bluuebunny/crossref_metadata_2025 huggingface dataset:
Screen-Cam Robust Image Watermarking with Feature-Based Synchronization
Authors: Chen Weitong , Ren Na , Zhu Changqing , Zhou Qifei , Seppänen Tapio , Keskinarkaus Anja
Published: October 2020

The screen-cam process, which is taking pictures of the content displayed on a screen with mobile phones or cameras, is one of the main ways that image information is leaked. However, traditional image watermarking methods are not resilient to screen-cam processes with severe distortion. In this paper, a screen-cam robust watermarking scheme with a feature-based synchronization method is proposed. First, the distortions caused by the screen-cam process are investigated. These distortions can be summarized into the five categories of linear distortion, gamma tweaking, geometric distortion, noise attack, and low-pass filtering attack. Then, a local square feature region (LSFR) construction method based on a Gaussian function, modified Harris–Laplace detector, and speeded-up robust feature (SURF) orientation descriptor is developed for watermark synchronization. Next, the message is repeatedly embedded in each selected LSFR by an improved embedding algorithm, which employs a non-rotating embedding method and a preprocessing method, to modulate the discrete Fourier transform (DFT) coefficients. In the process of watermark detection, we fully utilize the captured information and extract the message based on a local statistical feature. Finally, the experimental results are presented to illustrate the effectiveness of the method against common attacks and screen-cam attacks. Compared to the previous schemes, our scheme has not only good robustness against screen-cam attack, but is also effective against screen-cam with additional common desynchronization attacks.
Computational Fluid Dynamics Study of Superselective Intra-arterial Chemotherapy for Oral Cancer: Flow Simulation of Anticancer Agent in the Linguofacial Trunk
Authors: Kitajima Hiroaki , Iwai Toshinori , Yajima Yasuharu , Mitsudo Kenji
Published: October 2020

Superselective intra-arterial chemotherapy (SSIAC) for oral cancer can deliver a higher concentration of anticancer agent into a tumor-feeding artery than intravenous systemic chemotherapy. However, the agent distribution between the lingual artery and facial artery (FA) is not clear in SSIAC for patients with the linguofacial trunk. The agent distribution in the SSIAC method was investigated using computational fluid dynamics (CFD). Ten three-dimensional vessel models were created from CT images of two patients with oral cancer (patients A and B) with the linguofacial trunk. Catheter models were combined with vessel models to mimic intra-arterial infusion, and the agent flow was analyzed. In patient A models, the agent distribution varied depending on the catheter tip position in the linguofacial trunk, while all anticancer agents flowed into the FA only in patient B models. This study revealed that the behavior of the agent in the common trunk is determined by the blood flow field which depends on the topography of the vessels in each patient. Therefore, the catheter tip position should be changed according to the vessel topography to deliver anticancer agents into the tumor-feeding artery. Moreover, CFD can be a useful method to predict the agent flow for each patient before SSIAC.
Hydrogenation of Adiponitrile to Hexamethylenediamine over Raney Ni and Co Catalysts
Authors: Lee Younghyun , Lee Sung Woo , Kim Hyung Ju , Kim Yong Tae , Lin Kun-Yi Andrew , Lee Jechan
Published: October 2020

Hexamethylenediamine (HMDA), a chemical for producing nylon, was produced on Raney Ni and Raney Co catalysts via the hydrogenation of adiponitrile (ADN). HMDA was hydrogenated from ADN via 6-aminohexanenitrile (AHN). For the two catalysts, the effects of five different reaction parameters (reaction temperature, H2 pressure, catalyst loading, and ADN/HMDA ratio in the reactant) on the hydrogenation of ADN were investigated. Similar general trends demonstrating the dependence of ADN hydrogenation on the reaction conditions for both catalysts were observed: higher temperature (60–80 °C) and H2 pressure, as well as lower ADN/catalyst and ADN/HMDA ratios, led to higher HMDA yields. A further increase in temperature from 80 to 100 °C increased the HMDA yield from 90.5 to 100% for the Raney Ni catalyst, but did not affect the HMDA yield (85~87%) for the Raney Co catalyst. A 100% HMDA yield (the highest yield reported to date) was also achieved via ADN hydrogenation over the Raney Ni catalyst, with a high HMDA content in the reactant (e.g., ADN/HMDA volumetric ratio of 0.06). No sign of metal leaching into the product solution was found, meaning that the Raney Ni and Raney Co catalysts were stable during ADN hydrogenation.
Kidney Boundary Detection Algorithm Based on Extended Maxima Transformations for Computed Tomography Diagnosis
Authors: Les Tomasz , Markiewicz Tomasz , Dziekiewicz Miroslaw , Lorent Malgorzata
Published: October 2020

This article describes the automated computed tomography (CT) image processing technique supporting kidney detection. The main goal of the study is a fully automatic generation of a kidney boundary for each slice in the set of slices obtained in the computed tomography examination. This work describes three main tasks in the process of automatic kidney identification: the initial location of the kidneys using the U-Net convolutional neural network, the generation of an accurate kidney boundary using extended maxima transformation, and the application of the slice scanning algorithm supporting the process of generating the result for the next slice, using the result of the previous one. To assess the quality of the proposed technique of medical image analysis, automatic numerical tests were performed. In the test section, we presented numerical results, calculating the F1-score of kidney boundary detection by an automatic system, compared to the kidneys boundaries manually generated by a human expert from a medical center. The influence of the use of U-Net support in the initial detection of the kidney on the final F1-score of generating the kidney outline was also evaluated. The F1-score achieved by the automated system is 84% ± 10% for the system without U-Net support and 89% ± 9% for the system with U-Net support. Performance tests show that the presented technique can generate the kidney boundary up to 3 times faster than raw U-Net-based network. The proposed kidney recognition system can be successfully used in systems that require a very fast image processing time. The measurable effect of the developed techniques is a practical help for doctors, specialists from medical centers dealing with the analysis and description of medical image data.
Observability Analysis and Navigation Filter Optimization of High-Orbit Satellite Navigation System Based on GNSS
Authors: Xiao Yaqi , Zhou Xuanying , Wang Jiongqi , He Zhangming , Zhou Haiyin
Published: October 2020

Global Navigation Satellite System (GNSS) can be applied for the navigation of the high-orbit satellites. The system observability will change due to the changes in the visible satellite numbers and the spatial geometry between the navigation satellites and the users in the navigation system. The influence of the observability changing is not considered in the traditional navigation filter algorithm. In this paper, an optimized navigation filter method based on observability analysis is proposed. Firstly, a novel criterion for the relative observable degree is proposed for each observation component by making use of observation data from previous and posterior time simultaneously. Secondly, according to the relationship between observability and navigation filter accuracy, a novel optimized navigation filter method is constructed by introducing an adjusting factor based on the relative observable degree. Through the comparative simulations with the traditional Extended Kalman Filter (EKF), the optimized navigation filter method can reduce the estimation error of position and velocity by about 36% and 44% respectively. Therefore, the superiority of the proposed filter optimization algorithm is verified.
Pressure Loss Optimization to Reduce Pipeline Clogging in Bulk Transfer System of Offshore Drilling Rig
Authors: Kim Yongho , Lee Kwangkook
Published: October 2020

In offshore drilling systems, the equipment localization rate is less than 20%, and the monopoly of a few foreign conglomerates over the equipment is intensifying. To break this monopoly, active technology development and market entry strategies are required. In a drillship or a floating production, storage, and offloading unit, the distance from the tank top to the upper deck is approximately 30–40 m. Therefore, the pressure loss problem inside the vertical pipe from the tank to the deck should be considered. To transport the bulk at the target transport rate without clogging, the pressure loss inside the vertical pipe should be optimized. Moreover, the operating pressure, air volume, and transport rate accuracy determine the system and operating costs. Hence, system optimization is necessary. In this study, pressure loss modeling and simulation of the bulk transfer system are performed to prevent frequent pipeline clogging. The proposed simulation model is verified using real test data. The bulk transfer system is verified through a simulation, indicating an error rate of 4.27%. In addition, the number of air boosters required to minimize the pipeline’s pressure loss and the optimal distance between the boosters are obtained using a genetic algorithm. With the optimized air booster, pressure loss for approximately 0.54 bar was compensated. The improved bulk transfer system is expected to reduce uncertainty and minimize maintenance and repair costs during operation. Moreover, it can contribute to high-value fields such as construction, commissioning, installation, maintenance, and equipment localization improvement.
A Source Code Similarity Based on Siamese Neural Network
Authors: Xie Chunli , Wang Xia , Qian Cheng , Wang Mengqi
Published: October 2020

Finding similar code snippets is a fundamental task in the field of software engineering. Several approaches have been proposed for this task by using statistical language model which focuses on syntax and structure of codes rather than deep semantic information underlying codes. In this paper, a Siamese Neural Network is proposed that maps codes into continuous space vectors and try to capture their semantic meaning. Firstly, an unsupervised pre-trained method that models code snippets as a weighted series of word vectors. The weights of the series are fitted by the Term Frequency-Inverse Document Frequency (TF-IDF). Then, a Siamese Neural Network trained model is constructed to learn semantic vector representation of code snippets. Finally, the cosine similarity is provided to measure the similarity score between pairs of code snippets. Moreover, we have implemented our approach on a dataset of functionally similar code. The experimental results show that our method improves some performance over single word embedding method.
Visibility Parameter in Sand/Dust Storms’ Radio Wave Attenuation Equations: An Approach for Reliable Visibility Estimation Based on Existing Empirical Equations to Minimize Potential Biases in Calculations
Authors: Mahmood Hamzah N. , Ismail Widad
Published: October 2020

In efforts to structure an expression for wave attenuation under a sand/dust storm, most established calculations pronounce optical visibility as an essential parameter. Although visibility information can be retrieved from weather stations, other commonly encountered sources may present it differently, i.e., as total suspended particles (TSP). Consequently, several empirical equations linking visibility to TSP concentrations were evaluated to address offset tendencies in estimations. In addition to substantiating specific equations, the results revealed that averaging a pair of equations has a 46.09% chance of estimating visibilities with a probability of 37.27%, a relatively low error compared to that achieved by employing single equations, which were found to have a probability of 28.93% with a lesser chance (29.58%) of a low estimation error for the same set of data. The resulting enhancement was evaluated by considering a study on a wireless sensor network’s (WSN’s) signal performance under vaguely labelled meteorological conditions. The meteorological conditions were converted to visibility using the results’ suggestions and were found to be in good agreement with an observation standard set by the China Meteorological Administration (CMA) for sand/dust storm outbreak classifications.
An Optimization Model for Operational Planning and Turnaround Maintenance Scheduling of Oil and Gas Supply Chain
Authors: Ghaithan Ahmed M.
Published: October 2020

Hydrocarbon supply chain (HCSC) is a complex network that extends from oil and gas fields to demand nodes. Integrating operation and maintenance activities along this complex network is crucial since the hydrocarbon industry is the most influential sector in the world economy, and any disruptions or variations in hydrocarbon product supply will affect the whole world economy. Therefore, effective and thoughtful maintenance extends the life of an asset and enhances its reliability. To prevent huge losses in production and ultimately satisfy customer needs, the maintenance jobs are preferred to be performed during times of low demand. Thus, operation planning and maintenance scheduling decisions are dependent and should be optimized simultaneously. Therefore, the aim of this study is to develop an integrated mathematical model for the operation and maintenance planning of the oil and gas supply chain. The utility of the proposed model has been demonstrated using the Saudi Arabian HCSC. The proposed model effectively produces optimal operation and maintenance schedule decisions. A sensitivity analysis was conducted to study the effect of critical parameters on the obtained results.
WRF-LES Simulation of the Boundary Layer Turbulent Processes during the BLLAST Campaign
Authors: Udina Mireia , Montornès Àlex , Casso Pau , Kosović Branko , Bech Joan
Published: October 2020

A real case long-term nested large eddy simulation (LES) of 25-day duration is performed using the WRF-LES modelling system, with a maximum horizontal grid resolution of 111 m, in order to explore the ability of the model to reproduce the turbulence magnitudes within the first tens of metres of the boundary layer. Sonic anemometer measurements from a 60-m tower installed during the Boundary Layer Late Afternoon and Sunset Turbulence (BLLAST) field campaign are used for verification, which is focused on the turbulent magnitudes in order to assess the success and limitations in resolving turbulent flow characteristics. The mesoscale and LES simulations reproduce the wind speed and direction fairly well, but only LES is able to reproduce the energy of eddies with lifetimes shorter than a few hours. The turbulent kinetic energy in LES simulation is generally underestimated during the daytime, mainly due to a vertical velocity standard deviation that is too low. The turbulent heat flux is misrepresented in the model, probably due to the inaccuracy of the sub-grid scheme.
Prediction of Short-Time Cloud Motion Using a Deep-Learning Model
Authors: Su Xinyue , Li Tiejian , An Chenge , Wang Guangqian
Published: October 2020

A cloud image can provide significant information, such as precipitation and solar irradiation. Predicting short-time cloud motion from images is the primary means of making intra-hour irradiation forecasts for solar-energy production and is also important for precipitation forecasts. However, it is very challenging to predict cloud motion (especially nonlinear motion) accurately. Traditional methods of cloud-motion prediction are based on block matching and the linear extrapolation of cloud features; they largely ignore nonstationary processes, such as inversion and deformation, and the boundary conditions of the prediction region. In this paper, the prediction of cloud motion is regarded as a spatiotemporal sequence-forecasting problem, for which an end-to-end deep-learning model is established; both the input and output are spatiotemporal sequences. The model is based on gated recurrent unit (GRU)- recurrent convolutional network (RCN), a variant of the gated recurrent unit (GRU), which has convolutional structures to deal with spatiotemporal features. We further introduce surrounding context into the prediction task. We apply our proposed Multi-GRU-RCN model to FengYun-2G satellite infrared data and compare the results to those of the state-of-the-art method of cloud-motion prediction, the variational optical flow (VOF) method, and two well-known deep-learning models, namely, the convolutional long short-term memory (ConvLSTM) and GRU. The Multi-GRU-RCN model predicts intra-hour cloud motion better than the other methods, with the largest peak signal-to-noise ratio and structural similarity index. The results prove the applicability of the GRU-RCN method for solving the spatiotemporal data prediction problem and indicate the advantages of our model for further applications.
Mesosphere Ozone and the Lower Ionosphere under Plasma Disturbance by Powerful High-Frequency Radio Emission
Authors: Bakhmetieva Nataliya V. , Kulikov Yuri Yu. , Zhemyakov Ilia N.
Published: October 2020

We present the results of experiments on the Earth’s lower ionosphere at mesospheric heights by creating artificial periodic irregularities (APIs) of the ionospheric plasma and simultaneous measurement of the atmospheric emission spectrum in the ozone line by ground-based microwave radiometry when the ionosphere was disturbed by powerful high-frequency radio emission from the midlatitude SURA heating facility (56.15° N; 46.11° E). The diagnostics of the ionosphere was carried out on the basis of measuring amplitudes and phases of signals scattered by periodic irregularities in the altitude range of 50–130 km. For each heating session lasting 30 min, two ozone spectra were measured. These spectra were compared with the measured spectra the periods when heating was turned off. During the heating session of the ionosphere, a decrease in the intensity of the microwave radiation of the atmosphere in the ozone line was observed. The lower ionosphere was characterized by intense dynamics. Rapid variations in the amplitude of the scattered signal and the relaxation time of artificial periodic irregularities were observed. The velocity of a regular vertical movement in the D-region of the ionosphere constantly varied direction with average minute values up to 4–5 m/s. We assume the decrease in the ozone emission spectrum at the altitude of 60 km can be explained by an increase in the coefficient of electron attachment to oxygen molecules during heating sessions. The lower boundary of the region enriched with atomic oxygen was estimated from the height profile of the API relaxation time.
COSMO-CLM Performance and Projection of Daily and Hourly Temperatures Reaching 50 °C or Higher in Southern Iraq
Authors: Levi Yoav , Mann Yossi
Published: October 2020

Fortunately, extreme temperatures reaching 50 °C are not common on our planet. The capability of the consortium for small-scale modelling regional climate model (COSMO-CLM), with 0.44° resolution, to project future trends of an extremely hot environment with direct model output (DMO) is questioned. The temperature distribution of COSMO-CLM output driven by reanalysis and RCP4.5 scenario in southern Iraq was remarkably good, with a slight temperature overestimation, compared to the overlapping observations from Basra airport. An attempt to enhance the DMO with a statistical downscaling method did not improve the results. The COSMO-CLM projection indicates that a very sharp increase in the number of consecutive hours and days with the temperature reaching 50 °C or higher will occur. During 1951–1980, consecutive hours and days reaching 50 °C were rare events. By the end of the century, the projected climate in southern Iraq contains up to 13 consecutive hours and 21 consecutive days reaching 50 °C or higher. As the average projected temperature will increase by ~2 °C compared to the recent climate, new records may be expected. However, the major climate change feature is the increase in consecutive hours and days of very high temperatures. These findings require adaptation measures to support future habitation of the region.
The Effect of Emotional and Cultural Intelligences on Networks’ Behaviors in International SMEs: Evidence from Portugal
Authors: Cabral Ângelo Miguel R. , Carvalho Fernando Manuel P. O. , Ferreira José António V.
Published: October 2020

The major purpose of this research was to study the predictive value of the top managers’ psychological characteristics regarding their networking behavior. In the international business management context of small- and medium-sized enterprises, we took the top managers’ cultural intelligence and emotional intelligence as determinant capabilities to perform better in their external networking. The sample was composed of 307 Portuguese SMEs’ international decision-makers, specifically founders, owners, chief executive officers (CEOs), managers of international activities, international market managers, or commercial managers. The data was collected from 2–30 April 2019 through online surveys directed to the Portuguese decision-makers that were directly responsible for the firms’ international activities. As a data collection instrument, the surveys were pretested and sent by e-mail. The average age of the participants was approximately 50 years old for males and 45 years old for females. We used self-reported measures to assess the different constructs and the hierarchical regression analysis to test our hypotheses. The results showed that cultural intelligence and emotional intelligence were significant drivers of decision-makers’ external networking behavior. A new factor structure concerning external networking behavior was retained. The major results exhibited the predictive value of some cultural and emotional intelligence dimensions over the new retained external networking behavior factors. Therefore, in the international business management context, the capability to adapt to new cultural contexts, as well as the capability to reason about emotions, improved the international decision-makers’ external networking behavior.
Ion Channels as Therapeutic Targets in High Grade Gliomas
Authors: Griffin Michaela , Khan Raheela , Basu Surajit , Smith Stuart
Published: October 2020

Glioblastoma multiforme (GBM) is a lethal brain cancer with an average survival of 14–15 months even with exhaustive treatment. High grade gliomas (HGG) represent the leading cause of CNS cancer-related death in children and adults due to the aggressive nature of the tumour and limited treatment options. The scarcity of treatment available for GBM has opened the field to new modalities such as electrotherapy. Previous studies have identified the clinical benefit of electrotherapy in combination with chemotherapeutics, however the mechanistic action is unclear. Increasing evidence indicates that not only are ion channels key in regulating electrical signaling and membrane potential of excitable cells, they perform a crucial role in the development and neoplastic progression of brain tumours. Unlike other tissue types, neural tissue is intrinsically electrically active and reliant on ion channels and their function. Ion channels are essential in cell cycle control, invasion and migration of cancer cells and therefore present as valuable therapeutic targets. This review aims to discuss the role that ion channels hold in gliomagenesis and whether we can target and exploit these channels to provide new therapeutic targets and whether ion channels hold the mechanistic key to the newfound success of electrotherapies.
Roles of Farnesyl-Diphosphate Farnesyltransferase 1 in Tumour and Tumour Microenvironments
Authors: Ha Nguyen Thi , Lee Chang Hoon
Published: October 2020

Farnesyl-diphosphate farnesyltransferase 1 (FDFT1, squalene synthase), a membrane-associated enzyme, synthesizes squalene via condensation of two molecules of farnesyl pyrophosphate. Accumulating evidence has noted that FDFT1 plays a critical role in cancer, particularly in metabolic reprogramming, cell proliferation, and invasion. Based on these advances in our knowledge, FDFT1 could be a potential target for cancer treatment. This review focuses on the contribution of FDFT1 to the hallmarks of cancer, and further, we discuss the applicability of FDFT1 as a cancer prognostic marker and target for anticancer therapy.
Hypothermia Advocates Functional Mitochondria and Alleviates Oxidative Stress to Combat Acetaminophen-Induced Hepatotoxicity
Authors: Tan Yeong Lan , Ho Han Kiat
Published: October 2020

For years, moderate hypothermia (32 °C) has been proposed as an unorthodox therapy for liver injuries, with proven hepatoprotective potential. Yet, limited mechanistic understanding has largely denied its acceptance over conventional pharmaceuticals for hepatoprotection. Today, facing a high prevalence of acetaminophen-induced liver injury (AILI) which accounts for the highest incidence of acute liver failure, hypothermia was evaluated as a potential therapy to combat AILI. For which, transforming growth factor-α transgenic mouse hepatocytes (TAMH) were subjected to concomitant 5 mM acetaminophen toxicity and moderate hypothermic conditioning for 24 h. Thereafter, its impact on mitophagy, mitochondrial biogenesis, glutathione homeostasis and c-Jun N-terminal kinase (JNK) signaling pathways were investigated. In the presence of AILI, hypothermia displayed simultaneous mitophagy and mitochondrial biogenesis to conserve functional mitochondria. Furthermore, antioxidant response was apparent with higher glutathione recycling and repressed JNK activation. These effects were, however, unremarkable with hypothermia alone without liver injury. This may suggest an adaptive response of hypothermia only to the injured sites, rendering it favorable as a potential targeted therapy. In fact, its cytoprotective effects were displayed in other DILI of similar pathology as acetaminophen i.e., valproate- and diclofenac-induced liver injury and this further corroborates the mechanistic findings of hypothermic actions on AILI.
Plasma Etching Behavior of YOF Coating Deposited by Suspension Plasma Spraying in Inductively Coupled CHF3/Ar Plasma
Authors: Lee Seungjun , Lee Jaehoo , Kim Woongsik , Hwang Nong-Moon
Published: October 2020

Dense yttrium oxyfluoride (YOF) coating was successfully deposited by suspension plasma spraying (SPS) with coaxial feeding. After deposition for 6 min at a plasma power of 105 kW, the thickness of the YOF coating was 55 ± 3.2 µm with a porosity of 0.15% ± 0.01% and the coating rate was ~9.2 µm/min. The crystalline structure of trigonal YOF was confirmed by X-ray diffractometry (XRD). The etching behavior of the YOF coating was studied using inductively coupled CHF3/Ar plasma in comparison with those of the Al2O3 bulk and Y2O3 coating. Crater-like erosion sites and cavities were formed on the whole surface of the Al2O3 bulk and Y2O3 coating. In contrast, the surface of the YOF coating showed no noticeable difference before and after exposure to the CHF3/Ar plasma. Such high resistance of the YOF coating to fluorocarbon plasma comes from the strongly fluorinated layer on the surface. The fluorination on the surface of materials was confirmed by X-ray photoelectron spectrum analysis (XPS). Depth profiles of the compositions of Al2O3, Y2O3, and YOF samples by XPS revealed that the fluorination layer of the YOF coating was much thicker than those of Al2O3 and Y2O3. These results indicate that if the inner wall of the semiconductor process chamber is coated by YOF using SPS, the generation of contamination particles would be minimized during the fluorocarbon plasma etching process.
The Effect of the Laser Incidence Angle in the Surface of L-PBF Processed Parts
Authors: Sendino Sara , Gardon Marc , Lartategui Fernando , Martinez Silvia , Lamikiz Aitzol
Published: October 2020

The manufacture of multiple parts on the same platform is a common procedure in the Laser Powder Bed Fusion (L-PBF) process. The main advantage is that the entire working volume of the machine is used and a greater number of parts are obtained, thus reducing inert gas volume, raw powder consumption, and manufacturing time. However, one of the main disadvantages of this method is the possible differences in quality and surface finish of the different parts manufactured on the same platform depending on their orientation and location, even if they are manufactured with the same process parameters and raw powder material. Throughout this study, these surface quality differences were studied, focusing on the variation of the surface roughness with the angle of incidence of the laser with respect to the platform. First, a characterization test was carried out to understand the behavior of the laser in the different areas of the platform. Then, the surface roughness, microstructure, and minimum thickness of vertical walls were analyzed in the different areas of the platform. These results were related to the angle of incidence of the laser. As it was observed, the laser is completely perpendicular only in the center of the platform, whilst at the border of the platform, due to the incidence angle, it melts an elliptical area, which affects the roughness and thickness of the manufactured part. The roughness increases from values of Sa = 5.489 μm in the central part of the platform to 27.473 μm at the outer borders while the thickness of the manufactured thin walls increases around 40 μm.
Antifungal Polyvinyl Alcohol Coatings Incorporating Carvacrol for the Postharvest Preservation of Golden Delicious Apple
Authors: Sapper Mayra , Martin-Esparza Maria Eugenia , Chiralt Amparo , Gonzalez Martinez Chelo
Published: October 2020

Different polyvinyl alcohol (PVA) coating formulations incorporating starch (S) and carvacrol (C) as the active agent were applied to Golden Delicious apples to evaluate their effectiveness at controlling weight loss, respiration rate, fruit firmness, and fungal decay against B. cinerea and P. expansum throughout storage time. Moreover, the impact of these coatings on the sensory attributes of the fruit was also analyzed. The application of the coatings did not notably affect the weight loss, firmness changes, or respiration pathway of apples, probably due to the low solid surface density of the coatings. Nevertheless, they exhibited a highly efficient disease control against both black and green mold growths, as a function of the carvacrol content and distribution in the films. The sensory analysis revealed the great persistence of the carvacrol aroma and flavor in the coated samples, which negatively impact the acceptability of the coated products.
Characteristics of Flakes Stacked Cr2N with Many Domains in Super Duplex Stainless Steel
Authors: Lin Po-Chiang , Tsai Yu-Ting , Gan Neng-Hao , Yang Jer-Ren , Wang Shing-Hoa , Chang Horng-Yi , Lin Tzy-Rong , Chiu Po-Kai
Published: October 2020

This study mainly observed the Cr2N (chromium nitride) nucleation and growth in SAF 2507 duplex stainless steel. However, the investigation revealed that Cr2N has a complex substructure separated into many regions. In SAF 2507 duplex stainless steel, Cr2N nucleated at the dislocations and the precipitates were composed of many Cr2N flakes gathered together when aged at 600 °C.
Quantum Probability’s Algebraic Origin
Authors: Niestegge Gerd
Published: October 2020

Max Born’s statistical interpretation made probabilities play a major role in quantum theory. Here we show that these quantum probabilities and the classical probabilities have very different origins. Although the latter always result from an assumed probability measure, the first include transition probabilities with a purely algebraic origin. Moreover, the general definition of transition probability introduced here comprises not only the well-known quantum mechanical transition probabilities between pure states or wave functions, but further physically meaningful and experimentally verifiable novel cases. A transition probability that differs from 0 and 1 manifests the typical quantum indeterminacy in a similar way as Heisenberg’s and others’ uncertainty relations and, furthermore, rules out deterministic states in the same way as the Bell-Kochen-Specker theorem. However, the transition probability defined here achieves a lot more beyond that: it demonstrates that the algebraic structure of the Hilbert space quantum logic dictates the precise values of certain probabilities and it provides an unexpected access to these quantum probabilities that does not rely on states or wave functions.
FASTENER Feature Selection for Inference from Earth Observation Data
Authors: Koprivec Filip , Kenda Klemen , Šircelj Beno
Published: October 2020

In this paper, a novel feature selection algorithm for inference from high-dimensional data (FASTENER) is presented. With its multi-objective approach, the algorithm tries to maximize the accuracy of a machine learning algorithm with as few features as possible. The algorithm exploits entropy-based measures, such as mutual information in the crossover phase of the iterative genetic approach. FASTENER converges to a (near) optimal subset of features faster than other multi-objective wrapper methods, such as POSS, DT-forward and FS-SDS, and achieves better classification accuracy than similarity and information theory-based methods currently utilized in earth observation scenarios. The approach was primarily evaluated using the earth observation data set for land-cover classification from ESA’s Sentinel-2 mission, the digital elevation model and the ground truth data of the Land Parcel Identification System from Slovenia. For land cover classification, the algorithm gives state-of-the-art results. Additionally, FASTENER was tested on open feature selection data sets and compared to the state-of-the-art methods. With fewer model evaluations, the algorithm yields comparable results to DT-forward and is superior to FS-SDS. FASTENER can be used in any supervised machine learning scenario.
Thermal Efficiency of Oxyhydrogen Gas Burner
Authors: Moreno-Soriano Roberto , Soriano-Moranchel Froylan , Flores-Herrera Luis Armando , Sandoval-Pineda Juan Manuel , González-Huerta Rosa de Guadalupe
Published: October 2020

One of the main methods used to generate thermal energy is the combustion process. Burners are used in both industrial and residential applications of the open combustion process. The use of fuels that reduce polluting gas emissions and costs in industrial and residential processes is currently a topic of significant interest. Hydrogen is considered an attractive fuel for application in combustion systems due to its high energy density, wide flammability range, and only produces water vapor as waste. Compared to research conducted regarding hydrocarbon combustion, studies on hydrogen burners have been limited. This paper presents the design and evaluation of an oxyhydrogen gas burner for the atmospheric combustion process. The gas is generated in situ with an alkaline electrolyzer with a production rate of up to 3 sL min−1. The thermal efficiency of a gas burner is defined as the percentage of the input thermal energy transferred to the desired load with respect to a given time interval. The experimental results show a thermal efficiency of 30% for a minimum flow rate of 1.5 sL min−1 and 76% for a flow rate of 3.5 sL min−1. These results relate to a 10 mm height between the burner surface and heated container.
Performance of Communication Network for Monitoring Utility Scale Photovoltaic Power Plants
Authors: Eltamaly Ali M. , A. Ahmed Mohamed , Alotaibi Majed A. , Alolah Abdulrahman I. , Kim Young-Chon
Published: October 2020

The grid integration of large scale photovoltaic (PV) power plants represents many challenging tasks for system stability, reliability and power quality due to the intermittent nature of solar radiation and the site accessibility issues where most PV power plants are located over a wide area. In order to enable real-time monitoring and control of large scale PV power plants, reliable two-way communications with low latency are required which provide accurate information for the electrical and environmental parameters as well as enabling the system operator to evaluate the overall performance and identify any abnormal conditions and faults. This work aims to design a communication network architecture for the remote monitoring of large-scale PV power plants based on the IEC 61850 Standard. The proposed architecture consists of three layers: the PV power system layer, the communication network layer, and the application layer. The PV power system layer consists of solar arrays, inverters, feeders, buses, a substation, and a control center. Monitoring parameters are classified into different categories including electrical measurements, status information, and meteorological data. This work considers the future plan of PV power plants in Saudi Arabia. In order to evaluate the performance of the communication network for local and remote monitoring, the OPNET Modeler is used for network modeling and simulation, and critical parameters such as network topology, link capacity, and latency are investigated and discussed. This work contributes to the design of reliable monitoring and communication of large-scale PV power plants.
The Role of Multiple Injections on Combustion in a Light-Duty PPC Engine
Authors: Solsjö Rickard , Jangi Mehdi , Johansson Bengt , Bai Xue-Song
Published: October 2020

This paper presents a numerical investigation of the ignition and combustion process of a primary reference fuel in a partially premixed light-duty internal combustion (PPC) engine. Partially pre-mixed combustion is achieved by employing a multiple injection strategy with three short injection events of fuel pulses. The timing of the first two fuel pulses, 48 and 22 crank angle degrees before top dead center, are chosen with the purpose to stratify the fuel and air charge, whereas the third injection, at five crank angle degrees before top dead center, serves as an actuator of the main heat release. In addition to this baseline injection, three alternative injection strategies are studied, including a split-fuel two-injection strategy and modified triple-injection strategies. Large eddy simulations are employed utilizing a skeletal chemical kinetic mechanism for primary reference fuel capable of capturing the low-temperature ignition and the high temperature combustion. The large eddy simulation (LES) results are compared with experiments in an optical accessible engine. The results indicate that the first ignition sites are in the bowl region where the temperature is relatively higher, and the reaction fronts thereafter propagate in the swirl direction and towards the centerline of the cylinder. The charge from the first two injections initially undergoes low-temperature reactions and thereafter high-temperature reservoirs are formed in the bowl region. The main heat-release is initiated in the engine when the fuel from the third injection reaches the high-temperature reservoirs. Finally, the remaining fuel in the lean mixtures from the first two injections is oxidized. By variation of the injection strategy, two trends are identified: (1) by removing the second injection a higher intake temperature is required to enable the ignition of the charge, and (2) by retarding second injection, a longer ignition delay is identified. Both can be explained by the stratification of fuel and air mixture, and the resulting reactivity in various equivalence ratio and temperature ranges. The LES results reveal the details of the charge stratification and the subsequent heat release process. The present results indicate a rather high sensitivity of partially premixed combustion process to the injection strategies.
Feasibility of a 100% Global Renewable Energy System
Authors: Moriarty Patrick , Honnery Damon
Published: October 2020

Controversy exists as to whether renewable energy (RE) can provide for all the world’s energy needs. The purpose of this paper is to help resolve this vital question. Official forecasts see a resumption of a business-as-usual world after the pandemic-induced recession, with further economic growth out to at least 2050. The novel approach taken in this paper is to assume that such a world is fueled entirely with RE at global energy levels at or above those of today, and then to examine whether this scenario is feasible. Because the intermittent primary electricity sources, wind, and solar power, would have to supply nearly all this energy, a simplification made for this analysis is that they do supply 100% of all energy, including non-electrical energy needs. It is found that the energy that could be delivered by these two sources is much less than often assumed, for several reasons: The declining quality of inputs; the need for inclusion of uncounted environmental costs; the need for energy conversion and storage; and the removal of existing fossil fuel energy subsidies. It is concluded that a future world entirely fuelled by RE would necessarily be a lower-energy one.
A Rat Study to Evaluate the Protein Quality of Three Green Microalgal Species and the Impact of Mechanical Cell Wall Disruption
Authors: Wang Yanwen , Tibbetts Sean M. , Berrue Fabrice , McGinn Patrick J. , MacQuarrie Scott P. , Puttaswamy Anil , Patelakis Shane , Schmidt Dominique , Melanson Ronald , MacKenzie Sabrena E.
Published: October 2020

The present study was conducted to evaluate the protein quality of microalgae species Chlorella vulgaris (CV), Chlorella sorokiniana (CS), and Acutodesmus obliquus (AO) and assess the impact of mechanical cell wall disruption. Male Sprague–Dawley rats, around 156 g after adaptation, were placed in metabolic cages and fed experimental diets that were either protein-free or contained 10% protein solely from one of the undisrupted or disrupted CV, CS, and AO. After 3 days, feces were collected for a period of 5 days and analyzed together with diet samples for crude protein contents. Apparent protein digestibility, true protein digestibility, amino acid score, and protein digestibility-corrected amino acid score were calculated. In vitro protein digestibility was measured using the pepsin–pancreatin method and the in vitro protein digestibility-corrected amino acid score was calculated. The crude protein contents of CV, CS, and AO were 53.5, 50.2, and 40.3%, respectively. The amino acid score of the first limiting amino acid was 1.10, 1.27, and 0.86, true protein digestibility was 64.7, 59.3, and 37.9% and protein digestibility-corrected amino acid score was 0.63, 0.64, and 0.29, respectively, for CV, CS, and AO. Mechanical cell disruption significantly improved protein digestibility without a substantial impact on the amino acid profile and score, resulting in the increase of protein digestibility-corrected amino acid score to 0.77, 0.81, and 0.46, respectively, for disrupted CV, CS, and AO. There was a strong correlation between in vitro protein digestibility and apparent protein digestibility (r = 0.986), and also between in vitro protein digestibility-corrected amino acid score and in vivo protein digestibility-corrected amino acid score (r = 0.994). The results suggest that the CV and CS are acceptable sources of protein for humans and animals and quality can be markedly improved by mechanical cell wall disruption. Additionally, in vitro protein digestibility measured using the pepsin–pancreatin method may be used to screen protein product candidates, save animals, reduce cost, and accelerate product development.
Identification of Novel Mutations and Expressions of EPAS1 in Phaeochromocytomas and Paragangliomas
Authors: Islam Farhadul , Pillai Suja , Gopalan Vinod , Lam Alfred King-Yin
Published: October 2020

Endothelial PAS domain-containing protein 1 (EPAS1) is an oxygen-sensitive component of the hypoxia-inducible factors (HIFs) having reported implications in many cancers by inducing a pseudo-hypoxic microenvironment. However, the molecular dysregulation and clinical significance of EPAS1 has never been investigated in depth in phaeochromocytomas/paragangliomas. This study aims to identify EPAS1 mutations and alterations in DNA copy number, mRNA and protein expression in patients with phaeochromocytomas/paragangliomas. The association of molecular dysregulations of EPAS1 with clinicopathological factors in phaeochromocytomas and paragangliomas were also analysed. High-resolution melt-curve analysis followed by Sanger sequencing was used to detect mutations in EPAS1. EPAS1 DNA number changes and mRNA expressions were examined by polymerase chain reaction (PCR). Immunofluorescence assay was used to study EPAS1 protein expression. In phaeochromocytomas, 12% (n = 7/57) of patients had mutations in the EPAS1 sequence, which includes two novel mutations (c.1091A>T; p.Lys364Met and c.1129A>T; p.Ser377Cys). Contrastingly, in paragangliomas, 7% (n = 1/14) of patients had EPAS1 mutations and only the c.1091A>T; p.Lys364Met mutation was detected. In silico analysis revealed that the p.Lys364Met mutation has pathological potential based on the functionality of the protein, whereas the p.Ser377Cys mutation was predicted to be neutral or tolerated. The majority of the patients had EPAS1 DNA amplification (79%; n = 56/71) and 53% (n = 24/45) patients shown mRNA overexpression. Most of the patients with EPAS1 mutations exhibited aberrant DNA changes, mRNA and protein overexpression. In addition, these alterations of EPAS1 were associated with tumour weight and location. Thus, the molecular dysregulation of EPAS1 could play crucial roles in the pathogenesis of phaeochromocytomas and paragangliomas.
Novel Regulators of Sugar-Mediated Lateral Root Development in Arabidopsis thaliana
Authors: Li Jinzhu , Wang Bingxin , Zhu Xinxing , Li Rong , Fu Jing , Cui Hongchang
Published: October 2020

Lateral root development is a complex process regulated by numerous factors. An important role for sugar in lateral root development has been known for a while, but the underlying molecular basis still remains unclear. In this study, we first showed that WOX7, a sugar-inducible negative regulator of lateral root development, acts downstream of the glucose sensor HXK1. Using a transgenic line homozygous for a transgene expressing GFP under the control of the WOX7 promoter, we next performed a genetic screen to identify additional genes in this development pathway. A number of mutants with altered level of WOX7 expression were recovered, and two with increased WOX7 expression, named ewe-1 and ewe-2 (for Enhanced WOX7 Expression), were further characterized. Both mutants manifest delayed lateral root development, and genetic analysis indicates that single recessive mutations are responsible for the observed phenotypes. The mutations were then located to similar regions on chromosome 2 by marker-assisted analyses, and candidate genes were identified through whole genome sequencing. The significance and limitations of this work are discussed.