Miracle-dz/UniFAR-FTUs huggingface dataset:
What promotes smartphone-based mobile commerce? Mobile-specific and self-service characteristics

Purpose Given that smartphones are widely used as a key means for mobile commerce, the purpose of this paper is to provide in-depth understanding of determinants of the utilitarian value that customers seek to obtain from using smartphone-based mobile commerce. Drawing on the technology acceptance model (TAM), the study proposes that usefulness and ease of use are two typical factors representing utilitarian value and verifies their impacts on smartphone-based m-commerce use. Moreover, the paper expands the TAM by considering mobile-specific characteristics (i.e. service ubiquity and location-based service (LBS)) and a self-service technology (SST) characteristic (i.e. user control) as determinants of utilitarian value. Design/methodology/approach The study entailed conducting a survey, and analyses were conducted based on a total of 379 responses from undergraduate and graduate students who had experience using smartphones for mobile commerce. The analyses used structural equation modeling to test the research model and hypotheses. Findings First, in the context of the various technologies-involved m-commerce, TAM serves as a theoretical lens to predict user behavior. Second, usefulness is greatly increased by service ubiquity, LBS, and user control. Third, ease of use is enhanced by service ubiquity and user control. Finally, ease of use is a determinant of usefulness. Originality/value The findings imply that mobile-specific and SST characteristics are the key determinants of utilitarian value in performance-oriented mobile commerce, and utilitarian value is a key determinant of smartphone-based mobile commerce use.
The association between obesity and race among Brazilian adults is dependent on sex and socio-economic status

Abstract Objective To verify the association of race, independent of socio-economic status (SES), with obesity among Brazilian adults. Design We investigated data from the 2008–2009 Brazilian Household Budget Survey. Obesity was defined using the WHO classification. Self-declared race was classified as White, Black and ‘Pardo’ (Brown). Factor analysis with principal component extraction was used to derive the SES index. The association between race and obesity independent of SES, adjusted for demographic variables, was estimated using multiple logistic regression, accounting for the survey design. Interaction term between race and SES was tested. Setting Brazilian households (n 55 970). Subjects Adults aged 20–65 years (n 80 702). Results The prevalence of obesity was 14·9 %. The first factor explained 51 % of the variance and was used as a SES indicator. Odds of obesity increased with increasing SES level for men and for Black women, whereas Brown and White women showed a decrease of obesity. The association between race and obesity was modified by SES level in both sexes. At lower level of SES (−2 sd), Black and Brown in comparison to White men had 35 and 27 % decreased odds of obesity, respectively. For women, at lower SES level, only Black compared with White women had 30 % decreased odds of obesity. At the higher SES level (+2 sd), Black women compared with White presented a threefold increase of obesity. Conclusions Racial disparities in obesity are SES level- and sex-dependent in Brazil. Strategies exclusively targeting reductions in SES disparities are likely ineffective for decreasing racial disparities in obesity among women.
Control Contraction Metrics on Finsler Manifolds

Control Contraction Metrics (CCMs) provide a nonlinear controller design involving an offline search for a Riemannian metric and an online search for a shortest path between the current and desired trajectories. In this paper, we generalize CCMs to Finsler geometry, allowing the use of non-Riemannian metrics. We provide open loop and sampled data controllers. The sampled data control construction presented here does not require real time computation of globally shortest paths, simplifying computation.
3q29 Chromosomal duplication in a neonate with associated myelomeningocele and midline cranial defects.

Departments of Pediatrics, Pathology and Laboratory Medicine, Neurosurgery and Division of Neonatal-Perinatal Medicine, Department of Pediatrics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA Correspondence to Marley B. Lawrence, MD, Department of Pediatrics, UNC Hospitals, 101 Manning Drive, Chapel Hill, NC 27514, USA Fax: + 1 9199667299; e-mail: marley.lawrence@unchealth.unc. edu
Cooperative Transportation Using Small Quadrotors Using Monocular Vision and Inertial Sensing

Micro aerial vehicles have the potential to assist humans in tasks such as manipulation and transportation for construction and humanitarian missions, beyond simply acquiring data and building maps. In this letter, we address the state estimation, control, and trajectory planning in cooperative transportation of structures, which are either too heavy or too big to be carried by small microvehicles. Specifically, we consider small quadrotors, each equipped only with a single camera and inertial measurement unit as a sensor. The key contributions are 1) a new approach to coordinated control, which allows independent control of each vehicle while guaranteeing the system's stability and 2) a new cooperative localization scheme that allows each vehicle to benefit from measurements acquired by other vehicles. The latter relies on the vehicles exploiting the inherent rigid structure information to infer additional constraints between the vehicles’ poses allowing us to formulate the pose estimation problem as an optimization problem on the Lie group $\mathbf {SE(3)}$. The proposed approach is validated through experimental results with multiple quadrotors grasping and transporting a rigid structure.
Real-Time 6DOF Pose Relocalization for Event Cameras With Stacked Spatial LSTM Networks

We present a new method to relocalize the 6DOF pose of an event camera solely based on the event stream. Our method first creates the event image from a list of events that occurs in a very short time interval, then a Stacked Spatial LSTM Network (SP-LSTM) is used to learn the camera pose. Our SP-LSTM is composed of a CNN to learn deep features from the event images and a stack of LSTM to learn spatial dependencies in the image feature space. We show that the spatial dependency plays an important role in the relocalization task with event images and the SP-LSTM can effectively learn this information. The extensively experimental results on a publicly available dataset show that our approach outperforms recent state-of-the-art methods by a substantial margin, as well as generalizes well in challenging training/testing splits. The source code and trained models are available at https://github.com/nqanh/pose_relocalization.
What drives users' intentions to purchase a GPS Navigation app: The moderating role of perceived availability of free substitutes

Purpose Grounded on the value-based adoption model and innovation diffusion theory, this study examined consumer purchase decisions of mobile Global Positioning System (GPS) navigation apps. In addition, this study also investigated the moderating role that perceived availability of free substitutes (PAFS) plays in the relationship between perceived value and purchase intention. The paper aims to discuss these issues. Design/methodology/approach Data collected from 219 mobile users were analyzed against the research model using the partial least squares approach. Findings The results showed that compatibility, relative advantage, perceived enjoyment, perceived cost (positively), and complexity (negatively) influenced these users’ value perceptions and purchase decisions. Furthermore, PAFS significantly weakened the positive relationship between perceived value and purchase intentions. Practical implications Based on these findings, the authors provide practical suggestions for mobile app developers to increase mobile app sales. This study also helps advance knowledge of mobile internet marketing. Originality/value This study is a pioneering effort in explaining consumer purchase intentions in the context of mobile GPS navigation app.
Face Feature Extraction: A Complete Review

Feature extraction is vital for face recognition. In this paper, we focus on the general feature extraction framework for robust face recognition. We collect about 300 papers regarding face feature extraction. While some works apply handcrafted features, other works employ statistical learning methods. We believe that a general framework for face feature extraction consists of four major components: filtering, encoding, spatial pooling, and holistic representation. We analyze each component in detail. Each component could be applied in a task with multiple levels. Then, we provide a brief review of deep learning networks, which can be seen as a hierarchical extension of the framework above. Finally, we provide a detailed performance comparison of various features on LFW and FERET face database.
Learning Patterns and Pattern Sequences by Self-Organizing Nets of Threshold Elements

Various information-processing capabilities of self-organizing nets of threshold elements are studied. A self-organizing net, learning from patterns or pattern sequences given from outside as stimuli, "remembers" some of them as stable equilibrium states or state-transition sequences of the net. A condition where many patterns and pattern sequences are remembered in a net at the same time is shown. The stability degree of their remembrance and recalling under noise disturbances is investigated theoretically. For this purpose, the stability of state transition in an autonomous logical net of threshold elements is studied by the use of characteristics of threshold elements.
Deep Neural Networks as Gaussian Processes

It has long been known that a single-layer fully-connected neural network with an i.i. d. prior over its parameters is equivalent to a Gaussian process (GP), in the limit of infinite network width. This correspondence enables exact Bayesian inference for infinite width neural networks on regression tasks by means of evaluating the corresponding GP. Recently, kernel functions which mimic multi-layer random neural networks have been developed, but only outside of a Bayesian framework. As such, previous work has not identified that these kernels can be used as covariance functions for GPs and allow fully Bayesian prediction with a deep neural network. In this work, we derive the exact equivalence between infinitely wide deep networks and GPs. We further develop a computationally efficient pipeline to compute the covariance function for these GPs. We then use the resulting GPs to perform Bayesian inference for wide deep neural networks on MNIST and CIFAR-10. We observe that trained neural network accuracy approaches that of the corresponding GP with increasing layer width, and that the GP uncertainty is strongly correlated with trained network prediction error. We further find that test performance increases as finite-width trained networks are made wider and more similar to a GP, and thus that GP predictions typically outperform those of finite-width networks. Finally we connect the performance of these GPs to the recent theory of signal propagation in random neural networks.
Development of MQYY: A 90-mm NbTi Double Aperture Quadrupole Magnet for HL-LHC

In the context of the HL-LHC project, a NbTi double aperture quadrupole magnet called MQYY is being developed. This 90-mm-aperture quadrupole magnet has a magnetic length of 3.67 m and an operating gradient of 120 T/m at 1.9 K. Its development is done along two parallel paths: 1) the design, fabrication, and test of a short model; 2) the design and fabrication of two full-scale prototypes in industry within the H2020 EU Pre-Commercial Procurement project QUACO implemented by CERN, CEA, CIEMAT, and NCBJ. We report here on the short-model design choices the status of its fabrication and the preparation of the tests. In particular, we describe the magnetic and mechanical design relying on self-supporting collars, the protection aspects, the fabrication, and the cold test preparation. Finally, we present the unusual scheme of the QUACO project leading to the prototypes fabrication.
Association of SNP rs1867277 in FOXE1 Gene and Cleft Lip with or without Cleft Palate in a Han Chinese Population

ABSTRACT Background: The genetic factors causing cleft lip with or without cleft palate (CL ± P) are still unclear. The SNPs in FOXE1 gene were associated with CL ± P. However, the results have been inconsistent. Objective: We explored the associations of four SNPs in FOXE1 gene and CL ± P by a family based study. Materials and Methods: 128 children with CL ± P and their parents were recruited. rs3758249 and rs1867277 were genotyped by high-resolution melting curve (HRM) method, whereas rs1443434 and rs907577 were genotyped by Sequenom MassARRAY® method. The software PLINK, FBAT and FAMHAP were used for analyzing data. Results: rs1867277 was associated with CL ± P (Pm = 0.0395). The patients were divided into two subgroups, individuals with cleft lip only and persons with cleft lip and palate. There were no associations in subgroup analyses. Conclusion: We confirmed the association of FOXE1 gene and CL ± P by a family based study. For the first time, rs1867277 was significantly associated with CL ± P.
Estimation of accumulated oxygen deficit from accumulated blood lactate concentration during supramaximal running in middle-distance runners

The maximal accumulated oxygen deficit (MAOD), which is the gold standard for anaerobic energy metabolism capacity, requires multiple tests for evaluation that impose a heavy load on subjects. The maximal accumulated blood lactate (ΔbLa) concentration is also a measure of anaerobic energy metabolism capacity, and is related to the accumulated oxygen deficit (AOD). Thus, AOD has been estimated by using ΔbLa (3.0 mLO2 · kg−1 ·mM−1), but it is unclear if this coefficient is suitable for measurement of supramaximal running of athletes. The purpose of this study was to clarify the estimated expression of AOD by using ΔbLa from the relationship between MAOD and ΔbLa during supramaximal running in middle-distance runners. Eleven male middle-distance runners (800m running velocity: 425.3 ± 7.3 m·min−1) took part in this study. They performed three running tests (maximal, submaximal and supramaximal running test) to evaluate MAOD and ΔbLa. MAOD and ΔbLa were 56.6 ± 6.0 mLO2 · kg−1 and 9.9 ± 1.1 mmol ·L−1, respectively. We observed a significant positive relationship between MAOD and ΔbLa (r = 0.73); the regression line equation was y = 3.58x + 18.6. Results showed that the AOD per mM of the ΔbLa of athletes was 3.58 mLO2 · kg−1, which was 19% higher than the conventional coefficient value.
Consensus Forecasting of Species Distributions: The Effects of Niche Model Performance and Niche Properties

Ensemble forecasting is advocated as a way of reducing uncertainty in species distribution modeling (SDM). This is because it is expected to balance accuracy and robustness of SDM models. However, there are little available data regarding the spatial similarity of the combined distribution maps generated by different consensus approaches. Here, using eight niche-based models, nine split-sample calibration bouts (or nine random model-training subsets), and nine climate change scenarios, the distributions of 32 forest tree species in China were simulated under current and future climate conditions. The forecasting ensembles were combined to determine final consensual prediction maps for target species using three simple consensus approaches (average, frequency, and median [PCA]). Species’ geographic ranges changed (area change and shifting distance) in response to climate change, but the three consensual projections did not differ significantly with respect to how much or in which direction, but they did differ with respect to the spatial similarity of the three consensual predictions. Incongruent areas were observed primarily at the edges of species’ ranges. Multiple stepwise regression models showed the three factors (niche marginality and specialization, and niche model accuracy) to be related to the observed variations in consensual prediction maps among consensus approaches. Spatial correspondence among prediction maps was the highest when niche model accuracy was high and marginality and specialization were low. The difference in spatial predictions suggested that more attention should be paid to the range of spatial uncertainty before any decisions regarding specialist species can be made based on map outputs. The niche properties and single-model predictive performance provide promising insights that may further understanding of uncertainties in SDM.
“Somebody Who Was on My Side”

Youth initiated mentoring (YIM) is an innovative approach to mentoring being implemented by the National Guard Youth ChalleNGe Program in which youth identify and select their mentors. There is great interest in this approach; however, there has been little study of YIM or its implementation in ChalleNGe. Retrospective in-depth qualitative interviews with former ChalleNGe participants (n = 30) were conducted to gain a descriptive understanding of the mentor selection process, the role these relationships played in participants’ experiences of the ChalleNGe program and in their lives more generally, and the nature and strength of these connections. Findings indicate that youth were able to successfully enlist the participation of mentors and YIM yielded enduring and emotionally supportive relationships. That the adults came from within their communities was viewed by these participants as having expedited the development of feelings of trust and contributed to the relevancy and meaningfulness of the guidance and advice offered.
Swept under the carpet: organic matter burial decreases global ocean biogeochemical model sensitivity to remineralization length scale

Although of substantial importance for marine tracer distributions and eventually global carbon, oxygen, and nitrogen fluxes, the interaction between sinking and remineralization of organic matter, benthic fluxes and burial is not always represented consistently in global biogeochemical models. We here aim to investigate the relationships between these processes with a suite of global biogeochemical models, each simulated over millennia, and compared against observed distributions of pelagic tracers and benthic and pelagic fluxes. We concentrate on the representation of sediment–water interactions in common numerical models, and investigate their potential impact on simulated global sediment–water fluxes and nutrient and oxygen distributions. We find that model configurations with benthic burial simulate global oxygen well over a wide range of possible sinking flux parameterizations, making the model more robust with regard to uncertainties about the remineralization length scale. On a global scale, burial mostly affects oxygen in the meso- to bathypelagic zone. While all model types show an almost identical fit to observed pelagic particle flux, and the same sensitivity to particle sinking speed, comparison to observational estimates of benthic fluxes reveals a more complex pattern, but definite interpretation is not straightforward because of heterogeneous data distribution and methodology. Still, evaluating model results against observed pelagic and benthic fluxes of organic matter can complement model assessments based on more traditional tracers such as nutrients or oxygen. Based on a combined metric of dissolved tracers and biogeochemical fluxes, we here identify two model descriptions of burial as suitable candidates for further experiments and eventual model refinements.
Calf muscle density is independently associated with physical function in overweight and obese older adults

Objectives: To determine whether associations of calf muscle density with physical function are independent of other determinants of functional decline in overweight and obese older adults. Methods: This was a secondary analysis of a cross-sectional study of 85 community-dwelling overweight and obese adults (mean±SD age 62.8±7.9 years; BMI 32.3±6.1 kg/m2; 58% women). Peripheral quantitative computed tomography assessed mid-calf muscle density (66% tibial length) and dual-energy X-ray absorptiometry determined visceral fat area. Fasting glucose, Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) and C-reactive protein (CRP) were analysed. Physical function assessments included hand grip and knee extension strength, balance path length (computerised posturography), stair climb test, Short Physical Performance Battery (SPPB) and self-reported falls efficacy (Modified Falls Efficacy Scale; M-FES). Results: Visceral fat area, not muscle density, was independently associated with CRP and fasting glucose (B=0.025; 95% CI 0.009-0.042 and B=0.009; 0.001-0.017, respectively). Nevertheless, higher muscle density was independently associated with lower path length and stair climb time, and higher SPPB and M-FES scores (all P<0.05). Visceral fat area, fasting glucose and CRP did not mediate these associations. Conclusions: Higher calf muscle density predicts better physical function in overweight and obese older adults independent of insulin resistance, visceral adiposity or inflammation.
A Competency Model for "Industrie 4.0" Employees

This paper analyzes employee competencies for employees with higher education in Industry 4.0. An Industry 4.0 competency model based on a behavioral oriented approach concerning three variants, namely Information Systems, Information Technology and Engineering is developed by extending the SHL Universal Competency Framework through a structured literature review and focus groups with academic staff. The presented study contributes to research by providing a starting-point for further research regarding employee competencies for Industry 4.0. It contributes to practice as the provided competency model can be applied to Industry 4.0 job descriptions.
SIMULATION OF 3D ISOTHERMAL FLOW IN INTERMESHING CO-ROTATING TRI-SCREW EXTRUDERS

Three-dimensional isothermal flow of polymer melt in the kneading-disc element of an intermeshing co-rotating tri-screw extruder was simulated by using finite element package POLYFLOW. Based on the velocity fields calculated, flow patterns of the melt were analyzed, and particle trajectories were visualized. The numerical results indicated that, in intermeshing co-rotating tri-screw extruders,particles went through three intermeshing regions during one cycle around the screws, thus achieving better plasticating and mixing than intermeshing co-rotating twin-screw extruders. Flow in the central region was also studied by using particle tracking technique,and residence time distribution (RTD) and trajectories for particles in this region were presented. The simulation results showed that there was no stagnation in the central region. This study provided a clear insight into the flow mechanism of tri-screw extrusion. It also provided a new method for studies of flow mechanisms in other complicated mixers.