Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal Resource Scheduling for Energy Harvesting Communications under Strict Delay Constraint

This paper investigates the resource scheduling minimizing the packet loss when the wireless communication system operates with Energy Harvesting (EH) based devices. The packet loss occurs when the buffer is overflowed and when the queued packet is older than a certain pre-defined threshold. We so consider a strict delay constraint rather than an average delay constraint. The associated optimization problem can be modeled as Markov Decision Problem (MDP) where the actions are the number of packets sent on the known channel at each slot. The optimal deterministic offline policy is exhibited through dynamic programming techniques, i.e. Value Iteration (VI) algorithm. We show the gain in the number of transmitted packets and the consumed energy is substantial compared to a naive policy which forces the system to send the maximum number of packets using the available energy in the battery.
Vision-based surface roughness evaluation system for end milling

ABSTRACT This paper presents a vision-based surface roughness evaluation system for end-milled metals, addressing digital reconstruction and calibration of inspected surfaces, and quantitative and qualitative evaluation of surface texture. Specimens with different levels of surface roughness are machined, and a comparison between stylus-based and vision-based measurements is performed while using standard roughness parameters. The vison-based results vary among 9% and 11% compared to the stylus-based ones, which is a minor error to trade-off for faster measurements. Furthermore, surface texture evaluation is performed by detecting the generated cusp lines and tool marks on the machined surface. The tool marks’ distribution is analysed in order to determine whether the machining is performed under optimal cutting conditions. Results show that under optimal cutting conditions, the detected tool marks are normally distributed along the feed direction and the distance between two consecutive tool marks does not vary significantly. Based on the proposed methods software is implemented that enables the three-dimensional reconstruction, calibration and evaluation of the inspected surface.
Maximum Co-located Community Search in Large Scale Social Networks

The problem of k-truss search has been well defined and investigated to find the highly correlated user groups in social networks. But there is no previous study to consider the constraint of users' spatial information in k-truss search, denoted as co-located community search in this paper. The co-located community can serve many real applications. To search the maximum co-located communities efficiently, we first develop an efficient exact algorithm with several pruning techniques. After that, we further develop an approximation algorithm with adjustable accuracy guarantees and explore more effective pruning rules, which can reduce the computational cost significantly. To accelerate the real-time efficiency, we also devise a novel quadtree based index to support the efficient retrieval of users in a region and optimise the search regions with regards to the given query region. Finally, we verify the performance of our proposed algorithms and index using five real datasets.
Contextualized Character Representation for Chinese Grammatical Error Diagnosis

Nowadays, more and more people are learning Chinese as their second language. Establishing an automatic diagnosis system for Chinese grammatical error has become an important challenge. In this paper, we propose a Chinese grammatical error diagnosis (CGED) model with contextualized character representation. Compared to the traditional model using LSTM (Long-Short Term Memory), our model have better performance and there is no need to add too many artificial features.
On the Cost of Introducing Speech-Like Properties to a Stimulus for Auditory Steady-State Response Measurements

Validating hearing-aid fittings in prelingual infants is challenging because typical measures (aided audiometry, etc.) are impossible with infants. One objective alternative uses an aided auditory steady-state response (ASSR) measurement. To make an appropriate measurement, the hearing aid’s signal-processing features must be activated (or deactivated) as if the ASSR stimulus was real speech. Rather than manipulating the hearing-aid settings to achieve this, an ASSR stimulus with speech-like properties was developed. This promotes clinical simplicity and face validity of the validation. The stimulus consists of narrow-band CE-Chirps®, modified to mimic the International Speech Test Signal (ISTS). This study examines the cost of introducing the speech-like features into the ASSR stimulus. Thus, 90 to 100 Hz ASSRs were recorded to the ISTS-modified stimulus as well as an equivalent stimulus without the ISTS modification, presented through insert phones to 10 young normal-hearing subjects. Noise-corrected ASSR magnitudes and clinically relevant detection times were estimated and analyzed with mixed-model analyses of variance. As a supplement, the observed changes to the ASSR magnitudes were compared with an objective characterization of the stimuli based on modulation power. The main findings were a reduction in ASSR magnitude of 4 dB and an increase in detection time by a factor of 1.5 for the ISTS-modified stimulus compared with the standard. Detection rates were unaffected given sufficient recording time. For clinical use of the hearing-aid validation procedure, the key metric is the detection time. While this varied considerably across subjects, the observed 50% mean increase corresponds to less than 1 min of additional recording time.
Time Integration of Rank-Constrained Tucker Tensors

Dynamical low-rank approximation in the Tucker tensor format of given large time-dependent tensors and of tensor differential equations is the subject of this paper. In particular, a discrete time integration method for rank-constrained Tucker tensors is presented and analyzed. It extends the known projector-splitting integrator for dynamical low-rank approximation of matrices to Tucker tensors and is shown to inherit the same favorable properties. The integrator is based on iteratively applying the matrix projector-splitting integrator to tensor unfoldings but with inexact solution in a substep. It has the property that it reconstructs time-dependent Tucker tensors of the given rank exactly. The integrator is also shown to be robust to the presence of small singular values in the tensor unfoldings. Numerical examples with problems from quantum dynamics and tensor optimization methods illustrate our theoretical results.
Effect of Heat Stress on Yield, Monoterpene Content and Antibacterial Activity of Essential Oils of Mentha x piperita var. Mitcham and Mentha arvensis var. piperascens

Heat stress affects the yield of medicinal plants and can reduce biomass and/or metabolite production. In order to evaluate the effect of heat-induced stress on the essential oil production in Mentha x piperita L. var. Mitcham (Mitcham mint) and Mentha arvensis var. piperascens Malinv. ex L. H. Bailey (Japanese mint), we studied the chemical composition of the oils of the two mint species under different heat shock stresses in growth chambers. The antibacterial activity of the essential oils was also evaluated; microscopic observation (fluorescence and electron transmission) was used to assess the effect of the tested samples on bacterial growth. The results obtained shed light on the mint essential oils composition and biological activity in relation to heat stress.
Intrusion Detection in Cyber-Physical Systems Based on Petri Net

Intrusion detection is a major concern in Cyber-Physical Systems (CPSs). In this paper, an algorithm based on Petri Net (PN) is proposed that simultaneously detects misuse and anomaly behavior of the system. The proposed anomaly detection method is applicable to Supervisory Control and Data Acquisition (SCADA) system at the highest level of CPSs. Neural First Order Hybrid Petri Net model (NFOHPN) with online fast Independent Component Analysis (ICA) is proposed for anomaly detection. It is shown that the use of distributed and multidisciplinary intrusion detection methods in different layers of CPSs increases security of the net against coordinated cyber-attacks. Simulation results and comparative studies based on the Defense Advanced Research Projects Agency (DARPA) evaluation datasets demonstrate that the proposed model can detect normal or malicious behavior with satisfying accuracy and at surprisingly high convergence speed. DOI: http://dx.doi. org/10.5755/j01.itc. 47.2. 16277
Combinational Proanthocyanidins and Resveratrol Synergistically Inhibit Human Breast Cancer Cells and Impact Epigenetic–Mediating Machinery

Breast cancer is the second most common cancer and the second leading cause of death from cancer among women in the United States (US). Cancer prevention and therapy through the use of phytochemicals that have epigenetic properties has gained considerable interest during the past few decades. Such dietary components include, but are not limited to, grape seed proanthocyanidins (GSPs) and resveratrol (Res), both of which are present in red wine. In this study, we report for the first time the synergistic effects of GSPs and Res on inhibiting MDA-MB-231 and MCF-7 human breast cancer cells. Our results of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays and clonogenic assays indicate that treatments with the combinations of GSPs and Res synergistically decreased cell viability and posttreatment cell proliferation in both cell lines. Additional analyses show that treatments with GSPs and Res in combination synergistically induced apoptosis in MDA-MB-231 cells by upregulating Bax expression and down-regulating Bcl-2 expression. DNA methyltransferase (DNMT) activity and histone deacetylase (HDAC) activity were greatly reduced in MDA-MB-231 and MCF-7 cells after treatments with GSPs and Res in combination. Collectively, our findings suggest that GSPs and Res synergistically inhibit human breast cancer cells through inducing apoptosis, as well as modulating DNA methylation and histone modifications.
The SUMMA Platform: A Scalable Infrastructure for Multi-lingual Multi-media Monitoring

The open-source SUMMA Platform is a highly scalable distributed architecture for monitoring a large number of media broadcasts in parallel, with a lag behind actual broadcast time of at most a few minutes. The Platform offers a fully automated media ingestion pipeline capable of recording live broadcasts, detection and transcription of spoken content, translation of all text (original or transcribed) into English, recognition and linking of Named Entities, topic detection, clustering and cross-lingual multi-document summarization of related media items, and last but not least, extraction and storage of factual claims in these news items. Browser-based graphical user interfaces provide humans with aggregated information as well as structured access to individual news items stored in the Platform’s database. This paper describes the intended use cases and provides an overview over the system’s implementation.
Feature Optimization for Predicting Readability of Arabic L1 and L2

Advances in automatic readability assessment can impact the way people consume information in a number of domains. Arabic, being a low-resource and morphologically complex language, presents numerous challenges to the task of automatic readability assessment. In this paper, we present the largest and most in-depth computational readability study for Arabic to date. We study a large set of features with varying depths, from shallow words to syntactic trees, for both L1 and L2 readability tasks. Our best L1 readability accuracy result is 94.8% (75% error reduction from a commonly used baseline). The comparable results for L2 are 72.4% (45% error reduction). We also demonstrate the added value of leveraging L1 features for L2 readability prediction.
A musculoskeletal model of the lumbar spine using ArtiSynth – development and validation

Abstract A musculoskeletal model of the spine was created using ArtiSynth, an open-source biomechanical modelling toolkit. The model included the entire spine and rib cage, with the lumbar vertebrae being mobile and 210 muscle fascicles. Muscle parameters needed for a full Hill-type musculotendon model including tendon ratios and pennation angles along with muscle force-length and force-velocity curves were incorporated into the model, as were the nonlinear stiffness of the functional spinal units and the effect of intra-abdominal pressure. We used forward dynamics-assisted data tracking for the estimation of muscle forces and validated the solution method by comparing the predicted spinal forces vs. the results of two in vivo experiments in the literature. Our model produced larger maximum extension moment in flexion than extension, which is observed in in vivo experiments. These results could not be achieved without the inclusion of the muscle force-length relationship. The model was also able to predict the ratios of axial forces at L4–L5 as measured in vivo intradiscal pressures for three cases of upright standing, holding a crate close to and far from the chest. Due to the high stiffness of the spine, our solution method was sensitive to input kinematics, which hindered extensive validation of the model for body positions other than standing. Modifying the solution method, possibly by only tracking the angular motion of the vertebrae rather than their translational motion, should make the model less sensitive and enable further validation.
The effects of quercetin supplementation on metabolic and hormonal parameters as well as plasma concentration and gene expression of resistin in overweight or obese women with polycystic ovary syndrome

The aim of this study was to investigate the effect of quercetin on metabolic and hormonal parameters as well as plasma concentration and gene expression of resistin in overweight or obese women with polycystic ovary syndrome (PCOS). In this randomized, double‐blind, placebo‐controlled trial, 78 overweight or obese women (25 ≤ BMI ≤ 40 kg/m2, 20–40 years) with PCOS were recruited. Patients were randomized to receive 1,000 mg/day quercetin or placebo for 12 weeks. Resistin plasma concentration and gene expression in peripheral blood mononuclear cells, parameters of glucose homeostasis, circulatory testosterone, luteinizing hormone (LH), and sex hormone‐binding globulin, and anthropometries were assessed at baseline and at the end of the study. Following supplementation, quercetin significantly decreased resistin concentration (2.07 ± 0.23 vs. 2.88 ± 0.40 ng/ml, p < 0.001) and mRNA level (0.64 ± 0.58 vs. 1 ± 0.56 fold change, p = 0.008), compared with placebo group. Moreover, testosterone (0.72 ± 0.15 vs. 0.76 ± 0.12 ng/ml, p = 0.001) and LH (8.05 ± 2.88 vs. 8.77 ± 1.99 mIU/ml, p = 0.035) concentrations were significantly lower in quercetin compared with placebo group. Fasting blood glucose (p < 0.001), insulin (p = 0.02), and homeostatic model assessment of insulin resistance (p = 0.009) decreased within the quercetin group; however, no significant differences were observed compared with the placebo group (p = 0.074, p = 0.226, p = 0.22, respectively). Quercetin supplementation decreased resistin plasma levels and gene expression, and testosterone and LH concentration in overweight or obese women with PCOS.
Sulfide Protects Staphylococcus aureus from Aminoglycoside Antibiotics but Cannot Be Regarded as a General Defense Mechanism against Antibiotics

Sulfide production has been proposed to be a universal defense mechanism against antibiotics in bacteria (K. Shatalin, E. ABSTRACT Sulfide production has been proposed to be a universal defense mechanism against antibiotics in bacteria (K. Shatalin, E. Shatalina, A. Mironov, and E. Nudler, Science 334:986–990, 2011, doi:10.1126/science.1209855). To gain insight into the mechanism underlying sulfide protection, we systematically and comparatively addressed the interference of sulfide with antibiotic activity against Staphylococcus aureus, as a model organism. The impact of sulfide and sulfide precursors on the antibiotic susceptibility of S. aureus to the most important classes of antibiotics was analyzed using modified disk diffusion assays, killing kinetic assays, and drug uptake studies. In addition, sulfide production and the impact of exogenously added sulfide on the physiology of S. aureus were analyzed. Sulfide protection was found to be limited to aminoglycoside antibiotics, which are known to be taken up by bacterial cells in an energy-dependent process. The protective mechanism was found to rely on an inhibitory effect of sulfide on the bacterial respiratory chain, leading to reduced drug uptake. S. aureus was found to be incapable of producing substantial amounts of sulfide. We propose that bacterial sulfide production should not be regarded as a general defense mechanism against antibiotics, since (i) it is limited to aminoglycosides and (ii) production levels vary considerably among species and, as for S. aureus, may be too low for protection.
Controlling pre-movement sensorimotor rhythm can improve finger extension after stroke

Objective. Brain–computer interface (BCI) technology is attracting increasing interest as a tool for enhancing recovery of motor function after stroke, yet the optimal way to apply this technology is unknown. Here, we studied the immediate and therapeutic effects of BCI-based training to control pre-movement sensorimotor rhythm (SMR) amplitude on robot-assisted finger extension in people with stroke. Approach. Eight people with moderate to severe hand impairment due to chronic stroke completed a four-week three-phase protocol during which they practiced finger extension with assistance from the FINGER robotic exoskeleton. In Phase 1, we identified spatiospectral SMR features for each person that correlated with the intent to extend the index and/or middle finger(s). In Phase 2, the participants learned to increase or decrease SMR features given visual feedback, without movement. In Phase 3, the participants were cued to increase or decrease their SMR features, and when successful, were then cued to immediately attempt to extend the finger(s) with robot assistance. Main results. Of the four participants that achieved SMR control in Phase 2, three initiated finger extensions with a reduced reaction time after decreasing (versus increasing) pre-movement SMR amplitude during Phase 3. Two also extended at least one of their fingers more forcefully after decreasing pre-movement SMR amplitude. Hand function, measured by the box and block test (BBT), improved by 7.3 ± 7.5 blocks versus 3.5 ± 3.1 blocks in those with and without SMR control, respectively. Higher BBT scores at baseline correlated with a larger change in BBT score. Significance. These results suggest that learning to control person-specific pre-movement SMR features associated with finger extension can improve finger extension ability after stroke for some individuals. These results merit further investigation in a rehabilitation context.
Be Aware of Aggregators in the Search for Potential Human ecto-5′-Nucleotidase Inhibitors

Promiscuous inhibition due to aggregate formation has been recognized as a major concern in drug discovery campaigns. Here, we report some aggregators identified in a virtual screening (VS) protocol to search for inhibitors of human ecto-5′-nucleotidase (ecto-5′-NT/CD73), a promising target for several diseases and pathophysiological events, including cancer, inflammation and autoimmune diseases. Four compounds (A, B, C and D), selected from the ZINC-11 database, showed IC50 values in the micromolar range, being at the same time computationally predicted as potential aggregators. To confirm if they inhibit human ecto-5′-NT via promiscuous mechanism, forming aggregates, enzymatic assays were done in the presence of 0.01% (v/v) Triton X-100 and an increase in the enzyme concentration by 10-fold. Under both experimental conditions, these four compounds showed a significant decrease in their inhibitory activities. To corroborate these findings, turbidimetric assays were performed, confirming that they form aggregate species. Additionally, aggregation kinetic studies were done by dynamic light scattering (DLS) for compound C. None of the identified aggregators has been previously reported in the literature. For the first time, aggregation and promiscuous inhibition issues were systematically studied and evaluated for compounds selected by VS as potential inhibitors for human ecto-5′-NT. Together, our results reinforce the importance of accounting for potential false-positive hits acting by aggregation in drug discovery campaigns to avoid misleading assay results.
Evaluating Information Quality in Delivering IoT-as-a-Service

Combining the Internet of Things (IoT) and Cloud computing is pursuing new levels of efficiency in delivering IoTas-a-Service (IoTaaS). In such scenario, Public Administrations (PAs) benefit from digitalization process improving development of innovation and administrative transparency. In this paper we propose a strategy to evaluate the quality of information in order to deliver IoTaaS in Smart City context. The goal of the work is to provide an advanced method to support PAs in the process of enhancing public information assets. The proposed strategy extends traditional approaches by using Multiple Criteria Decision Making (MCDM) models for the numerical and qualitative evaluation of public data and related metadata. Furthermore, it provides guidelines to implement the models starting from the data path.
Fractional Frequency Reuse in Non-Orthogonal Multiple Access Heterogeneous Networks

Non-orthogonal multiple access (NOMA) is considered one of the key techniques to increase spectral efficiency for 5G technologies. However, the superposition of non-orthogonal signals degrades the edge user performance due to additional interference from serving base stations. Therefore, the interference coordination becomes essential to provide fair service to all users. This paper presents an extensive coverage analysis of NOMA with well-known interference coordination schemes in the form of fractional frequency reuse in heterogeneous networks. The analysis include coexistence scenarios of NOMA with strict fractional frequency reuse and soft frequency reuse in both open and closed access $K$-tier heterogeneous networks. The numerical results indicate potential performance enhancements, especially in dense heterogeneous networks.
KylinX: A Dynamic Library Operating System for Simplified and Efficient Cloud Virtualization

Unikernel specializes a minimalistic LibOS and a target application into a standalone single-purpose virtual machine (VM) running on a hypervisor, which is referred to as (virtual) appliance. Compared to traditional VMs, Unikernel appliances have smaller memory footprint and lower overhead while guaranteeing the same level of isolation. On the downside, Unikernel strips off the process abstraction from its monolithic appliance and thus sacrifices flexibility, efficiency, and applicability. This paper examines whether there is a balance embracing the best of both Unikernel appliances (strong isolation) and processes (high flexibility/efficiency). We present KylinX, a dynamic library operating system for simplified and efficient cloud virtualization by providing the pVM (process-like VM) abstraction. A pVM takes the hypervisor as an OS and the Unikernel appliance as a process allowing both page-level and library-level dynamic mapping. At the page level, KylinX supports pVM fork plus a set of API for inter-pVM communication (IpC). At the library level, KylinX supports shared libraries to be linked to a Unikernel appliance at runtime. KylinX enforces mapping restrictions against potential threats. KylinX can fork a pVM in about 1.3 ms and link a library to a running pVM in a few ms, both comparable to process fork on Linux (about 1 ms). Latencies of KylinX IpCs are also comparable to that of UNIX IPCs.