Miracle-dz/UniFAR-FTUs huggingface dataset:
High-frequency Near-field Physeter macrocephalus Monitoring by Stereo-Autoencoder and 3D Model of Sonar Organ

Passive acoustics allow us to study large animals and obtain information that could not be gathered through other methods. In this paper we study a set of near-field audiovisual recordings of a sperm whale pod, acquired with a ultra high-frequency and small aperture antenna. We propose a novel kind of autoencoder, a Stereo-Autoencoder, and show how it allows to build acoustic manifolds in order to increase our knowledge regarding the characterization of their vocalizations, and possible acoustic individual signature.
Face Authentication in E-Learning using Local Binary Pattern and Haar Cascade

Face Authentication is one way to secure a system against attacks, especially useful for systems such as E-Learning which is used by many people as a medium of online learning for students. We review several methods that have been tried in the E-Learning system, discuss the advantages and disadvantages of each method. The results of the review it was found that face detection alone would be better if using Deep Convolutional Neural Network when compared to Local Binary Pattern. As for the effective feature recognition method for E-Learning is Deep-Learning, because the accuracy level generated by deep learning is very good at 95%, and the speed of the method for someone's technician requires only 1.7 ms (millisecond), Haar is good enough for used, but the resulting accuracy rate is only 68%, and the time required for someone's technician is 4s (second).
Joint Spectral and Spatiotemporal Underwater Acoustic Environment Characterization via Tensor Co-Clustering

Using data-driven methods for characterizing spectral and spatiotemporal structures in underwater acoustic environments complements the traditional use of physics-based acoustic propagation models that often focus on capturing average environmental characteristics. One-way clustering of acoustic data in time, space and frequency can reveal individual, that is per mode, structure, but fails to identify couplings among the structures in these modes. Co-clustering is a clustering approach that can identify groups of similar elements (co-clusters) across all modes in a tensor. Our proposed co-clustering approach acts on a tensor build with acoustic data captured by a hydrophone array. It identifies the co-clusters, and the spectral and spatiotemporal structure that defines them by coupling one-way clustering with a Tucker approximation model. One-way clustering reveals the tensor structure per mode, namely time, frequency, and space, while the Tucker model captures trilinear structures coupling each mode. A co-clustering algorithm based on the alternating directions method of multipliers and the Levenberg-Marquardt method is developed. Numerical test on real acoustic-array data are used to illustrate the performance of the proposed co-clustering algorithm.
RailNet: A Segmentation Network for Railroad Detection

Future trains will use more computer vision aids to help achieve fully autonomous driving. One of the most important parts of the train’s visual function is the detection of railroad obstacles. This makes it important to identify and segment the railroad region within each video frame as it allows the train to identify the driving area so that it can do effective obstacle detection. Traditional railroad detection methods rely on hand-crafted features or highly specialized equipment such as lidar, which typically require expensive equipment to be maintained and are less reliable in scene changes. RailNet is a deep learning segmentation algorithm for railroad detection for videos captured by the front-view on-board cameras. RailNet provides an end-to-end solution that combines feature extraction and segmentation. We have modified the backbone network to extract multi-convolution features and use a pyramid structure to make the features have a top-to-bottom propagation. Our model can detect the railroad without generating large numbers of regions, which greatly increases the detection speed. Tested on a railroad segmentation dataset (RSDS) which we have built, RailNet exhibits very good performance while achieving 20 frames per second processing speed.
Extending Functionality of Early Fault Diagnostic System for Online Security Assessment of Nuclear Power Plant

The new instrumentation and control (I&C) systems of the nuclear power plants (NPPs) improve the ability to operate the plant enhance the safety and performance of the NPP. However, they bring a new type of threat to the NPP's industry-cyber threat. The early fault diagnostic system (EDS) is one of the decision support systems that might be used online during the operation stage. The EDS aim is to prevent the incident/accident evolution by a timely troubleshooting process during any plant operational modes. It means that any significative deviation of plant parameters from normal values is pointed-out to plant operators well before reaching any undesired threshold potentially leading to a prohibited plant state, together with the cause that has generated the deviation. The paper lists the key benefits using the EDS to counter the cyber threat and proposes the framework for cybersecurity assessment using EDS during the operational stage.
Experiences and Perceptions of Menopause among women in Ibadan South East Local Government area, Nigeria

Menopause is a natural period in which menstruation stops, thus ending in most cases, a woman’s childbearing years. More still needs to be known about the discomforts which are associated with menopause. The study was therefore designed to determine the menopausal experiences and perceptions of menopausal women in Ibadan South East Local Government Area. A three-stage sampling technique was used to select the LGA, wards, and participants for the study. Eight Focus Group Discussions (FGD) were conducted and a validated questionnaire was used to interview 240 participants aged 46 to 69 years. Five questions were used to assess participants’ knowledge with each question attracting 1 point thus culminating to a maximum of 5 points. Data from the FGD were recorded on audio-tapes, transcribed and subjected to content analysis. Descriptive and Chi-square statistics were used to analyze the quantitative data. The mean age of participants was 56.9 ± 6.2 years. The mean age at menopause was 46.1 ± 2.5 years. Eighty-five percent of participants had ever heard about menopause and the participants’ major source of information included close relatives (75.5%). The mean knowledge score for menopause using a 5-point scale was 2.8 ±1.0. Only 28.0% of the participants could state at least one symptom of menopause and 4.1% could list the risks associated with it. Fifty-four percent who scored above the mean knowledge score had positive attitude towards menopause regarding it as a natural occurrence. Seventy percent had the belief that sexual intercourse causes sickness for menopausal women. The belief of 60.8% of the participants was that women should not tell anyone about their menopausal experiences. Eighty-three percent had experienced at least one out of the 19 common symptoms of menopause. Discomforting experiences attributed to menopause included dryness of the vagina (81.3%), pain during intercourse (76.7%) and joint pains (74.2%). Only 32.9% took action to alleviate the discomforts. Actions taken included self-medication (47.4%), adoption of sexual abstinence (13.0%) among others. Illnesses perceived to be associated with menopause included: fibroid (34.4%), weakness of the body (30.0%) and protruding stomach (18.0%). FGD revealed that many of the participants were of the opinion that sex should be avoided by menopausal women in order to prevent adverse effects associated with menopause. There are gaps in knowledge, wrong perceptions and use of inappropriate palliative measures regarding menopause among the participants. Public enlightenment and community-based patient education interventions are needed to address these challenges.
Estimating the Axial Load of In-Service Continuously Welded Rail Under the Influences of Rail Wear and Temperature

Linear guided wave based methods have been proposed to measure the axial load of continuously welded rail (CWR) in service. The underlying principle is that the propagation velocities of excited guided waves are sensitive to the axial load. However, the in-service CWR inevitably faces changes in rail wear and temperature, which also affects the propagating guided waves and results in severe degradation of existing methods. In this paper, we proposed the IGA-IWLS algorithm to estimate the axial load of in-service CWR using multiple guided wave modes. This novel load estimation method takes rail profile and phase velocities of a small set of wave modes as input, then uses an improved genetic algorithm to roughly search the candidate solutions of axial load and Young’s modulus, and finally employs weighted least squares algorithm to iteratively converge to the estimated value of axial load. The paper presents the estimation theory in detail, including selection of the optimal set of guided wave modes and the IGA-IWLS algorithm. Numerical experiments show that the proposed method is able to estimate the axial load of CWR with an accuracy less than 2 MPa and is robust to measurement error and model error.
Channel Capacity for Underwater Visible Light Communication Systems

This paper focuses on the capacity of underwater visible light communication (UVLC) system. The system is based on intensity modulation with direct detection (IM/DD). In such a system, the channel gain is often based on Lambertian radiation pattern of the transmitting light emitting diode (LED) taking absorption and scattering into account. The channel gain directly changes with different amount of turbidity in water and several related geometrical parameters. Under the non-negativity, peak power, and average power constraint, the lower bound on the point-to-point (P2P) capacity of UVLC system is derived. The lower bound is obtained using the fact that the differential entropy of the channel output is larger than the differential entropy of the channel input. Simulation results demonstrate that the capacity of the UVLC system varies with various water types and spatial location of the transmitter and receiver.
Exploiting Malay Corpus On Islamic Issue using Sketch Engine

The aim of this paper is to create and compile a corpus and then studies how it can be query and exploit in Sketch Engine. We present A Malay Corpus that created based on Islamic issues keywords which crawled from new media sources between the year 2015 until 2018. Sources chosen are such as website, blog, journals, downloaded books and online newspaper. The collection consists of 329,835 words from total of 123 articles. Sketch Engine is used as a tool to learn how language is processed. It works as an online corpus processing system with large samples of language. Function as Search, Word Sketch, Thesaurus, Word List and Sketch diff are features used in this research to do a test on data processing from Malay corpus in Islamic Issues named Isu_Islam1.
Statistical Shipping Noise Characterization and Mitigation for Underwater Acoustic Communications

Achieving high data rate robust communication in shallow and harbour underwater acoustic (UA) environments can be a demanding challenge in the presence of shipping noise. Noise generated from nearby passing ships can lead to impulsive agitations which impair UA communication systems. Utilizing the assumption that impulse noise exhibits sparsity, we realize a compressed sensing (CS) based framework for noise estimation exploiting the pilot sub-carriers of UA orthogonal frequency-division modulation systems. Under the CS framework, we propose the use of a empirical Bayesian approach which first characterizes the statistical properties of shipping noise prior to conceiving an estimate. In addition, we invoke the K-SVD algorithm for dictionary learning. K-SVD iteratively forms a sparse representation for the class of shipping noise signals, which is later used for noise estimation. Numerical results show that the empirical Bayesian based signal recovery algorithm yields the best performance for interference estimation.
Diagnosis of inverter-fed induction motors in short time windows using physics-assisted deep learning framework

This article presents a framework for accurate fault diagnostics in inverter-fed induction machinery operating under variable speed and load conditions within very short time windows. Condition indicators based on fault characteristic frequencies observed over the extended Park's vector modulus are fused with deep features extracted using stacked autoencoders to generate a multidimensional feature space for fault classification using support vector machine. The proposed approach is demonstrated in a laboratory setup to detect the most commonly occurring faults, namely, the stator turns fault, broken rotor bars fault and bearing fault with an accuracy > 98% within a short time window of 2–3 seconds.
Medicare Part D&Apos;S Effects on Elderly Drug Costs and Utilization

We analyze Medicare Part D's net effect on elderly out-of-pocket (OOP) costs and use of prescription drugs using a dataset containing 1.4 billion prescription records from Wolters Kluwer Health (WKH). These data span the period December 2004-December 2007 and include pharmacy customers whose age as of 2007 is greater than 57 years. The outcomes we examine are OOP cost per day's supply of a medication, the days of medication supplied per capita, and the number of individuals filling prescriptions. We compare outcomes before vs. after January 2006, for those over age 66 years vs. for those age 58-64 years, adjusting for the under-reporting of certain cash-only transactions in the WKH data. Our results indicate that from 2005-2007, Part D reduced elderly OOP costs per day's supply of medication by 21.7%, and increased elderly use of prescription drugs by 4.7%, implying a price elasticity of demand of -0.22. These effects occurred primarily during the first year of the program. An age- and time-standardized comparison of our quantity results with previous estimates from Walgreens data shows that our findings are 2.6 times as large. We conclude that Part D lowered elderly patients' OOP costs substantially and increased utilization modestly, and note that in comparing results across studies on this topic, magnitudes may vary substantially due to differences in data and methods.
Stable Hemodynamics within “No-Touch” Saphenous Vein Graft

Purpose: To investigate the hemodynamics characteristics of the “no-touch” saphenous vein graft (SVG) conduits by nicardipine intraluminal administration in vivo experiment. Methods: A total of 59 consecutive patients were enrolled and underwent a sequential SVG to three non-left anterior descending (LAD) targets with the average runoff ≤2 mm, 30 with “no-touch” harvest technique (group A) and 29 with conventional preparation (group B). The patients were subject to nicardipine intraluminal injection during off-pump coronary artery bypass grafting (CABG) procedure. The intraoperative flow was measured with the ultrasonic transit time flow meter (TTFM), and the graft patency testified by multi-detector computed tomography (MDCT) angiography, respectively. Results: The baseline blood flow was higher in group A than that in group B (p <0.05). However, the increases in blood flow of SVG conduits in group A were lower than those in group B with 19.7 ± 5.9 vs. 35.4 ± 9.2 mL/min, 14.8 ± 5.6 vs. 23.1 ± 6.8 mL/min, 6.6 ± 2.1 vs. 11.2 ± 4.3 mL/min before the first, second, and third anastomose after nicardipine intraluminal administration, respectively (all p <0.01). Conclusions: No-touch SVGs were associated with higher baseline blood flow and less rises after nicardipine intraluminal administration during off-pump CABG procedure compared with conventional preparation. The no-touch SVGs seemed to be less spastic and well-tolerated on flow dilatation.
A Mixed Methods Study of Change Processes Enabling Effective Transition to Team-Based Care

Team-based care is considered central to achieving value in primary care, yet results of large-scale primary care transformation initiatives have been mixed. We explore how underlying change processes influence the effectiveness of transition to team-based care. We studied 12 academically affiliated primary care practices participating in a learning collaborative, using longitudinal staff survey data to measure progress toward team-based care and qualitative interviews with practice staff to understand practice transformation. Transformation efforts focused on team formation and capacity building for quality improvement. Using thematic analysis, we explored types of change processes undertaken and the relationship between change processes and effective team-based care. We identified three prototypical approaches to change: pursuing functional and cultural change processes, functional only, and cultural only. Practice sites prioritizing both change processes formed the most effective teams: simultaneous functional and cultural change spurred a mutually reinforcing virtuous cycle. We describe implications for research, practice, and policy.
Air pollution: the emergence of a major global health risk factor.

Air pollution is now recognized by governments, international institutions and civil society as a major global public health risk factor. This is the result of the remarkable growth of scientific knowledge enabled by advances in epidemiology and exposure assessment. There is now a broad scientific consensus that exposure to air pollution increases mortality and morbidity from cardiovascular and respiratory disease and lung cancer and shortens life expectancy. Although air pollution has markedly declined in high-income countries, it was still responsible for some 4.9 million deaths in 2017, largely in low- and middle-income countries, where air pollution has increased over the past 25 y. As governments act to reduce air pollution there is a continuing need for research to strengthen the evidence on disease risk at very low and very high levels of air pollution, identify the air pollution sources most responsible for disease burden and assess the public health effectiveness of actions taken to improve air quality.
Structure-based inhibitors of amyloid beta core suggest a common interface with tau

Alzheimer’s disease (AD) pathology is characterized by plaques of amyloid beta (Aβ) and neurofibrillary tangles of tau. Aβ aggregation is thought to occur at early stages of the disease, and ultimately gives way to the formation of tau tangles which track with cognitive decline in humans. Here, we report the crystal structure of an Aβ core segment determined by MicroED and in it, note characteristics of both fibrillar and oligomeric structure. Using this structure, we designed peptide-based inhibitors that reduce Aβ aggregation and toxicity of already-aggregated species. Unexpectedly, we also found that these inhibitors reduce the efficiency of Aβ-mediated tau aggregation, and moreover reduce aggregation and self-seeding of tau fibrils. The ability of these inhibitors to interfere with both Aβ and tau seeds suggests these fibrils share a common epitope, and supports the hypothesis that cross-seeding is one mechanism by which amyloid is linked to tau aggregation and could promote cognitive decline.
More precise, more universal and more specific – the next generation of RNA‐guided endonucleases for genome editing

CRISPR is a prokaryotic defence system that was adapted as a tool for genome editing and has become one of the most important discoveries of this century. CRISPR-associated endonucleases cleave DNA at precise sites, which are marked by complementary short-guided RNA. The recently developed versions of endonucleases are compatible with a broad range of PAM motifs, have a higher specificity and enable a specific nucleotide to be replaced.
Simulation of Chemotherapy Effects in Older Breast Cancer Patients With High Recurrence Scores.

BACKGROUND Tumor genomic expression profile (GEP) data is used to guide chemotherapy choice, but there are gaps in evidence for women 65+. We estimate chemotherapy effects by age and comorbidity-level among women with early stage, hormone-receptor+/HER2- breast cancers and Oncotype DX scores of 26+. METHODS A discrete-time stochastic state-transition simulation model synthesized data from population studies and clinical trials to estimate outcomes over a 25-year horizon for subgroups based on age (65-69, 70-74, 75-79, 80-89y) and comorbidity-levels (no/low, moderate, severe). Outcomes were discounted at 3%, and included quality-adjusted life years (QALYs), life years, and breast cancer and other-cause mortality with chemo-endocrine vs. endocrine therapy. Sensitivity analysis tested the impact of varying uncertain parameters. RESULTS Women ages 65-69y with no/low comorbidity gained 0.16 QALYs with chemo-endocrine and reduced breast cancer mortality from 34.8% to 29.7%, for an absolute difference of 5.1%; this benefit was associated with a 12.8% rate of grade 3/4 toxicity. Women ages 65-69y with no/low or moderate comorbidity levels, and women aged 70-74 with no/low comorbidity had small chemotherapy benefits. All women ages 75+ experienced net losses in QALYs with chemo-endocrine therapy. The results were robust in sensitivity analyses. Chemotherapy had greater benefits as treatment effectiveness increased, but toxicity reduced the QALYs gained. CONCLUSION Among women ages 65-89 whose tumors indicate a high recurrence risk, only those age 65-74y with no/low or moderate comorbidity have small benefits from adding chemotherapy to endocrine therapy. GEP testing (and chemotherapy use) should be reserved for women under age 75y without severe comorbidity.
The effect of vitamin E & vitamin B on sperm function in rat varicocele model

We assessed the effect of vitamin E and vitamin B (Vit E & Vit B) and their combination on sperm functional parameters in the rat varicocele model. Male rats (n = 120) were divided into control (n = 30), sham (n = 30) and varicocele induction (n = 60) groups. After 2 months, 10 rats from each group were sacrificed to verify varicocele model. This part of results showed that sperm parameters, DNA damage, lipid peroxidation and residual histone were adversely effected in the varicocele group. From the 50 remaining rats in varicocele group, 10 rats received Vit B complex (6, 9.6, 30.4, 9.6 and 0.006 mg/kg for B6, B2, B9, B1 and B12 respectively), 10 rats received Vit E (40 mg/kg), 10 rats received Vit B & E, 10 rats only received water and 10 rats were only received sesame oil as a solvent for Vit E, for 2 months. From 40 remaining rats in control and sham groups, 20 rats only received water and other 20 rats only received sesame oil for 2 months. Then, all the aforementioned parameters were assessed. These results showed that Vit B antioxidant was more efficient in improvement of sperm parameters, chromatin integrity and lipid peroxidation in varicocelized rats compared with Vit E.