Miracle-dz/UniFAR-FTUs huggingface dataset:
Abstract P132: Anti-Müllerian Hormone Levels and Risk of Type 2 Diabetes in Women

Introduction: Given its role in ovarian follicle development, circulating anti-Müllerian hormone (AMH) is correlated with timing of menopause. Accordingly, women with higher AMH levels become menopausal at a higher age. Previous research suggests that a higher age at menopause is associated with a decreased risk of type 2 diabetes (T2D). In contrast, AMH levels are increased in women with polycystic ovary syndrome (PCOS), who have a higher risk of insulin resistance and T2D than women without PCOS. However, it is not clear yet whether AMH actually plays a role in the development of T2D. We aimed to investigate whether plasma AMH levels and age-related AMH trajectories are associated with risk of T2D in women. Hypothesis: Higher age-specific plasma AMH levels are associated with a decreased risk of T2D. Methods: We analyzed longitudinal data from 3104 female participants, aged 20-60 years at recruitment, in the population-based Doetinchem Cohort Study. In total, we analyzed 12460 plasma AMH measurements. We calculated age-specific AMH tertiles, to account for the strong AMH-age correlation. Cox Proportional hazards models adjusted for known risk factors for diabetes were used to assess the relation between age-specific AMH tertiles and T2D. We applied linear mixed models to compare age-related AMH trajectories between T2D cases and non-cases. Results: After a median follow-up of 20 years, 163 incident T2D cases were identified. Higher age-specific AMH levels were associated with a lower risk of T2D (hazard ratio (HR) T2vsT1 = 0.77, 95%CI: 0.53-1.11; HR T3vsT1 =0.62, 95%CI: 0.40-0.94; p for trend = 0.02). These findings were supported by predicted AMH trajectories, which suggested that plasma AMH levels were lower at younger ages and declined at a slower rate in women who were diagnosed with T2D compared to women who were not. However, differences in trajectories between T2D cases and non-cases were not statistically significant. Conclusions: We observed that women with higher age-specific AMH levels were at a lower risk of T2D. In addition, our longitudinal analyses may suggest that AMH is lower in women who develop T2D compared to women who do not. These findings are in line with previous studies that observed that a higher age at menopause was associated with a decreased risk of T2D.
Dynamic Multiconnectivity Based Joint Scheduling of eMBB and uRLLC in 5G Networks

Multiple use cases are the dominant feature for the fifth-generation mobile communication system (5G). Enhanced mobile broadband (eMBB) and ultrareliability low latency communication (uRLLC) are considered as two main scenarios. Different from the eMBB, which requires high data rate, the uRLLC requires extremely high reliability and very low latency. With multiple demands, the coexistence of eMBB and uRLLC will be an urgent challenge for the 5G networking strategy. In this article, a dynamic multiconnectivity (MC)-based joint scheduling framework with traffic steering for eMBB and uRLLC is proposed. The eMBB and uRLLC are specifically sliced with each other, which avoids the queue of uRLLC. A modified effective capacity (EC) model is proposed to measure the performance of our framework, which improves the throughput of eMBB under the guarantee of uRLLC latency. The proposed EC model turns the analytical target to the queue of users, different from the queue of base stations in traditional EC model. By a two-step optimization, the typical mixed integer nonlinear programming conducted by the EC model is decomposed into the integral programming and the nonlinear programming. The system-level simulation results show the proposed framework enhances the system throughput effectively while guaranteeing the uRLLC latency.
The Preparation and Characterization of Alginate–Chitosan Membranes as Solid Support for BTB and Urease Entrapment

A study of alginate-chitosan membrane synthesize was done. The membrane was prepared by mixing alginate hydrosol and chitosan hydrosol at mass ratio of 1:1 and pH of 5.28 approximately. Then it was applied for matrix immobilization of urease and bromothymol blue (BTB) by entrapment technique. The physical, chemical, thermal properties of alginate–chitosan membrane and their impact on immobilized urease activity were investigated. The polymer products were characterized by Fourier Transform Infrared Spectroscopy (FTIR), X-Ray Diffraction (XRD), Thermogravimetric Analysis (TGA), Differential Scanning Calorimetry (DSC), and Scanning Electron Microscopy (SEM). It’s showed that alginate-chitosan membrane was formed by electrostatic interaction. The obtained membran has better mechanical properties than original alginat and chitosan membranes. The immobilization urease into alginate-chitosan membrane retained the catalytic activity of the enzyme, as confirmed by color change of BTB indicator after membrane was immersed in substrate solution (urea). Therefore, alginate-chitosan membrane has good characteristics as matrix of enzyme immobilization.
Not All Sheep Are Equal

Knowing the factors that cause fluctua-tions in the density of large mammal populations is important for planning conservation and harvesting measures. As [Gaillard and colleagues][1] discuss in their informative Perspective, a remarkable 11-year study of a remote island population of Soay sheep ([ Coulson et al .][2]) reveals that the age and sex structure of the herd is a crucial factor in its response to ecological stresses, such as adverse weather conditions or increasing population density. [1]: http://www.sciencemag. org/cgi/content/full/292/5521/1499 [2]: http://www.sciencemag. org/cgi/content/short/292/5521/1528
A Smart Terrain Identification Technique Based on Electromyography, Ground Reaction Force, and Machine Learning for Lower Limb Rehabilitation

Automatic terrain classification in lower limb rehabilitation systems has gained worldwide attention. In this field, a simple system architecture and high classification accuracy are two desired attributes. In this article, a smart neuromuscular–mechanical fusion and machine learning-based terrain classification technique utilizing only two electromyography (EMG) sensors and two ground reaction force (GRF) sensors is reported for classifying three different terrains (downhill, level, and uphill). The EMG and GRF signals from ten healthy subjects were collected, preprocessed and segmented to obtain the EMG and GRF profiles in each stride, based on which twenty-one statistical features, including 9 GRF features and 12 EMG features, were extracted. A support vector machine (SVM) machine learning model is established and trained by the extracted EMG features, GRF features and the fusion of them, respectively. Several methods or statistical metrics were used to evaluate the goodness of the proposed technique, including a paired-t-test and Kruskal–Wallis test for correlation analysis of the selected features and ten-fold cross-validation accuracy, confusion matrix, sensitivity and specificity for the performance of the SVM model. The results show that the extracted features are highly correlated with the terrain changes and the fusion of the EMG and GRF features produces the highest accuracy of 96.8%. The presented technique allows simple system construction to achieve the precise detection of outcomes, potentially advancing the development of terrain classification techniques for rehabilitation.
Charging/discharging system based on zeta/sepic converter and a sliding mode controller for dc bus voltage regulation

This study proposes a charging/discharging system of energy storage devices (ESDs) to regulate the voltage of a dc bus. The proposed charging/discharging system is formed by a zeta/sepic converter and a sliding mode controller (SMC). The SMC uses a single sliding surface to regulate the dc bus voltage for the three operating modes of the charger/discharger converter (charging, discharging, and stand-by) and for ESD voltages lower, equal, or higher than the dc bus voltage. This study includes the stability analysis of the SMC and a design procedure of the SMC parameters. The charging/discharging system is simulated in PSIM, where the results confirm that the proposed SMC regulates the bus voltage in charging, discharging, and stand-by modes for different operating points of the system. Finally, the proposed charging/discharging system was constructed for demonstrating the feasibility of the solution for real applications. Moreover, the experimental results obtained in such a platform put into evidence the accuracy of the proposed SMC in regulating the bus voltage in all the possible conditions: bus voltage lower, equal or higher than ESD voltage, and during charge, discharge, and stand-by modes of the ESD.
Adversarial Text Image Super-Resolution using Sinkhorn Distance

Convolutional neural network-based methods have demonstrated promising results for single image super-resolution. However, existing methods usually approach the problem on natural scenes rather than texts, whereas the latter can provide more informative messages to viewers. In this paper, instead of using the Lp-norm as the supervision metric, we propose a novel one for better preserving semantic information in text images. Our new metric combines optimal transport in a primal form with Sinkhorn distance defined in an adversarially learned feature space. Since the Sinkhorn distance measures the similarity between two features in terms of both feature components and spatial locations, our metric can maintain the spatial structure of texts during network optimization. Experimental results on text datasets show that our method performs favorably against state-of-the-art approaches in both quantitative and qualitative evaluations. We will publish the code, datasets, and models upon acceptance.
Influence of coffee blends and roasting process on the antioxidant activity of coffee

The aim of this paper is to develop specification for the production of roasted coffee with improved nutritional quality. In this sense, the influence of different coffee blends and temperatures of roasting on the antioxidant activity of coffee was examined. Also, the composition of some bioactive components in the analyzed samples was determined. Two Arabica coffees of different quality and Robusta coffee were used for preparation of coffee blends. Experimentally determined green coffee blends B1, B2 and B3 were roasted at 167°C, 171°C and 175°C for 25 minutes in order to establish the effect of temperature roasting on the antioxidant activity and the content of bioactive components in blends. Based on results of DPPH and ABTS test, coffee blends B3 and B2, roasted at 171°C, had the highest (P<0.05) antioxidant activity. Those coffee blends had higher content of Robusta coffee than coffee blend B1. Results of this research can provide opportunities for development roasted ground coffee with improved nutritive quality, which could ensure competitiveness of producers in the target market. Keywords: coffee blends, antioxidant activity, nutritive quality
New Bubble Mitomycin C Application Technique for Haze Prevention following Customized Photorefractive Keratectomy

Present investigation deals with a pilot study in which a new technique for applying mitomycin C directly onto the ablated corneal surface in the form of an injector-administered bubble. Here, a technique was introduced and the observations made with this technique in this pilot study involving 125 patients who received wave front bilateral photorefractive keratectomy. Mitomycin C was administered using the common minisponge application technique in one eye and mitomycin C was administered using the new bubble technique in the other eye. Photorefractive keratectomy presentation was compared between the minisponge-treated and bubble-treated eyes. Visual parameters such as visual acuity, spherical refractive error and cylindrical refractive error were similar in eyes across the two treatments before and after wave front photorefractive keratectomy. None of the minisponge-treated or bubble-treated eyes developed clinically evident photorefractive keratectomy haze. Compared to the minisponge-treated eyes, bubbletreated eyes showed faster healing (3 d vs. 5 d for contact lens bandage removal) and faster visual recovery (≤5 d vs. 7-10 d). In conclusion, the new bubble technique for applying mitomycin C after wave front photorefractive keratectomy provided a safe, effective and time-saving alternative to the standard mini sponge mitomycin C application technique.
Experimental Testing of Bandstop Wave Filter to Mitigate Wave Reflections in Bilateral Teleoperation

A bilateral teleoperation system can become unstable in the presence of a modest time delay. However, the wave variable algorithm provides stable operation for any fixed time delay using passivity arguments. Unfortunately, the wave variable method produces wave reflection that can degrade teleoperation performance when a mismatched impedance exists between the master and slave robot. In this work, we develop a novel bandstop wave filter and experimentally verify that the technique can mitigate the effects of wave reflections in bilaterally teleoperated systems. We apply the bandstop wave filter in the wave domain and filtered the wave signal along the communication channel. We placed the bandstop wave filter in the master-to-slave robot path to alleviate lower frequency components of the reflected signal. With the lower frequency components reduced, wave reflections that degrade teleoperation performance were mitigated and we obtained a better transient response from the system. Results from our experiment show that the bandstop wave filter performed better by 67% when compared to the shaping wave filter respectively.
Mapping RO-Water Desalination System Powered by Standalone PV System for the Optimum Pressure and Energy Saving

Brackish water desalination is widely used to supply fresh water; reverse osmosis (RO) desalination units are considered as the most widespread technology used for this purpose due to the advantage of low power consumption. On the other hand, renewable energy resource integration into the power systems is an important trend, which serves energy supply especially in rural areas and non-stable power supply places. RO units powered from Photovoltaic (PV) systems are considered one of the reliable solutions in places where both water and energy demands are issues to be improved. In this research, the idea of storing energy in water salinity is introduced and discussed to reduce conventional battery storage banks. This concept depends on changing the pressure of the RO unit based on solar profiles to get high distilled water at high solar radiation times (high pressure applied) and low distilled water at low radiation times (low pressure values). Then, the produced water is mixed to get an acceptable salinity in the produced water. This research was applied on a small-scale RO testing unit with a pressure that changed from 40 to 60 bar, and, as a result, the water conductivity changed from 1.7 to 1.1 mS/cm. This was the base line to investigate the possibility of curtailing the battery storage system of the selected plant. Following the variable pressure scenarios, energy storage capacity was reduced by a factor of 20%.
Beamformed Feature for Learning-based Dual-channel Speech Separation

This paper deals with the problem of separating target speech signal from reverberant and noisy environment with dual microphones, where the target speech comes from a predefined direction range. First, we apply two differential beamformers with opposite directions to dual-channel inputs. Then, the power spectra of beamforming outputs are used as input feature of deep learning architecture. As input features, the beamformer outputs reflect not only spectral information but also directional information by their power level difference. And the calculation is very simple. Systematic evaluation and comparison show that the proposed system achieves very good separation performance and substantially outperforms related algorithms under very challenging environments where both interfering speaker, noise and reverberations are present.
Libri-Adapt: a New Speech Dataset for Unsupervised Domain Adaptation

This paper introduces a new dataset, Libri-Adapt, to support unsupervised domain adaptation research on speech recognition models. Built on top of the LibriSpeech corpus, Libri-Adapt contains 7200 hours of English speech recorded on mobile and embedded-scale microphones, and spans 72 different domains that are representative of the challenging practical scenarios encountered by ASR models. More specifically, Libri-Adapt facilitates the study of domain shifts in ASR models caused by a) different acoustic environments, b) variations in speaker accents, c) previously unexplored factors such as heterogeneity in the hardware and platform software of the microphones, and d) a combination of the aforementioned three shifts. We also provide a number of baseline results quantifying the impact of these domain shifts on the Mozilla DeepSpeech2 ASR model.
Pro-inflammatory properties of flavobacterium columnare cells and products on channel catfish (Ictalurus punctatus) neutrophils

Flavobacterium columnare and Edwardsiella ictaluri are the leading causes for losses in the aquaculture industry. The losses from the diseases caused by these pathogens total $2.5 million for catfish and $100 million for total aquaculture. F. columnare’s infection rates and stressors associated with outbreaks have been well-characterized, but the specific inflammatory responses of catfish neutrophils to the bacteria have not been studied. The objective, therefore, was to investigate the pro-inflammatory effects of the outer membrane proteins, extracellular products, and whole live bacteria, heat-killed (HK), and formalin-killed (FK) F. columnare and E. ictaluri to determine the effects on channel catfish phagocyte physiology. Phorbol myristate acetate-stimulated hydrogen peroxide production, inducible nitric oxide production, and phagocytosis of yeast particles, and the expression of CYP1A and lysozyme protein were measured in phagocytes after exposure to F. columnare and E. ictaluri bacteria or product. F. columnare-treated cells did not produce hydrogen peroxide or nitric oxide, nor was phagocytosis affected. E. ictaluri increased hydrogen peroxide production, nitric oxide production, and enhanced phagocytosis in phagocytes when given as ECPs, OMPs, HK bacteria, and FK bacteria. Both OMPs increased lysozyme protein expression, and ECPs and OMPs of both bacteria suppressed CYP1A expression.
Application of Video Recognition Technology in Sports Stunt Teaching

In recent years, with the rapid development of sports in our country, the national importance of sports is also increasing. In order to further improve the level of physical education in our country, we began to pay attention to the teaching of physical stunt. Sports stunt is difficult and dangerous. These characteristics determine that sports stunt teaching should improve teaching efficiency as much as possible. Therefore, the decomposition and identification of sports stunt is particularly important. The traditional sports stunt teaching can not identify the movements accurately, which brings some difficulties to the sports stunt teaching. Video recognition technology provides a new means for the teaching of physical stunt and greatly improves the teaching effect. This paper first gives an overview of video recognition and sports stunt, analyzes the advantages of video recognition technology in sports stunt teaching, and analyzes its feasibility based on data feature screening algorithm. It not only promotes the further integration of video recognition technology and teaching, but also deepens the research on this aspect.
ANALYSIS OF THE EFFECT OF DEBT STRUCTURE, FIRM SIZE, SALES GROWTH, AND TOTAL ASSET TURNOVER ON PROFITABILITY IN MANUFACTURING FIRMS LISTED ON THE INDONESIAN STOCK EXCHANGE

This research was conducted to test and analyze the influence of debt structure (short-term debt and long-term debt), company size, sales growth and Total turnover of assets to profitability in manufacturing companies Listed on the Indonesia Stock Exchange period 2016-2018. The type of research used by research is Causal Research. The population in this study amounted to 136 manufacturing companies listed on the Indonesia Stock exchange period of 2016 – 2018 ' with a sample number of 73 companies, selected by a purposive sampling method. Data processing uses multiple linear regression analysis techniques and residual tests with the smallest quadratic equations and hypothesis tests using F – statistic to test the simultaneous impact and T statistic to test the partial regression coefficient With a significant 5% level. The results of a partial study show that the debt structure (short-term debt) significantly affects profitability. Debt structure (long-term debt has significant negative impact on profitability. Company size and sales growth have significant positive effect on profitability. Total asset turnover has no significant positive impact on profitability. Simultaneously the debt structure (short-term debt and long-term debt), company size, sales growth and Total turnover of assets positively affect profitability.
Receptor and ion-channel trafficking : cell biology of ligand-gated and voltage-sensitive ion channels

ION CHANNELS 1. Voltage-gated sodium channels 2. The assembly and targeting of potassium channels 3. Assembly and targeting of voltage-dependent calcium channels ACETYLCHOLINE RECEPTORS 4. Targeting of acetylcholine receptors to the postsynaptic endplate of the nerve-muscle synapse 5. Assembly and targeting of neuronal nicotinic acetylcholine receptors AMINO ACID RECEPTORS 6. AMPA/kainate receptors 7. NMDA receptor targeting 8. Structure, assembly and targeting of glycine receptors 9. GABAA and GABAC receptors: regulation of assembly, localization, clustering and turnover
Sequential Joint Detection and Estimation with an Application to Joint Symbol Decoding and Noise Power Estimation

Jointly testing multiple hypotheses and estimating a random parameter of the underlying model is investigated in a sequential setup. The optimal scheme is designed such that it minimizes the expected number of used samples while keeping the probabilities of falsely rejecting a hypothesis and the mean-squared estimation errors below a pre-set level. The underlying constrained problem is first converted to an unconstrained problem and then reduced to an optimal stopping problem, whose solution is characterized by a non-linear Bellman equation. The optimal cost coefficients are obtained by exploiting a connection between the derivatives of the cost function and the detection/estimation errors. The paper concludes with a numerical example, namely solving the problem of sequential joint amplitudeshift keying symbol decoding and noise power estimation.
The influence of the visual surrounding environment in older adults and young adults’ cognitive performance: an alternative paradigm

ABSTRACT This study investigated how the characteristics of the visual surrounding environment influence older- and young-adults’ cognitive performance. Sixty-four older adults and 64 young adults performed four visual cognitive tasks (attention and memory tasks) in two independent sessions while being exposed to a high-load and a low-load visual surrounding environment. We expected that the high-load environment would hurt the older-adults performance due to typical difficulties in ignoring irrelevant stimuli, whereas no such effect would likely occur for the young-adults whose cognitive abilities are at their best. Overall, our results were consistent with our prediction in three tasks (go/no-go, choice reaction time, and Corsi block-tapping). Additionally, the older adults performed worse than the young adults in all tasks, thus confirming expected age-related differences. Our results are consistent with those obtained when distractors and targets are presented in the same display, now using a paradigm which locates the distractors in the surrounding environment.