Miracle-dz/UniFAR-FTUs huggingface dataset:
In-Hand Pose Estimation Using Hand-Mounted RGB Cameras and Visuotactile Sensors

This paper proposes a method to estimate the 6D pose of an object grasped by a robot hand using RGB cameras mounted on the palm and visuotactile sensors installed at the fingertips. It can deal with objects made from a wide range of materials thanks to combining the two types of sensors. The method allows a robot to robot to perform in-hand pose estimation while holding the object, eliminating the need for preparatory actions or particular environmental backgrounds. The mechanism at the back of the method includes deep-learning-based background subtraction and denoising auto-encoder-based sensor fusion. With the poses estimated using the proposed method, a robot controller can rectify the grasping uncertainty and adjust the robot motion to move an object toward required goals with satisfying accuracy. We conduct various studies and analyses in the experimental Section to understand the proposed method’s advantages and disadvantages. The results demonstrate the benefits of the proposed combination and mechanism. They also provide essential knowledge to readers considering using a similar configuration for estimating object poses.
Examining The Preschool to First-Grade Literacy and Language Outcomes of Black Children Experiencing a High-Quality Early Childhood Program

This study examined the literacy trajectories of 185 Head Start-eligible Black children from preschool to first grade enrolled in a high-quality early learning program physically connected to an elementary school where they attended kindergarten and first grade. Social emotional, language, and literacy skills were assessed in the fall and spring of the school year in preschool and prekindergarten (PreK) and the fall only in kindergarten and first grade. Children made literacy and language gains in early childhood that were maintained into first grade. Although children in the connected early learning/elementary experience performed above peers on language and literacy skills, only differences in language skills reached significance. Advantages in kindergarten were gone by first grade as comparison children evidenced improvement of language skills that narrowed the performance gap. Findings point to the importance of creating clear academic pathways for young learners that prioritize instructional opportunities designed to maintain positive learning trajectories.
Understanding the Environmentally Sustainable Behavior of Chinese University Students as Tourists: An Integrative Framework

The purpose of this study is to develop a theoretical framework by integrating the value-belief-norm (VBN) theory with environmental awareness in measuring Chinese university students’ environmentally sustainable behavior toward tourism destinations. University students tend to engage in sustainability efforts since their values and beliefs are still being formed. The participants were 301 university students from a university in eastern China. The empirical findings demonstrate that: (1) environmental awareness has positive influences on biospheric value, altruistic value and egoistic value; (2) biospheric value positively predicts the new ecological paradigm (NEP), whereas altruistic and egoistic values do not; (3) the NEP, awareness of consequence and personal norms play an important mediating role. Results indicate that extended VBN can explain students’ environmentally sustainable behavior. This research supports the growth of sustainable tourism and has a number of practical implications for universities and the relevant environmental departments to promote university students’ involvement in sustainable tourism.
Distinct effects of zwitterionic molecules on ionic solvation in (ethylene oxide)10: a molecular dynamics simulation study.

Ion-containing polymers play a critical role in various energy and sensing applications. Adjusting ionic solvation is one approach to tune the performance of ion-containing polymers. Small zwitterionic molecule additives have presented their ability to regulate ionic solvation because they possess two charged groups covalently connected together. One remaining question is how the effect of zwitterionic molecules on ionic solvation depends on their own chemical structures, especially the anionic groups. To shed light on this question, we investigate the ionic solvation structure and dynamics in LiTFSI/(ethylene oxide)10 (EO10) with the presence of three distinct zwitterionic molecules (MPC, SB, and CB) using molecular dynamics simulations (MPC: 2-methacryloyloxyethyl phosphorylcholine, SB: sulfobetaine ethylimidazole, CB: carboxybetaine ethylimidazole, and LiTFSI: lithium bis(trifluoromethylsulfonyl)-imide). The simulation systems include two Li+ : O(EO10) molar ratios: 1 : 6 and 1 : 18. The simulation results show that all three zwitterionic molecules reduce the Li+-EO10 coordination number in the order of MPC > CB > SB. In addition, nearly 10% of Li+ exclusively coordinates with MPC molecules, only 2-4% of Li+ exclusively cooridinates with CB molecules, while no Li+ exclusively coordinates with SB molecules. MPC molecules also present the most stable Li+ coordination among the three zwitterionic molecules. Our simulations indicate that zwitterionic molecule additives may benefit a high Li+ concentration environment. At a low Li+ concentration, all three zwitterionic molecules reduce the diffusion coefficient of Li+. However, at a high Li+ concentration, only SB molecules reduce the diffusion coefficient of Li+.
Stability of Bifurcating Solutions for the Ginzburg-Landau Equations

This paper is concerned with superconducting solutions of the Ginzburg–Landau equations for a film. We study the structure and the stability of the bifurcating solutions starting from normal solutions as functions of the parameters (κ, d), where d is the thickness of the film and κ is the Ginzburg–Landau parameter characterizing the material. Although κ and d play independent roles in the determination of these properties, we will exhibit the dominant role taken up by the product κd in the existence and uniqueness of bifurcating solutions as much as in their stability. Using the semi-classical analysis developed in our previous papers for getting the existence of asymmetric solutions and asymptotics for the supercooling field, we prove in particular that the symmetric bifurcating solutions are stable for (κ, d) such that κd is small and (for any η>0) and unstable for (κ, d) such that κd is large. We also show the existence of an explicit critical value Σ0 such that, for κ≤Σ0-η and κd large, the asymmetric solutions are unstable, while, for κ≥Σ0+η and κd large, the asymmetric solutions are stable. Finally, we also analyze the symmetric problem which leads to other stability results.
Volunteers’ well-being with the maqashid shariah approach: Evidence from charitable organizations in Indonesia

Purpose – This study aims to analyze the influence of the five dimensions of Maqashid Sharia on the life satisfaction of Muslim volunteers of charitable organizations di Indonesia.Methodology – This study used data from the World Value Survey Wave 7 with a sample of 504 muslim volunteers who are active members of charitable organizations in Indonesia. The data were analyzed using logit and probit regression.Findings – The results of this study reveal that both the logit and probit methods consistently show that from the five Maqashid Syariah dimensions, the dimensions of faith, life and wealth positively influence the life satisfaction of volunteers. In contrast, the intellectual and descendants dimensions are not significant to the life satisfaction of volunteers. Furthermore, the wealth dimension has the greatest tendency toward the life satisfaction of Muslim volunteers from charitable organizations in Indonesia. Implications – This research has implications for developing empirical analysis of individual well-being in Indonesia and the research on the subjective well-being of volunteers, which is part of a national and international analysis of economic happiness linked with the Islamic economy, specifically maqashid sharia as an essential part of Muslim individuals. Originality – This research is expected to fill in the existing research gap regarding welfare analysis of volunteer life satisfaction from an Islamic economic point of view through the Dimension of Maqashid Sharia. This study employs volunteers as objects because Indonesian volunteers are the most numerous in the world, contributing to Indonesia's position as the most generous country in the world.
The long-term behaviour of the pulsation periods and amplitudes of the β Cephei star 16 (EN) Lacertae

The blue-light observations of this pulsating and eclipsing variable (BCEP+EA) cover an interval from 1950 to 1992. The out-of-eclipse (that is, pulsational) variation contains three sinusoidal terms with variable amplitudes. In our 1996 paper (JP96), based on the 1950–1983 data, we showed that for the first two terms, having frequencies equal to about 5.9112 and 5.8551 d−1, the amplitudes varied with time-scales of the order of 50 yr. The remaining term formed a doublet with constant amplitudes and frequencies close to 5.5033 d−1, resulting in a beat-period of 1.85 yr. In the present paper we confirm this picture using additional data, derive improved values of the time-scales and refine the parameters of the doublet. In addition, we determine the year-to-year variation of the epochs of maximum light of the first two terms. This allows us to account for (1) the ground-based blue-filter observations that were not extensive enough to be used in the analysis, and (2) the Hp magnitudes from the Hipparcos mission. In particular, we demonstrate that the period of 0.171 203 d, given in the Hipparcos Variability Annex, is spurious.
Detection of Pathogens and Antimicrobial Resistance Genes in Ventilator-Associated Pneumonia by Metagenomic Next-Generation Sequencing Approach

Background The early identification of pathogens and their antibiotic resistance are essential for the management and treatment of patients affected by ventilator-associated pneumonia (VAP). However, microbiological culture may be time-consuming and has a limited culturability of many potential pathogens. In this study, we developed a rapid nanopore-based metagenomic next-generation sequencing (mNGS) diagnostic assay for detection of VAP pathogens and antimicrobial resistance genes (ARGs). Patients and Methods Endotracheal aspirate (ETA) samples from 63 patients with suspected VAP were collected between November 2021 and July 2022. Receiver operating characteristic (ROC) curves were established to compare the pathogen identification performance of the target pathogen reads, reads percent of microbes (RPM) and relative abundance (RA). The evaluation of the accuracy of mNGS was performed comparing with the gold standard and the composite standard, respectively. Then, the ARGs were analyzed by mNGS. Results ROC curves showed that RA has the highest diagnostic value and the corresponding threshold was 9.93%. The sensitivity and specificity of mNGS test were 91.3% and 78.3%, respectively, based on the gold standard, while the sensitivity and specificity of mNGS test were 97.4% and 100%, respectively, based on the composite standard. A total of 13 patients were virus-positive based on mNGS results, while the coinfection rate increased from 27% to 46% compared to the rate obtained based on clinical findings. The mNGS test also performed well at predicting antimicrobial resistance phenotypes. Patients with a late-onset VAP had a significantly greater proportion of ARGs in their respiratory microbiome compared to those with early-onset VAP (P = 0.041). Moreover, the median turnaround time of mNGS was 4.43 h, while routine culture was 72.00 h. Conclusion In this study, we developed a workflow that can accurately detect VAP pathogens and enable prediction of antimicrobial resistance phenotypes within 5 h of sample receipt by mNGS.
Uncertainty and Information Systems

This paper is an explorative journey into the design and use of information systems (IS) in organizations. We argue that conventionally IS are constructed from a perspective of Certainty which result in two major problems: the problem of rigidity and the problem of structural blindness. In order to overcome both problems another perspective on the design and use of IS is needed which we have termed Uncertainty. This perspective is described using two dimensions; the systems dimesion and the information dimension. Where the systems dimension is concerned this perspective allows for a continuously changable and changing structure which reflects the dynamic nature of organizational reality. The information dimension of the Uncertainty perspective draws attention to the relevance of ambiguous, unexpected and seemingly irrelevant information. Both dimensions of Uncertainty stress the support of the process which is underlying the functioning of IS instead of the IS as a static and defined entity. We have tried to argue that certain types of IS like internet and CSCW-systems need a different perspective to understand their construction and use.
Unsupervised Machine Learning for Explainable Health Care Fraud Detection

The US federal government spends more than a trillion dollars per year on health care, largely provided by private third parties and reimbursed by the government. A major concern in this system is overbilling, waste and fraud by providers, who face incentives to misreport on their claims in order to receive higher payments. In this paper, we develop novel machine learning tools to identify providers that overbill Medicare, the US federal health insurance program for elderly adults and the disabled. Using large-scale Medicare claims data, we identify patterns consistent with fraud or overbilling among inpatient hospitalizations. Our proposed approach for Medicare fraud detection is fully unsupervised, not relying on any labeled training data, and is explainable to end users, providing reasoning and interpretable insights into the potentially suspicious behavior of the flagged providers. Data from the Department of Justice on providers facing anti-fraud lawsuits and several case studies validate our approach and findings both quantitatively and qualitatively.
The Ameliorating Effects of Biochar and Poultry Manure on the Properties of Two Degraded Soils and Sweet Potato Yield in Sub-Humid Nigeria

ABSTRACT Soil amendments and critical agronomic practices like biochar (B) and poultry manure (PM) change soil characteristics and have a direct impact on soil sustainability and crop productivity. Hence, a two-year field trial was conducted in the forest-savanna transition zone of southwest Nigeria at two locations (Owo – site A and Obasooto – site B) to examine the impacts of different levels of biochar (B) and poultry manure (PM) on soil physical and chemical qualities, sweet potato (Ipomoea batatas L.) growth, and yield. The experiment consisted of a 2 × 4 × 3 factorial layout with three replicates. The treatments applied at two locations were: four levels of biochar (B) (0, 10.0, 20.0 and 30.0 t ha−1) and three levels of poultry manure (PM) (0, 5.0 and 10.0 t ha−1). The biochar (B) and poultry manure (PM) significantly (p = .05) improved both soil physical and chemical properties, sweet potato growth and yield with their rates of application when compared to the control. In comparison to Owo (site A), Obasooto (site B) had significantly higher sweet potato growth and yield, and better soil properties. Application of 30.0 t ha−1 biochar (B) and 10.0 t ha−1 poultry manure (PM) had the best sweet potato growth and yield parameters of all the biochar (B) combined with poultry manure (PM) treatments.
The Effect of Axial Constraint on the Instability of Thin Conical Shells Under External Pressure

Abstract : The effect of axial elastic restraint in the direction of the generators on the instability of a thin circular conical shell under hydrostatic pressure, or under uniform lateral pressure, is analysed by a Rayleigh Ritz approach. For the case of hydrostatic pressure, the effect is calculated for wide range of parameters and design curves are presented for the percentage increase in critical pressure. (Author)
Compressed Sensing Approach for Physiological Signals: A Review

The immense progress in physiological signal acquisition and processing in health monitoring allowed a better understanding of patient disease detection and diagnosis. With the increase in data volume and power consumption, effective data compression, signal acquisition, transmission, and processing techniques are essential, especially in telemonitoring healthcare applications. An emerging research area focuses on integrating compressed sensing (CS) with physiological signals to deal with a massive amount of physiological data, transmission bandwidth, and power-saving purposes. A review of CS for physiological signals is presented in this article, including electroencephalography (EEG), electrocardiography (ECG), electromyography (EMG), and electrodermal activity (EDA), focusing on the pros and cons of CS in treating such signals and the suitability of CS for hardware implementation. Furthermore, we emphasize performance matrices, such as compression ratio (CR), signal-to-noise ratio (SNR), Percentage Root-mean-square Difference (PRD), and processing time to evaluate the performance of CS. We also investigate the current practices, challenges, and opportunities of using CS in healthcare applications.
Nonlinear balanced simulation of a baroclinic wave

The nonlinear balanced time integration of a baroclinic wave with a model applicable for synoptic and meso‐scale weather systems and based on the conservation of the Ertel–Rossby potential vorticity (PV) is presented. The simulation is performed for a realistic, but idealized, atmospheric configuration involving troposphere, stratosphere and flexible tropopause. The balanced model, compared with the primitive equation (PE) one, proves to be highly accurate. The balanced integration allowed strict implementation of the conservation of PV for the simulation of frontal processes, without generation of spurious low‐level PV anomalies, which emerge in PE simulations of baroclinic waves in the region of frontal collapse. Also, a hypothesis is formulated on the substantial role of these PV anomalies in the baroclinic amplification of the modelled PE baroclinic wave at advanced stages of its evolution. Copyright © 2002 Royal Meteorological Society
Peroneal Tendon Dislocation: A Report of Two Cases

Ankle injuries are a very common cause of patient visits to the primary care units and emergency departments. Although the most frequent ones are lateral ligament sprains, peroneal tendon subluxations have the same inversion mechanism and are described as one of the main causes of lateral ankle pain and instability. They are often missed during the acute phases as they are misdiagnosed as ankle sprains since both injuries share similar mechanisms and often occur in athletes and patients with high sports activity. We present two different cases of peroneal tendon dislocation that illustrate how this pathological condition may be present under different circumstances. We aim, through these cases, to provide clinical awareness and help improve earlier diagnosis of this condition; we also demonstrate the effectiveness of surgical reattachment of the upper retinaculum that two of our patients underwent.
SHRINKAGE, PRETEST AND ABSOLUTE PENALTY ESTIMATORS IN PARTIALLY LINEAR MODELS

We consider a partially linear model in which the vector of coefficients β in the linear part can be partitioned as (β1, β2), where β1 is the coefficient vector for main effects (e.g. treatment effect, genetic effects) and β2 is a vector for ‘nuisance’ effects (e.g. age, laboratory). In this situation, inference about β1 may benefit from moving the least squares estimate for the full model in the direction of the least squares estimate without the nuisance variables (Steinian shrinkage), or from dropping the nuisance variables if there is evidence that they do not provide useful information (pretesting). We investigate the asymptotic properties of Stein‐type and pretest semiparametric estimators under quadratic loss and show that, under general conditions, a Stein‐type semiparametric estimator improves on the full model conventional semiparametric least squares estimator. The relative performance of the estimators is examined using asymptotic analysis of quadratic risk functions and it is found that the Stein‐type estimator outperforms the full model estimator uniformly. By contrast, the pretest estimator dominates the least squares estimator only in a small part of the parameter space, which is consistent with the theory. We also consider an absolute penalty‐type estimator for partially linear models and give a Monte Carlo simulation comparison of shrinkage, pretest and the absolute penalty‐type estimators. The comparison shows that the shrinkage method performs better than the absolute penalty‐type estimation method when the dimension of the β2 parameter space is large.
Scale-free animal movement patterns: Lévy walks outperform fractional Brownian motions and fractional Lévy motions in random search scenarios

The movement patterns of a diverse range of animals have scale-free characteristics. These characteristics provide necessary but not sufficient conditions for the presence of movement patterns that can be approximated by Lévy walks. Nevertheless, it has been widely assumed that the occurrence of scale-free animal movements can indeed be attributed to the presence of Lévy walks. This is, in part, because it is known that the super-diffusive properties of Lévy walks can be advantageous in random search scenarios when searchers have little or no prior knowledge of target locations. However, fractional Brownian motions (fBms) and fractional Lévy motions (fLms) are both scale-free and super-diffusive, and so it is possible that these motions rather than Lévy walks underlie some or all occurrences of scale-free animal movement patterns. Here this possibility is examined in numerical simulations through a determination of the searching efficiencies of fBm and fLm searches. It is shown that these searches are less efficient than Lévy walk searches. This finding does not rule out the possibility that some animals with scale-free movement patterns are executing fBm and fLm searches, but it does make Lévy walk searches the more likely possibility.
Artificial Intelligence and Its Ethical Implications for Marketing

Despite the recent developments in AI, ethical questions arise when consumers contemplate how their data is being treated. This paper develops a conceptual model building on the theory of acceptance, risk, trust, and attitudes towards AI to understand the drivers that lead consumers to accept AI, considering consumers' ethical concerns. The model was empirically tested with 200 consumers of AI marketing services. The findings reveal that perceived risk significantly impacts attitudes toward AI, ethical concerns, and perceived trust and suggest a significant association between perceived risk, ethical concerns, and social norms. This research provides important theoretical and managerial implications for the ethical aspects of AI in marketing by highlighting the ethical and moral questions surrounding AI's acceptance. Doi: 10.28991/ESJ-2023-07-02-01 Full Text: PDF