Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiblock modeling of flow in porous media and applications

We investigate modeling flow in porous media in multiblock domain. Mixed finite element methods are used for subdomain discretizations. Physically meaningful boundary conditions are imposed on the non-matching interfaces via mortar finite element spaces. We investigate the pollution effect of nonmatching grids error on the numerical solution away from interfaces. We prove that most of the error in the velocity occurs along the interfaces, and that high accuracy is preserved in the interior of the subdomains. In case of discontinuous coefficients, the pollution from the singularity affects the accuracy in the whole domain. We investigate the upscaling error resulting when fine resolution data is approximated on a very coarse scale. Extending work of Wheeler and Yotov, we incorporate this upscaling error in an a posteriori error estimator for the pressure, velocity and mortar pressure. We employ a non-overlapping domain decomposition method reducing the global system to one that is solved iteratively via a preconditioned conjugate gradient method. This approach is suitable for parallel implementation. The balancing domain decomposition method for mixed finite elements following Cowsar, Mandel, and Wheeler is extended to the case of mortar mixed finite elements on non-matching multiblock grids. The algorithm involves solution of a mortar interface problem with one local Dirichlet solve and one local Neumann solve on each iteration. A coarse solve is used to guarantee consistency and to provide global exchange of information. Quasi-optimal condition number bounds independent of the jump in coefficients are derived. We finally consider multiscale mortar mixed finite element discretizations for single and two phase flows. We show optimal convergence and some superconvergence in the fine scale for the solution and its flux. We also derive efficient and reliable a posteriori error estimators suitable for adaptive mesh refinement. We have incorporated the above methods into a parallel multiblock simulator on unstructured prismatic meshes employing a non-overlapping domain decomposition algorithm and mortar spaces. Numerical experiments are presented confirming all theoretical results.
Lipomics: A Potential Carrier for the Intravenous Delivery of Lipophilic and Hydrophilic Drugs

In the present work, we propose the development of a novel carrier that does not need organic solvents for its preparation and with the potential for the intravenous delivery of lipophilic and hydrophilic drugs. Named lipomics, this is a mixed colloid of micelles incorporated within a liposome. This system was designed through ternary diagrams and characterized by physicochemical techniques to determine the particle size, zeta potential, shape, morphology, and stability properties. The lipomics were subjected to electron microscopy (SEM, TEM, and STEM) to evaluate their physical size and morphology. Finally, pharmacokinetic studies were performed by radiolabeling the lipomics with Technetium-99m chelated with BMEDA to evaluate the in vivo biodistribution through techniques of molecular imaging (microSPECT/CT) in rats. Radiolabeling efficiency was used to compare the encapsulation efficiency of the hydrophilic and lipophilic molecules in lipomics and liposomes. According to the results, lipomics are potentially carriers of lipophilic and hydrophilic drugs.
Robust and sparse learning of varying coefficient models with high-dimensional features

ABSTRACT Varying coefficient model (VCM) is extensively used in various scientific fields due to its capability of capturing the changing structure of predictors. Classical mean regression analysis is often complicated in the existence of skewed, heterogeneous and heavy-tailed data. For this purpose, this work employs the idea of model averaging and introduces a novel comprehensive approach by incorporating quantile-adaptive weights across different quantile levels to further improve both least square (LS) and quantile regression (QR) methods. The proposed procedure that adaptively takes advantage of the heterogeneous and sparse nature of input data can gain more efficiency and be well adapted to extreme event case and high-dimensional setting. Motivated by its nice properties, we develop several robust methods to reveal the dynamic close-to-truth structure for VCM and consistently uncover the zero and nonzero patterns in high-dimensional scientific discoveries. We provide a new iterative algorithm that is proven to be asymptotic consistent and can attain the optimal nonparametric convergence rate given regular conditions. These introduced procedures are highlighted with extensive simulation examples and several real data analyses to further show their stronger predictive power compared with LS, composite quantile regression (CQR) and QR methods.
Color-dependent pruning in immersive video coding

This paper presents the color-dependent method of removing inter-view redundancy from multiview video. The pruning of input views decides which fragments of views are redundant, i.e., do not provide new information about the three-dimensional scene, as these fragments were already visible from different views. The proposed modification of the pruning uses both color and depth and utilizes the adaptive pruning threshold which increases the robustness against the noisy input. As performed experiments have shown, the proposal provides significant improvement in the quality of encoded multiview videos and decreases erroneous areas in the decoded video caused by different camera characteristics, specular surfaces, and mirror-like reflections. The pruning method proposed by the authors of this paper was evaluated by experts of the ISO/IEC JTC1/SC29/WG 11 MPEG and included by them in the Test Model of MPEG Immersive Video.
AR technology in the design of oil and gas field surface engineering: Applications and prospects

Wearable devices based on Augmented Reality (AR) technology can overlay computer-generated images into the real world, whereas simulation is applied to enable users to view the real world with an overlay of digital data. In the past 10 years, AR technology has moved from research laboratories to gradually a wide range of commercially available technologies for its use in the medical, manufacturing, industrial design, entertainment, marketing and military applications. This review includes an overview of AR wearables in the last 5 years including its development milestone and application cases, where specifically, some successful application cases and implications of AR technology in the oil and gas industry in the past five years are reviewed, with the aim of discussing the aspects of AR technology applications in the design of oil and gas field surface engineering, from station and line designs to its use in supporting construction. Since AR technology can provide real-time information, it will have a non-negligible application prospect in the whole lifecycle of oil and gas field surface engineering from design to operation and maintenance and will occupy a place in the digital transformation of the oil and gas industry.
Analyzing Factors Associated with the Behavior-Change Stage of Colorectal Cancer Screening

This study attempted to identify the stages of colorectal cancer screening (CRCS) behavior change by applying the precaution adoption process model (PAPM) and to examine the factors affecting each stage. A quantitative, descriptive, cross-sectional design was used. A total of 305 workers at one of the largest industrial complexes in South Korea were allocated using convenience sampling. Data were analyzed using independent t-test, one way ANOVA and multi-nominal logistic regression using SPSS 25.0 (SPSS Inc., Chicago, IL, USA). Most of the subjects were in the undecided-to-act stage. The factors affecting each stage were gender, marital status, family history, private insurance subscription, perceived barrier, and self-efficacy. It is critical to select a target group considering the behavioral change stage to establish a strategy for improving the CRCS rate. Developing and implementing a CRCS education program in consideration of the behavioral change stage will be a strategy to increase the examination of effectiveness of CRCS.
An effective global learning framework for hyperspectral image classification based on encoder-decoder architecture

ABSTRACT Most deep learning methods in hyperspectral image (HSI) classification use local learning methods, where overlapping areas between pixels can lead to spatial redundancy and higher computational cost. This paper proposes an efficient global learning (EGL) framework for HSI classification. The EGL framework was composed of universal global random stratification (UGSS) sampling strategy and a classification model BrsNet. The UGSS sampling strategy was used to solve the problem of insufficient gradient variance resulted from limited training samples. To fully extract and explore the most distinguishing feature representation, we used the modified linear bottleneck structure with spectral attention as a part of the BrsNet network to extract spectral spatial information. As a type of spectral attention, the shuffle spectral attention module screened important spectral features from the rich spectral information of HSI to improve the classification accuracy of the model. Meanwhile, we also designed a double branch structure in BrsNet that extracted more abundant spatial information from local and global perspectives to increase the performance of our classification framework. Experiments were conducted on three famous datasets, IP, PU, and SA. Compared with other classification methods, our proposed method produced competitive results in training time, while having a greater advantage in test time.
Optimal Estimation of Parameters

1. Introduction 2. Coding 3. Basics of information 4. Modeling problem 5. Other optimality properties 6. Interval estimation 7. Hypothesis testing 8. Denoising 9. Sequential models Appendix A. Elements of algorithmic information Appendix B. Universal prior for integers.
We just try to work with the needs in front of us

The Ontario government’s International Education Strategy (2015) establishes goals for international education and the hosting of international students in Ontario schools. Using a critical policy lens, we focus on teachers as key to enacting these policy objectives in local contexts. The article presents findings from four focus groups of Ontario teachers working in schools with large international student cohorts. We found teacher participants were generally unaware of a broader vision or strategic goal for the presence of these students in their schools. They found it difficult to meet the needs of this growing cohort, and they faced this challenge with varying degrees of enthusiasm. Factors that influenced their enactment included personal background and education, as well their ability to collaborate and work in contexts with a professional ethos. Overall, teachers expressed a desire for more information, support, and professional development, including opportunities for collaboration, with regard to educating international students in their schools.
The Influence of Maturity Status on Dynamic Balance Following 6 Weeks of Eccentric Hamstring Training in Youth Male Handball Players

Information about when to apply an appropriate eccentric hamstring strength training stimulus during long-term athlete development is essential for effective programming and improving balance performance. This study examined the effects of six-week eccentric hamstring training on dynamic balance performance in youth handball players of different maturity statuses (pre- or post-peak height velocity (PHV)). A randomized controlled design with 45 young male handball players (14.6 ± 0.3 years) from a local national handball club were randomly allocated to a 6 week, twice weekly eccentric hamstring training in two experimental groups: a pre-PHV (maturation offset: −2.13 ± 0.63, n = 10) and post-PHV (maturation offset: 0.79 ± 0.34, n = 12) group and two control groups: maturation offset: −2.09 ± 0.61, n = 10 and maturation offset: 0.55 ± 0.67, n = 13. Dynamic balance performance was evaluated by using the composite score during the lower quarter Y-balance test from pre- and post-intervention. A significant effect on balance scores was found from pre to post (F = 11.4; p = 0.002; η2p = 0.22), intervention (F = 5.4; p = 0.025; η2p = 0.12), and maturation (F = 369; p < 0.001; η2p = 0.9), but no significant interaction effects were found (F ≥ 3.3; p ≥ 0.077; η2p ≤ 0.07). Post hoc analysis revealed that the post-PHV group had a higher score than the pre-PHV group. Furthermore, that dynamic balance increased in the post-PHV group after intervention much more in the control post-PHV group. It was concluded that somatic maturation influences dynamic balance performance and that eccentric hamstring training results in greater improvement in balance performance in young male handball players for the post-pubertal group.
Development and Space-Qualification of a Miniaturized CubeSat’s 2-W EDFA for Space Laser Communications

The Japanese National Institute of Information and Communications Technology (NICT) is currently developing a high-performance laser-communication terminal for CubeSats aimed at providing a high-datarate communication solution for LEO satellites requiring transmission of large volumes of data from orbit. A key aspect of the communication system is a high-power optical amplifier capable of providing enough gain to the transmitted signals to be able to close the link on its counterpart’s receiver with the smallest impact in terms of energy and power on the CubeSat’s platform. This manuscript describes the development of a miniaturized 2-W space-grade 2-stage erbium-doped fiber amplifier (EDFA) compatible with the CubeSat form factor, showing the best power-to-size ratio for a space-qualified EDFA to the best of the authors’ knowledge. Performance results under realistic conditions as well as full space qualification and test are presented, proving that this module can support short-duration LEO-ground downlinks as well as long-duration intersatellite links.
Factors affecting e-government adoption in the UAE public sector organisations: the knowledge management perspective

Purpose This study aims to investigate factors that influence e-government adoption among public sector departments with the view to determine how such factors may be used to better facilitate e-government adoption across United Arab Emirates (UAE) public sectors. The use of e-government is advocated for the central government in the UAE. Design/methodology/approach Using random sampling, a total of 172 participants from ten departments and organisations in Dubai and Sharjah completed the online survey for this pilot study. Findings The authors found that performance expectancy and facilitating conditions have positive effects on e-government adoption. Furthermore, this study revealed the factors that encourage more e-government adoption between government organisations in the UAE. This study reveals three facilitating conditions may encourage e-government adoption in UAE public sector organisations when short- and long-term performances have positive effects on e-government usage. Practical implications This study provides middle managers clarity on factors that would influence government-to-government (G2G) uptake in more government organisations across the country. For uniformity and consistency, middle managers are now better informed as a result of this study to determine how best to use the six factors to motivate subordinates for more effective G2G. Originality/value The scope and results of this study is a contribution to e-government studies because it identifies the factors that positively influence G2G adoption. This scope exceeds the studies by Chan et al. (2021) and Habib et al. (2020) which focuses on the use of e-government for citizens or the public. This study focuses on the use of e-government within the government and between government departments.
Cubosomes for Enhancing Intestinal Absorption of Fexofenadine Hydrochloride: In situ and in vivo Investigation

Purpose The aim of this work was to probe cubosomes for enhanced intestinal absorption and oral bioavailability of poorly absorbable fexofenadine HCl (FEX-HCl). Materials and Methods Two cubosomal systems were fabricated utilizing glyceryl mono-oleate, a lyotropic mono lamellar lipid as oil phase and poloxamer407 as stabilizer at weight ratios of 8:2 and 7:3. The morphology of cubosomes was researched using transmission electron microscopy (TEM) and particle size was measured using photon correlation spectroscopy. FEX-HCl release was monitored in vitro. The effect of cubosomal encapsulation on intestinal absorption was assessed using in situ rabbit intestinal perfusion technique. Carrageenan induced rat paw edema model was utilized to monitor in vivo anti-inflammatory effect before and after cubosomal encapsulation. Results TEM revealed the existence of spherical and polygonal nanostructures arranged in honeycomb organization. Size measurement reflected nanoparticles with reduced size at higher poloxamer concentration. Release studies revealed liberation of FEX-HCl from cubosomes based on Higuchi kinetics model. The intestinal permeability data indicated incomplete absorption of FEX-HCl from simple aqueous solution with P-glycoprotein efflux contributing to this poor intestinal absorption. Incorporation of FEX-HCl in cubosomes enhanced membrane transport parameters. The intestinal absorption did not correlate with drug release suggesting that drug release is not the rate limiting with possible intact cubosomal transport. Cubosomal encapsulation of FEX-HCl significantly enhanced its in vivo anti-inflammatory efficacy compared to the aqueous FEX-HCl dispersion. Conclusion Cubosomes are promising novel carriers for enhancing intestinal absorption of FEX-HCl. Intact FEX-HCl-cubosomal absorption is possible via trans-lymphatic pathway but this requires further investigations.
Pharmacological Strategies for Suicide Prevention Based on the Social Pain Model: A Scoping Review

Suicidal behaviour is a public health problem whose magnitude is both substantial and increasing. Since many individuals seek medical treatment following a suicide attempt, strategies aimed at reducing further attempts in this population are a valid and feasible secondary prevention approach. An evaluation of the available evidence suggests that existing treatment approaches have a limited efficacy in this setting, highlighting the need for innovative approaches to suicide prevention. Existing research on the neurobiology of social pain has highlighted the importance of this phenomenon as a risk factor for suicide, and has also yielded several attractive targets for pharmacological strategies that could reduce suicidality in patients with suicidal ideation or a recent attempt. In this paper, the evidence related to these targets is synthesized and critically evaluated. The way in which social pain is related to the “anti-suicidal” properties of recently approved treatments, such as ketamine and psilocybin, is examined. Such strategies may be effective for the short-term reduction in suicidal ideation and behaviour, particularly in cases where social pain is identified as a contributory factor. These pharmacological approaches may be effective regardless of the presence or absence of a specific psychiatric diagnosis, but they require careful evaluation.
Horae: A Hybrid I/O Request Scheduling Technique for Near-Data Processing-Based SSD

Near-data processing (NDP) architecture is promised to break the bottleneck of data movement in many scenarios (e.g., databases and recommendation systems), which limits the efficiency of data processing. Different from traditional SSD, NDP-based SSD not only needs to handle normal I/Os (e.g., read and write), but also needs to handle NDP requests that contain data processing operations. NDP and normal I/O requests share some function units of NDP-based SSD, such as flash chips and embedded processors. However, existing works ignore the resource competition between normal I/Os and NDP requests, which drastically degrades the performance. In this article, we propose a novel scheduling technique called Horae, which can efficiently schedule hybrid NDP-normal I/O requests in NDP-based SSD to improve performance. Horae exploits the critical paths on critical resources to maximize the parallelism of multiple stages of requests. The experimental results on typical workloads show that Horae can significantly improve the performance of hybrid NDP-normal I/O requests over the state-of-the-art scheduling algorithms of NDP-based SSDs.
Research status and progress of intelligent wearable system for first aid based on body area network

With the rise of electronic health services, wireless body area network (WBAN) technology has attracted great international attention. The body area network can obtain human vital sign parameters in its natural state, and support applications in areas such as clinical diagnosis and treatment, emergency rescue and treatment, and health information services. This article introduces the concept of body area network and the electronic medical architecture of body area network, summarizes the advantages of body area network: in low data rate scenarios, the system power consumption of body area network is much lower than that of other wireless communication standards, providing more choices for special frequency bands for medical equipment (500 MHz to 5 GHZ), thereby reducing the interference problem between different communications; proposing bottlenecks and hot spots of body area network: ultra-low power consumption requirements of sensor nodes and hardware resource constraints with limited computing power, and data security protection problems in body area network sensor nodes; the application of body area network in emergency scenarios was analyzed, and the hot spots of body area network research in the field of emergency were summarized and predicted: the development of ultra-low-power chips, wearable wireless nodes, intelligent medical terminals, health and monitoring instruments and other devices and equipment.
Arbuscular mycorrhizal fungi enhanced the growth, phosphorus uptake and Pht expression of olive (Olea europaea L.) plantlets

Olive (Olea europaea L.) is a highly mycotrophic species that has been introduced and cultivated in China for half a century. The arbuscular mycorrhizal fungi (AMF) is extremely valuable as a kind of biofertilizer to promote the health and vigor of olive plants. However, it is still unclear how native AMF impact growth and mineral nutrients, especially phosphorus absorption in the area where olive trees were introduced in China. In the present study, through a pot experiment, the effects of native AMF on the growth, phosphorus uptake and expression levels of four phosphate transporter genes (Pht) of olive plantlets were characterized. We found that (1) typical AMF colonization was observed within the roots of inoculated olive plantlets, and the growth of plantlets was significantly promoted; (2) some indigenous consortia (AMF1 and AMF2) notably promoted the absorption of phosphorus, fertilizers significantly increased the foliar content of nitrogen, and both AMF inoculation and fertilization had no significant effect on the uptake of potassium; and (3) AMF inoculation enhanced the expression of phosphate transporter genes in inoculated olive roots. This work demonstrates the effectiveness of native AMF on the cultivation of robust olive plantlets and highlights the role of AMF in increasing phosphorus uptake. There is great potential in using native AMF consortia as inoculants for the production of healthy and robust olive plantlets.