Miracle-dz/UniFAR-FTUs huggingface dataset:
Tanshinone IIA Ameliorates Streptozotocin-Induced Diabetic Nephropathy, Partly by Attenuating PERK Pathway-Induced Fibrosis

Purpose Tanshinone IIA (Tan IIA), a compound extracted from Salvia miltiorrhiza, can improve type II diabetes, while the molecular mechanisms underlying Tan IIA-mediated protective effects in diabetic nephropathy are unclear. This study explored the protective actions of Tan IIA on renal tissues in streptozotocin (STZ)-induced diabetic nephropathy. Materials and Methods Tan IIA (2, 4, 8 mg/kg/day) was daily administered to STZ-treated rats by intraperitoneal injection for 42 days. The morphologic pathology was evaluated by hematoxylin-eosin and Masson’s trichrome staining, and transmission electron microscopy. The protein expression levels in renal tissues were evaluated by Western blotting and immunohistochemistry; the mRNA expression level was determined by quantitative real-time PCR. Results Tan IIA at 2 and 4 mg/kg attenuated the increase in the levels of uric acid and blood urea nitrogen and restored the reduction in the superoxide dismutase activity in the serum of the diabetic rats. Tan IIA at 2 and 4 mg/kg, but not 8 mg/kg, ameliorated the thickening of renal tubule in the diabetic rats; Tan IIA at 2 and 4 and 8 mg/kg attenuated the thickening of glomerular basement membrane and the collagen deposition in the renal tissues of the diabetic rats. Tan IIA treatment at 2, 4, 8 mg/kg decreased the expression levels of transforming growth factor-beta1, TSP-1, Grp78 and CHOP in the diabetic rats. Tan IIA at 2 and 4 and 8 mg/kg attenuated the increase in the protein levels of p-PERK, p-elf2α and ATF-4 from the renal tissues of diabetic rats, while the protein level of AFT-6 and the mRNA expression levels of XBP-1t, XBP-1s and p58IPK in the renal tissues were not affected by STZ or Tan IIA treatment. Conclusion Tan IIA-mediated protective effects on the STZ-induced diabetic nephropathy may be associated with the reduced endoplasmic reticulum stress via attenuating PERK signaling activities.
Efficient and Secure Strategy for Energy Systems of Interconnected Farmers′ Associations to Meet Variable Energy Demand

Since ancient times, agriculture has been one of the most important resources of national development. At a national level, clean energy is a strategic objective of Romania, in accordance with the EC directive 2016/30.11. 2016 (“Clean Energy for All”). At a European level, the European Commission published in January 2019 the “Towards a Sustainable Europe by 2030” strategy, highlighting the strategic importance of the Internet of Things (IoT) and blockchain technologies. In this context, the synergy between the energy management of a hybrid energy system and blockchain technology, applied to farmers’ associations, represents a priority research direction in the field of information and communication technology, blockchain, and security. This paper presents the integration of the management of the energy produced by photovoltaic panels owned by farmers’ association, to support the variable energy demand (necessary for water pumps, charging stations of the electric agricultural machines, the animal farms, and the auxiliary equipment) based on the IoT, DLT, blockchain technologies and smart contracts applied to farmers associations registered as users of the SmartFarm platform.
Callus Induction and Micropropagation of Lilium candidum L. Using Stem Bulbils and Confirmation of Genetic Stability via SSR-PCR

Natural populations of Lilium candidum L. are remarkably affected by biotic and abiotic factors therefore there is a requirement to develop effective micropropagation protocol to provide mass production, multiplication and conservation of these plants. For this reason, this study was aimed to develop an efficient micropropagation method for multiple shoot production via somatic embryogenesis induced from L. candidum stem bulbils and also to determine the genetic stability of in vitro grown plants using SSR markers. The obtained results of this study are the first comprehensive reports including an investigation of genetic fidelity on somatic embryogenesis of L. candidum . After surface sterilization of bulbils, the calculated regeneration percentage of them was 89.5% and the callus induction was achieved using leaf segments of in vitro grown bulbils. The well formed somatic embryos were obtained from smooth whitish-yellow colored calli and these somatic embryos produced well formed healthy L. candidum seedlings with adventitious roots. All rooted seedlings were easily adapted to greenhouse conditions and the genetic stability of in vitro grown seedlings were determined by using SSR-PCR technique and it was calculated as 100%.
Structures of the four avenacins, oat root resistance factors to ‘take-all’ disease

The true aglycones of the avenacins are acid sensitive triterpene 12,13-epoxides, not 12-ketones, and one such avenestergenin epoxide is isolated direct from oat roots; this, together with study of the attached trisaccharide, permits complete structures to be proposed for the four avenacins (3a—d); avenestergenins readily undergo an acid-catalysed anhydrodimerisation via acetal formation.
Activity coefficients in nearly athermal model polymer/solvent systems

Phase equilibria play a crucial role in the design of polymer manufacturing processes. Knowledge of the phase behavior of polymer/solvent solutions is especially important for polymer production and purification operations. Constant pressure Monte Carlo simulations were performed to study the activity coefficients of bead-spring polymers dissolved in a monomeric solvent. Activity coefficients were obtained for binary mixtures of monomer and 20-mer for compositions ranging from pure 20-mer to pure solvent, using the chain increment method to obtain the chemical potentials of long-chain solute and monomeric solvent. Infinite dilution activity coefficients were also calculated for polymeric solutes in monomeric solvents and monomeric solutes in polymeric solvents solutions with chain length up to 60. Such detailed information on activity coefficients in polymer/solvent systems with large size differences had not been available previously from simulation or experiment. Several engineering models were tested for their ability to predict the activity coefficients in these nearly a thermal systems. Results indicate that simple free-volume models can provide qualitatively accurate predictions for both short-chain solvent and long-chain solutes, provided that the functional form of the free-volume dependence is chosen appropriately.
Congener Specific Analysis of 140 Chlorobiphenyls in Technical Mixtures on Five Narrow-Bore GC Columns

Abstract The separation of 140 chlorobiphenyl (CB) congeners from technical polychlorinated biphenyl (PCB) mixtures was investigated on five narrow-bore (0.22–0.25 mm I.D.) gas chromatography (GC) columns with stationary phases representing a broad range of polarities: dimethylsiloxane (0.15 μm SIL-5, 50 m), 5% diphenyl dimethylsiloxane (0.26 μm SIL-8, 50 m), 14% cyanopropylphenyl 1% vinyl dimethylsiloxane (0.26 μm SIL-19, 50 m), bis-cyanopropyl phenylsiloxane (0.20 μm SIL-88, 50 m) and 1,2-dicarba-closo-dodecarborane dimethylsiloxane (0.1 μm HT-5, 25 m). Technical PCB mixtures (Aroclors) and authentic standards (totally 66 CBs) were injected on the narrow-bore columns and analyzed by GC-ECD and GC-MS. Peak assignments were based on experimental data together with published retention data and data on the quantitative composition of Aroclors. Structural principles for retention of CBs on polar stationary GC phases were developed. Surprisingly, the general performance of the classical column for PCB analysi.
Functionality of Special Beer Processes and Potential Health Benefits

Consumers’ demand for functional fermented food that can fulfill nutritional needs and help maintain a balanced diet while also having a positive impact on one’s health status is increasing all over the world. Thus, healthy choices could include beverages with nutrients and bioactive compounds which can be used as an effective disease-prevention strategy. Regular beer has certain health benefits which inspire further research with the prospect of obtaining special functional beers with little or no alcohol content. As observed, the special beer market remains highly dynamic and is predicted to expand even further. Therefore, brewers need to keep up with the consumers’ interests and needs while designing special beers, namely nonalcoholic beers (NABs), low-alcohol beers (LABs), and craft beers (CBs). Thus, understanding the potential uses of bioactive compounds in special beer, the wide range of therapeutic effects, and the possible mechanisms of action is essential for developing healthier beverages. This review aimed to evaluate the nutritional features of special beers, and their proven or potential beneficial actions on one’s health status and in preventing certain diseases.
Indo-Pacific Phylogeography of the Lemon Sponge Leucetta chagosensis

The sponge Leucetta chagosensis Dendy (1913) has a wide distribution throughout the Indo-Pacific (IP) region, with previous studies focussing primarily on the western Pacific Ocean. To increase our knowledge of the spatial variation of genetic diversity throughout the IP, we constructed a phylogeny for L. chagosensis for the IP to assess the evolutionary patterns for this species. We generated 188 sequences of L. chagosensis and constructed maximum likelihood and Bayesian inference trees, using concatenated mitochondrial cytochrome oxidase subunit 3 gene (cox3) and nuclear ribosomal RNA gene (28S) markers for the first time. The spatial variation of genetic diversity of L. chagosensis was assessed using a phylogeographic approach. Leucetta chagosensis is composed of five cryptic lineages confined to different biogeographic regions with the specimens found in the Indian Ocean differing significantly from those found in the rest of the IP region. Genetic divergence was particularly high for the cox3 marker, with a low nucleotide diversity but high haplotype diversity for most lineages. This study highlights the need for a sustained effort in studying sponge diversity, boosted by the ongoing discovery of hidden biodiversity among this ecologically important taxon.
Absolute reliability and validity of the OptoGaitTM system to measure spatiotemporal gait parameters during running

The biomechanics of walking and running, in both ground and treadmill conditions, have been extensively analysed and important differences have been reported. Despite some previous studies having examined the validity and reliability of the OptoGait™ system for measuring gait characteristics during walking, no previous works have determined the reliability and validity of this system while running on a treadmill. Therefore, this study aimed to determine the absolute reliability (within-subject variation) and evaluate the concurrent validity of the OptoGait™ system for measuring spatiotemporal variables while running at a comfortable speed by comparing data with a highly accurate system of measuring those parameters (i.e. video analysis at 1000 Hz). Forty-nine endurance runners performed a running protocol on a treadmill at a comfortable speed. Two systems were used to collect data: OptoGait™ system and high-speed video analysis at 1000 Hz. The coefficient of variation (CV) was calculated as a measure of absolute reliability. The OptoGait™ system reported a CV range between 2.2% and 11.4% for spatiotemporal parameters, while the video analysis showed a CV range between 0.02% and 9.9%. To determine concurrent validity, intra class correlation coefficients (ICC) and pairwise comparisons of means (t-test) were calculated between data from both systems. Although the paired t-test demonstrated significant differences between systems, a high level of agreement (ICC > 0.89) was obtained in spatiotemporal parameters between systems. When compared to a high-speed video analysis at 1000 Hz, the results indicate that the OptoGait™ system is a reliable and valid tool to measure spatiotemporal gait characteristics while running on a treadmill at a comfortable speed.
Adequately reflecting the severity of tropical cyclones using the new Tropical Cyclone Severity Scale

For decades, meteorologists and governments have been warning communities in coastal areas for an imminent tropical cyclone (TC) using the Saffir-Simpson Hurricane Wind Scale (SSHWS). The SSHWS categorizes a TC based on its maximum wind speed, and is used in defining evacuation strategies and humanitarian response. However, the SSHWS considers only the wind hazard of a TC, whereas a TC can also cause severe conditions through its high storm surges and extreme rainfall, triggering coastal and inland flooding. Consequently, the SSHWS fails to mirror the TC’s total severity. This becomes evident when looking at past events such as Hurricane Harvey (2017), which was classified as a Tropical Storm while it caused widespread flooding in the Houston (TX) area, with precipitation totals exceeding 1.5 m. Without including storm surge and rainfall information, adequate risk communication with the SSHWS can be challenging, as the public can (mistakenly) perceive a low-category TC as a low-risk TC. To overcome this, we propose the new Tropical Cyclone Severity Scale (TCSS) that includes all three major TC hazards in its classification. The new scale preserves the categorization as used in the SSHWS, to maintain familiarity amongst the general public. In addition, we extend the scale with a Category 6, to support communication about the most extreme TCs with multiple hazards. The TCSS is designed to be applied on a local-scale, hereby supporting local-scale risk communication efforts and evacuation strategies prior to a TC landfall. The scale can be used for risk communication on both the total TC risk and on the categories of the separate hazards, which can be valuable especially in cases when one hazard is the predominant risk factor, such as excess rainfall triggering flooding.
Culturally Inclusive Adaptive User Interface (CIAUI) Framework: Exploration of Plasticity of User Interface Design

This paper presents a Culturally Inclusive Adaptive User Interface (CIAUI) Framework for developing Mobile Learning (M-Learning) and other mobile applications. The CIAUI Framework specifically incorporates the concepts of universal design aimed for culturally diverse users. This was derived as an outcome of a research project involving the design, analysis and evaluation of artificial intelligence (AI)-based adaptive interface development, known as the “Mobile Academy”, using plasticity of user interface (UI) design techniques for culturally inclusive design. The CIAUI Framework, was one of the major and significant output of the research, which satisfied the broad requirement for cross-cultural usability. The framework was not only defined but a complete analysis was conducted. Its parameters, validation, examples of developing applications and indicated direction of further research are presented here. The principles of culturally inclusive design are finally reviewed.
A deep learning-based ensemble method for helmet-wearing detection

Recently, object detection methods have developed rapidly and have been widely used in many areas. In many scenarios, helmet wearing detection is very useful, because people are required to wear helmets to protect their safety when they work in construction sites or cycle in the streets. However, for the problem of helmet wearing detection in complex scenes such as construction sites and workshops, the detection accuracy of current approaches still needs to be improved. In this work, we analyze the mechanism and performance of several detection algorithms and identify two feasible base algorithms that have complementary advantages. We use one base algorithm to detect relatively large heads and helmets. Also, we use the other base algorithm to detect relatively small heads, and we add another convolutional neural network to detect whether there is a helmet above each head. Then, we integrate these two base algorithms with an ensemble method. In this method, we first propose an approach to merge information of heads and helmets from the base algorithms, and then propose a linear function to estimate the confidence score of the identified heads and helmets. Experiments on a benchmark data set show that, our approach increases the precision and recall for base algorithms, and the mean Average Precision of our approach is 0.93, which is better than many other approaches. With GPU acceleration, our approach can achieve real-time processing on contemporary computers, which is useful in practice.
Side-chain engineering as a powerful tool to tune the properties of polymeric field-effect transistors

Abstract During the past ten years, the performance of polymeric field-effect transistors has been largely improved, not only in mobility but also in durability. Among the factors contributed to such improvements, side-chain engineering plays an important role. Various techniques, such as branch point adjustment, hydrogen-bonding introduction and the incorporation of other functional groups in the side-chain were developed, which greatly altered the crystallinity, alignment and morphology of the conjugated polymers hence their charge transport behavior. In this review, the side-chain engineering strategies that have been employed in polymeric field-effect transistors are summarized and discussed in detail, which we hope could provide an insight into further development in this area.
The use of artificial neural networks for modelling rumen fill

Abstract: Artificial neural network (ANN) and random forest models for predicting rumen fill of cattle and sheep were developed. Data on rumen fill were collected from studies that reported body weights, measured rumen fill, and stated diets fed to animals. Animal and feed factors that affected rumen fill were identified from each study and used to create a dataset. These factors were used as input variables for predicting the weight of rumen fill. For ANN modelling, a three-layer Levenberg–Marquardt back-propagation neural network was adopted and achieved 96% accuracy in prediction of the weight of rumen fill. The precision of the ANN model’s prediction of rumen fill was higher for cattle (80%) than sheep (56%). On validation, the ANN model achieved 95% accuracy in prediction of the weight of rumen fill. A random forest model was trained using a binary tree-based machine-learning algorithm and achieved 87% accuracy in prediction of rumen fill. The random forest model achieved 16% (cattle) and 57% (sheep) accuracy in validation of the prediction of rumen fill. In conclusion, the ANN model gave better predictions of rumen fill compared with the random forest model and should be used in predicting rumen fill of cattle and sheep.
Novel center potential based analytical sub-threshold model for dual metal broken gate TFET

Purpose The purpose of this paper is to present an improved model based on center potential instead of surface potential which is physically more relevant and accurate. Also, additional analytic insights have been provided to make the model independent and robust so that it can be extended to a full range compact model. Design/methodology/approach The design methodology used is center potential based analytical modeling using Psuedo-2D Poisson equation, with ingeniously developed boundary conditions, which help achieve reasonably accurate results. Also, the depletion width calculation has been suitably remodeled, to account for proper physical insights and accuracy. Findings The proposed model has considerable accuracy and is able to correctly predict most of the physical phenomena occurring inside the broken gate Tunnel FET structure. Also, a good match has been observed between the modeled data and the simulation results. Ion/Iambipolar ratio of 10^(−8) has been achieved which is quintessential for low power SOCs. Originality/value The modeling approach used is different from the previously used techniques and uses indigenous boundary conditions. Also, the current model developed has been significantly altered, using very simple but intuitive technique instead of complex mathematical approach.
Kinetic Study of the Ozonation of Some Industrial Wastewaters

Abstract Kinetic studies of the ozonation of two wastewaters released by distillery and tomato processing plants have been carried out. Once it has been assumed that an irreversible gas-liquid reaction is developed between ozone and the matter present in the water, the film theory concept was applied to this system for kinetic determinations. The evolution of the organic and inorganic matter with ozonation time has been followed by the chemical oxygen demand. The procedure allows the determination of the rate coefficients of ozone with the wastewaters treated. According to the results obtained, ozone is consumed through fast reactions which take place near the water-gas interface during an initial period. This period is used to determine the rate coefficients. Then, at more advanced ozonation times, the reactions become slower and hence they take place in the bulk of the water, articularly for the case of tomato wastewaters. Values of the rate coefficient allow us to establish both the kinetic regime of a.
Two New Limonoids from the Fruits of Melia azedarach (Meliaceae)

Two new limonoids, trichilinin M (1) and ohchinin benzoate (2), along with two known limonoids, 12‐hydroxyamoorastatone (3) and mesendanin H (4), were isolated from the fruits of Melia azedarach Linn. The structures of new limonoids were determined by analyses of HR‐ESI‐MS, 1D and 2D NMR (HSQC, HMBC and NOESY) data. All compounds were evaluated against human pancreatic cancer PANC1 cells and the results showed that compounds 3–4 exhibited substantial cytotoxic activity (3: IC50=4.55 μM; 4: IC50=7.54 μM), and compounds 1–2 exhibited moderate cytotoxicity (1: IC50=27.06 μM; 2: IC50=21.17 μM).
Teaching Programming Using the Robot-Based Learning Approach

This paper discusses learning theories, STEM, educational robotics as well as the current generation of students found in classrooms by reviewing previous and current academic literature on these topics, to assist in ascertaining the current advancements and theories related to the Robot-based learning approach as well as how these advancements have helped improve this approach and enabled educators to better make use of it. Furthermore, this paper reviews previous academic literature on computer programming to discuss the current learning approaches in use and the kind of learning tools being utilized. Once this topics are reviewed the reader can have a clear picture of the learning approach, what learning theory does it belong too, the type of students found in the classroom as well as what motivates them and the subject that is being taught as well as the different learning tools for this subject. The reader will also learn why improving the effectiveness of how programming is learned helps create more students good in STEM and how it assists in realising the Malaysian Educational Development Plan. This paper reviewed literature from the year 2014 and above as the information is more relevant and current, except for literature that is from a leading or renowned individual in any field that is being discussed in this dissertation.