Miracle-dz/UniFAR-FTUs huggingface dataset:
The impact financial resources on implementation of large-scale electronic health records in the Saudi Arabia's primary healthcare centers: Mixed methods

Introduction There is worldwide demand for the implementation of electronic health systems and a transformation to electronic transactions in healthcare organizations. This move to e-health transformation stems from the perceived positive impact that e-health systems have in improving the quality of healthcare and, in turn, reducing expenses. Despite this, more than half of previous Electronic Health Record System (EHRS) implementation projects have failed due to several barriers and challenges such as cost. Aim of the study To evaluate the impact of financial resources (FR) on the implementation of the EHRS in PHCs in SA. Methods A mixed methods approach was implemented. SPSS and AMOS-SEM are used to test reliability and validity and hypotheses. Thirty-one (59%) out of 51 policy makers at the MoH filled and returned the questionnaire while 13 policymakers were interviewed using semi-structure interviews. Results Results revealed that both measurement model and structural models met the threshold. All scales are found reliable and valid. Furthermore financial resources have positive impact on EHRS implementation. Findings from both studies show that financial resources have a very positive impact to facilitate large-scale EHRs implementation and overcome barriers that may lead to the failure of the project.
Diet self-management: A qualitative study of college students' experiences and perspectives

Background Overweight and obesity among college students have become an emergent public health concern, which may be effectively prevented by diet self-management (DSM). The purpose of this explorative study was to explore college students' experiences and perspectives on diet self-management (DSM), as well as its influencing factors. Method Thirty-three college students were recruited from different universities in China. A qualitative method was used to conduct semi-structured interviews with audio recording to explore their DSM experience and factors that influence DSM. Data were analyzed using thematic analysis to develop themes related to DSM. Result In the perception of what "good DSM" means, three themes and ten subthemes were identified: characteristics of good DSM (including 5 subthemes: regularity, balanced diet, no picky eating, good eating habits, and scientificity), method of good DSM (including three subthemes: self-control, adjusting, and making plans), and content of good DSM (including two subthemes: nutrition management and safety management). The influencing factors of DSM can be categorized into four levels of themes and 34 subthemes: individual, family, school, and social levels. Conclusion The results of this qualitative research highlighted the complexity and multi-dimension of DSM and its influencing factors. Our findings may help to inform diverse and needs-based intervention approaches to improve DSM and promote healthy diet among college students so as to prevent overweight and obesity.
Resonance-free frequency response of a semiconductor laser

We show experimentally and analytically that fast spontaneous recombination lifetime, τB,spon, leads to resonance-free frequency response in semiconductor lasers, and as a consequence higher speed operation. Faster τB,spon is obtained by a reverse-bias collector field pinning and tilting a dynamic (removable) charge population in a thin base (τt∼ps), allowing only “fast” recombination. We show resonance-free optical response on a prototype transistor laser (TL) with τB,spon∼29 ps. Based on the TL, a resonance-free tilted-charge diode laser, is demonstrated with a 10.3 Gb/s “clean open-eye” signal achieved with a −3 dB bandwidth device of only 5.6 GHz.
Inter ocean basin moisture fluxes and the onset of the summer rainy season over southern Mexico

The onset of the rainy season in monsoonal climates is a key element for the development of water related activities. In southern Mexico, it starts in late May or early June, while in western and northwestern part of the country in begins between early and mid-July. Previous studies indicate that it depends on the meridional position of the eastern Pacific Inter Tropical Convergence Zone (ITCZ). By mean of analyses of the Vertically Integrated Moisture Flux, the low level atmospheric dynamics in the tropical Americas is analyzed to establish the temporal evolution of inter ocean moisture fluxes that lead to the onset of the summer rainy season in southern Mexico. The onset of the rainy season depends on the longitudinal position of the center of maximum convective activity in the ITCZ, which induces a quasi-stationary low-level cyclonic circulation that results in moisture fluxes to the Mexican Pacific coast and rains. The Caribbean Low-Level Jet (CLLJ) is a mechanism that modulates inter ocean basin moisture fluxes into the eastern Pacific ITCZ and the location of the maximum convective activity in this system. We propose that the sequence of events that leads to the onset of the rainy season in southern Mexico is: (i) an episode of strong moisture flux from the Caribbean Sea into the eastern Pacific ITCZ, (ii) a region of intense convective activity in the ITCZ that triggers a quasi-stationary low-level cyclonic circulation which in turn, induces moisture flux into southern Mexico, and (iii) the development of convective activity in southern Mexico that determines the onset of the rainy season. The intensification of the CLLJ from June to July also results in a westward displacement of the region of maximum convection within the ITCZ that leads to changes in the atmospheric circulations and moisture fluxes that determine the onset of the rainy season at higher latitudes in the Mexican Pacific coast.
Even Small Forest Patches Can Help Fight Climate Change!

Climate change is caused by humans emitting polluting gases. Carbon dioxide (CO2) is one of the most important and well-known polluting gases we emit. Forests are carbon vacuum cleaners: via their leaves, trees take up carbon and store it in their wood, roots, and leaves. We found that forest edges, where it is warmer and sunnier, can store more carbon than the forest interior, where it is cooler and shadier. This is important, because the amount of forest edges has increased due to large forests being split up into small forest patches by roads, towns, or agriculture. In Europe, this extra carbon storage in forest edges is not usually considered important, but it represents the equivalent of a forest with an area of more than 1.4 million football (soccer) fields! To maximize carbon storage, we should not only protect small forests, but also plant new forests—even very small ones.
Full-information item bifactor model for mathematical ability assessment in Chinese compulsory education quality monitoring

This study focuses on the measurement of mathematical ability in the Chinese Compulsory Education Qualification Monitoring (CCEQM) framework using bifactor theory. First, we propose a full-information item bifactor (FIBF) model for the measurement of mathematical ability. Second, the performance of the FIBF model is empirically studied using a data set from three representative provinces were selected from CCEQM 2015–2017. Finally, Monte Carlo simulations are conducted to demonstrate the accuracy of the model evaluation indices and parameter estimation methods used in the empirical study. The obtained results are as follows: (1) The results for the four used model selection indices (AIC, SABIC, HQ, BIC) consistently showed that the fit of the FIBF model is better than that of the UIRT; (2) All of the estimated general and domain-specific abilities of the FIBF model have reasonable interpretations; (3) The model evaluation indices and parameter estimation methods exhibit excellent accuracy, indicating that the application of the FIBF model is technically feasible in large-scale testing projects.
A Dataset of Symbolic Texture Annotations in Mozart Piano Sonatas

Musical scores are generally analyzed under different as-pects, notably melody, harmony, rhythm, but also through their texture, although this last concept is arguably more delicate to formalize. Symbolic texture depicts how sound-ing components are organized in the score. It outlines the density of elements, their heterogeneity, role and interactions. In this paper, we release a set of manual annotations for each bar of 9 movements among early piano sonatas by W. A. Mozart, totaling 1164 labels that follow a syntax dedicated to piano score texture. A quantitative analysis of the annotations highlights some characteristic textural features in the corpus. In addition, we present and release the implementation of low-level descriptors of symbolic texture, that are preliminary experimented for textural elements prediction. The annotations and the descriptors offer promising applications in computer-assisted music analysis and composition.
Hydrogen concentration and its relation to interplanar spacing and layer thickness of 1000-Å Nb(110) films during in situ hydrogen charging experiments

The Nb layers of a $[1000\ensuremath{-}\mathrm{\AA{}}\mathrm{}\mathrm{N}\mathrm{b}/26\ensuremath{-}\mathrm{\AA{}}\mathrm{}\mathrm{Fe}]\ifmmode\times\else\texttimes\fi{}5$ multilayer were repeatedly charged with hydrogen from the gas phase. The equilibrium hydrogen concentration in the Nb layers and the hydrogen-induced layer thickness expansion perpendicular to the film plane were determined as a function of pressure by means of in situ neutron reflectivity measurements. In situ x-ray-diffraction experiments performed on the same sample yielded the corresponding expansion of the out-of-plane Nb(110) interplanar spacing and the time-dependence of the charging and decharging process. It was found that the relative expansion of the Nb layers is considerably larger than the relative increase of the Nb(110) interplanar spacing. This shows that during hydrogen incorporation a large amount of additional volume, presumably in the form of voids in the vicinity of grain boundaries, is created. These lattice imperfections may effectively trap hydrogen atoms. The maximum hydrogen concentration at ${p}_{\mathrm{H}2}=900\mathrm{mbar}$ and $T=185\ifmmode^\circ\else\textdegree\fi{}\mathrm{C}$ is found to be 95 [H]/[Nb] at. %.
On Some Aspects of the Definition of Initial Conditions for Ensemble Prediction

Abstract Four methods for initialization of ensemble forecasts are systematically compared, namely the methods of singular vectors (SV) and bred modes (BM), as well as the ensemble Kalman filter (EnKF) and the ensemble transform Kalman filter (ETKF). The comparison is done on synthetic data with two models of the flow, namely, a low-order model introduced by Lorenz and a three-level quasigeostrophic atmospheric model. For the latter, both cases of a perfect and an imperfect model are considered. The performance of the various initialization methods is assessed in terms of the statistical reliability and resolution of the ensuing predictions. The relative performance of the four methods, which is statistically significant to a range of about 6 days, is in the order EnKF > ETKF > BM > SV. The difference between the former two methods and the latter two is on the whole more significant than the differences between EnKF and ETKF, or between BM and SV separately. The general conclusion is that, if the quality .
Two-photon subwavelength lithography with thermal light

We propose an incoherent interferometer which can partly modify the spatial correlation property of thermal light. Applying the interferometer to the two-photon double-slit interference with thermal light, we find that the subwavelength interference patterns appear in the intensity correlation not only between two same polarized photons at different positions but also between two orthogonally polarized photons at the same position. The latter can correspond to the two-photon double-slit interference using a two-photon entangled source. Our experimental result suggests that a thermal light source is capable of accomplishing subwavelength lithography technique to surpass the Rayleigh resolution limit.
Classification of Biological Data using Deep Learning Technique

A huge amount of newly sequenced proteins is being discovered on daily basis. The mainconcern is how to extract the useful characteristics of sequences as the input features for thenetwork. These sequences are increasing exponentially over the decades. However, it is veryexpensive to characterize functions for biological experiments and also, it is really necessaryto find the association between the information of datasets to create and improve medicaltools. Recently machine learning algorithms got huge attention and are widely used. Thesealgorithms are based on deep learning architecture and data-driven models. Previous workfailed to properly address issues related to the classification of biological sequences i.e.protein including efficient encoding of variable length biological sequence data andimplementation of deep learning based neural network models to enhance the performance ofclassification/ recognition systems. To overcome these issues, we have proposed a deeplearning based neural network architecture so that classification performance of the systemcan be increased. In our work, we have proposed 1D-convolution neural network whichclassifies the protein sequences to 10 top common classes. The model extracted features fromthe protein sequences labels and learned through the dataset. We have trained and evaluateour model on protein sequences downloaded from protein data bank (PDB). The modelmaximizes the accuracy rate up to 96%.
Unterschiede in fehlertoleranten Methoden für zustandsbehaftete container-basierte Fog Applikationen

The fog computing paradigm enables the deployment of services near end-users, i.e., in predominant heterogeneous environments at the edge of the network. Kubernetes manages the deployment and orchestrates the communication of containerised applications since they merely provide isolated execution contexts. In particular, it provides an easy-to-use platform to deploy stateless services since they do not need additional configuration concerning fault-tolerant methods. However, stateful applications do require implementing such methods, as their internal state can be lost in case they encounter a failure and crash. Therefore, this bachelor thesis presents two fault-tolerant methods with different underlying architectures deployed on a Kubernetes cluster. The centralised method follows the traditional approach of storing backups at a single location. The decentralised faulttolerant method implements state-machine replication (SMR) by replicating servers and executing incoming client requests in the same order on all those instances. In doing so, each server follows equal state changes and produces identical results. The library Hazelcast is used to consistently distribute data onto multiple servers as it implements the consensus algorithm Raft. Both of the fault-tolerant methods are containerised and deployed on a Kubernetes cluster. Moreover, each is integrated within a stateful application with an ephemeral state that simulates real-world interactions of clients accessing stateful servers and modifying stored data. The evaluation of the stateful application and each fault-tolerant method shows that although the decentralised approach takes more time to resume its operation after it crashed, it eventually outperforms the centralised approach in terms of the persisting and retrieving states. However, the centralised fault-tolerant method performs better right after startup and generally requires less memory during the whole evaluation period. Despite both approaches being deployed with a varying number of replica, they seemingly provide constant results.
Many Sequential Iterative Algorithms Can Be Parallel and Work-efficient

Some recent papers showed that many sequential iterative algorithms can be directly parallelized, by identifying the dependences between the input objects. This approach yields many simple and practical parallel algorithms, but there are still challenges in achieving work-efficiency and high-parallelism. Work-efficiency means that the number of operations is asymptotically the same as the best sequential solution. This can be hard for certain problems where the number of dependences between objects is asymptotically more than optimal sequential work, and we cannot even afford to generate them. To achieve high-parallelism, we want to process as many objects as possible in parallel. The goal is to achieve ˜ 𝑂 ( 𝐷 ) span for a problem with the deepest dependence length 𝐷 . We refer to this property as round-efficiency . This paper presents work-efficient and round-efficient algorithms for a variety of classic problems and propose general approaches to do so. To efficiently parallelize many sequential iterative algorithms, we propose the phase-parallel framework . The framework assigns a rank to each object and processes the objects based on the order of their ranks. All objects with the same rank can be processed in parallel. To enable work-efficiency and high parallelism, we use two types of general techniques. Type 1 algorithms aim to use range queries to extract all objects with the same rank to avoid evaluating all the dependences. We discuss activity selection, and Dijkstra’s algorithm using Type 1 framework. Type 2 algorithms aim to wake up an object when the last object it depends on is finished. We discuss activity selection, longest increasing subsequence (LIS), greedy maximal independent set (MIS), and many other algorithms using Type 2 framework. All of our algorithms are (nearly) work-efficient and round-efficient. Many of them improve previous best bounds, and some of them (e.g., LIS) are the first to achieve work-efficiency with round-efficiency. We also implement many of them. On inputs with reasonable dependence depth, our algorithms are highly parallelized and significantly outperform their sequential counterparts
Evaluation of Vascular Cognitive Impairment Using the ICMR-Neuro Cognitive Tool Box (ICMR-NCTB) in a Stroke Cohort from India

Background and Purpose: Vascular cognitive impairment (VCI) presents with a spectrum of cognitive impairment due to stroke and poses a huge socioeconomic burden especially in low middle-income countries. There is a critical need for early recognition and identification of VCI patients. Therefore, we developed and validated culturally appropriate neuropsychological instruments, the ICMR-Neuro Cognitive Tool-Box (ICMR-NCTB) and Montreal Cognitive Assessment (MoCA) to diagnose vascular MCI and dementia in the Indian context. Methods: A total of 181 participants: 59 normal cognition, 25 stroke with normal cognition, 46 vascular MCI (VaMCI) and 51 vascular dementia (VaD) were recruited for the study. The ICMR-NCTB and MoCA were administered to patients with VCI and major cognitive domains were evaluated. Results: The ICMR-NCTB was found to have good internal reliability in VaMCI and VaD. The sensitivity of the ICMR-NCTB to detect VaMCI and VaD ranged from 70.8% to 72.9% and 75.9% to 79.7%, respectively, and the specificity for VaMCI and VaD ranged from 84.8% to 86.1% and 82.5% to 85.2%, respectively. The MoCA had excellent sensitivity and specificity to detect VaMCI and VaD at ideal cut-off scores. Conclusion: The ICMR-NCTB is a valid neuropsychological toolbox that can be used for comprehensive cognitive assessment and diagnosis of VCI in India. In addition, the Indian version of MoCA is more adept as a screening instrument to detect VCI due to its high sensitivity. The ICMR-NCTB will aid in early detection and management of many patients, thereby reducing the burden of vascular MCI and dementia in India.
Effects of KrF excimer laser irradiation on metal contacts to n-type and p-type GaN

Electrical properties of metal contacts on laser-irradiated n-type and p-type GaN surfaces were investigated using current–voltage, capacitance–voltage, and synchrotron radiation photoemission spectroscopy. After the irradiation of a KrF excimer laser pulse (600 mJ/cm2 at 248 nm for 38 ns) onto Si-doped GaN, a nonalloyed Ti/Al metallization formed an ohmic contact with the specific contact resistivity of 1.7×10−6 Ω cm2. The laser irradiation decomposed GaN into metallic Ga and nitrogen gas. The decomposed metallic Ga reacted with oxygen in air to form a Ga oxide layer with the thickness of ∼40 A, producing a large number of N vacancies near the surface. The formation of a degenerated n-type GaN layer resulted in the low contact resistivity. For Mg-doped GaN, the laser irradiation increased the effective acceptor concentration. Simultaneously, the activation efficiency of Mg dopants was enhanced by the photon-assisted breaking of Mg–H bonds and/or the removal of hydrogen atoms in the presence of oxygen, pr.
Supersonic flows of dense gases in cascade configurations

We examine the steady, inviscid, supersonic flow of Bethe-Zel'dovich–Thompson (BZT) fluids in two-dimensional cascade configurations. Bethe-Zel'dovich–Thompson fluids are single-phase gases having specific heats so large that the fundamental derivative of gasdynamics, Γ, is negative over a finite range of pressures and temperatures. The equation of state is the well-known Martin–Hou equation, and the numerical scheme is the explicit predictor-corrector method of MacCormack. Numerical comparisons between BZT fluids and lighter fluids such as steam are presented. It was found that the natural dynamics of BZT fluids can result in significant reductions in the adverse pressure gradients associated with the collision of compression waves with neighbouring turbine blades. A numerical example of an entirely isentropic supersonic cascade flow is also presented.
Determination of MgO/GaN heterojunction band offsets by x-ray photoelectron spectroscopy

MgO is a promising gate dielectric and surface passivation film for GaN transistors but little is known of the band offsets in the MgO∕GaN system. X-ray photoelectron spectroscopy was used to measure the energy discontinuity in the valence band (ΔEv) of MgO∕GaN heterostructures in which the MgO was grown by rf plasma-assisted molecular beam epitaxy on top of thick GaN templates on sapphire substrates. A value of ΔEv=1.06±0.15eV was obtained by using the Ga 3d energy level as a reference. Given the experimental band gap of 7.8eV for the MgO, this would indicate a conduction band offset ΔEC of 3.30eV in this system.
Measurement of the gauge factor of few-layer graphene

Abstract. Graphene, one of the recently discovered carbon nanostructures, has shown good piezoresistive properties. One of the most important areas of research for graphene sheets, in terms of basic science and application in strain or stress sensors, is the measurement of gauge factors. The gauge factors of various layers of graphene sheets are measured based on the equivalent stress beam. The measurement is carried out using a beam-bending method to detect the change in resistance of graphene sheets in different bending states. The gauge factor ranges from 10 to 15, depending on the number of layers in the graphene sheet. These results reveal the piezoresistance effect of single- and multi-layer graphene sheets, which will be of benefit in the fabrication of microsensors. The resistance of graphene sheets decreases as temperature increases from 20°C to 60°C, and the gauge factor is not very sensitive to changes in environmental temperature.