Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Pretreated Phosphogypsum and Granulated Blast-Furnace Slag on the Rheological Properties of the Paste Excited by NaOH

The main component of phosphogypsum (PG) is CaSO4·2H2O. PG contains a few impurities, heavy metals, and radioisotopes, which limit the use of PG and pose a danger to the environment. In this study, under the excitation of a sodium hydroxide solution, the rheological properties of a paste with granulated blast-furnace slag (GGBS) and PG treated with ultrasonic water washing were investigated. Experimental results showed that the ratio of GGBS to PG and the amount of sodium hydroxide solution significantly affect the density and viscosity of the paste, but the effect patterns of both are different. The maximum viscosity was 498 mPa·s when the ratio of GGBS to PG was 4:1. When the ratio changed from 3:2 to 1:4, the viscosity of the paste gradually decreased by 15.5%, 32.1%, 36.1%, and 46.8%, respectively. In contrast, the ratio of GGBS to PG had a greater effect on the viscosity than the amount of sodium hydroxide solution in terms of the standard consistency water consumption, viscosity, and water release ratio. The larger the PG ratio, the smaller the density, viscosity, and water release ratio of the paste. The variation in the ratio of GGBS to PG had a significant effect on the water film thickness of the paste, demonstrating that the larger the PG mixture, the larger the water film thickness of the paste, which reached 1.122 μm, 2.31 times the minimum water film thickness of the paste. At the same time, the water film thickness of the paste was negatively correlated with the water consumption of the standard consistency, viscosity, and water release ratio, and was positively correlated with the fluidity.
Step-by-step excimer laser induced crystallization of a-Si:H

Amorphous silicon films (a-Si:H) with a hydrogen content of 10 at. % were crystallized employing a step-by-step crystallization method. Structural changes during the sequential crystallization process were monitored by Raman spectrometry. Initially, at low laser fluences EL, a two-layer system is created. Independent of the thickness of the a-Si:H layer explosive crystallization of a thin surface layer is observed at EL⩾100 mJ/cm2 confirming recent theoretical results. Crystallization is accompanied by dehydrogenation. In completely crystallized poly-Si a residual H concentration of up to 5 at. % was observed.
On winds and X-rays of O-type stars

The dependence between stellar wind parameters and their X-ray fluxes is studied. Bolometric corrections are examined as a function of temperature, and a bolometric luminosity scale is proposed for the O-type stars. New mass-loss rates and terminal velocities of 40 well-known, bright single stars or binaries are measured, and the Lyman-alpha profile is modeled for the stars to determine the amount of X-ray-absorbing hydrogen. The mass-loss rates found for the latest O-type stars are significantly smaller than expected from the power-law dependences known for brighter, hot stars. The mass-loss rates for binary system do not differ significantly from those of single stars. A dependence is found between the wind energy of the single stars and the X-ray luminosity, and it is suggested that this dependence is at least partially responsible for the proportionality between L(x) and L(bol). The X-ray fluxes from the close binaries behave in qualitative agreement with predictions from simple theories of colliding stellar winds. 83 refs.
Functional enhancement strategies to potentiate the therapeutic properties of mesenchymal stromal cells for respiratory diseases

Respiratory diseases remain a major health concern worldwide because they subject patients to considerable financial and psychosocial burdens and result in a high rate of morbidity and mortality. Although significant progress has been made in understanding the underlying pathologic mechanisms of severe respiratory diseases, most therapies are supportive, aiming to mitigate symptoms and slow down their progressive course but cannot improve lung function or reverse tissue remodeling. Mesenchymal stromal cells (MSCs) are at the forefront of the regenerative medicine field due to their unique biomedical potential in promoting immunomodulation, anti-inflammatory, anti-apoptotic and antimicrobial activities, and tissue repair in various experimental models. However, despite several years of preclinical research on MSCs, therapeutic outcomes have fallen far short in early-stage clinical trials for respiratory diseases. This limited efficacy has been associated with several factors, such as reduced MSC homing, survival, and infusion in the late course of lung disease. Accordingly, genetic engineering and preconditioning methods have emerged as functional enhancement strategies to potentiate the therapeutic actions of MSCs and thus achieve better clinical outcomes. This narrative review describes various strategies that have been investigated in the experimental setting to functionally potentiate the therapeutic properties of MSCs for respiratory diseases. These include changes in culture conditions, exposure of MSCs to inflammatory environments, pharmacological agents or other substances, and genetic manipulation for enhanced and sustained expression of genes of interest. Future directions and challenges in efficiently translating MSC research into clinical practice are discussed.
Travel Time Distribution Estimation by Learning Representations Over Temporal Attributed Graphs

Travel time estimation is a crucial task in practical transportation applications, while providing the reliability of estimation is important in many working scenarios. Most existing studies do not consider the dynamics of traffic status for different road segments in real time, thus yielding unsatisfactory results. To address the problem, we propose to formulate the traffic network as a temporal attributed graph and perform node representation learning on it. The learned representation is capable of jointly exploiting the dynamic traffic conditions and the topology of the road network, which is then fed into a route-based spatio-temporal dependence learning module to estimate the travel time. By incorporating a distribution loss function, our proposed model is able to predict the distribution of travel time. In the meantime, we design an auxiliary local task of predicting the congestion status of each road segment, which further enhances the generalization performance of the representation learning. Extensive experiments on real-world large-scale datasets demonstrated the superiority of our method compared with the state-of-the-arts.
Creativity, Critical Thinking, Communication, and Collaboration: Assessment, Certification, and Promotion of 21st Century Skills for the Future of Work and Education

This article addresses educational challenges posed by the future of work, examining “21st century skills”, their conception, assessment, and valorization. It focuses in particular on key soft skill competencies known as the “4Cs”: creativity, critical thinking, collaboration, and communication. In a section on each C, we provide an overview of assessment at the level of individual performance, before focusing on the less common assessment of systemic support for the development of the 4Cs that can be measured at the institutional level (i.e., in schools, universities, professional training programs, etc.). We then present the process of official assessment and certification known as “labelization”, suggesting it as a solution both for establishing a publicly trusted assessment of the 4Cs and for promoting their cultural valorization. Next, two variations of the “International Institute for Competency Development’s 21st Century Skills Framework” are presented. The first of these comprehensive systems allows for the assessment and labelization of the extent to which development of the 4Cs is supported by a formal educational program or institution. The second assesses informal educational or training experiences, such as playing a game. We discuss the overlap between the 4Cs and the challenges of teaching and institutionalizing them, both of which may be assisted by adopting a dynamic interactionist model of the 4Cs—playfully entitled “Crea-Critical-Collab-ication”—for pedagogical and policy-promotion purposes. We conclude by briefly discussing opportunities presented by future research and new technologies such as artificial intelligence and virtual reality.
Development of a novel line scanner for speckle contrast diffuse correlation tomography of microvascular blood flow

Partial thickness burn wounds extend partially through the dermis, leaving many pain receptors intact and making the injuries very painful. Due to the painfulness, quick assessment of the burn depth is important to not delay surgery of the wound if needed. Laser speckle imaging (LSI) of skin blood flow can be helpful in finding severe coagulation zones with impaired blood flow. However, LSI measurements are typically too superficial to properly reach the full depth of adult dermis and cannot resolve the flow in depth. Diffuse correlation spectroscopy (DCS) uses varying source-detector separations to allow differentiation of flow depths but requires time-consuming 2D scanning to form an image of the burn area. We here present a prototype for a hybrid DCS and LSI technique called speckle contrast Diffuse Correlation Tomography (scDCT) with the novel approach of using a laser line as a source. This will allow for fast 1D scanning to perform 3D tomographic imaging, making quantitative estimates of the depth and area of the coagulation zone from burn wounds. Simulations and experimental results from a volumetric flow phantom show promise to differentiate flows at different depths. The aim is to create a system that will provide more quantitative estimates of coagulation depth in partial thickness burn wounds to better estimate when surgery is needed.
The effect of a formative assessment practice on student achievement in mathematics

Research has shown that formative assessment can enhance student learning. However, it is conceptualised and implemented in different ways, and its effects on student achievement vary. A need has been identified for experimental studies to carefully describe both the characteristics of implemented formative assessment practices and their impact on student achievement. We examined the effects on student achievement of changes in formative assessment of a random sample of 14 secondary school mathematics teachers after a professional development programme. This study describes practices implemented and students’ achievement as measured by pre-tests and post-tests. We found no significant differences in achievement on the post-test, after controlling for pre-test scores, between the intervention group and control group, and no significant correlation between the number of formative assessment activities implemented and the post-test scores (controlled for the pre-test scores). We discuss characteristics of formative assessment implementations that may be critical for enhancing student achievement.
Charge exchange neutral particle analysis with natural diamond detectors on LHD heliotron

Semiconductor detectors based on natural diamonds have been installed on the Large Helical Device (LHD) heliotron to measure the energy distribution of charge exchange fast neutral particles from different viewing angles. Advantages of a natural diamond detector (NDD) are (1) very compact size, (2) relatively easy handling, and (3) high energy resolution. Although NDDs are sensitive to visible light, vacuum ultraviolet, and soft x rays, unfavorable pulses produced by such radiation were greatly reduced by choosing an appropriate stainless steel shield in this experiment. In LHD, the time-resolved energy distribution of counter-going beam ions and ion cyclotron range of frequency-produced energetic ions have been successfully obtained by means of an NDD. The performance of NDDs as a neutral particle analyzer and its good suitability to LHD plasmas were demonstrated throughout this work.
Sybil Attack Detection in Internet of Flying Things-IoFT: A Machine Learning Approach

Sybil attack refers to the situation when a malicious node falsely claims to have numerous identities and is known to be one of the security threats to the Internet of Things (IoT). Due to recent increase usage of unmanned aerial vehicles (UAVs) in various applications, Sybil attack has been identified as a threat to the flying ad hoc network (FANET) paradigm and its integration with the IoT to form the Internet of Flying Things (IoFT). In this article, we propose an intelligent Sybil attack detection approach for FANETs-based IoFT using physical layer characteristics of the radio signals emitted from the UAVs as detected by two ground nodes. A supervised machine learning approach is employed and experimented with several different classifiers available in the Weka workbench platform. The experiment was carried out based on two features of the radio signals, namely, the received signal strength difference (RSSD) and the Time Difference of Arrival (TDoA). Simulation results revealed that the proposed scheme can achieve a high correct classification accuracy of above 91% on average, even for smart malicious nodes with power control capability operating at power levels not directly trained. In addition to its high performance, the proposed scheme is also less susceptible to various attacks commonly carried out on the upper layers, such as data spoofing, due to the use of only intrinsically generated physical layer data. Furthermore, no additional communications overheads of the UAV nodes are required for the functionality of this scheme.
On the Rate-Independent Limit of Systems with Dry Friction and Small Viscosity

Rate-independent systems with nonconvex energies generate solutions with jumps. To resolve the full jump path we consider two difierent regularizations, namely (i) small viscosity and (ii) local minimization in the time discretized setting. After rescaling the solutions via arc-length parametrization we obtain a new limit problem, which is again rate independent. We establish convergence results for the viscously regularized solutions as well as for the time-discretized solutions. In general the limit function is no longer parametrized by arc length; however, another reparametrization leads to a solution. Using a Young-measure argument, we show that the latter reparamterization is not necessary if the dry-friction potential and the viscous potential satisfy a structural compatibility condition.
Cadmium does not affect post-hatching maternal care or early offspring development in earwigs

Anthropogenic pollution is steadily increasing and has a major impact on biodiversity. Chemical pollutants in particular affect many reproductive, physiological, and survival traits in a wide range of organisms. However, the effects on behavioral traits have been less studied, although they could have wide-ranging negative effects from the individual to the community level. Here, we attempted to fill this knowledge gap by investigating the effect of a common heavy metal pollutant, cadmium, on post-hatching maternal care and juvenile development in the European earwig Forficula auricularia. We fed 108 earwig families with five different cadmium concentrations (0, 12.5, 25, 50, and 100 mg.L−1), and measured ten parameters related to offspring care, non-care maternal behaviors, investment in maternal care and two parameters of offspring development (offspring weight gain and survival). Somewhat surprisingly, we found no effect of cadmium ingestion on any of the parameters measured, except for maternal self-grooming behavior. In particular, the ingestion of cadmium by group members did not result in an overall decrease in the expression of care by the contaminated mothers or in an overall higher level of care received by the contaminated offspring. By contrast, mothers fed the highest dose of cadmium showed an increase in self-grooming, probably due to the stress of toxic ingestion. Overall, our study raises questions about whether and how parent–offspring interactions can alter the negative effects of contaminated environments in social species.
Robust Cubature Kalman Filter With Gaussian-Multivariate Laplacian Mixture Distribution and Partial Variational Bayesian Method

This article explores the problem of nonlinear state estimation in the presence of outlier-contaminated measurements. First, to deal with the non-stationary non-Gaussian noises caused by randomly occurring measurement outliers, we propose a new Gaussian-multivariate Laplacian mixture (GMLM) distribution and construct it as a hierarchical Gaussian expression. Next, utilizing the GMLM distribution and existing variational Bayesian (VB) method, a robust cubature Kalman filter is derived (VB-GMLMRCKF). Then, considering the high computational complexity of the existing VB inference process, a new partial VB (PVB) method is developed, which can separately estimate state vector and mismatched measurement noise covariance matrix. Building upon the VB-GMLMRCKF and PVB approach, a novel robust cubature Kalman filter is derived (PVB-GMLMRCKF). Finally, a target tracking model is utilized to evaluate the PVB-GMLMRCKF in terms of estimation accuracy, estimation consistency and computational efficiency.
The Cataloging and Conservation of Digital Survey in Archaeology: A Photogrammetry Protocol in the Context of Digital Data Curation

The technological advancement of software and hardware and the lowering of the prices of instrumentation has made photogrammetry the preferred instrument for surveying activities in archaeological projects. Consequently, archaeological datasets have been enriched with 3D models of archaeological finds and structures. Each project has developed its work pipeline for raw data acquisition and the elaboration of models and their archiving and dissemination. In most cases, the pipeline is the result of empirical experimentation and is designed to act within the specific context of the project. To date, we still lack a shared method for a photogrammetric survey that derives from the specific design and techniques/contexts. This paper aims at proposing an approach for a shared 3D survey workflow for photogrammetry in archaeology. The general approach relies on the digital data curation framework for cultural heritage and encompasses several specialized tasks. We describe the general functions and processes and how they can be implemented in a practical workflow. As a proof of concept, we show how a preliminary release of the workflow has been applied in the context of the BeArchaeo project, for the acquisition, processing, export, modeling, archiving, and indexing of 3D models, resulting from photogrammetric surveys. A long-term aim is a methodological approach for different endeavors of cultural heritage.
Evaluation of Biofilm Cultivation Models for Efficacy Testing of Disinfectants against Salmonella Typhimurium Biofilms

Within the European Union, Salmonella is frequently reported in food and feed products. A major route of transmission is upon contact with contaminated surfaces. In nature, bacteria such as Salmonella are often encountered in biofilms, where they are protected against antibiotics and disinfectants. Therefore, the removal and inactivation of biofilms is essential to ensure hygienic conditions. Currently, recommendations for disinfectant usage are based on results of efficacy testing against planktonic bacteria. There are no biofilm-specific standards for the efficacy testing of disinfectants against Salmonella. Here, we assessed three models for disinfectant efficacy testing on Salmonella Typhimurium biofilms. Achievable bacterial counts per biofilm, repeatability, and intra-laboratory reproducibility were analyzed. Biofilms of two Salmonella strains were grown on different surfaces and treated with glutaraldehyde or peracetic acid. Disinfectant efficacy was compared with results for planktonic Salmonella. All methods resulted in highly repeatable cell numbers per biofilm, with one assay showing variations of less than 1 log10 CFU in all experiments for both strains tested. Disinfectant concentrations required to inactivate biofilms were higher compared to planktonic cells. Differences were found between the biofilm methods regarding maximal achievable cell numbers, repeatability, and intra-laboratory reproducibility of results, which may be used to identify the most appropriate method in relation to application context. Developing a standardized protocol for testing disinfectant efficacy on biofilms will help identify conditions that are effective against biofilms.
Deletion diagnostics for transformations of time series

Deletion diagnostics are derived for the effect of individual observations on the estimated transformation of a time series. The paper uses the modified power transformation of Box and Cox to provide a parametric family of transformations. Inference about the transformation parameter is made through regression on a constructed variable. The effect of deletion of observations on residuals and on the estimate of the regression parameter are obtained. Index plots of the diagnostic quantities are shown to be highly informative. Structural time series modelling is used, so that the results readily extend to inference about regression on other explanatory variables.
Bio-priming of banana tissue culture plantlets with endophytic Bacillus velezensis EB1 to improve Fusarium wilt resistance

Tissue culture techniques have been routinely used for banana propagation and offered rapid production of planting materials with favorable genotypes and free of pathogenic microorganisms in the banana industry. Meanwhile, extensive scientific work suggests that micropropagated plantlets are more susceptible to Fusarium oxysporum f. sp. cubense (Foc), the deadly strain that causes Fusarium wilt of bananas than conventional planting material due to the loss of indigenous endophytes. In this study, an endophytic bacterium Bacillus velezensis EB1 was isolated and characterized. EB1 shows remarkable in vitro antagonistic activity against Foc with an inhibition rate of 75.43% and induces significant morphological and ultrastructural changes and alterations in the hyphae of Foc. Colony-forming unit (c.f.u.) counting and scanning electron microscopy (SEM) revealed that EB1 could colonize both the surface and inner tissues of banana tissue culture plantlets. Banana tissue culture plantlets of late rooting stage bioprimed with EB1 could efficiently ward off the invasive of Foc. The bio-priming effect could maintain in the acclimatized banana plants and significantly decrease the disease severity of Fusarium wilt and induce strong disease resistance by manipulating plant defense signaling pathways in a pot experiment. Our results provide the adaptability and potential of native endophyte EB1 in protecting plants from pathogens and infer that banana tissue culture plantlets bio-priming with endophytic microbiota could be a promising biological solution in the fight against the Fusarium wilt of banana.
A Review of Depth-Based Human Motion Enhancement: Past and Present

In this article, we survey the current research trends of enhancement and denoising of depth-based motion capture data (D-Mocap) and also discuss possible future research issues. We first present the commonly used problem formulation for human motion enhancement. We then review related work and cover a broad set of methodologies including filtering based, learning based, and evolutionary based approaches. In addition, we present some important experiments-related issues, such as data creation or collection, reference data generation, and the metrics used for performance evaluation. It is our intent to provide a comprehensive tutorial and survey on the recent efforts on D-Mocap improvement, both methodologically and experimentally. By comparing the state-of-the-art methods, we also propose future research needs that could make D-Mocap more useful and relevant for real-world clinical applications.