Miracle-dz/UniFAR-FTUs huggingface dataset:
The Multiway Relay Channel

The multiuser communication channel, in which multiple users exchange information with the help of a relay terminal, termed the multiway relay channel (mRC), is introduced. In this model, multiple interfering clusters of users communicate simultaneously, such that the users within the same cluster wish to exchange messages among themselves, i.e., each user multicasts its message to all the other users in its own cluster. It is assumed that the users cannot receive each other's signals directly. Hence, the relay terminal in this model is the enabler of communication. In particular, restricted encoders are considered, such that the encoding function of each user depends only on its own message and the received signal is used only for decoding the messages of the other users in the cluster. Achievable rate regions and an outer bound are characterized for the Gaussian mRC, and their comparison is presented in terms of the exchange rate, the symmetric rate point in the capacity region in a symmetric Gaussian mRC scenario. It is shown that the compress-and-forward (CF) protocol achieves exchange rates within a constant bit offset of the optimal exchange rate, independent of the power constraints of the terminals in the network. A finite bit gap between the exchange rates achieved by the CF and the amplify-and-forward protocols is also shown. The two special cases of the mRC, the full data exchange model, in which every user wants to receive messages of all other users, and the pairwise data exchange model which consists of multiple two-way relay channels, are investigated in detail. In particular for the pairwise data exchange model, in addition to the proposed random coding-based achievable schemes, a nested lattice coding-based scheme is also presented and is shown to achieve exchange rates within a constant bit gap of the exchange capacity.
Bathroom accident detection with 79GHz-band millimeter wave sensor

79GHz millimeter-wave radar has many advantages against image sensor, infrared sensor and microwave band radar. In this paper, we present a bathroom monitoring system using a 79GHz band sensor in order to prevent accidents caused by heat- shock and so on where a k-means clustering method is proposed to monitor the existence and motion of a bathing person. The measurement was conducted for various scenarios (normal bathing, falling, drowning, etc.) and the usefulness is discussed against waving from the surface of bathtub hot water. As a result, the estimated rate of the dangerous state is shown to be more than 90% for various bathing person’s movements in a bathroom.
Test on Gravity Distortion Effect of Concrete Filled Steel Tubular Single Arch Rib Under Shaking Tables

In order to understand the effects of gravity distortion on seismic responses under shaking table test, based on the theory of hybrid model of artificial mass, a CFST arch rib model scaled 1:10 was conducted under shaking tables. Five artificial masses were set up to realize the different gravity distortion parameters. Several earthquake waves and artificial waves with five time-compressive similarity coefficients were input both in the longitudinal direction and transverse direction in the test. The testing results indicate that the gravity distortion has great effects on the first natural vibration frequency of the model. The effects of gravity distortion on acceleration response of transverse direction are more significant than longitudinal direction. The effects of gravity distortion on acceleration response can be reduced by adjusting the complementary artificial mass of model.
Effect of Prolonged Hyperdynamic Endotoxemia on Jejunal Motility in Fasted and Enterally Fed Pigs

ObjectiveTo determine the effects of hyperdynamic endotoxemia on the motility of the small intestine. Summary Background DataMotility disorders of the gastrointestinal tract are a common complication of sepsis. It has been suggested that gram-negative endotoxin plays a role in the pathogenesis of the accompanying diarrhea frequently observed. MethodsPigs were infused with Escherichia coli lipopolysaccharide for a 24-hour period. During this fasting period jejunal motility was measured using ambulatory manometry. One and 4 days after cessation of endotoxin, pigs were enterally fed, and again motility was recorded. ResultsHyperdynamic endotoxemia was achieved in this model. Manometric pressure recordings revealed that endotoxin infusion accelerated the migrating motor complex (MMC) migration along the jejunum. Also, a simultaneous increase in MMC cycling frequency was observed in the endotoxin-treated group. Elevated MMC migration velocity and cycling frequency were maintained the following day after endotoxin during feeding and returned to basal values 4 days after endotoxin. ConclusionsA small dose of continuously infused endotoxin significantly provokes jejunal motility disturbances that may contribute to diarrhea.
Generative Adversarial Networks based X-vector Augmentation for Robust Probabilistic Linear Discriminant Analysis in Speaker Verification

Data augmentation is an effective method to increase the quantity of training data, which improves the model’s robustness and generalization ability. In this paper, we propose a generative adversarial network (GAN) based data augmentation approach for probabilistic linear discriminant analysis (PLDA), which is a standard back-end for state-of-the-art x-vector based speaker verification system. Instead of generating new spectral feature samples, a conditional Wasserstein GAN is adopted to directly generate x-vectors. Experiments are carried out on the standard NIST SRE 2016 evaluation dataset. Compared to manually adding noise, the GAN augmented PLDA achieves better performance and this performance can be further boosted when combined with manual augmented data. EER of 11.68% and 4.43% were obtained for Tagalog and Cantonese evaluation condition, respectively.
Magnetic Beads Enhance Adhesion of NIH 3T3 Fibroblasts: A Proof-of-Principle In Vitro Study for Implant-Mediated Long-Term Drug Delivery to the Inner Ear

Introduction Long-term drug delivery to the inner ear may be achieved by functionalizing cochlear implant (CI) electrodes with cells providing neuroprotective factors. However, effective strategies in order to coat implant surfaces with cells need to be developed. Our vision is to make benefit of electromagnetic field attracting forces generated by CI electrodes to bind BDNF-secreting cells that are labelled with magnetic beads (MB) onto the electrode surfaces. Thus, the effect of MB-labelling on cell viability and BDNF production were investigated. Materials and Methods Murine NIH 3T3 fibroblasts—genetically modified to produce BDNF—were labelled with MB. Results Atomic force and bright field microscopy illustrated the internalization of MB by fibroblasts after 24 h of cultivation. Labelling cells with MB did not expose cytotoxic effects on fibroblasts and allowed adhesion on magnetic surfaces with sufficient BDNF release. Discussion Our data demonstrate a novel approach for mediating enhanced long-term adhesion of BDNF-secreting fibroblasts on model electrode surfaces for cell-based drug delivery applications in vitro and in vivo. This therapeutic strategy, once transferred to cells suitable for clinical application, may allow the biological modifications of CI surfaces with cells releasing neurotrophic or other factors of interest.
The Scalability Challenge of Ethereum: An Initial Quantitative Analysis

The concerns held on the scalability of permissionless Blockchain platforms are a significant hindrance to their wider adoption. To address this issue rigorously, we consider it opportune to assess the current implementation and the associated improvement proposals, within a single coherent evaluation framework. This work addresses this specific question in the particular context of Ethereum, a prominent implementation of Blockchain, using a threefold approach. First, it maps the internal constituents of Ethereum onto a layered architecture inspired in the ISO/OSI model, so that its provisioning organization can be better understood. Second, it employs the AKF Scale Cube to analyze the pros and cons of the present specification of Ethereum, as well as of the current improvement proposals, so that the scalability challenges can be reasoned about in an orderly fashion. Finally, it uses an extensible test environment with synthetic benchmarks so that the transaction throughput of the current implementation of Ethereum can be evaluated in a private scenario, when no smart contract is to run. Our conclusions suggest that Ethereum respects the scalability trilemma being versed on security and decentralization renouncing scalability. These limits can be mitigated by adopting novel solutions such as Plasma and Sharding which enable a significant increment of performance by partitioning the data, and, ultimately, unlocking parallel execution of the transactions.
Vertex-Cut Partitioning Performance Analysis for FASTCD Algorithm in Large-Scale Graph

Large-scale graph processing has become a popular research topic in domain graph partitioning and community detection. FastCD is a community-based detection algorithm based on modularity optimization capable of detecting communities on large-scale graphs. Community detection on large graphs requires graph partitioning techniques that partition large-scale graphs into several subgraphs for processing carried out in parallel, so that computational loads can be distributed across machines in the cluster. The research was conducted on graph-parallel distributed framework, GraphX, which is a graph processing component in Spark. The strategies of vertex-cut partitioning method such as RandomVertexCut, CanonicalRandomVertexCut, EdgePartition1D, and EdgePartition2D applied to the FastCD to perform community detection on large scale graphs in parallel. Furthermore, EdgePartition1D has the best performance for FastCD performing parallel community detection on large-scale graphs with the number of edges 7,600,595 and vertices 685,230. The results of this research can be seen that the FastCD algorithm with EdgePartition1D and EdgePartition2D is able to maintain valuable information contained in graphs by considering vertices and neighboring edges quickly.
Measurements of a MOSFET sub-THz detector integrated with rectangular patch antenna

This paper presents a measurement-based analysis of operation of an example MOSFET detector integrated with a narrow-band patch antenna. First, responsivity of the detector was measured versus frequency of incident wave revealing two responsivity peaks, and then the antenna and the transistor were on-wafer probed to extract their impedances and antenna resonances in order to better explain the behavior of the detector.
Multispectral Texture Fidelity Measure

Automatic texture fidelity assessment that would correspond to the human visual perception is an important, but still unsolved computer vision problem with numerous useful applications in the various vision application areas such as image compression and modeling, video streaming or fast image database retrieval. The problem is not satisfyingly solved even for the most simple static monospectral texture representation thus progress in the automatic assessment of texture fidelity is required. We propose improved multiresolution texture fidelity measure based on Markovian random field texture model, which correlates well with human texture fidelity evaluation obtained from texture fidelity benchmark.
An empirical study on the impact of organizational memory on organizational performance in manufacturing companies

Knowledge is the important asset in organizations. Effective knowledge management plays a crucial role in organizational development. Organizational memory (OM) integrates all kinds of organizational knowledge. It is regarded as the central prerequisite for IT support of knowledge management. The paper analyzes the knowledge structure of OM in manufacturing company from internal and external sources of organizational knowledge. OM in manufacturing company is composed of four types, that is, managerial OM, technical OM, cultural OM and marketing OM. These four types of OM components enhance organizational development jointly. Based on the data from international manufacturing strategy survey (IMSS), factor analysis is used to test the classification of OM and organizational performance (OP), canonical correlation analysis is conducted on the impact of OM components on OP in manufacturing companies. The results from structural equation modeling suggest that OM is a dynamic factor, OM formed in different time has different impact on OP.
Trend Adjustment Prior to Testing for the Cointegrating Rank of a VAR Process

Testing the cointegrating rank of a vector autoregressive process which may have a deterministic linear trend is considered. Previous proposals for dealing with such a situation are either to allow for a deterministic trend term in computing a suitable test statistic or else remove the linear trend first and then derive the test statistic from the trend-adjusted data. In this study the latter approach is considered and a new, simple method for trend removal is proposed which is based on estimating the trend parameters under the null hypothesis. LR (likelihood ratio) and LM (Lagrange multiplier) type test statistics are derived on the basis of the trend-adjusted data and their asymptotic distributions are considered under the null hypothesis and under local alternatives. A simulation comparison with other proposals is performed which demonstrates the potentially superior small sample performance of the new tests.
Iris Recognition in Visible Wavelength: Impact and Automated Detection of Glasses

The prevalence of visual impairment around the world is rapidly increasing, causing large numbers of people to wear glasses. Glasses are generally considered an important noise source in iris recognition; under objective metrics, they have recently been shown to deteriorate the sample quality of near-infrared (NIR) ocular images (consequently impairing the segmentation accuracy and biometric performance). Automatically and robustly detecting glasses in ocular images is therefore one of the prerequisites for the acquisition of high quality iris samples. While this issue has recently been addressed for NIR ocular images, it remains an open issue in the visible wavelength (VW) spectrum. As the popularity of VW iris recognition increases (due to e.g. deployment of iris recognition in consumer grade mobile devices and general improvements in VW recognition algorithms), it becomes a matter of interest to quantitatively evaluate the impact of glasses on such systems, as well as develop methods for automatic detection of glasses in VW ocular images. In this paper, the impact of glasses on VW iris segmentation performance is investigated using the UBIRISv2 and MobBIO iris databases. It is shown that the presence of glasses significantly degrades the accuracy of iris segmentation. In addition, a state-of-the-art iris segmentation method which can perform a semantic segmentation of ocular images (including the segmentation of glasses) is employed for the purpose of glasses detection. On the used databases, correct classification rates (CCRs) of 98.57% and 83.62% are obtained, respectively.
Sequential replication-coupled destruction at G1/S ensures genome stability

In this study, Coleman et al. investigated the temporal order of protein degradation among substrates of a single human E3 ubiquitin ligase, CRL4Cdt2, triggered by DNA synthesis. They show that differential CRL4Cdt2 targeting is regulated by a PCNA-interacting motif or “PIP degron” by manipulating the order of substrate degradation. These findings demonstrate that consecutive protein degradation is critical for normal S-phase progression.
Role of large arteries in regulation of blood flow to brain stem in cats.

1. The goal of this study was to examine the regulation of resistance in the large arteries and small vessels that supply the brain stem. 2. We used a new method in anaesthetized cats to measure blood flow to the medulla (microspheres) and pressure (servo‐null) in branches of the basilar artery that supply the medulla. Resistance was determined during normocapnia, hypercapnia, hypocapnia and seizures (produced with intravenous bicuculline). 3. Pressure in arteries that supply the medulla (150 microns internal diameter) was 71 +/‐ 4% (mean +/‐ S.E. of mean) of aortic pressure and large artery resistance was 31 +/‐ 4% of the total resistance in the medulla. Hypercapnia and seizures decreased large artery resistance by 67 and 50%, respectively, and hypocapnia increased large artery resistance by 58%. Small vessel resistance decreased by 82% during hypercapnia and by 43% during seizures, and increased by 96% during hypocapnia. 4. Thus, resistance of the large arteries (greater than 150 microns diameter) accounts for about one‐third of the total vascular resistance in the brain stem. Both large arteries and small vessels respond to alterations in arterial carbon dioxide tension and seizures, and contribute to the regulation of blood flow to the brain stem.
The Jülich Experience With Simultaneous 3T MR-BrainPET: Methods and Technology

Building on the success of positron emission tomography (PET)/CT scanners, a hybrid imaging technology, combining PET with the versatile attributes of magnetic resonance imaging (MRI), has been in use for over ten years. At the Forschungszentrum Jülich, one of the four prototypes available worldwide, combining a commercial 3T MRI with a newly developed BrainPET insert, was installed in 2008, allowing simultaneous data acquisition with PET and MRI. Here, we report on our ten-year-long experience of the methods and technology developed through this paper with numerous patients and volunteers. In the course of our research, a number of different radiotracers, such as [18F]Fluoroethyltyrosine, [11C]Flumazenil, [11C]Raclopride, and [15O]H2O, have been applied while simultaneously measuring several different MR sequences. The PET data obtained with the BrainPET has demonstrated higher image quality and superior resolution capability compared to the stand-alone PET scanner, ECAT Exact HR+. Furthermore, the simultaneous acquisition of MR images alongside BrainPET scans, using different sequences, showed an excellent quality without any relevant artifacts and provided useful complementary information. Our experiences with the hybrid 3T MR-BrainPET indicate a promising basis for further developments of this unique technique, allowing simultaneous brain imaging in a clinical setting.
The relationship between cough-specific quality of life and abdominal muscle endurance, fatigue, and depression in patients with COPD

Background Cough is a prevalent symptom that impacts quality of life in COPD. The aim of this study was to assess the relationship between cough-specific quality of life, abdominal muscle endurance, fatigue, and depression in stable patients with COPD. Methods Twenty-eight patients with COPD (mean age 60.6±8.7 years) referred for pulmonary rehabilitation participated in this cross-sectional study. Sit-ups test was used for assessing abdominal muscle endurance. Leicester Cough Questionnare (LCQ) was used to evaluate symptom-specific quality of life. Fatigue perception was evaluated with Fatigue Impact Scale (FIS). Beck Depression Inventory (BDI) was used for assessing depression level. Results The LCQ total score was significantly associated with number of sit-ups; BDI score; FIS total; physical, cognitive, and psychosocial scores (P<0.05). Scores of the LCQ physical, social, and psychological domains were also significantly related with number of sit-ups, FIS total score, and BDI score (P<0.05). FIS total score and number of sit-ups explained 58% of the variance in LCQ total score (r=0.76, r2=0.577, F(2–20)=12.296, P<0.001). Conclusion Chronic cough may adversely affect performance in daily life due to its negative effect on fatigue and decrease abdominal muscle endurance in patients with COPD. Decreased cough-related quality of life is related with increased level of depression in COPD patients. Effects of increased abdominal muscle endurance and decreased fatigue in COPD patients with chronic cough need further investigation.
Oriented Tracklets Approach for Anomalous Scene Detection in High Density Crowd

Anomalous scene detection in high density crowd has become a topic of great interest for public safety at the venues of mass gatherings. In this paper, we proposed an anomalous crowd scene detection approach in active contour region. To this end, the oriented tracklets are extracted and analyzed in active contour region. The idea of active contouring helps in minimizing the tracking region. The extracted oriented tracklets are quantized into histogram bins based on their flow direction. For each bin of histogram, an entropy and temporal occupancy measures are computed for every temporal window of some frames. The huge deviation in both measures between temporal windows indicates the occurrence of an abnormal state of motion in the scene. Experiments have been conducted on publicly available UCF Web and Violent Flows datasets, and obtained interesting results. The proposed approach is compared with various stat-of-the-art methods against ROC curve and achieve remarkable accuracy while maintain lower computational complexity.
A contextual model of information literacy

This article reports a contextual model of information literacy (IL) which emerged from an exploratory case study of IL in a joint online distance learning (ODL) Geographic Information Sciences/Systems (GIS) programme, and demonstrates how it contributes to the development of information literate GIS learners in ODL environments. Adopting Eisenhardt’s (1989) ‘process of building theories from case study research’, it explores IL in the context of a wide range of teaching and learning experiences in the programme, using interview, questionnaire, students’ reflection, observation and document study as data collection methods. The two-level within- and across-case analysis, suggested by Eisenhardt, was innovatively combined with grounded theory data analysis approaches. It appeared that in the ODL GIS programmes IL is needed, not just as a set of transferable skills, but as an enabler for independent, connective, transferable and lifelong learning.
Application of Radial Basis Function Interpolation for Content Aware Image Retargeting

Several imaging and graphics applications usually require the resizing/retargeting of the spatial resolution of a given image. In real time applications, the retargeting process is expected to be computationally fast and free of any visually disturbing structural distortions. Accordingly, several content-aware retargeting methods, which resize images while preserving important image structures, have been introduced. However, it has also been shown that finding a single method that can be effectively applicable in all types of situation is very challenging. Specifically, many of the existing methods are not capable of avoiding visible structural distortions during high level of image squeezing or stretching processes. The distortions become even more evident with the presence of numerous high frequency contents. Accordingly, we have proposed a new and efficient image retargeting method which is based on Radial Basis Function (RBF) interpolation. We have introduced a novel pre-processing step and modifications to the generic form of the RBF interpolation technique for a better structural as well as size preservation of important image regions. The method is finally evaluated with respect to prior retargeting methods and leads to improved performances, both in terms of quality and complexity measures.