Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Adhesive Resin as a Modeling Liquid on Elution of Resin Composite Restorations

Background Adhesive resin is increasingly used as a modeling liquid for composite. Based on previous studies, elution of some components from the composite mass negatively affects the oral tissues. Since few studies have focused on the effect of adhesive resin on composite mass, this study aimed to investigate the effect of dental adhesion factors as modeling liquid on the elution of substances from composite restorations. Materials and Methods Sixty-four composite specimens (6 × 2 mm diameter × height) were prepared in four groups (n = 16) by using a Teflon ring. Composite mass was incrementally applied in four layers (0.5 mm). The control group contained no material between the layers, but other groups had one of the single bond, SE bond, and wetting resin adhesives between the layers. Specimens were immersed in distilled water and methanol. The amount of released triethylene glycol dimethacrylate (TEGDMA), urethane dimethacrylate (UDMA), and camphorquinone (CQ) was monitored by gas chromatography after 24 hours and 7 days. Data were analyzed with SPSS software through Kruskal–Wallis and Mann–Whitney U tests (α = 0.05). Results The highest rate of released TEGDMA comonomer was seen in the wetting resin group in the water medium. The highest rate of released UDMA monomer was seen in SE bond and wetting resin groups in the methanol medium after 24 hours. The highest amount of released CQ in the methanol medium was observed in the SE bond group after 7 days. Conclusion Single bond adhesive can be used as modeling liquid since it has no significant effect on the elution of components from composite mass. Whereas, wetting resin and SE bond adhesives are not suitable to be used as modeling liquid due to the high amounts of released TEGDMA and UDMA.
Personality, Interpersonal Problems, and Anxiety Among Older Adults

Introduction: This study examined relationships between personality disorder (PD) features, Big Five personality traits, and interpersonal problems with anxiety. Method: Older adults (N = 130) completed the Geriatric Anxiety Scale, Coolidge Axis Two Inventory, Big Five Inventory-2, and Circumplex Scales of Interpersonal Problems. Pearson correlation analyses were used to assess simple relationships between anxiety with PD features (CATI scales), Big Five personality domains (BFI-2 scales), and interpersonal problems (CSIP scales). Multiple linear regression analyses were performed to determine the extent to which the PD scales of the CATI, the personality scales of the BFI-2, and the scales of the CSIP explained variance in anxiety. Results: Anxiety was positively correlated with 13 of 14 PD scales, ranging from . 23 (Narcissistic) to . 61 (Depressive). Regarding Big Five personality traits, anxiety was negatively associated with Agreeableness (−.23), Conscientiousness (−.30), and Extraversion (−.31) but was positively associated with Negative Emotionality (.56). Regarding interpersonal problems, anxiety was positively related to all eight CSIP scales, ranging from Self-sacrificing (.30) to Distant/Cold (.62). Regression analyses indicated that PD features accounted for the most variance in anxiety symptoms (53%), followed by interpersonal problems (46%), and Big Five personality traits (33%). Discussion: Anxiety appears to be meaningfully associated with PD features, several aspects of Big Five personality traits, and interpersonal problems, suggesting that these variables may play important roles in the development and maintenance of anxiety, or vice versa. Our findings especially speak to the growing awareness of the deleterious impact of PD features on clinical syndromes in later life, as evidenced by strong comorbidities with anxiety.
Differentiation Model for Insomnia Disorder and the Respiratory Arousal Threshold Phenotype in Obstructive Sleep Apnea in the Taiwanese Population Based on Oximetry and Anthropometric Features

Insomnia disorder (ID) and obstructive sleep apnea (OSA) with respiratory arousal threshold (ArTH) phenotypes often coexist in patients, presenting similar symptoms. However, the typical diagnosis examinations (in-laboratory polysomnography (lab-PSG) and other alternatives methods may therefore have limited differentiation capacities. Hence, this study established novel models to assist in the classification of ID and low- and high-ArTH OSA. Participants reporting insomnia as their chief complaint were enrolled. Their sleep parameters and body profile were accessed from the lab-PSG database. Based on the definition of low-ArTH OSA and ID, patients were divided into three groups, namely, the ID, low- and high-ArTH OSA groups. Various machine learning approaches, including logistic regression, k-nearest neighbors, naive Bayes, random forest (RF), and support vector machine, were trained using two types of features (Oximetry model, trained with oximetry parameters only; Combined model, trained with oximetry and anthropometric parameters). In the training stage, RF presented the highest cross-validation accuracy in both models compared with the other approaches. In the testing stage, the RF accuracy was 77.53% and 80.06% for the oximetry and combined models, respectively. The established models can be used to differentiate ID, low- and high-ArTH OSA in the population of Taiwan and those with similar craniofacial features.
Cultural factors affecting the adoption of e-learning in Turkey

This paper aims to examine ways in which cultural factors shape the adoption and use of information technology for online teaching. This research focuses on influential early adopters in the tertiary education sector in Turkey who have become change-agents by inspiring small networks of their peers. The study examines the operation of trust and inspiration in networking and teamwork in the Asian academic environment. Findings from this research can assist individuals and institutions to better understand ways in which to optimize the online teaching and learning experience for staff.
High-frequency power transformer model for circuit simulation

A model for the circuit simulation of transformers used in high-frequency power processing is proposed. Many important transformer effects are combined in a single formulation. An Atherton-Jiles model with improved minor-loop handling ability is employed to simulate the hysteresis effect in the magnetic core. Eddy currents and skin and proximity effects are simulated by dynamically approximating the field and flux distributions in the entire structure. Leakage fluxes, capacitive couplings and the influence of temperature on electric and magnetic materials are also included. The parameters needed for simulation are magnetic material characteristics, available in data sheets, core geometry and winding geometry. The model was implemented (built) in the source code of SPICE3.
Improvement of estimating method for construction management service fee by case study

The objective of this paper is to suggest the improvement of estimating system for construction management (CM) service fee through the analysis of the previous literatures and criteria and case study. In order to do this, this paper considered the relevance of existing criteria to estimate the CM service fee, the condition of input ratio of engineering resources in the real cases, and current utilization strategy of nonresident technical engineers. Based on the analysis, the following problems were identified; a) the different estimating system for CM fee and construction supervision fee, b) impractical estimating system for the CM fee, and c) inappropriate allocation of human resources for CM. Consequently, this paper suggested the following 4 items for the improvement of the existing system; (1) modification of the current structure of CM fee calculation, (2) rationalization of current level of the CM fee which is required to be raised approximately 5.4 percent compared to design or supervision fee, (3) securement of elasticity of the input ratio of engineering resources from the inception phase, and (4) development of the utilization strategy of nonresident engineers based on the technical requirement of the jobsite. Thus, it is anticipated that this research would affect the compensation package of CM in order to make the estimation process of CM service fee more efficient and to revitalize CM as business.
Mesoscopic comparison of interface tool/workpiece for simulation by FEM of EN AW 1350 bulk forming alloy

This paper presents an improved numerical simulation of bulk metal forming processes. It takes into the account the advanced formalism of large displacements and large deformations. Also, the interface workpiece formalism is considered. Metallographic studies are conducted to determine the evolution of the micro hardness as a function of annealing time and that to characterize accurately the plastic range of aluminum alloy for a range of plasticity 160%. The obtained results of metallographic studies are used to simulate a upsetting under the friction law of the plastic wave. A numerical simulation by FEM of bulk forming alloy is carried out by replacing the real profile of the surface roughness by two triangular profiles, the first has the same height as the real profile and the second has the same area then by a trapezoidal profile of the same height. The obtained results are compared to Challen and Oxley results in order to validate the triangular profile used in the friction model of plastic wave.
Molecular Evolution and Amino Acid Characteristics of Main Antigen Genes of Clinical Duck-Derived H5N6 Subtype Avian Influenza Virus in East China from 2015 to 2019

SUMMARY. H5N6 subtype avian influenza virus (AIV) continues to erupt in poultry, and there have also been many incidents of human infection. Its outbreak is devastating to the poultry breeding industry, and it also threatens human public health safety. Forty-five strains of H5N6 subtype AIV isolated from sick ducks in East China were used in this study. HA gene analysis found that the amino acid sequences at the cleavage site of the HA gene of the 45 isolates were all continuous basic amino acids, which was in line with the characteristics of highly pathogenic avian influenza. Amino acid analysis showed that specific amino acid substitutions and deletions occurred in both HA and NA proteins, indicating that 45 isolates may have the ability to infect mammals and humans. The results of the Muscovy duck (Carina moschata) infection experiment showed that the clinical symptoms and visceral pathologic changes of Muscovy ducks infected with the virus strains isolated in different years were similar. Mutations at multiple amino acid sites were found in the HA and NA genes of duck-derived H5N6 subtype AIV that were clinically isolated in Eastern China in our study. And the influence of some mutations on the pathogenicity and transmission ability of the virus is still unclear. Therefore, it is necessary to continuously monitor and study the H5N6 subtype AIV of ducks.
Numerical model describing the effect(s) of a barrier and the space charge fields on the electrical strength of a point-plane air gap using the finite elements

In this paper, we have computed fields of the positive ions and electrons created at the head of avalanche in a positive point-barrier-plane air gap. The polarisation field effect of the dielectric is taken into account. The general problem will be formulated with finite elements and it is focussed on the polarisation field formulation. It was found that the effect of the two space charge fields is to reduce the breakdown voltage.
Detection of concealed explosives at stand-off distances using wide band swept millimetre waves

Millimetre waves in the range 20 to 110 GHz have been used to detect the presence and thickness of dielectric materials, such as explosives, by measuring the frequency response of the return signal. Interference between the reflected signals from the front and back surfaces of the dielectric provides a characteristic frequency variation in the return signal, which may be processed to yield its optical depth [Bowring et al, Meas. Sci. Technol. 19, 024004 (2008)]. The depth resolution depends on the sweep bandwidth, which is typically 10 to 30 GHz. By using super-heterodyne detection the range of the object can also be determined, which enables a signal from a target, such as a suicide bomber to be extracted from background clutter. Using millimetre wave optics only a small area of the target is illuminated at a time, thus reducing interference from different parts of a human target. Results are presented for simulated explosive materials with water or human backing at stand-off distances. A method of data analysis that involves pattern recognition enables effective differentiation of target types.
Optical Fiber-Based Monitoring of X-ray Pulse Series from a Linear Accelerator

We investigated in this work the radioluminescence properties of a Ce-doped multimode silica-based optical fiber (core diameter of 50 µm) manufactured by the sol–gel technique when exposed to the high-energy X-rays (~600 keV) of the ORIATRON facility of CEA. We demonstrated its potential to monitor in real-time the beam characteristics of this facility that can either operate in a pulsed regime (pulse duration of 4.8 µs, maximum repetition rate of 250 Hz) or in a quasi-continuous mode. The radiation-induced emission (radioluminescence and a minor Cerenkov contribution) linearly grew with the dose rate in the 15–130 mGy(SiO2)/s range, and the afterglow measured after each pulse was sufficiently limited to allow a clear measurement of pulse trains. A sensor with ~11 cm of sensitive Ce-doped fiber spliced to rad-hard fluorine-doped optical fiber, for the emitted light transport to the photomultiplier tube, exhibited interesting beam monitoring performance, even if the Cerenkov emission in the transport fiber was also considered (~5% of the signal). The beam monitoring potential of this class of optical fiber was demonstrated for such facilities and the possibilities of extending the dose rate range are discussed based on possible architecture choices such as fiber type, length or size.
Smart Transportation: Modeling Barriers of Electric Vehicles Charging Infrastructure

It is to identify the potential barriers for Electric Vehicles Charging Infrastructure (EVsCI) for Smart transportation management in India, to model the barriers, to obtain the hidden constructs of identified barriers, to validate a four-level transition management framework, and to understand the inter-relationships among these barriers. After identifying 20 barriers, Exploratory Factor Analysis (EFA) has been employed to get hidden constructs and categorize them in four-level transition management framework. Then, a seven-level hierarchical Total Interpretive Structural Modeling (TISM) based model has been proposed for finding inter-relationships among the barriers and to understand the driving power and dependency among barriers. The hierarchical framework has been developed using TISM which reveals the inter-relationships among barriers. This research work classifies barriers into four quadrants using Matriced ’ Impacts Croises Multiplication Applique ’ and Classment (MICMAC). This research highlights the necessity of using EVs in public transportation and the need of minimizing drawbacks in the way of adopting Electric Vehicles (EVs). This study will help policy makers to pay proper attention to frame policies to encourage manufacturing and adoption of EVs and to overcome drawbacks in the path of adopting EVs suitable for the developing countries.
Fuzzy Controller Design For Nonlinear SystemsWith Case Study Of TORA System

In this article, we study the problem of Fuzzy Controller Design For Nonlinear Systems With Case Study Of TORA System. Fuzzy control for nonlinear systems is proposed on the framework from model of Takagi-Sugeno fuzzy model and PDC(paralel distributed compensation) controller. A lyapanouv-based stabilizing fuzzy control design for nonlinear systems using Takagi-Sugeno fuzzy models is applied. The stability analysis and control design problems are reduced to linear of matrix inequality (LMI) problems. The fuzzy controller design procedure is to solve a set of LMI conditions. We apply PDC controller, robust controller and optimal controller are applied to a nonlinear control benchmark problem: TORA system. The designed fuzzy controllers are to yield an asymtotic stable closed-loop system. The fuzzy controller Simulation results are given to ilustrate the utility of the present fuzzy control
Kel1 is a phosphorylation-regulated noise suppressor of the pheromone signaling pathway

Mechanisms have evolved that allow cells to detect signals and generate an appropriate response. The accuracy of these responses relies on the ability of cells to discriminate between signal and noise. How cells filter noise in signaling pathways is not well understood. We have analyzed noise suppression in the yeast pheromone signaling pathway. By combining synthetic genetic array screening, mass spectrometry and single-cell time-resolved microscopy, we discovered that the poorly characterized protein Kel1 serves as a major noise suppressor of the pathway. At the molecular level, Kel1 suppresses spontaneous activation of the pheromone response by inhibiting membrane recruitment of Ste5 and Far1. Kel1 is regulated by phosphorylation, and only the hypophosphorylated form of Kel1 suppresses signaling, reduces noise and prevents pheromone-associated cell death. Our data indicate that in response to pheromone the MAPKs Fus3 and Kss1 phosphorylate Kel1 to relieve inhibition of the pheromone pathway. Taken together, Kel1 serves as a phospho-regulated suppressor of the pheromone pathway to reduce noise, inhibit spontaneous activation of the pathway, regulate mating efficiency and to prevent pheromone-associated cell death.
An image-based crash risk prediction model using visual attention mapping and a deep convolutional neural network

Abstract Crash risk prediction plays a pivotal role in traffic management and infrastructure optimization. Previous research has studied the relationship between crashes and multiple factors using statistical methods. As both drivers’ attention and environmental complexity substantially affect traffic safety, this article presents a novel method to predict crash risk proactively by combining these two interactive factors. More than 200 high-risk zones and 300 noncrash zones were screened out through social media data. Corresponding environmental information was collected using the street view map. Spectral saliency mapping was applied to depict the driver’s attention distribution toward images. A DeepLabV3 pretrained network was implemented to label the semantic features in the environment. A featured vector was then constructed by fuzing the visual attention model and image semantics. The gradient boosting decision tree algorithm was applied to analyze the relationship between the multitype crash data and featured vectors. The results showed that the accuracy of the proposed method for detecting different types of crashes was over 0.81. Dynamic objects are the most substantial factors that affect crash possibility and categories. Traffic signals are vulnerable to drivers’ attention, which may be easily overlooked. The proposed method provides new insights into understanding traffic crash risk, which can help us predict different types of crashes more effectively.
Correction of Geometric Influence in Permittivity Determination

Determination of relative permittivity of dielectric materials is generally done with a rather low accuracy, in the order of several percent. This is in a sharp contrast to the accuracy of measurements of the dissipation factor, both usually being determined in the same measurement. A common understanding for the inferior accuracy in permittivity measurements is the effects of electrode edges. However, further studies indicate that geometric effects, arising from electrode shielding box, guard ring, electrode supporting materials, etc., also influence the accuracy significantly if the responding voltage present at the measuring electrode is non-negligible. With help of the Finite Element Method (FEM), geometric correction factors are estimated from an electrode model to increase the accuracy. This study is specially focused on the application of contact-free electrode arrangement using the air reference method. In this paper, a few examples of how geometric influences affect results are presented as well as a comparison of experimental results. From these insights, we discuss how to minimize and compensate the geometric effects.
Scenario-Based Test Automation for Highly Automated Vehicles: A Review and Paving the Way for Systematic Safety Assurance

Highly Automated Vehicles (HAVs) must undergo strict safety testing before being released to the public. Mileage-based on-road testing suffers from unaffordable time costs and high safety risks. Simulated scenario-based testing has been found to be a trustworthy alternative for testing HAVs’ built-in algorithms and functionalities. Test automation is typically used to generate target scenarios. This approach facilitates customized testing and avoids wasting time on simple and redundant scenarios. This study aims to review test automation methods and discuss how to accentuate their strengths rather than be trapped in their weaknesses under certain applicable conditions. According to their main purposes, we classify test automation methods into coverage-oriented, unsafe-scenario-oriented, and naturalistic-assessment-oriented categories. To further demonstrate the differences of these methods, we then design numerical experiment to compare the capabilities of seven test automation methods. Finally, we compile our observations to form a comprehensive guide for selecting test automation methods with different test requirements in mind.
Nanoengineered biomimetic hydrogels: A major advancement to fabricate 3D‐printed constructs for regenerative medicine

Nanostructured compounds already validated as performant reinforcements for biomedical applications together with different fabrication strategies have been often used to channel the biophysical and biochemical features of hydrogel networks. Ergo, a wide array of nanostructured compounds has been employed as additive materials integrated with hydrophilic networks based on naturally‐derived polymers to produce promising scaffolding materials for specific fields of regenerative medicine. To date, nanoengineered hydrogels are extensively explored in (bio)printing formulations, representing the most advanced designs of hydrogel (bio)inks able to fabricate structures with improved mechanical properties and high print fidelity along with a cell‐interactive environment. The development of printing inks comprising organic–inorganic hybrid nanocomposites is in full ascent as the impact of a small amount of nanoscale additive does not translate only in improved physicochemical and biomechanical properties of bioink. The biopolymeric nanocomposites may even exhibit additional particular properties engendered by nano‐scale reinforcement such as electrical conductivity, magnetic responsiveness, antibacterial or antioxidation properties. The present review focus on hydrogels nanoengineered for 3D printing of biomimetic constructs, with particular emphasis on the impact of the spatial distribution of reinforcing agents (0D, 1D, 2D). Here, a systematic analysis of the naturally‐derived nanostructured inks is presented highlighting the relationship between relevant length scales and size effects that influence the final properties of the hydrogels designed for regenerative medicine.