Miracle-dz/UniFAR-FTUs huggingface dataset:
Trajectory Tracking for Swing Phase of the Lower Limb Exoskeleton

In this paper, the dynamic model of swing phase of the lower limb exoskeleton is firstly established. Based on the proposed model, system identification experiments at each joint are conducted to determine unknown parameters and joint friction torques by tracking desired reference signals. The experimental data are processed by the least squares method. Another validation experiment is taken to verify the accuracy of the estimated model. Both linear and nonlinear controllers are designed. The linear controller is a proportional-derivative (PD) controller, and the nonlinear controller is a PD controller with gravity and friction torque compensation. Experiments show that the transient response of the tracking performance of the nonlinear controller is significantly better than that of the linear controller.
Safety‐critical control for robotic systems with uncertain model via control barrier function

Usually, it is difficult to build accurate dynamic models for real robots, which makes safety‐critical control a challenge. In this regard, this article proposes a double‐level framework to design safety‐critical controller for robotic systems with uncertain dynamics. The high level planner plans a safe trajectory for low level tracker based on the control barrier function (CBF). First, the high level planning is done independently of the dynamic model by quadratic programs subject to CBF constraint. Afterward, a novel method is proposed to learn the uncertainty of drift term and input gain in nonlinear affine‐control system by a data‐driven Gaussian process (GP) approach, in which the learning result of uncertainty in input gain is associated with CBF. Then, a Gaussian processes‐based control barrier function (GP‐CBF) is designed to guarantee the tracking safety with a lower bound on the probability for the low level tracker. Finally, the effectiveness of the proposed framework is verified by the numerical simulation of UR3 robot.
Electrochemical Micro-Immunosensor of Cubic AuPt Dendritic Nanocrystals/Ti3C2-MXenes for Exosomes Detection

Exosomes are extracellular vesicles that exist in body circulation as intercellular message transmitters. Although the potential of tumor-derived exosomes for non-invasive cancer diagnosis is promising, the rapid detection and effective capture of exosomes remains challenging. Herein, a portable electrochemical aptasensor of cubic AuPt dendritic nanocrystals (AuPt DNs)/Ti3C2 assisted in signal amplification, and aptamer CD63 modified graphene oxide (GO) was immobilized on a screen-printed carbon electrode (SPCE) as the substrate materials for the direct capture and detection of colorectal carcinoma exosomes. Cubic AuPt DNs/Ti3C2 was synthesized according to a simple hydrothermal procedure, and the AuPt DNs/Ti3C2-Apt hybrid demonstrated an efficient recognition of exosomes. Under optimal conditions, a detection limit of down to 20 exosomes µL−1 was achieved with the linear range from 100 exosomes μL−1 to 5.0 × 105 exosomes μL−1. The proposed immunosensor could be suitable for the analysis of exosomes and has clinical value in the early diagnosis of cancer.
A New Species of Proctoporus (Reptilia, Gymnophthalmidae, Cercosaurinae) from the Puna of the Otishi National Park in Peru

We describe a new species of Proctoporus from the scientifically unexplored southern sector of the Otishi National Park (Region Cusco) in Peru, on the basis of molecular and morphological characters. Seven type specimens were obtained from six localities between 3241–3269 m a.s. l. within a radius of ca. 1.5 km in a Puna valley. Nine adult specimens (four males, five females) from Chiquintirca (Region Ayacucho, ca. 85 km airline from the type locality) are considered referred specimens. Males of the new species have a snout–vent length of 41.3–53.9 mm (x¯ = 46.7, n = 6), females have a snout–vent length of 43.6–52.6 mm (x¯ = 48.1, n = 8). The new species has dorsal scales striated, four supraoculars, four anterior supralabials, loreal and prefrontal scales absent, two pairs of genials (rarely one or three), three rows of pregulars, and five to seven femoral pores in males (absent in females). Sexual dimorphism is evident in the ventral coloration: males have neck, chest, and belly dark gray to black, whereas females have neck, chest, and belly pale gray with a diffuse dark gray fleck in the center of each scale, and an orange iris with a fringed pupil in both sexes.
Assignment methods in combinatorial data analysis

This monograph is extremely interesting because it integrates many classes of permutation techniques in a highly cohesive manner. Being confined to permutation methods, the techniques are strictly data dependent (i.e., all inferences depend only on the permutation structure associated with the available data). As a consequence, this monograph avoids the all-too-common practice involving the assumption of a totally unjustified distribution (e.g., a univariate or multivariate normal distribution) in applications of statistical methods that influences (perhaps overwhelms) any inference resulting from such methods. All the methods considered in this monograph depend on indices of merit that are called objective functions. A well-known example of an objective function is the Pearson correlation coefficient. In this perspective, the objective functions considered in this monograph are nothing more than univariate or multivariate variations and/or extensions of the Pearson correlation coefficient. The intuitive notion of proximity ("closeness" between objects) is a major consideration in the choice of an objective function. Because permutation methods involve random assignments, the statistical approaches of this monograph are termed assignment models. First, second, and higher order assignment models are considered. A general rth-order assignment model is based on an objective function given by
An Automatic Deep Neural Network Model for Fingerprint Classification

The accuracy of fingerprint recognition model is extremely important due to its usage in forensic and security fields. Any fingerprint recognition system has particular network architecture whereas many other networks achieve higher accuracy. To solve this problem in a unified model, this paper proposes a model that can automatically specify itself. So, it is called an automatic deep neural network (ADNN). Our algorithm can specify the appropriate architecture of the neural network used and some significant parameters of this network. These parameters are the number of filters, epochs, and iterations. It guarantees the highest accuracy by updating itself until achieving 99% accuracy then it stops and outputs the result. Moreover, this paper proposes an end-to-end methodology for recognizing a person’s identity from the input fingerprint image based on a residual convolutional neural network. It is a complete system and is fully automated whether in the features extraction stage or the classification stage. Our goal is to automate this fingerprint recognition system because the more automatic the system is, the more time and effort it saves. Our model also allows users to react by inputting the initial values of these parameters. Then, the model updates itself until it finds the optimal values for the parameters and achieves the best accuracy. Another advantage of our algorithm is that it can recognize people from their thumb and other fingers and its ability to recognize distorted samples. Our algorithm achieved 99.75% accuracy on the public fingerprint dataset (SOCOFing). This is the best accuracy compared with other models.
Formal Quality and Compliance of Informed Consent Forms in Critical Care and Surgical Areas in Spain: An Observational Study

(1) Background: The informed consent form must contain all the relevant information about the procedure to be performed to guarantee the patient’s freedom to choose. (2) Objective: To analyze the formal quality of, and compliance with informed consent forms in critical care and surgical areas in a county hospital in Spain. (3) Methods: The formal quality of informed consent forms in critical care and surgical areas from the hospital were analyzed, following the established formal quality criteria for informed consent forms. The compliance with specific criteria for each of the operated patients during the period of study was also evaluated. (4) Results: The formal quality of 224 informed consent forms was analyzed from 8 disciplines observing a median of non-compliances of 4 with a minimum of 1 and a maximum of 5, with the most breaches being in verifying the delivery of a copy to the patient and showing contraindications. The compliance of 376 documents from 188 operated patients were assessed, highlighting that the non-complied items were: the personalized risks and complete identification of the patient and the physician. A significant association was found between disciplines analyzed and the identification of the physician and personalized risks, with anesthesia and critical care showing the best compliance. (4) Conclusions: The informed consent forms in critical care and surgical areas were shown to have a deficient formal quality and an inadequate compliance. These deficiencies should be corrected to improve the information received by the patients and to guarantee their freedom to choose. As nurses have a responsibility to ensure that patients are adequately informed about both nursing interventions and care, as well as the surgical treatments they receive, consideration should be given to the possibility of nursing professionals taking the lead in obtaining informed consent.
The Hybrid Wild Bootstrap for Time Series

We introduce a new and simple bootstrap procedure for general linear processes, called the hybrid wild bootstrap. The hybrid wild bootstrap generates frequency domain replicates of the periodogram that imitate asymptotically correct the first- and second-order properties of the ordinary periodogram including its weak dependence structure at different frequencies. As a consequence, the hybrid wild bootstrapped periodogram succeeds in approximating consistently the distribution of statistics that can be expressed as functionals of the periodogram, including the important class of spectral means for which all so far existing frequency domain bootstrap methods generally fail. Moreover, by inverting the hybrid wild bootstrapped discrete Fourier transform, pseudo-observations in the time domain are obtained. The generated time domain pseudo-observations can be used to approximate correctly the random behavior of statistics, the distribution of which depends on the first-, second-, and, to some extent, on the fourth-order structure of the underlying linear process. Thus, the proposed hybrid wild bootstrap procedure applied to general time series overcomes several of the limitations of standard linear time domain bootstrap methods.
REFLECTION AND TRANSMISSION OF SHEAR WAVES IN MONOCLINIC MEDIA

This paper deals with the propagation, reflection and transmission of shear waves in monoclinic media. The dispersion equation for a monoclinic layer overlying a monoclinic half-space has been obtained and curves are plotted. The amplitude ratios for both the reflected and transmitted waves due to reflection of shear waves at the interface of two monoclinic half-spaces have also been computed and the numerical results are presented graphically. The results are compared with the isotropic case. It has been observed that, in monoclinic media, the amplitude ratios for reflected and transmitted wave increases approximately by 25 and 50 per cent respectively, in comparison to the isotropic case. © 1997 John Wiley & Sons, Ltd.
Validity of the bond-energy picture for the energetics at Si − SiO 2 interfaces

Using a first-principles approach, we assess the validity of a picture for the energetics at Si-SiO2 interfaces based on bond energies complemented with penalty energies for silicon atoms in intermediate oxidation states. By total-energy calculations on cluster models, we demonstrate that such penalty energies only depend on the composition of the first-neighbor shell of the silicon atoms and can thus be taken as additive contributions to the total energy. Considering oxygen incorporation processes in Si-SiO2 interface models, we show that variations in the interface energy result from suboxide and strain contributions of comparable magnitude. Hence, simplified schemes for the energetics at Si-SiO2 interfaces should account for both contributions with similar accuracy.
Mental Health Impact of Early Stages of the COVID-19 Pandemic on Individuals with Pre-Existing Mental Disorders: A Systematic Review of Longitudinal Research

In view of disease-related threats, containment measures, and disrupted healthcare, individuals with pre-existing mental illness might be vulnerable to adverse effects of the COVID-19 pandemic. Previous reviews indicated increased mental distress, with limited information on peri-pandemic changes. In this systematic review, we aimed to identify longitudinal research investigating pre- to peri-pandemic and/or peri-pandemic changes of mental health in patients, focusing on the early phase and considering specific diagnoses. PsycINFO, Web of Science, the WHO Global literature on coronavirus disease database, and the Cochrane COVID-19 Study Register weresearched through 31 May 2021. Studies were synthesized using vote counting based on effect direction. We included 40 studies mostly from Western, high-income countries. Findings were heterogeneous, with improving and deteriorating mental health observed compared to pre-pandemic data, partly depending on underlying diagnoses. For peri-pandemic changes, evidence was limited, with some suggestion of recovery of mental distress. Study quality was heterogeneous; only few studies investigated potential moderators (e.g., chronicity of mental illness). Mental health effects on people with pre-existing conditions are heterogeneous within and across diagnoses for pre- to peri-pandemic and peri-pandemic comparisons. To improve mental health services amid future global crises, forthcoming research should understand medium- and long-term effects, controlling for containment measures.
Approximating statistical functions by using fractional polynomial regression

SUMMARY In statistics it is common to require a simple approximating equation for a smooth relationship between Yand X. The exact mathematical form may be known (but complicated) or unknown. We show that fractional polynomials are particularly good at providing concise and accurate formulae for representing such relationships. We give several examples, including the approximation of the 5% point of a statistic used in the analysis of means and of an unbiasing factor for calculating the standard deviation from a doubly censored normal sample.
Study on Multiobjective Programming Problem under Bifuzzy Environment

In this paper, based on bifuzzy theory, we have studied the multiobjective programming problem under bifuzzy environment, and presented the expected-value model which is a deterministic multiobjective problem. To the expected value model, the concepts of non-inferior solution are defined, and their relations are also discussed. According to practical decision-making process, a solution method, called the method of main objective function, has been studied, whose results can facilitate us to design algorithms to solve the bifuzzy multiobjective programming problem.
Immune Pathways with Aging Characteristics Improve Immunotherapy Benefits and Drug Prediction in Human Cancer

Simple Summary By integrating large-scale transcriptomic and genomic data, this study identified immune-related pathways with aging characteristics among 25 cancer types. We found that the perturbation of immune-related pathways showed a cancer-specific expression pattern. Moreover, the aging- and cancer-related dysregulated patterns of pathways were in the same direction in most cancer types. Furthermore, the study found that aging-related immune pathways with clinical relevance improved immunotherapy benefits in melanoma and non-small cell lung cancer patients. Using a network-based method, this study predicted potential drug targets for immunotherapy and treatment combinations. Collectively, this study may provide insight into cancer immunotherapy, thus improving treatment benefits. Abstract (1) Background: Perturbation of immune-related pathways can make substantial contributions to cancer. However, whether and how the aging process affects immune-related pathways during tumorigenesis remains largely unexplored. (2) Methods: Here, we comprehensively investigated the immune-related genes and pathways among 25 cancer types using genomic and transcriptomic data. (3) Results: We identified several pathways that showed aging-related characteristics in various cancers, further validated by conventional aging-related gene sets. Genomic analysis revealed high mutation burdens in cytokines and cytokines receptors pathways, which were strongly correlated with aging in diverse cancers. Moreover, immune-related pathways were found to be favorable prognostic factors in melanoma. Furthermore, the expression level of these pathways had close associations with patient response to immune checkpoint blockade therapy in melanoma and non-small cell lung cancer. Applying a net-work-based method, we predicted immune- and aging-related genes in pan-cancer and utilized these genes for potential immunotherapy drug discovery. Mapping drug target data to our top-ranked genes identified potential drug targets, FYN, JUN, and SRC. (4) Conclusions: Taken together, our systematic study helped interpret the associations among immune-related pathways, aging, and cancer and could serve as a resource for promoting clinical treatment.
Adaptive compressive sensing camera

We have embedded Adaptive Compressive Sensing (ACS) algorithm on Charge-Coupled-Device (CCD) camera based on the simplest concept that each pixel is a charge bucket, and the charges comes from Einstein photoelectric conversion effect. Applying the manufactory design principle, we only allow altering each working component at a minimum one step. We then simulated what would be such a camera can do for real world persistent surveillance taking into account of diurnal, all weather, and seasonal variations. The data storage has saved immensely, and the order of magnitude of saving is inversely proportional to target angular speed. We did design two new components of CCD camera. Due to the matured CMOS (Complementary metal–oxide–semiconductor) technology, the on-chip Sample and Hold (SAH) circuitry can be designed for a dual Photon Detector (PD) analog circuitry for changedetection that predicts skipping or going forward at a sufficient sampling frame rate. For an admitted frame, there is a purely random sparse matrix [Φ] which is implemented at each bucket pixel level the charge transport bias voltage toward its neighborhood buckets or not, and if not, it goes to the ground drainage. Since the snapshot image is not a video, we could not apply the usual MPEG video compression and Hoffman entropy codec as well as powerful WaveNet Wrapper on sensor level. We shall compare (i) Pre-Processing FFT and a threshold of significant Fourier mode components and inverse FFT to check PSNR; (ii) Post-Processing image recovery will be selectively done by CDT&D adaptive version of linear programming at L1 minimization and L2 similarity. For (ii) we need to determine in new frames selection by SAH circuitry (i) the degree of information (d.o.i) K(t) dictates the purely random linear sparse combination of measurement data a la [Φ]M,N M(t) = K(t) Log N(t).
Technical Inefficiency in Nine Clusters of Indonesian Manufacturing Firms And its Determinants: Stochastic Frontier Analysis

The current study examines the technical inefficiency of Indonesian manufacturing firms and its key determinants. Extending the previous research that mainly focuses on firms in a specific industry, the current study groups firms into nine industrial clusters and estimates them separately to find a variety of results among the clusters. The stochastic frontier analysis (SFA) method is applied to estimate the inefficiency score and the key determinants of 5,848 firms for five years (29,240 total observations). Data period ended in 2014 due to the substantial change in the classification code of the manufacturing industry in the survey by the Indonesian Central Board of Statistics. Five notable findings are recorded. First, the average efficiency score of all observed firms is 0.8815. Second, firm size is found to have a negative effect on inefficiency in the sample of all firms and three out of nine clusters (ISIC 34, ISIC 35, and ISIC 37). Third, foreign ownership generates a negative contribution to firms’ technical inefficiency in both the sample of all firms and the sample of each nine industrial clusters. Fourth, export orientation has various effects on firms across nine industrial clusters, with a dominant significant negative impact in paper and paper product industry (ISIC 34) and metal product industry (ISIC 38). Finally, import intensity provides a significant negative impact on firms in most industrial clusters. These findings support the argument on the importance of absorption capacity and unique firm characteristics in analyzing the impact of key determinants of technical inefficiency.
Negative refraction in one-dimensional photonic crystals

Photonic crystals are artificial structures that have periodic dielectric components with different refractive indices. Under certain conditions, they abnormally refract the light, a phenomenon called negative refraction. Here, we discuss recent theoretical and simulation results that showed that negative refraction could be present near the low frequency edge of at least the second, fourth and sixth bandgaps of a lossless one-dimensional photonic crystals (1DPC) structure. That is, negative refraction is a multiband phenomenon. We also discuss the negative refraction correctness condition that gives the angular region where negative refraction occurs. We compare two current negative refraction theoretical models with recent experimental results. In order to succeed, an output refraction correction is utilized. The correction uses Snell’s law and an effective refractive index based on two effective dielectric constants. We found good agreement between experiment and both theoretical models in the negative refraction zone.
The dynamics of the k–ϵ mix model toward its self-similar Rayleigh–Taylor solution

We propose an analysis of the non-linear system of partial differential equations for the k–ϵ model expressing the evolution of a turbulent mixing zone induced by the Rayleigh–Taylor instability. The method developed in this work is based on dynamical system theory. Our objective is to prove the global stability of the self-similar solution and at the same time to investigate the dynamics of transient phases. In fact, it is possible to show the existence of a central manifold allowing to reduce the dimension of the problem to a set of two ordinary differential equations.We establish that this simplified non-linear system globally converges toward a fixed point representing the self-similar solution by application of the Poincaré–Bendixson theorem. In addition, we shed light on the existence of a second fixed point which influences the trajectories in the phase space and leads to a non-physical enhanced growth rate in some cases explicitly detailed.