Miracle-dz/UniFAR-FTUs huggingface dataset:
Unsupervised Creation of Normalization Dictionaries for Micro-Blogs in Arabic, French and English

Text normalisation is a necessity to correctand make more sense of the micro-blogs messages, for information retrieval purposes. Unfortunately, tools and resources of text normalization are rarely shared. In this paper, an approach is presented based onan unsupervised method for text normalization using distributed representations of words, known also as "word embedding", applied on Arabic, French and English Languages. In addition, a tool will be supplied to create dictionaries for micro-blogs normalisation, in a form of pairs of misspelled word with its standard-form word, in the languages: Arabic, French and English. The tool will be available as open source including the resources: word embedding’s models (with vocabulary size of million words for Arabic language model, 5 million words for English language model and 683 thousand words for French language model), and also three normalization dictionaries of 10 thousand pairs in Arabic language, 3 thousand pairs in French language and 18 thousand pairs in English language. The evaluation of the tool shows an average in Normalization success of 96% for English language, 89.5% for Arabic Language and 85% for French Language. Also, the results of using an English language normalization dictionary with a sentiment analysis tool for micro-blog’s messages, show an in crease in f-measure from 58.15 to 59.56.
Successful Endoscopic Surgery for L5 Radiculopathy Caused by Far-Lateral Disc Herniation at L5-S1 and L5 Isthmic Grade 2 Spondylolisthesis in a Professional Baseball Player

ABSTRACT Background: We report the case of a professional baseball player who had severe leg pain due to lumbar lateral disc herniation at L4-5 and isthmic spondylolisthesis at L5 (double crash syndrome). For early recovery to competitive level, we performed minimally invasive endoscopic decompression surgery without fusion. There are few reports to discuss the usefulness of minimally invasive treatment for top athletes. Methods: A 29-year-old professional baseball player who played catcher was referred to us with a complaint of right leg pain. The previous doctor diagnosed far-lateral disc herniation and Grade 2 isthmic spondylolisthesis and recommended arthrodesis at L5-S1 as treatment for both pathologies. Radiological imaging showed that the right L5 nerve root was impinged by the 2 lumbar disorders, namely, far-lateral disc herniation and a ragged edge around a pars defect. We had taken into account the patient's occupation and his wish to avoid a lengthy sick leave, and we had performed endoscopic decompression surgery during the offseason. The far-lateral disc herniation at L5-S1 was removed under local anesthesia by percutaneous endoscopic discectomy, after which the ragged edge at the pars defect was removed under general anesthesia using a microendoscopic discectomy system. Given that the patient did not have any low back pain, arthrodesis was not considered. Results: The leg pain resolved after surgery. The following year (2015), the patient resumed playing baseball from the beginning of the season and played in 41 games. In the 2016 season, he played in 71 games without any symptoms. No further slippage was observed at radiological follow up 1 year after the surgery. Conclusions: Minimally invasive endoscopic surgery is an option for radiculopathy in very active patients who need an early return to their previous level of physical activity.
Congenital Nasolacrimal Duct Obstruction (CNLDO): A Review

Congenital nasolacrimal duct obstruction (CNLDO) is a common condition causing excessive tearing or mucoid discharge from the eyes, due to blockage of the nasolacrimal duct system. Nasolacrimal duct obstruction affects as many as 20% children aged <1 year worldwide and is often resolved without surgery. Available treatment options are conservative therapy, including observation, lacrimal sac massage and antibiotics, and invasive therapy. Observation, combined with conservative options, seems to be the best option in infants aged <1 year. Meanwhile, in children aged >1 year, nasolacrimal probing successfully addresses most obstructions. However, the most favorable timing for probing remains controversial. To alleviate persistent epiphora and mucous drainage that is refractory to probing, repeat probing, silicone tube intubation, balloon catheter dilation or dacryocystorhinostomy can be considered as available treatment options. Our review aims to provide an update to CNDO management protocols.
User-Oriented EFL Speaking through Application and Exercise: Instant Speech Translation and Shadowing in Authentic Context

In this study, an application (app) called ezTranslate was developed to aid English as foreign language (EFL) learning by assigning lessons that adapt to students’ interests, in order to motivate them to engage concurrently in physical activity in a real context. ezTranslate was developed by combining state-of-the-art technologies—automatic speech recognition and a cloud translation service, which permit effortless language translation. ezTranslate also offers user-oriented, self-speaking practice opportunities via its speech shadowing function. This app is designed (1) as an effective support tool for EFL speaking in authentic contexts and (2) to engage students in exercise as they walk in their environment. Results suggest that using ezTranslate in familiar situations significantly promotes student cooperation, as evidenced by their increased listening and speaking. Furthermore, there were significant differences in English speaking performance and homework aptitude in participants when using ezTranslate with or without authentic contexts. Indeed, this study’s findings emphasize the importance of authentic support for EFL speaking; namely, students’ interests. The familiarity and fascination of students with real contexts can motivate them to communicate in English better and more frequently. As for the effect of exercise on EFL learning, statistical analysis revealed that the more steps students take, the more they practice speaking English. These results are very promising. Creating an interactive medium in which students not only acquire knowledge but also move their bodies promotes brain and body activity vital to their overall health. In the near future, we plan to extend activity design, executing authentic drama-play to sustain effective, healthy EFL learning.
Optimal feature set for finger movement classification based on sEMG

One of the most important electrophysiological signal is the Electromyography (EMG) signal, which is widely used in medical and engineering studies. This signal contains a wealth of information about muscle functions. Therefore, the EMG signal is becoming increasingly important and has started to be used in many applications like finger movement rehabilitation. However, an advanced EMG signal analysis method is required for efficient usage of such applications. This signal analysis can include signal detection, decomposition, processing, and classification. There are many approaches in studying the EMG signals, however, one of the important factor of analyzing is to get the most efficient and effective features that can be extracted from the raw signal. This paper presents the best feature extraction set compared to previous studies. Where eighteen well-known features algorithm has been tested using the sequential forward searching (SFS) method to get excellent classification accuracy in a minimum processing time. Among these novel features only four combinations have been selected with perfect results, which are; Hjorth Time Domain parameters (HTD), Mean Absolute Value (MAV), Root Mean Square (RMS) and Wavelet Packet Transform (WPT). The superiority of this feature set has been proven experimentally, and the results show that the classification accuracy could reach up to 99% to recognize the individual and combined for ten classes of finger movements using only two EMG channels.
Convolutional Recurrent Neural Network for Fault Diagnosis of High-Speed Train Bogie

Timely detection and efficient recognition of fault are challenging for the bogie of high-speed train (HST), owing to the fact that different types of fault signals have similar characteristics in the same frequency range. Notice that convolutional neural networks (CNNs) are powerful in extracting high-level local features and that recurrent neural networks (RNNs) are capable of learning long-term context dependencies in vibration signals. In this paper, by combining CNN and RNN, a so-called convolutional recurrent neural network (CRNN) is proposed to diagnose various faults of the HST bogie, where the capabilities of CNN and RNN are inherited simultaneously. Within the novel architecture, the proposed CRNN first filters out the features from the original data through convolutional layers. Then, four recurrent layers with simple recurrent cell are used to model the context information in the extracted features. By comparing the performance of the presented CRNN with CNN, RNN, and ensemble learning, experimental results show that CRNN achieves not only the best performance with accuracy of 97.8% but also the least time spent in training model.
Making Sense of Family Deaths in Urban Senegal: Diversities, Contexts, and Comparisons

Despite calls for cross-cultural research, Minority world perspectives still dominate death and bereavement studies, emphasizing individualized emotions and neglecting contextual diversities. In research concerned with contemporary African societies, on the other hand, death and loss are generally subsumed within concerns about AIDS or poverty, with little attention paid to the emotional and personal significance of a death. Here, we draw on interactionist sociology to present major themes from a qualitative study of family deaths in urban Senegal, theoretically framed through the duality of meanings-in-context. Such themes included family and community as support and motivation; religious beliefs and practices as frameworks for solace and (regulatory) meaning; and material circumstances as these are intrinsically bound up with emotions. Although we identify the experience of (embodied, emotional) pain as a common response across Minority and Majority worlds, we also explore significant divergencies, varying according to localized contexts and broader power dynamics.
Screening of reference genes using real-time quantitative PCR for gene expression studies in Neoseiulus barkeri Hughes (Acari: Phytoseiidae)

Abstract A stable reference gene is a key prerequisite for accurate assessment of gene expression. At present, the real-time reverse transcriptase quantitative polymerase chain reaction has been widely used in the analysis of gene expression in a variety of organisms. Neoseiulus barkeri Hughes (Acari: Phytoseiidae) is a major predator of mites on many important economically crops. Until now, however, there are no reports evaluating the stability of reference genes in this species. In view of this, we used GeNorm, NormFinder, BestKeeper, and RefFinder software tools to evaluate the expression stability of 11 candidate reference genes in developmental stages and under various abiotic stresses. According to our results, β-ACT and Hsp40 were the top two stable reference genes in developmental stages. The Hsp60 and Hsp90 were the most stable reference genes in various acaricides stress. For alterations in temperature, Hsp40 and α-TUB were the most suitable reference genes. About UV stress, EF1α and α-TUB were the best choice, and for the different prey stress, β-ACT and α-TUB were best suited. In normal conditions, the β-ACT and α-TUB were the two of the highest stable reference genes to respond to all kinds of stresses. The current study provided a valuable foundation for the further analysis of gene expression in N. barkeri.
The relationship between serum leptin level and disease activity and inflammatory markers in fibromyalgia patients

OBJECTIVE: The aim of this study was to investigate whether there is a correlation between serum leptin level, disease activity and inflammation markers in patients with fibromyalgia syndrome (FMS). METHODS: A total of 48 patients with FMS diagnosed according to the 1990 American College of Rheumatology criteria were included in the study, as well as 36 healthy women as controls. The Visual Analogue Scale was used to gauge pain severity, the Fibromyalgia Impact Questionnaire was used to assess physical function, the 36-Item Short Form Health Survey was used to examine quality of life, and depression was measured with the Beck Depression Inventory. Blood samples were examined for erythrocyte sedimentation rate (ESR), C-reactive protein level (CRP), high-sensitivity CRP level (hsCRP), the neutrophil-to-lymphocyte ratio (NLR), and the serum leptin level was determined using the enzyme-linked immunosorbent assay method. RESULTS: The serum leptin level in patients with FMS was significantly higher than in the healthy group. However, no significant relationship was found between leptin level and clinical and inflammatory parameters. In addition, there were no significant differences between the patients and the control group in measurements of ESR, CRP, hsCRP, or NLR. CONCLUSION: A higher serum leptin level in patients with FMS suggested that leptin may play role in the pathogenesis of FMS, yet there was no relationship between leptin and clinical and inflammatory parameters, suggesting that leptin is not an indicator of disease activity in FMS. Additional research should be performed with larger patient groups.
Social Media and Suicide: A Review of Technology-Based Epidemiology and Risk Assessment.

INTRODUCTION Suicide is a significant public health problem among teenagers and young adults in the United States, placing significant stress on emergency departments (EDs) to effectively screen and assess for the presence of suicidality in a rapid yet efficient manner. METHODS A literature search was performed using PubMed and MEDLINE with the following terms: "Social media," "Suicide," "Facebook," "Twitter," "MySpace," "Snapchat," "Ethics," "Digital Media," and "Forums and Blog. " Data were extracted from each article, specifically the sample size, study setting, and design. Only English-language studies were included. We reviewed the reference lists of included articles for additional studies, as well. Abstracts, unpublished data, and duplicate articles were excluded. RESULTS A total of 363 articles met our initial criteria. Studies older than 10 years and/or in a language other than English were removed. After review, a total of 31 peer-reviewed articles were included in the study. Teenagers and young adults often fail to disclose risk factors to physicians, despite sharing them with the public on social media platforms such as Facebook and Twitter. Therefore, physician access to a patient's social media can assist in identifying suicidal ideation and/or acts. CONCLUSIONS Viewing a patient's social media accounts can help ED physicians gain perspective into his or her mental health status and identify those at risk for suicide; however, ethical and privacy concerns associated with this method of data gathering make implementation of such a practice controversial. To justify its use, formal prospective studies analyzing if and how physician access to a patient's social media influences care should be performed.
Flash Photography for Data-Driven Hidden Scene Recovery

Vehicles, search and rescue personnel, and endoscopes use flash lights to locate, identify, and view objects in their surroundings. Here we show the first steps of how all these tasks can be done around corners with consumer cameras. Recent techniques for NLOS imaging using consumer cameras have not been able to both localize and identify the hidden object. We introduce a method that couples traditional geometric understanding and data-driven techniques. To avoid the limitation of large dataset gathering, we train the data-driven models on rendered samples to computationally recover the hidden scene on real data. The method has three independent operating modes: 1) a regression output to localize a hidden object in 2D, 2) an identification output to identify the object type or pose, and 3) a generative network to reconstruct the hidden scene from a new viewpoint. The method is able to localize 12cm wide hidden objects in 2D with 1.7cm accuracy. The method also identifies the hidden object class with 87.7% accuracy (compared to 33.3% random accuracy). This paper also provides an analysis on the distribution of information that encodes the occluded object in the accessible scene. We show that, unlike previously thought, the area that extends beyond the corner is essential for accurate object localization and identification.
Constitutive androstane receptor 1 is constitutively bound to chromatin and ‘primed’ for transactivation in hepatocytes

The constitutive androstane receptor (CAR) is a xenobiotic sensor expressed in hepatocytes that activates genes involved in drug metabolism, lipid homeostasis, and cell proliferation. Much progress has been made in understanding the mechanism of activation of human CAR by drugs and xenobiotics. However, many aspects of the activation pathway remain to be elucidated. In this report, we have used viral constructs to express human CAR, its splice variants, and mutant CAR forms in hepatocytes from Car−/− mice in vitro and in vivo. We demonstrate CAR expression rescued the ability of Car−/− hepatocytes to respond to a wide range of CAR activators including phenobarbital. Additionally, two major splice isoforms of human CAR, CAR2 and CAR3, were inactive with almost all the agents tested. In contrast to the current model of CAR activation, ectopic CAR1 is constitutively localized in the nucleus and is loaded onto Cyp2b10 gene in the absence of an inducing agent. In studies to elucidate the role of threonine T38 in CAR regulation, we found that the T38D mutant was inactive even in the presence of CAR activators. However, the T38A mutant was activated by CAR inducers, showing that T38 is not essential for CAR activation. Also, using the inhibitor erlotinib, we could not confirm a role for the epidermal growth factor receptor in CAR regulation. Our data suggest that CAR is constitutively bound to gene regulatory regions and is regulated by exogenous agents through a mechanism which involves protein phosphorylation in the nucleus.
Fundamental Heart Sound Classification using the Continuous Wavelet Transform and Convolutional Neural Networks

Correct identification of the fundamental heart sounds is an important step in identifying the heart cycle stages. Heart valve pathologies can cause abnormal heart sounds or extra sounds, and an important distinguishing feature between different pathologies is the timing of these extra sounds in the heart cycle. In the design of an understandable heart sound analysis system, heart sound segmentation is an indispensable step. In this study classification of the fundamental heart sounds using continuous wavelet transform (CWT) scalograms and convolutional neural networks (CNN) is investigated. Classification between the first and second heart sound of scalograms produced by the Morse analytic wavelet was compared for CNN, support vector machine (SVM), and knearest neighbours (kNN) classifiers. Samples of the first and second heart sound were extracted from a publicly available dataset of normal and abnormal heart sound recordings, and magnitude scalograms were calculated for each sample. These scalograms were used to train and test CNNs. Classification using features extracted from a fully connected layer of the network was compared with linear binary pattern features. The CNN achieved an average classification accuracy of 86% when distinguishing between the first and second heart sound. Features extracted from the CNN and classified using a SVM achieved similar results (85.9%). Classification of the CNN features outperformed LBP features using both SVM and kNN classifiers. The results indicate that there is significant potential for the use of CWT and CNN in the analysis of heart sounds.
Betulinic acid inhibits cell proliferation, migration, and inflammatory response in rheumatoid arthritis fibroblast‐like synoviocytes

Betulinic acid (BA), a pentacyclic triterpene derived from the bark of the white birch tree, has been reported to have a variety of pharmacological effects, including antioxidant, anti‐inflammatory, antitumor, immunomodulatory, and antiarthritis properties. However, the role of BA in rheumatoid arthritis (RA) remains unclear. Thus, the objective of this study was to examine the effects of BA on RA fibroblast‐like synoviocytes (RA‐FLS) proliferation, migration, and inflammatory response, and further explore the potential underlying mechanisms. Our results showed that BA inhibited the proliferation, migration, and invasion of RA‐FLSs. BA also attenuated tumor necrosis factor‐α (TNF‐α), enhanced matrix metalloproteinases (MMPs) expression, and inflammatory cytokines production in RA‐FLS. Furthermore, BA prevented the activation of Akt/NF‐κB pathway in RA‐FLS exposed to TNF‐α. In conclusion, these findings indicated that BA inhibits cell proliferation, migration, and inflammatory response in RA‐FLS; and the Akt/NF‐κB signaling pathway was involved in the protective effect of BA on RA‐FLS. Thus, BA might be a potential therapeutic agent for the treatment of RA.
CEA LIST: Processing Low-Resource Languages for CoNLL 2018

In this paper, we describe the system used for our first participation at the CoNLL 2018 shared task. The submitted system largely reused the state of the art parser from CoNLL 2017 (https://github.com/tdozat/Parser-v2). We enhanced this system for morphological features predictions, and we used all available resources to provide accurate models for low-resource languages. We ranked 5th of 27 participants in MLAS for building morphology aware dependency trees, 2nd for morphological features only, and 3rd for tagging (UPOS) and parsing (LAS) low-resource languages.
Critical Packet Prioritisation by Slack-Aware Re-Routing in On-Chip Networks

Packet based Network-on-Chip (NoC) connect tens to hundreds of components in a multi-core system. The routing and arbitration policies employed in traditional NoCs treat all application packets equally. However, some packets are critical as they stall application execution whereas others are not. We differentiate packets based on a metric called slack that captures a packet's criticality. We observe that majority of NoC packets generated by standard application based benchmarks do not have slack and hence are critical. Prioritising these critical packets during routing and arbitration will reduce application stall and improve performance. We study the diversity and interference of packets to propose a policy that prioritises critical packets in NoC. This paper presents a slack-aware re-routing (SAR) technique that prioritises lower slack packets over higher slack packets and explores alternate minimal path when two no-slack packets compete for same output port. Experimental evaluation on a 64-core Tiled Chip Multi-Processor (TCMP) with 8×8 2D mesh NoC using both multiprogrammed and multithreaded workloads show that our proposed policy reduces application stall time by upto 22% over traditional round-robin policy and 18% over state-of-the-art slack-aware policy.