Miracle-dz/UniFAR-FTUs huggingface dataset:
Setting Air Quality Standards for PM2.5: A Role for Subjective Uncertainty in NAAQS Quantitative Risk Assessments?

The U.S. Clean Air Act (CAA) requires the Administrator of the U.S. Environmental Protection Agency (EPA) to set and periodically review national ambient air quality standards (NAAQS) for criteria pollutants. Because NAAQS must be set without balancing health risks against cost, Administrators look for where health risk tapers off. For some pollutants, however, no evidence exists of such a diminishment. The Administrator must instead evaluate how the strength of evidence for the scientific validity of risk estimates weakens for exposure levels below the central mass of observations indicating a pollutant–health risk relationship. Such an evaluation requires judgments about uncertainties that are inherently subjective. The risk assessments the Agency prepares during NAAQS reviews provide a natural platform for quantitatively characterizing these subjective uncertainty judgments, but the Agency is no longer making use of this opportunity. This article describes EPA's early development of methods to quantitatively characterize subjective uncertainty in NAAQS risk assessments, then traces the progressive elimination of such uncertainty analysis in the risk assessments for the three past NAAQS reviews for fine particulate matter (PM2.5), even while judgments about this uncertainty were becoming increasingly central to Administrators’ NAAQS decisions. As a result, the risk assessments now lack relevance to NAAQS decision making. To reestablish a meaningful decision‐support role for NAAQS risk assessments, this article suggests alterations to the process of preparing them. Taking no position on the scientific or legal appropriateness of past NAAQS decisions, the suggested process is intended to better synthesize the scientific evidence to better inform (without constraining) the Administrator's policy decisions.
Classification for SAR Scene Matching Areas Based on Convolutional Neural Networks

The selection of scene matching areas is a difficult problem in the field of matching guidance. Compared with the traditional methods of matching feature extraction and pattern classification, this letter applies convolutional neural networks (CNN) to the extraction of synthetic aperture radar (SAR) scene matching regions for the first time. First of all, we match the SAR images of the same land taken by satellites from different angles and in different phases, and then automatically label the matching suitability of the images as the output of the network according to the matching results. Next, the digital elevation model data reflecting the elevation information and the SAR image grayscale information are fused as the input to the network. Finally, CNN is used to automatically extract the matching features and classify the suitability of the SAR images. The proposed method avoids the steps of extracting features manually and improves the classification performance of SAR scene matching area. Compared with the support vector machine method, the classification accuracy increases from 86.1% to 93.3%.
Smokeless tobacco use: pattern of use, knowledge and perceptions among rural Bangladeshi adolescents

Background The aim of the study was to investigate the practice and pattern of smokeless tobacco (SLT) use as well as the knowledge and perception about its ill effects among rural Bangladeshi adolescents. Methods A cross-sectional survey was conducted among students aged 13–18 years in two rural secondary schools in Bangladesh in August 2015. Data were collected through a self-administered questionnaire which consists of topics derived from the Social Cognitive Theory and Health Belief Model (personal characteristics, environmental factors, self-efficacy, outcome expectancies, perceived susceptibility, perceived severity, perceived benefits, perceived barriers, and cues to action). Data analysis was performed using SPSS version 24. A descriptive analysis was conducted to determine the current pattern of SLT use and knowledge about its ill effects. A chi-square test and Fisher exact test were conducted to explore associations between variables. Lastly, a logistic regression model was used to locate the predictors for current SLT use. Results A total of 790 students participated in the study. Among them, 9.5% (75) had used SLT at least once and 3.7% (29) were current SLT users. Males had a higher incidence of SLT use compared with females. The majority of students (77.3%) initiated SLT use between 10–13 years of age. ‘Zarda’ was the most common type of SLT used and most of the current users (86%) were able to buy SLT without age restrictions. Most of the current users (90%) wanted to quit SLT immediately; however, professional help was not available in schools. Overall, students had a good knowledge about the harmful effects of SLT with 54.8% (428) of respondents scoring in the good knowledge category. However, the majority of never SLT users (55.4%; 396) had a good knowledge compared to ever SLT users (42.7%; 32). Significant predictors of current SLT use included being a student aged 14 years and above (OR = 6.58, 95% CI [2.23–28.31]) as well as the variables of self-efficacy (OR = 5.78, 95% CI [1.46–19.65]), perceived barriers (OR = 0.30, 95% CI [0.10–0.74]), perceived benefit (OR = 0.21, 95% CI [0.05–1.03]) and perceived severity (OR = 0.36, 95% CI [0.16–0.91]). Discussion This study demonstrates the need for comprehensive prevention and control programme in rural schools targeting young adolescents. Effective measure should be taken to reshape the attitude of rural adolescents towards self-confidence and competence, as to prevent SLT use.
High Confidence Staple for Visual Tracking

In the visual tracking, correlation filtering (CF) based on tracking algorithms have shown favorable performance in recent years, and have the impressive performance on benchmark datasets. However, the tracking model has limited information about their context and can easily drift in cases of fast motion, occlusion or background clutter, and the trackers update tracking models at each frame without considering whether the detection is accurate or not. In this paper, we present an improved strategy that is adding more background context and changing the tracker model updating strategy. Experimental results show that the performance of the model has been improved effectively.
A Noniterative Approximation of a Full-Wave Model of Thin Wire Above and Buried in a Lossy Ground

This work proposes a formulation to overcome some of the numerical challenges of a full-wave model of a lossy single-phase overhead line or a bare underground conductor without significant loss of accuracy. This approach is defined as a quasi full-wave approximation which consists to a non-iterative approach to avoid solving the integral equation associated with a full-wave model. For the sake of comparison, four possibilities are considered in the evaluation, namely: full-wave, quasi-full-wave, quasi-transverse-electromagnetic and image approximations. The results show that the loss of information of the proposal approach is minimal and it can be used for a suitable evaluation of the electromagnetic fields associated with the overhead line or buried conductor.
Characterization of Relative Complex Permittivity and Permeability for Magneto-Dielectric Sheets

A new method is developed to extract relative complex permittivity and permeability of magneto-dielectric sheets. Two test fixtures are used to separately extract electric and magnetic properties of the material under test (MUT). The unknown parameters corresponding to dispersion models of the complex permittivity and permeability of the magneto-dielectric sheet are optimized by comparing the measured <inline-formula><tex-math notation="LaTeX">$\vert S_{{\rm{21}}}\vert $</tex-math></inline-formula> of the test fixtures containing the MUT with the <inline-formula> <tex-math notation="LaTeX">$\vert S_{{\rm{21}}}\vert $</tex-math></inline-formula> obtained from full-wave simulation. CST Microwave Studio is used to perform the simulations and optimization. The method is verified and the extracted electromagnetic properties of two ferrite sheet samples are presented. Also, the uncertainty of the system due to air gaps in the test fixtures is investigated.
A Modified System Model and its Application on SINS/GPS Integrated System

Kalman filter has been extensively applied in vast areas. However, the performance of Kalman filter rests on the accuracy of prior information such as model construction. In the integrated system of Strapdown Inertial Navigation System (SINS)/Global Positioning System (GPS), the model construction is affected by a certain error sources. The most significant one is computational errors, which are caused by improper reference frame and the absence of true values. To solve the problem, this paper presents a modified system model which reduce the impact of computational errors by selecting computational frame as reference coordinate frame and removing all true values. Simulation results have demonstrated that modified system model effectively improves the performance of Kalman filter in SINS/GPS integrated system.
Single-cell RNA-sequencing reveals the existence of naive and primed pluripotency in pre-implantation rhesus monkey embryos

Naive pluripotency exists in epiblast cells of mouse pre-implantation embryos. However, whether the naive pluripotency is transient or nonexistent in primate embryos remains unclear. Using RNA-seq in single blastomeres from 16-cell embryos through to hatched blastocysts of rhesus monkey, we constructed the lineage segregation roadmap in which the specification of trophectoderm, epiblast, and primitive endoderm is initiated simultaneously at the early blastocyst stage. Importantly, we uncovered the existence of distinct pluripotent states in monkey pre-implantation embryos. At the early- and middle-blastocyst stages, the epiblast cells have the transcriptome features of naive pluripotency, whereas they display a continuum of primed pluripotency characteristics at the late and hatched blastocyst stages. Moreover, we identified potential regulators that might play roles in the transition from naive to primed pluripotency. Thus, our study suggests the transient existence of naive pluripotency in primates and proposes an ideal time window for derivation of primate embryonic stem cells with naive pluripotency.
One Cycle Control for Battery Connected Standalone Photovoltaic Systems for DC Loads

This paper proposes the utilization of one-cycle controller for multi proposal tasks in a stand-alone photovoltaic system that supplies power to direct current (DC) applications. The photovoltaic system proposed in this paper is composed of one photovoltaic panel, a battery bank as an energy storage system and two DC-DC converters: one for track the maximum power point and the other to regulate the bus voltage for DC applications. Both of the converters are switched by controllers that utilizes the one-cycle control technique instead of the classical pulse width modulation. The one-cycle control technique has been used in the switching converters in this work to allow fast response to transients, no overshoots, zero steady state error and low cost implementation due to the controller analogic circuitry simplicity
Neural networks for predicting student performance in online education

Failure rates in online higher education raises as a major problem for the modal instruction, thus, prediction of student performance is proposed as a preventive strategy to diminish student failure. Research in student performance prediction is of a wide variety that complicates the replication of studies in order to take advantage of research results. This study tackles this issue by proposing three types of neural networks for student performance prediction, which are built from standardized variables more easily obtained than those used in most of studies identified. By the statistical comparison of the prediction accuracies of the neural networks with that of a statistical lineal regression, the three neural networks obtained higher prediction accuracy. As conclusion, neural networks are proposed as techniques for an early prediction and identification of students in risk of failure.
How Agile is the Adaptive Data Rate Mechanism of LoRaWAN?

The LoRaWAN based Low Power Wide Area networks aim to provide long-range connectivity to a large number of devices by exploiting limited radio resources. The Adaptive Data Rate (ADR) mechanism controls the assignment of these resources to individual end-devices by a runtime adaptation of their communication parameters when the quality of links inevitably changes over time. This paper provides a detailed performance analysis of the ADR technique presented in the recently released LoRaWanSpecifications (v1.1). We show that the ADR technique lacks the agility to adapt to the changing link conditions, requiring a number of hours to days to converge to a reliable and energy-efficient communication state. As a vital step towards improving this situation, we then change different control knobs or parameters in the ADR technique to observe their effects on the convergence time.
Transdermal applications of ethosomes – a detailed review

Abstract Skin, the largest organ of the body serves as a potential route of drug delivery for local and systemic effects. However, the outermost layer of skin, the stratum corneum (SC) acts as a tough barrier that prevents penetration of hydrophilic and high molecular weight drugs. Ethosomes are a novel phospholipid vesicular carrier containing high ethanol concentrations and offer improved skin permeability and efficient bioavailability due to their structure and composition. This article gives a review of ethosomes including their compositions, types, mechanism of drug delivery, stability, and safety behaviour. This article also provides a detailed overview of drug delivery applications of ethosomes in various diseases.
Combined Donepezil and Ethanolic Extract of Propolis Improved Memory Better Than Donepezil and Propolis Monotherapy in Wild Type Drosophila melanogaster

Background Donepezil is the most common drug used in the treatment of disorders associated with memory loss, especially that in Alzheimer's disease. Healthy individuals however have continued to use it as a memory enhancer. This study was aimed at evaluating the combined therapy of donepezil and propolis on cognition in Drosophila melanogaster. Method. Drosophila melanogaster flies were divided into five groups and fed with the different treatment doses of ethanolic extract of propolis and donepezil as follows: normal food, propolis 250 mg/mL, propolis 50 mg/mL, donepezil 0.001M, and donepezil 0.001M/propolis 50 mg/mL added to their food. The flies were fed from larval stage for 30 days. The memory and learning tests were conducted after every 10 days to assess improvement with time. Results The results obtained showed that the combination of propolis with donepezil caused a remarkable improvement in both the short- and long-term memory. In addition, there was a dose dependent improvement with the administration of propolis. Conclusion Propolis extract obtained from different parts of Uganda expressed cognitive improvement when coadministered with donepezil in wild type Drosophila melanogaster.
Estimation of Eyelid Pressure Using a Blepharo-Tensiometer in Patients with Functional Nasolacrimal Duct Obstruction

Purpose To compare the eyelid pressure between patients with functional nasolacrimal duct obstruction (FNLDO) and normal controls using blepharo-tensiometer, and to evaluate the relationship between eyelid pressure and the outcomes of silicone intubation (SI) in patients with FNLDO. Study design Prospective case-control study. Methods We enrolled 36 eyes of 36 patients with suspected FNLDO who underwent SI and 36 healthy eyes of age-matched controls. One eye of each patient with FNLDO was randomly selected for analysis. The eyelid pressure was estimated using a blepharo-tensiometer and compared between the control and FNLDO groups. The relationship between eyelid pressure and clinical variables was analyzed. The outcomes of SI were assessed at 6 months after surgery using subjective and objective criteria. Results The eyelid pressure was significantly lower in the FNLDO group than in the control group (P=0.008). In the control group, the eyelid pressure was correlated with age (P<0.001) and lower eyelid laxity (P=0.016). In the FNLDO group, the eyelid pressure was only correlated with age (P<0.001). The success rate of SI for FNLDO was 69.4% (25 of 36 eyes). The eyelid pressure was higher in the surgical success subgroup than in the failure subgroup, although the difference was not statistically significant (P=0.08). Conclusions Our results suggest that the eyelid pressure measured using a blepharo-tensiometer has a diagnostic value since it is decreased in patients with FNLDO. The role of eyelid pressure as a possible predictor of the outcomes of SI for FNLDO should be investigated in further studies. This trial is registered with KCT0002828.
Real-Time High-Quality Stereo Matching System on a GPU

In this paper, we propose a low error rate and realtime stereo vision system on G PU. Many stereo vision systems on G PU have been proposed to date. In those systems, the error rates and the processing speed are in trade-off relationship. We propose a real-time stereo vision system on GPU for the high resolution images. This system also maintains a low error rate compared to other fast systems. In our approach, we have implemented the cost aggregation (CA), cross-checking and median filter on GPU in order to realize the real-time processing. Its processing speed is 40 fps for $1436\times 992$ pixels images when the maximum disparity is 145, and its error rate is the lowest among the GPU systems which are faster than 30 fps.
Indications for the use of human chorionic gonadotropic hormone for the management of infertility in hypogonadal men

Hypogonadism among men desiring fertility preservation presents a unique challenge to physicians. Over the past decade the number of younger men with hypogonadism has increased dramatically. These men are often treated with testosterone replacement therapy (TRT) which can result in azoospermia and potentially infertility. Human chorionic gonadotropin (hCG) therapy can help re-establish or maintain spermatogenesis in hypogonadal men. We review the indications, and discuss the current evidence for the role of hCG in men with hypogonadisms.
Prediction Models for Oral Health-Related Quality of Life in Patients with Temporomandibular Joint Osteoarthritis 1 and 6 Months After Arthrocentesis with Hyaluronic Acid Injections.

AIMS To develop models for prognostic prediction of oral health-related quality of life (OHRQoL) for patients with temporomandibular joint osteoarthritis (TMJ OA) at 1- and 6-month follow-ups after arthrocentesis treatment with hyaluronic acid (HA) injections once a week for 4 weeks. METHODS From a cohort of 522 adult patients with TMJ OA treated with arthrocentesis with HA injections, 510 and 463 adult patients were included in the 1- and 6-month follow-ups, respectively. Patient characteristics and history, clinical examinations, and questionnaires were recorded as potential predictors at start of treatment, and all patients underwent an identical treatment protocol. Patients' OHRQoL values at 1 and 6 months after completing the treatment were used as outcome measures. Logistic regression methods were used to develop prediction models, and the performance and validity of these models were evaluated according to state-of-the-art methods, including receiver-operating characteristics curve for the discrimination of the models and calibration plots for the calibration of the models. RESULTS History of mental disease, maximal protrusion of the jaw, muscular pain with palpation, joint pain with palpation, awake bruxism, chewing-side preference, and low OHRQoL at baseline were significantly associated with OHRQoL at the 1-month follow-up, while age, pain in other joints, history of mental disease, joint pain with palpation, sleep bruxism, awake bruxism, chewing-side preference, and low OHRQoL at baseline were significantly associated with OHRQoL at the 6-month follow-up. While the performance of both models was found to be good in terms of calibration, discrimination, and internal validity, the added predictive values of the 1-month and 6-month models for ruling in the risk of low OHRQoL were 19% and 31%, respectively, while those for ruling it out were 28% and 15%, respectively. CONCLUSION Several predictors were found to be significantly associated with patients' OHRQoL after treatment. Both prediction models may be reliable and valid for clinicians to predict a patient's risk of low OHRQoL at follow-up, so the models may be useful for clinicians in decision-making for patient management and for informing the patient.
Comparative Proteome Analysis Reveals Lipid Metabolism-Related Protein Networks in Response to Rump Fat Mobilization

Altay is a typical fat-tailed sheep breed displaying the unique ability to rapidly mobilize fat, which is vital for maintaining a normal metabolism that facilitates its survival in lengthy winter conditions. However, the physiological, biochemical, and molecular mechanisms underlying fat mobilization remain to be elucidated. In this study, the monitoring of rump fat adipocyte sizes disclosed a positive correlation between cell size and fat deposition ability. In addition, we subjected sheep to persistent starvation to imitate the conditions that trigger rump fat mobilization and screened 112 differentially expressed proteins using the isobaric peptide labeling approach. Notably, increased secretion of leptin and adiponectin activated the key fat mobilization signaling pathways under persistent starvation conditions. Furthermore, the upregulation of resistin (RETN), heat-shock protein 72 (HSP72), and complement factor D (CFD) promoted lipolysis, whereas the downregulation of cell death-inducing DFFA-like effector C (CIDEC) inhibited lipid droplet fusion, and the increase in HSP72 and apolipoprotein AI (Apo-AI) levels activated the body’s stress mechanisms. The synergistic actions of the above hormones, genes, and signaling pathways form a molecular network that functions in improving the adaptability of Altay sheep to extreme environments. Our findings provide a reference for elucidating the complex molecular mechanisms underlying rump fat mobilization.