Miracle-dz/UniFAR-FTUs huggingface dataset:
Silk ProteinsEnriched Nanocomposite Hydrogels Based on Modified MMT Clay and Poly(2-hydroxyethyl methacrylate-co-2-acrylamido-2-methylpropane Sulfonic Acid) Display Favorable Properties for Soft Tissue Engineering

Due to their remarkable structures and properties, three-dimensional hydrogels and nanostructured clay particles have been extensively studied and have shown a high potential for tissue engineering as solutions for tissue defects. In this study, four types of 2-hydroxyethyl methacrylate/2-acrylamido-2-methylpropane sulfonic acid/montmorillonite (HEMA/AMPSA/MMT) hydrogels enriched with sericin, and fibroin were prepared and studied in the context of regenerative medicine for soft tissue regenerative medicine. Our aim was to obtain crosslinked hydrogel structures using modified montmorillonite clay as a crosslinking agent. In order to improve the in vitro and in vivo biocompatibility, silk proteins were further incorporated within the hydrogel matrix. Fourier transform infrared spectroscopy with attenuated total reflectance (FTIR-ATR) were performed to prove the chemical structures of the modified MMT and nanocomposite hydrogels. Swelling and rheological measurements showed the good elastic behavior of the hydrogels due to this unique network structure in which modified MMT acts as a crosslinking agent. Hydrogel biocompatibility was assessed by MTT, LDH and LIVE/DEAD assays. The hydrogels were evaluated for their potential to support adipogenesis in vitro and human stem cells isolated from adipose tissue were seeded in them and induced to differentiate. The progress was assessed by evaluation of expression of adipogenic markers (ppar-γ2, perilipin) evaluated by qPCR. The potential of the materials to support tissue regeneration was further evaluated on animal models in vivo. All materials proved to be biocompatible, with better results on the 95% HEMA 5% AMPSA enriched with sericin and fibroin material. This composition promoted a better development of adipogenesis compared to the other compositions studied, due the addition of sericin and fibroin. The results were confirmed in vivo as well, with a better progress of soft tissue regeneration after implantation in mice. Therefore, hydrogel 95% HEMA 5% AMPSA enriched with sericin as well as fibroin showed the best results that recommend it for future soft tissue engineering application.
Room Temperature Deposition of Nanocrystalline SiC Thin Films by DCMS/HiPIMS Co-Sputtering Technique

Due to an attractive combination of chemical and physical properties, silicon carbide (SiC) thin films are excellent candidates for coatings to be used in harsh environment applications or as protective coatings in heat exchanger applications. This work reports the deposition of near-stoichiometric and nanocrystalline SiC thin films, at room temperature, on silicon (100) substrates using a DCMS/HiPIMS co-sputtering technique (DCMS—direct current magnetron sputtering; HiPIMS—high-power impulse magnetron sputtering). Their structural and mechanical properties were analyzed as a function of the process gas pressure. The correlation between the films’ microstructure and their mechanical properties was thoroughly investigated. The microstructure and morphology of these films were examined by appropriate microscopic and spectroscopic methods: atomic force microscopy (AFM), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), and Raman spectroscopy, while their mechanical and tribological properties were evaluated by instrumented indentation and micro-scratch techniques. The lowest value of the working gas pressure resulted in SiC films of high crystallinity, as well as in an improvement in their mechanical performances. Both hardness (H) and Young’s modulus (E) values were observed to be significantly influenced by the sputtering gas pressure. Decreasing the gas pressure from 2.0 to 0.5 Pa led to an increase in H and E values from 8.2 to 20.7 GPa and from 106.3 to 240.0 GPa, respectively. Both the H/E ratio and critical adhesion load values follow the same trend and increase from 0.077 to 0.086 and from 1.55 to 3.85 N, respectively.
Application of dynamic innovation GM(1,1) to power prediction of satellite battery array

The early forecast of satellite battery array's performance attenuation can been realized according to the prediction of historical datum of satellite battery array's output power. The GM(1,1) of grey prediction method fits model for time series prediction of monotonic increasing or degression only. A real time method is proposed according to the fluctuant character of batter matrix output power. The prediction model of dynamic innovation GM(1,1) is founded in this paper. The prediction precision is improved greatly by example. What's more, the fluctuant tendency of batter array output power can be predicted exactly. The method of model making has referential value for other prediction of non monotonic time series.
FUZZY SYNTHETIC EVALUATION OF POWER QUALITY BASED ON CHANGEABLE WEIGHT

The quantified description from power quality synthetic evaluation is available for reference to the consumers in choosing the power suppliers, and it is also beneficial to fix the price according to the quality of electric energy. Combining the analytic hierarchy process (AHP) with fuzzy theory, at first the subjective weights are obtained, then by means of modifying the obtained subjective weights the changeable synthetic weights are formed, at last power quality at the point of common coupling(PCC) is evaluated by fuzzy synthetic evaluation and the power quality level and the power quality factor are obtained. Case results show that the proposed method is beneficial to distinguish power quality level and to conduct the quantitative and qualitative evaluation of power quality.
Fault Diagnosis of Electronic Throttle System Using Parameter Estimation

The use of electronics, intelligent sensors/actuators and microprocessor-based control technology enables online real-time fault detection and diagnosis (FDD) of automobiles. In this paper, a FDD method for electronic throttle system is proposed. The proposed FDD method is based on parameter estimation in closed-loop and a nonlinear model of the electronic throttle system. The nonlinear mathematical model of the electronic throttle system is identified in closed-loop, and then the parameter estimation technique is applied to the closed-loop nonlinear system model for the detection and isolation of faults. The simulation results are presented to investigate the performance and effectiveness of the proposed method.
Using mobile phone big data to discover the spatial patterns of rural migrant workers’ return to work in China’s three urban agglomerations in the post-COVID-19 era

Knowing how workers return to work is a key policymaking issue for economic recovery in the post-COVID-19 era. This paper uses country-wide time-series mobile phone big data (comparing monthly and annual figures), obtained between February 2019 and October 2019 and between February 2020 and October 2020, to discover the spatial patterns of rural migrant workers’ (RMWs’) return to work in China’s three urban agglomerations (UAs): the Beijing–Tianjin–Hebei Region, the Yangtze River Delta and the Pearl River Delta. Spatial patterns of RMWs’ return to work and how these patterns vary with location, city level and human attribute were investigated using the fine-scale social sensing related to post-pandemic human mobility. The results confirmed the multidimensional spatiotemporal differentiations, interaction effects between variable pairs and effects of the actual situation on the changing patterns of RMWs’ return to work. The spatial patterns of RMWs’ return to work in China’s major three UAs can be regarded as a comprehensive and complex interaction result accompanying the nationwide population redistribution, which was affected by various hidden factors. Our findings provide crucial implications and suggestions for data-informed policy decisions for a harmonious society in the post-COVID-19 era.
Realisation of online musical instrument instruction during the COVID-19 pandemic: Perspectives of music school teachers

Since the COVID-19 pandemic made online classes a necessity throughout the world, Serbia included, the music education system has gone through an extensive transformation, and the teachers faced a number of difficulties and challenges in their work. With this paper, we wanted to provide a clear insight into the teaching practices that were established after the pandemic was declared. The goal was to identify the obstacles that appeared in online classes for musical instruments, but also the advantages that, according to the teachers, may be integrated into traditional classes once the pandemic is over. The research was based on a sample of 220 teachers of elementary music schools, combining a qualitative and quantitative analysis of the obtained data. The results have shown that teachers, younger ones in particular, overcome the obstacles of online teaching without major difficulties. As to the particular difficulties they encountered, the teachers most often mentioned those of a technical nature, and the inability to properly work on the techniques of playing an instrument due to the lack of a direct contact with the students. Almost all of the teachers feel that the students cannot improve their skills through online classes as effectively as in a regular class. However, in their future work, the teachers would continue to make audio and video recordings of themselves and their students playing, and practice online teaching when the students are sick or otherwise unable to attend regular classes. The pedagogical implications of this research are that it is necessary to implement technological solutions that would support all aspects of instrument instruction, but also to intensify technical support for teachers, particularly older ones, regarding competences needed for online classes.
The Effect of the US Macroeconomic Indicators on the International Geopolitical Risk

ABSTRACT The recent economic literature concludes that geopolitical risk has significantly impacted various economic variables over the past years. This paper focuses on a new dimension and seeks to answer if the US major macroeconomic indicators affect the international geopolitical risk (GPR). Based on our knowledge, there is no such study conducted so far, and thus, we propose to fill this gap. We constructed a theoretical framework and estimated an econometric model using the Autoregressive Distributed Lag methodology and quarterly data (1973–2020). The results show a statistically significant effect of the US macroeconomic variables on the GPR. The long-run results are decisive and unique, while the short-run influences are mixed in significance levels and signs. Hence, the short-run impact may differ over time and its final impact depends on the outweighing effect between the harmful and beneficial outcomes. The findings prove that a dominant country with economic and political powers can influence the GPR. From a policy implication side, we affirm that globalization should proceed side by side with cooperation and coordination among nations to solve economic glitches. Otherwise, geopolitical risk will make the economic performance worse.
Negative impact of roadside mowing on arthropod fauna and its reduction with ‘arthropod‐friendly’ mowing technique

An underestimated factor that contributes to the decline of insects observed during the last year is probably the mortality, which is caused by mowing of grassland. We studied the negative impact of mowing on the arthropod fauna of roadside grassland, which might serve as potential habitat for insects to prevent their local extinction and as corridor for the dispersal in anthropogenic landscapes. In addition, we studied if losses due to mowing can be mitigated by the use of ‘arthropod‐friendly’ mowing technique. In agreement with earlier studies, we found that mowing with a conventional mowing head (MK 1200 from MULAG) caused considerable losses in arthropods, ranging from 29% for Heteroptera over around 50% in Araneae, Cicadina, Hymenoptera and Diptera, up to 73% for holometabolous larvae, and 87% for Lepidoptera. These losses by mowing were fully offset for Araneae, Cicadina, Heteroptera, Lepidoptera and larvae of holometabolous insects when using the mowing head Eco 1200 from MULAG, which was designed to be ‘arthropod‐friendly’. For Hymenoptera and Diptera, the losses were reduced by 15% and 25% respectively. For Saltatoria and Coleoptera, we did not find any significant differences between all treatments. These data demonstrate that mowing of roadsides with conventional mowing technology has a highly detrimental effect on the grassland arthropod fauna. However, this effect can be offset or at least mitigated by the use of ‘arthropod‐friendly’ mowing technique. Therefore, this technique has a high potential to reduce insect decline in roadside grassland, making these areas a habitat for insects.
Intelligent Detection and Analysis of Polycyclic Aromatic Hydrocarbons Based on Surface-Enhanced Raman Scattering Spectroscopy

Cycloaromatic hydrocarbons are a type of potentially hazardous chemicals that are widely present in the environment and pose a serious threat to human health. However, the traditional research methods for their detection process are cumbersome, the detection cycle is long, and the sensitivity is low. In response to the above problems, this article combines the molecular fingerprint information characteristics of surface-enhanced Raman scattering technology to simulate the four polycyclic aromatic hydrocarbons of pyrene, anthracene, phenanthrene, and trichenium and quantitative detection of cyclic aromatic hydrocarbons and four kinds of polycyclic aromatic hydrocarbon mixtures. The experimental results show that the PAHs based on SERS have the advantages of higher sensitivity and high selectivity, which verifies the accuracy and feasibility of the method in this article.
Modeling and Optimization of Water Distribution in Mineral Processing considering Water Cost and Recycled Water

Reducing mineral processing water costs and freshwater consumption is a challenging task in the mineral processing water distribution (MPWD). The work presented in this paper focuses on two aspects of the MPWD optimization model and the MPWD optimization method. To achieve MPWD optimization effectively, a nonlinear constrained multiobjective model is built. The problem is formulated with two objectives of minimizing the mineral processing water costs and maximizing the amount of recycled water. In this paper, an optimization method named enhancing the multiobjective artificial bee colony (EMOABC) algorithm is proposed to solve this model. The EMOABC algorithm uses four strategies to obtain the Pareto-optimal solutions and to achieve the MPWD optimal solutions. With the three benchmark functions, the EMOABC algorithm outperforms the other two widely used algorithms in solving complex multiobjective optimization problems. The EMOABC algorithm is then applied to two cases. Results have shown that the proposed algorithm has the ability to solve the MPWD optimization model. The developed model and the proposed algorithm provide decision support for the actual MPWD problem.
Effects of Mechanical Wheel Slide Protection Devices Action on Railway Vehicles Braking Process

The paper investigates the effects of mechanical wheel slide protection devices (WSPD) on the braking capacity for coaches equipped with disc or cast iron block brakes. Decelerations and jerks, that affect the passengers comfort, are also analyzed. An original simulation program, based on experimentally determined air pressure evolutions in brake cylinder is used for this purpose. Results of numerical simulations show that in the case of repeated actuations of mechanical WSPDs, disc brake vehicles are more affected in terms of braking capacity. Regarding jerks during braking actions, in both normal and low adhesion conditions, vehicles equipped with high power cast iron block brake with two pressure levels prove to be more affected.
Design and Characteristic Analysis of a Buckling Plate Vibration Isolator with Quasi-zero-stiffness

This paper presented the prototype of a buckling plate vibration isolator with the propitious characteristic of quasi-zero stiffness(QZS). The isolator was devised by combining a rubber pad with a buckling steel plate.To facilitate the analysis of the characteristics of the QZS isolator,an approximate expression of force and displacement was formulated on the basis of Abaqus analysis and Matlab tool.Analytical result reveals the stiffness criterion of the supporting rubber for the QZS system.The force transmissibility of the vibration isolation systems was derived in the harmonic balance method(HB),and the effects of the damping were investigated for the performance evaluation of the systems.The results show that the QZS isolator can outperform the linear system in low frequency domain,and there is no involvement of resonance when damping is set properly.
Measuring red tape in a hospital setting: A survey experiment

Public administration research is actively exploring alternatives for the General Red Tape (GRT) scale to measure red tape. Owing to increasing criticism on the GRT scale, scholars proposed the Three-Item Red Tape (TIRT) scale as an alternative. Using a repeated cross-sectional design, this article tests both scales in a before–after analysis of a major change in the organization of administration in a hospital. The results indicate that the GRT scale does not capture the resulting major change in red tape, which raises questions on the instrument's validity in a bottom-up research design within one organization. The TIRT scale, however, which measures red tape at the work environment level, does reflect the change in red tape but shows empirical weaknesses in its design. Additionally, by randomly assigning respondents to substantially different red tape definitions, this article shows that the red tape definition does not significantly impact respondents’ GRT ratings. Points for practitioners The predominantly used GRT scale is not able to capture an increase in red tape in a bottom-up intraorganizational research design in a hospital, which raises questions on the instrument's validity. A more recent alternative for the GRT scale, more specifically the TIRT scale, captures the increase in red tape but shows empirical weaknesses. The wording of the red tape definition does not impact respondents’ answers on the GRT scale.
Higher-order semi-rational solutions for the coupled complex modified Korteweg-de Vries equation

We explore the Darboux-dressing transformation of the coupled complex modified Korteweg-de Vries equation. Next, with the aid of an asymptotic expansion theory, we derive the concrete forms of three types of semi-rational solutions. In particular, the seed solution is related to the normalized distance and retarded time. Interestingly, we construct a kind of novel rogue wave called as curve rogue wave. More importantly, the kinetics of semi-rational solutions are discussed in detail. We hope that these results would shed more light on comprehending of the solutions occurring in multi-component coupled systems.
Erratum

First, the Cortesi, Giannotti, Sebastiani, Panunzi, & Valente (2012) article was coded under the ‘‘children/adolescents’’ category when the population studied was exclusively children with autism spectrum disorders and thus should have been in the category of ‘‘special populations. ’’ Second, the Blunden 2011 study was labeled as ‘‘graduated extinction’’ when it is more appropriately described as a ‘‘responsive behavioral sleep intervention. ’’ This article presents the revised Tables I, III, and IV and two text paragraphs. These corrections do not affect any other results or the conclusions reached in this review.
Defining and measuring time poverty in South Africa

ABSTRACT This study primarily adopted the absolute approach to examine time poverty in South Africa by analysing the 2000 and 2010 Time Use Survey data. The findings indicated that absolute time-poor individuals were predominantly young unmarried female Africans who had incomplete primary education, were inactive in the labour market and resided in bigger-sized households in KwaZulu-Natal and Gauteng. Examining the relationship between money-metric poverty and absolute time poverty, the results showed the proportion of people who were both income- and time-poor decreased whereas the percentage of individuals who were neither income- nor time-poor increased over time. Last, money-metric, multidimensional non-money-metric and absolute time poverty headcount rates all declined between 2000 and 2010, but the extent of decrease was greatest in the first rate.
Physicochemical Properties Importance For Type Classification of Wines Using Machine Learning Techniques

As a subfield of artificial intelligence, machine learning designed to learn the structure of the data. Machine learning has been widely used in many scientific problems. In this study, we used machine learning techniques to figure out the most important physicochemical properties for type classification of red wines. We used a wines' dataset with 13 physicochemical properties. We used a Random Forest classifier to predict wine’s type from its features, and permutation feature importance, in order to detect the most important properties of the wine for type classification. The properties: flavanoids, proline, and color intensity were found to be most important for type classification. Additional 4 classifiers: Laso classifier, Ridge classifier, Decision Tree classifier, and Support Vector classifier were used and examined for classification and feature importance. Flavanoids and proline were very important across all classifiers.
A simple framework to characterize land aridity based on surface energy partitioning regimes

Land aridity is often characterized by the aridity index (AI), which does not account for land surface water-energy interactions that are crucially important in determining regional climate. Such interactions can be captured by the evaporative fraction (EF, ratio of evapotranspiration to available energy) regimes. As EF is subject to energy and water limitations in humid and dry areas, respectively, EF regimes may be used to characterize land aridity to account for the influence of complex land characteristics and their impact on water availability. Here, we propose a simple framework to characterize land aridity by statistically ranking the coupling strength between EF and surface energy and water terms. The framework is demonstrated using gridded data and compared with AI over the U.S. and China. Results show that regionalization of aridity zones based on EF regimes and a two-tiered classification scheme may provide information such as surface energy and water variability complementary to the background aridity depicted by AI, with implications for extreme events.