Miracle-dz/UniFAR-FTUs huggingface dataset:
STABILITY OF HIGH-BETA TOKAMAK PLASMAS

By means of expressing the equilibrium configurations of high-beta tokamak plasmas analytically, the ideal MHD local stability criterion is derived with emphasis on the exploration of the possibility of existence of low-q, high-beta tokamaks. Results obtained show that a great variety of equilibria with these figures of merit may exist, some of them having great stability margin in the central region of the confined plasma against the local modes. Comparisons are made of results corresponding to configurations with different p′(ψ) and △(ρ) functions (△ being the displacement of the magnetic surface) and the tendency is found that the larger the displacement and the flatter the p′(ψ) profile is, the more stable the equilibrium will be.
Analysis of 25-hydroxyvitamin D2 and 25-hydroxyvitamin D3 in Serum Using Ultra-performance Liquid Chromatography with Tandem Mass Spectrometry

Background: Measurement of serum 25-hydroxyvitamin D metabolites (25OHD) may be useful in the laboratory diagnosis and treatment of vitamin D deficiency. A standardized liquid chromatography-tandem mass spectrometry (LC-TMS) assay has been used for accurate analysis of 25-hydroxyvitamin D levels. We evaluated the performance of a recently developed ultra-performance liquid chromatography combined with tandem mass spectrometry (UPLC-TMS) for the simultaneous quantification of 25OHD3 and 25OHD2 in human serum. Materials and Methods: We established the measurement method of 25-hydroxyvitamin D using UPLC-TMS and evaluated the precision and made a comparison between the UPLC-TMS and the chemiluminescence immunoassay (CLIA). Proportions of vitamin D deficiency in a local population and the spectrum of vitamin D2 measured were investigated. Results: UPLC-TMS revealed within-run precision and between-run precision of less than 4% and showed a bias of less than 5%. The CLIA measurements of 25OHD showed a correlation of CLIA = 0.86 × UPLC- TMS + 1.16 (r 2 = 0.98). The means±SD of serum 25OHD, 25OHD2, and 25OHD3 in 1,047 individuals were 12.8±9.3 ng/mL (0.5-62.7 ng/mL), 0.6±1.6 ng/mL (0-22.4 ng/mL), and 12.2±9.2 ng/mL (0.4-62.4 ng/mL), respectively. The proportions of vitamin D insufficiency and deficiency were 34.4% (360/1047) and 48.6% (509/1047), respectively. Discussions: The newly developed 25OHD assay using the MSMS Vitamin D kit based on the UPLC-TMS assay showed excellent performance and is suitable for routine clinical measurements of serum 25OHD2 and 25OHD3. We expect that this method will contribute to improved accuracy and reduced interlaboratory variation versus other methods for 25OHD measurement. (Yong-Wha Lee. Analysis of 25-hydroxyvitamin D2 and 25-hydroxyvitamin D3 in Serum Using Ultra- performance Liquid Chromatography with Tandem Mass Spectrometry. Life Sci J 2013; 10(3): 1648-1652). (ISSN: 1097-8135). http://www.lifesciencesite. com 247
Road Information Detection Method Based on Deep Learning

Autonomous driving technology has developed rapidly in recent years, and computer vision has shown significant role in automated vehicles. Researchers use the combination of computer vision and deep learning to improve the speed and accuracy of road element detection technology. This article focuses on the semantic segmentation and road detection elements, especially in lane line segmentation and signal light detection. It summarizes the visual inspection technology and a series of visual perception algorithms based on deep learning. Although semantic segmentation and target detection technologies in general scenarios are already very mature, they are not ideal when applied to autonomous driving environments, especially where segmentation and detection are performed simultaneously. Therefore, this paper builds a fusion network of lane line segmentation and signal light detection suitable for autonomous driving scenarios.
Damage Detection of Transmission Tower Based on Stochastic Subspace and Statistic Model

During the long service period of the transmission tower, the severe environment, material aging and fatigue effects result in the damage accumulation and resistance fading of the transmission tower, which even lead to the structural failure. In this paper, a stochastic subspace-based damage detection algorithm combined with statistical model is proposed for the damage identification of transmission tower structures through processing and analysing its vibration signals. Based on the structural modal parameters identified from the structural vibration response, the nominal modal parameters are defined. Considering that the Hankel matrixes constructed by the system observability matrix and the system output covariance matrix have the same kernel space, the damage index sensitive to the modal parameters is constructed. In the manuscript, firstly, the damage index establishment method and process of the algorithm are presented; and then the vibration data of transmission tower structure simulation under different damage conditions are obtained through numerical simulations; finally, above data are analysed to obtain the damage identification results of transmission tower. The results show that the method proposed in this work can effectively identify the local damage of transmission tower structure.
Peran Self Monitoring sebagai Mediator antara Job Characteristics dan Well-Being pada Guru Sekolah Inklusi

This study aims to determine the role of teacher self-monitoring as a mediator between job characteristics (emotional job demands and trust in colleagues) and teacher well-being teachers in inclusive schools. The sample of this study was 204 teachers in Indonesia from elementary to high school levels in inclusive schools using G*power. The sample selection technique in this study was accidental sampling teachers in Indonesia from elementary to high school levels in inclusive schools. The research method used is correlational quantitative research. This study uses four measuring instruments, namely the teacher well being scale, the self-monitoring scale, and, to measure job characteristics, the omnibus trust and the emotional job demand scales. Analysis of research data refers to Baron & Kenny using process modeling analysis version 3.0 by Andrew Hayes. As a result, self monitoring is able to become a mediator between emotional job demand and teacher well-being. Self monitoring has also proven to be a mediator between trust in colleagues and teacher well-being.Keywords: Job characterstics, self monitoring, well-being, teacher, inclusive schoolAbstrak: Penelitian ini bertujuan mengetahui peran teacher self monitoring sebagai mediator antara job characteristic (emotional job demands dan trust in colleagues) dan teacher well-being guru disekolah inklusi. Sampel dalam penelitian 204 guru dari jenjang Pendidikan Sekolah Dasar sampai dengan Sekolah Menengah Atas di sekolah inklusi menggunakan aplikasi G*power. Teknik pemilihan sampel dalam penelitian ini adalah accidental sampling yaitu seluruh guru inkusi yang ditemui dari jenjang Sekolah Dasar sampai Menengah Atas. Metode penelitian yang digunakan adalah penelitian kuantitatif korelasional. Penelitian ini menggunakan empat alat ukur, yaitu skala teacher well being, self monitoring dan, untuk mengukur job characteristics, skala omnibus trust dan emotional job demand. Analisis data penelitian mengacu pada Baron & Kenny menggunakan analisis process modeling versi 3.0 oleh Andrew Hayes. Hasilnya self monitoring mampu menjadi mediator antara emotional job demand dan teacher well-being. Self monitoring juga terbukti mampu menjadi mediator antara trust in colleagues dan teacher well-being.
Therapierefraktäres Sodbrennen und Reflux

Uebersc Etwa 10–40% der Patienten mit Sodbrennen leiden unter therapierefraktären Beschwerden. Therapierefraktärer Reflux ist definiert als fehlendes oder nicht ausreichendes Ansprechen auf die optimierte säuresupprimierende Therapie mittels eines Protonenpumpenhemmers zweimal täglich oder eines anderen Therapieverfahrens. Dieser Beitrag schildert Ursachen, Diagnostik und Management des therapierefraktären Sodbrennens.
Mechanical and Physical Characteristics of Bubble Alumina Reinforced Aluminum Syntactic Foams Made Through Recyclable Pressure Infiltration Technique

Metal matrix syntactic foams (MMSFs) are advance hybrid materials which reflect synergetic combination of particle reinforced composites and close cell metal foams. Recently, MMSFs have become considerably popular for several industrial areas because of their low density, high compression strength, good ductility and perfect energy absorption ability. In this paper, Al 7075/bubble alumina syntactic foams were fabricated by recyclable pressure infiltration casting method. Macroscopic and microscopic investigations showed that almost flawless infiltration was obtained between 2 – 4 mm hollow bubble alumina spheres and total porosity values of fabricated foams varied between % 43.2 and % 45.6. As for mechanical analyses, all foam samples were subjected to quasi-static compression test (1 mm/min deformation rate) and their crucial properties such as compression strength, plateau strength, densification strain and energy absorption capacity were determined. Besides, aging heat treatment (T6) was applied to certain samples in order to explore probable effects of heat treatment on the mechanical responses. The outcomes indicated that there was a positive relationship between the aging treatment and compressive features. Under the compressive loading, even though T6 treated foams showed a tendency to brittle fracture, their as-cast variants exhibited ductile behavior. Received: 06/01/2021 Accepted: 06/03/2021
Effect of Edmodo to improve number sense

The aim of this research for knowing the improvement of student’s number sense by using Edmodo. This type of research used the experimental method with the pretest-posttest control group design the group. This study uses the quasi-experiment method with a tutorial model conducted on class VII students one of junior high school in Bandung City. The instrument used in this research in a test. The test is used to know the improvement student’s number sense. Data analysis technique of quantitative used N-gain and independent t-test. Based on the results of the research show that there is no difference of number sense improvement from students who get Edmodo and conventional learning and the improvement both are included in the low number sense improvement. According to the results of the research can be concluded that the use of Edmodo not appropriate to improve number sense.
New Media User Behaviour Research Based on Big Data Analysis

With the rapid development of diversified business models and market segments in the era of big data, many industries are facing the dual challenges of high customer acquisition costs and churn rates. How to accurately obtain user behavior data has become a top priority. This article uses big data technology to scientifically analyze the ratings and behavior data of new media users. Through new media user behavior analysis, we can accurately discover user behavior characteristics, optimize users’ personalized experience, and bring better new media business operations—basis for decision-making.
The role of users’ engagement in shaping financial reporting: should activists target accounting more?

We define accounting engagement as stakeholders’ actions taken with the intention of influencing corporate reporting. Using this definition, we review the literature on such activism and discuss avenues for research. The evidence reviewed suggests accounting engagement is rare. We reflect on the reasons of this, given evidence on increasing overt engagement on other corporate issues, such as managerial compensation and governance, social, and environmental responsibility. Both information production and information acquisition costs have decreased over time, raising further questions about why engagement has not increased. We consider potential reasons linked to concerns over whether financial reporting meets users’ information needs, particularly, given the emergence of new users and the role of new technologies in the diffusion and processing of information. These concerns have accompanied claims of increasing complexity of financial accounting and the threat of information overload.
Developing an unmanned vehicle local trajectory using a reinforcement learning algorithm

This article describes the algorithm development for constructing a local trajectory for an unmanned vehicle or for implementation in an ADAS system using the reinforcement learning method. A special part is dedicated to reinforcement learning. One of the methods that is best suitable for the task conditions will also be implemented. This method will allow bypassing obstacles and reaching the specified short target points.
Potential of bran from various wheat variety for cookies production

Abstract The effect of replacing wheat flour with different kinds of wheat bran and spelt bran at level 5, 10 and 15 % on dough rheology, qualitative parameters of cookies as well as on sensory properties was studied. Addition of bran increased water absorption and mixing tolerance index, prolonged dough development time and decreased dough stability. It was also observed that incorporation of wheat bran modified qualitative parameters of cookies (volume, specific volume, spread ratio and porosity decreased). From the sensory evaluation resulted that higher amounts of wheat bran negatively affected taste, hardness and overall acceptability of cookies. Addition of bran up to 5 % resulted in cookies with high overall acceptability.
Nutraceutical Alternatives to Pharmaceutical Analgesics in Osteoarthritis

Chronic pain is a considerable health concern worldwide, effecting almost 30% of all European adults. Osteoarthritis (OA), a progressive pro-inflammatory condition, is one of the leading causes of chronic pain (effecting 13% of all ﻿those over 50 years, globally) and is the most common cause of joint pain. The prevalence of non-steroidal anti-inflammatory drug (NSAIDs) and analgesic use has been well studied and is abundant throughout the western world, with women being the greatest users and ibuprofen generally being the most ﻿reported NSAID. In the US, 65% of all OA patients are prescribed NSAIDs for pain management and form part of the current recommended strategy for OA clinical management. While some NSAIDs and analgesics are effective at improving pain and physical function, they come with significant and harmful side effects such as gastrointestinal complications, renal disturbances and severe cardiovascular events. Given these side-effects, any reduction in NSAID and analgesia use (and the resulting potentially harmful side effects) is of particular importance to OA public health. As such, a number of non-pharmaceutical alternatives (bioactive nutraceuticals) have been developed that may reduce NSAID and analgesia use while maintaining pain reduction and improvements in physical function. This chapter will discuss select nutraceuticals that are not currently in mainstream use but may have the potential to aid in the treatment of OA.
Real-time facial emotion recognition using lightweight convolution neural network

In recent years, facial expression recognition has played an important role in the field of human-computer interaction, and the application of deep learning technology has enabled it to develop more rapidly. In this paper, we create a lightweight network model for real-time emotion classification to recognize student facial expressions. The system includes: using Haar cascade for face detection, combined with the idea of Xception to propose a lightweight CNN network model, using pre-activation in the residual block to optimize the model and reduce the impact of overfitting. The experimental results on the FER2013 database show that our model has a better expression classification effect than other state-of-the-art methods. Besides, our model uses fewer parameters, which reduces the complexity of network training. When real-time emotional recognition of students, the system can help teachers adjust their teaching methods according to the emotional state of students.
M-Learning in Promoting Green Building Awareness in Palestine

Most Palestinians have yet to have the urge to participate in green building practices. To enhance green building education in Palestine, we built a mobile application named “Let’s Go Green” to deliver awareness and incorporate green building technologies. In order to validate the mobile learning (m-learning) effect, we have conducted separate measurements by using ARCS motivation model and paper-based quiz among 80 engineering and architecture students in Hebron, Palestine. The students were split into two groups; group A (experimental; applied m-learning method) and group B (control; adopted conventional lecture note method). This study has three important findings (1) m-learning users found to have stronger learning motivation than those who used the conventional lecture note; (2) m-learning users generally exhibited better learning effectiveness than non-users; (3) the m-learning was found to be attractive to the students, implying that it can be an important content for educational and leisure for green building education. The findings demonstrated that the Let’s Go Green Application is an effective instructional material to improve students’ knowledge on green building. This application can be downloaded for both smartphones; Android, and iPhone. These functions have not been implemented yet, therefore this is the first attempt of such an approach.
EFFECT OF THE GABA DERIVATIVE SUCCICARD ON THE LIPID AND CARBOHYDRATE METABOLISM IN THE OFFSPRING OF RATS WITH EXPERIMENTAL PREECLAMPSIA IN EARLY AND LATE ONTOGENY

Maternal preeclampsia can bring about metabolic disorders in the offspring at different stages of ontogeny. Up to date, no ways of preventive pharmacological correction of lipid and carbohydrate metabolism disorders developing in different periods of ontogeny in the children born to mothers with this pregnancy complication, have been developed.The aim of the experiment was to study the effect of the gamma-aminobutyric acid derivative succicard (22 mg/kg) and its reference drug pantogam (50 mg) administered per os in the course of treatment in puberty (from 40 to 70 days after birth), on the parameters of lipid and carbohydrate metabolism in the offspring of the rats with experimental preeclampsia, in different periods of ontogeny.Materials and methods. To assess the activity of lipid and carbohydrate metabolism in the offspring, an oral glucose tolerance test was performed at 40 days, 3, 6, 12 and 18 months of age. The level of glycosylated hemoglobin was measured at the age of 6, 12, and 18 months, and the concentrations of total cholesterol, high-density lipoprotein cholesterol and triglycerides were tested at 40 days, 3, 6, 12, and 18 months of age.Results. The offspring of the rats with experimental preeclampsia, were found out to have lipid and carbohydrate metabolism disturbances during early (40 days and 3 months of age) and late (6, 12, and 18 months of age) ontogeny. In comparison with the offspring of healthy females, these disturbances were manifested by significantly higher levels of glucose revealed during the oral glucose tolerance test, by high glycosylated hemoglobin in males, and with elevated concentration of total cholesterol and triglycerides and a low level of high-density lipoprotein cholesterol in the negative control rats. Both the gamma-aminobutyric acid derivative succicard and its reference drug pantogam, reduced the negative effect of experimental preeclampsia on lipid and carbohydrate metabolism in the offspring in late ontogeny (6, 12 and 18 months of age). The effectiveness of succicard was either higher or comparable with pantogam.Conclusion. Thus, the negative impact manifestations of experimental preeclampsia on lipid and carbohydrate metabolism, are revealed in the offspring in early (40 days and 3 months) and late (6, 12 and 18 months of age) ontogeny. The gamma-aminobutyric acid derivative succicard reduces the negative effect of experimental preeclampsia. Based on this finding, the drug implies the possibility of the development of a safe and highly effective medicine for preventive correction of lipid and carbohydrate metabolism disorders in the children born to mothers with preeclampsia.
Adaptive three-photon microscopy for fine structure imaging deep in the mouse brain

In order to study dynamic biological processes in-vivo in mammalian organisms techniques are required which enable non-invasive imaging at large tissue depth with sub-cellular resolution. However, optical aberrations and scattering in biological tissue lead to signal loss and a degradation of both spatial resolution and penetration depth. Here, we combine two powerful optical techniques, multi-photon microscopy and adaptive optics, to push the depth limit further while retaining diffraction limited resolution. We apply these techniques to open questions in the field of neuron and glia biology. By utilizing three-photon excitation at the 1300 nm spectral excitation window we achieve highresolution imaging of GFP-labeled neurons up to a depth of 1.2 mm in the in-vivo mouse brain. Furthermore, we have combined our approach with indirect modal-based wavefront correction and synchronization of our microscope to the animal’s heart pulsation. This allowed us to improve the resolution up to ~6-fold and achieve synaptic resolution throughout an entire cortical column. With adaptive optics correction, small structures such a dendritic branches thus become clearly visible at over 1mm depth in the hippocampus. Furthermore, our adaptive three-photon microscope system enabled, for the first time, to investigate calcium dynamics of fibrous astrocytes which reside in the corpus callosum and whose dynamics have previously not been possible to image.
Time switching based, outage-constrained, energy harvesting and energy-efficient cooperative radio communication policy

Funding information OPERA research grant (FR/SCM/160714/EEEI/) from Birla Institute of Technology & Science (BITS) Pilani, Pilani campus, India Abstract In this work, the authors consider a two-hop cooperative radio communication system that consists of energy harvesting relays. The EH relays harvest energy from its received radio frequency signal. The EH relay nodes adopt the time-switching protocol for simultaneous EH and information processing. For the system model, the authors propose an energyefficient, outage-constrained relaying policy. In it, the EH relay that harvests maximum energy forwards the information to the destination. However, the selected EH relay transmissions are outage-constrained. For the proposed outage-constrained collaborative EH system model, the authors present insightful analysis. Specifically, the authors derive a single integral expression for the expectation of maximum energy harvested over frequencyflat Rayleigh fading and shadowing channel. The authors also present an insightful link outage probability analysis and asymptotic analysis in a useful scaling regime. Besides outage analysis, the authors investigate the proposed policy’s performance in terms of average spectral efficiency and average energy efficiency. To validate the analytical results, the authors conduct numerical simulations. Using the numerical plots, the authors quantify the proposed policy’s link outage and energy efficiency performance gains compared with benchmark policies. The proposed outage-constrained, green cooperative communication policy and its analysis are useful for green collaborative EH systems.