Miracle-dz/UniFAR-FTUs huggingface dataset:
Patients with neuropsychological disorders short after stroke have worse functional outcome: a systematic review and meta-analysis

Abstract Purpose To investigate if patients with neuropsychological disorders (neglect, aphasia, or cognitive dysfunction measured with the Mini-mental state examination) short after stroke have different functional outcome at follow-up compared to patients without these disorders. Methods Embase, Medline-Ovid, PsycINFO, Cochrane CENTRAL, Web of Science and Google Scholar were systematically searched for cohort studies up to 3 March 2019. PRISMA guidelines were followed. Functional outcome had to be measured with the Barthel Index or the Functional Independence Measure. If at least three studies studying the same neuropsychological disorder reported functional outcome at comparable follow-up, meta-analysis were performed and the quality of evidence was assessed using GRADE. Results The search resulted in 5398 unique articles and finally 27 articles were included. Pooled results show a standardized mean difference of −0.93 (95% confidence interval [−1.27 to −0.59]), indicating that the group with neglect short after stroke has significant lower functional outcome at follow-up. Regarding aphasia, the standardized mean difference was −0.50 (95% confidence interval [−0.72 to −0.28]). It appears in the limited articles available that patients with cognitive dysfunction have lower scores for functional outcome. Conclusions Patients with neglect or aphasia, especially aphasia with comprehension deficits, short after stroke have significant worse functional outcome. Implications for rehabilitation Clinicians should perform an extensive screening for neglect, aphasia, and cognitive disorders to make sure to diagnose the different neuropsychological disorders correctly. When patients with neuropsychological disorders are referred for rehabilitation, it can be expected that they need a longer rehabilitation period or may never reach the same level of functioning. Clinicians should pay attention to instructions of training moments outside therapy and involve caregivers and patients family making these training moments more effective.
Hospital-acquired and Community-acquired Uropathogens; Modelling of Infection

Urinary tract infections are among the most common human infections. They may be community-acquired or nosocomial, and caused by a variety of microorganisms. In the present study, we analysed more than 4000 urine samples collected from in-patients and outpatients, and registered the differences in the etiological spectrum of agents. The most widespread uropathogens are gram-negative rods, from them E. coli, Klebsiella spp. and the non-fermentive genus Pseudomonas. Women are more intensively affected by E. coli. From gram-positive cocci, the leading agents are coagulase negative Staphylococci, followed by S. aureus. No differences were registered between the genders. Polyresistance among gramnegative uropathogens is high.
Метод профилей для селекции признаков из временных рядов в задачах анализа данных

The problem of generating informative features based on time series can make models easier to use and improve the the quality of various data analysis methods. We introduce technology which includes the step of calculating the time series profiles, then applying the received characters in higher-level machine learning techniques. We use this approach to solve the problem of communication of weather factors and infectious diseases. Experimental results obtained on the data for the city Yekaterinburg for 200 5-2010 years.
Cabazitaxel Induced Thrombotic Microangiopathy in a Patient with Prostate Cancer

Cancer-associated thrombotic microangiopathy (TMA) refers to a group of disorders characterized by microangiopathic haemolytic anemia, thrombocytopenia, and ischemic organ damage. TMA manifestations can be induced by cancer or by chemotherapy. We report the case of a 64-year-old man with metastatic prostate cancer who experienced a Cabazitaxel-induced TMA manifestation. TMA responds to conservative therapy, dialysis without plasmaphoresis, with progressive recovered renal function.
COMPRESSIVE STRENGTH OF PLA BASED SCAFFOLDS: EFFECT OF LAYER HEIGHT, INFILL DENSITY AND PRINT SPEED

In the field of tissue engineering, the scaffold is required to provide a suitable environment for tissue regeneration. The scaffold should have desired mechanical properties that mimic the properties of the tissue. Fused deposition modeling (FDM) is one of the most widely used additive manufacturing process that can be used for scaffold fabrication. The mechanical properties of the fabricated scaffold are greatly dependent on the printing parameters. The goal of this study to evaluate the influence of the print parameter on the mechanical properties of the printed scaffold. Hence, in the present study three important process parameter namely, layer height, infill density, and print speed have been selected to study their effect on the mechanical strength by performing a compressive test. The scaffold has been fabricated using biocompatible, biodegradable Poly-lactic acid (PLA) material and compression test perform in accordance with ASTM D695 standard. Results reveal that compressive strength is significantly affected by infill density. Higher compressive strength was obtained at the higher infill density with a low porous structure. Suitable infill density has to be applied so that scaffold can be obtained with required porosity and compressive strength.
A Bit Error Rate Model of M-ary PSK OFDM Satellite Communication Systems for Educational Purpose

In this work, after a basic theoretical background on orthogonal frequency division multiplexing, our virtual bit error rate mode of M-ary PSK OFDM satellite communication systems, realised in Matlab, is presented. Elementary guide for the program is given: by simply typing the wanted parameters, communication system is defined. BER for this system can be plotted. This program is especially suitable for educational propose. Furthermore, in this work, influence of different PSK modulation, number of subcarriers and length of cyclic prefix on the signal performance and communication quality is analysed. It was shown that the BPSK gained the best signal performance, number of subcarriers has no influence on the transmission quality and by increasing the cyclic prefix BER is smaller.
Neurotrichinose : À propos d'une observation documentée par IRM

Les complications neurologiques des trichinoses sont rares. Nous en rapportons un cas documente par imagerie par resonance magnetique (IRM). A notre connaissance, seuls 3 cas de neurotrichinose avec anomalies IRM ont, jusqu'ici, ete rapportes. Les mecanismes physiopathologiques restent discutes (emboles parasitaires, phenomenes immuno-allergiques ou effet prothrombotique, voire neurotoxique des eosinophiles).
The prevalence of atrial fibrillation among adult Saudi patients with chronic heart failure at Prince Sultan Cardiac Center, Qassim (2011–2014)

Introduction: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia. The prevalence of both chronic heart failure and AF is steadily increasing. AF usually occurs as a consequence of heart failure itself and therefore it usually has a poor prognosis. Since the two conditions share common risk factors they frequently coexist. Objectives: To estimate the prevalence of AF among Saudi adult patients with chronic heart failure in Qassim province, and to identify the clinical and the sociodemographic characteristics of these patients. Materials and methods: A cross-sectional study using all medical records of patients who had been registered in Prince Sultan Center and diagnosed with heart failure during the period from 1 January 2011 to 30 June 2014. The review process included patients diagnosed with chronic heart failure and registered for follow-up during the study period. Prevalence of AF was calculated and the associated risk factors were determined. Results: The prevalence of AF among patients with chronic heart failure (n =68) was 14.7%. Prevalence among male patients (15.3%) was higher than female patients (12.5%). In both genders, the prevalence rose steeply with advancing age, and in each age stratum it was higher in males than females. The prevalence was significantly higher if chronic heart failure was associated with chronic diseases. Diabetes mellitus was present in 14.2% of patients with AF, and 19.3% in those with hypertension. None of the patients had a history of chronic kidney disease. Conclusions: Prevalence of AF among Saudi patients with chronic heart failure is high and it is significantly higher among male patients and patients with hypertension and diabetes mellitus.
The 2007 Asian Roundtable on Corporate Governance

This paper provides evidence of the causal relation between corporate governance and firm value, which is free from the endogeneity problems. A unique experimental setting is created by the first target announcement of an investment vehicle that focuses its attention exclusively on companies whose stocks are undervalued due to governance problems. We examine the stock price reaction of other firms to the announcement, and find that those companies whose governance qualities are poorer experience a more positive stock price reaction, even after controlling for the valuation level. This finding is consistent with the presence of potential gains accruing to outside investors from improving the quality of corporate governance, and thus shows that governance plays an independent role in determining the market value of a company. * Respectively, Mr Choi (buycorea@korea.ac.kr); Mr Lee (donglee@korea.ac.kr); and Mr Park (kspark@korea.ac.kr).
Comparing Portuguese Opinion Lexicons in Feature-Based Sentiment Analysis

In this paper we evaluate different lexicons in feature leve l opinion mining on Brazilian Portuguese movie reviews. Research in this field often considers English data, while other languag es are less explored. So we discuss and compare available resource s and techniques that can be applied to Portuguese for dealing wit h th s task. We found better results when using SentiLex adjetives . The results indicate a F-score of 0.73 for positive polarity rec ognition and 0.76 for negative polarity recognition.
SENTIPEDE: A Smart System for Sentiment-based Personality Detection from Short Texts

Personality distinctively characterises an individual and profoundly influences behaviours. Social media offer the virtual community an unprecedented opportunity to generate content and share aspects of their life which often reflect their personalities. The interest in using deep learning to infer traits from digital footprints has grown recently; however, very limited work has been presented which explores the sentiment information conveyed. The present study, therefore, used a computational approach to classify personality from social media by gauging public perceptions underlying factors encompassing traits. In the research reported in this paper, a Sentiment-based Personality Detection system was developed to infer trait from short texts based on the ’Big Five’ personality dimensions. We exploited the spirit of Neural Network Language Model (NNLM) by using a unified model that combines a Recurrent Neural Network named Long Short-Term Memory (LSTM) with a Convolutional Neural Network (CNN). We performed sentiment classification by grouping short messages harvested online into three categories, namely positive, negative, and nonpartisan. This is followed by employing Global Vectors (GloVe) to build vectorial word representations. As such, this step aims to add external knowledge to short texts. Finally, we trained each variant of the models to compute prediction scores across the five traits. Experimental study indicated the effectiveness of our system. As part of our investigation, a case study was carried out to investigate the existing correlation of personality traits and opinion polarities which employed the proposed system. The results support the prior findings of the tendency of persons with the same traits to express sentiments in similar ways.
Increasing Density through New Relations and PoS Encoding in WordNet.PT

This paper reports research developed in the scope of building a wordnet for Portuguese (WordNet.PT), particularly f ocusing on the impact the results obtained have in the dens ity of the network of relations and, thus, on its usability for NLP tasks. Following from basic research on different linguist ic phenomena and on strategies for modeling them in relationa l models of the lexicon, the implementation of these results am ounts to a richer resource, with new cross-PoS relations and inf ormation on event and argument structures, thus crucially co ntributing to accurately modeling all the main PoS in the databas e. We also define a way to integrate prepositions in wordnets a nd discuss the motivations and modeling strategies used to do so. Based on this work, we show how our contributions augment the c overage and the accuracy of WordNet.PT, by increasing th e density of the network of relations, thus making it more usa ble for NLP applications.
Observations sur la répartition et le comportement des anophèles de l'Afrique-Equatoriale Française, du Cameroun et de l'Afrique Occidentale

Les auteurs etudient les populations anoph6liennes de l'Afrique au sud du Sahara du point de vue de leur r6partition geographique et de leur r6le dans la transmission du paludisme. Ils analysent le comportement de toutes les especes rencontrees et appellent l'atten-tion sur certaines particularites (fluctuations des densites larvaires, variations de l'indice sporozoitique et du nombre des femelles unipares et multipares, relation entre l'indice maxillaire, les habi- tudes de repos et les gites, etc.) qu'ils ont pu observer au cours de leurs recherches. Ils presentent egalement un tableau et des cartes de repartition des differentes especes d'anopheles dans les pays et territoires consider6s.
Effects of Brassinosteroids on Postharvest Physiology of Horticultural Crops: A Concise Review

Brassinosteroids are natural polyhydroxylated steroidal plant growth regulators or phyto-hormones. These are ubiquitous in plant kingdom and influence a wide variety of molecular, physiological and biochemical responses of plants. Brassinosteroids have also been applied and their possible role has been investigated on postharvest physiology of various horticultural crops. Brassinosteroids regulate ripening of different non-climacteric and climacteric fruits and influence colour metabolism. They inhibit activities of peroxidase and polyphenol oxidase enzymes and delay enzymatic browning. Exogenous application of brassinosteroids inhibits cell wall degradation and delays softening of fruits. In addition, their application regulates sugar and energy metabolism in different fruit and vegetable crops. They suppress lipoxygenase and phospholipase D enzyme activities and conserve higher unsaturated fatty acid contents, suppress electrolyte leakage, inhibit lipid peroxidation and maintain higher membrane integrity eventually leading to suppressed chilling injury during postharvest storage. These alleviate oxidative stress and prolong storage life potential of various horticultural crops. So, the present review summarizes various roles and mechanism of action of brassinosteroids in extending postharvest life and maintaining quality of different horticultural crops.
Face Recognition with a 3D Camera On an Embedded Processor

In the recent years there have been significant advances in 2D face recognition by using deep neural networks. One of the potential next steps is to develop optimized 3D facial recognition. Shifting from 2D to 3D increases complexity of the problem by adding another dimension to data, making possible solutions more resource hungry. In this thesis we investigate different depth camera based facial recognition techniques and test their performance by deploying them on an embedded processor. We focus on applications for embedded systems and use a small low-resolution time of flight (ToF) camera with Raspberry Pi to keep overall system portable and compact. The first approach involves feature enrichment using an auto encoder and uses a Support Vector Machine (SVM) to train a classifier on these encoded features. The second and third approach are based on two different variant of Iterative Closest Point (ICP) along with a face detector and a facial landmark detector. In order to evaluate the performance of the developed techniques, we created a dataset of 20 identities captured with a low-resolution depth camera and use it for both training and testing. The presented results show that the ICP based techniques perform better in terms of accuracy and run several times faster than SVM based classifier. We achieved almost real-time performance on Raspberry Pi for face recognition.
Predicting Tamil Movies Sentimental Reviews Using Tamil Tweets

Recently people are more frequently using their mother tongue to express their opinion and view in the social media. Especially Indian languages are often used in social media messages. Tamil is one of the oldest language which has been used slightly higher percentage in micro blogs. Sentiment analysis has gained incredible development in recent times mostly for English language. However very less work of sentiment analysis has done for Indian languages like Hindi, Tamil, Kannada etc., In this paper we focus on Tamil language tweets. It is essential to analyse the Tamil language content for tweets and get perception of opinion expressed by the tweets. Our objective is to classify the sentiment of the Tamil movies based on Tamil tweets using Tamil SentiWordNet (TSWN). We proposed Term Frequency - Inverse Document Frequency (TF-IDF) method to find the sentiment polarity of the Tamil movie dataset. This method provides baseline for our research. Domain specific ontology is used to identify the primary sentiment categorization of the Tamil movies. In contextual semantic, the sentiment of a word may flip based on the neighbouring word. In this research, sentiment-bearing terms and its neighbouring terms in Tamil tweets are evaluated using contextual semantic sentiment analysis to get more accurate result for the movie sentimental classification.
Multipoint Passive Monitoring in Packet Networks

Traffic monitoring is essential to manage large networks and validate Service Level Agreements. Passive monitoring is particularly valuable to promptly identify transient fault episodes and react in a timely manner. This article proposes a novel, non-invasive and flexible method to passively monitor large backbone networks. By using only packet counters, commonly available on existing hardware, we can accurately measure packet losses, in different segments of the network, affecting only specific flows. We can monitor not only end-to-end flows, but any generic flow with packets following several different paths in the network (multipoint flows). We also sketch a possible extension of the method to measure average one-way delay for multipoint flows, provided that the measurement points are synchronized. Through various experiments we show that the method is effective and enables easy zooming in on the cause of packet losses. Moreover, the method can scale to very large networks with a very low overhead on the data plane and the management plane.
Supplementary material for Costly Information and Random Choice

In this supplementary material we show how the limited observability result for random choice proved in the main paper as an auxiliary result can be extended to other settings. A similar result naturally holds for menu preferences as considered in [Dillenberger et al (2014)] and for dynamic stochastic choice models as considered in [Frick, Iijima, Strzalecki (2018)] and [Duraj (2018)]. 1 Limited Observability in ex-ante choice and dynamic random utility models 1.1 Ex-ante choice and limited observability. In this subsection we keep the notation and preliminaries from subsection 2.1 of the main body of the paper. A considerable literature in decision theory starting from [Kreps (1979)] takes preferences over menus as the observable of the analyst. Similar limited observability results as for ex-post random choice hold true for menu preferences as well. [Dillenberger et al (2014)] axiomatize the menu preference coming from an agent as in the set up of our model. A valuation for menus V : A→R satisfying the conditions in [Dillenberger et al (2014)] and corresponding to an agent who can use information at no cost is said to satisfy a a subjective learning model in their paper. A similar result as Theorem 0 holds for the case where the data consists of comparisons between menus of options: to identify the taste and the information of the agent it is enough to observe comparisons from a sub-collection of menus Â which is again ‘rich’ enough. Take as an example a stronger version of the Non-degeneracy condition in Definition 3 of the main paper: Richness of the domain The set Â has non-empty interior in the Hausdorff topology. The axiom replacing the Local Mixture Invariance condition, is a relaxation of the usual Independence Axiom for menus. It says that when perturbing two menus from Â through a pair of arbitrary menus A,B ∈ A so that the pairs of perturbed menus are again in Â (that is, the analyst can observe their rankings), then the ranking of menus should only depend on whether the menu from Â was perturbed through A or through B and not on which menu from Â was used for the perturbation. Formally we write as follows. ∗duraj@g.harvard. edu †yihsuanl@bu.edu Note that this assumption is not minimal. We keep it throughout for expositional reasons.
Effect of Phosphinothricin on Transgenic Downy Birch (Betula pubescens Ehrh.) Containing bar or GS1 Genes

Weeds are a big problem in agriculture and forestry, and herbicides are the main tools to control them. Phosphinotricin (ammonium glufosinate, PPT) is one of the most effective non-selective herbicides, to which weeds hardly gain resistance, but the reasons for its effect and toxicity to plants are still unclear, and especially, it is little studied in trees, including transgenic ones. We studied the physiological responses of downy birch (Betula pubescens Ehrh.) containing the herbicide resistance bar gene or the cytosol glutamine synthetase GS1 gene (the target enzyme of the herbicide) to PPT-based Basta herbicide treatment in various doses under open-air conditions during two years. Birch saplings with the bar gene were resistant to a double field dose (10 L/ha), but the expression of the GS1 gene only slightly increased resistance compared to the control. Herbicide treatment increased the ammonium level in leaf tissue by 3–8 times, but this, apparently, was not the main cause of plant death. Among leaf pigments, chlorophyll B was the most resistant to PPT, and carotenoids were the most sensitive. Responses of birch trees with the GS1 gene (accumulation of ammonium, pigment content, and dehydration) during treatment with a low dose of herbicide were less pronounced than in control plants. One-year-old control and transgenic plants with the GS gene died after 2.5 L/ha treatment, and two-year-old plants lost foliage after such treatment but remained alive and developed buds four weeks after treatment. Herbicide treatment of plants with the bar gene did not cause significant deviations in height (first year) or the accumulation of aboveground biomass (second year). The obtained results improve our understanding of the effect of PPT on woody plants and can be used both to clarify mechanisms of herbicide action and in plantation forestry.