Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring Tourists’ Responsible Behavior: Evidence from Thailand

The study aims to measure tourists’ responsible behavior, and to develop a structural equation model of responsible tourist behavior among Thai tourists. A questionnaire survey was conducted using an online questionnaire. A total of 503 Thai domestic tourists who practiced responsible behavior participated in the study. The data were analyzed through structural equation modeling with a two-stage approach. The results of the analysis revealed a good fit with the empirical data (CMIN/DF = 2.62, RMSEA = 0.06, CFI = 0.94, TLI = 0.92). Moreover, the findings highlight two underlying factors which emerged for responsible behavior, namely impact consideration and local connections. The establishment of an extended Theory of Planned Behavior (TPB) model with two additional predictors including environmental and social concern, and pro-environmental behavior in everyday life, explains the formation of tourists’ responsible behavior. Destination managers and marketers can encourage tourists’ responsible behavior by implementing meaningful experiences with various low-impact tourism activities. Relevant government agencies and policy makers can promote responsible campaigns and events to enhance responsible behavior.
Principios del Aprendizaje Aplicados a los Adultos

El reciente inicio del programa de la ITF para adultos Tennis Xpress nos hace considerar y revisar la forma en la que enseñamos a los adultos a jugar al tenis. Para ello, debemos equilibrar las razones por las cuales los adultos juegan al tenis con el logro de las metas personales y al mismo tiempo, reconocer que son diferentes de los niños y debemos ayudarles a jugar y a amar el juego.
Determinants of Innovation Capability and Nexus between Innovation Capability and Performance of SMEs

Small and medium-sized businesses (SMEs) are essential for the expansion of any economy, and innovation is what ensures their continued success and improved performance. The main objectives of this study are to identify the key factors that influence innovation capability, to ascertain the effect of innovation capability on SMEs' performance, and to examine the role of innovation capability as a mediator between its key determinants and SMEs' performance. Partial least squares structural equation modelling (Smart PLS-SEM) was used in the study to accomplish this purpose, and data from 249 manufacturing SMEs registered at the Hattar Industrialist Association (HIA), Industrial Estate, Khyber Pakhtunkhwa, Pakistan, were used to collect the data. All of the constructs used in the study are valid and trustworthy according to Cronbach's alpha, which measures structural stability. The results show that operational and managerial capabilities are not statistically significant drivers of SMEs' innovation potential, while technological and transactional capabilities are statistically significant predictors of SMEs' innovation capabilities. The results also show that innovative competency has a positive effect on SMEs' success. The study also found that innovation capability plays a statistically significant role in mediating the relationship between technological capabilities and performance as well as the relationship between transactional capacities and performance. But neither the role of innovation capabilities in mediating the link between operational capabilities and performance nor the function of innovation capabilities in mediating the relationship between managerial capabilities and performance are statistically significant. It indicates that in order to improve the performance of SMEs, it is necessary to investigate the attitudes and behaviour of SMEs in order to identify the causes of their lack of management and operational competencies.
“Antecedents promoting e-learner’s engagement behavior: Mediating effect of e-learner’s intention to use behavior”

Abstract Despite the massive growth and benefits of online learning platforms, engaging and retaining learners showcases a major challenge in the present scenario. There is a dearth of literature on measuring the antecedent factors of learner engagement behavior through mediating effect in the online learning context. Therefore, the current study was designed to empirically confirm the factors influencing the learner’s engagement in online learning platforms through the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. The data was collected from 336 learners who have accessed online learning platforms. Structural equation modeling was tested to evaluate the proposed relationships in the conceptual framework. The results identified performance expectancy, facilitating conditions, learner self-efficacy, and e-learner’s intention to use behavior as key antecedents of e-learner’s engagement behavior in the online learning platform. Subsequently, the e-learner’s intention to use behavior played a significant role as a mediator in influencing the e-learner’s engagement. The novelty of the study is to offer statistical significance on limitedly studied phenomena in online learning towards investigating the e-learner’s intention to use behavior as mediation in envisioning e-learner’s engagement behavior. Additionally, the study theoretically contributes to the existing body of literature. Also, the study findings underscore the need for organizations, policymakers, and academic institutions to develop online learning platforms that enhance learners’ engagement behavior.
Biasing Deep ConvNets for Semantic Segmentation of Medical Images with a Prior-driven Prediction Function

Organ segmentation in CT-scans is a major issue in medical image analysis. Recently deep learning methods have brought impressive results for the task of semantic segmentation (Chen et al., 2018; Ronneberger et al., 2015; Long et al., 2015). However it remains very challenging especially due to the visual ambiguities (Kohl et al., 2018). The local visual context is insufficient and including external knowledge could help obtaining a better segmentation. In this paper we address the problem of including prior information about the shape and spatial position of the organs to improve the performance of semantic segmentation. It is particularly relevant in medical imaging where there is conventions on the structure of the images. For example, the position of the patient is always the same (spine at the bottom). The main changes reside on the patient anatomy which slightly varies from one to another. Including such a knowledge by biasing the predictions of Fully Convolutional Networks (FCN) is a difficult problem. Due to weight sharing and pooling operations, FCN models focus on local structures and loose the input position information. Moreover, it has also been highlighted that ConvNets have difficulties succeeding at simple spatial prediction tasks like coordinate transform (Liu et al., 2018). In the medical imaging literature, some methods have been proposed to incorporate such kind of information. For example cascaded networks (Roth et al., 2018) rely on selecting a Region of Interest (RoI) by a first model, which is then finely segmented by a second model. Those methods are efficient but rely on the good localization of the RoI. As a consequence, each step limits the overall performances. Other methods try to incorporate spatial information implicitly. For instance by generating distance maps with a GAN (Trullo et al., 2019) or by learning attention maps through an attention mechanism (Oktay et al., 2018). In those approaches, the spatial information is learned during training so we have no control of what is actually learned and how it biased the prediction.
Endosome Traffic Modulates Pro-Inflammatory Signal Transduction in CD4+ T Cells—Implications for the Pathogenesis of Systemic Lupus Erythematosus

Endocytic recycling regulates the cell surface receptor composition of the plasma membrane. The surface expression levels of the T cell receptor (TCR), in concert with signal transducing co-receptors, regulate T cell responses, such as proliferation, differentiation, and cytokine production. Altered TCR expression contributes to pro-inflammatory skewing, which is a hallmark of autoimmune diseases, such as systemic lupus erythematosus (SLE), defined by a reduced function of regulatory T cells (Tregs) and the expansion of CD4+ helper T (Th) cells. The ensuing secretion of inflammatory cytokines, such as interferon-γ and interleukin (IL)-4, IL-17, IL-21, and IL-23, trigger autoantibody production and tissue infiltration by cells of the adaptive and innate immune system that induce organ damage. Endocytic recycling influences immunological synapse formation by CD4+ T lymphocytes, signal transduction from crosslinked surface receptors through recruitment of adaptor molecules, intracellular traffic of organelles, and the generation of metabolites to support growth, cytokine production, and epigenetic control of DNA replication and gene expression in the cell nucleus. This review will delineate checkpoints of endosome traffic that can be targeted for therapeutic interventions in autoimmune and other disease conditions.
Factors Affecting Transcranial Motor-Evoked Potential Measurements Using Single-Train Stimulation with an Increased Number of Pulses during Adolescent Scoliosis Surgery: A Prospective Observational Study

Measurement of transcranial motor-evoked potentials (TcMEPs) during scoliosis surgery helps detect postoperative new neurological defects. However, TcMEP interpretation is difficult owing to the influence of intraoperative physiological, pharmacological, and time-related factors as well as stimulation conditions. In this study, we aimed to investigate the effect of the abovementioned factors on TcMEP amplitude using single-train stimulation with an increased number of pulses (STS-INP) during adolescent scoliosis surgery; moreover, we evaluated the complications of TcMEP measurement. We included 50 patients and 706 TcMEP measurements. A total of 1412 TcMEP waveforms were analyzed, each on the bilateral abductor pollicis brevis, tibialis anterior, and abductor hallucis muscles. We estimated the mean difference (95% confidence interval (CI)) and predicted mean difference (95% CI) evaluated using the interquartile range of each factor, based on a mixed-effect model with random intercepts for TcMEP amplitude. The predicted mean differences in TcMEP amplitude were clinically small compared with the actual TcMEP amplitude, suggesting that each factor had a limited effect on TcMEP amplitude. No intraoperative bite injuries or seizures were observed. Using STS-INP during adolescent scoliosis surgery may enable accurate measurement of TcMEP amplitude with neither complications nor the influence of various intraoperative factors.
Instructional cues in the teaching of dribbling in school physical education classes

Background and Study Aim. A cue is a short and concise instruction about the key aspects of a successful performance. In addition to an attentional strategy, an instructional cue has been considered as a Physical Education teaching content for developing the students' knowledge about performing motor skills. This study investigated the effects of perceptual and motor instructional cues on the learning of dribbling during physical education classes at school. Material and Methods. The sample comprised 81 students from three elementary full-time classes of a public school, aged between 6 to 9 years old. The study consisted of three experimental groups each one from a given PE classroom: (1) perceptual cue - “eye on the circuit”; (2) motor cue - “pushing the ball at waist level”; and control group – no cue. Results. Results showed that motor cue group improved the performance in relation to all measures (stage of development, ball control, and runtime). In addition, they revealed that this group had superior performance comparatively to perceptual cue and control groups. Conclusions. This study examined the effect of verbal motor cues on students' learning of dribbling in a Physical Education class. The results showed that the verbal motor cue functioned as a useful tool for providing students with information about the correct technique for dribbling. This information helped students to understand and execute the correct technique, resulting in improved dribbling performance. Overall, this study suggests that verbal motor cues can be a valuable teaching tool for Physical Education teachers when designing practice tasks. By selecting instructions that have the potential to improve students' knowledge about performance, teachers can help their students to acquire skills more effectively. These findings have important implications for the design of practice tasks in Physical Education classes and can help to optimize student learning outcomes.
Low-Cost Online Monitoring System for the Etching Process in Fiber Optic Sensors by Computer Vision

The present research exposes a novel methodology to manufacture fiber optic sensors following the etching process by Hydrofluoric Acid deposition through a real-time monitoring diameter measurement by computer vision. This is based on virtual instrumentation developed with the National Instruments® technology and a conventional digital microscope. Here, the system has been tested proving its feasibility by the SMS structure diameter reduction from its original diameter of 125 μ until approximately 42.5 μm. The results obtained have allowed us to demonstrate a stable state behavior of the developed system during the etching process through diameter measurement at three different structure sections. Therefore, this proposal will contribute to the etched fiber optic sensor development that requires reaching an enhanced sensitivity. Finally, to demonstrate the previously mentioned SMS without chemical corrosion, and the etched manufactured SMS, both have been applied as glucose concentration sensors.
Discrete simulations of fluid-driven transport of naturally shaped sediment particles

A numerical scheme is developed to simulate the transport of natural gravel. Starting with computerized tomographic (CT) scans of natural grains, our method approximates the shapes of these grains by “gluing” spheres of different sizes together with overlaps. The conglomerated spheres move using a Discrete Element Method (DEM) which is coupled with a Lattice Boltzmann Method (LBM) fluid solver, forming the first complete workflow from particle shape measurement to high resolution simulations with hundreds of distinct shapes. The simulations are quantitatively benchmarked by flume experiments. The numerical tool is used to further validate a recently proposed modified sediment transport relation, which takes particle shape effects into account, including the competition between hydrodynamic drag and material friction. Unlike a physical experiment, our simulations allow us to vary the hydrodynamic drag coefficient of the natural gravel independently of the material friction. Our studies support the modified sediment transport relation. The simulations also provide insights on the particle-level kinematics, such as particle orientations, in the bedload transport process. Particles below the bed surface prefer to orient with their shortest axes perpendicular to the bed surface, but the tendency goes down as the packing fraction decreases far from the bed surface. The particles rotate freely in the dilute particle flow regime. }
O ct 2 01 3 Volumes and geodesic ball packings to the regular prism tilings iñ

After having investigated the regular prisms and prism tili ngs in the S̃L2R space in the previous work [14] of the second author, we consi der the problem of geodesic ball packings related to those tilin gs and their symmetry groupspq21. S̃L2R is one of the eight Thurston geometries that can be derived from the 3-dimensional Lie group of all 2× 2 real matrices with determinant one. In this paper we consider geodesic spheres and balls iñ SL2R (even in SL2R), if their radii ρ ∈ [0, π2 ), and determine their volumes. Moreover, we consider the prisms of the above space and compute their vo lumes, define the notion of the geodesic ball packing and its density. W e develop a procedure to determine the densities of the densest geodesi c ball packings for the tilings, or in this paper more precisely, for their ge nerating groups ∗Mathematics Subject Classification 2010: 52C17, 52C22, 52B 1 , 53A35, 51M20.
Implementation of a monitoring system for a photovoltaic installation based on IoT technology

In the present work, the monitoring of a grid-connected photovoltaic system of 3.7kW of installed power based on an Internet of Things (IoT) solution is designed and implemented, the monitoring system is implemented in a real facility located in Juliaca, Peru. IoT-based monitoring integrates the data acquisition system (DAQ) of the photovoltaic system, complementing the existing local monitoring with a flexible architecture capable of connecting to different devices and communication environments. The DAQ connects to the IoT-based monitoring system via open-source software, and Microsoft cloud services are also used to visualize the data in real time, as well as to store it. The proposed solution overcomes the challenges faced by a monitoring system of a conventional photovoltaic installation at a low cost.
Highly doped graphene on ion-exchanged glass

Engineering the doping level in graphene is essential to realizing functional electronic and optoelectronic devices. While achieving strong p-doping is relatively straightforward, electrostatic or chemical approaches to negatively dope graphene have yielded electron densities (ns ) of −9.5 × 1012 cm−2 or below. In this work, we demonstrate very high ns (−1013 to −1014 cm−2) in graphene, on an ion-exchanged glass substrate, which is widely used in touch screen displays (e.g. smart phones). Moreover, the proposed method, which is easy to implement and scalable, leads to relatively stable graphene doping, with about a 40% increase in sheet resistance over 5 months at ambient conditions.
Simultaneous correlations in complementary bases as quantitative resource for quantum steering

A hitherto unnoticed feature of quantum steering is demonstrated, namely that, while entanglement is necessary for steering, higher degree of entanglement does not necessarily imply higher degree of quantum steering. This leads to the question as to what aspect of correlation entailed by the quantum state serves as the appropriate quantitative resource for steering. To this end, considering Bell-diagonal states, suitable measures of simultaneous correlations in two and three complementary bases are identified as the relevant quantitative resources for quantum steering involving two- and three-settings respectively. This means that, for steerable Bell-diagonal states, higher value of simultaneous correlations in mutually unbiased bases necessarily implies higher degree of quantum steering.
Mapping the environmental impacts from land subsidence hazard in Pekalongan City and its correlation with the subsurface condition

Land subsidence in Pekalongan city has affected almost the entire municipality for at least ten years. Land subsidence has occurred in almost all Pekalongan city areas at 2-12 cm/year rates. The direct and indirect environmental impacts of land subsidence are enormous. We aim to map the environmental impacts of land subsidence in Pekalongan city and evaluate the severity of the impacts with the subsurface condition of the affected area. We employed site investigation using resistivity and CPTu soundings at representative sites to reveal the subsurface soils and site survey to map the environmental impacts. Resistivity measurements using a Schlumberger array were carried out at 24 sites, along with 12 CPTu measurements up to 30 m deep. Results show that the subsurface condition up to the depth of 30 m consists of alluvial sediment of clay, silt, and organic soils intercalated with lenses of sand. The alluvial sediment in the southern part is dominated by sandy soils and has a higher stiffness with cone resistance of 1-2 MPa and a friction ratio of 50-200 kPa. The subsurface soils in the northern part are dominated by clay, silt, and organic soils with low cone tip resistance of <0.5- 1 MPa, and friction ratio of <0.25-100 kPa. These values indicate that the sandy soils in the southern part are more compact and have higher bearing capacity than the soft, fine-grained soils in the northern area. The visible impacts of land subsidence include flood and inundation, settlement of buildings and roads, and cracks in houses and infrastructure. The severity of impacts worsens from South to North of the city. This condition is related to the subsurface stratification and engineering properties, where lower bearing capacity occurs in the north.
Beyond Metadata: the New Challenges in Mining Scientific Papers

Scientific articles make use of complex argumentative structures whose exploitation from a computational point of view is an important challenge. The exploration of scientific corpora involves methods and techniques from Natural Language Processing in order to develop applications in the field of Information Retrieval, Automatic Synthesis, citation analyses or ontological population. Among the problems that remain to be addressed in this domain is the developing fine-grained analyses of the text content of articles to identify specific semantic categories such as the expression of uncertainty and controversy that are an integral part of the scientific process. The well-known IMRaD structure (Introduction, Methods, Results, and Discussion) is often used as a standard template that governs the structure of articles in experimental sciences and provides clearly identifiable text units. We study the internal structure of articles from several different perspectives and report on the processing of a large sample extracted from the PLOS corpus. On the one hand, we analyse citation contexts with respect to their positions, verbs used and similarities across the different sections, and on the other hand, we study other phenomena such as the expression of uncertainty. The production of standard datasets dedicated to such tasks is now necessary and would provide favourable environment for the development of new approaches, e.g. using neural networks, that require large amounts of labelled data.
Controlled-NOT Gate Interferometer with a Thermal Source

We theoretically demonstrate a multiphoton interferometer able to reproduce, by using only a thermal source, the operation of a quantum logic gate known as controlled-NOT gate. We show how 100%-visibility correlations typical of any Bell state can be obtained by performing polarization correlation measurements in the fluctuation of the number of photons at the interferometer output. The physics of multiphoton interference at the heart of this proposal can be readily used, in general, for the implementation of higher-dimension bosonic networks leading to higher-order entanglementlike correlations.
COVARIANCE BASED MIMO RADAR BEAMFORMING FOR PATTERNS WITH DEEP NULLS

Multiple Input-Multiple Output radar is an emerging technology and has exclusive advantages and flexibilities. In this paper, we propose a method for beampattern synthesis in order to construct a desired pattern which has specific nulls. It is shown that arbitrary cross correlation matrix (R) can be approximated to achieve a desired beam-pattern with a null in a specific direction. Besides constrained convex optimization problem is investigated and it is shown that reconstructed pattern by this matrix requires null at arbitrary angle. Penalty function and barrier methods are applied to solve this constrained convex optimization problem. Finally, power and advantages of our method for beam-pattern synthesizing has been depicted through simulation results.