the optimum and robust performance by integrating a large pool of feature spaces, scales and even features originally computed for non-diffusion-based salient object detection. A closed-form solution of the optimal parameters for the integration is determined through supervised learning. At the local level, we propose to promote each individual diffusion before the integration. Our mathematical analysis reveals the close relationship between saliency diffusion and spectral clustering. Based on this, we propose to re-synthesize each individual diffusion matrix from the most discriminative eigenvectors and the constant eigenvector (for saliency normalization). The proposed framework is implemented and experimented on prevalently used benchmark datasets, consistently leading to state-of-the-art performance.
Smart Ocean: A New Fast Deconvolved Beamforming Algorithm for Multibeam Sonar

A new fast deconvolved beamforming algorithm is proposed in this paper, and it can greatly reduce the computation complexity of the original Richardson–Lucy (R–L algorithm) deconvolution algorithm by utilizing the convolution theorem and the fast Fourier transform technique. This algorithm makes it possible for real-time high-resolution beamforming in a multibeam sonar system. This paper applies the new fast deconvolved beamforming algorithm to a high-frequency multibeam sonar system to obtain a high bearing resolution and low side lobe. In the sounding mode, it restrains the tunnel effect and makes the topographic survey more accurate. In the 2D acoustic image mode, it can obtain clear images, more details, and can better distinguish two close targets. Detailed implementation methods of the fast deconvolved beamforming are given, its computational complexity is analyzed, and its performance is evaluated with simulated and real data.
Association of Candidate Genes with Response to Heat and Newcastle Disease Virus

Newcastle disease is considered the number one disease constraint to poultry production in low and middle-income countries, however poultry that is raised in resource-poor areas often experience multiple environmental challenges. Heat stress has a negative impact on production, and immune response to pathogens can be negatively modulated by heat stress. Candidate genes and regions chosen for this study were based on previously reported associations with response to immune stimulants, pathogens, or heat, including: TLR3, TLR7, MX, MHC-B (major histocompatibility complex, gene complex), IFI27L2, SLC5A1, HSPB1, HSPA2, HSPA8, IFRD1, IL18R1, IL1R1, AP2A2, and TOLLIP. Chickens of a commercial egg-laying line were infected with a lentogenic strain of NDV (Newcastle disease virus); half the birds were maintained at thermoneutral temperature and the other half were exposed to high ambient temperature before the NDV challenge and throughout the remainder of the study. Phenotypic responses to heat, to NDV, or to heat + NDV were measured. Selected SNPs (single nucleotide polymorphisms) within 14 target genes or regions were genotyped; and genotype effects on phenotypic responses to NDV or heat + NDV were tested in each individual treatment group and the combined groups. Seventeen significant haplotype effects, among seven genes and seven phenotypes, were detected for response to NDV or heat or NDV + heat. These findings identify specific genetic variants that are associated with response to heat and/or NDV which may be useful in the genetic improvement of chickens to perform favorably when faced with pathogens and heat stress.
Evaluating a Deep-Learning System for Automatically Calculating the Stroke ASPECT Score

The stroke is one of the leading causes of death around the world. It is a dangerous disease that results in a permanent disability. CT and MRI are representative imaging diagnostic tools for diagnosing the stroke. Particularly, CT has an advantage of examining the disease quickly. The Alberta Stroke Program Early CT Score (ASPECTS) is widely used as a tool to demonstrate the severity of the stroke based on CT images. However, it has a scoring variability issue among medical experts. This study proposed an object and automated ASPECT Score estimation system based on the image processing and deep learning technology for resolving the issue.
CARM1 methylates MED12 to regulate its RNA-binding ability

CARM1 methylates MED12 at arginine 1899 to generate a TDRD3 binding site, which in turn regulates the ability of mediator to interact with activating ncRNAs and modulate gene expression. The coactivator-associated arginine methyltransferase (CARM1) functions as a regulator of transcription by methylating a diverse array of substrates. To broaden our understanding of CARM1's mechanistic actions, we sought to identify additional substrates for this enzyme. To do this, we generated CARM1 substrate motif antibodies, and used immunoprecipitation coupled with mass spectrometry to identify cellular targets of CARM1, including mediator complex subunit 12 (MED12) and the lysine methyltransferase KMT2D. Both of these proteins are implicated in enhancer function. We identified the major CARM1-mediated MED12 methylation site as arginine 1899 (R1899), which interacts with the Tudor domain–containing effector molecule, TDRD3. Chromatin immunoprecipitation–seq studies revealed that CARM1 and the methyl mark it deposits are tightly associated with ERα-specific enhancers and positively modulate transcription of estrogen-regulated genes. In addition, we showed that the methylation of MED12, at the R1899 site, and the recruitment of TDRD3 by this methylated motif are critical for the ability of MED12 to interact with activating noncoding RNAs.
Bone marrow–derived fibroblasts are a functionally distinct stromal cell population in breast cancer

Cancer-associated fibroblasts (CAFs) are highly prominent in breast tumors, but their functional heterogeneity and origin are still largely unresolved. We report that bone marrow (BM)–derived mesenchymal stromal cells (MSCs) are recruited to primary breast tumors and to lung metastases and differentiate to a distinct subpopulation of CAFs. We show that BM-derived CAFs are functionally important for tumor growth and enhance angiogenesis via up-regulation of Clusterin. Using newly generated transgenic mice and adoptive BM transplantations, we demonstrate that BM-derived fibroblasts are a substantial source of CAFs in the tumor microenvironment. Unlike resident CAFs, BM-derived CAFs do not express PDGFR&agr;, and their recruitment resulted in a decrease in the percentage of PDGFR&agr;-expressing CAFs. Strikingly, decrease in PDGFR&agr; in breast cancer patients was associated with worse prognosis, suggesting that BM-derived CAFs may have deleterious effects on survival. Therefore, PDGFR&agr; expression distinguishes two functionally unique CAF populations in breast tumors and metastases and may have important implications for patient stratification and precision therapeutics.
Prognosis of Young Survivors of Gastric Cancer in China and the U.S.: Determining Long-Term Outcomes Based on Conditional Survival.

BACKGROUND Young survivors of gastric cancer (GC) have better prognoses than elderly patients, yet their disease-specific survival (DSS) has received little attention. PATIENTS AND METHODS Data on young patients (aged ≤40 years) with GC undergoing resections at three Chinese institutions (n = 542) and from the SEER database (n = 533) were retrospectively analyzed. Three-year conditional disease-specific survival (CS3) was assessed. The effects of well-known prognostic factors over time were analyzed by time-dependent Cox regression. RESULTS Overall, young Chinese patients with GC had a better 5-year DSS than U.S. patients (62.8% vs. 54.1%; p < .05). The disease-specific mortality likelihood of the entire cohort was not constant over time, with most deaths occurring during the first 3 years after surgery but peaking at 1 and 2 years in China and the U.S., respectively. Based on 5-year survivorship, the CS3 rates of both groups were similar (90.9% [U.S.] vs. 91.5% [China]; p > .05). Cox regression showed that for Chinese patients, site, size, T stage, and N stage were independent prognostic factors at baseline (p < .05). For U.S. patients, grade, T stage. and N stage significantly affected DSS at baseline (p < .05). In both groups, only T stage continuously affected DSS within 3 years after gastrectomy. However, for both groups, the initial well-known prognostic factors lost prognostic significance after 5 years of survival (all p > .05). Although the 5-year DSS rates of young Chinese patients with T3 and T4a disease were significantly better than those of young U.S. patients, in each T stage, the CS3 of both regions trended toward consistency over time. CONCLUSION For young patients with GC, the factors that predict survival at baseline vary over time. Although the initial 5-year DSS is heterogeneous, insight into conditional survival will help clinicians evaluate the long-term prognoses of survivors while ignoring population differences. IMPLICATIONS FOR PRACTICE With the increasing number of young survivors of gastric cancer (GC), it is essential for clinicians to understand the dynamic prognosis of these patients. Based on large data sets from China and the U.S., this study found that the prognostic factors that predict survival for young patients with GC at baseline vary over time. Although the initial 5-year disease-specific survival is heterogeneous, insight into conditional survival will help clinicians evaluate the long-term prognoses of survivors while ignoring population differences. This knowledge may be more effective in helping young patients with GC to manage future uncertainties, especially when they need to make important life plans.
Activity Recognition Using Gazed Text and Viewpoint Information for User Support Systems

The development of information technology has added many conveniences to our lives. On the other hand, however, we have to deal with various kinds of information, which can be a difficult task for elderly people or those who are not familiar with information devices. A technology to recognize each person’s activity and providing appropriate support based on that activity could be useful for such people. In this paper, we propose a novel fine-grained activity recognition method for user support systems that focuses on identifying the text at which a user is gazing, based on the idea that the content of the text is related to the activity of the user. It is necessary to keep in mind that the meaning of the text depends on its location. To tackle this problem, we propose the simultaneous use of a wearable device and fixed camera. To obtain the global location of the text, we perform image matching using the local features of the images obtained by these two devices. Then, we generate a feature vector based on this information and the content of the text. To show the effectiveness of the proposed approach, we performed activity recognition experiments with six subjects in a laboratory environment.
The Performance of Blum-Blum-Shub Elliptic Curve Pseudorandom Number Generator as WiFi Protected Access 2 Security Key Generator

WiFi Protected Access 2 (WPA2) is considered the most secure network security protocol in wireless routers, despite the discovery of partial key exposure vulnerability. In light of, an experiment was conducted to investigate the strength of WPA2 default passwords generated by the algorithms embedded in routers using a simulated brute-force attack. The findings ascertain the prevalence of insecurities in the default WPA2 passwords due to low charset size and weak encryption algorithm. For these reasons, we propose Blum-Blum-Shub Elliptic Curve Pseudorandom Number Generator (BBS-ECPRNG) algorithm as a replacement to the algorithms embedded in routers. To prove its validity, we generated distinct sequences of 106 bits each and analyzed sequence output using the NIST statistical test suite. The generated bit sequence of BBS-ECPRNG was converted to password characters and subjected to simulation test. Findings reveal that the BBS-ECPRNG password significantly decreased the password-cracking success by 25 times more as compared to the default WPA2 passwords generated by router-based algorithms in the Philippine market.
Contextual Anonymization for Secondary Use of Big Data in Biomedical Research: Proposal for an Anonymization Matrix

Background The current law on anonymization sets the same standard across all situations, which poses a problem for biomedical research. Objective We propose a matrix for setting different standards, which is responsive to context and public expectations. Methods The law and ethics applicable to anonymization were reviewed in a scoping study. Social science on public attitudes and research on technical methods of anonymization were applied to formulate a matrix. Results The matrix adjusts anonymization standards according to the sensitivity of the data and the safety of the place, people, and projects involved. Conclusions The matrix offers a tool with context-specific standards for anonymization in data research.
Persistent restoration to the immunosupportive tumor microenvironment in glioblastoma by bevacizumab

Although vascular endothelial growth factor (VEGF) promotes the immunosuppressive microenvironment, the efficacy of bevacizumab (Bev) on tumor immunity has not been fully investigated. The present study used 47 glioblastoma tissues obtained at 3 different settings: tumors of initial resection (naïve Bev group), tumors resected following Bev therapy (effective Bev group), and recurrent tumors after Bev therapy (refractory Bev group). The paired samples of the initial and post‐Bev recurrent tumors from 9 patients were included. The expression of programmed cell death‐1 (PD‐1)/PD ligand‐1 (PD‐L1), CD3, CD8, Foxp3, and CD163 was analyzed by immunohistochemistry. The PD‐L1+ tumor cells significantly decreased in the effective or refractory Bev group compared with the naïve Bev group (P < .01 for each). The PD‐1+ cells significantly decreased in the effective or refractory Bev group compared with the naïve Bev group (P < .01 for each). The amount of CD3+ and CD8+ T cell infiltration increased in the refractory Bev group compared with the naïve Bev group (CD3, P < .01; CD8, P = .06). Both Foxp3+ regulatory T cells and CD163+ tumor‐associated macrophages significantly decreased in the effective or refractory Bev group compared with the naïve Bev group (Foxp3, P < .01 for each; CD163, P < .01 for each). These findings were largely confirmed by comparing paired initial and post‐Bev recurrent tumors. Bevacizumab restores the immunosupportive tumor microenvironment in glioblastomas, and this effect persists during long‐term Bev therapy.
PSYCHOMETRIC PROPERTIES OF FUNCTIONAL CAPACITY TESTS IN CHILDREN AND ADOLESCENTS: SYSTEMATIC REVIEW

ABSTRACT Objectives: To identify studies that evaluated psychometric properties of functional capacity tests in children and adolescents, and to verify which of these have satisfactory properties of measurement. Data sources: Searches on MEDical Literature Analysis and Retrieval System Online (MEDLINE), Cumulative Index to Nursing and Allied Health Literature (CINAHL) and Scientific Electronic Library Online (SciELO) databases without limiting period or language. Two investigators independently selected articles based on the following inclusion criteria: children and/or adolescent population (healthy or with cardiorespiratory diseases); and assessment of psychometric properties of functional capacity tests. Studies with (I) adult samples, (II) sample with neurological diseases, and (III) on reference values or prediction equations only were excluded. Data synthesis: From the total of 677 articles identified, 11 were selected. These evaluated the psychometric properties of the following tests: 6-minute walk test (6MWT) (n=7); 6MWT and the 3-minute step test (3MST) (n=1); and Incremental Shuttle Walk Test (ISWT) (n=3). Reproducibility and reliability were good for 6MWT and ISWT, and moderate for 3MST. The ISWT showed high validity measures for both healthy children and children with chronic respiratory disease. The validity of 6MWT varied across studies, and should be analyzed according to the health conditions of test takers. The validity of 3MST is unclear, and further studies in pediatric population are required. Conclusions: Most studies investigated 6MWT measurement properties. Validity of 6MWT varied according to different pediatric populations. The use of 6MWT, ISWT and 3MST tests to measure clinically important changes in children and adolescents with cardiorespiratory diseases is still unclear.
A Study on 3D Surface Graph Representations

Surface graphs have been used in many application domains to represent three-dimensional (3D) data. Another approach to representing 3D data is making projections onto two-dimensional (2D) graphs. This approach will result in multiple displays, which is time-consuming in switching between different screens for a different perspective. In this work, we study the performance of 3D version of popular 2D visualization techniques for time series: horizon graph, small multiple, and simple line graph. We explore discrimination tasks with respect to each visualization technique that requires simultaneous representations. We demonstrate our study by visualizing saturated thickness of the Ogallala aquifer - the Southern High Plains Aquifer of Texas in multiple years. For the evaluation, we design comparison and discrimination tasks and automatically record result performed by a group of students at a university. Our results show that 3D small multiples perform well with stable accuracy over numbers of occurrences. On the other hand, shared-space visualization within a single 3D coordinate system is more efficient with small number of simultaneous graphs. 3D horizon graph loses its competence in the 3D coordinate system with the lowest accuracy comparing to other techniques. Our demonstration of 3D spatial-temporal is also presented on the Southern High Plains Aquifer of Texas from 2010 to 2016.
Transfer of rosuvastatin into breast milk: liquid chromatography–mass spectrometry methodology and clinical recommendations

Introduction Rosuvastatin reduces concentrations of total cholesterol (TC) and is used for the management of hypercholesterolemia and prevention of acute coronary syndromes. There are no published reports estimating infant exposure to rosuvastatin through breast milk. Purpose The aims of this study were to quantify concentrations of rosuvastatin in human milk and plasma from a lactating woman taking rosuvastatin and to investigate potential infant exposure. Materials and methods A 38-year-old breastfeeding mother was commenced on rosuvastatin 20 mg daily for secondary prevention of an acute coronary syndrome. Eight maternal breast milk samples and a single plasma sample were collected over a 24-hour period. The samples were quantified using a sensitive liquid chromatography–mass spectrometry (LC-MS/MS) method. Results The average concentration of rosuvastatin in breast milk was 30.84 ng/mL, and a peak concentration of 58.59 ng/mL occurred at 17 hours after oral administration. Although the milk-to-plasma (M/P) ratio was 16.49 at 14 hours, the theoretical infant dosage (TID) and relative infant dose (RID) were 0.005 mg/kg/day and 1.50%, respectively. Conclusion The findings suggest that only small amounts of rosuvastatin pass into breast milk. Should the maternal condition necessitate treatment, consideration could be given to the use of rosuvastatin during breastfeeding provided the infant is monitored.
RM-KVStore: New MXNet KVStore to Accelerate Transfer Performancewith RDMA

Large-scale distributed machine learning (ML) systems need to transfer a large number of parameters, introducing high communication overhead which imposes a negative impact on the performance significantly. In recent years, the network interface cards of Ethernet and InfiniBand mostly support RDMA (Remote Direct Memory Access) technology, which provides superior communication performance, whereas, many of these systems such as MXNet has not benefited from the new technology yet. MXNet is one of these state-of-the-art distributed ML systems, and KVStore is its key module for parameter synchronization. In this paper we describe the design and implementation of RM-KVStore, a new highperformance RDMA-capable MXNet KVStore that exploits RDMA to improve throughput by providing memory pool and different mechanisms for small and large messages to achieve high time-efficient transfer. Experimental results show that, our RM-KVStore outperforms the KVStore over IPoIB and TCP/IP by 225% and 331% on average in terms of the push performance, respectively. And for the pull operation, RMKVStore achieves higher performance than the KVStore over IPoIB and TCP/IP by 141% and 247% on average, respectively. Consequently, the overall performance of MXNet is improved by 112% and 142% respectively compared with running on IPoIB and TCP/IP.