Miracle-dz/UniFAR-FTUs huggingface dataset:
Raw Multi-Channel Audio Source Separation using Multi- Resolution Convolutional Auto-Encoders

Supervised multi-channel audio source separation requires extracting useful spectral, temporal, and spatial features from the mixed signals. the success of many existing systems is therefore largely dependent on the choice of features used for training. In this work, we introduce a novel multi-channel, multiresolution convolutional auto-encoder neural network that works on raw time-domain signals to determine appropriate multiresolution features for separating the singing-voice from stereo music. Our experimental results show that the proposed method can achieve multi-channel audio source separation without the need for hand-crafted features or any pre- or post-processing.
Low-voltage ride-through capability enhancement of a grid-connected photovoltaic/wind hybrid power system

This paper proposes an effective control strategy to enhance the Low-Voltage Ride-Through (LVRT) capability of photovoltaic (PV)/wind hybrid power system. The proposed LVRT strategy is implemented by modification of the control strategy for the hybrid power system. During the severe grid faults, the Maximum Power Point Tracking (MPPT) technique of the boost converter is disabled and the inverter is employed to inject reactive power for enhancing the LVRT capability of PV station. On the other hand, the outer crowbar protection system is activated for enhancing the LVRT capability of wind farm during the grid faults. The effectiveness of the proposed LVRT strategy is evaluated during a voltage sag, symmetrical fault and unsymmetrical fault in the electrical grid. The simulation results show that the proposed LVRT strategy improves the dynamic performance of hybrid power system during and after grid faults, fulfills the German grid code requirements, and protects the power electronic interfaces from overvoltage.
Joint multi-feature fusion and attribute relationships for facial attribute prediction

Predicting facial attributes from wild images is very challenging due to complex face variations. The key to this problem is to construct rich facial representations and take advantage of attribute relationships. In this paper, we propose a novel multi-task convolutional neural network (MTCNN) and a supervision signal called Online Batch Relation Loss (OBRL) for face attribute prediction in the wild. In particular, MTCNN builds informative facial features by embedding identity, age and race features from IdentityNet, AgeNet and RaceNet respectively. In addition, OBRL can diminish distribution shift of attribute relationships by mining attribute correlation within each minibatch, while it penalizes the probability divergence between a pair of attributes. In order to learn discriminative attribute features, we feed AttributeNet with fused facial features and partition attributes into nine groups to share intra-group features and reduce redundant computation. Finally, AttributeNet is optimized with the joint supervision of Cross Entropy Loss and OBRL. Experiments on CelebA and LFWA show that the proposed method outperforms the state-of-the-art methods with a significant margin.
Adaptive MPPT for PV systems under partial shadow condition and different loads using advanced optimization techniques

This work is aimed to enhance the efficiency of the PV system by using modern techniques such as Deterministic Particle Swarm Optimization (DPSO) and Modified Firefly Algorithm (MFA) by extracting the maximum available power from PV modules under different shadow patterns and different load impedances. The main function of each algorithm is to find the optimal duty cycle at which maximum power is transferred to the load. Moreover, a comparative study is carried out between the switching modes DC/DC converters (BOOST and BUCK-BOOST) used in this study The simulation results are compared with the MATLAB/SIMULINK model. The results verified that, the modern techniques have the ability to extract the extreme power from the shaded PV array in high accuracy. Furthermore, the BUCK-BOOST DC converter is more reliable and outperforms the BOOST converter at different shadow patterns and load impedance. Since it has the potentiality of stepping up/down the generated voltage to have Maximum power point (MPP).
Accelerometer- versus questionnaire-based assessment of physical activity and their changes over time in patients with COPD

Background and objective Physical activity (PA) is an important outcome parameter in patients with COPD regarding hospitalizations and mortality. Both objective assessment by accelerometers and self-evaluation by questionnaires were used in studies investigating PA in COPD. Whether self-reported questionnaires can adequately reflect PA and its changes over time compared to objective assessments has not been thoroughly investigated in COPD. In this COPD cohort study, we evaluated whether PA measured by accelerometer and its annual changes can also be assessed by self-reported questionnaires. Methods In 178 COPD patients with at least two assessments of PA, the agreement between objectively measured and self-reported activity was analyzed by Bland–Altman plots. Daily PA was assessed by a triaxial activity monitor over 1 week and by the self-reported German PA questionnaire 50+. Results Comparison between the two methods of measurement revealed no convincing agreement with a mean difference and limits of agreement (±1.96 standard deviation [SD]) of time spent in at least moderate PA (>3 metabolic equivalent of task [MET]) of −77.6 (−340.3/185.2) min/day, indicating a self-reported overestimation of PA by the questionnaire. The mean difference and limits of agreement (±1.96SD) in the annual change of PA was 1.2 min/day (−208.2/282.6 min/day), showing also a poor agreement on an individual level. Conclusion Evaluation of objectively measured and self-reported PA and their annual changes revealed no agreement in patients with COPD. Therefore, the evaluated questionnaire seems not helpful for measurement of PA and its changes over time.
Numerical Approach to Solving Problems of Two-Phase Multicomponent Flow in Porous Medium Based on Finite Volume Method

The article describes the numerical approach uniting finite volume method, Newton method and one of the MUSCL-type schemes for convective transport approximation for gas mixture components concentrations displaced by the water out of the porous medium. Numerical and analytical solutions for the case of radial two-dimensional flow of incompressible gas mixture and water have been compared. The obtained results allow considering the offered algorithm to be effective.
Inventory of anthropogenic methane emissions in mainland China from 1980 to 2010

Abstract. Methane (CH4) has a 28-fold greater global warming potential than CO2 over 100 years. Atmospheric CH4 concentration has tripled since 1750. Anthropogenic CH4 emissions from China have been growing rapidly in the past decades and contribute more than 10 % of global anthropogenic CH4 emissions with large uncertainties in existing global inventories, generally limited to country-scale statistics. To date, a long-term CH4 emission inventory including the major sources sectors and based on province-level emission factors is still lacking. In this study, we produced a detailed annual bottom-up inventory of anthropogenic CH4 emissions from the eight major source sectors in China for the period 1980–2010. In the past 3 decades, the total CH4 emissions increased from 24.4 [18.6–30.5] Tg CH4 yr−1 in 1980 (mean [minimum–maximum of 95 % confidence interval]) to 44.9 [36.6–56.4] Tg CH4 yr−1 in 2010. Most of this increase took place in the 2000s decade with averaged yearly emissions of 38.5 [30.6–48.3] Tg CH4 yr−1. This fast increase of the total CH4 emissions after 2000 is mainly driven by CH4 emissions from coal exploitation. The largest contribution to total CH4 emissions also shifted from rice cultivation in 1980 to coal exploitation in 2010. The total emissions inferred in this work compare well with the EPA inventory but appear to be 36 and 18 % lower than the EDGAR4.2 inventory and the estimates using the same method but IPCC default emission factors, respectively. The uncertainty of our inventory is investigated using emission factors collected from state-of-the-art published literatures. We also distributed province-scale emissions into 0.1° × 0.1° maps using socioeconomic activity data. This new inventory could help understanding CH4 budgets at regional scale and guiding CH4 mitigation policies in China.
Dynamic Deep Neural Networks: Optimizing Accuracy-Efficiency Trade-offs by Selective Execution

We introduce Dynamic Deep Neural Networks (D2NN), a new type of feed-forward deep neural network that allows selective execution. Given an input, only a subset of D2NN neurons are executed, and the particular subset is determined by the D2NN itself. By pruning unnecessary computation depending on input, D2NNs provide a way to improve computational efficiency. To achieve dynamic selective execution, a D2NN augments a feed-forward deep neural network (directed acyclic graph of differentiable modules) with controller modules. Each controller module is a sub-network whose output is a decision that controls whether other modules can execute. A D2NN is trained end to end. Both regular and controller modules in a D2NN are learnable and are jointly trained to optimize both accuracy and efficiency. Such training is achieved by integrating backpropagation with reinforcement learning. With extensive experiments of various D2NN architectures on image classification tasks, we demonstrate that D2NNs are general and flexible, and can effectively optimize accuracy-efficiency trade-offs.
The noninvasive simultaneous measurement of tissue oxygenation and microvascular hemodynamics during incremental handgrip exercise.

Limb blood flow increases linearly with exercise intensity; however, invasive measurements of muscle microvascular blood flow during incremental exercise have demonstrated submaximal plateaus. We tested the hypotheses that 1) brachial artery blood flow (Q̇BA) would increase with increasing exercise intensity until task failure, 2) blood flow index of the flexor digitorum superficialis (BFIFDS) measured noninvasively via diffuse correlation spectroscopy would plateau at a submaximal work rate, and 3) muscle oxygenation characteristics (total-[heme], deoxy-[heme], and percentage saturation) measured noninvasively with near-infrared spectroscopy would demonstrate a plateau at a similar work rate as BFIFDS. Sixteen subjects (23.3 ± 3.9 yr, 170.8 ± 1.9 cm, 72.8 ± 3.4 kg) participated in this study. Peak power (Ppeak) was determined for each subject (1.8 ± 0.4 W) via an incremental handgrip exercise test. Q̇BA, BFIFDS, total-[heme], deoxy-[heme], and percentage saturation were measured during each stage of the exercise test. On a subsequent testing day, muscle activation measurements of the FDS (RMSFDS) were collected during each stage of an identical incremental handgrip exercise test via electromyography from a subset of subjects ( n = 7). Q̇BA increased with exercise intensity until the final work rate transition ( P < 0.05). No increases in BFIFDS or muscle oxygenation characteristics were observed at exercise intensities greater than 51.5 ± 22.9% of Ppeak. No submaximal plateau in RMSFDS was observed. Whereas muscle activation of the FDS increased until task failure, noninvasively measured indices of perfusive and diffusive muscle microvascular oxygen delivery demonstrated submaximal plateaus. NEW & NOTEWORTHY Invasive measurements of muscle microvascular blood flow during incremental exercise have demonstrated submaximal plateaus. We demonstrate that indices of perfusive and diffusive microvascular oxygen transport to skeletal muscle, measured completely noninvasively, plateau at submaximal work rates during incremental exercise, even though limb blood flow and muscle recruitment continued to increase.
Electrical Conductivity Characterization and Porosity Determination of (Dy 2 O 3 ) x (WO 3 ) y (Bi 2 O 3 ) 1-x-y Ternary Compounds Used for IT-SOFC

Zirconium based electroceramics which are used on solid oxide fuel cells are operating at temperatures up to 1000°C today. Operating temperature of solid electrolyte based on Bismuth Oxide is lower than the electrolyte based on Zirconium. Bismuth Oxide based electroceramics has the oxygen ionic conductivity type at about 600°C and at these temperatures and have more efficiency in the ratio of 5-15% the other electrolytes. In this study, (Dy2O3)x(WO3)y(Bi2O3)1-x-y ternary compounds were synthesized with the solidstate reaction method by doping Dy2O3 and WO3 into pure Bi2O3 at different ratios. Cubic phase structures were determined by X-ray diffraction analysis method. Pellets were prepared from these cubic phase samples and also films were produced by spin coating method. After that pore structures of these samples were compared from their surface images taken from scanning electron microscopy. Also density of the samples was evaluated and porosity was bench marked. At the end, electrical conductivity of some selected samples was characterized by electrochemical impedance spectroscopy method. ©2014 Usak University all rights reserved.
The differential extension in dsDNA bound to Rad51 filaments may play important roles in homology recognition and strand exchange

RecA and Rad51 proteins play an important role in DNA repair and homologous recombination. For RecA, X-ray structure information and single molecule force experiments have indicated that the differential extension between the complementary strand and its Watson–Crick pairing partners promotes the rapid unbinding of non-homologous dsDNA and drives strand exchange forward for homologous dsDNA. In this work we find that both effects are also present in Rad51 protein. In particular, pulling on the opposite termini (3′ and 5′) of one of the two DNA strands in a dsDNA molecule allows dsDNA to extend along non-homologous Rad51-ssDNA filaments and remain stably bound in the extended state, but pulling on the 3′5′ ends of the complementary strand reduces the strand-exchange rate for homologous filaments. Thus, the results suggest that differential extension is also present in dsDNA bound to Rad51. The differential extension promotes rapid recognition by driving the swift unbinding of dsDNA from non-homologous Rad51-ssDNA filaments, while at the same time, reducing base pair tension due to the transfer of the Watson–Crick pairing of the complementary strand bases from the highly extended outgoing strand to the slightly less extended incoming strand, which drives strand exchange forward.
A new recommendation system on the basis of consumer initiative decision based on an associative classification approach

The purpose of this paper is to improve the customer satisfaction by offering online personalized recommendation system. ,By employing an innovative associative classification method, this paper is able to predict a customer’s pleasure during the online while-recommending process. Consumers can make an active decision to recommended products. Based on customer’s characteristics, a product will be recommended to the potential buyer if the model predicts that he/she will click to view the product. That is, he/she is satisfied with the recommended product. Finally, the feasibility of the proposed recommendation system is validated through a Taobao shop. ,The results of the experimental study clearly show that the online personalized recommendation system maximizes the customer’s satisfaction during the online while-recommending process based on an innovative associative classification method on the basis of consumer initiative decision. ,Conventionally, customers are considered as passive recipients of the recommendation system. However, customers are tired of the recommendation system, and they can do nothing sometimes. This paper designs a new recommendation system on the basis of consumer initiative decision. The proposed recommendation system maximizes the customer’s satisfaction during the online while-recommending process.
Preventive Suboccipital Decompressive Craniectomy for Cerebellar Infarction: A Retrospective-Matched Case–Control Study

Background and Purpose— No evidence is available on the benefits of preventive suboccipital decompressive craniectomy (SDC) for patients with cerebellar infarction. The purpose of this matched case–control study was to investigate whether preventive SDC was associated with good clinical outcomes in patients with cerebellar infarction and to evaluate its predisposing factors. Methods— Between March 2007 and September 2015, 28 patients underwent preventive SDC. We performed propensity score matching to establish a proper control group among 721 patients with cerebellar infarction during the same period. Group A (n=28) consists of those who underwent preventive SDC, and group B (n=56) consists of those who did not undergo preventive SDC. We analyzed and compared clinical outcomes between groups. Results— Clinical outcomes were better in group A than in group B at discharge (P=0.048) and 12-month follow-up (P=0.030). Group B had more deaths within 12 months than group A (log-rank, P<0.05). Logistic regression analysis showed that preventive SDC (odds ratio, 4.815; P=0.009) and the absence of brain stem infarction (odds ratio, 2.862; P=0.033) were independently associated with favorable outcomes (modified Rankin Scale score of 0–2) at 12-month follow-up. Conclusions— Favorable clinical outcomes including overall survival can be expected after preventive SDC in patients with a volume ratio between 0.25 and 0.33 and the absence of brain stem infarction. Among these patients, preventive SDC might be better than the best medical treatment alone.
DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world Applications

This paper introduces DuReader, a new large-scale, open-domain Chinese machine reading comprehension (MRC) dataset, designed to address real-world MRC. DuReader has three advantages over previous MRC datasets: (1) data sources: questions and documents are based on Baidu Search and Baidu Zhidao; answers are manually generated. (2) question types: it provides rich annotations for more question types, especially yes-no and opinion questions, that leaves more opportunity for the research community. (3) scale: it contains 200K questions, 420K answers and 1M documents; it is the largest Chinese MRC dataset so far. Experiments show that human performance is well above current state-of-the-art baseline systems, leaving plenty of room for the community to make improvements. To help the community make these improvements, both DuReader and baseline systems have been posted online. We also organize a shared competition to encourage the exploration of more models. Since the release of the task, there are significant improvements over the baselines.
TEMPORAL INSTABILITY OF LONGITUDINAL ELECTROKINETIC WAVE IN SEMICONDUCTOR PLASMA DOPED WITH A METAL NANOPARTICLE

Temporal instability of longitudinal electrokinetic wave in a nanoparticle impinged semiconductor plasma medium is investigated in this present report. Using hydrodynamic approach, we examined dispersion and gain characteristics of wave and found that two new models are induced within the medium due to the inclusion of a nanoparticle. The dependency of the characteristics of four modes propagating in the medium on carrier drift and wave number are explored.
Mapping the microRNA Expression Profiles in Glyoxalase Over-expressing Salinity Tolerant Rice

Abstract: In the recent years, glyoxalase pathway has been an active area of research in both human and plants. This pathway is reported to confer stress tolerance in plants, by modulating the glutathione homeostasis to achieve detoxification of a potent cytotoxic and mutagenic compound, methylglyoxal. The microRNAs (miRNAs) are also reported to play significant role in stress tolerance for plants. However, the cross-talk of miRNAs with the metabolism regulated by glyoxalase in the salinity-tolerance is unexplored. We therefore investigated whether expression profiles of miRNAs are altered in response to glyoxalase overexpression, and if any of these are also responsible for modulating the stress responses of plants. In this study, the Next Generation Sequencing (NGS) was employed to profile miRNA expression levels from glyoxalase overexpressing transgenic lines. The associated targets of differentially expressed miRNAs were predicted and their functional annotation was carried out using Gene Ontology (GO) and KEGG Orthology (KO), which showed their involvement in several crucial biological pathways. The analysis of NGS datasets also identified other isoforms or isomiRs of selected miRNAs, which may have an active role in developing tolerance against salt stress. Different aspects of miRNA modifications were also studied in glyoxalase overexpressing lines.
. ) Lindl . , the type species of Specklinia , and a few other mainly orange-flowered species , including Specklinia fulgens ( Rchb . f . )

Adam P. Karremans*, Franco Pupulin, David Grimaldi, Kevin K. Beentjes, Roland Butôt, Gregorio E. Fazzi, Karsten Kaspers, Jaco Kruizinga, Peter Roessingh, Erik F. Smets and Barbara Gravendeel Lankester Botanical Garden, University of Costa Rica, P.O. Box 302-7050 Cartago, Costa Rica, Naturalis Biodiversity Center, Leiden, The Netherlands, Harvard University Herbaria, Cambridge, MA, USA – Marie Selby Botanical Gardens, Sarasota, FL, USA, Division of Invertebrate Zoology, American Museum of Natural History, New York, NY, USA, Department of Pharmacology, Cardiovascular Research Institute Maastricht, Maastricht University, Maastricht, The Netherlands, University of Applied Sciences Leiden, Leiden, The Netherlands, Hortus botanicus, Leiden University, Leiden, The Netherlands, Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam, The Netherlands and Ecology, Evolution and Biodiversity Conservation, KU Leuven, Leuven, Belgium *For correspondence. E-mail adam.karremans@ucr.ac. cr
Collaborative filtering denoising algorithm based on the nonlocal centralized sparse representation model

An improved image denoising algorithm based on block-matching and 3D collaborative filtering (BM3D) is proposed in this manuscript. Instead of using the same filtering model for all patches in an image, we employ two different nonlocal filtering models in edge and smooth regions, respectively. We realize it by using the nonlocal centralized sparse representation (NCSR) to capture both local sparsity of wavelet coefficients and nonlocal similarity of grouped blocks. Experimental results demonstrate that the proposed method outperforms several state-of-the-art denoising methods in terms of objective metrics and visual quality.
5G Readiness on the Horizon [Mobile Radio]

Ericsson has released its "5G Readiness Survey 2017" [1]. The report shows that many operators have accelerated preparations for the new technology and that trials are being carried out by 78% of the respondents. Furthermore, 28% expect to deploy fifth generation (5G) in 2018. The survey also shows that operators have further developed their business strategies for 5G services. They are now looking beyond the consumer segment and foresee opportunities in the business and industrial areas. According to the survey, operators are seeing that the consumer market is becoming saturated. As a result, 5G planning this year is more evenly distributed across specialized industry segments (58%), business users (56%), and consumers (52%). Those surveyed highlighted the top three industry sectors as media and entertainment, automotive, and public transport, but many also ranked health care as well as energy and utilities among the most attractive sectors for 5G applications. A clear majority of the respondents believe that the Internet of Things (IoT) will play an important role and that third-party collaboration will be essential in this context.