Miracle-dz/UniFAR-FTUs huggingface dataset:
A blended neurostimulation protocol to delineate cortico-muscular and spino-muscular dynamics following neuroplastic adaptation

In this paper we propose a novel neurostimulation protocol that provides an intervention-based assessment to distinguish the contributions of different motor control networks in the cortico-spinal system. Specifically, we use a combination of non-invasive brain stimulation and neuromuscular stimulation to probe neuromuscular system behavior with targeted impulse-response system identification. In this protocol, we use an in-house developed human-machine interface (HMI) for an isotonic wrist movement task, where the user controls a cursor on-screen. During the task, we generate unique motor evoked potentials based on triggered cortical or spinal level perturbations. Externally applied brain-level perturbations are triggered through TMS to cause wrist flexion/extension during the volitional task. The resultant contraction output and related reflex responses are measured by the HMI. These movements also include neuromodulation in the excitability of the brain-muscle pathway via transcranial direct current stimulation. Colloquially, spinal-level perturbations are triggered through skin-surface neuromuscular stimulation of the wrist muscles. The resultant brain-muscle and spinal-muscle pathways perturbed by the TMS and NMES, respectively, demonstrate temporal and spatial differences as manifested through the human-machine interface. This then provides a template to measure the specific neural outcomes of the movement tasks, and in decoding differences in the contribution of cortical- (long-latency) and spinal-level (short-latency) motor control. This protocol is part of the development of a diagnostic tool that can be used to better understand how interaction between cortical and spinal motor centers changes with learning, or injury such as that experienced following stroke.
Advancing the 3Rs: innovation, implementation, ethics and society

The 3Rs principle of replacing, reducing and refining the use of animals in science has been gaining widespread support in the international research community and appears in transnational legislation such as the European Directive 2010/63/EU, a number of national legislative frameworks like in Switzerland and the UK, and other rules and guidance in place in countries around the world. At the same time, progress in technical and biomedical research, along with the changing status of animals in many societies, challenges the view of the 3Rs principle as a sufficient and effective approach to the moral challenges set by animal use in research. Given this growing awareness of our moral responsibilities to animals, the aim of this paper is to address the question: Can the 3Rs, as a policy instrument for science and research, still guide the morally acceptable use of animals for scientific purposes, and if so, how? The fact that the increased availability of alternatives to animal models has not correlated inversely with a decrease in the number of animals used in research has led to public and political calls for more radical action. However, a focus on the simple measure of total animal numbers distracts from the need for a more nuanced understanding of how the 3Rs principle can have a genuine influence as a guiding instrument in research and testing. Hence, we focus on three core dimensions of the 3Rs in contemporary research: (1) What scientific innovations are needed to advance the goals of the 3Rs? (2) What can be done to facilitate the implementation of existing and new 3R methods? (3) Do the 3Rs still offer an adequate ethical framework given the increasing social awareness of animal needs and human moral responsibilities? By answering these questions, we will identify core perspectives in the debate over the advancement of the 3Rs.
STATISTICAL APPROXIMATIONS OF DATABASE QUERIES WITH CONFIDENCE INTERVALS

of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy STATISTICAL APPROXIMATIONS OF DATABASE QUERIES WITH CONFIDENCE INTERVALS By Lixia Chen December 2011 Chair: Alin Dobra Major: Computer Engineering Explosive data growth in databases presents significant challenges for fast query processing. Computation of exact values of complex queries over large databases can take a long time due to the large volume of data they need to access. Approximate query processing provides an essential solution to this problem. Versatile approximation methods are available to be used in databases nowadays. In order to evaluate the effectiveness of these approximations, it is desirable to provide confidence intervals of estimators; the confidence intervals effectivelly provide error guarantees of estimated values. The focus of this dissertation is approximating database queries and providing corresponding confidence intervals. We first revisit the approximation method histograms as used in traditional databases and interpret as a statistical method. Then we estimate aggregates over probabilistic databases and provide efficient algorithms to compute them. The traditional assumption for interpreting histograms and justifying approximate query processing methods based on them is that all elements in a bucket have the same frequency – this is called uniform distribution assumption. We show that a significantly less restrictive statistical assumption – the elements within a bucket are randomly arranged even though they might have different frequencies – leads to identical formulas for approximating aggregate queries using histograms. We analyze, under this assumption, the behaviors of the both unidimensional and multidimensional
Functional Polymorphisms of the Arachidonic Acid Pathway Associate with Risks and Clinical Outcomes of Allergic Diseases

Introduction: The arachidonic acid (AA) pathway plays a crucial role in allergic inflammatory diseases; however, the functional roles of allergy-associated single nucleotide polymorphisms (SNPs) in this pathway remain incompletely illustrated. Methods: This study belongs to a part of an ongoing Singapore/Malaysia cross-sectional genetics and epidemiological study (SMCSGES). We performed population genotyping on n = 2,880 individuals from the SMCSGES cohort to assess the associations of SNPs in the AA pathway genes with asthma and allergic rhinitis (AR). Spirometry assessments were performed to identify associations between SNPs and lung function among n = 74 pediatric asthmatic patients from the same cohort. Allergy-associated SNPs were functionally characterized using in vitro promoter luciferase assay, along with DNA methylome and transcriptome data of n = 237 peripheral blood mononuclear cell (PBMC) samples collected from a subset of the SMCSGES cohort. Results: Genetic association analysis showed 5 tag-SNPs from 4 AA pathway genes were significantly associated with asthma (rs689466 at COX2, rs35744894 at hematopoietic PGD2 synthase (HPGDS), rs11097414 at HPGDS, rs7167 at CRTH2, and rs5758 at TBXA2R, p < 0.05), whereas 3 tag-SNPs from HPGDS (rs35744894, rs11097414, and rs11097411) and 2 tag-SNPs from PTGDR (rs8019916 and rs41312470) were significantly associated with AR (p < 0.05). The asthma-associated rs689466 regulates COX2 promoter activity and associates with COX2 mRNA expression in PBMC. The allergy-associated rs1344612 was significantly associated with poorer lung function, increased risks of asthma and AR, and increased HPGDS promoter activity. The allergy-associated rs8019916 regulates PTGDR promoter activity and DNA methylation levels of cg23022053 and cg18369034 in PBMC. The asthma-associated rs7167 affects CRTH2 expression by regulating the methylation level of cg19192256 in PBMC. Conclusions: The present study identified multiple allergy-associated SNPs that modulate the transcript expressions of key genes in the AA pathway. The development of a “personalized medicine” approach with consideration of genetic influences on the AA pathway may hopefully result in efficacious strategies to manage and treat allergic diseases.
Improved accuracy for the Helmholtz equation in unbounded domains

Based on properties of the Helmholtz equation, we derive a new equation for an auxiliary variable. This reduces much of the oscillations of the solution leading to more accurate numerical approximations to the original unknown. Computations confirm the improved accuracy of the new models in both two and three dimensions. This also improves the accuracy when one wants the solution at neighbouring wavenumbers by using an expansion in k. We examine the accuracy for both waveguide and scattering problems as a function of k, h and the forcing mode l. The use of local absorbing boundary conditions is also examined as well as the location of the outer surface as functions of k. Connections with parabolic approximations are analysed. Copyright © 2004 John Wiley & Sons, Ltd.
The Material Point Method for the Physics-Based Simulation of Solids and Fluids

Author(s): Jiang, Chenfanfu | Advisor(s): Terzopoulos, Demetri | Abstract: Simulating fluids and solid materials undergoing large deformation remains an important and challenging problem in Computer Graphics. The dynamics of these materials usually involve dramatic topological changes and therefore require sophisticated numerical approaches to achieve sufficient accuracy and visual realism. This dissertation focuses on the Material Point Method (MPM) for simulating solids and fluids for use in computer animation, and it makes four major contributions: First, we introduce new MPM for simulating viscoelastic fluids, foams and sponges. Our second contribution is to introduce a novel technique designed to retain the stability of the original PIC, without suffering from the noise and instability of FLIP. Our third contribution is to introduce a novel material point method for heat transport, melting and solidifying materials. Our fourth contribution is to show that recasting the backward Euler method as a minimization problem allows Newton's method to be stabilized by standard optimization techniqueswith some novel improvements of our own.
Microtubule stabilization targeting regenerative chondrocyte cluster for cartilage regeneration

Purpose: Chondrocytes (CHs) in cartilage undergo several detrimental events during the development of osteoarthritis (OA). However, the mechanism underlying CHs regeneration involved in pathogenesis is largely unknown. The aim of this study was to explore the underlying mechanism of regeneration of CHs involved in the pathological condition and the potential therapeutic strategies of cartilage repair. Methods and Materials: CHs were isolated from human cartilage in different OA stages and the high-resolution cellular architecture of human osteoarthritis was examined by applying single-cell RNA sequencing. The analysis of gene differential expression and gene set enrichment was utilized to reveal the relationship of cartilage regeneration and microtubule stabilization. Microtubule destabilizer (nocodazole) and microtubule stabilizer (docetaxel) treated-human primary CHs and rats cartilage defect model were used to investing the effects and downstream signaling pathway of microtubule stabilization on cartilage regeneration. Results: CHs subpopulations were identified on the basis of their gene markers and the data indicated an imbalance caused by an increase in the degeneration and disruption of CHs regeneration in OA samples. Interestingly, the CHs subpopulation namely CHI3L1+ CHs, was characterized by the cell regenerative capacity, stem cell potency and the activated microtubule (MT) process. Furthermore, the data indicated that MT stabilization was effective in promoting cartilage regeneration in rats with cartilage injury model by inhibiting YAP activity. Conclusion: These findings lead to a new understanding of CHs regeneration in the OA pathophysiology context and suggest that MT stabilization is a promising therapeutic target for OA and cartilage injury.
The landscape of abnormal pathway activation confers COVID-19 patients' molecular sequelae earlier than clinical phenotype

Rationale: The 2019 coronavirus disease (COVID-19) pandemic poses a significant threat to human health. After SARS-CoV-2 infection, major clinical concerns are organ damage and possible sequelae. Methods: In this study, we analyzed serum multi-omics data based on population-level, including healthy cohort, non-COVID-19 and COVID-19 covered different severity cohorts. We applied the pseudo-SpatioTemporal Consistency Alignment (pST-CA) strategy to correct for individualized disease course differences, and developed pseudo-deterioration timeline model and pseudo-recovery timeline model based on the "severe index" and "course index". Further, we comprehensively analyzed and discussed the dynamic damage signaling in COVID-19 deterioration and/or recovery, as well as the potential risk of sequelae. Results: The deterioration and course models based on the pST-CA strategy can effectively map the activation of blood molecular signals on cellular, pathway, functional and disease phenotypes in COVID-19 deterioration and throughout the disease course. The models revealed the neurological, cardiovascular, and hepatic toxicity present in SARS-CoV-2. The abundance of differentially expressed proteins and the activity of upstream regulators were comprehensively analyzed and evaluated to predict possible target drugs for SARS-CoV-2. On molecular docking simulation analysis, it was further demonstrated that blocking CEACAM1 is a potential therapeutic target for SARS-CoV-2. Conclusions: Clinically, the risk of organ failure and death in COVID-19 patients rises with increasing number of infections. Individualized sequelae prediction for patients and assessment of individualized intervenable targets and available drugs in combination with the upstream regulator analysis results are of great clinical value.
Influence of Coronary Artery Bypass Grafts on Blood Aminothiols in Patients with Coronary Artery Disease

Coronary artery disease (CAD) and the coronary artery bypass graft (CABG) are associated with a decreased blood glutathione (bGSH) level. Since GSH metabolism is closely related to other aminothiols (homocysteine and cysteine) and glucose, the aim of this study was to reveal the associations of bGSH with glucose and plasma aminothiols in CAD patients (N = 35) before CABG and in the early postoperative period. Forty-three volunteers with no history of cardiovascular disease formed the control group. bGSH and its redox status were significantly lower in CAD patients at admission. CABG had no significant effect on these parameters, with the exception of an increase in the bGSH/hemoglobin ratio. At admission, CAD patients were characterized by negative associations of homocysteine and cysteine with bGSH. All these associations disappeared after CABG. An association was found between an increase in oxidized GSH in the blood in the postoperative period and fasting glucose levels. Thus, CAD is associated with the depletion of the intracellular pool and the redox status of bGSH, in which hyperhomocysteinemia and a decrease in the bioavailability of the extracellular pool of cysteine play a role. The present study indicates that CABG causes disruptions in aminothiol metabolism and induces the synthesis of bGSH. Moreover, glucose becomes an important factor in the dysregulation of GSH metabolism in CABG.
Compact model of the Vertical Slit Field-Effect Transistor (VeSFET)

This paper presents a compact model of the Vertical-Slit Field-Effect Transistor (VeSFET), a novel junctionless device based on majority-carrier flow, featuring two symmetric, independent gates. The VeSFET is the crucial component Vertical Slit Transistor-based ICs (VeSTICs) – a novel class of circuits, proposed by W. Maly [1 – 3], characterized by very small static power consumption as well as high density and extreme regularity of the layout.
Potential Induced Degradation in Photovoltaic Modules: A Review of the Latest Research and Developments

Photovoltaic (PV) technology plays a crucial role in the transition towards a low-carbon energy system, but the potential-induced degradation (PID) phenomenon can significantly impact the performance and lifespan of PV modules. PID occurs when a high voltage potential difference exists between the module and ground, leading to ion migration and the formation of conductive paths. This results in reduced power output and poses a challenge for PV systems. Research and development efforts have focused on the use of new materials, designs, and mitigation strategies to prevent or mitigate PID. Materials such as conductive polymers, anti-reflective coatings, and specialized coatings have been developed, along with mitigation strategies such as bypass diodes and DC-DC converters. Understanding the various factors that contribute to PID, such as temperature and humidity, is critical for the development of effective approaches to prevent and mitigate this issue. This review aims to provide an overview of the latest research and developments in the field of PID in PV modules, highlighting the materials, designs, and strategies that have been developed to address this issue. We emphasize the importance of PID research and development in the context of the global effort to combat climate change. By improving the performance and reliability of PV systems, we can increase their contribution to the transition towards a low-carbon energy system.
Even period quaternary sequence pair with three-level autocorrelation

A new form of discrete signals,the quaternary sequence pair with three-level autocorrelation,is proposed.The quaternary sequence pairs with even period is studied.The maximum out-of-phase autocorrelation is at least two is gotten,which has the character of any quaternary sequence pairs with even period and three-level autocorrelation.A construction of quaternary sequence pairs with even period and the autocorrelation value of {0,-2} is presented.And the balanced quaternary sequence pairs with optimal autocorrelation values can be obtained if the used pseudorandom binary sequence pairs have the optimum properties of balance.
Optimization of a Gas Chromatography–Mass Spectrometry (GCMS) Method for Detecting 28 Allergens in Various Personal Care Products

Fragrances are among the most common ingredients in cosmetics products. Importantly, exposure to fragrances on a daily basis might pose a health risk, leading to serious effects, such as contact dermatitis or contact eczema. Annex III of the European Union Directive on Cosmetic Products and Gulf Cooperation Council standardization organization (GSO) introduced restrictions for 26 allergens, with their concentrations exceeding 0.001% and 0.01% in leave-on products and rinse-off products, respectively. In the current study, we aimed to expand the scope of the analytical method (EN16274, 2012) to include a broader range of matrices. The optimized method was validated by examining a statistical approach, including selectivity, linearity, accuracy, precision, and measurement of uncertainty. Successfully, the validated data demonstrated acceptable limits according to validation protocols, with linearity showing satisfactory regression of r > 0.995. During method performance assessment, samples were extracted using ultrasound-assisted extraction to extract allergens that yielded relatively high recoveries. Studies on matrices spiked with allergens at different levels showed insignificant bias as an average of 0.07 µg/g. Method performance was assessed by analyzing 140 cosmetics samples, including perfumes, deodorants, aftershave, baby wet wipes, shampoos, lotions, and lip care products. The new optimized analytical method is believed to be a valuable analytical tool to be used in surveillance studies covering a wide range of cosmetic matrices.
Applications of moving frame in object recognition

It was presented that invariant,dierential invariants of Euclidean curves in plane,namely,curvature and its derivatives(include higher order derivatives) with respect to the arc length,were obtained by theclassical method of construction of moving frames,armed with Fels-Olver equivariant moving frame theory developed by Mark Fels and Peter J.Olver. The Euclidean signature curves of curves were constructed in terms of Euclidean differential invariants.The signature curves were generally applied to the problems of object recognition,visual tracking and symmetry detection.Moreover,Cartan's equivalence theorem was a fundamental theorem in signature curves.Based on the joint invariants,noise resistant was numerically approximated for signature curves,and some examples were used to indicate the efficiencies of the differential invariant method while dealing with computer vision problems.
The impact of Different Rotation Patterns on the Composite Estimator

One of key elements in the repeated sample design is the rotation pattern. High sampling overlap between periods reduces the sampling variance of estimates of period change and the degree of sample overlap between any two periods is determined by the rotation pattern design. Composite estimation is used in the rotation pattern design to reduce the variance of estimators. The aim of the paper is to determine an optimal rotation pattern by comparing the effect of different rotation patterns in terms of the variances, biases and mean square errors used as the performance criteria of monthly, month-to-month and year-to-year change of the composite estimators. The analysis based on the CPS data on different rotation patterns under study indicates that the variance, bias and the mean square error of the composite estimate under the 6-6-6 rotation pattern for all levels are lesser with small differences than those of estimates under any other rotation pattern. These differences compared to those under the 4-84 are so small that they do not strongly support the rotation pattern 6-6-6 performing better than any other specified rotation pattern, particularly, no better than the current 4-8-4 rotation pattern. This leads that 4-8-4 rotation pattern is preferable and can be retained.
Fast topology optimization for transient mechanical problems

Topology optimization is increasingly used as a design tool in engineering. Within structural mechanics, most applications focus on statics. An extension to time-domain (transient) dynamics will have many useful applications, but this is currently hindered by high computational costs. The goal of this research is to reduce these costs by applying model order reduction. In model order reduction, the full coordinates of a system are approximated by a much smaller number of reduced coordinates and associated basis vectors. A few options for these vectors will be discussed. It is shown that using load-based methods results in high accuracy, especially the Ritz vector method. In the total optimization this leads to significant reduction of both CPU-time and memory requirements.
Stability of Stratified Couple-Stress Dusty Fluid in the Presence of Magnetic Field through Porous Medium

The combined effect of magnetic field and dust particles on the stability of a stratified couplestress fluid through a porous medium is considered. For stable stratification, the system is found to be stable for disturbances of all wave numbers. The magnetic field succeeds in stabilizing the potentially unstable stratifications for a certain wave-number range which were unstable in the absence of the magnetic field. Discussions of oscillatory and non-oscillatory modes are also made.
Ion fractions and the weak wind problem

Abstract Some late-type O stars display anomalously weak winds, possibly due to decoupling of the main driving ions from the bulk plasma. This issue and the uncertainty about the nature of wind clumping are a challenge to line-driven wind theory and need resolving in order to fully understand hot stars. We describe the results from the computation of ion fractions for the various elements in O star winds using non-LTE code CMFGEN, including parameterisation of microclumping and X-rays.