Miracle-dz/UniFAR-FTUs huggingface dataset:
Top-down sampling convolution network for face segmentation

The paper adopts two different convolution sampling paths: from large scale to small scale sampling (top-down) and small scale to large scale sampling (bottom-up), and propose the top-down sampling convolution neural network for face segmentation (TDNN). On the LFW and the Helen dataset, it is demonstrated about the advantage of face segmentation by TDNN. In addition, the shared weight is added to each convolution integral, we propose TDNN with shared weight (TDNNSW). On the Helen dataset, TDNNSW with shared weight further improves the accuracy of face segmentation. Since TDNN is trained end-to-end, our model has advantageous properties such as less parameters and more rapid calculation for face segmentation.
Energy-based control applied to humanoid robots

In this paper, an energy-based controller is proposed in the context of humanoid gait design and humanoid fall avoidance applications. The proposed energy-based controller aims at not only reaching the desired final state but also at tracking a desired reference trajectory with minimal energy expenditure. The controller is validated on two nonlinear systems, an inverted pendulum with a fixed pivot and an inverted pendulum with a moving pivot. The results are benchmarked against a tuned traditional PID controller as well as the controlled Lagrangian approach. The performance improvements in terms of energy efficiency and work expenditure are validated through both simulations and experiments on an actual system. Finally, the novel energy-based control strategy is applied to the fall avoidance problem on a NAO humanoid robot where it was simulated in Webots.
Interplay Between Antibiotic Resistance and Virulence During Disease Promoted by Multidrug-Resistant Bacteria

Diseases caused by antibiotic-resistant bacteria in hospitals are the outcome of complex relationships between several dynamic factors, including bacterial pathogenicity, the fitness costs of resistance in the human host, and selective forces resulting from interventions such as antibiotic therapy. The emergence and fate of mutations that drive antibiotic resistance are governed by these interactions. In this review, we will examine how different forms of antibiotic resistance modulate bacterial fitness and virulence potential, thus influencing the ability of pathogens to evolve in the context of nosocomial infections. We will focus on 3 important multidrug-resistant pathogens that are notoriously problematic in hospitals: Pseudomonas aeruginosa, Acinetobacter baumannii, and Staphylococcus aureus. An understanding of how antibiotic resistance mutations shape the pathobiology of multidrug-resistant infections has the potential to drive novel strategies that can control the development and spread of drug resistance.
Dietary guidelines and patterns of intake in Denmark

Food-based dietary guidelines in Denmark have usually been expressed in simple terms only and need to be elaborated. Quantitative recommendations on fruit and vegetable intake were issued in 1998, recommending 600 g/d (potatoes not included). This paper is based on a national dietary survey in 1995 (n = 3098, age range 1–80 years) supplemented with data from a simple frequency survey in 1995 (n = 1007, age range 15–80 years) and from the first national survey in 1985 (n = 2242, age range 15–80 years). Only data on adults are included in this paper. Fat intake, saturated fat in particular, is too high (median intake 37 %energy and 16 %energy, respectively). Main fat sources are separated fats (butter, margarine, oil, etc.: 40 %), meat (18 %), and dairy products (21 %). Total fat intake decreased from 1985 to 1995 but fatty acid composition did not improve. Dietary fibre intake is from 18 to 22 g/d (women and men, respectively) with 62 % from cereals, 24 % from vegetables and 12 % from fruit. Mean intake of vegetables and potatoes was from 200 to 250 g/d (women and men, respectively). Mean intake of fruit and vegetables (potatoes not included) was 277 g/d, or less than half of the new recommendation (600 g/d). Only 15 % of participants in the frequency survey reported consuming both fruit and vegetables every day, and only 28 % reported to do so almost every day. In conclusion, dietary intake in Denmark is characterized by a high intake of saturated fat and total fat, and by a relatively low intake of fruit and vegetables.
MicroRNA-34a regulates proliferation and apoptosis of gastric cancer cells by targeting silent information regulator 1

The present study aimed to identify whether microRNA (miRNA/miR)-34a regulates the proliferation and apoptosis of gastric cancer cells by targeting silent information regulator 1 (SIRT1). The expression of miR-34a and SIRT1 and cell viability was investigated in gastric cancer cells. Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was applied to determine miR-34a expression in gastric adenocarcinoma, normal pericarcinomatous tissues, human normal gastric mucosa epithelial cell line GES and various gastric cancer cell strains. A bioinformatics method was then used to predict the target gene of miR-34a. A human miR-34a over expression lentiviral vector system was constructed and then used for transfection of the gastric cancer cell line SCG-7901 to determine the expression of SIRT1 mRNA and SIRT1 protein using RT-qPCR and western blot analysis. The MTT method and flow cytometry was used to measure cell proliferation and apoptosis. The relative expression of miR-34a in gastric cancer tissues was significantly decreased compared with that in normal tissues (P<0.01). miR-34a expression was also significantly decreased in low differentiated N2, N3 gastric cancer tissues (P<0.01). However, tumor size and filtration degree were not significantly associated with miR-34a expression. The relative expression of miR-34a was decreased in gastric cancer cells, especially in the SGC-7901 cell line (P<0.01) compared with the GES group. The relative expression of SIRT1 protein was decreased in the miR-34a group compared with the negative control (P<0.01). The rate of proliferation was significantly decreased, whereas the rate of apoptosis was significantly increased in the miR-34a group compared with the NC group (P<0.01). Therefore, the present results suggested that miRNA-34a serves a pivotal role in gastric cancer as a cancer suppressor gene by targeting SIRT1 to regulate the proliferation and apoptosis of gastric cancer cells.
An Improvement on Remote User Authentication Schemes Using Smart Cards

In 2010, Yeh et al. proposed two robust remote user authentication schemes using smart cards; their claims were such that their schemes defended against ID-theft attacks, reply attacks, undetectable on-line password guessing attacks, off-line password guessing attacks, user impersonation attack, server counterfeit attack and man-in-the-middle attack. In this paper, we show that Yeh et al.’s schemes are still vulnerable to ID-theft attack, off-line password guessing attacks, undetectable on-line password guessing attacks and user impersonation attack. Notably, problems remain in situations where the user lost a smart card or the malicious legal user. To remedy these flaws, this paper proposes an improvement on Yeh et al.’s remote user authentication schemes using smart cards.
Hemodynamic effects of HPMA copolymer based doxorubicin conjugate: A randomized controlled and comparative spectral study in conscious rats

Abstract Conjugation of Doxorubicin (DOX) to N-(2-hydroxypropyl) methylacrylamide copolymer (HPMA) has significantly reduced the DOX-associated cardiotoxicity. However, the reports on the impact of HPMA–DOX conjugates on the cardiovascular system such as blood pressure (BP) and heart rate (HR) were in restrained animals using tail cuff and/or other methods that lacked the resolution and sensitivity. Herein, we employed radiotelemetric-spectral-echocardiography approach to further understand the in vivo cardiovascular hemodynamics and variability post administration of free DOX and HPMA–DOX. Rats implanted with radio-telemetry device were administered intravenously with DOX (5 mg/kg), HPMA–DOX (5 mg DOX equivalent/kg) and HPMA copolymer and subjected to continuous cardiovascular monitoring and echocardiography for 140 days. We found that DOX-treated rats had ruffled fur, reduced body weight (BW) and a low survival rate. Although BP and HR were normal, spectral analysis indicated that their BP and HR variabilities were reduced. All rats exhibited typical signs of cardiotoxicity at histopathology. In contrast, HPMA–DOX rats gained weight over time and survived. Although BP, HR and related variabilities were unaffected, the left ventricular end diastolic volume (EDV) of these rats, as well as of the HPMA copolymer-treated rats, was found increased at the end of observation period. Additionally, HPMA copolymer caused microscopic injury of the heart tissue. All of these suggest the necessity of caution when employing HPMA as carrier for prolonged drug delivery. The current study also indicates the potential of radiotelemetric-spectral-echocardiography approach for improved preclinical cardiovascular risk assessment of polymer–drug conjugate and other nano-sized-drug constructs.
High titer oncolytic measles virus production process by integration of dielectric spectroscopy as online monitoring system

Oncolytic viruses offer new hope to millions of patients with incurable cancer. One promising class of oncolytic viruses is Measles virus, but its broad administration to cancer patients is currently hampered by the inability to produce the large amounts of virus needed for treatment (1010–1012 virus particles per dose). Measles virus is unstable, leading to very low virus titers during production. The time of infection and time of harvest are therefore critical parameters in a Measles virus production process, and their optimization requires an accurate online monitoring system. We integrated a probe based on dielectric spectroscopy (DS) into a stirred tank reactor to characterize the Measles virus production process in adherent growing Vero cells. We found that DS could be used to monitor cell adhesion on the microcarrier and that the optimal virus harvest time correlated with the global maximum permittivity signal. In 16 independent bioreactor runs, the maximum Measles virus titer was achieved approximately 40 hr after the permittivity maximum. Compared to an uncontrolled Measles virus production process, the integration of DS increased the maximum virus concentration by more than three orders of magnitude. This was sufficient to achieve an active Measles virus concentration of > 1010 TCID50 ml−1.
The genetic heterogeneity of Arab populations as inferred from HLA genes

This is the first genetic anthropology study on Arabs in MENA (Middle East and North Africa) region. The present meta-analysis included 100 populations from 36 Arab and non-Arab communities, comprising 16,006 individuals, and evaluates the genetic profile of Arabs using HLA class I (A, B) and class II (DRB1, DQB1) genes. A total of 56 Arab populations comprising 10,283 individuals were selected from several databases, and were compared with 44 Mediterranean, Asian, and sub-Saharan populations. The most frequent alleles in Arabs are A*01, A*02, B*35, B*51, DRB1*03:01, DRB1*07:01, DQB1*02:01, and DQB1*03:01, while DRB1*03:01-DQB1*02:01 and DRB1*07:01-DQB1*02:02 are the most frequent class II haplotypes. Dendrograms, correspondence analyses, genetic distances, and haplotype analysis indicate that Arabs could be stratified into four groups. The first consists of North Africans (Algerians, Tunisians, Moroccans, and Libyans), and the first Arabian Peninsula cluster (Saudis, Kuwaitis, and Yemenis), who appear to be related to Western Mediterraneans, including Iberians; this might be explained for a massive migration into these areas when Sahara underwent a relatively rapid desiccation, starting about 10,000 years BC. The second includes Levantine Arabs (Palestinians, Jordanians, Lebanese, and Syrians), along with Iraqi and Egyptians, who are related to Eastern Mediterraneans. The third comprises Sudanese and Comorians, who tend to cluster with Sub-Saharans. The fourth comprises the second Arabian Peninsula cluster, made up of Omanis, Emiratis, and Bahrainis. It is noteworthy that the two large minorities (Berbers and Kurds) are indigenous (autochthonous), and are not genetically different from “host” and neighboring populations. In conclusion, this study confirmed high genetic heterogeneity among present-day Arabs, and especially those of the Arabian Peninsula.
Free Vibration and Bending Analysis of Uniformly Distributed Carbon Nanotube Composite Plate Using Finite Element Method

In this work, free vibration and bending behaviour of uniformly distributed carbon nanotube composite plate are analysed. The material properties of single-walled carbon nanotube evaluated through molecular dynamics simulation using LAMMPS software. The effective material properties of the composite plates are obtained using an extended rule of mixture. A finite element model is developed for the single-walled carbon nanotube composite plate using ANSYS Parametric Design Language (APDL) code in ANSYS environment. For the discretization purpose, an eight-noded serendipity shell element is used from the ANSYS library. Subsequently, the validation study is performed through the available published literature. Finally, the parametric study is demonstrated by varying different material and geometrical parameters for free vibration and bending responses of composite plate.
Visualising mental representations: A primer on noise-based reverse correlation in social psychology

ABSTRACT With the introduction of the psychophysical method of reverse correlation, a holy grail of social psychology appears to be within reach – visualising mental representations. Reverse correlation is a data-driven method that yields visual proxies of mental representations, based on judgements of randomly varying stimuli. This review is a primer to an influential reverse correlation approach in which stimuli vary by applying random noise to the pixels of images. Our review suggests that the technique is an invaluable tool in the investigation of social perception (e.g., in the perception of race, gender and personality traits), with ample potential applications. However, it is unclear how these visual proxies are best interpreted. Building on advances in cognitive neuroscience, we suggest that these proxies are visual reflections of the internal representations that determine how social stimuli are perceived. In addition, we provide a tutorial on how to perform reverse correlation experiments using R.
Association of vasomotor symptoms and sleep apnea risk in midlife women

Objective: The aim of the study was to determine the association between self-reported vasomotor symptoms (VMS) and obstructive sleep apnea (OSA) risk. Methods: The STOP-BANG to evaluate OSA and Menopause Rating Scale (MRS) were administered to 2,935 women seen in the Women's Health Clinic at Mayo Clinic in Rochester, MN, between May 2015 and December 2016. Of these, 1,691 women were included in the analysis. Total MRS and VMS ratings were compared using logistic regression, with age, smoking, and body mass index (BMI) included as covariates between women at intermediate/high risk versus low risk for OSA. Results: Total MRS scores were significantly higher in women with intermediate/high-risk OSA scores versus those with low-risk scores [mean (SD): 16.8 (8.0) vs 12.9 (7.0), P < 0.001]. Women at intermediate/high OSA risk were older, had more education, self-reported hypertension, BMI >35 kg/m2, and were less likely to be married or employed. Self-reported severe/very severe VMS were significantly associated with intermediate/high risk versus low risk for OSA (26.6% vs 15.0%; P < 0.001). After adjusting for age, BMI, smoking status, and self-reported hypertension, the odds of having intermediate/high risk for OSA were 1.87 times higher for those with severe/very severe VMS compared with those with none/mild/moderate VMS (95% CI, 1.29-2.71, P < 0.001). This association persisted upon subgroup analysis based on BMI <25 kg/m2 (odds ratio 2.15; 95% CI, 1.12-4.16, P = 0.022). Conclusions: Self-reported severe/very severe VMS were associated with intermediate/high risk for OSA in midlife women, even in women with BMI <25 kg/m2. Given the limitations of the STOP-BANG tool, OSA risk may, however, have been overestimated.
Deep Binaries: Encoding Semantic-Rich Cues for Efficient Textual-Visual Cross Retrieval

Cross-modal hashing is usually regarded as an effective technique for large-scale textual-visual cross retrieval, where data from different modalities are mapped into a shared Hamming space for matching. Most of the traditional textual-visual binary encoding methods only consider holistic image representations and fail to model descriptive sentences. This renders existing methods inappropriate to handle the rich semantics of informative cross-modal data for quality textual-visual search tasks. To address the problem of hashing cross-modal data with semantic-rich cues, in this paper, a novel integrated deep architecture is developed to effectively encode the detailed semantics of informative images and long descriptive sentences, named as Textual-Visual Deep Binaries (TVDB). In particular, region-based convolutional networks with long short-term memory units are introduced to fully explore image regional details while semantic cues of sentences are modeled by a text convolutional network. Additionally, we propose a stochastic batch-wise training routine, where high-quality binary codes and deep encoding functions are efficiently optimized in an alternating manner. Experiments are conducted on three multimedia datasets, i.e. Microsoft COCO, IAPR TC-12, and INRIA Web Queries, where the proposed TVDB model significantly outperforms state-of-the-art binary coding methods in the task of cross-modal retrieval.
Reliability of a Scoring System for Qualitative Evaluation of Lymphoscintigraphy of the Lower Extremities

Lymphoscintigraphy is an imaging technique to diagnose and characterize the severity of edema in the upper and lower extremities. In lymphoscintigraphy, a scoring system can increase the ability to differentiate between diagnoses, but the use of any scoring system requires sufficient reliability. Our aim was to determine the inter- and intraobserver reliability of a proposed scoring system for visual interpretation of lymphoscintigrams of the lower extremities. Methods: The lymphoscintigrams of 81 persons were randomly selected from our database for retrospective evaluation. Two nuclear medicine physicians scored these scans according to the 8 criteria of a proposed scoring system for visual interpretation of lymphoscintigrams of the lower extremities. Each scan was scored twice 3 mo apart. The total score was the sum of the scores for all criteria, with a potential range of 0 (normal lymphatic drainage) to 58 (severe lymphatic impairment). The intra- and interobserver reliability of the scoring system was determined using the Wilcoxon signed-rank test, percentage of agreement, weighted κ, and intraclass correlation coefficient with 95% confidence interval. In addition, for 7 categories, differences in total scores between and within observers were determined. Results: We found some insignificant differences between observers. Percentage agreement was high or very high, at 82.7%–99.4% between observers and 84.6%–99.4% within observers. For each criterion of the scoring system, the κ-correlations showed moderate to very good inter- or intraobserver reliability. The total scores for all criteria had good inter- and intraobserver reliability. Regarding the interobserver comparison, 66% and 64% of the difference in total scores were within ±1 scale point (−1, +1), and regarding the intraobserver comparison, 68% and 72% of the difference in total scores were within ±1 scale point. Conclusion: The proposed scoring system is a reliable tool for visual qualitative evaluation of lymph transport problems in patients with lymphedema of the lower extremities.
An hybrid front-end for robust speaker identification under noisy conditions

The automatic speaker identification systems provide acceptable performances when they are used with clean speech. However they become practically unstable when they operate in noisy environments. So the robustness of these systems remains a delicate research problem. We study a novel hybrid features extractor based on a combination of robust Relative Spectral Transform Perceptual Linear Prediction (RASTA-PLP) method and the conventional Mel Frequency Cepstral Coefficients (MFCC). We show the experiments carried out on a database corresponding to a population of 51 speakers, with a system entrained on clean speech and the test data degraded by an additive white Gaussian noise of SNR level variable from 40 db to 0 db that the proposed hybrid front-end using MFCC parameters combined with those of RASTA-PLP in the same feature vector gives better results compared to those obtained using separating these previous methods. An improvement accuracy of about 3.38% was observed by comparison to the base line method MFCC.
Multislice CEST MRI improves the spatial assessment of tumor pH

Multislice maps of extracellular pH (pHe) are needed to interrogate the heterogeneities of tumors and normal organs. To address this need, we have developed a multislice chemical exchange saturation transfer (CEST) MRI acquisition method with a CEST spectrum‐fitting method that measures in vivo pHe over a range of 6.3 to 7.4.
Deep Learning Policy Quantization

We introduce a novel type of actor-critic approach for deep reinforcement learning which is based on learning vector quantization. We replace the softmax operator of the policy with a more general and more flexible operator that is similar to the robust soft learning vector quantization algorithm. We compare our approach to the default A3C architecture on three Atari 2600 games and a simplistic game called Catch. We show that the proposed algorithm outperforms the softmax architecture on Catch. On the Atari games, we observe a nonunanimous pattern in terms of the best performing model.
Automated representation of non-emotional expressivity to facilitate understanding of facial mobility: Preliminary findings

We present an automated method of identifying and representing non-emotional facial expressivity in video data. A benchmark dataset is created using the framework of an existing clinical test of upper and lower face movement, and initial findings regarding automated quantification of facial motion intensity are discussed. We describe a new set of features which combine tracked interest point statistics within a temporal window, and explore the effectiveness of those features as methods of quantifying changes in non-emotional facial expressivity of movement in the upper part of the face. We aim to develop this approach as a protocol which could inform clinical diagnosis and evaluation of treatment efficacy of a number of neurological conditions including Parkinson's disease.
Simple, Robust and (almost) Unsupervised Generation of Polarity Lexicons for Multiple Languages

This paper presents a simple, robust and (almost) unsupervised dictionary-based method, qwn-ppv (Q-WordNet as Personalized PageRanking Vector) to automatically generate polarity lexicons. We show that qwn-ppv outperforms other automatically generated lexicons for the four extrinsic evaluations presented here. It also shows very competitive and robust results with respect to manually annotated ones. Results suggest that no single lexicon is best for every task and dataset and that the intrinsic evaluation of polarity lexicons is not a good performance indicator on a Sentiment Analysis task. The qwn-ppv method allows to easily create quality polarity lexicons whenever no domain-based annotated corpora are available for a given language.