Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Domain-Agnostic and Domain-Adaptive Dementia Detection from Spoken Language

Health-related speech datasets are often small and varied in focus. This makes it difficult to leverage them to effectively support healthcare goals. Robust transfer of linguistic features across different datasets orbiting the same goal carries potential to address this concern. To test this hypothesis, we experiment with domain adaptation (DA) techniques on heterogeneous spoken language data to evaluate generalizability across diverse datasets for a common task: dementia detection. We find that adapted models exhibit better performance across conversational and task-oriented datasets. The feature-augmented DA method achieves a 22% increase in accuracy adapting from a conversational to task-specific dataset compared to a jointly trained baseline. This suggests promising capacity of these techniques to allow for productive use of disparate data for a complex spoken language healthcare task.
AnyTeleop: A General Vision-Based Dexterous Robot Arm-Hand Teleoperation System

Vision-based teleoperation offers the possibility to endow robots with human-level intelligence to physically interact with the environment, while only requiring low-cost camera sensors. However, current vision-based teleoperation systems are designed and engineered towards a particular robot model and deploy environment, which scales poorly as the pool of the robot models expands and the variety of the operating environment increases. In this paper, we propose AnyTeleop, a unified and general teleoperation system to support multiple different arms, hands, realities, and camera configurations within a single system. Although being designed to provide great flexibility to the choice of simulators and real hardware, our system can still achieve great performance. For real-world experiments, AnyTeleop can outperform a previous system that was designed for a specific robot hardware with a higher success rate, using the same robot. For teleoperation in simulation, AnyTeleop leads to better imitation learning performance, compared with a previous system that is particularly designed for that simulator. Project page: http://anyteleop.com/.
X-ray EM simulation tool for ptychography dataset construction

In this paper, we present an electromagnetic full-wave modeling framework, as a support EM tool providing data sets for X-ray ptychographic imaging. Modeling the entire scattering problem with Finite Element Method (FEM) tools is, in fact, a prohibitive task, because of the large area illuminated by the beam (due to the poor focusing power at these wavelengths) and the very small features to be imaged. To overcome this problem, the spectrum of the illumination beam is decomposed into a discrete set of plane waves. This allows reducing the electromagnetic modeling volume to the one enclosing the area to be imaged. The total scattered field is reconstructed by superimposing the solutions for each plane wave illumination.
Supersymmetric gauge dynamics : minimal supersymmetry

It is very di cult to fully or even partially answer these questions, in general. However, as we will discuss in this and subsequent lectures, for supersymmetric theories this is possible, sometime. Before entering into any details, there are a number of general remarks we want to make regarding the low energy behavior of field theories, more specifically asymptotically free gauge theories. This will help to better appreciate what comes next.
Forming Terrains by Glacial Erosion

We introduce the first solution for simulating the formation and evolution of glaciers, together with their attendant erosive effects, for periods covering the combination of glacial and inter-glacial cycles. Our efficient solution includes both a fast yet accurate deep learning-based estimation of highorder ice flows and a new, multi-scale advection scheme enabling us to account for the distinct time scales at which glaciers reach equilibrium compared to eroding the terrain. We combine the resulting glacial erosion model with finer-scale erosive phenomena to account for the transport of debris flowing from cliffs. This enables us to model the formation of terrain shapes not previously adequately modeled in Computer Graphics, ranging from U-shaped and hanging valleys to fjords and glacial lakes.
VectorVisor: A Binary Translation Scheme for Throughput-Oriented GPU Acceleration

Beyond conventional graphics applications, general-purpose GPU acceleration has had signiﬁcant impact on machine learning and scientiﬁc computing workloads. Yet, it has failed to see widespread use for server-side applications, which we argue is because GPU programming models offer a level of abstraction that is either too low-level (e.g., OpenCL, CUDA) or too high-level (e.g., TensorFlow, Halide), depending on the language. Not all applications ﬁt into either category, resulting in lost opportunities for GPU acceleration. We introduce VectorVisor, a vectorized binary translator that enables new opportunities for GPU acceleration by introducing a novel programming model for GPUs. With Vec-torVisor, many copies of the same server-side application are run concurrently on the GPU, where VectorVisor mimics the abstractions provided by CPU threads. To achieve this goal, we demonstrate how to (i) provide cross-platform support for system calls and recursion using continuations and (ii) make full use of the excess register ﬁle capacity and high memory bandwidth of GPUs. We then demonstrate that our binary translator is able to transparently accelerate certain classes of compute-bound workloads, gaining signiﬁcant improvements in throughput-per-dollar of up to 2.9 × compared to Intel x86-64 VMs in the cloud, and in some cases match the throughput-per-dollar of native CUDA baselines.
Optimization of enzyme-linked immunosorbent assay kit protocol to detect trimethylamine N-oxide levels in humans

The serum level of trimethylamine N-oxide (TMAO), a gut microbiota metabolite associated with diabetes, cancer, inflammatory and neurological diseases, can be determined by the micro-enzyme-linked immunosorbent assay (ELISA) method. However, we had problems obtaining accurate standard curves with the original kit protocol from Bioassay Technology Laboratory. We aimed to acquire proper standard curves by modifying the kit protocol in this study. First, we evaluated the human TMAO ELISA kit protocols and other human ELISA kits. We maintained the incubation times longer and increased the wash cycle. Moreover, we incubated the standards containing biotinylated antibody in the wells alone. Then we washed the wells and added streptavidin-HRP for the second incubation step. The data of original and modified ELISA kit protocol were analyzed with Student's t-test. We measured higher absorbance with lower standard solution concentration in experiments that followed the original kit protocol. After investigating other human TMAO ELISA kits, we noticed that the SunRed Biotechnology Company and MyBioSource companies suggested similar protocols to the Bioassay Technology Laboratory company. The ELK Biotechnology ELISA protocol was different from others. However, since there is no biotinylated antibody in the standard solution in the ELK biotechnology kit, we changed some steps by examining other human ELISA protocols from different companies. After performing the modified protocol, we found that the absorbances of the standard solutions were consistent with their concentrations, and we obtained an accurate standard curve. Higher R2 values and lower absolute difference of standard concentrations were found in the modified kit protocol. The human TMAO ELISA protocol, which we modified in this study, will enable researchers to obtain more reliable results and prevent them from failing time and resources.
Fast Electromigration Simulation for Chip Power Grids

Electromigration (EM) continues to be a serious concern for large chip design. We are focused on EM in the on-chip power grid, because grid lines carry mostly unidirectional currents and because of the very large sizes of modern grids. In the last few years, the capability to simulate EM has become available by simulating the stress in metal lines, which is the main cause of EM-induced failures. In this work, we have improved on the state of the art by developing a new EM simulator that is both faster and has better features than previous work. The work builds on recent results on the equivalence between stress and voltage, and introduces both a model reduction technique that provides up to 4.2X speedup, and a very efficient method for updating the grid currents during the void growth phase.
Analysing the impact of cloth fabrics on skin temperature during and after exercise using an FDM model

This study presents a 1D finite difference model that examines the influence of cloth fabrics on skin temperature during and after exercise, considering the complex nature of the human body and its susceptibility to infections and viruses. The aim is to design comfortable, high-quality fabrics that minimize potential issues caused by body temperature fluctuations. The model incorporates various physical, physiological, and thermal parameters of cloth to develop protective clothing suitable for exercise. Numerical results were compared to previous studies that analyzed skin temperature without clothing to validate the model’s accuracy. The findings indicate a minimal difference in skin temperature when wearing cotton and polyester cloth, with polyester fabric demonstrating superior characteristics such as stretchability, durability, and sweat resistance. The thermal information obtained from this model can be utilized to design appropriate clothing for diverse weather conditions, ultimately enhancing the performance and comfort of athletes, military personnel, and individuals engaged in physically demanding work. Additionally, the model can aid in developing thermal stress protocols for infection treatment and provide guidelines for physical activity to promote healthy living. This research contributes to the field of materials research by offering valuable insights into the design and development of protective clothing for exercise. By understanding the impact of cloth fabrics on skin temperature, advancements can be made in creating clothing that optimizes human comfort and performance.
Adaptive quantised H∞ observer-based output feedback control for non-linear systems with input and output quantisation

This study investigates the case of simultaneous input and output quantisation for a class of non-linear output feedback systems subject to uncertain non-linear dynamics and non-zero initial states. An adaptive quantised observer-based output feedback controller is designed to guarantee bounded stability and H∞ performance despite input and output quantisation. In comparison with the existing work, the main contributions of this study are that: (i) an important lemma is proposed to remove the matrix equality constraint used in many existing results, and three new design methods in strict terms of linear matrix inequality techniques are proposed; (ii) this study focuses on eliminating the impact of both input and output quantisation errors. Since the impact of input and output quantisation errors cannot be fully eliminated, the estimation error is proved to be ultimately bounded and to converge to a residual set; and (iii) an adaptive compensation term is constructed to compensate for the time-variant effects caused by non-linear dynamics and uncertain parameter vectors. Finally, two numerical examples are given to show the efficacy and advantages of the proposed methods.
Classification of the Attempted Arm and Hand Movements of Patients with Spinal Cord Injury Using Deep Learning Approach

The primary objective of this research is to improve the average classification performance for specific movements in patients with cervical spinal cord injury (SCI). The study utilizes a lowfrequency multi-class electroencephalography (EEG) dataset obtained from the Institute of Neural Engineering at Graz University of Technology. The research combines convolutional neural network (CNN) and long-short-term memory (LSTM) architectures to uncover strong neural correlations between temporal and spatial aspects of the EEG signals associated with attempted arm and hand movements. To achieve this, three different methods are used to select relevant features, and the proposed model's robustness against variations in the data is validated using 10-fold cross-validation (CV). Furthermore, the study explores the potential for subject-specific adaptation in an online paradigm, extending the proof-of-concept for classifying movement attempts. In summary, this research aims to make valuable contributions to the field of neuro-technology by developing EEG-controlled assistive devices using a generalized brain-computer interface (BCI) and deep learning (DL) framework. The focus is on capturing high-level spatiotemporal features and latent dependencies to enhance the performance and usability of EEG-based assistive technologies.
Comorbid Psychiatric Symptom Associated With Oppositional Defiant Symptom in Community School-Age Children

Objectives Oppositional defiant disorder (ODD) is often comorbid with other psychiatric disorders in childhood. This study aimed to investigate comorbid psychiatric symptoms and associated factors in elementary school children with symptoms of ODD. Methods The participants consisted of 205 mother-offspring pairs. Psychiatric symptoms were measured using the Diagnostic Predictive Scales and Korean Child Behavior Checklist. Psychiatric comorbid symptoms were compared between children with ODD symptom and those without ODD symptom. Multivariate logistic regression analysis was used to estimate the odds ratio of psychiatric symptom on ODD. Results ODD group had a significant association with internalizing and externalizing problem (p=0.001, p<0.001, respectively). ODD group were more comorbid with anxiety disorder, depressive disorder, attention-deficit/hyperactivity disorder, and conduct disorder. Among psychiatric disorder, generalized anxiety disorder (GAD) (adjusted odds ratio [AOR]=18.620, p<0.001) and conduct disorder (AOR=9.529, p=0.014) were associated with ODD symptom. Conclusion These findings suggest that children with ODD symptom had significantly higher rates of comorbid psychiatric symptoms. And GAD and conduct disorder are related to ODD symptom.
Difference of cardiac rehabilitation in the morning or evening on indexes of left ventricular and N-terminal pro-brain natriuretic peptide: a randomized controlled trial

Background: The present study aimed to evaluate the effects a cardiac rehabilitation program (CRP) performed in the morning or evening on left ventricular (LV) filling indices and the level of N-terminal fragment of pro-brain natriuretic peptide (NT-proBNP) in patients undergoing percutaneous coronary angioplasty during the COVID-19 pandemic. Methods: This was a randomized controlled single-blinded clinical trial. Ninety-six patients (mean age: 50.2 ± 8.1 years, 36 women and 44 men) with percutaneous coronary angioplasty were divided into two groups of intervention and control. In each group, the CRP was performed in either morning or evening. The CRP included walking and performing push-ups and sit-ups for 8 weeks. The participants of the control groups received routine care. The functional indices of LV, including LV ejection fraction, systolic function, and diastolic function (i.e. the transmitral flow), the E/e’ to left atrium peak strain ratio (as an estimation for LA stiffness), and NT-proBNP level were measured in all participants before starting and at the end of the CRP. Results: In the intervention group, the individuals performing the CRP in the evening had significantly higher E-wave (0.76±0.02 vs. 0.75±0.03; P=0.008), ejection fraction (52.5±5.64 vs. 55.5±3.59; P=0.011), and diastolic function velocity (E/A ratio, 1.03±0.06 vs. 1.05±0.03; P=0.014) and significantly lower A-wave (0.72±0.02 vs. 0.71±0.01; P=0.041), E/e’ ratio (6.74±0.29 vs. 6.51±0.38; P=0.038), and NT-proBNP level (2007.9±214.24 vs. 1933.9±253.13; P=0.045) compared with those performing the program in the morning. Conclusions: A supervised CRP performed in the evening compared with morning was more effective in improving LV functional indices. Therefore, such home-based interventions are recommended to be performed in the evening during the COVID-19 pandemic.
Dithiothreitol‐Measured Oxidative Potential of Reference Materials of Mineral Dust: Implications for the Toxicity of Mineral Dust Aerosols in the Atmosphere

Oxidative stress is a mechanism that might raise the toxicity of mineral dust aerosols. We evaluated the oxidative potential (OP) of four reference materials (RMs) of mineral dusts using dithiothreitol assay. The OP of the water‐soluble fraction of the dust RMs accounts for 40%–70% of the OP of the total fraction. The values of total and water‐soluble OP normalized by the surface area of insoluble particles showed agreement among the different dust RMs. The surface area of insoluble dust particles was therefore inferred as an important factor affecting the OP of mineral dust. Using the relation between total OP and the surface area of insoluble particles of the dust RMs, we estimated the total OPs of fine and coarse atmospheric mineral dust aerosols assuming a typical particle size distribution of Asian dust aerosols observed in Japan. Mass‐normalized total OPs were estimated at 44 and 23 pmol min−1 μg−1 for fine and coarse atmospheric mineral dust particles. They closely approximate the values observed for urban aerosols in Japan, which suggests that mineral dust plume advection can lead to a marked increase in human exposure to redox‐active aerosols, even far downwind from mineral dust source regions.
UNSTEADY HYDROMAGNETIC HEAT AND MASS TRANSFER NATURAL CONVECTION FLOW PAST AN EXPONENTIALLY ACCELERATED VERTICAL PLATE WITH HALL CURRENT AND ROTATION IN THE PRESENCE OF THERMAL AND MASS DIFFUSIONS

In the present analytical study, we have considered unsteady hydromagnetic heat and mass transfer natural convection flow of an electrically conducting, heat absorbing and chemically reacting fluid past an exponentially accelerated vertical plate in a uniform porous medium taking Hall current and rotation into account. The species concentration near the plate is considered to be varies linearly with time. Two particular cases for plate temperature are considered i.e. (i) plate temperature is uniform and (ii) plate temperature varies linearly with time and after some time it is maintained at uniform temperature. The coupled partial differential equations governing the fluid flow problem are solved analytically for fluid velocity, temperature and species concentration using Laplace transform method. To examine the physical characteristic of this problem the graphs for velocity, temperature, species concentration, skin friction, Nusselt number and Sherwood number distributions are computed and generated for various values of different pertinent flow parameters. It is observed that for small thermal diffusion, the free stream value of velocity and temperature are achieved nearer to the plate in comparison to that for large thermal diffusion.
Reusable nano-catalyzed green protocols for the synthesis of quinoxalines: an overview

Heterocyclic compounds are very widely distributed in nature and are essential for life activities. They play a vital role in the metabolism of all living cells, for example, vitamins and co-enzyme precursors thiamine, riboflavin etc. Quinoxalines are a class of N-heterocycles that are present in a variety of natural and synthetic compounds. The distinct pharmacological activities of quinoxalines have attracted medicinal chemists considerably over the past few decades. Quinoxaline-based compounds possess extensive potential applications as medicinal drugs, presently; more than fifteen drugs are available for the treatment of different diseases. Diverse synthetic protocols have been developed via a one-pot approach using efficient catalysts, reagents, and nano-composites/nanocatalysts etc. But the use of homogeneous and transition metal-based catalysts suffers some demerits such as low atom economy, recovery of catalysts, harsh reaction conditions, extended reaction period, expensive catalysts, the formation of by-products, and unsatisfactory yield of products as well as toxic solvents. These drawbacks have shifted the attention of chemists/researchers to develop green and efficient protocols for synthesizing quinoxaline derivatives. In this context, many efficient methods have been developed for the synthesis of quinoxalines using nanocatalysts or nanostructures. In this review, we have summarized the recent progress (till 2023) in the nano-catalyzed synthesis of quinoxalines using condensation of o-phenylenediamine with diketone/other reagents with plausible mechanistic details. With this review, we hope that some more efficient ways of synthesizing quinoxalines can be developed by synthetic chemists.
A randomized stepped wedge trial of an intensive combination approach to roll back the HIV epidemic in Nigerian adolescents: iCARE Nigeria treatment support protocol

Background Nigeria is one of six countries with half the global burden of youth living with HIV. Interventions to date have been inadequate as AIDS-related deaths in Nigeria’s youth have remained unchanged in recent years. The iCARE Nigeria HIV treatment support intervention, a combination of peer navigation and SMS text message medication reminders to promote viral suppression, demonstrated initial efficacy and feasibility in a pilot trial among youth living with HIV in Nigeria. This paper describes the study protocol for the large-scale trial of the intervention. Methods The iCARE Nigeria-Treatment study is a randomized stepped wedge trial of a combination (peer navigation and text message reminder) intervention, delivered to youth over a period of 48 weeks to promote viral suppression. Youth receiving HIV treatment at six clinical sites in the North Central and South Western regions of Nigeria were recruited for participation. Eligibility criteria included registration as a patient at participating clinics, aged 15–24 years, on antiretroviral therapy for at least three months, ability to understand and read English, Hausa, Pidgin English, or Yoruba, and intent to remain a patient at the study site during the study period. The six clinic sites were divided into three clusters and randomized to a sequence of control and intervention periods for comparison. The primary outcome is plasma HIV-1 viral load suppression, defined as viral load ≤ 200 copies/mL, in the intervention period versus the control period at 48 weeks of intervention. Discussion Evidence-based interventions to promote viral load suppression among youth in Nigeria are needed. This study will determine efficacy of a combination intervention (peer navigation and text message reminder) and collect data on potential implementation barriers and facilitators to inform scale-up if efficacy is confirmed. Trial registration ClinicalTrials.gov number, NCT 04950153, retrospectively registered July 6, 2021, https://clinicaltrials.gov/.