Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards a better understanding of statistical post-editing

We describe several experiments to better understand the usefulness of statistical post-edition (SPE) to improve phrasebased statistical MT (PBMT) systems raw outputs. Whatever the size of the training corpus, we show that SPE systems trained on general domain data offers no breakthrough to our baseline general domain PBMT system. However, using manually post-edited system outputs to train the SPE led to a slight improvement in the translations quality compared with the use of professional reference translations. We also show that SPE is far more effective for domain adaptation, mainly because it recovers a lot of specific terms unknown to our general PBMT system. Finally, we compare two domain adaptation techniques, post-editing a general domain PBMT system vs building a new domain-adapted PBMT system with two different techniques, and show that the latter outperforms the first one. Yet, when the PBMT is a “black box”, SPE trained with post-edited system outputs remains an interesting option for domain adaptation.
Real-Time Traffic Volatility Forecasting in Urban Arterial Networks

A methodology is presented for forecasting traffic volatility in urban arterial networks with real-time traffic flow information. This methodology provides a generalization of the standard modeling approach, in which both the mean, modeled by an autoregressive moving average process, and the variance, modeled by an autoregressive conditional heteroscedastic process, are time-varying. The statistical analysis and forecasting performance of the proposed model are investigated with real-time traffic detector data from a real urban arterial network. The results indicate the potential of the proposed model to improve the accuracy of predicted traffic volatility across different lengths of forecasting horizon in comparison with the standard generalized autoregressive conditional heteroscedastic methodology.
Microbiochemical reactors for enzymatic reactions including cell-free mRNA translation

As the first step toward the 'lab on a chip' or 'cell on a chip' concept, several microbiochemical reactors were fabricated using conventional MEMS (microelectromechanical systems) techniques: silicon anisotropic etching and glass-silicon anodic bonding. The microreactors have main reaction channels which are 14 mm long, 200-800 μm wide, and 20 μm deep. In these channels, enzymatic reactions - luciferin-luciferase reaction and cell-free mRNA translation - were demonstrated. Luminescence induced by the luciferin-luciferase reaction was observed in two ways, by photograph on a high-speed film and sensitive video imaging. In both cases, diffusion-based mixing in the microreactors was clearly visualized. In the cell-free protein synthesis experiment, the amount of polyphenylalanine, which was synthesized by translating polyuridylic acid template in the microreactors, was determined using radioisotope assay.
Vibration Control Performance of Damping Coupled Tuned Mass Dampers

Recently tuned mass dampers have been installed on three-story prefabricated houses for reducing of traffic-induced vibration and improving living comfort. This tuned mass damper consists of a mass unit, spring units and laminated rubber bearings. The mass is supported by four laminated rubber bearings, and spring units are used for adjusting the natural frequency of the tuned mass damper to the optimal value. Vibration control performance of this type of tuned mass dampers is deteriorated when the natural frequency of the house is changed. To solve this problem, the authors have developed a damping coupled tuned mass damper. In this type of tuned mass damper, two mass units having slightly different natural frequencies are coupled by using a damping unit. In this paper, mechanism and vibration control performance of the damping coupled tuned mass damper are described.Copyright © 2004 by ASME
Application of deep learning methods to the mitigation of nonlinear effects in communication systems

—This work focused on the application of deep learning techniques at digital predistortion for power amplifiers. Artificial neural networks and Random Forest were approached as workarounds for PA modeling and Volterra kernels selection. Results from this research are presented in this work. Furthermore, the student explains his future career plans and intention to attend to a MTT-S Sponsored Conference.
Low-resource machine translation using MaTrEx

In this paper, we give a description of the Machine Translation (MT) system developed at DCU that was used for our fourth participation in the evaluation campaign of the International Workshop on Spoken Language Translation (IWSLT 2009). Two techniques are deployed in our system in order to improve the translation quality in a low-resource scenario. The first technique is to use multiple segmentations in MT training and to utilise word lattices in decoding stage. The second technique is used to select the optimal training data that can be used to build MT systems. In this year’s participation, we use three different prototype SMT systems, and the output from each system are combined using standard system combination method. Our system is the top system for Chinese‐English CHALLENGE task in terms of BLEU score.
Experimental and numerical probe into the effects of adding one and two steps to a mono-hull planing vessel on its performance in calm water

In the current study, two different vessels with a single step and two steps are experimentally and numerically studied. The considered speeds are 8 and 9 m/s, equivalent to beam Froude numbers of 3.44 and 3.86. The experimentally measured parameters include bow rise-up, trim, and vessel’s resistance. On the other hand, numerical simulations of fluid flow around the vessel at 10 m/s and 12 m/s speeds are conducted using STAR-CCM+ software. Two-phase flow is analyzed using finite volume method and volume of fluid technique. Moving mesh approach through the Overset technique is applied for discretization of the domain. Based on the experimental results, it is observed that addition of the transverse step enhances the vessel’s stability and reduces its trim. It is also concluded that the resistance of a single stepped high-speed vessel reduces, compared to a vessel of without step. Meanwhile, numerical studies indicate that as the second step moves away from the transom, the resistance increases, and trim decreases. It is also concluded that both single-step and two-step models are stable at speeds up to 12 m/s.
rmvPFBAM: Removing Primers from BAM Files Based on Amplicon-Based Next-Generation Sequencing and Cloud Computing When Analyzing Personal Genome Data

Personal genomic data constitute one important part of personal health data. However, due to the large amount of personal genomic data obtained by the next-generation sequencing technology, special tools are needed to analyze these data. In this article, we will explore a tool analyzing cloud-based large-scale genome sequencing data. Analyzing and identifying genomic variations from amplicon-based next-generation sequencing data are necessary for the clinical diagnosis and treatment of cancer patients. When processing the amplicon-based next-generation sequencing data, one essential step is removing primer sequences from the reads to avoid detecting false-positive mutations introduced by nonspecific primer binding and primer extension reactions. At present, the removing primer tools usually discard primer sequences from the FASTQ file instead of BAM file, but this method could cause some downstream analysis problems. Only one tool (BAMClipper) removes primer sequences from BAM files, but it only modified the CIGAR value of the BAM file, and false-positive mutations falling in the primer region could still be detected based on its processed BAM file. So, we developed one cutting primer tool (rmvPFBAM) removing primer sequences from the BAM file, and the mutations detected based on the processed BAM file by rmvPFBAM are highly credible. Besides that, rmvPFBAM runs faster than other tools, such as cutPrimers and BAMClipper.
Simulation optimisation of pull control policies for serial manufacturing lines and assembly manufacturing systems using genetic algorithms

Several efficient pull production control policies for serial lines implementing the lean/JIT manufacturing philosophy can be found in the production management literature. A recent development that is less well-studied than the serial line case is the application of pull-type policies to assembly systems where manufacturing operations take place both sequentially and in parallel. Systems of this type contain assembly stations where two or more parts from lower hierarchical manufacturing stations merge in order to produce a single part of the subsequent stage. In this paper we extend the application of the Base Stock, Kanban, CONWIP, CONWIP/Kanban Hybrid and Extended Kanban production control policies to assembly systems that produce final products of a single type. Discrete-event simulation is utilised in order to evaluate the performance of serial lines and assembly systems. It is essential to determine the best control parameters for each policy when operating in the same environment. The approach that we propose and probe for the problem of control parameter selection is that of a genetic algorithm with resampling, a technique used for the optimisation of stochastic objective functions. Finally, we report our findings from numerical experiments conducted for two serial line simulation scenarios and two assembly system simulation scenarios.
RESEARCH OF THE EFFICIENCY OF THE APRIORI GROUP ALGORITHMS ON DIFFERENT DATABASE SIZES

The results of the work analysis of associative rule search algorithms for handling Big data are presented in the paper. The most famous modifica-tions of Apriori algorithms for finding associative rules are considered. The re-sults of the research of the efficiency of linear algorithms Apriori and Apriori-TID on the data of different volumes using computers with standard RAM vol-ume are presented. The feasibility of using the AIS algorithm and its parallel implementation on the Hadoop MapReduce framework is substantiated. A comparison of the linear implementation of the AprioriTID algorithm and the parallel implementation of the AIS algorithm is provided. The conclusions about the effectiveness of using a parallel algorithm to solve a formulated prob-lem was given.
Motion Sickness, Motivation, Workload and Task Performance in Automated Vehicles

Previous literature has reported moderate losses in performance on cognitive tasks in the presence of mild motion sickness and concluded that motion sickness likely affected task motivation. These studies have used simple fundamental cognitive tasks, unlike the activities users of automated vehicles are expected to engage in. In this study we used a reading comprehension task with ecological relevance to automated driving. The study had a 2x2 withinsubjects factorial design. The factors were the presence or the absence of motion and task incentive. We found no effect of motion nor incentive on task performance. We did however find a significant effect of motion sickness on subjective workload. This may mean that under more naturalistic conditions motion sickness may lead to task avoidance, which is of importance to the utility and acceptance of automated vehicles
AMD Prefetch Attacks through Power and Time

Modern operating systems fundamentally rely on the strict isolation of user applications from the kernel. This isolation is enforced by the hardware. On Intel CPUs, this isolation has been shown to be imperfect, for instance, with the prefetch side-channel. With Meltdown, it was even completely circum-vented. Both the prefetch side channel and Meltdown have been mitigated with the same software patch on Intel. As AMD is believed to be not vulnerable to these attacks, this software patch is not active by default on AMD CPUs. In this paper, we show that the isolation on AMD CPUs suffers from the same type of side-channel leakage. We discover timing and power variations of the prefetch instruction that can be observed from unprivileged user space. In contrast to previous work on prefetch attacks on Intel, we show that the prefetch instruction on AMD leaks even more information. We demonstrate the signiﬁcance of this side channel with multiple case studies in real-world scenarios. We demonstrate the ﬁrst microarchitectural break of (ﬁne-grained) KASLR on AMD CPUs. We monitor kernel activity, e.g., if audio is played over Bluetooth, and establish a covert channel. Finally, we even leak kernel memory with 52 . 85 B / s with simple Spectre gadgets in the Linux kernel. We show that stronger page table isolation should be activated on AMD CPUs by default to mitigate our presented attacks successfully.
Externally controlled and switchable 2D electron gas at the Rashba interface between ferroelectrics and heavy d metals

Strong spin-orbit coupling in noncentrosymmetric materials and interfaces results in remarkable physical phenomena, such as nontrivial spin textures, which may exhibit Rashba, Dresselhaus, and other intricated configurations. This provides a promising basis for nonvolatile spintronic devices and further implications. Here, we simulate from first principles a two-dimensional electron gas in ultrathin platinum and palladium layers grown on ferroelectric PbTiO3(001). The latter allows, in principle, to switch and control the spin-to-charge conversion by the polarization reversal. We show how the band structure and its Rashba splitting differ in the Pt and Pd overlayers and how these electronic features change with increasing the overlayer thickness and upon reversal of polarization. Besides, for both overlayers, we simulated their current-voltage (I−V ) characteristics, the resistance of which upon the polarization reversal changes between 20 % and several hundred percent. The reported findings can be used to model directly the Rashba-Edelstein effect.
Recognition of Abnormal Human Behavior in Elevators based on CNN

This study explores a CNN based model to identify abnormal behavior in elevator cabs, which I have named S-LRCN ( S-Long-term Recurrent Convolutional Network). It starts with the detection of key points of the human skeleton by using the Openpose method, then further detects and tracks the human body through the CenterNet and DeepSort methods, and finally integrates the Long Short Term Memory Network (LSTM) and Convolutional Neural Network (CNN) to form a deep learning model. In this study, a large dataset (500 video clips) collected from real elevator cabs with different backgrounds has been applied to ensure the robustness and generalizability of the proposed model. At last, this study applies the two mainstream dangerous human behaviors, i.e., door blocking and door picking as case studies to test and evaluate the usability and availability. Experimental results show that the model has a 85% recognition rate of abnormal behavior.
Analytical procedures for evaluating factors that affect joint faulting for jointed plain concrete pavements using the Long-Term Pavement Performance database

The objective of this study was to identify and quantify design and construction features most important to joint faulting of joint plain concrete pavements. With data obtained from the Long-Term Pavement Performance (LTPP) database, an analysis approach that combined pavement engineering expertise and modern data analysis techniques was to develop guidelines for improved design and construction of Portland cement concrete (PCC) pavement. The approach included typical preliminary analyses, but emphasis was placed on using a series of multivariate data analysis techniques. Discriminant analysis was used to develop models that classify individual pavement into performance groups developed by cluster analysis, which was used to partition the pavements into three distinct groups representing good, normal, and poor performance. These models can be used to classify and evaluate additional or new pavements performance throughout the pavement's design life. To quantify the levels of the key design and constructio.
Integrated and Continuing Transportation Services for Seniors

The aging of the American population has raised a number of concerns about senior mobility. The New Freedom (NF) program, which was designed to go above and beyond the transportation requirements of the Americans with Disabilities Act, has been used to fund transportation for seniors. The primary purpose of this paper is to present the results of an exploratory analysis of the social, physical, and functional health and mobility outcomes experienced by seniors who are clients of NF services and the associated Coordinated Human Services Transportation Plan (CHSTP) processes. The paper uses data from primary surveys of the following groups from seven urban, suburban, and rural locations: (a) NF-funded transportation service users, (b) program managers operating the services, and (c) locally selected lead and partner organizations involved in developing the CHSTPs. Results show that concerns about senior mobility vary significantly by a number of functional, social, and physical disability indicators, including instrumental activities of daily living. These indicators are substantially more complex than a chronological accounting of age. A principal component analysis yielded two constructs underlying seniors’ mobility: a transportation deprivation component and an independence and health deprivation component. Each component has implications for different types of services. To the extent that the NF program has supported transportation services that are supplemental to integrated care for seniors and thereby enable a continuum of care, the program has enhanced community-based interventions to meet the complex mobility needs of seniors in the seven locations.
Predictive Value of the PaO2/FIO2 Ratio for Mortality in Patients with Acute Respiratory Distress Syndrome: A Systematic Review and Meta-Analysis

BackgroundPaO2/FIO2 (P/F) ratio has been used to define the severity of acute respiratory distress syndrome (ARDS) despite the controversy of its clinical utility. This systematic review and meta-analysis (SRMA) aimed to obtain summary estimates of predictive performance of the P/F ratio for predicting mortality in ARDS patients.MethodsWe included a study wherein the study population comprised ARDS patients in anyclinical setting. Medline and Cochrane Central Registry of Controlled Trials were searched for all English language articles. We performed a SRMA on the accuracy of diagnostic prognostic tests using QUADAS-2 tool to evaluate the risk of bias. To pool the results, we applied the bivariate model and obtained summary point estimates of sensitivity and specificity with 95% CIs.ResultsTwenty-eight trials and 38270 patients were included in the meta-analysis. Most of the study settings were in the intensive care units. The overall risk of bias was high. The pooled sensitivity of the P/F ratio in all included studies for a P/F ratio of 100 was 43.6% (95% CI, 36.9-50.5%) and the specificity was 71.1% (95% CI, 66.7-75.1%) and those for a P/F ratio of 200 were 83.2% (95% CI, 78.2-87.2%) and 26.2% (95% CI, 21.2-31.9%). ConclusionThe P/F ratio had high sensitivity and moderate specificity at a P/F ratio of 200 and 100 respectively. , which supports the use of the P/F ratio for screening ARDS patients who are at risk of deterioration.Trial registration: The study was registered in UMIN with registration number 000041058.
Mode conversion at discontinuities in finite-width conductor-backed coplanar waveguide

The effect of overmoding in a conductor-backed coplanar waveguide is discussed, with special emphasis on mode conversion of discontinuities. The coplanar waveguide gap end and shorted end are studied by means of a fully electromagnetic application of the moment-method technique. Significant conversion occurs at the gap end. The results of a simple experiment which partially verify the analysis are described. >
The structure-activity relationship between precursor ne structure and cathodes performance in Ni-rich layered oxide

Lang Qiu Sichuan University Mengke Zhang Sichuan University Kanghui Hu Sichuan University Yang Song Sichuan University Zhenguo Wu Sichuan University Luchao Yue University of Electronic Science and Technology of China Wei Xiang Sichuan University Yong Ming Sungkyunkwan University (SKKU) Gong-Ke Wang Henan Normal University Yu-Xia Liu Shaanxi University of Science and Technology https://orcid.org/0000-0003-1139-8563 Yan Sun 13207516703 Jun Zhang Sichuan University Bin Zhang Yibin Libao New Material Co., Ltd Xiaodong Guo (  xiaodong2009@163.com ) Sichuan University https://orcid.org/0000-0003-2180-1985
Optical Coherence Tomography for Non-Invasive ex vivo Investigations in Dental Medicine — a Joint Group Experience (Review)

This review emphasizes the current knowledge related to optical coherence tomography (OCT) as a non-invasive diagnostic tool to perform ex vivo and showing great potential for in vivo structural imaging of features in the oral cavity. OCT technology can generate high-resolution cross-sectional and en-face images of the internal architecture of the investigated sample (2-3 mm in depth). To this goal, en-face time domain OCT (TD-OCT) and spectral domain OCT (SD-OCT) were employed. Topics included in this review refer to OCT non-destructive evaluations of: dental abfraction and attrition, material defects and micro-leakages at the tooth-filling interface, temporal-mandibular joint disc, quality of bracket bonding on dental hard tissue, prosthetic restorations and micro-leakages at prosthetic interfaces, root canals, presence or absence of apical micro-leakages, and osteo-integration of dental implants and of bone grafting materials. OCT revealed internal features of the material investigated with greater sensitivity than current diagnostic methods. We put our research in context with others’ results but the review reflects primarily our joint group experience and it presents images collected with our OCT systems only. The studies demonstrate the viability of OCT as a useful tool in dental medicine practice, as well as in research. Being completely non-invasive, OCT can be extended to soft tissue. Both TD and SD implementations prove the unique capabilities of OCT. For handheld scanning devices it is expected that the swept source principle (as one of the SD possibilities) will prevail, due to its high speed that allows for the reduction of distorting effects caused by the involuntary movements of the hand and of the patient. For high transversal resolution investigations, especially in more research oriented studies, it is expected that en-face TD-OCT will continue to coexist with SD-OCT methods, offering additionally a low cost quick provision of en-face view and compatibility with dynamic focus. Dynamic focus, that is the simultaneous adjustment of focus and coherence gate in depth is incompatible with SD-OCT methods and require repetitions of acquisitions under different focus in order to improve the transversal resolution, or more complex heads with division of the optical path in the object arm along different focus adjustments. In this respect, en-face TD-OCT provides a lower cost alternative to high transversal resolution of static samples. We have shown that complementary studies are possible embracing OCT with more traditional methods, such as confocal microscopy and microCT. Combination of principles is expected to evolve due to their limitations when considered separately.