Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Monte Carlo dropout for non-stationary noise reduction from speech

In this work, we propose the use of dropout as a Bayesian estimator for increasing the generalizability of a deep neural network (DNN) for speech enhancement. By using Monte Carlo (MC) dropout, we show that the DNN performs better enhancement in unseen noise and SNR conditions. The DNN is trained on speech corrupted with Factory2, M109, Babble, Leopard and Volvo noises at SNRs of 0, 5 and 10 dB. Speech samples are obtained from the TIMIT database and noises from NOISEX-92. In another experiment, we train five DNN models separately on speech corrupted with Factory2, M109, Babble, Leopard and Volvo noises, at 0, 5 and 10 dB SNRs. The model precision (estimated using MC dropout) is used as a proxy for squared error to dynamically select the best of the DNN models based on their performance on each frame of test data. We propose an algorithm with a threshold on the model precision to switch between classifier based model selection scheme and model precision based selection scheme. Testing is done on speech corrupted with unseen noises White, Pink and Factory1 and all five seen noises.
Cultural Factors Influencing Functional Gastrointestinal Disorders in the East

Culture forms an integral aspect of environmental factors which influences disease presentation and clinical outcomes in functional gastrointestinal disorders (FGIDs). In this review, the role of culture in FGIDs in the East is briefly explored with regards to symptom presentation and diagnostic issues, lifestyle and cultural habits, epidemiology, and healthcare seeking behavior. In both functional dyspepsia and irritable bowel syndrome, symptom presentation and disease sub-typing in Asians are known to differ from their Western counterparts, possibly relating to cultural dietary practices and from cultural perception of symptoms. Dietary patterns, together with defecating practices are explored as factors contributing to a lower prevalence of constipation in the East. An urban-rural difference in the prevalence of FGIDs in Asia is attributed to a change in dietary patterns in rapidly developing urban communities, together with an increased level of psychological morbidity. Lastly, cultural attitudes towards traditional/local remedies, variation in healthcare systems, anxiety regarding organic disease, and religious practices have been shown to influence healthcare seeking behavior among FGID patients in the East.
Nonproliferative and Proliferative Lesions of the Ratand Mouse Special Sense Organs(Ocular [eye and glands], Olfactory and Otic)

Meg Ferrell Ramos1, a* (Co-Chair), Julia Baker (Co-Chair)2, a, Elke-Astrid Atzpodien3, a, Ute Bach4, a, Jacqueline Brassard5, a, James Cartwright6, a, Cynthia Farman7, a, Cindy Fishman8, a, b, Matt Jacobsen6, a, Ursula Junker-Walker9, d, Frieke Kuper10, c, Maria Cecilia Rey Moreno11, b, Susanne Rittinghausen12, c, Ken Schafer13, a, d, Kohji Tanaka14, a, Leandro Teixeira15, a, Katsuhiko Yoshizawa16, a, Hui Zhang17, a
Effectiveness and safety of polymyxin B for the treatment of infections caused by extensively drug-resistant Gram-negative bacteria in Thailand

Background Colistimethate sodium (colistin) has been used in the treatment of infections caused by extensively drug-resistant (XDR) Gram-negative bacteria in Thailand over the past decade, with a mortality rate of 50% and a nephrotoxicity rate of 40%. Polymyxin B has not been available in Thailand. We conducted a Phase II clinical study to determine the effectiveness and safety of polymyxin B, compared with colistin, for the treatment of XDR Gram-negative bacterial infections in Thai patients. Methods A total of 73 adult patients hospitalized at four participating tertiary care hospitals from January 2015 to December 2015 who had infections caused by XDR Gram-negative bacteria and had to receive colistin were enrolled in the study. Polymyxin B (100 mg/day) was administered intravenously every 12 hours for 7–14 days. Results Most of the patients were older males with comorbidities who had received antibiotics, particularly carbapenems, prior to receiving polymyxin B. More than half of the patients had pneumonia, and 51.5% of the infections were caused by XDR Acinetobacter baumannii, which was susceptible to colistin. Good clinical responses at the end of treatment were observed in 78.1% of cases, the overall 28-day mortality rate from all causes was 28.7%, the microbiological clearance of the targeted bacteria after therapy was 56.2% and nephrotoxicity occurred in 24.7% of cases. Neurotoxicity relating to reversible numbness was observed in two cases. Conclusion Polymyxin B seems to be effective and safe for the treatment of XDR Gram-negative bacterial infections. Polymyxin B should be considered as an alternative to colistin for treatment of infections caused by XDR Gram-negative bacteria in Thai adult patients, especially those at risk of nephrotoxicity.
Review Helpfulness Assessment based on Convolutional Neural Network

In this paper we describe the implementation of a convolutional neural network (CNN) used to assess online review helpfulness. To our knowledge, this is the first use of this architecture to address this problem. We explore the impact of two related factors impacting CNN performance: different word embedding initializations and different input review lengths. We also propose an approach to combining rating star information with review text to further improve prediction accuracy. We demonstrate that this can improve the overall accuracy by 2%. Finally, we evaluate the method on a benchmark dataset and show an improvement in accuracy relative to published results for traditional methods of 2.5% for a model trained using only review text and 4.24% for a model trained on a combination of rating star information and review text.
3-D LiDAR + Monocular Camera: An Inverse-Depth-Induced Fusion Framework for Urban Road Detection

Road detection is an important task in autonomous navigation systems. In this paper, we propose a road detection framework induced by the inverse depth of LiDAR's point cloud. This framework is a fusion of a 3-D LiDAR and a monocular camera, where the 3-D point cloud of LiDAR is projected onto the camera's image frame, to exploit both range and color information. For the same road detection task, we propose an inverse-depth aware fully convolutional neural network based on image information and a line scanning strategy based on an inverse-depth histogram of LiDAR's point cloud. Finally, a conditional random field fusion method integrates the two road detection results. Our method is evaluated on KITTI-Road benchmark. Experiments demonstrate that our method achieves the state-of-the-art performance in road detection among all the referable methods that have ever reported their results on the KITTI-Road benchmark.
Novel Real-time Face Recognition from Video Streams

Real-time recognition from video streams is a very challenging task due to background, facial expressions, and lighting differences. Recent studies show that deep learning approaches can achieve impressive performance on this task. Our system solves these problems well using deep learning method. It contains face detection module and face recognition module. Our face detection module is based on MTCNN, which is very fast and accurate, and is robust enough for changes in lighting differences and background. Our face recognition module is based on FaceNet, which directly learns mapping the face images to the points in Euclidean space, where the distance of two points in Euclidean space directly corresponds to how similar two face images are. Once such Euclidean space is created, we transform the face images into the FaceNet embedding, as the feature vectors for face images. Next, we put the feature vectors into an SVM classifier to help us quickly identify the face images. The experimental results show that the system has very high accuracy and low computational complexity, which is the key to real-time face recognition, and has significant value in application.
Type 1 diabetes mellitus: Complex interplay of oxidative stress, cytokines, gastrointestinal motility and small intestinal bacterial overgrowth

Oxidative stress is risk factor in progression of diabetes. It can increase cytokine production via several different mechanisms. Inflammation can affect gut neural apparatus that may lead to dysmotility which may exaggerate occurrence of bacterial overgrowth in intestine. Thus, a study was planned to understand the complex interplay of oxidative stress, inflammatory cytokines, gut motility and small intestinal bacterial overgrowth in type 1 diabetes mellitus (T1DM) patients.
Neurophysiological Measures of the Perception of Antismoking Public Service Announcements Among Young Population

Tobacco constitutes a global emergency with totally preventable millions of deaths per year and smoking-related illnesses. Public service announcements (PSAs) are the main tool against smoking and by now their efficacy is still assessed through questionnaires and metrics, only months after their circulation. The present study focused on the young population, because at higher risk of developing tobacco addiction, investigating the reaction to the vision of Effective, Ineffective and Awarded antismoking PSAs through: electroencephalography (EEG), autonomic activity variation (Galvanic skin response—GSR- and Heart Rate—HR-) and Eye-Tracking (ET). The employed indices were: the EEG frontal alpha band asymmetry and the frontal theta; the Emotional Index (EI), deriving from the GSR and HR signals matching; the ET Visual Attention (VA) index, based on the ratio between the total time spent fixating an area of interest (AOI) and its area. Smokers expressed higher frontal alpha asymmetry values in comparison to non-smokers. Concerning frontal theta, Awarded PSAs reported the highest values in comparison to both Effective and Ineffective PSAs. EI results highlighted that lowest values were expressed by Heavy Smokers (HS), and Effective PSAs obtained the highest EI values. Finally, concerning the Effective PSAs, regression analysis highlighted a correlation between the number of cigarettes smoked by participants (independent variable) and frontal alpha asymmetry, frontal theta and EI values. ET results suggested that for the Ineffective PSAs the main focus were texts, while for the Effective and Awarded PSAs were the visual elements. Results support the use of methods aimed at assessing the physiological reaction for the evaluation of PSAs images, in particular when considering the smoking habits of target populations.
A Pilot Study of Short-Duration Hyperbaric Oxygen Therapy to Improve HbA1c, Leukocyte, and Serum Creatinine in Patients with Diabetic Foot Ulcer Wagner 3-4

Objective To evaluate the short-duration hyperbaric oxygen therapy (HBOT) can improve HbA1c levels, leukocyte count, and serum creatinine levels in patients with diabetic foot ulcer (DFU) Wagner 3-4. Methods Blood samples from all DFU patients at Sanglah General Hospital, Denpasar, were taken for HbA1c, leukocyte, and serum creatinine test before debridement procedure, and the patients were then grouped into either standard therapy or standard therapy with HBOT for 10 sessions (combination therapy). At the end of therapy, all blood tests were resumed. Results Each group consisted of 15 patients. Results of laboratory analysis before and after treatment were significant regarding decrease of HbA1c levels in standard therapy (10.98 ± 2.37 % to 9.70 ± 2.46 %; p = 0.006), HbA1c levels in combination therapy (9.42 ± 1.96 % to 7.07 ± 1.16 %; p < 0.001), and leukocyte count in combination therapy (13.97 ± 6.24 x 103 cells/μL to 8.84 ± 2.88 x 103 cells/μL; p = 0.009). The HbA1c levels at the end of therapy were significantly different between groups (p = 0.001). Serum creatinine level was decreased only in combination therapy but it was not significant. The effect size of all variables was larger in the combination therapy, but it was not significant (p > 0.05). Conclusion The use of short-duration HBOT on DFU reduces HbA1c levels, leukocyte count, and serum creatinine levels better than standard therapy alone. This protocol would save time and effort in future HBOT implementation. This trial is registered with ClinicalTrials.gov Identifier: NCT03615755.
Differential Proteomic Analysis Predicts Appropriate Applications for the Secretome of Adipose-Derived Mesenchymal Stem/Stromal Cells and Dermal Fibroblasts

The adult stem cell secretome is currently under investigation as an alternative to cell-based therapy in regenerative medicine, thanks to the remarkable translational opportunity and the advantages in terms of handling and safety. In this perspective, we recently demonstrated the efficient performance of the adipose-derived mesenchymal stem/stromal cell (ASC) secretome in contrasting neuroinflammation in a murine model of diabetic neuropathy, where the administration of factors released by dermal fibroblasts (DFs) did not exert any effect. Up to now, the complex mixture of the constituents of the conditioned medium from ASCs has not been fully deepened, although its appropriate characterization is required in the perspective of a clinical use. Herein, we propose the differential proteomic approach for the identification of the players accounting for the functional effects of the cell secretome with the aim to unravel its appropriate applications. Out of 967 quantified proteins, 34 and 62 factors were found preponderantly or exclusively secreted by ASCs and DFs, respectively. This approach led to the recognition of distinct functions related to the conditioned medium of ASCs and DFs, with the former being involved in the regulation of neuronal death and apoptosis and the latter in bone metabolism and ossification. The proosteogenic effect of DF secretome was validated in vitro on human primary osteoblasts, providing a proof of concept of its osteoinductive potential. Besides discovering new applications of the cell type-specific secretome, the proposed strategy could allow the recognition of the cocktail of bioactive factors which might be responsible for the effects of conditioned media, thus providing a solid rationale to the implementation of a cell-free approach in several clinical scenarios involving tissue regeneration.
Full-Duplex Amplify-and-Forward Transmitter Cooperations for Compound Multiple Access Channels

This paper considers a compound multiple access channel (MAC), where two transmitters send two messages to two receivers respectively and each receiver decodes both the source messages. In particular, transmitter cooperations by utilizing in-band full-duplex (FD) amplify-and-forward (AF) scheme are deployed to enhance the system performance. Based on the proposed scheme, the equivalent channel model is analyzed, as well as the statistics of the accumulated residual self-interference and noise (ARIN). With the joint decoding scheme, the corresponding achievable rate region is derived by a two-step iterative algorithm. Simulation results reveal that the proposed scheme can significantly improve the achievable rate under several typical scenarios.
Serological and Molecular Surveillance of Infectious Bronchitis Virus Infection in Free-Range Chickens and Guinea Fowls in the Ga-East District of Ghana

Infectious bronchitis is an economically important disease with worldwide distribution. Information is available on the presence of infectious bronchitis virus in commercial chicken in parts of Ghana but there is no information on free-range poultry and guinea fowls in the country. Possible IBV infections among free-range chickens and guinea fowls in Abokobi and Frafraha communities in the Ga-East district of the Greater Accra Region of Ghana were investigated using serology and PCR. Blood, tracheal, and cloacal swabs were obtained from 219 free-range chickens and guinea fowls with no respiratory symptoms and no history of IBV vaccination. Sera were evaluated for IBV antibodies by ELISA using commercial IBV test kit from IDEXX, Inc., USA. Swab samples were evaluated for S1 glycoprotein gene by one-step RT PCR. All the swab samples tested negative for IBV. 16% of all tested sera were positive for IBV. IBV seroprevalence in guinea fowls was 0%. 21.2% of sera from local chickens were positive for IBV. The seroprevalence of IBV among local chickens from Frafraha was 30% and that of Abokobi was 7.7%. This study shows exposure of local chickens in the study communities to IBV.
Effect of Ceftriaxone versus Amoxicillin + Clavulanic Acid for Treatment of Acute Bacterial Rhino Sinusitis: Short Course Therapy

BACKGROUND: Acute bacterial rhinosinusitis is one of upper respiratory tract infection that disturbs patient life and requires special consideration. AIM: To evaluate the efficiency of Ceftriaxone versus a high dose of Amoxicillin-clavulanic acid for the treatment of acute bacterial rhinosinusitis. PATIENTS AND METHOD: Observational retrospective study include120 patients of both sex classified into two groups equally conducted. G1 treated with Ceftriaxone 1 g intramuscular injection once daily while, G2 treated with oral Amoxicillin-clavulanic acid (875 mg/125 mg) twice daily for 3-4 days then, the outcome of treatment evaluated as a cure or failed at the fifth or fourth day of treatment. RESULTS: Significant cure response observed in Ceftriaxone treated patient’s P ≤ 0.05 and significant failure response observed in Amoxicillin-clavulanic acid-treated patients when groups compared with each other. About gender and age groups, no significant differences in number between group 1 and 2 P ≥ 0.05. CONCLUSION: Ceftriaxone found more effective in the treatment of acute bacterial sinusitis than Amoxicillin+ clavulanic acid. Amoxicillin+clavulanic acid associated with more male failure cases recorded than female.
Deriving Bathymetry From Optical Images With a Localized Neural Network Algorithm

We present a localized neural network algorithm for water depth estimation from optical remote sensing images. Our new model is called a locally adaptive back-propagation neural network (LABPNN). In an LABPNN, the neural networks were trained at regularly distributed normative sites. For each unit of LABPNN, training data samples were identified by a specified search radius from the normative sites. Water depth was estimated by an ensemble of LABPNNs, with weights assigned inversely by their distances to the point of estimation. The water depth prediction accuracy from the LABPNN models doubled compared to the regular back-propagation network that uses all of the samples without considering nonstationarity. We also compared the LABPNN model with the regression-based inversion model with the localization feature. The prediction error of LABPNN is less by about 5% in the first case study, and 7% less in the second case study. It is because of the better performance of neural networks than that of the regression models when the sample data are relatively sparse. The experiments suggest that the LABPNN model is a viable solution to water depth retrieval from optical images.
Equipment failure: conducts of nurses and implications for patient safety.

OBJECTIVES To identify equipment failures during handling by nurses and analyze the conduct of the professionals when these failures occur. METHODS Descriptive, exploratory and qualitative study, whose field was the intensive care unit of a public institution, and the participants were day nurses that worked providing direct care to patients. Data were produced in 2014 through systematic observation and interviews and were examined with thick description and content analysis. RESULTS The outcomes evinced the inadequate functioning of infusion bombs, users' errors related to the design of equipment and problems with batteries of artificial fans. These failures related to the management of equipment in the unit. FINAL CONSIDERATIONS It is necessary to strengthen the monitoring systems of safety conditions of equipment in intensive nursing care to prevent incidents.
All You Need is "Love": Evading Hate Speech Detection

With the spread of social networks and their unfortunate use for hate speech, automatic detection of the latter has become a pressing problem. In this paper, we reproduce seven state-of-the-art hate speech detection models from prior work, and show that they perform well only when tested on the same type of data they were trained on. Based on these results, we argue that for successful hate speech detection, model architecture is less important than the type of data and labeling criteria. We further show that all proposed detection techniques are brittle against adversaries who can (automatically) insert typos, change word boundaries or add innocuous words to the original hate speech. A combination of these methods is also effective against Google Perspective - a cutting-edge solution from industry. Our experiments demonstrate that adversarial training does not completely mitigate the attacks, and using character-level features makes the models systematically more attack-resistant than using word-level features.
Assessment of knowledge, attitude, and practice toward responsible self-medication among students of pharmacy colleges located in Anantapur district, Andhra Pradesh, India

INTRODUCTION: Responsible self-medication plays a vital role in appropriate use of nonprescription drugs which will improve safety and reduces unwanted effects of drugs. AIM: This study is designed to assess knowledge, attitude, and practice (KAP) toward responsible self-medication among pharmacy students. SETTINGS AND DESIGN: A cross-sectional survey was conducted in pharmacy students of various colleges located in Anantapur district, Andhra Pradesh, India. MATERIALS AND METHODS: A total of 403 pharmacy students were enrolled and subjected for interview using prevalidated KAP questionnaire on responsible self-medication. STATISTICAL ANALYSIS: Descriptive statistics were used to represent the sociodemographic characteristics and KAP levels. Association of socio-demographic variables with KAP levels are determined using the Chi-square test. RESULTS AND DISCUSSION: A total of 403 pharmacy students are recruited in the study, in these 19 (4.7%) diploma in pharmacy, 260 (64.5%) bachelor in pharmacy, 27 (6.7%) master in pharmacy, and 97 (24.1%) are doctor of pharmacy. Among 403 respondents, 150 (37.2%) good knowledge, 397 (98.5%) positive attitude, and 170 (42.2%) practice toward responsible self-medication. Respondent's age, pharmacy division, residence, and their parents’ profession were significantly associated with good knowledge and rational practice toward responsible self-medication with a P < 0.05. CONCLUSION: The study concludes that pharmacy students are shown more positive attitude toward responsible self-medication. However, students are lack of knowledge and practice of responsible self-medication.