Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep interactive text prediction and quality estimation in translation interfaces

The output of automatic translation systems is usually destined for human consumption. In most cases, translators use machine translation (MT) as the first step in the process of creating a fluent translation in a target language given a text in a source language. However, there are many possible ways for translators to interact with MT. The goal of this thesis is to investigate new interactive designs and interfaces for translation. In the first part of the thesis, we present pilot studies which investigate aspects of the interactive translation process, building upon insights from Human-Computer Interaction (HCI) and Translation Studies. We developed HandyCAT, an open-source platform for translation process research, which was used to conduct two user studies: an investigation into interactive machine translation and evaluation of a novel component for post-editing. We then propose new models for quality estimation (QE) of MT, and new models for es- timating the confidence of prefix-based neural interactive MT (IMT) systems. We present a series of experiments using neural sequence models for QE and IMT. We focus upon token-level QE models, which can be used as standalone components or integrated into post-editing pipelines, guiding users in selecting phrases to edit. We introduce a strong recurrent baseline for neural QE, and show how state of the art automatic post-editing (APE) models can be re-purposed for word-level QE. We also propose an auxiliary con- fidence model, which can be attached to (I)-MT systems to use the model’s internal state to estimate confidence about the model’s predictions. The third part of the thesis introduces lexically constrained decoding using grid beam search (GBS), a means of expanding prefix-based interactive translation to general lexical constraints. By integrating lexically constrained decoding with word-level QE, we then suggest a novel interactive design for translation interfaces, and test our hypotheses using simulated editing. The final section focuses upon designing an interface for interactive post-editing, incorporating both GBS and QE. We design components which introduce a new way of interacting with translation models, and test these components in a user-study.
Voting based ensemble improves robustness of defensive models

Developing robust models against adversarial perturbations has been an active area of research and many algorithms have been proposed to train individual robust models. Taking these pretrained robust models, we aim to study whether it is possible to create an ensemble to further improve robustness. Several previous attempts tackled this problem by ensembling the soft-label prediction and have been proved vulnerable based on the latest attack methods. In this paper, we show that if the robust training loss is diverse enough, a simple hard-label based voting ensemble can boost the robust error over each individual model. Furthermore, given a pool of robust models, we develop a principled way to select which models to ensemble. Finally, to verify the improved robustness, we conduct extensive experiments to study how to attack a voting-based ensemble and develop several new white-box attacks. On CIFAR-10 dataset, by ensembling several state-of-the-art pre-trained defense models, our method can achieve a 59.8% robust accuracy, outperforming all the existing defensive models without using additional data.
A Review on Design and Implementation of Sigma Delta Converter for Neural Recording Implants

Downsized neural distinguishing microsystem has ended up being dynamically basic for brain work examination. Progress in remote and microsystems advancement have presented new devices that can clearly interface with the central tactile framework for enabling and also watching neural equipment. In this paper, we have review a ultra lowcontrol sigma-delta easy to-automated converter (ADC) proposed for use into huge scale multi-channel neural record embeds. An inductively filled 32-channel remote joined neural record (WINeR) structure on-achip (SoC) to be in the long run used for no less than one little uninhibitedly acting animals. The inductive controlling is proposed to facilitate the animals from passing on unwieldy batteries used as a piece of various remote systems, and enables long narrative sessions. We have survey the WINeR structure uses time-division multiplexing close by a novel power arranging technique that reductions the current in unused low-tumult enhancers (LNAs) to cut the total SoC control usage. This proposed diagram, which gives a survey on 9 bits using a one-piece oversampled ADC, presents a couple of alluring features that contemplate an in-channel ADC contrive, where one sigma-delta converter is suited each channel, enabling change of flexible systems that would interface have the capacity to with different sorts of highthickness neural microprobes. The proposed 11 bit ADC is reviewed in TSMC 90nm general propose (GP) CMOS development.
Efeitos de dois procedimentos educacionais sobre os sintomas musculoesqueléticos em trabalhadores administrativos Effects of two educational programs on musculoskeletal symptoms in office workers

Objective: To investigate the effect of applying two educational programs (one using a self-instructional approach and the other using a traditional approach similar to educational workshops), on the perceived frequency of musculoskeletal symptoms. Methods: A quasi- experimental study was conducted in 94 office workers in a public company. The participants were divided into three groups through simple randomized sampling with no replacement. The first group (32 employees) underwent a traditional/workshop program, the second (28) used a self-instructional manual and the third (34) was a Control Group. The frequency of musculoskeletal symptoms was measured by means of the Nordic Musculoskeletal Questionnaire, at the beginning of the program and 30 days after its completion. The statistical analysis consisted of descriptive statistics, a nonparametric analysis of variance technique for a repeated measure model in three independent groups and the Goodman test. Results: From the data collected in pre and post-test comparisons, it was observed that the traditional/workshop educational program significantly reduced the frequency of musculoskeletal symptoms over the final seven days. For the self-instructional manual group and control group, no difference was observed in the frequency of musculoskeletal symptoms. Conclusions: It could be concluded that the interventions, particularly the traditional approach using educational workshops, had a positive effect on the individuals' actions. Despite the complexity of some of the preventive measures needed, there was a reduction in musculoskeletal symptoms of the participants during work.
RNA nucleosides built in one prebiotic pot

Origins-of-life research models integrate the synthesis of RNA building blocks For decades, the RNA world has been one of the most influential hypotheses regarding the origins of life on Earth. In this hypothetical era before the emergence of DNA and proteins, “life” on primordial Earth consisted of RNA molecules that both store genetic information and catalyze self-replication reactions (1). Despite its popularity with researchers, the RNA world hypothesis has suffered from its own origins conundrum: A mechanism for the simultaneous prebiotic synthesis of RNA nucleosides from both the purine and pyrimidine families has long eluded scientists (2). Although disparate prebiotic syntheses have been demonstrated for the two classes of RNA nucleosides (3, 4), no single geochemical scenario has generated both. Now, on page 76 of this issue, Becker et al. (5) report on chemistry that accomplishes this long-awaited goal.
Preference-based serial decisions are counterintuitively influenced by emotion regulation and conscientiousness

Our decisions have a temporally distributed order, and different choice orders (e.g., choosing preferred items first or last) can lead to vastly different experiences. We previously found two dominant strategies (favorite-first and favorite-last) in a preference-based serial choice setting (the ‘sushi problem’). However, it remains unclear why these two opposite behavioral patterns arise: i.e., the mechanisms underlying them. Here we developed a novel serial-choice task, using pictures based on attractiveness, to test for a possible shared mechanism with delay discounting, the ‘peak-end’ bias (i.e., preference for experienced sequences that end well), or working-memory capacity. We also collected psychological and clinical metric data on personality, depression, anxiety, and emotion regulation. We again found the two dominant selection strategies. However, the results of the delay, peak-end bias, and memory capacity tasks were not related to serial choice, while two key psychological metrics were: emotion regulation and conscientiousness (with agreeableness also marginally related). Favorite-first strategists actually regulated emotions better, suggesting better tolerance of negative outcomes. Whereas participants with more varied strategies across trials were more conscientious (and perhaps agreeable), suggesting that they were less willing to settle for a single, simpler strategy. Our findings clarify mechanisms underlying serial choice and show that it may reflect a unique ability to organize choices into sequences of events.
Design and performance of a second-generation surface-induced dissociation cell for Fourier transform ion cyclotron resonance mass spectrometry of native protein complexes.

A second-generation ("Gen 2") device capable of surface-induced dissociation (SID) and collision-induced dissociation (CID) for Fourier transform ion cyclotron resonance mass spectrometry of protein complexes has been designed, simulated, fabricated, and experimentally compared to a first-generation device ("Gen 1"). The primary goals of the redesign were to 1) simplify SID by reducing the number of electrodes, 2) increase CID and SID sensitivity by lengthening the collision cell, and 3) increase the mass range of the device for analysis of larger multimeric proteins, all while maintaining the normal instrument configuration and operation. Compared to Gen 1, Gen 2 exhibits an approximately 10x increase in sensitivity in flythrough mode, 7x increase in CID sensitivity for protonated leucine enkephalin (m/z 556) and 14x increase of CID sensitivity of 53 kDa streptavidin tetramer. It also approximately doubles of the useful mass range (from m/z 8,000 to m/z 15,000) using a rectilinear ion trap with a smaller inscribed radius or triples it (to m/z 22,000) using a hexapole collision cell and yields a 3-10x increase in SID sensitivity. We demonstrate the increased mass range and sensitivity on a variety of model molecules spanning nearly 3 orders of magnitude in absolute mass and present examples where the high resolution of the FT-ICR is advantageous for deconvoluting overlapping SID fragments.
Flat foot among Saudi Arabian army recruits: prevalence and risk factors.

This study determined the prevalence and risk factors for flat foot among 18-21-year-old male Saudi Arabian army recruits. Among 2100 military recruits, the prevalence of flat foot was 5.0%. A case-control logistic regression analysis of risk factors (104 cases and 412 controls) showed family history, wearing shoes during childhood, obesity and urban residence were significantly associated with flat foot. No associated complaints were reported among the cases and thus flexible flat foot does not seem to be a cause of any disability. Le pied plat parmi les recrues militaires saoudiennes : prevalence et facteurs de risque RESUME Cette etude a determine la prevalence et les facteurs de risque pour le pied plat chez des recrues militaires saoudiennes âgees de 18 a 21 ans. La prevalence du pied plat s'elevait a 5,0 % parmi 2100 recrues militaires. Une analyse de regression logistique des facteurs de risque portant sur 104 cas et 412 temoins a montre que des antecedents familiaux, le port de chaussures durant la petite enfance, l'obesite et la residence urbaine etaient significativement associes au pied plat. Aucune plainte associee n'a ete signalee parmi les cas et le pied plat souple ne semble donc pas etre une cause d'incapacite.
Automation Of Independent Path Searching using Depth First Search

In a basis path testing, there are independent paths that must be passed/tested at least once to make sure there are no errors in the code and ensure all pseudocode have implemented on the code. Previously, the independent path was generated using the Genetic Algorithm, but the number of iterations influenced the likelihood of the emergence of the corresponding the independent path. Besides, the pseudocode was also unable to be used directly since it must be implemented first, this makes finding an independent path longer because it has to implement the code. This research aims to find out how to find the independent path directly from pseudocode using a graph and how well the Depth First Search algorithm in finding the independent path. It was chosen because it was able to find the paths from a point to a particular point in a graph. The result of the system accuracy test was able to find the correct independent path as much as 52 from 76 test data, where the result of accuracy is 68.4% on average.
Three-dimensional convolutional neural networks applied to video sensor-based gait recognition

In this paper, we propose a novel gait representation based on 3D-CNN, i.e., learning spatio-temporal multi-scale gait identity features (GaitID) using the 3-dimensional convolutional networks. Our contributions include: 1) explore different numbers of input frames for 3D-CNN model, 2) evaluate different features and gait representations in 3D-CNN, and 3) improve the net structure to learn multi-scale gait features with low dimensions. Nearest neighbor (NN) classifier was applied to identify the gait. When compared with other existing methods, the results reported on the CASIA-B dataset demonstrated that the proposed method not only achieved a competitive performance, but also still retained the discriminative power in a very low dimension (128-D), even with a simpler classifier.
The Effect of Explicit and Implicit Instructions and Sleep on Consolidation of the Accuracy of Elements of a Fine Motor Skill

Two processes are suggested for intervention in the learning of motor skills. These include explicit process in which the performer consciously knows the acquisition of the skill and the other one is an implicit process in which the performer has no conscious knowledge of acquiring the skill. The purpose of this study was to investigate the effect of explicit and implicit instructions and sleep on the performance of the fine motor skill. Participants in this study included 30 right-handed volunteer students with a good sleep quality, aged between 18-25 years old. They were randomly divided into two homogeneous explicit (N = 15) and implicit (N = 15) groups based on Purdue Fine Motor Skill Test and Simple Reaction Time. Each group participated in a three-time round at six in the afternoon, 12 midday on the same day, and at eight o'clock next morning in a Timed Motor Sequences Task. The data was analyzed by ANOVA with repeated measures. The results showed that in the accuracy of the short elements, stabilization was done but promotion was not observed but there was no change in the accuracy of the long elements and there was no significant difference between groups.
A recipe for big data value creation

Purpose The purpose of this paper is to present a process-theory-based model of big data value creation in a business context. The authors approach the topic from the viewpoint of a single firm. Design/methodology/approach The authors reflect current big data literature in two widely used value creation frameworks and arrange the results according to a process theory perspective. Findings The model, consisting of four probabilistic processes, provides a “recipe” for converting big data investments into firm performance. The provided recipe helps practitioners to understand the ingredients and complexities that may promote or demote the performance impact of big data in a business context. Practical implications The model acts as a framework which helps to understand the necessary conditions and their relationships in the conversion process. This helps to focus on success factors which promote positive performance. Originality/value Using well-established frameworks and process components, the authors synthetize big data value creation-related papers into a holistic model which explains how big data investments translate into economic performance, and why the conversion sometimes fails. While the authors rely on existing theories and frameworks, the authors claim that the arrangement and application of the elements to the big data context is novel.
Efeito do pilates sobre a flexibilidade do tronco e as medidas ultrassonográficas dos músculos abdominais

INTRODUCAO: a Pilates consiste em um metodo de treinamento fisico e mental que trabalha a flexibilidade e a forca muscular. Esse metodo prioriza fortalecer o conjunto de musculos responsavel pelo controle de tronco, chamado de Powerhouse e, consequentemente, aumentar o trofismo dos musculos abdominais reto do abdome, obliquo interno e externo, transverso do abdome, gluteos, musculos do perineo e paravertebrais lombares.OBJETIVO: avaliar o efeito do metodo Pilates sobre o trofismo do grupamento abdominal e na flexibilidade do tronco, comparado a aplicacao de uma tecnica tradicional de fortalecimento dos musculos abdominais e alongamentos estaticos em mulheres saudaveis.METODOS: treze mulheres sedentarias e saudaveis na faixa etaria entre 18 e 25 anos foram submetidas a 10 sessoes de Pilates grupo Pilates, n = 6 e 10 sessoes de alongamento e fortalecimento tradicionais grupo controle, n = 7. Antes e apos as intervencoes, o trofismo da musculatura abdominal das voluntarias foi avaliado atraves do ultrassom e a flexibilidade do tronco atraves do fleximetro.RESULTADOS: no grupo Pilates, apos a intervencao, houve um aumento significativo das medidas ultrassonograficas do reto do abdome, da amplitude da rotacao para direita e esquerda e da inclinacao da coluna vertebral para a esquerda. No grupo controle, observou-se melhora apenas na rotacao para a esquerda.CONCLUSAO: o numero de sessoes pode ter sido insuficiente para que ocorresse aumento do trofismo de todos os musculos avaliados e da flexibilidade do tronco. E importante investir em pesquisas sobre Pilates, especialmente com a utilizacao de metodos de imagem mais acurados.
QRED: A Q-Learning-based Active Queue Management Scheme

The Active Queue Management (AQM) algorithm is one of most important research fields in network congestion control. To adjust the maximum dropping probability (maxp) according to the network situation the maxp calculation based on the RED algorithm is improved using the Q-learning algorithm, and a new algorithm, known as QRED (Q-learning RED), is proposed. The self-adaptive adjustment for the maxp is achieved using the QRED algorithm and the queue length stability in a dynamic network environment is realized. In addition, the QRED algorithm not only avoids the sensitivity of the RED algorithm parameters, but also adapts the packet loss rate according to the specific network service type. Results based on the NS2 simulation show that the QRED algorithm has better stability in complex network environments, and hence, are superior to the RED active queue management algorithm.
A Uniform Query Framework for Heterogenous Data Management Systems

Most organizations today store their data in a variety of data storage systems such as relational databases, columnar stores, document stores, text search engines, and so forth. The adoption of multiple data storage systems tailored towards specific needs has its own challenges. The developers using these specialized systems have to often integrate several of them together. In the absence of a uniform framework, multiple engineers have to independently develop optimization logic and support different data retrieval mechanism for each system. The framework proposed in this paper intends to solve these problems by providing a uniform query framework to retrieve data from heterogenous systems. This paper also analyzes the response time of query framework with respect to individual data sources.
Autonomic Nervous System Responses to WholeBody Vibration and Mental Workload: A Pilot Study

Background: Whole-body vibration (WBV) and mental workload (MWL) are common stressors among drivers who attempt to control numerous variables while driving a car, bus, or train. Objective: To examine the individual and combined effects of the WBV and MWL on the autonomic nervous system. Methods: ECG of 24 healthy male students was recorded using NeXus-4 while performing two difficulty levels of a computerized dual task and when they were exposing to WBV (intensity 0.5 m/s2; frequency 3–20 Hz). Each condition was examined for 5 min individually and combined. Inter-beat intervals were extracted from ECG records. The time-domain and frequency-domain heart rate variability parameters were then extracted from the inter-beat intervals data. Results: A significant (p=0.008) increase was observed in the mean RR interval while the participants were exposed to WBV; there was a significant (p=0.02) reduction in the mean RR interval while the participants were performing the MWL. WBV (p=0.02) and MWL significantly (p<0.001) increased the standard deviation of normal-to-normal intervals with a moderate-to-large effect size. All active periods increased the low-frequency component and low-frequency/high-frequency ratio. However, only the WBV significantly increased the highfrequency component. A significant (p=0.01) interaction was observed between the WBV and MWL on low-frequency component and low-frequency/high-frequency ratio. Conclusion: Exposure to WBV and MWL can dysregulate the autonomic nervous system. WBV stimulates both sympathetic and parasympathetic nervous system; MWL largely affects sympathetic nervous system. Both variables imbalance the sympatho-vagal control as well.
The Echobot: An automated system for stimulus presentation in studies of human echolocation

Echolocation is the detection and localization of objects by listening to the sounds they reflect. Early studies of human echolocation used real objects that the experimental leader positioned manually before each experimental trial. The advantage of this procedure is the use of realistic stimuli; the disadvantage is that manually shifting stimuli between trials is very time consuming making it difficult to use psychophysical methods based on the presentation of hundreds of stimuli. The present study tested a new automated system for stimulus presentation, the Echobot, that overcomes this disadvantage. We tested 15 sighted participants with no prior experience of echolocation on their ability to detect the reflection of a loudspeaker-generated click from a 50 cm circular aluminum disk. The results showed that most participants were able to detect the sound reflections. Performance varied considerably, however, with mean individual thresholds of detection ranging from 1 to 3.2 m distance from the disk. Three participants in the loudspeaker experiment also tested using self-generated vocalization. One participant performed better using vocalization and one much worse than in the loudspeaker experiment, illustrating that performance in echolocation experiments using vocalizations not only measures the ability to detect sound reflections, but also the ability to produce efficient echolocation signals. Overall, the present experiments show that the Echobot may be a useful tool in research on human echolocation.