Miracle-dz/UniFAR-FTUs huggingface dataset:
Chinese Grammatical Error Diagnosis using Statistical and Prior Knowledge driven Features with Probabilistic Ensemble Enhancement

This paper describes our system at NLPTEA-2018 Task #1: Chinese Grammatical Error Diagnosis. Grammatical Error Diagnosis is one of the most challenging NLP tasks, which is to locate grammar errors and tell error types. Our system is built on the model of bidirectional Long Short-Term Memory with a conditional random field layer (BiLSTM-CRF) but integrates with several new features. First, richer features are considered in the BiLSTM-CRF model; second, a probabilistic ensemble approach is adopted; third, Template Matcher are used during a post-processing to bring in human knowledge. In official evaluation, our system obtains the highest F1 scores at identifying error types and locating error positions, the second highest F1 score at sentence level error detection. We also recommend error corrections for specific error types and achieve the best F1 performance among all participants.
Combining Chronic Ischemic Preconditioning and Inspiratory Muscle Warm-Up to Enhance On-Ice Time-Trial Performance in Elite Speed Skaters

Elite athletes in varied sports typically combine ergogenic strategies in the hope of enhancing physiological responses and competitive performance, but the scientific evidence for such practices is very scarce. The peculiar characteristics of speed skating contribute to impede blood flow and exacerbate deoxygenation in the lower limbs (especially the right leg). We investigated whether combining preconditioning strategies could modify muscular oxygenation and improve performance in that sport. Using a randomized, single-blind, placebo-controlled, crossover design, seven male elite long-track speed skaters performed on-ice 600-m time trials, preceded by either a combination of preconditioning strategies (COMBO) or a placebo condition (SHAM). COMBO involved performing remote ischemic preconditioning (RIPC) of the upper limbs (3 × 5-min compression at 180 mmHg and 5-min reperfusion) over 3 days (including an acute treatment before trials), with the addition of an inspiratory muscle warm-up [IMW: 2 × 30 inspirations at 40% maximal inspiratory pressure (MIP)] on the day of testing. SHAM followed the same protocol with lower intensities (10 mmHg for RIPC and 15% MIP). Changes in tissue saturation index (TSI), oxyhemoglobin–oxymyoglobin ([O2HbMb]), deoxyhemoglobin–deoxymyoglobin ([HHbMb]), and total hemoglobin–myoglobin ([THbMb]) in the right vastus lateralis muscle were monitored by near-infrared spectroscopy (NIRS). Differences between COMBO and SHAM were analyzed using Cohen’s effect size (ES) and magnitude-based inferences. Compared with SHAM, COMBO had no worthwhile effect on performance time while mean Δ[HHbMb] (2.7%, ES 0.48; -0.07, 1.03) and peak Δ[HHbMb] (1.8%, ES 0.23; -0.10, 0.57) were respectively likely and possibly higher in the last section of the race. These results indicate that combining ischemic preconditioning and IMW has no practical ergogenic impact on 600-m speed-skating performance in elite skaters. The low-sitting position in this sport might render difficult enhancing these physiological responses.
Transmitting and Sharing: A Truthful Double Auction for Cognitive Radio Networks

The scarcity of spectrum channels resides in the limited bandwidth resource and the exploding demand from spectrum-based services and devices. To help ease this scarcity, the concept of cognitive radio networks (CRNs) is proposed, where licensed spectrum holders (primary users) may lease their channels to unlicensed users (secondary users). Many CRN auctions are thus designed to incentivize primary users (PUs) to share their idle channels with secondary users (SUs). Most of these auctions assume that a transmitting PU does not lease its channel to SUs; if it leases its channel to SUs, it does not transmit itself. To further utilize the resource, researchers have studied the scenario where a transmitting PU is allowed to lease its channels to SUs if the transmissions of the SUs do not undermine the transmission of the PU. However, the study assumes that there is only one PU who owns the licensed channels, whereas in practice, channels may be contributed by multiple PUs. This prevents the result of the study from being directly applied to the multi-PU scenario, as the potential competitions among the PUs are neglected. We extend the scenario to the CRN with multiple PUs and propose TDSA-PS as a Truthful Double Spectrum Auction with transmitting Primary users Sharing. We prove that TDSA-PS is truthful, individually rational, budget-balanced, and computationally efficient.
A Cluster-Based Random-Access Scheme for LTE/LTE-A Networks Supporting Massive Machine-Type Communications

In the Internet of Things (IoT), it is desirable that every IoT device will be capable to communicate with the network at any time. Among various technologies to enable network connectivity, the Long Term Evolution (LTE) is by far the most ubiquitous technology to provide large coverage of IoT devices. Machine-Type Communications (MTC) is seen as a major service in the next generation cellular mobile networks for IoT. However, the predicted large number of MTC devices will overload the Radio Access Network (RAN), with impact on non-MTC devices. In this work, we propose a design of a RAN overload control mechanism based in clustering that is exclusively engineered for delay-tolerant MTC devices. The proposed solution is intended for delay-tolerant MTC devices with a Radio Resource Control (RRC) context (have a Cell Radio Network Temporary Identity (C-RNTI)) but without being synchronized with the network. By simulation, we show that the proposed scheme leads to acceptable collision levels, besides ameliorating the energy efficiency.
tpIP: A Time-Predictable TCP/IP Stack for Cyber-Physical Systems

Cyber-physical systems are networks of computers connected to the physical world. Often the interaction with the physical world is time critical. In that case computation and communication must be performed in real time. However, a standard implementation of a network stack is hardly time predictable. This paper addresses the challenge of real-time communication for time-critical cyber-physical systems with a time-predictable network stack. We present tpIP, a real-time implementation of the TCP/IP stack. We achieve time predictability by two properties: (1) the application interface is based on polling functions, instead of blocking sockets, that fits for periodic real-time tasks; (2) the implementation is carefully crafted to enable static worst-case execution time analysis of all functions.
Audio fingerprint hierarchy searching strategies on GPGPU massively parallel computer

ABSTRACT Audio fingerprint was developed for representing the audio based on the content of waveform. With the audio fingerprint database, we can easily manage the song/music with high reliability and flexibility. However, with the well-developed Internet of today, the audio data have become bigger and bigger which make the management of audio/music data more difficult. There are two problems that we need to solve when the audio fingerprint database turn into bigdata: the size of the database needs to be sufficient for storing 10 millions of audio fingerprint and the strategies for searching the nearest song in acceptable time for thousands of queries at once [Nguyen Mau, T. , & Inoguchi, Y. (2016). Audio fingerprint hierarchy searching on massively parallel with multi-gpgpus using K-modes and lsh. Eighth international conference on knowledge and systems engineering (KSE) (pp. 49–54). IEEE]. In this research, we propose the methods for storing the audio fingerprint using multiple GPGPU and nearest song searching strategies based on these databases. We also showed that our methods have the significant result for deploying the real system in the future.
Progressive parameterizations

We propose a novel approach, called Progressive Parameterizations, to compute foldover-free parameterizations with low isometric distortion on disk topology meshes. Instead of using the input mesh as a reference to define the objective function, we introduce a progressive reference that contains bounded distortion to the parameterized mesh and is as close as possible to the input mesh. After optimizing the bounded distortion energy between the progressive reference and the parameterized mesh, the parameterized mesh easily approaches the progressive reference, thereby also coming close to the input. By iteratively generating the progressive reference and optimizing the bounded distortion energy to update the parameterized mesh, our algorithm achieves high-quality parameterizations with strong practical reliability and high efficiency. We have demonstrated that our algorithm succeeds on a massive test data set containing over 20712 complex disk topology meshes. Compared to the state-of-the-art methods, our method has achieved higher computational efficiency and practical reliability.
Compiling Combinatorial Prediction Games

In online optimization, the goal is to iteratively choose solutions from a decision space, so as to minimize the average cost over time. As long as this decision space is described by combinatorial constraints, the problem is generally intractable. In this paper, we consider the paradigm of compiling the set of combinatorial constraints into a deterministic and Decomposable Negation Normal Form (dDNNF) circuit, for which the tasks of linear optimization and solution sampling take linear time. Based on this framework, we provide efficient characterizations of existing combinatorial prediction strategies, with a particular attention to mirror descent techniques. These strategies are compared on several real-world benchmarks for which the set of Boolean constraints is preliminarily compiled into a dDNNF circuit.
CRUISE: Cold-Start New Skill Development via Iterative Utterance Generation

We present a system, CRUISE, that guides ordinary software developers to build a high quality natural language understanding (NLU) engine from scratch. This is the fundamental step of building a new skill in personal assistants. Unlike existing solutions that require either developers or crowdsourcing to manually generate and annotate a large number of utterances, we design a hybrid rule-based and data-driven approach with the capability to iteratively generate more and more utterances. Our system only requires light human workload to iteratively prune incorrect utterances. CRUISE outputs a well trained NLU engine and a large scale annotated utterance corpus that third parties can use to develop their custom skills. Using both benchmark dataset and custom datasets we collected in real-world settings, we validate the high quality of CRUISE generated utterances via both competitive NLU performance and human evaluation. We also show the largely reduced human workload in terms of both cognitive load and human pruning time consumption.
mTOR complex 1 controls the nuclear localization and function of glycogen synthase kinase 3β

Glycogen synthase kinase 3β (GSK3β) phosphorylates and thereby regulates a wide range of protein substrates involved in diverse cellular functions. Some GSK3β substrates, such as c-Myc and Snail, are nuclear transcription factors, suggesting the possibility that GSK3β function is controlled through its nuclear localization. Here, using ARPE-19 and MDA-MB-231 human cell lines, we found that inhibition of mTOR complex 1 (mTORC1) leads to partial redistribution of GSK3β from the cytosol to the nucleus and to a GSK3β-dependent reduction of the levels of both c-Myc and Snail. mTORC1 is known to be controlled by metabolic cues, such as by AMP-activated protein kinase (AMPK) or amino acid abundance, and we observed here that AMPK activation or amino acid deprivation promotes GSK3β nuclear localization in an mTORC1-dependent manner. GSK3β was detected on several distinct endomembrane compartments, including lysosomes. Consistently, disruption of late endosomes/lysosomes through a perturbation of RAS oncogene family member 7 (Rab7) resulted in loss of GSK3β from lysosomes and in enhanced GSK3β nuclear localization as well as GSK3β-dependent reduction of c-Myc levels. These findings indicate that the nuclear localization and function of GSK3β is suppressed by mTORC1 and suggest a link between metabolic conditions sensed by mTORC1 and GSK3β-dependent regulation of transcriptional networks controlling cellular biomass production.
High Mobility Multi Modal E-Health Services

In emergency medical services, the lag time between injury and treatment is one of the most critical parameters with respect to patient survivability. Ambulance services aim to maximize the likelihood of prompt medical treatment to prevent death and/or potential non-reversible damages. The emerging Tactile Internet has a vital role to play on that frontier by allowing next generation of ambulances to be equipped with advanced haptic/tactile devices to allow pre-hospital treatment/diagnosis or even remote surgery while en route. In this paper we propose a novel reliable multi-modal e- health high mobility service optimization framework for ambulances utilizing mobile edge clouds to efficiently transport real time patient information to the hospital. The main challenge of the proposed e- health service is to guarantee the heterogeneous QoS requirements of all involved data flows between the ambulance and the medical personnel. To this end, we formulate the service configuration problem as an optimization problem. In addition, a set of low- complexity algorithms are proposed to provide competitive solutions in real-time. A comprehensive set of numerical investigations are presented to characterize the attainable system performance of the proposed schemes.
EESS: An Energy-Efficient Spectrum Sensing Method by Optimizing Spectrum Sensing Node in Cognitive Radio Sensor Networks

In cognitive radio sensor networks (CRSNs), the sensor devices which are enabled to perform dynamic spectrum access have to frequently sense the licensed channel to find idle channels. The behavior of spectrum sensing will consume a lot of battery power of sensor devices and reduce the network lifetime. In this paper, we aim to answer the question of how many spectrum sensing nodes (SSNs) are required. In order to achieve this, SSN ratio effects on the accuracy of spectrum sensing from the perspective of network energy efficiency are analyzed first. Based on these analyses, the optimal SSN ratio is derived for maximizing the network lifetime by optimizing the cooperative detection probability (CDP). Simulation results show that the optimal SSN ratio can guarantee the spectrum sensing performance in terms of detection and false alarm probabilities and effectively extend the network lifetime.
PR-CCA MAC: A Prioritized Random CCA MAC Protocol for Mission-Critical IoT Applications

A fundamental challenge in Mission-Critical Internet of Things (MC-IoT) is to provide reliable and timely delivery of the unpredictable critical traffic. In this paper, we propose an efficient prioritized Medium Access Control (MAC) protocol for Wireless Sensor Networks (WSNs) in MC-IoT control applications. The proposed protocol utilizes a random Clear Channel Assessment (CCA)-based channel access mechanism to handle the simultaneous transmissions of critical data and to reduce the collision probability between the contending nodes, which in turn decreases the transmission latency. We develop a Discrete-Time Markov Chain (DTMC) model to evaluate the performance of the proposed protocol analytically in terms of the expected delay and throughput. The obtained results show that the proposed protocol can enhance the performance of the WirelessHART standard by 80% and 190% in terms of latency and throughput, respectively along with better transmission reliability.
A survey on stereo vision-based autonomous navigation for multi-rotor MUAVs

SUMMARY This paper presents an overview of the most recent vision-based multi-rotor micro unmanned aerial vehicles (MUAVs) intended for autonomous navigation using a stereoscopic camera. Drone operation is difficult because pilots need the expertise to fly the drones. Pilots have a limited field of view, and unfortunate situations, such as loss of line of sight or collision with objects such as wires and branches, can happen. Autonomous navigation is an even more difficult challenge than remote control navigation because the drones must make decisions on their own in real time and simultaneously build maps of their surroundings if none is available. Moreover, MUAVs are limited in terms of useful payload capability and energy consumption. Therefore, a drone must be equipped with small sensors, and it must carry low weight. In addition, a drone requires a sufficiently powerful onboard computer so that it can understand its surroundings and navigate accordingly to achieve its goal safely. A stereoscopic camera is considered a suitable sensor because of its three-dimensional (3D) capabilities. Hence, a drone can perform vision-based navigation through object recognition and self-localise inside a map if one is available; otherwise, its autonomous navigation creates a simultaneous localisation and mapping problem.
Sleeping habits of adolescents in relation to their physical activity and exercise output: results from the ELSPAC study

Background Little is known about the effects of physical activity and fitness on sleep timing parameters in adolescence. Methods We investigated the development of sleep timing between age 8 and 15 and its association with physical fitness at age 15 in 787 adolescents (408 males, 379 females). Physical fitness was measured using the physical work capacity (PWC) protocol. Information on sport activity was collected at ages 11 and 15. Finally, the contribution of other covariates (sex, body mass index (BMI), parental education and occupational skill level) to the association between sleep parameters and physical fitness was evaluated. The correlation of BMI and physical fitness was assessed separately. Results Mild correlation of sleep duration at ages 8 and 15 was observed (r=0.08–0.16). Higher sport activity participation and physical fitness were found to be mildly associated with delayed bedtime and reduced sleep duration; the association with bedtime was significant after adjustment for all covariates. Sport activity at age 11 was not associated with sleep timing at age 15. Interestingly, higher BMI was linked to delayed bedtime and higher physical fitness. Conclusion Our findings do not support existing hypotheses suggesting the association of low physical activity and fitness with shorter sleep duration and high BMI in a generally non-obese adolescent population without severe sleep restriction.
On Design of SILU Algorithm to Enable Our New ABPM System for Stroke Risk Early-Warning

Nowadays, stroke is regarded as the first killer of public health, causing around 5 million deaths every year worldwide. However, study shows that stroke can be predicted and prevented if people's Blood Pressure (BP) statuses are appropriately monitored daily, since these malignant events have some foreboding physiological signals. Unfortunately, there is no any BP devices to find these signals in real-time, even for Ambulatory Blood Pressure Monitor (ABPM) devices. Furthermore, all data of BP and ABPM devices are collected via a deflation-type mode, which couldn't capture most of the vasculopaty due to elastic deformation problem of blood vessels. To solve these challenges above, a new ABPM system is designed as a Mobile Health (mHealth) system for stroke risk early-warning, in which a customized inflation-type BP measurement, i.e., SILU algorithm, is proposed. Our clinical results demonstrate that the system is a useful tool for stroke prevention, and other BP-related diseases early-risk monitoring.
Circulating Cell-Free miR-375 as Surrogate Marker of Tumor Burden in Merkel Cell Carcinoma

Purpose: Merkel cell carcinoma (MCC) is an aggressive skin cancer with neuroendocrine differentiation. There is an unmet need for MCC-specific blood-based surrogate biomarkers of tumor burden; circulating cell-free miRNA may serve this purpose. Experimental Design: Expression of miR-375 was quantified in 24 MCC and 23 non-MCC cell lines, 67 MCC and 58 non-MCC tumor tissues, sera of 2 preclinical MCC models, and sera of 109 patients with MCC and 30 healthy controls by nCounter human-v2-miRNA expression or miR-375–specific real-time PCR assays. The patients’ sera consisted of two retrospective (discovery and training) and two prospective (validation) cohorts. Results: miR-375 expression was high in MCC cell lines and tissues compared with non-MCCs. It was readily detected in MCC-conditioned medium and sera of preclinical models bearing MCC xenografts. miR-375 levels were higher in sera from tumor-bearing patients with MCC than in tumor-free patients or healthy controls (P < 0.0005). Moreover, miR-375 serum levels correlated with tumor stage in tumor-bearing (P = 0.037) but not in tumor-free (P = 0.372) patients with MCC. miR-375 serum level showed high diagnostic accuracy to discriminate tumor-bearing and tumor-free patients with MCC as demonstrated by ROC curve analysis in the retrospective cohorts (AUC = 0.954 and 0.800) as well as in the prospective cohorts (AUC = 0.929 and 0.959). miR-375 serum level reflected dynamic changes in tumor burden of patients with MCC during therapeutic interventions. Conclusions: Circulating cell-free miR-375 proved as a surrogate marker for tumor burden in MCC without restriction to polyomavirus positivity; it thus appears to be useful for therapy monitoring and the follow-up of patients with MCC.
OntoCoins : données ouvertes liées pour la numismatique, patrimoine culturel

Résumé : Le patrimoine culturel est en partie conservé dans des collections publiques et privées difficilement accessibles au grand public ainsi qu’aux chercheurs, historiens de l’art, économistes, ou archéologues, qui trouvent là un frein majeur à leurs recherches. Nous sommes aujourd’hui en mesure de partager et de valoriser ce patrimoine par le biais du Web sémantique et des données ouvertes liées sous l’impulsion du Ministère de la Culture. Dans cet article, nous développons un vocabulaire qui a pour vocation d’ouvrir les données « numismatiques », c’est-à-dire des données relatives aux monnaies anciennes, véritables œuvres d’art réalisés par des artistes graveurs, témoins de l’évolution des cultures depuis plus de deux millénaires, dont seule une petite partie (dans le meilleur des cas) est exposée au public à travers les vitrines des musées. La conception et le développement de notre vocabulaire baptisé OntoCoins sont traités dans cet article. L’application Wikimoneda a été développée pour montrer la pertinence du vocabulaire, et est d’ores et déjà alimentée (et consultée) par cinq des plus importants conservateurs de collections publiques collaborant dans ce travail.