Miracle-dz/UniFAR-FTUs huggingface dataset:
The dark side of group heterogeneity on a brand-based online community

Abstract Online brand community (OBC) refers to a group of consumers who share similar enthusiasm for a particular brand and connected through online platforms. The members of OBC community engage jointly through online platforms to accomplish a collective objective or goal. Normally members of this community express similar sentiments, views, or commitments. Extant literature has nurtured issues such as the influence of OBCs on firms, the dysfunction that invites conflicts and rivalry, homogeneity that helps OBCs to develop shared responsibility, among others. However, there is limited study on the dark side of group heterogeneity on a brand-based online community. Using literature and theories, a theoretical model was developed, which was subsequently validated using the PLS-SEM technique to analyze responses from 348 respondents who were members of online brand communities, mainly of the FMCG and automobile sectors. This study finds that there is a significant negative moderating impact of group heterogeneity on OBC. This study has provided several theoretical and managerial implications to brand community literature and has contributed that brand-based online community commitment could impact brand trust and loyalty along with purchase intention, though such impacts are adversely affected by group heterogeneity culture.
MCSG: A Morphology Configurable Soft Gripper With Self-Adaption Modular Composite Finger

Current soft grippers lack active variable stiffness composite fingers and flexible modular configuration, which limit their robust grasp abilities. We proposed a morphology configurable soft gripper (MCSG) assembled with self-adaption modular composite fingers (SAMCFs), whose grasping force can be up to 193 N. The SAMCF with three actuator modules embedded arranged sponge and paperboard and one sensor module made with preinflated air chamber is developed to perform soft grasp with high load capacity and self-sensing ability. Through assembling corresponding SAMCFs to main frame, MCSGs with dual fingers, with three fingers, with four fingers, and with six fingers are manufactured to adapt for grasping objects with different shapes, sizes, and weights. A pneumatic control system with hybrid valve combination is designed to output air pressure from negative to positive to perform contraction and elongation motion simultaneously, and output positive pressure to provide preset pressure for sensor modules. Finally, a multichannel pneumatic control system is developed to control MCSGs to grasp a variety of objects, such as cherry tomato (10 g), egg (170 g), banana (155 g), and stool (3570 g). Furthermore, MCSGs can complete complicated tasks in daily life, such as water decanting, bottle cap unscrewing, mobile phone charging and water pumping.
Unsteady Euler airfoil solutions using unstructured dynamic meshes

Two algorithms for the solution of the time-dependent Euler equations are presented for unsteady aerodynamic analysis of oscillating airfoils. Both algorithms were developed for use on an unstructured grid made up of triangles. The first flow solver involves a Runge-Kutta time-stepping scheme with a finite-volume spatial discretization that reduces to central differencing on a rectangular mesh. The second flow solver involves a modified Euler time-integration scheme with an upwind-biased spatial discretization based on the flux-vector splitting of Van Leer. A significant aspect of the research is the implementation of a dynamic mesh algorithm that is employed for problems where the airfoil moves. Steady and unsteady results are presented for the NACA 0012 airfoil to demonstrate application of the Euler solvers and dynamic mesh algorithm. The unsteady flow results were obtained for the airfoil pitching harmonically about the quarter chord. The two sets of calculated instantaneous pressure distributions and lift and moment coefficients during a cycle of motion compare well with each other and with the experimental data. The paper presents descriptions of the Euler solvers and dynamic mesh algorithm along with results which assess the capability.
The Specification of Causal Models with Tetrad IV: A Review

Tetrad IV is a program designed for the specification of causal models. It is specifically designed to search for causal relations, but also offers the possibility to estimate the parameters of a structural equation model. It offers a remarkable graphical user interface, which facilitates building, evaluating, and searching for causal models. The search algorithms make it possible to find alternatives for existing models, as well as to find new models when a theoretical directive is lacking. This is illustrated by the detection of a causal model for longitudinal data, which is a viable alternative for a latent growth model.
On discrete time nonnegative storage functions and state functions

We study discrete time dissipativeness. Particularly, we focus on storage functions. Different from the continuous time case, every storage function is not necessarily a state function in discrete time. For this problem, we show that every nonnegative storage function is a state function in discrete time. In addition, we provide some of the necessary and sufficient conditions for the existence of the nonnegative storage function.
The Formation of a Composite Urban Image

Since image formation depends on the cognitive organization of perceptions, a change in the individual's available cognitive structure may affect his or her perceptual selectivity. This, in turn, might lead to a reconstruction of the image through selected fields of attention. Although this process is widely accepted, little is known of its neurophysiology, and the formation of an image, therefore, is drawn inferentially from introspective reports. This paper presents, accordingly, a conception of image formation and tests it with a model presenting paths among locational and nonlocational environmental stimuli and an introspective measure of a composite urban image. Changes in the paths due to information and personal attributes that reflect different realms (for example, fields of attention) are further examined with an expanded version of the model. Across the realms, the perceived residential appeal and the perceived level of activities are the main determinants of the composite urban image. Information and personal attributes not only affect the mix of image determinants, but also rearrange their relative effects on the emerging image.
A Novel Peptide-Based Detection of SARS-CoV-2 Antibodies

The need for rapidly developed diagnostic tests has gained significant attention after the recent pandemic. Production of neutralizing antibodies for vaccine development or antibodies to be used in diagnostic tests usually require the usage of recombinant proteins representing the infectious agent. However, peptides that can mimic these recombinant proteins may be rapidly utilized, especially in emergencies such as the recent outbreak. Here, we report two peptides that mimic the receptor binding domain of the spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and investigate their binding behavior against the corresponding human immunoglobulin G and immunoglobulin M (IgG and IgM) antibodies in a clinical sample using a quartz crystal microbalance (QCM) sensor. These peptides were immobilized on a QCM sensor surface, and their binding behavior was studied against a clinical serum sample that was previously determined to be IgG and IgM-positive. It was determined that designed peptides bind to SARS-CoV-2 antibodies in a clinical sample. These peptides might be useful for the detection of SARS-CoV-2 antibodies using different methods such as enzyme-linked immunosorbent assay (ELISA) or lateral flow assays. A similar platform might prove to be useful for the detection and development of antibodies in other infections.
Is REM Density a Measure of Arousal during Sleep?

Rapid eye movements (REMs), an expression of REM sleep phasic activity, occur against a stable background of cortical desynchronization and the absence of axial tone. The significance of REMs during the sleep period was initially attributed to the mental content of dreams, linking the REMs to the dream scenario. Although fascinating, the so-called “scanning hypothesis” has not been supported by consistent evidence, and thus an alternative hypothesis is necessary to understand REMs significance during sleep. Some data suggest that the frequency of REMs during the REM sleep period, known as REM density, might be related to sleep depth or arousal during sleep. REM density increases across the night concomitantly with the progressive reduction in sleep pressure, and consistently it is higher at the circadian time when arousal appears to be higher, and it is decreased in those conditions, such as after sleep deprivation, which produce increased sleep pressure. REM density is also increased in major affective disorders, and it has been suggested either as a risk factor to develop the illness or as a predictive index of response to drug treatment. Disfunction of the neurotransmitter systems involved in arousal mechanisms and wake/sleep control might underlie the altered REM density described in depression. Understanding of the REM density mechanisms could help to untangle functional significance and regulation of REM sleep. Following the seminal idea of Aserinsky that REM density is an index of sleep satiety, it may also provide a sensitive measure of sleep homeostasis in addition to, or even as an alternative to, the consolidated analysis of slow wave activity. REM density can also be utilized to explore those mechanisms which end sleep, and considered a physiological marker which indicate during sleep the “time to wake”.
Fingertip Proximity-Based Grasping Pattern Prediction of Transradial Myoelectric Prosthesis

For transradial amputees, especially those with insufficient residual muscle activity, it is challenging to quickly obtain an appropriate grasping pattern for a multigrasp prosthesis. To address this problem, this study proposed a fingertip proximity sensor and a grasping pattern prediction method base on it. Rather than exclusively utilizing the EMG of the subject for the grasping pattern recognition, the proposed method used fingertip proximity sensing to predict the appropriate grasping pattern automatically. We established a five-fingertip proximity training dataset for five common classes of grasping patterns (spherical grip, cylindrical grip, tripod pinch, lateral pinch, and hook). A neural network-based classifier was proposed and got a high accuracy (96%) within the training dataset. We assessed the combined EMG/proximity-based method (PS-EMG) on six non-disabled subjects and one transradial amputee subject while performing the “reach-and-pick up” tasks for novel objects. The assessments compared the performance of this method with the typical pure EMG methods. Results indicated that non-disabled subjects could reach the object and initiate prosthesis grasping with the desired grasping pattern on average within 1.93 s and complete the tasks 7.30% faster on average with the PS-EMG method, relative to the pattern recognition-based EMG method. And the amputee subject was, on average, 25.58% faster in completing tasks with the proposed PS-EMG method relative to the switch-based EMG method. The results showed that the proposed method allowed the user to obtain the desired grasping pattern quickly and reduced the requirement for EMG sources.
The influence of observations on misclassification probability in multiple discriminant analysis

The influence of observations in estimating the misclassification probability in multiple discriminant analysis is studied using the common omission approach. An empirical influence function for the misclassification probability is also derived, It can give a very good approximation to the omission approach, but the computational load is much reduced, Various extensions of the measures are suggested. The proposed measures are applied to the famous Iris data set. The same three observations are identified as having the most influence under different measures.
Direct quantum mechanical/molecular mechanical simulations of two-dimensional vibrational responses: N-methylacetamide in water

Multidimensional infrared (IR) spectroscopy has emerged as a viable tool to study molecular structure and dynamics in condensed phases, and the third-order vibrational response function is the central quantity underlying various nonlinear IR spectroscopic techniques, such as pump–probe, photon echo and two-dimensional (2D) IR spectroscopy. In this paper, a new computational method is presented that calculates this nonlinear response function in the classical limit from a series of classical molecular dynamics (MD) simulations, employing a quantum mechanical/molecular mechanical (QM/MM) force field. The method relies on the stability matrix formalism where the dipole–dipole quantum mechanical commutators appearing in the exact quantum response function are replaced by the corresponding Poisson brackets. We present the formulation and computational algorithm of the method for both the classical and the QM/MM force fields and apply it to the 2D IR spectroscopy of carbon monoxide (CO) and N-methylacetamide (NMA), each solvated in a water cluster. The conventional classical force field with harmonic bond potentials is shown to be incapable of producing a reliable 2D IR signal because intramolecular vibrational anharmonicity, essential to the production of the nonlinear signal, is absent in such a model. The QM/MM force field, on the other hand, produces distinct 2D spectra for the NMA and CO systems with clear vertical splitting and cross peaks, reflecting the vibrational anharmonicities and the vibrational couplings between the underlying vibrational modes, respectively. In the NMA spectrum, the coupling between the amide I and II modes is also well reproduced. While attaining the converged spectrum is found to be challenging with this method, with an adequate amount of computing it can be straightforwardly applied to new systems containing multiple chromophores with little modeling effort, and therefore it would be useful in understanding the multimode 2D IR spectrum of complex molecular systems.
Radio Monitoring Coverage Assessment Based on Nighttime Light Remote Sensing Data

– Improving coverage has been one of the main objectives of radio monitoring network construction, and radio monitoring coverage assessment has become a matter of concern. This article uses a graph model to associate nighttime light remote sensing (NTL-RS) data of a particular area with the corresponding spatial ﬁeld strength (SFS) data obtained from an elastic wave propagation simulation. The geographic coverage and population coverage of the radio monitoring station are characterized through adjacency matrix calculation. Taking Wuhua District, Kunming, Yunnan Province, as an example, two radio services are available. Results showed that the geographic coverage of digital TV and FM radio was 21.06% and 27.96%, respectively, while the respective population coverage was 48.1% and 57.5%. When considering the light intensity weight, the weighted population coverage was 92.9% and 94.3%. The method proposed in this article is vital for the scientiﬁc assessment of radio monitoring coverage.
Some complexity questions regarding controllability

Experience with accessibility and controllability suggests that the latter is much more difficult to characterize. The author's objective is to make this relative difficulty precise in a formal sense. In the spirit of computational complexity, he picks a class of systems (bilinear subsystems) and shows that for this class the accessibility property can be decided in polynomial time while controllability is NP-hard. <<ETX>>
The rapid–slow decomposition of the subgrid flux in inhomogeneous scalar turbulence

In large eddy simulation of turbulent flow, because of the spatial filter, inhomogeneity and anisotropy affect the subgrid stress via the mean flow gradient. A method of evaluating the mean effects is to split the subgrid stress tensor into ‘rapid’ and ‘slow’ parts. This decomposition was introduced by Shao et al. (L. Shao, S. Sarkar, and C. Pantano, On the relationship between the mean flow and subgrid stresses in large eddy simulation of turbulent shear flows, Phys. Fluids 11 (1999), pp. 1229–1248) and applied to a priori tests of existing subgrid models in the case of a turbulent mixing layer. In the present work, the decomposition is extended to the case of a passive scalar in inhomogeneous turbulence. The contributions of rapid and slow subgrid scalar flux, both in the equations of scalar energy and scalar flux, are analyzed. A priori numerical tests are performed in the turbulent Couette flow with a mean scalar gradient. Results are then used to evaluate the performances of different popular subgrid scalar models. It is shown that the existing models can not well simulate the slow part and need to be improved in future works.
Bayesian Survival Analysis

including a preoccupation with the frequentist coverage properties of credible intervals (to which I confess with a blush), something that D’Agostini characterizes as “a kind of condensate of frequentistic nonsense” (p. 229). D’Agostini makes no mention of Markov chain Monte Carlo (MCMC) methods, which is rather surprising because the technique was invented by physicists. This omission forces him to stick to analyses with closed-form or easily approximated solutions. For example, Chapter 11, which deals with the combination of experimental results, assumes that independent determinations, say of a physical constant, are normally distributed with the same mean and different nominal precisions, N(μ,pi). To allow for the possibility of large overlooked systematic errors, the true precision is modeled as τ · pi , where τ has a gamma(δ,λ) distribution, with δ and λ given fixed values. However, using MCMC, it is possible to assign fairly diffuse hyperprior distributions to δ and λ and allow the data to identify the distribution of τ , and it is possible to model overlooked systematic error as additive (1/pi +1/τ ), which seems more natural. What is encouraging and instructive for Bayesian statisticians is the seriousness with which D’Agostini takes the task of specifying informative prior distributions. It is tempting to shortchange this issue when teaching entry-level Bayesian statistics, on the assumption that real scientists prefer to shy away from informative priors. As Chapter 13, “Which Priors for Frontier Physics,” suggests, the reverse is the case. It appears that physicists are quite able to specify informative priors, and that not doing so can in many cases produce nonsensical results. According to the author, the audience for this book is practicing physicists and engineers who need to evaluate uncertainty. To that list, I would add upper-level and graduate students in physics and engineering, statisticians and statistics graduate students who collaborate with physicists and engineers, mathematicians who teach statistics courses, and all Bayesian statisticians. The two things I’d want added to the book are at least a heuristic axiomatic derivation of subjective probability and a chapter showing how to use MCMC to permit more flexible modeling.
Optical polarization in distant radio galaxies.

We review the optical polarization properties of radio galaxies with redshifts greater than 0.1. We find a strong tendency for the E-vector to be either perpendicular or parallel to the radio axis, and perpendicular to the axis in all the high-redshift galaxies. The observed degree of linear polarization is correlated with redshift and radio power, and is anticorrelated with the rest-frame wavelength of the measurement and the radio spectral index. No correlation is found with absolute magnitude. For the high-polarization objects (P≥3 per cent), the polarization also increases with the radio asymmetry parameter Q, which is thought to be related to the interstellar-medium density ratio
Ecology and epidemiology of Salmonella spp. isolated from the environment and the roles played by wild animals in their maintenance

Salmonella is a ubiquitous organism of public health importance that causes diarrhea and other systemic disease syndromes. The ecology and epidemiology of the organism in addition to the roles played by wild animals are important in understanding its disease. Relevant published peer-reviewed literature was obtained after imputing the study's keywords into the Google search engine. The publications were thereafter saved for the study. The study revealed the ecology of Salmonella is directly related to its epidemiology. These were found to be either positively or negatively influenced by the living and non-living parts of the environment. Free-ranging and captive wild animals can serve as asymptomatic carriers of Salmonella, therefore, help to maintain the cycle of the disease since wildlife serves as reservoir hosts to over 70% of emerging zoonotic diseases. Cockroaches transmit Salmonella through their feces, and body parts and when ingested by birds and animals. The statistically significant over 83% of Salmonella isolation in lizards suggests the reptile could be a source of Salmonella distribution. Snakes, foxes, badgers, rodents, and raccoons have been reported to have Salmonella as a natural component of their gut with the ability to shed the organism often. The high occurrence (>45%) of diverse Salmonella serovars coupled with the fact that some of these animals were handled, kept as pets and consumed by man portends these animals as potential sources of transmission of the organism and the disease. The etiology and epidemiology of Salmonella are overtly affected by several environmental factors which also determine their survival and maintenance. The roles played by wild animals in the relationship, transmission, growth or interaction within and between Salmonella spp. , the occurrence, prevalence, and distribution of the organism help maintain the organism in the environment. An understanding of the roles played by the different parts of the environment and wild animals in the ecology and epidemiology of Salmonella can help make informed decisions on the prevention and control of the diseases it causes. This review aimed to investigate the relationship between ecology, epidemiology, and environment, including the roles played by wild animals in the maintenance of the organism and its disease.
Experimental Evaluation of Novel Master-Slave Configurations for Position Control under Random Network Delay and Variable Load for Teleoperation

This paper proposes two novel master-slave configurations that provide improvements in both control and communication aspects of teleoperation systems to achieve an overall improved performance in position control. The proposed novel master-slave configurations integrate modular control and communication approaches, consisting of a delay regulator to address problems related to variable network delay common to such systems, and a model tracking control that runs on the slave side for the compensation of uncertainties and model mismatch on the slave side. One of the configurations uses a sliding mode observer and the other one uses a modified Smith predictor scheme on the master side to ensure position transparency between the master and slave, while reference tracking of the slave is ensured by a proportional-differentiator type controller in both configurations. Experiments conducted for the networked position control of a single-link arm under system uncertainties and randomly varying network delays demonstrate significant performance improvements with both configurations over the past literature.