Miracle-dz/UniFAR-FTUs huggingface dataset:
Parallel Hashing Using Representative Points in Hyperoctants

The goal of hashing is to learn a low-dimensional binary representation of high-dimensional information, leading to a tremendous reduction of computational cost. Previous studies usually achieved this goal by applying projection or quantization methods. However, the projection method fails to capture the intrinsic data structures, and the quantization method cannot make full use of complete information by its strategy of partitioning original space. To combine their advantages and avoid their drawbacks, we propose a novel algorithm, termed as representative points quantization (RPQ), by using the representative points defined as the barycenters of points in the hyperoctants. To settle the problem of exponential time complexity with the growth of the coding length, for long hashing codes, we further propose a parallel RPQ (PRPQ) algorithm, by separating a long code into several short codes, re-coding the short codes in different low dimensional subspaces, and then concatenating them to a long code. Experiments on image retrieval tasks demonstrate that RPQ and PRPQ can well capture the main topology structure of data, showing that our algorithm achieves better performance than state-of-the-art methods.
Learning with Virtual Patients in Medical Education

VPL – Virtual Patient Learning is an online simulation system designed to train and assess clinical and relational abilities in a realistic and interactive problem-based learning scenario, where users (doctors and medical students) can interact and communicate with characters specifically designed to challenge their skills and facilitate the generation of learning objectives. Virtual Patients are designed to improve users' effectiveness in the areas of anamnesis, diagnosis, treatment and follow-up. Our Virtual Patient simulator is presented as an interactive movie based on pre-recorded clips with real actors, in which the learner plays the role of a physician. The dialogue between the simulated patient and the user takes place through selection from a set of questions and answers, or through a natural language processing system. At the end of each visit, the system provides a feedback, given directly through the patient's comments during a call with a friend. This feedback is based on the decisions and the communication strategy that the user applied during the last visit.
Unsupervised Features Extraction for Binary Similarity Using Graph Embedding Neural Networks

In this paper we consider the binary similarity problem that consists in determining if two binary functions are similar only considering their compiled form. This problem is know to be crucial in several application scenarios, such as copyright disputes, malware analysis, vulnerability detection, etc. The current state-of-the-art solutions in this field work by creating an embedding model that maps binary functions into vectors in $\mathbb{R}^{n}$. Such embedding model captures syntactic and semantic similarity between binaries, i.e., similar binary functions are mapped to points that are close in the vector space. This strategy has many advantages, one of them is the possibility to precompute embeddings of several binary functions, and then compare them with simple geometric operations (e.g., dot product). In [32] functions are first transformed in Annotated Control Flow Graphs (ACFGs) constituted by manually engineered features and then graphs are embedded into vectors using a deep neural network architecture. In this paper we propose and test several ways to compute annotated control flow graphs that use unsupervised approaches for feature learning, without incurring a human bias. Our methods are inspired after techniques used in the natural language processing community (e.g., we use word2vec to encode assembly instructions). We show that our approach is indeed successful, and it leads to better performance than previous state-of-the-art solutions. Furthermore, we report on a qualitative analysis of functions embeddings. We found interesting cases in which embeddings are clustered according to the semantic of the original binary function.
Detection of Mycobacterium lepromatosis in patients with leprosy in India

Introduction The most commonly noted reactions in leprosy patients are type 1 reactions and erythema nodosum leprosum, with some rare phenomenon of host response known as Lucio phenomenon or leprosy of Lucio and Latapi which is caused by Mycobacterium lepromatosis. So far, no case of M. lepromatosis has been reported from India. Materials and methods The main objective of this study was to detect any positive cases of M. lepromatosis in India with such a complication. We screened slit skin smear/biopsy samples from lepromatous leprosy (LL) patients reporting to The Leprosy Mission Community Hospitals across the country. Eighty-eight slit skin smears were collected from leprosy patients in 70% ethanol. DNA was extracted from all these samples. Polymerase chain reaction (PCR) was done for 2 genes; one set was for 16S rRNA and the other set was for coproporphyrinogen III oxidase (hemN) gene. Then, sequencing was done for all positive amplicons. Homology of the sequences was analyzed using the Basic Local Alignment Search Tool at the National Center of Biotechnology Information database. Results Among 88 isolates, we found 4 positive cases for M. lepromatosis. All 4 were LL cases with a bacteriological index ranging from 2+ to 4+. On the basis of the National Center of Biotechnology Information Basic Local Alignment Search Tool analysis, the sequenced amplicons of both genes matched with the M. lepromatosis 16S rRNA and phosphofructokinase genes but not with hemN gene of lepromatosis. This is the first report for the presence of M. lepromatosis in LL cases from India. Conclusion This new species M. lepromatosis exists beyond Mexico, Singapore and it is the cause of DLL in India also. It may cause dual infections along with M. leprae in endemic areas like India.
High Expression of PTPN3 Predicts Progression and Unfavorable Prognosis of Glioblastoma

Background PTPN3 was demonstrated to be involved in the progression of several types of cancers, such as gastric adenocarcinoma, lung cancer, and intrahepatic cholangiocarcinoma. However, its clinical significance in glioblastoma (GBM) has not been elucidated. Material/Methods We investigated the expression of PTPN3 in 95 cases of GBM with immunohistochemistry and in 8 pairs of fresh GBMs and their adjacent tissues with qualitative polymerase chain reaction. Moreover, the correlation between PTPN3 and clinicopathological factors was evaluated by chi-square test. The prognostic value of PTPN3 was investigated with univariate analysis and multivariate analysis. With MTT assay and Transwell assay, the oncogenic functions of PTPN3 in GBM proliferation and invasion were further investigated. Results Expression of PTPN3 in GBM tissues was significantly higher than in their corresponding adjacent tissues. High expression of PTPN3 was significantly associated with unfavorable prognosis of GBM. Moreover, in GBM cell lines, PTPN3 promoted cell proliferation and invasion, and the PTP common inhibitor pervanadate suppressed GBM proliferation and invasion. Conclusions Our experiments show that PTPN3 is an independent prognostic factor in GBM and indicated that postoperative detection of PTPN3 can be used to identify high-risk patients and guide individual treatment.
Regional Maximum Activations of Convolutions with Attention for Cross-domain Beauty and Personal Care Product Retrieval

Cross-domain beauty and personal care product image retrieval is a challenging problem due to data variations (e.g., brightness, viewpoint, and scale), and the rich types of items. In this paper, we present a regional maximum activations of convolutions with attention (RA-MAC) descriptor to extract image features for retrieval. RA-MAC improves the regional maximum activations of convolutions (R-MAC) descriptor considering the influence of background in cross-domain images (i.e., shopper domain and seller domain). More specifically, RA-MAC utilizes the characteristics of the convolutional layer to find the attention of an image, and reduces the influence of the unimportant regions in an unsupervised manner. Furthermore, a few strategies have been exploited to improve the performance, such as multiple features fusion, query expansion, and database augmentation. Extensive experiments conducted on a dataset consisting of half a million images of beauty care products (Perfect-500K) manifest the effectiveness of RA-MAC. Our approach achieves the 2nd place in the leader board of the Grand Challenge of AI Meets Beauty in ACM Multimedia 2018. Our code is available at: https://github.com/RetrainIt/Perfect-Half-Million-Beauty-Product-Image-Recognition-Challenge.
Neuropsychiatric disturbances in atypical parkinsonian disorders

Multiple system atrophy (MSA), progressive supranuclear palsy (PSP), and corticobasal degeneration (CBD) are the most common atypical parkinsonisms. These disorders are characterized by varying combinations of autonomic, cerebellar and pyramidal system, and cognitive dysfunctions. In this paper, we reviewed the evidence available on the presence and type of neuropsychiatric disturbances in MSA, PSP, and CBD. A MedLine, Excerpta Medica, PsycLit, PsycInfo, and Index Medicus search was performed to identify all articles published on this topic between 1965 and 2018. Neuropsychiatric disturbances including depression, anxiety, agitation, and behavioral abnormalities have been frequently described in these disorders, with depression as the most frequent disturbance. MSA patients show a higher frequency of depressive disorders when compared to healthy controls. An increased frequency of anxiety disorders has also been reported in some patients, and no studies have investigated apathy. PSP patients may have depression, apathy, disinhibition, and to a lesser extent, anxiety and agitation. In CBD, neuropsychiatric disorders are similar to those present in PSP. Hallucinations and delusions are rarely reported in these disorders. Neuropsychiatric symptoms in MSA, PSP, and CBD do not appear to be related to the severity of motor dysfunction and are one of the main factors that determine a low quality of life. The results suggest that neuropsychiatric disturbances should always be assessed in patients with atypical parkinsonisms.
Molecular phylogeny and taxonomy of the genus Chaetophora (Chlorophyceae, Chlorophyta), including descriptions of Chaetophoropsis aershanensis gen. et sp. nov.

The broadly defined genus Chaetophora consisted of species with minute, uniseriate branching filaments enveloped in soft or firm mucilage forming macroscopic growths that are spherical, hemispherical, and tubercular or arbuscular, growing epiphytically on freshwater aquatic plants and other submerged surfaces in standing or fast‐flowing water. Recent molecular analyses clearly showed that this genus was polyphyletic. In this study, eight strains of Chaetophora and three strains of Stigeoclonium were identified and successfully cultured. In combination with the morphological data, a concatenated data set of four markers (18S + 5.8S + ITS2+ partial 28S rDNA) was also used to determine their taxonomic relationships and phylogenetic positions. The molecular analysis resolved the broadly defined Chaetophora to at least two genera. Species with a globose thallus of genus Chaetophora formed a separate monophyletic clade, which clearly separated from, a type of lobe‐form Chaetophora species. Therefore, we propose to erect a new genus, Chaetophoropsis, which includes all globose species of the Chaetophora. Chaetophoropsis aershanensis was determined to be a new species, based on its special characteristic of profuse long rhizoids. Stigeoclonium polyrhizum, as the closest relative to Chaetophoropsis, revealed its distant relationships to other species of Stigeoclonium. A globose thallus with a thick, soft mucilage matrix, and special rhizoidal branches lent further support to the placement of S. polyrhizum in the genus Chaetophoropsis and had the closest relationship to C. aershanensis. Taxonomic diversity was proven by distinctive morphological differences and by phylogenetic divergence in the broadly defined Chaetophora identified herein.
Toxic communication during streams on Twitch.tv. The case of Dota 2

This paper is devoted to the study of how toxic communication is structured in chats during streams on Twitch.tv and how chat size affects it. The data from Twitch chat logs was used to create a topic model of themes which are discussed by viewers during stream. The result indicate that there are statistically significant differences in the types of communication used in channels of different sizes.
HeterStyle: A Heterogeneous Video Style Transfer Application

Video style transfer aims to synthesize a stylized video that preserves the content of a given video and is rendered in the style of a reference image.A key issue in video style transfer is how to balance video content preservation and reference style rendering, in order to avoid over-stylization with serious video content loss or under-stylization with unrecognized reference style. In this demonstration, we illustrate a novel video style transfer application, named HeterStyle, which can stylize different regions in the video with adaptive intensities.The core algorithm of HeterStyle application is our proposed heterogeneous video style transfer method, which minimizes a heterogeneous style transfer loss function considering content, style and temporal consistency in a Convolutional Neural Networks based optimization framework.With the HeterStyle application, a user can easily generate the stylized videos with good video content preservation and reference style rendering.
Nurses' psychological empowerment: An integrative approach.

AIM To investigate the role of psychological empowerment as a mediator between authentic leadership and organisational citizenship behaviours (OCB), tardiness, absenteeism and intent to leave. BACKGROUND Despite the extensive literature on predictors and outcomes of psychological empowerment, there is a lack of studies on the nursing profession using an integrative model, simultaneously focusing on the effects of authentic leadership and psychological empowerment on OCB, and time-related misbehaviours. METHOD Data were collected from 172 nurses in 28 Israeli public hospitals from questionnaires, and tardiness and absenteeism records. We tested our model using structural equation modelling (SEM). RESULTS Nurses' perceptions of their head nurses as authentic leaders positively predicted psychological empowerment, while psychological empowerment positively predicted their OCB, tardiness and intent to leave the hospital. Psychological empowerment partially mediates the relationship between the nurses' perceptions of their head nurses as authentic leaders and OCB, tardiness and intent to leave the hospital. CONCLUSIONS Nurses' psychological empowerment and their head nurses' authentic leadership may increase the nurses' OCB, while simultaneously holding opposing behaviours. IMPLICATIONS FOR NURSING MANAGEMENT Nursing management should use the study measures to evaluate factors that can affect their nurses' effectiveness, including developing training programs to increase nurses' OCB.
ASYSST: A Framework for Synopsis Synthesis Empowering Visually Impaired

In an indoor scenario, the visually impaired do not have the information about the surroundings and finds it difficult to navigate from room to room. The sensor-based solutions are expensive and may not always be comfortable for the end users. In this paper, we focus on the problem of synthesis of textual description from a given floor plan image to assist the visually impaired. The textual description, in addition to a text reading software, can aid the visually impaired person while moving inside a building. In this work, for the first time, we propose an end to end framework (ASYSST) for textual description synthesis from digitized building floor plans. We have introduced a novel Bag of Decor (BoD) feature to learn $5$ classes of a room from $1355$ samples under a supervised learning paradigm. These learned labels are fed into a description synthesis framework to yield a holistic description of a floor plan image. Experimental analysis of real publicly available floor plan data-set proves the superiority of our framework.
Rapid Multiplexed Detection on Lateral-Flow Devices Using a Laser Direct-Write Technique

Paper-based lateral flow devices (LFDs) are regarded as ideal low-cost diagnostic solutions for point-of-care (POC) scenarios that allow rapid detection of a single analyte within a fluidic sample, and have been in common use for a decade. In recent years, there has been an increasing need for rapid and simultaneous detection of multiple analytes present within a single sample and to facilitate this, we report here a novel solution—detection using a multi-path LFD created via the precise partitioning of the single flow-path of a standard LFD using our previously reported laser direct-write (LDW) technique. The multiple flow-paths allow the simultaneous detection of the different analytes individually within each of the parallel channels without any cross-reactivity. The appearance of coloured test lines in individual channels indicates the presence of the different analytes within a sample. We successfully present the use of a LDW-patterned multi-path LFD for multiplexed detection of a biomarker panel comprising C-reactive protein (CRP) and Serum amyloid A-1 (SAA1), used for the diagnosis of bacterial infections. Overall, we demonstrate the use of our LDW technique in the creation of a novel LFD that enables multiplexed detection of two inflammation markers within a single LFD providing a detection protocol that is comparatively more efficient than the standard sequential multiplexing procedure.
A Perceptron Model for Joint Extraction of Drug Entities and Drug-Drug Interactions

Drugs1 can affect each other's activities such as synerigistic or antagonistic respectively, when they are administered together. It is called drug-drug interaction(DDI). This paper proposes a structured perceptron model for joint extraction of drug entities and DDIs. The experiment result shows that the joint model alleviate the error propagation between the two steps of the extraction of drug entity and DDI. Our experimental results outperform the pipeline approach's.
Magnitude and associated factors of diabetes mellitus and hypertension among adult HIV-positive individuals receiving highly active antiretroviral therapy at Jugal Hospital, Harar, Ethiopia

Background People with HIV infection are at increased risk of noncommunicable diseases (NCDs). Diabetes mellitus (DM) and hypertension are recognized as the major NCDs. Except few findings in general population, there is no well-documented evidence on the magnitude of NCDs and associated factors among HIV-positive patients. Purpose The aim of this study was to determine the magnitude and associated factors of DM and hypertension among adult HIV-positive subjects receiving highly active antiretroviral therapy (HAART) Methods A hospital-based cross-sectional study was conducted from February to April at Jugal Hospital, Harar, Eastern Ethiopia. Sociodemographic and anthropometric data and blood pressure (BP) were collected by senior clinical nurses. A total of 5 mL of venous blood was collected. Serum glucose and lipid profile were measured using the Autolab 18 clinical chemistry analyzer. Data were analyzed using STATA version 13. Results A total of 425 HIV-infected individuals taking HAART of age ranging from 18 to 68 years were included. The prevalence of DM and hypertension were 7.1% (95% CI: 4.9–9.9) and 12.7% (95% CI: 9.8–16.2), respectively. Increased blood triglyceride (adjusted odds ratio [AOR] =4.7, 95% CI: 1.7–13.1), high BP (AOR =3.3, 95% CI: 1.1–9.5), and high baseline body mass index (BMI) (AOR =8.7, 95% CI: 2.4–31.8) were significantly associated with DM. In contrast, raised waist–hip ratio (AOR =4.6, 95% CI: 1.6–13.3), raised blood glucose (AOR =3.5, 95% CI: 1.1–11.4), increased total cholesterol (AOR =3.9, 95% CI: 1.3–11.9), high current BMI (AOR =3.8, 95% CI: 1.5–9.6), drinking alcohol (AOR =3.4, 95% CI: 1.5–8.1), CD4 count <500 cell/mL (AOR =2.7, 95% CI: 1.3–5.6), and longer duration of HAART (AOR =2.3, 95% CI: 1.1–5.1) were significantly associated with hypertension. Conclusion DM and hypertension were frequent among HIV patients on HAART, and they were linked to the well-known risk factors. Therefore, regular screening and monitoring of DM and hypertension before and after the initiation of HAART is of paramount importance.
Normative Values for Heart Rate Variability Parameters in School-Aged Children: Simple Approach Considering Differences in Average Heart Rate

Background: Heart rate variability (HRV) analysis is a clinical tool frequently used to characterize cardiac autonomic status. The aim of this study was to establish normative values for short-term HRV parameters by considering their main determinants in school-aged children. Methods: Five-minute electrocardiograms were taken from 312 non-athlete children (153 boys) at age of 6 to 13 years for computation of conventional time- and frequency-domain HRV parameters. Heart rate (HR), respiratory rate, age, body mass index, and sex were considered as their potential determinants. Multiple regression analysis revealed that HR was the principal predictor of all standard HRV indices. To develop their universal normative limits, standard HRV parameters were corrected for prevailing HR. Results: The HRV correction for HR yielded the parameters which became independent on both sex and HR, and only poorly dependent on age (with small effect size). Normal ranges were calculated for both time- and frequency-domain indices (the latter computed with either fast Fourier transform and autoregressive method). To facilitate recalculation of standard HRV parameters into corrected ones, a calculator was created and attached as a Supplementary Material that can be downloaded and used for both research and clinical purposes. Conclusion: This study provides HRV normative values for school-aged children which have been developed independently of their major determinants. The calculator accessible in the Supplementary Material can considerably simplify determination if HRV parameters accommodate within normal limits.
Selection of Market Window Size in Portfolio Strategies

We propose a feasible selection method of market window size for four state-of-the-art portfolio strategies. Market window size is a common parameter in the machine learning strategy for portfolio selection. However, in previous researches, the selection of market window size often lacks the guidance of scientific theories. In this paper, we analyze the sensitivity of market window size for four strategies on six benchmark data sets respectively. We study the distribution rule of the best market window sizes, which bring the peak total wealth, and then present the market window size selection method that is effective whether there is ample history data or not. What's more, to appraise the result of our method, we divide the benchmark data sets into two parts. We select the appropriate window size in the first part by our method, while the second part is used to test. By comparing with the wealth achieved in the second part using original method, we find that our selection method can effectively optimize the final results.