Miracle-dz/UniFAR-FTUs huggingface dataset:
Mesoscale texture of cement hydrates

Significance Calcium–silicate–hydrate (C–S–H) nanoscale gels are the main binding agent in cement and concrete, crucial for the strength and the long-term evolution of the material. Even more than the molecular structure, the C–S–H mesoscale amorphous texture over hundreds of nanometers plays a crucial role for material properties. We use a statistical physics framework for aggregating nanoparticles and numerical simulations to obtain a first, to our knowledge, quantitative model for such a complex material. The extensive comparison with experiments ranging from small-angle neutron scattering, SEM, adsorption/desorption of N2, and water to nanoindentation provides new fundamental insights into the microscopic origin of the properties measured. Strength and other mechanical properties of cement and concrete rely upon the formation of calcium–silicate–hydrates (C–S–H) during cement hydration. Controlling structure and properties of the C–S–H phase is a challenge, due to the complexity of this hydration product and of the mechanisms that drive its precipitation from the ionic solution upon dissolution of cement grains in water. Departing from traditional models mostly focused on length scales above the micrometer, recent research addressed the molecular structure of C–S–H. However, small-angle neutron scattering, electron-microscopy imaging, and nanoindentation experiments suggest that its mesoscale organization, extending over hundreds of nanometers, may be more important. Here we unveil the C–S–H mesoscale texture, a crucial step to connect the fundamental scales to the macroscale of engineering properties. We use simulations that combine information of the nanoscale building units of C–S–H and their effective interactions, obtained from atomistic simulations and experiments, into a statistical physics framework for aggregating nanoparticles. We compute small-angle scattering intensities, pore size distributions, specific surface area, local densities, indentation modulus, and hardness of the material, providing quantitative understanding of different experimental investigations. Our results provide insight into how the heterogeneities developed during the early stages of hydration persist in the structure of C–S–H and impact the mechanical performance of the hardened cement paste. Unraveling such links in cement hydrates can be groundbreaking and controlling them can be the key to smarter mix designs of cementitious materials.
Job Satisfaction in the Home Health Care Context: Validating a Customized Instrument for Application

EXECUTIVE SUMMARY The purpose of this study is to present the development and validation process of a customized job satisfaction instrument within the home health care setting. During development, home health care agency directors selected items from preexisting scales to create a new 15‐item instrument designed to measure job satisfaction, supervisory relationships, and job environment. The instrument's reliability and validity were examined using a two‐step approach. First, exploratory factor analysis (EFA) was carried out with a sample of 398 aides, and three factors were identified. Second, confirmatory factor analysis was conducted with an independent sample of 328 aides using the three‐factor solution that was selected from the EFA. The reliability estimates for the job satisfaction, supervisory relationships, and job environment scales were 0.84, 0.93, and 0.74, respectively. Results from this study yield a statistically sound instrument that offers potential advantages to those interested in better understanding job satisfaction and two related constructs of employees in health‐related fields. Both research and practical implications are discussed. The final instrument will be a valuable tool for collecting information from home health care workers, a population that has historically been difficult to access and measure.
Different transmitter transients underlie presynaptic cell type specificity of GABAA,slow and GABAA,fast

Phasic (synaptic) and tonic (extrasynaptic) inhibition represent the two most fundamental forms of GABAA receptor-mediated transmission. Inhibitory postsynaptic currents (IPSCs) generated by GABAA receptors are typically extremely rapid synaptic events that do not last beyond a few milliseconds. Although unusually slow GABAA IPSCs, lasting for tens of milliseconds, have been observed in recordings of spontaneous events, their origin and mechanisms are not known. We show that neocortical GABAA,slow IPSCs originate from a specialized interneuron called neurogliaform cells. Compared with classical GABAA,fast IPSCs evoked by basket cells, single spikes in neurogliaform cells evoke extraordinarily prolonged GABAA responses that display tight regulation by transporters, low peak GABA concentration, unusual benzodiazepine modulation, and spillover. These results reveal a form of GABAA receptor mediated communication by a dedicated cell type that produces slow ionotropic responses with properties intermediate between phasic and tonic inhibition.
Outage Probability Analysis of DF Relay Networks with RF Energy Harvesting

In this paper, we analyze the outage probability of a three-node decode-and-forward (DF) relay network, where the relay adopts a power-splitting protocol to harvest energy from the received signal, and utilizes the harvested energy to forward information. First of all, the theoretical expression of outage probability is derived, and then the closed forms of the optimal amount of harvested energy and the best relay location are achieved analytically in order to minimize the outage probability. Furthermore, the condition that the outage performance with energy harvesting (EH) surpasses that without EH is also deduced to figure out when EH is indispensable to relay enhancements. Numerical results verify the correctness of our theoretical derivation, and validate that there exist the optimal amount of harvested energy and the best relay location to reach the minimum outage probability in the energy harvesting relay network. The work of this paper will provide valuable insights into the effect of harvested energy and relay location on outage probability, and be instrumental in how to deploy relays with RF energy harvesting functions.
Quantitative RNA-seq analysis of the Campylobacter jejuni transcriptome

Campylobacter jejuni is the most common bacterial cause of foodborne disease in the developed world. Its general physiology and biochemistry, as well as the mechanisms enabling it to colonize and cause disease in various hosts, are not well understood, and new approaches are required to understand its basic biology. High-throughput sequencing technologies provide unprecedented opportunities for functional genomic research. Recent studies have shown that direct Illumina sequencing of cDNA (RNA-seq) is a useful technique for the quantitative and qualitative examination of transcriptomes. In this study we report RNA-seq analyses of the transcriptomes of C. jejuni (NCTC11168) and its rpoN mutant. This has allowed the identification of hitherto unknown transcriptional units, and further defines the regulon that is dependent on rpoN for expression. The analysis of the NCTC11168 transcriptome was supplemented by additional proteomic analysis using liquid chromatography-MS. The transcriptomic and proteomic datasets represent an important resource for the Campylobacter research community.
SPRWeb: preserving subjective responses to website colour schemes through automatic recolouring

Colours are an important part of user experiences on the Web. Colour schemes influence the aesthetics, first impressions and long-term engagement with websites. However, five percent of people perceive a subset of all colours because they have colour vision deficiency (CVD), resulting in an unequal and less-rich user experience on the Web. Traditionally, people with CVD have been supported by recolouring tools that improve colour differentiability, but do not consider the subjective properties of colour schemes while recolouring. To address this, we developed SPRWeb, a tool that recolours websites to preserve subjective responses and improve colour differentiability - thus enabling users with CVD to have similar online experiences. To develop SPRWeb, we extended existing models of non-CVD subjective responses to CVD, then used this extended model to steer the recolouring process. In a lab study, we found that SPRWeb did significantly better than a standard recolouring tool at preserving the temperature and naturalness of websites, while achieving similar weight and differentiability preservation. We also found that recolouring did not preserve activity, and hypothesize that visual complexity influences activity more than colour. SPRWeb is the first tool to automatically preserve the subjective and perceptual properties of website colour schemes thereby equalizing the colour-based web experience for people with CVD.
Beating LM-Cut with hmax (Sometimes): Fork-Decoupled State Space Search

Factored planning decouples planning tasks into subsets (factors) of state variables. The traditional focus is on handling complex cross-factor interactions. Departing from this, we introduce a form of target-profile factoring, forcing the cross-factor interactions to take the form of a fork, with several leaf factors and one potentially very large root factor. We show that forward state space search gracefully extends to such structure, by augmenting regular search on the root factor with maintenance of the cheapest compliant paths within each leaf factor. We analyze how to guarantee optimality. Connecting to standard heuristics, the performance improvements relative to A* are substantial, and sometimes dramatic: In four IPC benchmark domains, fork-decoupled state space search outperforms standard state space search even when using h^max in the former vs. LM-cut in the latter.
A Survey of Machine Learning Approaches and Techniques for Student Dropout Prediction

School dropout is absenteeism from school for no good reason for a continuous number of days. Addressing this challenge requires a thorough understanding of the underlying issues and effective planning for interventions. Over the years machine learning has gained much attention on addressing the problem of students dropout. This is because machine learning techniques can effectively facilitate determination of at-risk students and timely planning for interventions. In order to collect, organize, and synthesize existing knowledge in the field of machine learning on addressing student dropout; literature in academic journals, books and case studies have been surveyed. The survey reveal that, several machine learning algorithms have been proposed in literature. However, most of those algorithms have been developed and tested in developed countries. Hence, developing countries are facing lack of research on the use of machine learning on addressing this problem. Furthermore, many studies focus on addressing student dropout using student level datasets. However, developing countries need to include school level datasets due to the issue of limited resources. Therefore, this paper presents an overview of machine learning in education with the focus on techniques for student dropout prediction. Furthermore, the paper highlights open challenges for future research directions.
Texture Image Segmentation Using Wavelet Filters and Cellular Neural Network

This paper presents a texture segmentation algorithm based on Discrete Wavelet Frames(DWF) and Cellular Neural Network(CNN). DWF, zero-crossing, texture energy and selective local averaging are used to get a texture feature extraction and t,o form feature images. Each feature image is segmented into parts by several gray range in its gray histogram. Resulting in the number of pixels that conform to each gray range composition of every feature image, segmentation can be got by those compositions that have a big pixel number. We call this method "CompositionArray method". A new CNN called "Multi-objective CNN" is developed using the fundamental theory of the traditional CNN, it is a multi-objective neural processing instead of 1 and -1 only. The noise of Composition-Array processing can be removed using this new CNN, and we can get a perfect final segmentation result,.
Heuristic Designs of SAD Algorithm for a Platform-Based Vision System

Vision sensors provide rich sources of information, but sensing images and processing them in real time would be a challenging task. This paper introduces a vision system using SoCBase platform and presents heuristic designs of SAD correlation algorithm as a component of the vision system. Simulation results show that the vision system is suitable for real-time applications and that the heuristic designs of SAD algorithm are worth utilizing since they save a considerable amount of space with little sacrificing in quality.
Comparison of Three-Dimensional Micro-CT Angiography of Cervical Spinal Cord between Two Contrast Agents

Purpose Barium sulfate and lead oxide are commonly used for angiographic studies, but there is no report on the comparison of two contrast agents in angiography of cervical spinal cord. This study was aimed to compare the microvascular architecture of cervical spinal cord in rats after angiography with the barium sulfate agent to the lead oxide agent. Methods Twelve adult Sprague-Dawley rats were randomly divided into the barium sulfate group (n=6) and the lead oxide group (n=6). Each rat was perfused under the same protocol using either two contrast agents. The angiography was evaluated with the vascular number at different ranks. The cervical spinal cord samples were scanned using micro-CT with low resolution and high resolution. The microvascular parameters, including ratio of vascular volume to tissue volume (VV/TV), vascular number (V.N), diameter (V.Dm), separation (V.Sp), connectivity density (Conn.D), structure model index (SMI), percentage, and volume of vessels at different diameters were measured. Results The perfusion was better in the barium sulfate group, with more blood vessel trees of rank II and III visible compared to the lead oxide group. Low-resolution micro-CT analysis showed no difference in microvascular parameters except SMI between the two groups. High-resolution micro-CT analysis results showed that V.N and Conn.D of barium sulfate group were 60% and 290% more than those of the lead oxide group; however, V.Sp was 41% less than the lead oxide group. The percentage of vessels with diameter of 10 μm and 20 μm, and the volume of vessels with diameter of less than 100 μm was higher in the barium sulfate group than in the lead oxide group. The SMI index in the barium sulfate group was higher than that in the lead oxide group at both low resolution and high resolution. Conclusions Compared with lead oxide, barium sulfate is more suitable for perfusion of cervical spinal cord microvessels, and cheap and nontoxic with high resolution.
First principle study of magnetism and vacancy energetics in a near equimolar NiFeMnCr high entropy alloy

We report the results of ab initio calculations of a novel NiFeMnCr high entropy alloy (HEA) with potential applications as a high performance structural material. The bulk and defect property variations due to chemical disordering and magnetic frustration have been studied using both supercell and coherent potential approximation-based techniques. While magnetic frustration due to the presence of multiple 3d transition metals can severely affect the accuracy of vacancy formation energy in first-principles calculations, this effect should be suppressed at intermediate and high temperatures. An efficient approach to evaluate the chemical potential in HEA is constructed and implemented. Vacancy formation energies are computed based on the chemical potential. The statistical distribution of formation energies is weakly dependent upon the chemical identity of the vacancy. On the other hand, the calculated vacancy migration energies show that Fe is more likely to have a large migration barrier than Cr, Mn, or Ni. Finally, atomic-level stresses are computed. A qualitative model to explain the elemental segregation trend in HEA is built upon the atomic-level stress calculation results and provides a reasonable qualitative agreement with ion irradiation experimental data of a NiFeMnCr HEA.We report the results of ab initio calculations of a novel NiFeMnCr high entropy alloy (HEA) with potential applications as a high performance structural material. The bulk and defect property variations due to chemical disordering and magnetic frustration have been studied using both supercell and coherent potential approximation-based techniques. While magnetic frustration due to the presence of multiple 3d transition metals can severely affect the accuracy of vacancy formation energy in first-principles calculations, this effect should be suppressed at intermediate and high temperatures. An efficient approach to evaluate the chemical potential in HEA is constructed and implemented. Vacancy formation energies are computed based on the chemical potential. The statistical distribution of formation energies is weakly dependent upon the chemical identity of the vacancy. On the other hand, the calculated vacancy migration energies show that Fe is more likely to have a large migration barrier than Cr, Mn, or .
SIMULATION AND VISUALIZATION SYSTEM FOR SENSOR AND ACTUATOR DATA GENERATION

Abstract The evolution of automation systems has reached a point where the increasing complexity requires new mechanisms to keep control of design and operation. In future all control systems will have to cope with massive data quantities that are collected from the environment. Such systems have to react based on the recognition of whole scenarios. In this paper we present a simulation tool, which is able to generate big amounts of sensor data in an animated, virtual environment. This data is used by two different systems to verify their accuracy.
Variation of refractive index of synthetic Mg-cordierite with H 2 O content

The mean refractive index of grain mounts has been measured for 50 synthetic end-member Mg-cordierites with water contents varying from 0.83 to 2.9O weight percent. A linear relationship appears adequate to describe the variation of the mean refractive index with water content and can be formulated as W : [n(m) - n(mo)]/0.00762 (esd:0.13 weight percent H2O) where W : HzO content in weight percent; n(m) : mean refractive index of hydrated Mgcordierite; and n(mo) : mean refractive index of the anhydrous starting material. The calibration curve is useful to determine water contents of Mg-cordierites in multiphase reaction products of the appropriate experimental systems. No change in the distortion index upon hydration of anhydrous Mg-cordierite has been observed, so the Stout model of cordierite hydration cannot be applicable to end-member Mg-cordierite.
Reflection vector shading hardware

Surface reflections of an environment can be rendered in real time if hardware calculates an unnormalized reflection vector at each pixel. Conventional perspective-correct texture hardware can then be leveraged to draw high-quality reflections of an environment or specular highlights in real time. This fully accommodates area light sources, allows a local viewer to move interactively, and is especially well suited to the inspection of surface orientation and curvature. By emphasizing the richness of the incoming illumination rather than physical surface properties, it represents a new direction for real-time shading hardware.
The multiple classifiers combination method for improving the accuracy of remotely sensed data classification

In this paper, the standard multiple classifier combination method was used for land cover mapping using remotely sensed data. Landsat TM data in Lanier Lake was used as an experimental data. Land cover maps were derived by combining classifiers at abstract level with same training features, combining classifiers at abstract level with different training features and by combining classifiers at measurement level respectively. Classification accuracies of these maps were compared with those of classifiers was combined. Results showed that for all classifiers combination methods, the classification accuracies were improved. Advantages and drawbacks of every method of classifiers combination were analyzed and further study in combining multiple classifiers for remotely sensed data classification was suggested.
Does Change of Catecholamine Use Improve the Outcome of Patients With Shock Admitted to Intensive Care Unit?

Up to 2008, dopamine was the catecholamine that was the most recommended in our intensive care unit (ICU) after fluid resuscitation. However, recently, norepinephrine has become the catecholamine that was most recommended in our ICU after fluid resuscitation. The aim of this study was to determine if there was an efficacy or safety benefit to this protocol therapeutic change in patients with shock admitted to our ICU. The primary outcome variable was ICU mortality. This is a prospective observational study conducted in 2 periods in our ICU (Habib Bourguiba University Hospital, Sfax, Tunisia). During the 2 study periods, 251 patients were included. There were 130 patients in group 1 and 121 patients in group 2. There were no significant differences between the 2 groups with regard to most of the baseline characteristics. The comparison between the 2 groups showed that in the first period, dopamine was the catecholamine that was the most used. However, in the second period, norepinephrine is the catecholamine that was most used. When we analyzed the catecholamine prescription in septic shock, we concluded that in the first study period, dopamine was used as the catecholamine as the first choice in 85.7% of cases (P < 0.001), and norepinephrine is the first choice in 100% of cases in the second period. In cardiogenic shock, in the first study period, dobutamine was used as the catecholamine as the first choice in 61% of cases (P < 0.001) and norepinephrine is the first choice in 43% of cases in the second period. Finally, in hypovolemic shock, dopamine was used as the catecholamine as the first choice in 68% of cases in group 1 and norepinephrine is the first choice in 88% of cases in the second period (P < 0.001). During the ICU stay, some adverse events related to catecholamine use were observed. The occurrence of arrhythmias was significantly more frequent in the first group. Mortality rate was at 51% in the first group and 44% in the second group (P = 0.27). The mortality rate was not significantly different for each type of shock (septic, cardiogenic, and hypovolemic) in both groups (P > 0.05 for all), although the occurrence of arrhythmias was significantly more frequent in the first group, in clinical practice, our study confirms that the rate of death did not differ significantly between the 2 groups of patients mostly treated with dopamine (group 1) and the group mostly treated with norepinephrine.