Miracle-dz/UniFAR-FTUs huggingface dataset:
A Framework for Studying Programming Teaching in Secondary Education

This study reviews extensively the literature on teaching programming to middle schoolers, with qualitative content analysis method, and basically intends to put forth a research design framework for researchers that will guide them in the processes of planning and designing their research on teaching programming for middle school learners. For access to the relevant literature; the databases were searched by using key words “computer”, “programming”, and “middle school” together limiting the findings to the articles published after 2000. As a result, an upward tendency was noted in studies about teaching of programming at secondary level considering years, most of which are comprised of empirical ones. Also, the existing studies were mostly carried out with 6th graders predominantly employing data collection tools of questionnaires/scales and achievement tests. As for programming tools, Scratch was seen to be the most commonly used one. Although there are quite a few articles investigating the context of the programming teaching lesson, some of the studies were found to use programming as a means of teaching mathematics, natural sciences, languages, writing skills, and social sciences. In conclusion, the present study is expected to pave the way for future research by highlighting the overall situation of programming teaching.
Ultrasonic Absorption and Dispersion in Cholesteryl Esters

Abstract Propagation of ultrasonic longitudinal waves at frequencies from 10 to 70 MHz was studied in three 18-carbon unsaturated fatty acid esters of cholesterol-cholesteryl oleate (CO), cholesteryl linoleate (CL), and cholesteryl linolenate (CLn)-and three mixtures of the esters-80%CL-20%CO, 95%CL-5%CO, and 80%CLn-20%CO. The study was made in temperature ranges over which all systems exhibited the isotropic, cholesteric, and smectic states. Measurements of the ultrasonic attenuation coefficient and velocity of propagation of longitudinal waves were made by a variable pathlength pulse transmission technique. Density measurements as a function of temperature were also made.
Study of Heavy Metal Speciation in Sediments Impacted with Crude Oil in the Niger Delta, Nigeria

Sequential chemical extraction was used to assess trace metal speciation and availability in sediments from Abalagada-Aboh catchments in the Niger Delta that have received significant impact of crude oil spillage. The proportions of trace metals in the various geochemical fractions were variable. The result of speciation among the five geochemical fractions indicates that Cd was associated with easily exchangeable/adsorbed and carbonate fractions, Cu and Cr predominantly to organic and residual fraction, Pb was associated with Fe-Mn oxides and carbonate fractions, Ni to residual and Fe-Mn oxides, Mn was associated with Fe-Mn oxides and residual and Zn was associated with carbonate and Fe-Mn oxide fractions. The data revealed that Cd, Pb, Zn and Ni have high mobility indices and are thus relatively labile and bioavailable to aquatic flora and fauna.
Heterogeneity in effective VAT rates across native and migrant households in France, Germany and Spain

This paper contributes to the literature on the distributional properties of VAT analysing who bears higher VAT payments between native and migrant household in France, Germany and Spain. The question is of interest both from a distributional and fiscal perspective, fitting the ongoing debate of the net fiscal impact of immigration. Using data from the 2010 EU HBS and a simple VAT calculator we show the existence of gaps in effective VAT rates between native and migrant households in France and in Spain, while no significant gap is observed in Germany. Our results also confirm the existing evidence on the regressivity of VAT with respect to income. These findings suggest that the fairness consequences of VAT reforms should be carefully assessed and advocate for the importance of considering indirect taxation when assessing the fiscal cost of migration.
Resistive switching characteristics of sol–gel based ZnO nanorods fabricated on flexible substrates

The authors report the resistive switching characteristics of sol–gel based ZnO nanorods (NRs) fabricated on flexible substrates. A resistance ratio of 10, endurance of over 100 cycles, and narrower dispersion in the ON/OFF voltages and resistances compared to ZnO thin‐film devices are demonstrated. Furthermore, the resistive switching characteristics on flexible substrates are maintained under severe substrate bending because of the ductile properties of the nanorods. Devices composed of the Au/sol–gel based NRs/Au structure have the potential for low‐temperature flexible nonvolatile memory applications. (© 2013 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)
Ultrasonic velocity and attenuation in an epoxy matrix containing lead inclusions

The single-scattering theory of Ying and Truell (1956) is compared with measurements of Kinra et al. (1982) on an epoxy matrix with lead inclusions in the form of spheres with radius a=600 mu m. Experiments on samples with 5% concentration of inclusion are in reasonable agreement with single-scatterer theory. However, measurements on samples with 15% lead show important deviations which are interpreted as being due to multiple-scattering effects. Oscillations in the ultrasonic velocity dispersion are correlated with oscillations in the ultrasonic attenuation. This correlation is discussed within the context of the Kramers-Kronig relations, relating the real and imaginary parts of the ultrasonic wavenumber.
Action Recognition of Excavator by Deep Learning Using Simulated Training Data

Measuring and recording an action performed by construction machinery is a very effective task for improving productivity of construction sites. However, measuring and recording the action by construction machinery is time consuming and expensive because the construction site managers have to observe and record data manually. Therefore, it is important to automatically recognize the action of construction machinery. Action recognition is achieved with high performance on humans using deep learning techniques but those approaches require large amounts of training data. There is no data set for action recognition of construction machinery. Therefore, the proposed method uses training data generated from a simulator. In this study, action recognition is performed for excavator that is most commonly used at construction sites. Experiments were conducted with a remote control excavator in laboratory conditions.
Quasi-aligned Ga2O3 nanowires grown on brass wire meshes and their electrical and field-emission properties

Quasi-aligned beta-Ga2O3 nanowires were fabricated using the brass wire meshes as the substrates. The nanowire roots were tightly connected to the brass wire surfaces that resulted in a very good physical and electrical contact. Electrical measurements showed that the ohmic contacts were achieved and the resistivities of the nanowires were 300-500 Omega.cm. The Ga2O3 nanowire/brass wire hybrid structures exhibited an enhanced field-emission performance. A turn-on field of similar to 6.2 V.mu m(-1) at an emission current density of 10 mu A.cm(-2) and an emission current fluctuation within +/-13% at a mean field-emission current density of similar to 0.56 mu A.cm(-2) were measured.
Recognizing Influential Nodes in Social Networks With Controllability and Observability

The analysis for social networks, such as the sensor-networks in socially networked industries, has shown a deep influence of intelligent information processing technology on industrial systems. The large amounts of data on these networks raise the urgent demands of analyzing the topological content effectively and efficiently in Industrial Internet of Things. One of the ways to locate important information amongst such large troves of data is to recognize influential nodes. In this article, we examine an intelligent way to recognize the influence of such nodes automatically. Motivated by the concepts of system controllability and observability from control theory, we introduce a novel method to evaluate nodes from two different aspects, namely, the ability of “observe” information on the network (i.e., observability), and the ability to propagate information to other nodes (i.e., controllability). We propose a unified data mining framework that incorporates content analysis with nodes behavioral tendencies, and show that it is able to outperform competitive baselines in recognizing influential nodes in networks. We also show that it is important to detect the presence of spammer nodes within networks, which might otherwise be wrongly recognized as influential nodes. The experimental results demonstrate the superiority of the proposed approach in comparison with baseline methods.
Digital twin of mechatronic drive based on the optimal control model of BLDC motor

This paper presents a digital twin of a mechatronic drive based on a brushless DC (BLDC) motor model based on a nonlinear discrete optimal control model. Some parameters of a BLDC motor, such as resistance and inductance of windings, magnetic flux, viscous friction coefficient in bearings, angular velocity and electromagnetic moment, can change due to both degradation of structural elements and external forces. Simulation by a complete enumeration of the values of the parameters of the mechatronic device with a certain step will make it possible to adapt the program of the control device to changing operating conditions according to the criterion of minimizing the control energy by changing the parameters of the state matrices and control of the digital twin. As a result, the accuracy of the movement of the mechatronic device along the given trajectory will increase due to the greater correspondence of the control parameters to the real object.
Moving Target Surrounding Control of Linear Multiagent Systems With Input Saturation

Formation control finds broad applications in numerous fields, such as cooperative detection, surveillance, transportation, and disaster rescue. In this article, aiming at hunting a moving target, a two-stage surrounding control algorithm is proposed for linear multiagent systems subject to input saturations. An adaptive distributed observer is developed for each agent to reconstruct the target’s position. With the assistance of the algebraic graph theory and low gain feedback technique, distributed controllers are designed to drive the agents to encircle the moving target with a fixed radius and evenly distributed phase angles. Finally, both numerical simulations and experiments are conducted to verify the effectiveness of the proposed control algorithm.
A Robust Data-Driven Approach for Fault Detection in Photovoltaic Arrays

In this paper, a robust data-driven method for fault detection in photovoltaic (PV) arrays is proposed. Our method is based on the random vector functional-link networks (RVFLN) which has the advantage of randomly assigning hidden layer parameters with no tuning. To eliminate the effect of measurement noise and overfitting in the training process which reduce the fault detection accuracy, the sparseregularization method is utilized which uses l2−norm with loss weighting factor to compute the output weights. To attain a strong robustness against the outlier samples, the non-parametric kernel density estimation is employed to assign a loss weighting factor. Through rigorous simulation studies, we validate the performance of our proposed method in detecting the short and open circuit faults based on only the output current and voltage measurements of PV arrays. In addition to a stronger robustness comparing with the least square-support vector machine, we also show that our proposed method provides 80% and 100% average detection accuracy for short circuit and open circuit, respectively.
SBGen: A Framework to Efficiently Supply Runtime Information for a Learning-Based HIDS for Multiple Virtual Machines

Much compelling evidence urges that the isolation provided by the hypervisor in a virtualized system is not complete at all, and in practice can be neutralized by elaborated adversaries, which consequently emphasizes the need of techniques to detect attacks on the guest VM kernels. In this regard, learning-based HIDSs have received much attention, which inspect the internals of each VM through monitoring models built by machine learning techniques. The inspection capability of learningbased HIDSs depends on the quality of the monitoring models, which in turn can be improved by using rich runtime information reflecting the exact behavior of VMs. However, as extracting such runtime behavior information is onerous on account of its vast quantity, many learning-based HIDSs have resorted to using only fragmentary runtime behavior information. To address this problem, in this paper, we present SBGen, a framework for efficient extraction of rich runtime behavior information of VMs, namely the system call traces and the execution paths of the kernel taken to serve system calls. To trace execution of the kernel efficiently, SBGen leverages a salient hardware feature, Intel Processor Trace (PT). Once receiving the execution of the kernel traces from PT, SBGen elaborately decodes and purifies them to extract execution paths of the kernel associated with system calls. The extracted runtime behavior information of VMs is fed into learning-based HIDSs to improve their detection accuracy. Our experiments show that SBGen can extract and supply runtime behavior information efficiently enough for learning-based HIDSs to detect in a timely fashion real-world attacks on the guest VM kernels running in a virtualized system, while incurring a reasonable amount of performance overhead. INDEX TERMS Intel Processor Trace (PT), Learning-based HIDS, VM monitoring, Extraction of runtime behavior information, Guest VM kernel execution traces
The operation of the semiconductor‐insulator‐semiconductor solar cell: Experiment

We have reported on the theory of semiconductor‐insulator‐semiconductor (SIS) solar cells in a previous publication. In this paper, the fabrication and properties of indium tin oxide/p‐Si single‐crystal solar cells will be described. The ITO is deposited by the ion‐beam sputtering method. Best photovoltaic devices are obtained when the composition of indium tin oxide (ITO) is 91 mole% and 9 mole% SnO2. The device properties as a function of the ITO composition will be described. The thickness and the composition of the oxide‐silicon interface is critical for device performance. The existence of a thin interfacial layer is demonstrated by Auger spectroscopy. The effect of temperature on device performance and the spectral response are compared with the theory. The SIS model accurately matches the major trends observed in experimental nITO/p‐Si solar cells.
Has the Objective of the Corporate Firm Changed Over Time

This paper argues that despite changes in the technological and the business environment, with new concerns placed on people and planet in addition to profits, the objective of the public firm remains the same as it always has been �? to maximize common shareholder wealth. We address the relevance of the old objective of the public firm in the current era of shareholder activism, instant social media, a discriminating customer base that wants products that do not destroy the planet, and the advent of corporate social responsibility. We suggest that although the world has changed, the age-old mantra of the objective of the firm remains unchanged. The business environment facing public firms has changed considerably over the last few decades, and firms have to manage the process of efficiently navigating these choppy waters.
Numerical investigation on water exchange of shale samples

Interest in the hydraulic and mechanical characterization of shales has grown in recent years, because of their application in the context of energy geotechnics. In the frame of nuclear waste disposal shales are considered as host formations for the placements of nuclear waste at high depths. In the frame of hydrocarbon production they are considered as unconventional reservoirs, from which extracting natural gas. Understanding how fluids flow through shales is then a key aspect for both fields of application. This paper focuses on the analysis of the transport of water vapour through laboratory samples. After reviewing the balance and flow laws that govern the transport of fluid in unsaturated porous media, a simplified model is put forward. The model was implemented in a commercial finite element code, and it was used to reproduce the results of a literature study on wetting and drying of Opalinus Clay shale samples, imposed through the vapour equilibrium technique. Back analysis of the water content and volume strains of these specimens suggests that existing models underestimate the actual flow rate of water vapour which takes place at low suctions. The current interpretation also seems to be consistent with microstructural investigations on the interconnection between large pores of this material.
Research on passenger flow forecast of Urban Rail Transit

Urban rail transit has the characteristics of large traffic volume, fast and convenient, so it has become the urban passenger transport mode which is given priority in the planning and design of each city. The prediction and analysis of rail transit passenger flow is a very important part in the planning and design stage. And it also provides important basic data for urban rail planning, construction and operation. When the rail transit network needs to be adjusted, the passenger flow forecast is also an essential step. In this paper, Taking Dongguan urban rail transit line 2 as an example, based on the full consideration of the uniqueness of Dongguan urban rail transit and the prediction of various social and economic indicators of Dongguan City, the “four step method” is adopted to forecast passenger flow. Through the investigation of resident’s travel survey, we can master the current travel distribution of all modes. Based on the analysis of land use change, traffic development policy and related influencing factors of Dongguan City, the trip distribution of each characteristic year is predicted. Then, the OD matrix of public transport (including subway and conventional public transport) is obtained through the study of traffic mode division model, and the predicted rail passenger flow is obtained through the allocation model of cooperation and competition. In the stage of passenger flow assignment, the influence of various factors on travel route selection is comprehensively considered in the public transport allocation model. Finally, the prediction index and sensitivity of rail passenger flow are analyzed.
Molecular dynamics simulations of water wires in a lipid bilayer and water/octane model systems

A series of classical molecular dynamics simulations of a water wire in a DPPC bilayer yielded lifetimes τ of up to 90 ps, with τ=37±8 ps (not including a significant fraction wires that broke during equilibration). This is sufficiently long to conduct protons across the bilayer through a quantum mechanical hopping mechanism, similar to proton conduction in ice. Lifetimes of wires in the octane region of a water/octane/water “sandwich” were qualitatively similar (τ=36±3 ps) though wires were rarely lost during equilibration. Hence, the utility of the water/octane system as a membrane surrogate depends on the application.
Central location and risk of imaging occult mediastinal lymph node involvement in cN0T2-4 non-small cell lung cancer

Background Appropriate pre-operative staging is a cornerstone in the treatment of non-small cell lung cancer (NSCLC). Central location and size greater than 3 cm are amongst indications for pre-operative invasive mediastinal staging but the quality of the evidence behind this recommendation is low. Methods We retrospectively reviewed all cases of cT2-4N0M0 NSCLCL after CT and TEP-CT which underwent surgical resection with lymph node dissection or had a positive invasive pre-operative mediastinal staging in our institution from 2014 to 2018. Results Three hundred and ten patients met inclusion criteria, 79 (25.5%) central and 231 (74.5%) peripheral tumors. Central tumor location was associated with a higher prevalence of pN2-3 disease (17.7% vs. 6.1%, P<0.001). In a multivariate analysis, central tumor location remained the only factor statistically associated with imaging occult mediastinal disease (OR 3.23, 95% CI: 1.45–7.18). NPV of PET-CT for occult mediastinal disease was 0.83 (95% CI: 0.72–0.90) in central and 0.94 (95% CI: 0.90–0.97) in peripheral tumor. Central location was also associated with a higher prevalence of occult N1 to N3 disease (43.0% vs. 15.2%, P<0.001). Conclusions This study suggests that invasive mediastinal staging is required in central cT2-4N0 NSCLC but can be questioned in peripheral one, especially in cT2N2 subgroup if the patient is a candidate for lobar resection.
Neural Learning Control of a Robotic Manipulator with Finite-Time Convergence in the Presence of Unknown Backlash-Like Hysteresis

A neural learning-based finite-time control policy is presented for a robotic manipulator with unknown backlash-like hysteresis and system uncertainties. Adaptive neural networks are adopted to deal with unknown robotic dynamics. In order to eliminate the effect of unknown backlash-like hysteresis, a robust adaptive term is designed in the backstepping design process. A neural network-based finite-time controller is designed by introducing a fractional order term, which guarantees the finite-time convergence of both neural networks and adaptive terms, and this type of convergence improves control accuracy to a certain extent. With the Lyapunov stability theory, the proposed scheme can be proved to make the errors be semiglobally finite-time stable (SGFTS). The effectiveness of the proposed control is shown by simulation and experimental results.
Effects of chronotype and sleep duration on life quality and psychopathology in childhood obesity.

INTRODUCTION Childhood obesity is associated with various levels of deterioration in the quality of life and many serious medical conditions such as psychiatric problems. AIM The objectives of this study are to investigate whether a difference in terms of chronotype among obese and non-obese children and adolescents, and restricted sleep duration, is associated with obesity and whether chronotype and sleep duration in children and adolescents with obesity are associated with quality of life and comorbid psychiatric disorders. MATERIAL AND METHODS Forty-two participants diagnosed with childhood obesity were included in the study as the study group, and thirty-five participants without childhood obesity were included as the control group. Participants and their parents completed the Questionnaire for Measuring Health-Related Quality of Life in Children and Adolescents, the Development and Well-Being Assessment, and the Childhood Chronotype Questionnaire. The duration of sleep of the participants was also provided by the parent's reporting within the scope of the study. RESULTS Sleep duration was an independent risk factor for becoming obese and had a significant effect on the number of comorbid psychiatric disorders independently of the morning-evening scale score. CONCLUSIONS Unlike the chronotype, this study provided important evidence that sleep duration was associated with the development of obesity and the quantity of comorbid psychiatric disorders.