Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Compensation Tracking Control for Parallel Robots Actuated by Pneumatic Artificial Muscles With Error Constraints

As pneumatic artificial muscles (PAMs) are similar to biological muscles in structure and movement mechanisms, parallel robots actuated by PAMs have development prospects in rehabilitation and industry, with advantages such as compliance, high safety, strong bearing capacity, and satisfactory dynamic performance. However, the parameter uncertainties and model complexity related to inherent characteristics of parallel robots actuated by PAMs (e.g., time-varying, coupling, hysteresis, creep, and high nonlinearity), bring challenges to accurate dynamic modeling and controller design. Therefore, to achieve satisfactory tracking performance, this article presents an adaptive compensation tracking controller with error constraints for parallel robots actuated by PAMs. The proposed controller deals with parameter uncertainties by estimating system parameters to ensure accurate tracking, which is indicated as an effective solution for a combination of PAMs and parallel robots. Furthermore, using desired trajectory signals in the complicated regression matrix, the online computational burden is significantly reduced. Moreover, to improve operation safety further, an auxiliary term with a theoretical demonstration guarantees that the tracking errors are maintained within allowable ranges. Then, the closed-loop stability is demonstrated by Lyapunov techniques. As far as we know, it is the first time that the challenges of parameter uncertainties, computational burdens, and error constraints of parallel robots actuated by PAMs are simultaneously addressed, which has both theoretical significance and practical value. Finally, the hardware experiments are implemented under different scenarios, and the results indicate that the proposed method achieves satisfactory tracking performance.
Multi-Machine Global Confinement and H-mode Threshold Analysis ITPA Confinement and H-mode Threshold Database Working Group

ITPA Confinement and H-mode Threshold Database Working Group# presented by J. A. Snipes* #From Alcator C-Mod: J.A. Snipes, M. Greenwald; ASDEX/ASDEX Upgrade: F. Ryter, O.J.W.F. Kardaun, J. Stober; COMPASS-D/ START/MAST: M. Valovic, S.J. Fielding, A. Sykes, A. Dnestrovskij, M. Walsh; DIII-D: J.C. DeBoo, T.N. Carlstrom; FTU: G. Bracco; JET/ EFDA: E. Righi, R. Sartori, J.G. Cordey, K. Thomsen, D. McDonald; JFT-2M/ JT-60U: Y. Miura, T. Takizuka, T. Fukuda, Y. Kamada, K. Shinohara, K. Tsuzuki, H. Urano; PBX-M/ PDX/ TFTR/NSTX: S.M. Kaye, C. Bush; TCV: Y. Martin; TdeV: A. Cote, G. Pacher; TEXTOR: J. Ongena; TUMAN-3M: S. Lebedev; T-10: V. Leonov, A. Chudnovskiy. *MIT Plasma Science and Fusion Center, Cambridge, MA 02139 USA. e-mail contact of main author: snipes@psfc.mit. edu
Research on Method of Vague Matter-element Decision Making Based on Entropy Weight

Entropy weight is estimated by the evaluation indices and their values.Considering the theories of vague set and matter-element,a model of vague matter-element decision making based on entropy weight is proposed.Firstly,some concepts of vague set are introduced,and the compound vague matter-element is defined.Secondly,entropy weight is established by the order function of vague set,and ideal solutions of scheme matter-elements are proposed.Thirdly,considering both expert weight and entropy weight,a synthesis evaluation method is presented for scheme matter-elements.Finally,a numerical example is given to apply the proposed method and some problems about vague matter-element decision making are summarized.
Uncovering Where Compensating Errors Could Hide in ENDF/B-VIII.0

Unconstrained physics spaces between two or more nuclear data observables in a library occur when their values can be simultaneously adjusted without violating the uncertainties in either differential information or simulations of relevant integral experiments. Differential data are often too imprecise to fully bound all nuclear data observables of interest for application simulations. Integral data are simulated with combinations of nuclear data so that an error in one observable may be hidden by a counterbalancing error in another. In this manner compensating errors may lurk within nuclear data libraries and these errors have the potential to undermine the predictive power of neutron transport simulations, particularly in situations where there is no conclusive validation experiment that resembles the application of interest. The EUCLID project (Experiments Underpinned by Computational Learning for Improvements in Nuclear Data) developed a preliminary workflow to identify these unconstrained physics spaces by bringing together results from a large collection of integral experiments with their simulated counter-parts as well as differential information that have a one-to-one correspondence to nuclear data. This wealth of information is processed by machine learning tools for subsequent refinement by human experts. Here, we show how the EUCLID work-flow is executed by applying it first to 239Pu and then to 9Be nuclear data in ENDF/B-VIII.0.
Lived experiences of personal growth among the oldest old: narrative evidence

ABSTRACT The pragmatist philosophical perspective deems it important to evaluate the experience of personal growth in terms of its practical consequences. Psychological literature has shown decreased levels of personal growth in later life, but less is known about how the oldest old continue or cease to develop themselves. This interdisciplinary study aims to expand the discourse on personal growth by providing narrative examples of how the oldest old cultivate personal growth. We performed a content analysis of Aging Our Way data documenting lived experiences of 30 community-dwelling persons aged 85 and above. We analyzed all of the direct quotes in the text in order to identify themes of personal growth. Although personal growth was not the purpose of the original data collection, we were able to find diverse examples in the narratives where the oldest old shared their everyday experiences of personal growth. We identified four agentic themes and two communal themes as well as subthemes for each. Consistent with a pragmatist view, the oldest old in the study continued to experience self-development and did not stagnate. Our findings provide contextual details to existing psychological measures, and bear practical implications for an anti-ageist agenda and for activities and programs to empower and engage the oldest old.
Bayesian inference for the offered optical network unit load

Abstract In this article, Bayesian inference for the Offered Optical Network Unit Load (OOL) using non-informative, gamma, power function, and gamma-power function priors is considered. Pareto distributed ON-and OFF-periods generated by the ON/OFF sources at an Optical Network Unit (ONU) in an Ethernet Passive Optical Network (EPON) system are assumed for our implementation in this article. A simulation study and a real-data-based illustrative example are given to demonstrate the advantages of the proposed Bayesian method over the large-sample method.
Residue Number Systems: Theory and Implementation

This book provides an up-to-date account of RNSs and arithmetic. It covers the underlying mathematical concepts of RNSs; the conversion between conventional number systems and RNSs; the implementation of arithmetic operations; various related applications are also introduced. In addition, numerous detailed examples and analysis of different implementations are provided.
Optimization of Operating Parameters of the Asphalt-Paver
 Vibration-Screed System in Improving Compaction Efficiency and Pavement Quality
 for Driving Vehicle Performance

The operating parameters of the asphalt-paver vibration-screed system (AP-VSS) including the excitation frequencies of the tampers and vibratory screed (ft and fs ) and the angular deviations of the tampers (α 1 and α 2) affect not only the pavement quality but also compaction efficiency. Based on the dynamic model of the AP-VSS and the interaction model of the tamper and hot-mixed asphalt, the experimental and numerical simulation studies of AP-VSS are performed to analyze in detail the influence of operating parameters of the AP-VSS on AP-VSS pavement quality and compaction efficiency. The maximum value of the root-mean-square acceleration (ar.m.s ) of the AP-VSS and the maximum value of the root-mean-square compaction force (Fr.m.s ) of the tampers are selected as the objective functions. The experimental and simulation results indicate that by using the AP-VSS design parameters, the pavement quality and compaction efficiency of the AP-VSS are quite low. To enhance the AP-VSS performance, the operation parameters are then optimized by the multi-objective optimization algorithm. The optimal result shows that the compression energy of the tampers and hot-mixed asphalt interaction is greatly increased by 36.2% in comparison without the optimization. Concurrently, both the values of ar.m. s and Fr.m. s are also increased and uniformly distributed over the length of the screed floor and surface of the hot-mixed asphalt in comparison without the optimization. Therefore, the pavement quality and compaction efficiency of the AP-VSS are remarkably improved.
Generating depth maps from stereo image pairs

In the 1960s a group of Al researchers came to the conclusion that automatic depth recovery by two cameras and a computer, the so-called Stereo Correspondence Problem (or SCP), was a simple task, and conquerable within an estimated five to ten years. Emboldened by the Information and Gestalt Theories, which say that the task is at least tractable, the field of Machine Vision was born. Forty years later, the task is still far from being solved, and is still a very active field of study. This thesis summarises the developments which have taken place in stereo vision research since its inception. The various solutions which have been developed are described and their deficiencies noted. An approach to generating depth maps from stereo image pairs using flow networks is proposed. This technique is suitable for implementation on low cost computing hardware and is intended to provide assistance to a human operator. Results are presented which show the operation of this system on synthetic and natural images and the observed performance is analysed and discussed. Declaration of originality I hereby declare that the research recorded in this thesis and the thesis itself was composed and originated entirely by myself in the Department of Electronics and Electrical Engineering at The University of Edinburgh.
Experimental Dengue Virus Type 4 Infection Increases the Expression of MicroRNAs-15/16, Triggering a Caspase-Induced Apoptosis Pathway

The World Health Organization has estimated the annual occurrence of approximately 392 million dengue virus (DENV) infections in more than 100 countries where the virus is endemic, which represents a serious threat to humanity. DENV is a serologic group with four distinct serotypes (DENV-1, DENV-2, DENV-3, and DENV-4) belonging to the genus Flavivirus, in the family Flaviviridae. Dengue is the most widespread mosquito-borne disease in the world. The ~10.7 kb DENV genome encodes three structural proteins (capsid (C), pre-membrane (prM), and envelope (E)) and seven non-structural (NS) proteins (NS1, NS2A, NS2B, NS3, NS4A, NS4B, and NS5). The NS1 protein is a membrane-associated dimer and a secreted, lipid-associated hexamer. Dimeric NS1 is found on membranes both in cellular compartments and cell surfaces. Secreted NS1 (sNS1) is often present in patient serum at very high levels, which correlates with severe dengue symptoms. This study was conducted to discover how the NS1 protein, microRNAs-15/16 (miRNAs-15/16), and apoptosis are related during DENV-4 infection in human liver cell lines. Huh 7.5 and HepG2 cells were infected with DENV-4, and miRNAs-15/16, viral load, NS1 protein, and caspases-3/7 were quantified after different durations of infection. This study demonstrated that miRNAs-15/16 were overexpressed during the infection of HepG2 and Huh 7.5 cells with DENV-4 and had a relationship with NS1 protein expression, viral load, and the activity of caspases-3/7, thus making these miRNAs potential injury markers during DENV infection in human hepatocytes.
Self-Phosphorylated Polybenzimidazole: An Environmentally Friendly and Economical Approach for Hydrogen/Air High-Temperature Polymer-Electrolyte Membrane Fuel Cells

The development of phosphorylated polybenzimidazoles (PBI) for high-temperature polymer–electrolyte membrane (HT-PEM) fuel cells is a challenge and can lead to a significant increase in the efficiency and long-term operability of fuel cells of this type. In this work, high molecular weight film-forming pre-polymers based on N1,N5-bis(3-methoxyphenyl)-1,2,4,5-benzenetetramine and [1,1′-biphenyl]-4,4′-dicarbonyl dichloride were obtained by polyamidation at room temperature for the first time. During thermal cyclization at 330–370 °C, such polyamides form N-methoxyphenyl substituted polybenzimidazoles for use as a proton-conducting membrane after doping by phosphoric acid for H2/air HT-PEM fuel cells. During operation in a membrane electrode assembly at 160–180 °C, PBI self-phosphorylation occurs due to the substitution of methoxy-groups. As a result, proton conductivity increases sharply, reaching 100 mS/cm. At the same time, the current-voltage characteristics of the fuel cell significantly exceed the power indicators of the commercial BASF Celtec® P1000 MEA. The achieved peak power is 680 mW/cm2 at 180 °C. The developed approach to the creation of effective self-phosphorylating PBI membranes can significantly reduce their cost and ensure the environmental friendliness of their production.
Bias Analysis of PMU-Based State Estimation and Its Linear Bayesian Improvement

With the rapidly changing states of modern power systems, real-time state estimation based on phasor measurement units (PMUs) plays an increasingly important role in energy management systems. However, due to the complicated distribution of PMU measurement errors, conventional state estimation methods such as the weighted least squares estimator suffer from the estimation bias. Consequently, they do not represent the least variance unbiased estimators. To solve the estimation bias, a state estimation method combining the PMU linear measurement model and the linear Bayesian estimation theory is proposed. Specifically, considering the prior information on estimated parameters and the complicated probability distribution of PMU measurement errors, the linear Bayesian theory is applied to PMU-based state estimation to improve the performance of state estimation. To support this method, the correlation between real and imaginary errors is analyzed, and the prior information of estimated parameters is determined by the volatility of system states. When the real states of practical power systems are unavailable, performance indicators for state estimation are proposed based on the estimation residuals. The efficacies of the proposed estimation and evaluation methods are verified using IEEE 14 bus system and a large-scale power grid in China.
Path-integral evaluation of Feynman propagator in curved spacetime

We develop an efficient approximation procedure for evaluating the scalar Feynman propagator in arbitrary spacetimes. In the familiar manner we represent it by an integral over the transition amplitude for a Schroedinger-type equation (proper-time method). The amplitude is then represented by a Feynman path integral which is dominated by the contribution of a certain extremal path. The contributions of adjacent paths are then simply expressed by working in Fermi normal coordinates based on the extremal path. In this manner the path integral becomes an ordinary multiple integral over ''Fourier coefficients'' which represent the various paths. For a conformal field, or for spacetimes with constant scalar curvature, we evaluate the integral in the Gaussian approximation in terms of the curvature along the (geodesic) extremal path. We show the result to be related to the Schwinger-DeWitt expansion for the amplitude, but valid for well-separated end points. In the Einstein universe our expression gives the exact amplitude and propagator. In the de Sitter spacetime it gives a good approximation for the amplitude even for well-separated points. We also evaluate the post-Gaussian corrections to the amplitude, though we do not implement them in a concrete spacetime. For nonconformal fields in spacetimes with varying scalarmore » curvature, we evaluate the amplitude in the Gaussian approximation in terms of the values of the curvature along the extremal (nongeodesic) path. It is very different in form from the one mentioned earlier, which suggests the existence of novel effects arising from variation in the scalar curvature. « less
Intimate Partner Violence Perpetration Denial and Underreporting in Cisgender Male Couples

ABSTRACT Intimate partner violence (IPV) perpetrators often deny their actions, limiting opportunities for intervention. Cisgender male couples experience similar IPV rates to mixed-gender couples, yet less is known about how men in same-sex relationships deny or report their IPV behavior. This study aimed to describe perpetration denial across emotional, monitoring/controlling, and physical/sexual IPV, and to identify correlates of perpetration denial, in a convenience sample of male couples (N = 848; United States, 2016-2017). Past-year victimization and perpetration were measured with the IPV-Gay and Bisexual Men (GBM) scale; perpetration deniers were men whose self-reported perpetration contradicted their partner’s reported victimization. Individual-, partner-, and dyadic-correlates of perpetration denial, by IPV-type, were identified using actor-partner interdependence models. We identified 663 (78.2%) perpetrators: 527 emotional; 490 monitoring/controlling; 267 physical/sexual. Thirty-six percent of physical/sexual-, 27.7% of emotional-, and 21.43% of monitoring/controlling-perpetrators categorically denied their actions. Depression was negatively associated with denying monitoring/controlling-perpetration (odds ratio 95% confidence interval: 0.91 [0.84, 0.99]) and physical/sexual-perpetration (0.91 [0.83, 0.97]); dyadic differences in depression were associated with emotional-perpetration denial (0.95 [0.90, 0.99]). Recent substance users had 46% lower odds of monitoring/controlling-denial (0.54 [0.32, 0.92]), versus non-users. Partner-race and employment were also significantly associated with emotional perpetration denial. This study highlights IPV denial’s complexities, including differences across IPV types. Further investigations into how cisgender men in same-sex couples perceive and report various types of IPV perpetration will provide valuable insight into how an underserved and understudied population experiences IPV.
Visualizing timeline‐anchored comments enhanced social presence and information searching in video‐based learning

Numerous learners watch knowledgeable videos with comments or annotations anchored to the video timeline. These comments are learners’ discussions with abundant informational and social content along with video timelines, but the content is usually fragmented and scattered. To extract, organize, and highlight useful information from the discussion, we adopted text mining approaches and designed an interactive visualization tool in the lecture interface for learners, including the following components along with the video timeline: (1) the relevance of comments to the lecture, (2) the comment topics throughout the lecture, and (3) the difficulty level perceived by learners. We conducted a lab experiment with 24 students to examine the effects of the visualization tool on the learning process and outcomes. We found that learners perceived a significantly higher social presence and performed better in open‐book quizzes, searching tasks, and summarizing lectures using the visualization tool. This suggests that the visualization of timeline‐anchored commenting potentially facilitates learners’ participation in discussions and contributions to the learning community.
SOME IDENTITIES OF DEGENERATE GENOCCHI POLYNOMIALS

L. Carlitz introduced higher order degenerate Euler polynomials in [4, 5] and studied a degenerate Staudt-Clausen theorem in [4]. D. S. Kim and T. Kim gave some formulas and identities of degenerate Euler polynomials which are derived from the fermionic p-adic integrals on Zp (see [9]). In this paper, we introduce higher order degenerate Genocchi polynomials. And we give some formulas and identities of degenerate Genocchi polynomials which are derived from the fermionic p-adic integrals on Zp.
Spectral Method for Solving The General Form Linear Fredholm-Volterra Integro Differential Equations Based on Chebyshev Polynomials

The main aim of this paper reports a pseudo spectral method based on integrated Chebyshev polynomials for numerically solving higher order linear Fredholm Volterra integro differential equations (FVIDE) in the most general form. This method transforms FVIDE to matrix equations which correspond to a system of linear algebraic equations with unknown Chebyshev coefficients. The present numerical results are in satisfactory agreement with the exact solutions and show the advantages of this method to some other known methods.
Anomaly Detection in Network Traffic using Machine Learning and Deep Learning Techniques

Due to the rise of sophisticated cyberattacks, network security has become an increasingly important field. One of the most common threats to the security of networks is network anomalies, which can cause system malfunctions and prevent them from working properly. Detecting such anomalies is very important to ensure the continued operation of the network. Deep learning and machine learning algorithms have demonstrated their ability to detect network anomalies, but their effectiveness is still not widely known. This paper presents an evaluation of the performance of three algorithms against the KDD-NSL dataset. This study aims to provide a comprehensive analysis of the various techniques used in deep learning and machine learning to detect network anomalies. It will also help improve the security of networks. The paper presents an evaluation of the performance of three algorithms against the KDD-NSL dataset. The three algorithms are the Support Vector Machine, the Random Forest, and the Artificial Neural Network. They will be compared with their accuracy, recall, and F1-score. The study also explores the impact of the algorithm's feature selection on its performance. The findings of the investigation will be used to inform the development of new techniques that can be utilized to enhance the security of networks. The KDD NSL dataset provides an ideal opportunity to analyze the performance of various algorithms for detecting network anomalies.
An image retrieval algorithm based on HSV color segment histograms

Aiming at the image retrieval based on color feature,a new image retrieval algorithm based on HSV non-uniform quantization color segment histogram was presented.The basic idea of segment histogram was to divide image space into fixed blocks according to a certain strategy,and then the color histogram of each block was calculated as the color feature of the corresponding block.Users assigned a weight to each block according to the importance of the space information that the block contains,and assigned zero to the unimportant of the block.This algorithm made use of HSV non-uniform quantization and the block of image.It improved the traditional histogram for its lack of space information.Compared with traditional histogram method,the results indicate that the proposed algorithm based on HSV non-uniform quantization color segment histogram has better retrieval precision.