Miracle-dz/UniFAR-FTUs huggingface dataset:
Neural dynamics underlying successful auditory short‐term memory performance

Listeners often operate in complex acoustic environments, consisting of many concurrent sounds. Accurately encoding and maintaining such auditory objects in short-term memory is crucial for communication and scene analysis. Yet, the neural underpinnings of successful auditory short-term memory (ASTM) performance are currently not well understood. To elucidate this issue, we presented a novel, challenging auditory delayed match-to-sample task while recording MEG. Human participants listened to “scenes” comprising 3 concurrent tone pip streams. The task was to indicate, after a delay, whether a probe stream was present in the just-heard scene. We present three key findings: First, behavioural performance revealed faster responses in correct vs. incorrect trials as well as in ‘probe present’ vs ‘probe absent’ trials, consistent with ASTM search. Second, successful compared to unsuccessful ASTM performance was associated with a significant enhancement of event-related fields and oscillatory activity in the theta, alpha, and beta frequency ranges. This extends previous findings of an overall increase of persistent activity during short-term memory performance. Third, using distributed source modelling, we found these effects to be confined mostly to sensory areas during encoding, presumably related to ASTM contents per-se. Parietal and frontal sources then became relevant during the maintenance stage, indicating that effective STM operation also relies on ongoing inhibitory processes suppressing task irrelevant information. In summary, our results deliver a detailed account of the neural patterns that differentiate successful from unsuccessful ASTM performance in the context of a complex, multi-object auditory scene.
Substrate displacement of CK1 C-termini regulates kinase specificity

CK1 kinases participate in many signaling pathways; how these enzymes are regulated is therefore of significant biological consequence. CK1s autophosphorylate their C-terminal non-catalytic tails, and eliminating these modifications increases substrate phosphorylation in vitro, suggesting that the autophosphorylated C-termini act as inhibitory pseudosubstrates. To test this prediction, we comprehensively identified the autophosphorylation sites on Schizosaccharomyces pombe Hhp1 and human CK1ε. Peptides corresponding to the C-termini interacted with the kinase domains only when phosphorylated, and phosphoablating mutations increased Hhp1 and CK1ε activity towards substrates. Interestingly, substrates competitively inhibited binding of the autophosphorylated tails to the substrate binding grooves. The presence or absence of tail autophosphorylation influenced the catalytic efficiency with which CK1s targeted different substrates, indicating that tails contribute to substrate specificity. Combining this mechanism with autophosphorylation of the T220 site in the catalytic domain, we propose a displacement specificity model to describe how autophosphorylation regulates substrate specificity for the CK1 family.
Structure-guided engineering of biased-agonism in the human niacin receptor via single amino acid substitution

The Hydroxycarboxylic acid receptor 2 (HCA2), also known as the niacin receptor or GPR109A, is a prototypical G protein-coupled receptor that plays a central role in the inhibition of lipolytic and atherogenic activities in our body. Interestingly, GPR109A activation also results in vasodilation that is linked to the side-effect of flushing associated with dyslipidemia drugs such as niacin. This receptor continues to be a key target for developing novel pharmacophores and lead compounds as potential therapeutics in dyslipidemia with minimized flushing response, however, the lack of structural insights into agonist-binding and receptor activation has limited the efforts. Here, we present five different cryo-EM structures of the GPR109A-G-protein complexes with the receptor bound to dyslipidemia drugs, niacin or acipimox, non-flushing agonists, MK6892 or GSK256073, and recently approved psoriasis drug, monomethyl fumarate (MMF). These structures allow us to visualize the binding mechanism of agonists with a conserved molecular interaction network, and elucidate the previously lacking molecular basis of receptor activation and transducer-coupling. Importantly, cellular pharmacology experiments, guided by the structural framework determined here, elucidate pathway-selective biased signaling elicited by the non-flushing agonists. Finally, taking lead from the structural insights, we successfully engineered receptor mutants via single amino acid substitutions that either fail to elicit agonist-induced transducer-coupling or exhibits G-protein signaling bias. Taken together, our study provides previously lacking structural framework to understand the agonist-binding and activation of GPR109A, and opens up the possibilities of structure-guided novel drug discovery targeting this therapeutically important receptor.
Are non-thermal, non-tumescent techniques more recommended? Endovenous treatment of saphenous veins reflux – methods and results overview and discussion

Chronic venous disease is one of the biggest health problems of today’s word. The consequences of the progression of venous disorders can lead to severe acute complications like superficial venous thrombosis, deep vein thrombosis, and pulmonary embolism, as well as chronic venous ulcers. The costs of the treatment of these conditions are still growing. The development of minimally invasive techniques has led to huge progress in the treatment of chronic venous disease. There are many modalities in the phlebological armamentarium, which can be chosen to eliminate axial reflux that is responsible for the progression of disease in the majority of cases. Various groups of techniques can be used: thermal and tumescent procedures, non-thermal tumescent options, or non-thermal non-tumescent treatment. In recent years special interest has been directed towards non-thermal, non-tumescent modalities, following suggestions that these procedures would create the same effects as thermal-tumescent ones, but are less invasive and give the patient a better outcome and quality of life. The review of recently published studies did not confirm this theory in general; however, some superiority of these options is present. Thus, further investigations and trials on this issue are highly recommended. Currently there is not enough strong evidence to promote non-thermal, non-tumescent techniques over other endovenous modalities.
IgG sialylation occurs via the FcRn-mediated recycling pathway in endothelial cells

IgG is a key mediator of immune responses throughout the human body, and the structure of the conserved glycan on the Fc region has been identified as a key inflammatory switch regulating its downstream effects. In particular, the absence of terminal sialic acid has been shown to increase the affinity of IgG for activating Fc receptors, cascading the inflammatory response in a variety of diseases and conditions. Previously, we have shown that IgG sialylation is mediated by B cell-extrinsic processes. Here, we show that the FcRn-mediated recycling pathway within endothelial cells is a critical modulator of IgG sialylation. Building a deeper understanding of how IgG sialylation is regulated will drive the development of novel therapeutics which dynamically tune IgG functionality in vivo. One-Sentence Summary Endothelial cells remodel IgG glycans within the FcRn-mediated recycling pathway.
Competitive Amplification Networks enable molecular pattern recognition with PCR

Gene expression has great potential to be used as a clinical diagnostic tool. However, despite the progress in identifying these gene expression signatures, clinical translation has been hampered by a lack of purpose-built. readily deployable testing platforms. We have developed Competitive Amplification Networks. CANs to enable analysis of an entire gene expression signature in a single PCR reaction. CANs consist of natural and synthetic amplicons that compete for shared primers during amplification, forming a reaction network that leverages the molecular machinery of PCR. These reaction components are tuned such that the final fluorescent signal from the assay is exactly calibrated to the conclusion of a statistical model. In essence, the reaction acts as a biological computer, simultaneously detecting the RNA targets, interpreting their level in the context of the gene expression signature, and aggregating their contributions to the final diagnosis. We illustrate the clinical validity of this technique, demonstrating perfect diagnostic agreement with the gold-standard approach of measuring each gene independently. Crucially, CAN assays are compatible with existing qPCR instruments and workflows. CANs hold the potential to enable rapid deployment and massive scalability of gene expression analysis to clinical laboratories around the world, in highly developed and low-resource J settings alike.
EEG Signal Processing to Control a Finger Rehabilitation System

This study aims to provide a comprehensive comparison for classification of Electroencephalography (EEG) signal based motor imagery, in time domain and time-frequency domain with different classifiers. We used EEG signals recorded while the subjects were imagining the movement of individual fingers, and analyzed the signals in time domain as well as using wavelet transform and Wigner transform. Our main goal is to compare different methods of feature extraction and classification as the important steps in the process of EEG signals for the Brain-Computer Interface (BCI) system. The experimental results indicate that the Support Vector Machine (SVM) method provides a better classification performance compared with other classification methods. Also, Linear Discriminative Analysis (LDA) performs as well as the SVM, after applying PCA for dimension reduction. The proposed scheme can be applied successfully to BCI systems where the amount of large data.
A new approach of kinematic geometry for error identification and compensation of industrial robots

A new approach for kinematic calibration of industrial robots, including the kinematic pair errors and the link errors, is developed in this paper based on the kinematic invariants. In most methods of kinematic calibration, the geometric errors of the robots are considered in forms of variations of the link parameters, while the kinematic pairs are assumed ideal. Due to the errors of mating surfaces in kinematic pairs, the fixed and moving axes of revolute pairs, or the fixed and moving guidelines of prismatic pairs, are separated, which can be concisely identified as the kinematic pair errors and the link errors by means of the kinematic pair errors model, including the self-adaption fitting of a ruled surface, or the spherical image curve fitting and the striction curve fitting. The approach is applied to the kinematic calibration of a SCARA robot. The discrete motion of each kinematic pair in the robot is completely measured by a coordinate measuring machine. Based on the global kinematic properties of the measured motion, the fixed and moving axes, or guidelines, of the kinematic pairs are identified, which are invariants unrelated to the positions of the measured reference points. The kinematic model of the robot is set up using the identified axes and guidelines. The results validate the approach developed has good efficiency and accuracy.
Double effects between reflection and edge-diffraction in NURBS-UTD method

ABSTRACT Second-order ray types in uniform geometrical theory of diffraction method are studied in this paper where non-uniform rational B-spline technique is introduced to construct targets. Reflection-edge diffraction ray type and edge diffraction-reflection ray type which are always appeared in multi-scatterer environments are investigated. Ray paths are found through numerical optimization based on Fermat’s principle. Ray fields carried by these kinds of rays are calculated based on single effected ray fields to discuss their contribution to the total ray fields. It can be seen that the consideration of reflection-edge diffraction effect and edge diffraction-reflection effect can improve the computational precision slightly in calculation of radiation patterns. Numerical results show the validation and the improvement.
Physics-Based Finite Element Simulation of the Dynamics of Soft Robots

Soft robots grew to prominence in large part because they promised a new and exciting means for engineers to develop robots that are both highly adaptable and safe for direct human interaction. However, despite showing substantial promise in this area, soft robots have not yet seen widespread adoption. Two major factors that have prevented the development of soft robots are the fundamental challenges of both the modeling and control of soft structures. While traditional robots enjoy a myriad of theoretical and computational tools for modeling and control, the options for soft robots are far more limited. In this work, we introduce a physics-based finite element simulation platform, Kraken, that can be used to accurately model the dynamic and oscillatory motions of soft robots. After a brief theoretical introduction to hyperelastic modeling and the finite element method, we show the utility of our approach by simulating the oscillations of a 1D hyperelastic actuator, the dynamics of a 2D hyperelastic pendulum, and a 3D spherical hyperelastic pendulum. We then demonstrate the accuracy of our approach by presenting the agreement of the simulated results with those obtained via physical experiments for three materials with different hyperelastic properties, with percent errors as low as 1%. Taken together, these results demonstrate that the aforementioned simulation platform is a critical step towards the fast and accurate simulation, prototyping, and control of soft robots.
Uncooled Tunable Laser Based on High-Density Integration of Distributed Feedback Semiconductor Lasers

Most types of tunable lasers are sensitive to the ambient temperature and require thermoelectric coolers (TECs) for temperature control. For conventional tunable laser modules, high power consumption of cooling is required for stabilizing the laser temperature and complex hermetic packages are normally used to avoid moisture condensation problems, which are expensive and difficult to manufacture. To overcome these drawbacks, we demonstrated an uncooled tunable laser via the monolithically integrated multi-wavelength distributed feedback (DFB) laser array based on the reconstruction-equivalent-chirp technique. Totally sixteen DFB semiconductor lasers are densely integrated with a 4-by-4 matrix laser array. To ensure the uncooled laser operates properly, the active material of the laser chip is designed to work at high temperatures without TEC cooling. Therefore, an uncooled wavelength-tuning range of 33.8 nm is achieved during the whole commercial operating temperature range from 0 °C to 70 °C.
Career Adaptability dan Self Perceived Employability pada Mahasiswa Magang

Academic ability is not enough, self perceived employability is also needed for students to be able to have sustainable jobs in accordance with the level of qualifications possessed. In achieving a dream job, an ability to understand self-competence is strongly needed in order to adapt to the world of work, it is called career adaptability. This study aims to find out the relationship between career adaptability and self perceived employability among internship students. The participants of this research are 83 internship students. This research instrument uses a career adaptability scale consisting of 30 items and a self-perceived employability scale consisting of 20 items. Based on the results of data analysis using the product-moment correlation method from Pearson, the value of the correlation coefficient (r) obtained is 0.663 with a significance level (p) 0.05, which is 0.000. The research hypothesis is accepted, which shows that there is a correlation between career adaptability and self-perceived employability among internship students. Kemampuan akademik yang diperoleh dari perguruan tinggi saja tidak cukup, dibutuhkan pula self perceived employability dalam diri mahasiswa untuk mampu memperoleh pekerjaan yang sesuai dengan tingkat kualifikasi yang dimiliki. Dalam mencapai pekerjaan tersebut dibutuhkan suatu kemampuan untuk memahami kompetensi diri supaya bisa beradaptasi dengan dunia kerja yaitu career adaptability. Ketika mahasiswa siap dengan tugas dalam pekerjaannya, maka mahasiswa akan siap menghadapi segala tuntutan peran. Ketika mahasiswa siap menghadapi segala tuntutan pekerjaan, maka mahasiswa tersebut juga akan lebih mampu untuk mendapatkan pekerjaan yang diinginkan nantinya. Penelitian ini bertujuan untuk mengetahui hubungan antara career adaptability dengan self perceived employability pada mahasiswa magang di Startup X. Subjek dalam penelitian ini sebanyak 83 mahasiswa magang di Startup X. Penelitian ini menggunakan skala career adaptability terdiri dari 30 aitem dan self perceived employability terdiri dari 20 aitem. Berdasarkan hasil analisis data dengan menggunakan metode korelasi product-moment dari Pearson, nilai koefisien korelasi (r) yang didapatkan yaitu 0,663 dengan taraf signifikansi (p) 0,05 yaitu sebesar 0,000. Hipotesis penelitian diterima yaitu terdapat hubungan antara career adaptability dengan self perceived employability pada mahasiswa magang.
Nighttime Pedestrian Detection Based on a Fusion of Visual Information and Millimeter-Wave Radar

A target detection algorithm based on the fusion of vision sensors and millimeter wave radar data can effectively improve the safety of self-driving vehicles. However, a single sensor cannot obtain comprehensive category status information on the target in the nighttime environment. To improve pedestrian detection in nighttime traffic scenarios, this paper proposes a nighttime pedestrian detection method based on the fusion of infrared vision information and millimeter wave (MMW) radar data. The lateral localization and category features of the target are obtained using the improved YOLOv5 deep learning algorithm, the distance and velocity information of the target is obtained by preprocessing the MMW radar acquisition data, the pedestrian target is tracked by using the extended Kalman filter for MMW radar detection, the projection of the valid radar target point on the Infrared Radiatio (IR) image is completed according to the spatiotemporal fusion, and then the correlation gate method is used to correlate the data, and the visual information is inherited to the radar points to get the target multimodal information, and the success associated valid target sequences are weighted to obtain the accurate target position. Finally, a decision-level fusion algorithm framework is proposed to complete the output of pedestrian multimodal information in nighttime traffic scenes. Theoretical analysis and experimental results show that the accuracy and robustness of this method for nighttime pedestrian recognition are better than those of a single sensor.
A Selection of 14 Tetrameric Microsatellite Markers for Genetic Investigations in Fallow Deer (Dama dama)

Simple Summary Monitoring and maintaining genetic diversity is essential for the conservation of most species, including fallow deer. Various markers can be tested to estimate genetic diversity. For this purpose, microsatellites consisting of four-base-pair repetitive units are highly recommended due to their polymorphisms and comparable and reliable detection during analyses. In this study, nearly one hundred tetrameric microsatellites were collected from nine other deer species, which were tested on twenty individuals from five Hungarian fallow deer populations. As a result, 14 polymorphic markers were selected for the investigation panel, which fills a gap in the field of experts dealing with fallow deer genetics. Abstract The fallow deer (Dama dama) represents significant game management value globally, and human activities are significantly impacting the species. Besides the positive effects, these activities can threaten its existence, health, and value. The aim of the authors was to develop a tetranucleotide microsatellite panel that could be clearly interpreted and used for genetic testing of fallow deer. Such a panel did not exist until now and could be particularly useful in the field of conservation genetics and forensics. A total of 99 tetrameric microsatellites, originally designed for related deer species, were tested on 20 fallow deer individuals from five Hungarian sampling areas. Original and newly designed primers were used to amplify the microsatellite regions using previously published or optimized PCR protocols. The lengths and sequences of specific amplicons were detected using capillary electrophoresis, and the rate of polymorphism was determined. Altogether, 80 markers provided PCR products of adequate quality and quantity. Among them, 15 markers proved to be polymorphic (2–5 alleles/locus), and 14 tetrameric markers were selected for further analysis. Statistical calculations showed that the selected polymorphic microsatellites can potentially enable key individualization in many areas of wildlife and population genetics, thus protecting the species.
Evaluation of Exacerbation and Symptom-Free Time in Patients with COPD

Abstract In clinical practice, clinicians mainly focus on Chronic Obstructive Pulmonary Disease (COPD) exacerbations and symptoms, while patients may prefer to evaluate periods free of COPD exacerbations and deteriorated symptoms. The latter would suit the positive health approach that centralizes people and their beliefs. We aimed to identify patient characteristics and health outcomes relating to: 1) COPD exacerbation-free days; 2) days with no more symptoms than usual; and 3) combined COPD exacerbation and comorbid flare-up-free days (i.e. chronic heart failure, anxiety, depression flare-ups) using negative binomial regression analyzes. Data were obtained from two self-management intervention trials including COPD patients with and without comorbidities. 313 patients (mean age 66.0 years, 63.6% male, 68.7% comorbidity) were included. Better baseline chronic respiratory questionnaire (CRQ) fatigue (incidence rate ratio (IRR) = 1.03 (95% CI 1.01–1.05), p = 0.02) and mastery scores (IRR = 1.03 (95% CI 1.00–1.06), p = 0.04) and fewer courses of antibiotics (IRR = 0.95 (95% CI 0.94–0.96), p < 0.01) were related to more COPD exacerbation-free days. Additionally, better baseline CRQ fatigue (IRR = 1.05 (95% CI 1.00–1.10), p = 0.04) and mastery scores (IRR = 1.06 (95% CI 1.00–1.12), p = 0.04), fewer courses of antibiotics (IRR = 0.94 (95% CI 0.91–0.96), p < 0.01), and improved CRQ dyspnea scores over 12 months of follow-up (IRR = 1.07 (95% CI 1.01–1.12), p < 0.01) were correlated to more days free of deteriorated symptoms. Less baseline dyspnea (modified Medical Research Council score) (IRR = 0.95 (95% CI 0.92–0.98), p < 0.01) and fewer courses of antibiotics (IRR = 0.94 (95% CI 0.93–0.95), p < 0.01) were associated with more combined COPD exacerbation and comorbid flare-up-free days. Healthcare professionals should be aware that less fatigue and better mastering of COPD relate to more exacerbation and symptom-free time in COPD patients.
Oscillation of Even Order Nonlinear Functional Dynamic Equations on Time Scales

The paper investigates the oscillation of even order nonlinear functional dynamic equation of the form [ φ(t) ( x n−1 (t) )α]∆ + q(t) [ x(τ(t)) ]β = 0 on [t0,∞)T with supT = ∞ and limt→∞ τ(t) = ∞. We establish several new oscillation criteria for the equation by employing Kiguradze’s lemma, the Taylor monomials on time scales and a generalized Riccati technique. The obtained results extend and supplement certain known results in the literature. Some interesting examples are shown to illustrate our main results.