bluuebunny/crossref_metadata_2025 huggingface dataset:
Thermal Stability of YSZ Thick Thermal Barrier Coatings Deposited by Suspension and Atmospheric Plasma Spraying
Authors: Tao Shiqian , Yang Jiasheng , Zhai Minglong , Shao Fang , Zhong Xinghua , Zhao Huayu , Zhuang Yin , Ni Jinxing , Li Wei , Tao Shunyan
Published: October 2020

Two types of segmentation-crack structured yttria-stabilized zirconia (YSZ) thick thermal barrier coatings (>500 μm, TTBCs) were deposited onto the stainless steel substrates using atmospheric plasma spraying (APS) and suspension plasma spraying (SPS) process, respectively. In this work, thermal aging behaviors, such as the microstructures, phase compositions, grain growth, and mechanical properties of APS TTBCs and SPS TTBCs, were systematically investigated. Results showed that both as-sprayed TTBCs exhibited a typical segmentation-crack structure in the through-thickness direction. APS coatings mainly comprised of larger columnar crystals, while a large number of smaller equiaxed grains existed in SPS coatings. Both of the coatings underwent tetragonal-monoclinic phase transformation after 155 °C/40 h heat treatment. The poorer phase stability of SPS TTBCs may have a connection with smaller grain size. Thermal-aged APS and SPS coatings exhibited a significant increase in H and E values with the rising of thermal aging temperature, and for the samples that thermal aged at 1550 °C, the H and E values increased sharply during initial stage then decreased after 80 h due to the phase decomposition. The segmented APS coatings had weak bonding between the lamellaes during thermal exposure, which caused the mean Vickers hardness value of APS TTBCs to be much lower than that of SPS TTBCs.
Blood Vessel Imaging at Pre-Larval Stages of Zebrafish Embryonic Development
Authors: Machikhin Alexander S. , Volkov Mikhail V. , Burlakov Alexander B. , Khokhlov Demid D. , Potemkin Andrey V.
Published: October 2020

The zebrafish (Danio rerio) is an increasingly popular animal model biological system. In cardiovascular research, it has been used to model specific cardiac phenomena as well as to identify novel therapies for human cardiovascular disease. While the zebrafish cardiovascular system functioning is well examined at larval stages, the mechanisms by which vessel activity is initiated remain a subject of intense investigation. In this research, we report on an in vivo stain-free blood vessel imaging technique at pre-larval stages of zebrafish embryonic development. We have developed the algorithm for the enhancement, alignment and spatiotemporal analysis of bright-field microscopy images of zebrafish embryos. It enables the detection, mapping and quantitative characterization of cardiac activity across the whole specimen. To validate the proposed approach, we have analyzed multiple data cubes, calculated vessel images and evaluated blood flow velocity and heart rate dynamics in the absence of any anesthesia. This non-invasive technique may shed light on the mechanism of vessel activity initiation and stabilization as well as the cardiovascular system’s susceptibility to environmental stressors at early developmental stages.
Construction and Application of Functional Brain Network Based on Entropy
Authors: Zhang Lingyun , Qiu Taorong , Lin Zhiqiang , Zou Shuli , Bai Xiaoming
Published: October 2020

Functional brain network (FBN) is an intuitive expression of the dynamic neural activity interaction between different neurons, neuron clusters, or cerebral cortex regions. It can characterize the brain network topology and dynamic properties. The method of building an FBN to characterize the features of the brain network accurately and effectively is a challenging subject. Entropy can effectively describe the complexity, non-linearity, and uncertainty of electroencephalogram (EEG) signals. As a relatively new research direction, the research of the FBN construction method based on EEG data of fatigue driving has broad prospects. Therefore, it is of great significance to study the entropy-based FBN construction. We focus on selecting appropriate entropy features to characterize EEG signals and construct an FBN. On the real data set of fatigue driving, FBN models based on different entropies are constructed to identify the state of fatigue driving. Through analyzing network measurement indicators, the experiment shows that the FBN model based on fuzzy entropy can achieve excellent classification recognition rate and good classification stability. In addition, when compared with the other model based on the same data set, our model could obtain a higher accuracy and more stable classification results even if the length of the intercepted EEG signal is different.
An Evaluation of Entropy Measures for Microphone Identification
Authors: Baldini Gianmarco , Amerini Irene
Published: October 2020

Research findings have shown that microphones can be uniquely identified by audio recordings since physical features of the microphone components leave repeatable and distinguishable traces on the audio stream. This property can be exploited in security applications to perform the identification of a mobile phone through the built-in microphone. The problem is to determine an accurate but also efficient representation of the physical characteristics, which is not known a priori. Usually there is a trade-off between the identification accuracy and the time requested to perform the classification. Various approaches have been used in literature to deal with it, ranging from the application of handcrafted statistical features to the recent application of deep learning techniques. This paper evaluates the application of different entropy measures (Shannon Entropy, Permutation Entropy, Dispersion Entropy, Approximate Entropy, Sample Entropy, and Fuzzy Entropy) and their suitability for microphone classification. The analysis is validated against an experimental dataset of built-in microphones of 34 mobile phones, stimulated by three different audio signals. The findings show that selected entropy measures can provide a very high identification accuracy in comparison to other statistical features and that they can be robust against the presence of noise. This paper performs an extensive analysis based on filter features selection methods to identify the most discriminating entropy measures and the related hyper-parameters (e.g., embedding dimension). Results on the trade-off between accuracy and classification time are also presented.
Fault-Tolerant Control of Coil Inter-Turn Short-Circuit in Five-Phase Permanent Magnet Synchronous Motor
Authors: Wang Dingyu , Chen Yiguang
Published: October 2020

In the five-phase permanent magnet synchronous motor (PMSM) control system, the torque ripple caused by coil inter-turn short-circuit (ITSC)fault will make the motor performance worse. Due to the existence of the short-circuit current in the faulty phase and the third harmonic component in the permanent magnet flux linkage, the electromagnetic torque will contain even-order ripple components when the faulty phase is removed. Torque ripple also cause speed ripple. In this paper, the repetitive controller (RC) is used to perform proportional gain compensation for speed ripple. By designing the RC and connecting RC and proportional integral (PI) controller in parallel for the speed loop, the torque ripple amplitude can be reduced. It can be seen from the simulation and experimental results that the torque ripple suppression strategy based on RC can effectively suppress the torque ripple under ITSC fault.
Liquefied Natural Gas in Mobile Applications—Opportunities and Challenges
Authors: Banaszkiewicz Tomasz , Chorowski Maciej , Gizicki Wojciech , Jedrusyna Artur , Kielar Jakub , Malecha Ziemowit , Piotrowska Agnieszka , Polinski Jaroslaw , Rogala Zbigniew , Sierpowski Korneliusz , Skrzypacz Janusz , Stanclik Michal , Tomczuk Krzysztof , Dowżenko Piotr
Published: October 2020

Liquefied natural gas (LNG) is one of the most influential fuels of the 21st century, especially in terms of the global economy. The demand for LNG is forecasted to reach 400 million tonnes by 2020, increasing up to 500 million tonnes in 2030. Due to its high mass and volumetric energy density, LNG is the perfect fuel for long-distance transport, as well as for use in mobile applications. It is also characterized by low levels of emissions, which is why it has been officially approved for use as a marine fuel in Emission Control Areas (ECAs) where stricter controls have been established to minimize the airborne emissions produced by ships. LNG is also an emerging fuel in heavy road and rail transport. As a cryogenic fuel that is characterized by a boiling temperature of about 120 K (−153 °C), LNG requires the special construction of cryogenic mobile installations to fulfill conflicting requirements, such as a robust mechanical construction and a low number of heat leaks to colder parts of the system under high safety standards. This paper provides a profound review of LNG applications in waterborne and land transport. Exemplary constructions of LNG engine supply systems are presented and discussed from the mechanical and thermodynamic points of view. Physical exergy recovery during LNG regasification is analyzed, and different methods of the process are both analytically and experimentally compared. The issues that surround two-phase flows and phase change processes in LNG regasification and recondensation are addressed, and technical solutions for boil-off gas recondensation are proposed. The paper also looks at the problems surrounding LNG installation data acquisition and control systems, concluding with a discussion of the impact of LNG technologies on future trends in low-emission transport.
Knowledge-Based Segmentation to Improve Accuracy and Explainability in Non-Technical Losses Detection
Authors: Calvo Albert , Coma-Puig Bernat , Carmona Josep , Arias Marta
Published: October 2020

Utility companies have a great interest in identifying energy losses. Here, we focus on Non-Technical Losses (NTL), which refer to losses caused by utility theft or meter errors. Typically, utility companies resort to machine learning solutions to automate and optimise the identification of such losses. This paper extends an existing NTL-detection framework: by including knowledge-based NTL segmentation, we have detected some opportunities for improving the accuracy and the explanations provided to the utility company. Our improved models focus on specific types of NTL and therefore, the explanations provided are easier to interpret, allowing stakeholders to make more informed decisions. The improvements and results presented in the article may benefit other industrial frameworks.
A Two-Stage Stochastic Optimisation Methodology for the Operation of a Chlor-Alkali Electrolyser under Variable DAM and FCR Market Prices
Authors: Baetens Jens , De Kooning Jeroen D. M. , Van Eetvelde Greet , Vandevelde Lieven
Published: October 2020

The increased penetration of renewable energy sources in the electrical grid raises the need for more power system flexibility. One of the high potential groups to provide such flexibility is the industry. Incentives to do so are provided by variable pricing and remuneration of supplied ancillary services. The operational flexibility of a chlor-alkali electrolysis process shows opportunities in the current energy and ancillary services markets. A co-optimisation of operating the chlor-alkali process under an hourly variable priced electricity sourcing strategy and the delivery of Frequency Containment Reserve (FCR) is the core of this work. A short term price prediction for the Day-Ahead Market (DAM) and FCR market as input for a deterministic optimisation shows good results under standard DAM price patterns, but leaves room for improvement in case of price fluctuations, e.g., as caused by Renewable Energy Sources (RES). A two-stage stochastic optimisation is considered to cope with the uncertainties introduced by the exogenous parameters. An improvement of the stochastic solution over the deterministic Expected Value (EV) solution is shown.
A New Production-Splitting Method for the Multi-Well-Monitor System
Authors: Zhang Jiaqi , He Chang , Yu Jichen , Teng Bailu , Luo Wanjing , Liu Xinfei
Published: October 2020

In order to reduce the cost of wellheads, the production rate of the gas wells in the Hechuan Gas Field are mostly measured in groups, which raises a stringent barrier for industries to determine the production rate of each single well. The technique for determining the production of a single well from the production of the well-group can be called the production splitting method (PSM). In this work, we proposed a novel PSM for the multi-well-monitor system (MWMS) on the basis of the Beggs and Brill (BB) correlation. This proposed method can account for the multi-phase flow together with the features of the pipelines. Specifically, we discretize the pipeline into small segments and recognize the flow pattern in each segment. The pressure drop along the pipeline is calculated with the Beggs and Brill correlation, and the production of each well is subsequently determined with a trial method. We also applied this proposed method to a field case, and the calculated results show that the results from this work undergo an excellent agreement with the field data.
Chattering Free Adaptive Sliding Mode Controller for Photovoltaic Panels with Maximum Power Point Tracking
Authors: Gohar Ali Hina , Arbos Ramon Vilanova
Published: October 2020

Photovoltaic system is utilized to generate energy that relies upon the ecological conditions, for example, temperature, irradiance, and the load associated with it. Considering the non-linear component of photovoltaic (PV) array and the issue of low effectiveness because of the variable natural conditions, the Maximum Power Point Tracking (MPPT) method is required to extract the maximum power from the PV system. The adopted control is executed utilizing an Adaptive Sliding Mode Controller (ASMC) and the enhancement is actualized utilizing an Improved Pattern Search Method (IPSM). This work employs IPSM based optimization approach in order to command the underlying ASMC controller. The upper level decision determines the sliding surface for the adaptive controller. As a non-linear strategy, the stability of the adaptive controller is guaranteed by conducting a Liapunov analysis. On the practical side, MATLAB/Simulink is used as simulator for the controller implementation and coupling with PSIM in order to connect it with the PV system object of control. The simulation results validate that the proposed controller effectively improves the voltage tracking, system power with reduced chattering effect and steady-state error. The performance of the proposed control architectures is validated by comparing the proposals with that of the well-known and widely used Proportional Integral Derivative (PID) controller. That operated as a lower level controller for a Perturb & Observe (P&O) and Particle Swarm Optimization (PSO).
A Novel Application of Improved Marine Predators Algorithm and Particle Swarm Optimization for Solving the ORPD Problem
Authors: Shaheen Mohamed A. M. , Yousri Dalia , Fathy Ahmed , Hasanien Hany M. , Alkuhayli Abdulaziz , Muyeen S. M.
Published: October 2020

The appropriate planning of electric power systems has a significant effect on the economic situation of countries. For the protection and reliability of the power system, the optimal reactive power dispatch (ORPD) problem is an essential issue. The ORPD is a non-linear, non-convex, and continuous or non-continuous optimization problem. Therefore, introducing a reliable optimizer is a challenging task to solve this optimization problem. This study proposes a robust and flexible optimization algorithm with the minimum adjustable parameters named Improved Marine Predators Algorithm and Particle Swarm Optimization (IMPAPSO) algorithm, for dealing with the non-linearity of ORPD. The IMPAPSO is evaluated using various test cases, including IEEE 30 bus, IEEE 57 bus, and IEEE 118 bus systems. An effectiveness of the proposed optimization algorithm was verified through a rigorous comparative study with other optimization methods. There was a noticeable enhancement in the electric power networks behavior when using the IMPAPSO method. Moreover, the IMPAPSO high convergence speed was an observed feature in a comparison with its peers.
Energetic and Economic Analyses of an LCPV/T Solar Hybrid Plant for a Sports Center Building in Mexico
Authors: Acosta-Pazmiño Iván , Rivera-Solorio Carlos , Gijón-Rivera Miguel
Published: October 2020

This study presents a techno-economic performance evaluation of a hybrid low-concentrating photovoltaic/thermal (LCPV/T) plant, which operates in a student sports and wellness center building situated at a university campus in Mexico. The solar plant comprises 144 LCPV/T collectors based on a hybridized version of a local parabolic trough technology. Dynamic thermal and electrical performance analyses were performed in the TRNSYS simulation studio. The results showed that the solar field could cover up to 72% of the hot water demand of the building during the summer season and 24% during the winter season. The hybrid system could annually save 7185 USD, accounting for heat (natural gas boiler) and electricity generation. However, the payback time was of 19.23 years, which was mainly attributed to a reduced natural gas price in Monterrey, Mexico. A new approach to evaluating the equivalent levelized cost of heat (LCOHeq), is proposed. This results in an LCOHeq of 0.065 USD/kWh, which is nearly equivalent to the LCOH of a natural gas-fired boiler (0.067 USD/kWh). Finally, the hybrid plant could achieve a specific CO2e emission reduction of 77.87 kg CO2e per square meter of the required installation area.
Cross-seasonal Experimental Study on the Comprehensive Performance of C-Si PV Window
Authors: Zhang Wei , Wang Wei , Xie Lingzhi , Tian Hao , Chen Mo , Li Zihao , Li Jianhui
Published: October 2020

PV windows can potentially produce electricity, reduce the air-conditioning load, and provide natural light. Cross-seasonal experimental tests for long period could eliminate the gap between real outdoor test and simulation estimation. In this research, the lighting-thermal-electricity performance of high-efficiency c-silicon PV windows was tested, and the improvement has been put forward according to the conditions. The long-term experiment was conducted cross different seasons, including summer, autumn, and winter seasons. The highest average power generation, 50W/m2, could be found in autumn. The average outside surface temperature of the PV window would reach 48 °C in sunny days in the autumn, which was higher than other seasons. Although the c-Si PV window maybe block the partial daylighting, the daylighting requirement still could be satisfied with the most days. Furthermore, the average Useful Daylight Illuminance was the highest in summer up to 0.79, and the average illumination uniform could be achieved at a high level in all seasons. For the improvement suggestions, some measures could be taken to reduce the indoor cooling load in summer. During winter, appropriate inner shading measures might be taken to prevent excessive illumination in the building, and allow the electricity and thermal performance of PV window.
An Improved Set of Design Criteria for Slotted Liners in Steam Assisted Gravity Drainage Operation
Authors: Wang Chenxi , Haftani Mohammad , David Montero Pallares Jesus , Nouri Alireza
Published: October 2020

Slotted liners are widely used in steam-assisted gravity drainage (SAGD) wells to control sand production and sustain wellbore productivity. The slotted liner can provide desirable performance when appropriately designed. A literature review indicates a limited number of studies that offer design criteria specifically for SAGD wells. Moreover, past criteria seem to neglect some key factors, which may lead to inadequate slot design. This paper proposes a set of graphical design criteria for slotted liners in SAGD production wells, using prepacked sand retention testing (SRT) data. The SRT is designed to incorporate several essential factors that are not present in the past design criteria, such as slot density, steam breakthrough, and particle size distribution (PSD). The proposed design criteria are presented graphically for normal and aggressive conditions, where the aggressive condition accounts for the potential occurrence of the steam breakthrough. It is found that the upper bound of the design window is substantially lower for the aggressive condition due to the higher sand production after the steam breakthrough. The design criteria also indicate that the slotted liner is suitable only for the formations with low fines content.
The Effect of Selected Factors on Floor Upheaval in Roadways—In Situ Testing
Authors: Małkowski Piotr , Ostrowski Łukasz , Bednarek Łukasz
Published: October 2020

The phenomenon of the floor upheaval occurs in virtually every type of rock mass and at every depth, accompanying the process of excavation of tunnels and headings. Despite its inconvenience, it is rarely studied because of the complexity of the process and the multiplicity of the factors causing deformations in floor rocks. To quantify the effect of the selected factors on floor upheaval, this article presents an analysis of results of in situ measurements carried out in three coal mine roadways at 15 measuring stations. These measurements were taken over varying periods of time, between 129 and 758 days. Groundwater and fault zones intersecting the excavations were considered as the key factors that affect floor upheavals. Therefore, the measurement bases were located at local faults and sites of water inflow. To compare the results, the stations were also located where the rock mass was not exposed to any factors other than stresses resulting from the depth of the excavation. The excavations were driven in various rocks and were located at different depths from 750 to 1010 m. The analyses of the study results show that the floor upheaval always depends on time and can be described in polynomial form: ufl = a·t2 + b·t + c or by a power function: ufl = a·tb. However, the further regression analyses show that roadway’s floor upheaval can be expressed by a complex form using the key parameters determining the phenomena. In the absence of an impact of geological factors on the stability of the excavation, the floor upheaval depends on floor rocks compressive strength σc and Young’s modulus E: ln(ufl)=a·ln(tσc)−bE−c; in the case of rock mass condition affected by water depends on the rock compressive strength reduction after submerging rock in water σcs 6h: ufl=a·t0.5−bσcs 6hσc+c and in the case of fault depends on the fault’s throw f: ufl=a·t0.8+b·f1.2−c. Statistical analysis has shown that the matching of the models to the measurement data is high and amounts to r = 0.841–0.895. Hence, in general, the analysis shows that the floor upheaval in underground excavation in any geological conditions may grow indefinitely.
Parameter Localization of Greenhouse Gas Value Model and Greenhouse Gas Storage Simulation for Forest Ecosystems in China
Authors: Li Mengdi , Cui Yaoping , Qin Yaochen , Chubwa Oliva Gabriel , Fu Yiming , Li Nan , Liu Xiaoyan , Run Yadi
Published: October 2020

Quantifying the greenhouse gas (GHG) storage in forest ecosystems can support global change directly, from a biogeochemical perspective. However, accurately assessing the amount of GHG storage in forest ecosystems still faces challenges in China because of their wide distribution, varying types, and the changing definitions and areas of forests. We used land-use data with 5-year intervals during 1990–2015 to investigate the spatiotemporal variations of forest ecosystems in China. As three major greenhouse gases in forest ecosystems, the potential storage of carbon dioxide, methane, and nitrous oxide can be calculated by a greenhouse gas value (GHGV) model. The results showed that the total area of forest ecosystems decreased by 15 × 105 ha during the study period. The area of forest ecosystems reached its highest level in 1995 and then declined. For various forest ecosystem types, shrubbery (Sh) increased by 0.82% but the broad-leaved forest, evergreen coniferous forest (ECF), and mixed forest (MF) all showed a downward trend. Correspondingly, the potential GHG storage of forest ecosystems declined from 156.97 Pg CO2-equivalent (CO2-eq) to 155.56 Pg CO2-eq, a decrease of 1.41 Pg CO2-eq. Compared with previous research results, the GHGV model proved to be an important supplementary method for estimating the potential storage of GHGs in forest ecosystems, especially in highly fragmented landscapes at a large scale. Our study indicated that the impact of forest ecosystems changes on potential GHG storage was serious during the study period. Our findings highlight that the GHGV model can be an effective and low-cost strategy to simulate the forest change and corresponding GHG storage. And considering the efficiency of the model and the historical analysis results of many periods, some of the results can also be used to inform the future afforestation programs and assess the expected GHG storage in China.
Changes in Water Retention and Carbon Sequestration in the Huangshan UNESCO Global Geopark (China) from 2000 to 2015
Authors: Gou Ruikun , Li Wei , Yang Yanzheng , Bai Jiankun , Meng Yuchen , Wu Jun , Ding Yali , Dai Zheng , Shi Qi , Song Shanshan , Lin Guanghui
Published: October 2020

Geopark ecosystem function assessments form an essential knowledge base for natural resource conservation and sustainable development. In this study, we evaluated changes in water retention and carbon sequestration in forests in the Huangshan United Nations Educational, Scientific, and Cultural Organization (UNESCO) Global Geopark (HUGG), China, from 2000 to 2015. We analyzed the relationship between these ecosystem functions and various controlling factors. The ecosystem functions in HUGG experienced significant changes during the study period. Water retention function increased slightly (0.15 m3 hm−2 year−1), while carbon sequestration increased sharply (25.57 g C m−2 year−1), with both showing increased spatial homogenization. Increased precipitation significantly enhanced the water retention function, whereas a temperature increase had a positive effect on the carbon sequestration. Both water retention and carbon sequestration decreased significantly with increased tourist disturbance. Pearson’s correlation coefficient and variance partitioning analysis identified the climate factors and tourist disturbance controlling water retention and carbon sequestration, respectively. The fitted structural equation model showed that climate factors had a greater total impact on water retention than tourist disturbance, while the total impact of climate factors on carbon sequestration was far less than that due to tourist disturbance. This study untangled the relationship between ecosystem functions (water retention and carbon sequestration) and influential factors in the HUGG and clarified that climate factors and tourist disturbance were determinants of changes in these ecosystem functions. The results from this study provide scientific foundations for the sustainable management of natural ecosystems in the HUGG and other geoparks.
Environmental Effects on Carbon Isotope Discrimination from Assimilation to Respiration in a Coniferous and Broad-Leaved Mixed Forest of Northeast China
Authors: Diao Haoyu , Wang Anzhi , Yuan Fenghui , Guan Dexin , Dai Guanhua , Wu Jiabing
Published: October 2020

Carbon (C) isotope discrimination during photosynthetic CO2 assimilation has been extensively studied, but the whole process of fractionation from leaf to soil has been less well investigated. In the present study, we investigated the δ13C signature along the C transfer pathway from air to soil in a coniferous and broad-leaved mixed forest in northeast China and examined the relationship between δ13C of respiratory fluxes (leaf, trunk, soil, and the entire ecosystem) and environmental factors over a full growing season. This study found that the δ13C signal of CO2 from canopy air was strongly imprinted in the organic and respiratory pools throughout C transfer due to the effects of discrimination and isotopic mixing on C assimilation, allocation, and respiration processes. A significant difference in isotopic patterns was found between conifer and broadleaf species in terms of seasonal variations in leaf organic matter. This study also found that δ13C in trunk respiration, compared with that in leaf and soil respiration, was more sensitive to seasonal variations of environmental factors, especially soil temperature and soil moisture. Variation in the δ13C of ecosystem respiration was correlated with air temperature with no time lag and correlated with soil temperature and vapor pressure deficit with a lag time of 10 days, but this correlation was relatively weak, indicating a delayed linkage between above- and belowground processes. The isotopic linkage might be confounded by variations in atmospheric aerodynamic and soil diffusion conditions. These results will help with understanding species differences in isotopic patterns and promoting the incorporation of more influencing factors related to isotopic variation into process-based ecosystem models.
A Comparative Analysis of Machine Learning Techniques for Cyberbullying Detection on Twitter
Authors: Muneer Amgad , Fati Suliman Mohamed
Published: October 2020

The advent of social media, particularly Twitter, raises many issues due to a misunderstanding regarding the concept of freedom of speech. One of these issues is cyberbullying, which is a critical global issue that affects both individual victims and societies. Many attempts have been introduced in the literature to intervene in, prevent, or mitigate cyberbullying; however, because these attempts rely on the victims’ interactions, they are not practical. Therefore, detection of cyberbullying without the involvement of the victims is necessary. In this study, we attempted to explore this issue by compiling a global dataset of 37,373 unique tweets from Twitter. Moreover, seven machine learning classifiers were used, namely, Logistic Regression (LR), Light Gradient Boosting Machine (LGBM), Stochastic Gradient Descent (SGD), Random Forest (RF), AdaBoost (ADB), Naive Bayes (NB), and Support Vector Machine (SVM). Each of these algorithms was evaluated using accuracy, precision, recall, and F1 score as the performance metrics to determine the classifiers’ recognition rates applied to the global dataset. The experimental results show the superiority of LR, which achieved a median accuracy of around 90.57%. Among the classifiers, logistic regression achieved the best F1 score (0.928), SGD achieved the best precision (0.968), and SVM achieved the best recall (1.00).
An Improved Deep Belief Network Prediction Model Based on Knowledge Transfer
Authors: Zhang Yue , Liu Fangai
Published: October 2020

A deep belief network (DBN) is a powerful generative model based on unlabeled data. However, it is difficult to quickly determine the best network structure and gradient dispersion in traditional DBN. This paper proposes an improved deep belief network (IDBN): first, the basic DBN structure is pre-trained and the learned weight parameters are fixed; secondly, the learned weight parameters are transferred to the new neuron and hidden layer through the method of knowledge transfer, thereby constructing the optimal network width and depth of DBN; finally, the top-down layer-by-layer partial least squares regression method is used to fine-tune the weight parameters obtained by the pre-training, which avoids the traditional fine-tuning problem based on the back-propagation algorithm. In order to verify the prediction performance of the model, this paper conducts benchmark experiments on the Movielens-20M (ML-20M) and Last.fm-1k (LFM-1k) public data sets. Compared with other traditional algorithms, IDBN is better than other fixed models in terms of prediction performance and training time. The proposed IDBN model has higher prediction accuracy and convergence speed.
Dietary Exposure Estimation to Chemicals Transferred from Milk and Dairy Products Packaging Materials in Spanish Child and Adolescent Population
Authors: Lestido-Cardama Antía , Sendón Raquel , Bustos Juana , Lomo Mª Luisa , Losada Perfecto Paseiro , de Quirós Ana Rodríguez Bernaldo
Published: October 2020

Packaging materials are subject to risk assessment since they can transfer their components to the food, and they may constitute a risk for the consumers’ health. Therefore, estimating the exposure to chemicals migrating from packaging is required. In this study, a novel approach based on a total diet study (TDS)-like investigation to evaluate the exposure to chemicals transferred from the packaging was presented. The proposed methodology involved a non-targeted gas chromatography coupled to mass spectrometry (GC-MS) method to identify potential migrants and the determination of the migrants in composite food samples. The method was applied to evaluate the dietary exposure to chemicals from food packaging materials used for milk and dairy products in the Spanish child and adolescent populations. Several migrants identified in packaging materials were selected to determine their concentration in composite food samples. These chemicals included diethyl phthalate (DEP), diisobutyl phthalate (DIBP), dibutyl phthalate (DBP), bis(2ethylhexyl) phthalate (DEHP), benzophenone (BP), 1,3-diphenylpropane (1,3-DPP), and bis(2-ethylhexyl) terephthalate (DEHT). The method exhibited a good sensitivity (limit of detection, LOD ≤ 0.05 µg/g) and a satisfactory recovery (78.4-124%). Finally, the exposure was estimated using the Spanish national dietary survey ENALIA. Phthalates DBP and DEHP showed the highest mean exposure, ranging from 2.42 (10–17 years)–4.40 (12–35 months) and 1.35 (10–17 years)–4.07 (12–35 months) µg/kg bw/day for DBP and DEHP, respectively.
Fabrication of Functional Bioelastomer for Food Packaging from Aronia (Aronia melanocarpa) Juice Processing By-Products
Authors: Lee Kang Hyun , Chun Youngsang , Jang Ye Won , Lee Soo Kweon , Kim Hyeong Ryeol , Lee Ju Hun , Kim Seung Wook , Park Chulhwan , Yoo Hah Young
Published: October 2020

Carbon-neutral and eco-friendly biomass-based processes are recognized as a frontier technology for sustainable development. In particular, biopolymers are expected to replace petrochemical-based films that are widely used in food packaging. In this study, the fabrication conditions of functional (antioxidant and antibacterial) bioelastomers were investigated using by-products from the juice processing (experimental group) and freeze-dried whole fruit (control group). Bioelastomer was fabricated by a casting method in which polydimethylsiloxane (PDMS) was mixed with 25 or 50 wt% aronia powder (juice processing by-products and freeze-dried whole fruit). The mechanical properties of the bioelastomers were measured based on tensile strength and Young’s modulus. When the mixture contained 50 wt% aronia powder, the strength was not appropriate for the intended purpose. Next, the surface and chemical properties of the bioelastomer were analyzed; the addition of aronia powder did not significantly change these properties when compared to PDMS film (no aronia powder). However, the addition of aronia powder had a significant effect on antioxidant and antimicrobial activities and showed higher activity with 50 wt% than with 25 wt%. In particular, bioelastomers fabricated from aronia juice processing by-products exhibited approximately 1.4-fold lower and 1.5-fold higher antioxidant and antimicrobial activities, respectively, than the control group (bioelastomers fabricated from freeze-dried aronia powder).
Risk Assessment of the Dietary Phosphate Exposure in Taiwan Population Using a Total Diet Study
Authors: Ling Min-Pei , Huang Jun-Da , Hsiao Huai-An , Chang Yu-Wei , Kao Yi-Ting
Published: October 2020

Phosphorus and calcium are essential nutrients for the human body. However, excessive intake of phosphates and a low calcium:phosphorus ratio can lead to disorders in calcium-phosphorus metabolism, kidney disease, or osteoporosis. In this study, a total diet study (TDS) was used. The total phosphorus concentrations of foods were combined with the average dietary consumption to calculate the estimated daily intake, which was compared with the maximum tolerable daily intake (MTDI) to assess the resulting health risk of total phosphorus exposure. The calcium concentration in food and total calcium intake were also analyzed and estimated to calculate the calcium:phosphorus ratio. In conclusion, the phosphate exposure risks for the Taiwanese population are acceptable. However, the calcium:phosphorus ratio in the Taiwanese population (0.51–0.63) is lower than the reference calcium:phosphorus ratio (1.25).
Phenotype and Genotype Correlations in Inherited Retinal Diseases: Population-Guided Variant Interpretation, Variable Expressivity and Incomplete Penetrance
Authors: Ellingford Jamie M. , Hufnagel Robert B. , Arno Gavin
Published: October 2020

Inherited retinal diseases (IRDs) are a diverse and variable group of rare human disorders [...]
WNT11-Conditioned Medium Promotes Angiogenesis through the Activation of Non-Canonical WNT-PKC-JNK Signaling Pathway
Authors: Wang Jingcai , Gong Min , Zuo Shi , Xu Jie , Paul Chris , Li Hongxia , Liu Min , Wang Yi-Gang , Ashraf Muhammad , Xu Meifeng
Published: October 2020

Background: We demonstrated that the transduction of Wnt11 into mesenchymal stem cells (MSCs) (MSCWnt11) promotes these cells differentiation into cardiac phenotypes. In the present study, we investigated the paracrine effects of MSCWnt11 on cardiac function and angiogenesis. Methods and Results: Conditioned medium was collected from MSCWnt11 (CdMWnt11) and their control cells (CdMGFP). CdMWnt11, especially obtained from MSCWnt11 exposed to hypoxia, significantly promoted human umbilical vein endothelial cells (HUVECs) migration and increased capillary-like tube (CLT) formation, which was blocked by Wnt11 neutralizing antibody. Wnt11 protein was significantly higher in CdMWnt11 compared to that in CdMGFP. Directly treating HUVECs with recombinant Wnt11 protein significantly increased CLT formation, which was abrogated by treating cells with the JNK inhibitor SP600125, as well as the PKC inhibitor Calphostin-C. Moreover, the transfection of Wnt11 to HUVECs (HWnt11) significantly increased CLT formation and HUVEC migration, as well as upregulated p-pan-PKC and p-JNK expression. Injection of CdMWnt11 into the peri-infarct region in a rat acute myocardial infarction (AMI) model significantly improved cardiac function, reduced infarct size, and increased myocardial blood flow and blood vessel density in the ischemic area. Conclusion: Wnt11 released from MSCWnt11 increased angiogenesis and improved cardiac function via non-canonical Wnt-PKC-JNK dependent pathways.
The Plant Target of Rapamycin: A Conduc TOR of Nutrition and Metabolism in Photosynthetic Organisms
Authors: Ingargiola Camille , Turqueto Duarte Gustavo , Robaglia Christophe , Leprince Anne-Sophie , Meyer Christian
Published: October 2020

Living organisms possess many mechanisms to sense nutrients and favorable conditions, which allow them to grow and develop. Photosynthetic organisms are very diverse, from green unicellular algae to multicellular flowering plants, but most of them are sessile and thus unable to escape from the biotic and abiotic stresses they experience. The Target of Rapamycin (TOR) signaling pathway is conserved in all eukaryotes and acts as a central regulatory hub between growth and extrinsic factors, such as nutrients or stress. However, relatively little is known about the regulations and roles of this pathway in plants and algae. Although some features of the TOR pathway seem to have been highly conserved throughout evolution, others clearly differ in plants, perhaps reflecting adaptations to different lifestyles and the rewiring of this primordial signaling module to adapt to specific requirements. Indeed, TOR is involved in plant responses to a vast array of signals including nutrients, hormones, light, stresses or pathogens. In this review, we will summarize recent studies that address the regulations of TOR by nutrients in photosynthetic organisms, and the roles of TOR in controlling important metabolic pathways, highlighting similarities and differences with the other eukaryotes.
A Review of the Important Role of CYP2D6 in Pharmacogenomics
Authors: Taylor Christopher , Crosby Ian , Yip Vincent , Maguire Peter , Pirmohamed Munir , Turner Richard M.
Published: October 2020

Cytochrome P450 2D6 (CYP2D6) is a critical pharmacogene involved in the metabolism of ~20% of commonly used drugs across a broad spectrum of medical disciplines including psychiatry, pain management, oncology and cardiology. Nevertheless, CYP2D6 is highly polymorphic with single-nucleotide polymorphisms, small insertions/deletions and larger structural variants including multiplications, deletions, tandem arrangements, and hybridisations with non-functional CYP2D7 pseudogenes. The frequency of these variants differs across populations, and they significantly influence the drug-metabolising enzymatic function of CYP2D6. Importantly, altered CYP2D6 function has been associated with both adverse drug reactions and reduced drug efficacy, and there is growing recognition of the clinical and economic burdens associated with suboptimal drug utilisation. To date, pharmacogenomic clinical guidelines for at least 48 CYP2D6-substrate drugs have been developed by prominent pharmacogenomics societies, which contain therapeutic recommendations based on CYP2D6-predicted categories of metaboliser phenotype. Novel algorithms to interpret CYP2D6 function from sequencing data that consider structural variants, and machine learning approaches to characterise the functional impact of novel variants, are being developed. However, CYP2D6 genotyping is yet to be implemented broadly into clinical practice, and so further effort and initiatives are required to overcome the implementation challenges and deliver the potential benefits to the bedside.
Iron Assimilation during Emerging Infections Caused by Opportunistic Fungi with emphasis on Mucorales and the Development of Antifungal Resistance
Authors: Stanford Felicia Adelina , Voigt Kerstin
Published: October 2020

Iron is a key transition metal required by most microorganisms and is prominently utilised in the transfer of electrons during metabolic reactions. The acquisition of iron is essential and becomes a crucial pathogenic event for opportunistic fungi. Iron is not readily available in the natural environment as it exists in its insoluble ferric form, i.e., in oxides and hydroxides. During infection, the host iron is bound to proteins such as transferrin, ferritin, and haemoglobin. As such, access to iron is one of the major hurdles that fungal pathogens must overcome in an immunocompromised host. Thus, these opportunistic fungi utilise three major iron acquisition systems to overcome this limiting factor for growth and proliferation. To date, numerous iron acquisition pathways have been fully characterised, with key components of these systems having major roles in virulence. Most recently, proteins involved in these pathways have been linked to the development of antifungal resistance. Here, we provide a detailed review of our current knowledge of iron acquisition in opportunistic fungi, and the role iron may have on the development of resistance to antifungals with emphasis on species of the fungal basal lineage order Mucorales, the causative agents of mucormycosis.
Risk Assessment of Rock Falls Released from the Former Quarry Near Spitz (Austria)
Authors: Poisel Rainer , Hoedlmoser Nikolaus , Grasemann Bernhard
Published: October 2020

In the former quarry near Spitz an der Donau (Austria), many rockfalls have occurred during operation as well as after closure. They have endangered a railway, the Wachau bicycle route, an important road, and the left Danube riverbank. Thus, future detachment scenarios were investigated and, in addition, weather and occurrence statistics were analyzed to determine the occurrence probabilities of these scenarios. Simulations of possible future rockslides were performed using the Distinct Element Code 3DEC in order to estimate the damage caused by these events. Based on these results, the risks of the scenarios were calculated according to the definition of risk as the product of damage and occurrence probability. By this means, the profitability of mitigation measures (e.g., a massive retaining structure fixed to the ground by bored piles) can be evaluated.
Supporting Role of Society and Firms to COVID-19 Management among Medical Practitioners
Authors: Zandi GholamReza , Shahzad Imran , Farrukh Muhammad , Kot Sebastian
Published: October 2020

Measurement of job stress and employees’ commitment are few of the admired topics in the corporate world amongst business writers. With a principal aim to trial the blow of exposure to COVID-19 patients on doctors’ job stress and commitment, in Pakistan; data have been collected through 7-10 min telephonic interview from voluntary participants and a sample of 129 responses were analyzed by Structure Equation Modeling-Partial Least Square (SEM-PLS) path modeling through Smart PLS 3.2. The results of the study indicated; direct positive & significant impact of Extent of Exposure on Job Stress while direct negative, significant association with Commitment. Job Stress also observed having direct negative impact on commitment. The Extent of Exposure-Job Stress relationship was also found stronger among group of doctors having Low level of Perceived Organizational Support and weaker among group of doctors having High level of Perceive Organizational support. Perceived Organizational Support showed a moderating effect on the Extent of Exposure-Job Stress relationship; while, Social Support showed no moderation. Researchers are required to investigate more and management of the medical services providers (both hospitals and government) needs to focus on doctors’ perception about Organizational Support, as doctors show no concern about the support from society as long as their well-being is cared for by respective hospitals. This study is an effort to stimulate more empirical evidence towards the treating and handling of COVID-19 patients and the psychological well-being of doctors.