Miracle-dz/UniFAR-FTUs huggingface dataset:
Brain-Machine Coupled Learning Method for Facial Emotion Recognition

Neural network models of machine learning have shown promising prospects for visual tasks, such as facial emotion recognition (FER). However, the generalization of the model trained from a dataset with a few samples is limited. Unlike the machine, the human brain can effectively realize the required information from a few samples to complete the visual tasks. To learn the generalization ability of the brain, in this article, we propose a novel brain-machine coupled learning method for facial emotion recognition to let the neural network learn the visual knowledge of the machine and cognitive knowledge of the brain simultaneously. The proposed method utilizes visual images and electroencephalogram (EEG) signals to couple training the models in the visual and cognitive domains. Each domain model consists of two types of interactive channels, common and private. Since the EEG signals can reflect brain activity, the cognitive process of the brain is decoded by a model following reverse engineering. Decoding the EEG signals induced by the facial emotion images, the common channel in the visual domain can approach the cognitive process in the cognitive domain. Moreover, the knowledge specific to each domain is found in each private channel using an adversarial strategy. After learning, without the participation of the EEG signals, only the concatenation of both channels in the visual domain is used to classify facial emotion images based on the visual knowledge of the machine and the cognitive knowledge learned from the brain. Experiments demonstrate that the proposed method can produce excellent performance on several public datasets. Further experiments show that the proposed method trained from the EEG signals has good generalization ability on new datasets and can be applied to other network models, illustrating the potential for practical applications.
Natural Convection Heat Transfer From Cylinders of Arbitrary Cross Section

Analytical, numerical, and experimental studies of free convection heat transfer from the external surface of isothermal two-dimensional bodies, especially circular cylinders and vertical flat plates, have been conducted by many investigators. A review of the existing literature shows that most workers have focused mainly on experimental data of circular cylinders and vertical plates with air (Pr[approximately]0.71) as working fluid. The results of these studies have been empirical correlations restricted either to some simple geometries or to a narrow range of Rayleigh numbers. Only a few scientists have carried out numerical techniques, which unfortunately, are also restricted to simple geometries such as circular cylinders. There are a few analytical solutions for cylinders of fairly arbitrary cross section, but, unfortunately, those solutions are restricted to a very narrow range of Rayleigh were the boundary layer is thin compared to the local radius of curvature of the cylinder. The approximate method suggested by Raithby and Hollands, however, is capable of predicting heat transfer from cylinders of various cross sections and for wide ranges of Prandtl and Rayleigh numbers. Unfortunately, following the steps of their approximate method is complex, and engineers might be discouraged from using it. Therefore it is the goal of thismore » study to simplify this approximate method and introduce an expression for predicting natural convection heat transfer from isothermal two-dimensional bodies of arbitrary cross section over a wide range of Rayleigh and Prandtl numbers. In this paper, following a similar procedure to that outlined by Hassani and Hollands, an expression for predicting the convection heat transfer from two-dimensional bodies (cylinders of different convex cross sections) is derived. « less
The Effect of High-Intensity Interval Training Type on Body Fat Percentage, Fat and Fat-Free Mass: A Systematic Review and Meta-Analysis of Randomized Clinical Trials

This systematic review and meta-analysis of randomized controlled trials (RCTs) compared body compositional changes, including fat mass (FM), body fat percentage (BF%), and fat-free mass (FFM), between different types of high-intensity interval training (HIIT) (cycling vs. overground running vs. treadmill running) as well as to a control (i.e., no exercise) condition. Meta-analyses were carried out using a random-effects model. The I2 index was used to assess the heterogeneity of RCTs. Thirty-six RCTs lasting between 3 to 15 weeks were included in the current systematic review and meta-analysis. RCTs that examined the effect of HIIT type on FM, BF%, and FFM were sourced from online databases including PubMed, Scopus, Web of Science, and Google Scholar up to 21 June 2022. HIIT (all modalities combined) induced a significant reduction in FM (weighted mean difference [WMD]: −1.86 kg, 95% CI: −2.55 to −1.18, p = 0.001) despite a medium between-study heterogeneity (I2 = 63.3, p = 0.001). Subgroup analyses revealed cycling and overground running reduced FM (WMD: −1.72 kg, 95% CI: −2.41 to −1.30, p = 0.001 and WMD: −4.25 kg, 95% CI: −5.90 to −2.61, p = 0.001, respectively); however, there was no change with treadmill running (WMD: −1.10 kg, 95% CI: −2.82 to 0.62, p = 0.210). There was a significant reduction in BF% with HIIT (all modalities combined) compared to control (WMD: −1.53%, 95% CI: −2.13, −0.92, p = 0.001). All forms of HIIT also decreased BF%; however, overground running induced the largest overall effect (WMD: −2.80%, 95% CI: −3.89 to −1.71, p = 0.001). All types of HIIT combined also induced an overall significant improvement in FFM (WMD: 0.51 kg, 95% CI: 0.06 to 0.95, p = 0.025); however, only cycling interventions resulted in a significant increase in FFM compared to other exercise modalities (WMD: 0.63 kg, 95% CI: 0.17 to 1.09, p = 0.007). Additional subgroup analyses suggest that training for more than 8 weeks, at least 3 sessions per week, with work intervals less than 60 s duration and separated by ≤90 s active recovery are more effective for eliciting favorable body composition changes. Results from this meta-analysis demonstrate favorable body composition outcomes following HIIT (all modalities combined) with overall reductions in BF% and FM and improved FFM observed. Overall, cycling-based HIIT may confer the greatest effects on body composition due to its ability to reduce BF% and FM while increasing FFM.
Internet of Things and Deep Learning Enabled Diabetic Retinopathy Diagnosis Using Retinal Fundus Images

Recently, the Internet of Things (IoT) and computer vision technologies find useful in different applications, especially in healthcare. IoT driven healthcare solutions provide intelligent solutions for enabling substantial reduction of expenses and improvisation of healthcare service quality. At the same time, Diabetic Retinopathy (DR) can be described as permanent blindness and eyesight damage because of the diabetic condition in humans. Accurate and early detection of DR could decrease the loss of damage. Computer-Aided Diagnoses (CAD) model based on retinal fundus image is a powerful tool to help experts diagnose DR. Some traditional Machine Learning (ML) based DR diagnoses model has currently existed in this study. The recent developments of Deep Learning (DL) and its considerable achievement over conventional ML algorithms for different applications make it easier to design effectual DR diagnosis model. With this motivation, this paper presents a novel IoT and DL enabled diabetic retinopathy diagnosis model (IoTDL-DRD) using retinal fundus images. The presented Internet of Things Deep Learning – Diabetic Retinopathy Diagnosis (IoTDL-DRD) technique utilizes IoT devices for data collection purposes and then transfers them to the cloud server to process them. Followed by, the retinal fundus images are preprocessed to remove noise and improve contrast level. Next, mayfly optimization based region growing (MFORG) based segmentation technique is utilized to detect lesion regions in the fundus image. Moreover, densely connected network (DenseNet) based feature extractor and Long Short Term Memory (LSTM) based classifier is used for effective DR diagnosis. Furthermore, the parameter optimization of the LSTM method can be carried out by Honey Bee Optimization (HBO) algorithm. For evaluating the improved DR diagnostic outcomes of the IoTDL-DRD technique, a comprehensive set of simulations were carried out. A wide ranging comparison study reported the superior performance of the proposed method.
Searching for the “native” speaker: A preregistered conceptual replication and extension of Reid, Trofimovich, and O’Brien (2019)

Abstract This study conceptually replicated and extended Reid, Trofimovich, and O’Brien (2019), who found that native English speakers could be biased positively (or negatively) relative to a control condition in terms of how they rate non-native English speech. Our internet-based study failed to replicate Reid et al. across a wider population sample of “native” speakers (n = 189). Listeners did not change how they rated non-native English speech after social bias orientations and performed similarly across all five measures of speech and across age and race (Asian, Black, and Caucasian). We attribute our results to differences in the methods (in-person vs. online) and/or participants. Of note, roughly one-third of our “native” participants indicated proficiency in languages other than English and residency in 12 different English-speaking countries, despite identifying as a) fluent English speakers who b) used English primarily and c) acquired English before any other language from birth. These screening items taken together qualified “native” participants in line with traditional psycholinguistics research. We conclude that the concept of “nativeness” is tied to culture-specific perspectives surrounding language use. As such, the native/non-native categorical variable simultaneously serves and limits the advancement of psycholinguistics research.
Features of the Degradation of the Proton-Conducting Polymer Nafion in Highly Porous Electrodes of PEM Fuel Cells

The stability of new membrane–electrode assemblies of a proton-exchange membrane fuel cell with highly porous electrodes and low Pt loading, based on the proton-conducting polymer Nafion, was characterized in conditions of electrochemical aging. A comprehensive study of the effect of the microstructure on the evolution of the electrochemical characteristics of the new assemblies was obtained by voltammetry, electrochemical impedance spectroscopy, X-ray powder diffraction, and scanning electron microscopy. Because high (>70%) porosity provides intensive mass transfer inside an electrode, structural-modifying additives—long carbon nanotubes—were introduced into the new electrodes. PEM fuel cells with electrodes of a conventional composition without carbon nanotubes were used for comparison. The aging of the samples was carried out according to the standard accelerated method in accordance with the DOE (Department of Energy) protocols. The results show two fundamental differences between the degradation of highly porous electrodes and traditional ones: 1. in highly porous electrodes, the size of Pt nanoparticles increases to a lesser extent due to recrystallization; 2. a more intense “washout” of Nafion and an increase in ionic resistance occur in highly porous electrodes. Mechanisms of the evolution of the characteristics of structurally modified electrodes under electrochemical aging are proposed.
A Binary Programming Approach to Automated Test Assembly for Cognitive Diagnosis Models

Automated test assembly (ATA) has been an area of prolific psychometric research. Although ATA methodology is well developed for unidimensional models, its application alongside cognitive diagnosis models (CDMs) is a burgeoning topic. Two suggested procedures for combining ATA and CDMs are to maximize the cognitive diagnostic index and to use a genetic algorithm. Each of these procedures has a disadvantage: The cognitive diagnostic index cannot control attribute-level information and the genetic algorithm is computationally intensive. The goal of this article is to solve both problems by using binary programming, together with the item discrimination indexes of Henson et al., for performing ATA with CDMs. The three procedures are compared in simulation. Advantages and disadvantages of each are discussed.
Psychometric Testing of the Bahasa Version of the Brief Illness Perception Questionnaire among Indonesians with Type 2 Diabetes Mellitus

The Brief Illness Perception Questionnaire (B-IPQ) has been recommended to validate illness perception. Nevertheless, this measurement has yet to be validated with an assessment of the construct and convergent validities and reliability in Indonesia. Our study aimed to psychometrically test the 8-item B-IPQ among Indonesians with type 2 diabetes mellitus (T2DM). Data included 294 patients with T2DM with stratified multistage clustering. The 36-item Short Form Survey, 21-item Depression Anxiety Stress Scale, and fasting blood glucose (FBG) were used to examine convergence and divergence. The validity analysis included the construct and convergent validities with significant person correlations. Cronbach’s alpha, composite reliability (CR), and average variance extracted (AVE) were used to assess reliability. Confirmatory and exploratory factor analyses indicated a multidimensional structure, including cognitive with a five-item structure and emotional illness representation with a three-item structure, with an acceptable goodness of model fit. The tool revealed good internal consistency for the cognitive, emotional, and overall domains and was positively moderately correlated with FBG, stress, anxiety, and depression but negatively correlated with the overall quality of life and mental and physical component scores. Findings provide empirical evidence that the Bahasa version of the B-IPQ showed adequate internal consistency, exploratory and confirmatory, and thus is valid and reliable for illness perception assessments among Indonesians with T2DM.
Benchmarking Neural Capacity Estimation: Viability and Reliability

Recently, several methods have been proposed for estimating the mutual information from sample data using deep neural networks. This approach is referred to as (). s differ from other approaches in the literature as they are data-driven estimators. As such, they have the potential to perform well on a large class of capacity problems. To test the performance across various s, it is desirable to establish a benchmark encompassing the different challenges of capacity estimation. This is the objective of this paper. We consider three scenarios for benchmarking: (i) the classic AWGN channel, (ii) channels continuous inputs– the optical intensity and peak-power constrained AWGN channel (iii) channels with a discrete output– i.e., the Poisson channel. We also consider the extension to the multi-terminal case with (iv) the AWGN and optical MAC models. We argue that benchmarking a certain across these four scenarios provides a substantive test of performance. We study the performance of mutual information neural estimator (MINE), smoothed mutual information lower-bound estimator (SMILE), and directed information neural estimator (DINE) and provide insights into the performance of other methods as well. To summarize our benchmarking results, MINE provides the most reliable performance.
Commentary: Progressive multifocal leukoencephalopathy genetic risk variants for pharmacovigilance of immunosuppressant therapies

COPYRIGHT © 2023 Berger and Hartung. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Commentary: Progressive multifocal leukoencephalopathy genetic risk variants for pharmacovigilance of immunosuppressant therapies
Open clusters - II. Fundamental parameters of B stars in Collinder 223, Hogg 16, NGC 2645, NGC 3114, and NGC 6025

Context. The knowledge of accurate values of effective temperature, surface gravity, and luminosity of stars in open clusters is very important not only to derive cluster distances and ages but also to discuss the stellar structure and evolution. Unfortunately, stellar parameters are still very scarce. Aims. Our goal is to study five open clusters to derive stellar parameters of the B and Be star population and discuss the cluster properties. In a near future, we intend to gather a statistically relevant samples of Be stars to discuss their origin and evolution. Methods. We use the Barbier-Chalonge-Divan spectrophotometric system, based on the study of low-resolution spectra around the Balmer discontinuity, since it is independent of the interstellar and circumstellar extinction and provides accurate Hertzsprung-Russell diagrams and stellar parameters. Results. We determine stellar fundamental parameters, such as effective temperatures, surface gravities, spectral types, luminosity classes, absolute and bolometric magnitudes and colour gradient excesses of the stars in the field of Collinder 223, Hogg 16, NGC 2645, NGC 3114, and NGC 6025. Additional information, mainly masses and ages of cluster stellar populations, is obtained using stellar evolution models. In most cases, stellar fundamental parameters have been derived for the first time. We also discuss the derived cluster properties of reddening, age and distance. Conclusions. Collinder 223 cluster parameters are E(B − V) = 0.25 ± 0.03 mag and (mv − Mv)0 = 11.21 ± 0.25 mag. In Hogg 16, we clearly distinguish two groups of stars (Hogg 16a and Hogg 16b) with very different mean true distance moduli (8.91 ± 0.26 mag and 12.51 ± 0.38 mag), mean colour excesses (0.26 ± 0.03 mag and 0.63 ± 0.08 mag), and spectral types (B early-type and B late-/Atype stars, respectively). The farthest group could be merged with Collinder 272. NGC 2645 is a young cluster (<14 Myr) with E(B − V) = 0.58±0.05 mag and (mv − Mv)0 = 12.18±0.30 mag. The cluster parameters of NGC 3114 are E(B − V) = 0.10 ± 0.01 mag and (mv − Mv)0 = 9.20 ± 0.15 mag. This cluster presents an important population of Be star, but it is difficult to define the cluster membership of stars because of the high contamination by field stars or the possible overlapping with a nearby cluster. Finally, we derive the following cluster parameters of NGC 6025: E(B − V) = 0.34 ± 0.02 mag, (mv − Mv)0 = 9.25 ± 0.17 mag, and an age between 40 Myr and 69 Myr. In all the cases, new Be candidate stars are reported based on the appearance of a second Balmer discontinuity.
Impact of the Frequency and Type of Procedures Performed in Nuclear Medicine Units on the Expected Radiological Hazard

Nuclear medicine procedures play an important role in medical diagnostics and therapy. They are related to the use of ionizing radiation, which affects the radiological exposure of all of the persons involved in their performance. The goal of the study was to estimate the doses associated with the performance of various nuclear medicine procedures in order to optimize workload management. The analysis was performed for 158 myocardial perfusion scintigraphy procedures, 24 bone scintigraphies, 9 thyroid scintigraphies (6 with use of 131I and 3 with 99mTc), 5 parathyroid glands and 5 renal scintigraphies. In this evaluation, two possible locations of thermoluminescent detectors, used for measurements, were taken into consideration: in the control room and directly next to the patient. It was shown how the radiological exposure varies depending on the performed procedure. For high activity procedures, ambient dose equivalent registered in the control room reached the level over 50% of allowed dose limit. For example, ambient dose equivalent obtained in control room when performing bone scintigraphy only was 1.13 ± 0.3 mSv. It is 68% of calculated dose limit in the examined time span. It has been shown that risk associated with nuclear medicine procedures is influenced not only by the type of procedure, but also by the frequency of their performance and compliance with the ALARA principle. Myocardial perfusion scintigraphy accounted for 79% of all evaluated procedures. The use of radiation shielding reduced the obtained doses from 14.7 ± 2.1 mSv in patient’s vicinity to 1.47 ± 0.6 mSv behind the shielding. By comparing the results obtained for procedures and dose limits established by Polish Ministry of Health, it is possible to estimate what should be the optimal division of duties between staff, so that everyone receives similar doses.
Reconstructing three-dimensional vocal fold movement via stereo matching

Isao T. Tokuda , Masahiro Iwawaki, Ken-Ichi Sakakibara, Hiroshi Imagawa, Takaharu Nito, Tatsuya Yamasoba and Niro Tayama Department of Mechanical Engineering, Ritsumeikan University, 1–1–1 Nojihigashi, Kusatsu, 525–8577 Japan Dai Nippon Printing Co., Ltd., 1–1–1 Ichigayakaga, Tokyo, 162–8001 Japan Department of Communication Disorders, Health Sciences University of Hokkaido, 2–5 Ainosato, Kita-ku, Sapporo, 002–8072 Japan Department of Otolaryngology, University of Tokyo, 7–3–1 Hongo, Bunkyo-ku, Tokyo, 113–8655 Japan Department of Otolaryngology, Head and Neck Surgery, National Center for Global Health and Medicine, 1–21–1 Toyama, Shinjuku-ku, Tokyo, 162–8655 Japan
Emissions of second‐harmonic auroral kilometric radiation

The cyclotron maser theory of Wu and Lee (1979) is used in treating second-harmonic auroral kilometric radiation (AKR). Good agreement is obtained with the ISIS 1 observation reported by Benson (1982). It is found that when the ratio of the electron plasma frequency to the electron gyrofrequency is less than 0.3, the fundamental AKR prevails over the second-harmonic AKR. When the value of this ratio is greater than or approximately equal to 0.3, the fundamental AKR may become weaker than the second-harmonic AKR, and when it is greater than 0.3 the fundamental AKR may diminish. It is also found that the second harmonic AKR with frequencies below twice the electron gyro-frequency can propagate downward.