bluuebunny/crossref_metadata_2025 huggingface dataset:
Recovery of Flexible Polyurethane Foam Waste for Efficient Reuse in Industrial Formulations
Authors: Kiss Gabriel , Rusu Gerlinde , Peter Francisc , Tănase Ionuț , Bandur Geza
Published: July 2020

Ester polyurethane (PU) foam waste was reacted at atmospheric pressure in an autoclave and using microwaves with diethylene glycol (DEG) at different PU/DEG ratios in the presence of diethanolamine as a catalyst to find the glycolysis conditions that allow for the improved recovery of the PU foam waste and enable the recycling of the whole glycolysis product in foam formulations suitable for industrial application. The recycled polyol was characterized by dynamic viscosity, hydroxyl number, water content, and density, while thermal stability was assessed using thermogravimetric analysis. In the PU foam formulation, 1% and 5% of the glycolyzed material was reused. The relationship between the reuse level of the recycled polyol and the physical properties of the foam was thoroughly investigated. It was observed that both hardness and air flow decreased with increasing recycled polyol content, particularly for the polyester type foam, while tensile strength and compression strength increased. Depending on the amount of recycled polyol and catalyst used, polyether-based foams could be obtained with a low air permeability, needed in special applications as sealed foams, or with higher air permeability desirable for comfort PU foams. The results open the way for further optimization studies of industrial polyurethane foam formulations using a glycolysis process without any separation stage.
Evaluation of Immobilization of Selected Peat-Isolated Yeast Strains of the Species Candida albicans and Candida subhashii on the Surface of Artificial Support Materials Used for Biotrickling Filtration
Authors: Marycz Milena , Brillowska-Dąbrowska Anna , Gębicki Jacek
Published: July 2020

The paper describes the process of n-butanol abatement by unicellular fungi, able to deplete n-butanol content in gas, by using n-butanol as source of carbon. Isolated and identified fungi species Candida albicans and Candida subhashii were subjected to a viability process via assimilation of carbon from hydrophilic and hydrophobic compounds. The isolates, which exhibited the ability to assimilate carbon, were immobilized on four different types of artificial support materials used for biotrickling filtration. Application of optical microscopy, flow cytometry and the tests employing propidium iodide and annexin V revealed viability of the fungi isolated on support materials’ surfaces at the average level of 95%. The proposed method of immobilization and its evaluation appeared to be effective, cheap and fast. Based on performed comparative analyses, it was shown that polyurethane foam and Bialecki rings (25 × 25) could be attractive support materials in biotrickling filtration.
Oxidant–Antioxidant Status in Canine Multicentric Lymphoma and Primary Cutaneous Mastocytoma
Authors: Cucchi Andrea , Ramoni Roberto , Basini Giuseppina , Bussolati Simona , Quintavalla Fausto
Published: July 2020

Oxidative stress is a prominent event in several acute and chronic diseases including neoplasia. Although its direct involvement in carcinogenesis still remains to be clearly defined, a deeper knowledge of oxidative stress in oncologic patients could help to monitor their clinical outcome and to develop new therapeutic approaches. Therefore, the present study was undertaken to explore redox status in blood of neoplastic dogs affected either by multicentric lymphoma or by primary cutaneous mastocytoma. Superoxide anion (O2 •−), nitric oxide (NO) and hydroperoxides (ROOH) were measured. Detoxifying enzyme superoxide dismutase (SOD) and total non-enzymatic antioxidant capacity (ferric reducing-antioxidant power (FRAP)) were assessed. The oxidative stress index (OSi) both for enzymatic (OSiE) and non-enzymatic (OSiNE) scavengers were evaluated. Both pathologies, showed a reduced NO generation, while O2 •− levels were decreased only in mastocytoma. The oxidative stress indexes showed a significant decrease in mastocytoma patients, only for OSiE.
Accelerated Solvent Extraction as a Green Tool for the Recovery of Polyphenols and Pigments from Wild Nettle Leaves
Authors: Repajić Maja , Cegledi Ena , Kruk Valentina , Pedisić Sandra , Çınar Fırat , Bursać Kovačević Danijela , Žutić Ivanka , Dragović-Uzelac Verica
Published: July 2020

This study aimed to investigate the performance of accelerated solvent extraction (ASE) as a green approach for the recovery of polyphenols and pigments from wild nettle leaves (NL). ASE was operated at different temperatures (20, 50, 80 and 110 °C), static times (5 and 10 min) and cycle numbers (1–4) using ethanol (96%) as an extraction solvent. In order to compare the efficiency of ASE, ultrasound assisted extraction (UAE) at 80 °C for 30 min was performed as a referent. Polyphenol and pigment analyses were carried out by HPLC and antioxidant capacity was assessed by ORAC. Seven polyphenols from subclasses of hydroxycinnamic acids and flavonoids, along with chlorophylls a and b and their derivatives and six carotenoids and their derivatives were identified and quantified. Chlorogenic acid was the most abundant polyphenol and chlorophyll a represented the dominant pigment. ASE conditions at 110 °C/10 min/3 or 4 cycles proved to be the optimal for achieving the highest yields of analyzed compounds. In comparison with UAE, ASE showed better performance in terms of yields and antioxidants recovery, hence delivering extract with 60% higher antioxidant capacity. Finally, the potential of NL as a functional ingredient from natural sources can be successfully accessed by ASE.
Statistical Optimization by the Response Surface Methodology of Direct Recycled Aluminum-Alumina Metal Matrix Composite (MMC-AlR) Employing the Metal Forming Process
Authors: Ahmad Azlan , Lajis Mohd Amri , Yusuf Nur Kamilah , Ab Rahim Syaiful Nizam
Published: July 2020

In this study, the response surface methodology (RSM) and desirability function (DF) were utilized to optimize the recycling conditions of aluminum (AA6061) chips, in the presence of particulate alumina (Al2O3), to obtain a metal matrix composite of recycled aluminum (MMC-AlR) using hot press forging processes. The effects of temperature (430–530 °C) and holding time (60–120 min) were investigated. The introduction of 2.0 wt. % of Al2O3 to the aluminum matrix was based on preliminary research and some pilot tests. This study employed the 2k factorial design of experiments that should satisfy the operating temperatures (T) of 430 °C and 530 °C with holding times (t) of 60 min and 120 min. The central composite design (CCD) was utilized for RSM with the axial and center point to evaluate the responses to the ultimate tensile strength (UTS), elongation to failure (ETF), and microhardness (MH). Based on RSM, with the desirability of 97.6%, the significant parameters T = 530 °C and t = 120 min were suggested to yield an optimized composite performance with UTS = 317.99 MPa, ETF = 20.45%, and MH = 86.656 HV. Three confirmation runs were performed based on the suggested optimum parameters, and the error revealed was less than 25%. The mathematical models suggested by RSM could adequately describe the MMC-AlR responses of the factors being investigated.
New Insights on the Estimation of the Anaerobic Biodegradability of Plant Material: Identifying Valuable Plants for Sustainable Energy Production
Authors: Pabón-Pereira Claudia P. , Hamelers H. V. M. , Matilla Irene , van Lier Jules B.
Published: July 2020

Based on fifteen European plant species, a statistical model for the estimation of the anaerobic biodegradability of plant material was developed. We show that this new approach represents an accurate and cost-effective method to identify valuable energy plants for sustainable energy production. In particular, anaerobic biodegradability (Bo) of lignocellulosic material was empirically found to be related to the amount of cellulose plus lignin, as analytically assessed by the van Soest method, i.e., the acid detergent fiber (ADF) value. Apart from being theoretically meaningful, the ADF-based empirical model requires the least effort compared to the other four proposed conceptual models proposed, as individual fractions of cellulose, hemicellulose, and lignin do not need to be assessed, which also enhances the predictive accuracy of the model’s estimation. The model’s results showed great predictability power, allowing us to identify interesting crops for sustainable crop rotations. Finally, the model was used to predict Bo of 114 European plant samples that had been previously characterized by means of the van Soest method.
Reckoning the Dearth of Bioinformatics in the Arena of Diabetic Nephropathy (DN)—Need to Improvise
Authors: Oh Jae-Wook , Muthu Manikandan , Haga Steve W. , Anthonydhason Vimala , Paul Piby , Chun Sechul
Published: July 2020

Diabetic nephropathy (DN) is a recent rising concern amongst diabetics and diabetologist. Characterized by abnormal renal function and ending in total loss of kidney function, this is becoming a lurking danger for the ever increasing population of diabetics. This review touches upon the intensity of this complication and briefly reviews the role of bioinformatics in the area of diabetes. The advances made in the area of DN using proteomic approaches are presented. Compared to the enumerable inputs observed through the use of bioinformatics resources in the area of proteomics and even diabetes, the existing scenario of skeletal application of bioinformatics advances to DN is highlighted and the reasons behind this discussed. As this review highlights, almost none of the well-established tools that have brought breakthroughs in proteomic research have been applied into DN. Laborious, voluminous, cost expensive and time-consuming methodologies and advances in diagnostics and biomarker discovery promised through beckoning bioinformatics mechanistic approaches to improvise DN research and achieve breakthroughs. This review is expected to sensitize the researchers to fill in this gap, exploiting the available inputs from bioinformatics resources.
Numerical Study of Shear Banding in Flows of Fluids Governed by the Rolie-Poly Two-Fluid Model via Stabilized Finite Volume Methods
Authors: Abuga Jade Gesare , Chinyoka Tiri
Published: July 2020

The flow of viscoelastic fluids may, under certain conditions, exhibit shear-banding characteristics that result from their susceptibility to unusual flow instabilities. In this work, we explore both the existing shear banding mechanisms in the literature, namely; constitutive instabilities and flow-induced inhomogeneities. Shear banding due to constitutive instabilities is modelled via either the Johnson–Segalman or the Giesekus constitutive models. Shear banding due to flow-induced inhomogeneities is modelled via the Rolie–Poly constitutive model. The Rolie–Poly constitutive equation is especially chosen because it expresses, precisely, the shear rheometry of polymer solutions for a large number of strain rates. For the Rolie–Poly approach, we use the two-fluid model wherein the stress dynamics are coupled with concentration equations. We follow a computational analysis approach via an efficient and versatile numerical algorithm. The numerical algorithm is based on the Finite Volume Method (FVM) and it is implemented in the open-source software package, OpenFOAM. The efficiency of our numerical algorithms is enhanced via two possible stabilization techniques, namely; the Log-Conformation Reformulation (LCR) and the Discrete Elastic Viscous Stress Splitting (DEVSS) methodologies. We demonstrate that our stabilized numerical algorithms accurately simulate these complex (shear banded) flows of complex (viscoelastic) fluids. Verification of the shear-banding results via both the Giesekus and Johnson-Segalman models show good agreement with existing literature using the DEVSS technique. A comparison of the Rolie–Poly two-fluid model results with existing literature for the concentration and velocity profiles is also in good agreement.
Effects of Blueberry and Black Carrot Extracts Addition on Antioxidant Properties and Protein-Precipitating Capacity of Ultrasound-Treated Cider
Authors: Brezan Boris , Bădărău Carmen Liliana , Woinaroschy Alexandru
Published: July 2020

The results presented in this study highlight the level of total phenolic content (TPC), total flavonoid content (TFC) and protein-precipitating capacity (PPC) correlated with the antioxidant capacity of new cider varieties enriched with valuable bio compounds by the addition of blueberry and black carrot extracts. The cider variants were treated with ultrasound (constant frequency of 20 kHz) at 20%, 30% and 40% amplitude (A) for two, five or seven minutes. TPC determination was performed by Folin–Ciocâlteu method and TFC was determined by an aluminum chloride colorimetric method. The antioxidant capacity was determined by ferric-reducing antioxidant power assay (FRAP), ABTS (2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)) assay and DPPH (2,2-diphenyl-1-picrylhydrazyl) radical scavenging activity. The results showed that the antioxidant performance indicators (FRAP, ABTS and DPPH) were positively correlated with the TPC and TFC of the ultrasound-treated cider variants, suggesting that the content of these bio compounds may be improved by the treatments applied. The highest mean values for TPC and TFC were found in the cider variant enriched with black carrot extract (0.3%, v/v), subsequently ultrasound-treated (A20%, five minutes) Conclusively, the extracts used in this study could improve the antioxidant capacity of the cider, especially in case of variants ultrasound-treated.
A Workflow Incorporating an Artificial Neural Network to Predict Subsurface Porosity for CO2 Storage Geological Site Characterization
Authors: Koperna George , Jonsson Hunter , Ness Richie , Cyphers Shawna , MacGregor JohnRyan
Published: July 2020

The large scale and complexity of Carbon, Capture, Storage (CCS) projects necessitates time and cost saving strategies to strengthen investment and widespread deployment of this technology. Here, we successfully demonstrate a novel geologic site characterization workflow using an Artificial Neural Network (ANN) at the Southeast Regional Carbon Anthropogenic Test in Citronelle, Alabama. The Anthropogenic Test Site occurs within the Citronelle oilfield which contains hundreds of wells with electrical logs that lack critical porosity measurements. Three new test wells were drilled at the injection site and each well was paired with a nearby legacy well containing vintage electrical logs. The test wells were logged for measurements of density porosity and cored over the storage reservoir. An Artificial Neural Network was developed, trained, and validated using patterns recognized between the between vintage electrical logs and modern density porosity measurements at each well pair. The trained neural network was applied to 36 oil wells across the Citronelle Field and used to generate synthetic porosities of the storage reservoir and overlying stratigraphy. Ultimately, permeability of the storage reservoir was estimated using a combination of synthetic porosity and an empirically derived relationship between porosity and permeability determined from core.
Comparative Study of a Compression–Absorption Cascade System Operating with NH3-LiNO3, NH3-NaSCN, NH3-H2O, and R134a as Working Fluids
Authors: Herrera-Romero JV , Colorado-Garrido Dario
Published: July 2020

This research presents a comprehensive bibliographic review from 2006 through 2020 about the state of the art of the compression–absorption cascade systems for refrigeration. In consequence of this review, this research identifies the significant development of systems that consider lithium bromide as a working fluid; however, the use of other working fluids has not been developed. This study is motivated toward the development of a parametric analysis of the cascade system using NH3-LiNO3, NH3-NaSCN and NH3-H2O in the absorption cycle and R134a in the compression cycle. In this study, the effect of the heat source temperature, condensation temperature in the compression cycle, the use of heat exchangers in the system (also known as economizers) and their contribution to the coefficient of performance is deepened numerically. The economizers evaluated are the following: an internal heat exchanger, a refrigerant heat exchanger, a solution refrigerant heat exchanger, and a solution heat exchanger. Mass and energy balance equations—appropriate equations to estimate the thermophysical properties of several refrigerant–absorbent pairs—were used to develop a thermodynamic model. The studied heat source temperature range was from 355 to 380 K, and the studied condensation temperature range in the compression cycle was from 281 to –291 K; additionally, the importance of each economizer on the coefficient of performance was numerically estimated. In this way, NH3-NaSCN solution in the absorption cycle and R134a in the compression cycle provided promising numerical results with the highest COPs (coefficient of performance).
Beastly Boasts and Apocalyptic Affects: Reading Revelation in a Time of Trump and a Time of Plague
Authors: Moore Stephen D.
Published: July 2020

Waxing “biblical,” Donald Trump has described the COVID-19 pandemic as a “plague.” In a different but related register, millions of Christians worldwide have interpreted the pandemic as one of the eschatological plagues prophesied in the Book of Revelation. This article appropriates the reading tactics of Gilles Deleuze and Félix Guattari, together with the resources of affect theory, to connect the Book of Revelation with both the Trump phenomenon and the COVID-19 pandemic. Specifically, the article attempts to relate Revelation’s Beast to Trump (to unleash the Beast against Trump) non-eschatologically, in a non-representationalist reading strategy, and to analyze how Trump has manipulated the pandemic for his post-ideological ends.
The Soil Moisture during Dry Spells Model and Its Verification
Authors: Biniak-Pieróg Małgorzata , Chalfen Mieczysław , Żyromski Andrzej , Doroszewski Andrzej , Jóźwicki Tomasz
Published: July 2020

The objective of this study was the development and verification of a model of soil moisture decrease during dry spells—SMDS. The analyses were based on diurnal information of the occurrence of atmospheric precipitation and diurnal values of soil moisture under a bare soil surface, covering the period of 2003–2019, from May until October. A decreasing exponential trend was used for the description of the rate of moisture decrease in six layers of the soil profile during dry spells. The least squares method was used to determine, for each dry spell and soil depth, the value of exponent α , which described the rate of soil moisture decrease. Data from the years 2003–2015 were used for the identification of parameter α of the model for each of the layers separately, while data from 2016–2019 were used for model verification. The mean relative error between moisture values measured in 2016–2019 and the calculated values was 3.8%, and accepted as sufficiently accurate. It was found that the error of model fitting decreased with soil layer depth, from 8.1% for the surface layer to 1.0% for the deepest layer, while increasing with the duration of the dry spell at the rate of 0.5%/day. The universality of the model was also confirmed by verification made with the use of the results of soil moisture measurements conducted in the years 2009–2019 at two other independent locations. However, it should be emphasized that in the case of the surface horizon of soil, for which the process of soil drying is a function of factors occurring in the atmosphere, the developed model may have limited application and the obtained results may be affected by greater errors. The adoption of calculated values of coefficient α as characteristic for the individual measurement depths allowed calculation of the predicted values of moisture as a function of the duration of a dry spell, relative to the initial moisture level adopted as 100%. The exponential form of the trend of soil moisture changes in time adopted for the analysis also allowed calculation of the duration of a hypothetical dry spell t, after which soil moisture at a given depth drops from the known initial moisture θ0 to the predicted moisture θ. This is an important finding from the perspective of land use.
CloudScout: A Deep Neural Network for On-Board Cloud Detection on Hyperspectral Images
Authors: Giuffrida Gianluca , Diana Lorenzo , de Gioia Francesco , Benelli Gionata , Meoni Gabriele , Donati Massimiliano , Fanucci Luca
Published: July 2020

The increasing demand for high-resolution hyperspectral images from nano and microsatellites conflicts with the strict bandwidth constraints for downlink transmission. A possible approach to mitigate this problem consists in reducing the amount of data to transmit to ground through on-board processing of hyperspectral images. In this paper, we propose a custom Convolutional Neural Network (CNN) deployed for a nanosatellite payload to select images eligible for transmission to ground, called CloudScout. The latter is installed on the Hyperscout-2, in the frame of the Phisat-1 ESA mission, which exploits a hyperspectral camera to classify cloud-covered images and clear ones. The images transmitted to ground are those that present less than 70% of cloudiness in a frame. We train and test the network against an extracted dataset from the Sentinel-2 mission, which was appropriately pre-processed to emulate the Hyperscout-2 hyperspectral sensor. On the test set we achieve 92% of accuracy with 1% of False Positives (FP). The Phisat-1 mission will start in 2020 and will operate for about 6 months. It represents the first in-orbit demonstration of Deep Neural Network (DNN) for data processing on the edge. The innovation aspect of our work concerns not only cloud detection but in general low power, low latency, and embedded applications. Our work should enable a new era of edge applications and enhance remote sensing applications directly on-board satellite.
Miniaturised Infrared Spectrophotometer for Low Power Consumption Multi-Gas Sensing
Authors: Muhiyudin Manu , Hutson David , Gibson Desmond , Waddell Ewan , Song Shigeng , Ahmadzadeh Sam
Published: July 2020

Concept, design and practical implementation of a miniaturized spectrophotometer, utilized as a mid-infrared-based multi gas sensor is described. The sensor covers an infrared absorption wavelength range of 2.9 to 4.8 um, providing detection capabilities for carbon dioxide, carbon monoxide, nitrous oxide, sulphur dioxide, ammonia and methane. A lead selenide photo-detector array and customized MEMS-based micro-hotplate are used as the detector and broadband infrared source, respectively. The spectrophotometer optics are based on an injection moulded Schwarzschild configuration incorporating optical pass band filters for the spectral discrimination. This work explores the effects of using both fixed-line pass band and linear variable optical filters. We report the effectiveness of this low-power-consumption miniaturized spectrophotometer as a stand-alone single and multi-gas sensor, usage of a distinct reference channel during gas measurements, development of ideal optical filters and spectral control of the source and detector. Results also demonstrate the use of short-time pulsed inputs as an effective and efficient way of operating the sensor in a low-power-consumption mode. We describe performance of the spectrometer as a multi-gas sensor, optimizing individual component performances, power consumption, temperature sensitivity and gas properties using modelling and customized experimental procedures.
Broadband Electrical Sensing of a Live Biological Cell with In Situ Single-Connection Calibration
Authors: Ma Xiao , Du Xiaotian , Li Lei , Ladegard Caroline , Cheng Xuanhong , Hwang James C. M.
Published: July 2020

Single-connection in situ calibration using biocompatible solutions is demonstrated in single-cell sensing from 0.5 to 9 GHz. The sensing is based on quickly trapping and releasing a live cell by dielectrophoresis on a coplanar transmission line with a little protrusion in one of its ground electrodes. The same transmission line is used as the calibration standard when covered by various solutions of known permittivities. The results show that the calibration technique may be precise enough to differentiate cells of different nucleus sizes, despite the measured difference being less than 0.01 dB in the deembedded scattering parameters. With better accuracy and throughput, the calibration technique may allow broadband electrical sensing of live cells in a high-throughput cytometer.
Forecasting the Concentration of Particulate Matter in the Seoul Metropolitan Area Using a Gaussian Process Model
Authors: Jang JoonHo , Shin Seungjae , Lee Hyunjin , Moon Il-Chul
Published: July 2020

Recently, the population of Seoul has been affected by particulate matter in the atmosphere. This problem can be addressed by developing an elaborate forecasting model to estimate the concentration of fine dust in the metropolitan area. We present a forecasting model of the fine dust concentration with an extended range of input variables, compared to existing models. The model takes inputs from holistic perspectives such as topographical features on the surface, chemical sources of the fine dusts, traffic and the human activities in sub-areas, and meteorological data such as wind, temperature, and humidity, of fine dust. Our model was evaluated by the index-of-agreement (IOA) and the root mean-squared error (RMSE) in predicting PM2.5 and PM10 over three subsequent days. Our model variations consist of linear regressions, ARIMA, and Gaussian process regressions (GPR). The GPR showed the best performance in terms of IOA that is over 0.6 in the three-day predictions.
A 3D Scanning System for Inverse Analysis of Moist Biological Samples: Design and Validation Using Tendon Fascicle Bundles
Authors: Dabrowska Sylwia , Ekiert Martyna , Wojcik Kaja , Kalemba Marek , Mlyniec Andrzej
Published: July 2020

In this article, we present the design and validation of a non-contact scanning system for the development of a three-dimensional (3D) model of moist biological samples. Due to the irregular shapes and low stiffness of soft tissue samples, the use of a non-contact, reliable geometry scanning system with good accuracy and repeatability is required. We propose a reliable 3D scanning system consisting of a blue light profile sensor, stationary and rotating frames with stepper motors, gears and a five-phase stepping motor unit, single-axis robot, control system, and replaceable sample grips, which once mounted onto the sample, are used for both scanning and mechanical tests. The proposed system was validated by comparison of the cross-sectional areas calculated based on 3D models, digital caliper, and vision-based methods. Validation was done on regularly-shaped samples, a wooden twig, as well as tendon fascicle bundles. The 3D profiles were used for the development of the 3D computational model of the sample, including surface concavities. Our system allowed for 3D model development of samples with a relative error of less than 1.2% and high repeatability in approximately three minutes. This was crucial for the extraction of the mechanical properties and subsequent inverse analysis, enabling the calibration of complex material models.
Performance Degradation Prediction Based on a Gaussian Mixture Model and Optimized Support Vector Regression for an Aviation Piston Pump
Authors: Lu Chuanqi , Wang Shaoping
Published: July 2020

Performance degradation prediction plays a key role in realizing aviation pump health management and condition-based maintenance. Thus, this paper proposes a new approach that combines a Gaussian mixture model (GMM) and optimized support vector regression (SVR) to predict aviation pumps’ degradation processes based on the pump outlet pressure signals. Different from other feature extraction methods in which the information of intrinsic mode functions (IMFs) is not fully utilized, some useful IMF components are firstly chosen, and the corresponding multi-domain features are extracted from each selected component. Considering that it is not the case that all features are equally sensitive to degradation assessment, PCA is used to select more sensitive degradation features. Since the distribution of these extracted features is a stochastic process in feature space, meanwhile, self-information quantity can describe the uncertainty of system by measuring the average information quantity contained in the probability distribution, self-information quantity based on GMM is defined as degradation index (DI) to describe the degradation degree of the pump quantitatively. Finally, an SVR model is constructed to predict the degradation status of the pump. To achieve higher prediction accuracy, phase space reconstruction theory is first employed to determine the number of the inputs of the SVR model, then a new method combining particle swarm optimization (PSO) with grid search (GS) is developed to optimize the parameters of the SVR model. Finally, both the online data and historical data are utilized for the construction of the SVR model, respectively. The effectiveness of the proposed approach is validated by full life cycle data collected from an aviation pump test rig. The results demonstrate that the DI extracted from pump outlet pressure signals can effectively identify and track the current deterioration stage, and the established SVR model has better prediction ability when compared with previously published methods.
Real-Time and Accurate Drone Detection in a Video with a Static Background
Authors: Seidaliyeva Ulzhalgas , Akhmetov Daryn , Ilipbayeva Lyazzat , Matson Eric T.
Published: July 2020

With the increasing number of drones, the danger of their illegal use has become relevant. This has necessitated the creation of automatic drone protection systems. One of the important tasks solved by these systems is the reliable detection of drones near guarded objects. This problem can be solved using various methods. From the point of view of the price–quality ratio, the use of video cameras for a drone detection is of great interest. However, drone detection using visual information is hampered by the large similarity of drones to other objects, such as birds or airplanes. In addition, drones can reach very high speeds, so detection should be done in real time. This paper addresses the problem of real-time drone detection with high accuracy. We divided the drone detection task into two separate tasks: the detection of moving objects and the classification of the detected object into drone, bird, and background. The moving object detection is based on background subtraction, while classification is performed using a convolutional neural network (CNN). The experimental results showed that the proposed approach can achieve an accuracy comparable to existing approaches at high processing speed. We also concluded that the main limitation of our detector is the dependence of its performance on the presence of a moving background.
The Culture of Violent Talk: An Interpretive Approach
Authors: Simi Pete , Windisch Steven
Published: July 2020

One of the defining characteristics of extremist movements is the adherence to an ideology highly antagonistic to the status quo and one that permits or explicitly promotes the use of violence to achieve stated goals and to address grievances. For members of extremist groups, talk is one of the most concrete manifestations of how adherents communicate their ideas to each other and the general public. These discussions, however, do not necessarily involve a direct correspondence between words and future behavior. To better understand the culture of violent talk, we investigate how white supremacist extremists use these discussions as a rhetorical device that provides them with a sense of doing and an opportunity to express their frustrations and anger. Our analysis is grounded primarily in the ethnographic data we collected on a variety of US white supremacists since 1997. Our investigation offers important insight regarding the interactional qualities of extremist culture as well as policy implications regarding the assessment process.
The Multi-Method Tool ‘PAST’ for Evaluating Cultural Routes in Historical Cities: Evidence from Cagliari, Italy
Authors: Garau Chiara , Annunziata Alfonso , Yamu Claudia
Published: July 2020

Thematic paths are a central aspect of urban policies for cultural heritage valorization. In fact, thematic paths are central spatial features for structuring the image of a historical landscape. Hence, this study proposes the cultural paths assessment tool (PAST) as a methodological framework for individuating a network of routes connecting cultural heritage components and for assessing their usefulness. Usefulness is herein defined as the potential of a street network to support the meaningful experience of a historical urban landscape. PAST combines space syntax techniques, a geographic information system, and a qualitative analysis within a multi-criteria analysis framework for addressing four aspects of connecting cultural heritage components, including: (i) the individuation of relevant assets; (ii) the identification of the sub-network of most central street segments; (iii) the definition of the street network of thematic routes; (iv) the assessment of the usefulness of thematic paths, according to the criteria of usability, imageability, and accessibility. The proposed methodology, applied to the historical district of Marina in the city of Cagliari in Italy, supports planning and design processes in two ways: (1) by identifying street segments and squares comprising a network of thematic routes; (2) by individuating high-leverage interventions for improving the usefulness of thematic routes. Consequently, the proposed study addresses the need to establish methodologies and analytic tools that support decision making processes for conserving, managing, and valorizing historic urban landscapes.
Future Energy and Environmental Implications of Electric Vehicles in Palestine
Authors: Hassouna Fady M. A , Al-Sahili Khaled
Published: July 2020

During the last two decades, problems related to high-energy consumption and greenhouse gas (GHG) emissions by the transportation sector have arisen. Therefore, several alternatives have been investigated, in order to reduce the dependence on the conventional fuels that are used by land transportation modes. One of these promising alternatives is the electric vehicles (EVs), which seem to be the future replacement for conventional vehicles. Thus, this study aims to quantify the energy and the environmental implications of EVs in Palestine in 2030, considering that the current percentage of EVs is almost 0%. In this study, the needed parameters related to the number of vehicles and energy costs by source in Palestine were collected. Then, several prediction models have been developed in order to determine the energy and environmental implications of EVs in 2030, considering that 10% of conventional vehicles could be replaced by EV during the next 10 years (2020–2030). The results have showed that this could save USD 464.31 million in operating energy costs during 2030 (one year of saving). More specifically, this number is almost equal to 3.18% of the gross domestic product (GDP) of Palestine in 2018. Furthermore, significant amounts of GHG emissions could be reduced. The reduction (during 2030) in NH4, N2O, and CO2 emissions could be around 10.51%, 10%, and 6.86%, respectively.
I Can’t Go to Work Tomorrow! Work-Family Policies, Well-Being and Absenteeism
Authors: Medina-Garrido José Aurelio , Biedma-Ferrer José María , Sánchez-Ortiz Jaime
Published: July 2020

Among the main causes of absenteeism are health problems, emotional problems, and inadequate work-family policies (WFP). This paper analyses the impact of the existence and accessibility of WFP on work absenteeism, by considering the mediating role of the well-being, which includes emotional as well as physical or health problems, that is generated by these policies. We differentiate between the existence of the WFP and its accessibility, as the mere existence of the WFP in an organisation is not enough. Additionally, workers must be able to access these policies easily and without retaliation of any kind. The model includes the hierarchy and the gender as moderating variables. To test the proposed hypotheses, a structural equation model based on the partial least squares structural equation modelling (PLS-SEM) approach is applied to a sample of employees in the service sector in Spain. On the one hand, the findings show that the existence of WFP has no direct effect on absenteeism; however, accessibility to these policies does have a direct effect on absenteeism. On the other hand, both the existence and accessibility of WFP have positive direct effects on emotional well-being. In addition, emotional well-being is positively related to physical well-being which, in turn, promotes a reduction in absenteeism. Finally, significant differences in the relationship between the existence of WFP and emotional well-being confirm the special difficulty of female managers in reconciling family life and work life.
Environmental Impacts: Local Perspectives of Selected Mining Edge Communities in Sierra Leone
Authors: Mabey Prince T. , Li Wei , Sundufu Abu J. , Lashari Akhtar H.
Published: July 2020

Despite its contributions to the development of the country, the mining sector in Sierra Leone, has been attributed to a multitude of impacts on the environment. This article focuses on assessing the environmental impacts of mining in mining edge communities in Sierra Leone. A survey of 360 people from three mining edge communities (Sierra Rutile Limited (SRL), Bonthe district; Octea Mining Company (OMC), Kono district and Sierra Leone Mining Company (SLM), Port Loko district) was conducted. Key informant interviews, focus groups, and secondary data sources - Government policies and regulatory documents, government’s Mines Department annual reports-provided data for this article. Data were analyzed using the Statistical Analysis System with a mean separation done at α = 0.05 (SAS version 9.4). As a result of mining operations, the rates of deforestation, land degradation and destruction of farmlands, inadequate availability of clean water, poor air quality and noise pollution were the main impacts exacerbated by rutile, iron ore and diamond mining. Strategies as recommended by the local communities to be put in place, to restore ecological function in the mining edge communities include, the Environmental Protection Agency (EPA), the Mines and Mineral Agency, and other responsible authorities addressing weakness in mining and environmental policies, thereby strengthening enforcement and monitoring regulations relating to mining operations; and companies embarking on rehabilitation, reclamation, and restoration measures to ensure environmental sustainability.
Sustainability Practices and Stability in the Insurance Industry
Authors: Chiaramonte Laura , Dreassi Alberto , Paltrinieri Andrea , Piserà Stefano
Published: July 2020

While the concept of sustainability is receiving growing attention from investors, firms, regulators, and researchers, little is known about its role in the insurance industry. As institutional investors and risk-absorbers from businesses and individuals, insurers adopt an operating model that is more inclined to target long-term objectives; they should be among the firms benefiting the most from engaging in sustainable practices. The existing literature provides evidence of the positive impact of sustainability on commercial stability, but this is the first study to examine this relationship for the insurance sector. Focusing on American listed insurers, we found that sustainability, proxied by Environmental, Social and Governance (ESG) scores, enhances the stability of insurers, and that this relationship is driven by environmental and social dimensions. We did not observe a significant contribution from the governance dimension. Finally, we found a stronger association for life insurers. Our results are shown to be robust to endogeneity, enterprise heterogeneity and potential sample selection biases.
Meeting Cyber Age Needs for Governance in a Changing Global Order
Authors: Young Oran R. , Yang Jian , Guttman Dan
Published: July 2020

The advent of the cyber age has created a world in which digital systems, operating on their own and interacting with more conventional material or physical systems, have become an increasingly prominent feature of the landscape of human affairs. This development, affecting every aspect of human life, has generated a class of increasingly critical needs for governance that are difficult to address effectively within the confines of the current global order in which sovereign states compete to maximize their influence in the absence of any overarching public authority. These needs include concerns associated with the management of powerful digital technologies (e.g., artificial intelligence, robotics, machine learning, blockchain technology, the internet of things, and big data) as well as problems relating to the use of these technologies by many actors to exercise influence from the level of the individual (e.g., identity theft) to the level of international society (e.g., foreign interventions in national electoral systems). The challenge of meeting these needs prompts an analysis of processes leading to change in the prevailing global order, energized at least in part by the growing role of the digital systems of the cyber age. Our analysis includes both Western perspectives highlighting changes in the identity and behavior of key actors and Chinese perspectives emphasizing the spread of social narratives embedded in the concepts of tianxia and gongsheng. While it is premature to make explicit predictions, we conclude with some observations about the most important trends to watch regarding efforts to meet cyber age needs for governance, and we note the connections between these developments and the overarching challenge of fulfilling the suite of goals commonly associated with the idea of sustainable development.
Time Series Analysis for the Dynamic Relationship between an Enterprise’s Business Growth and Carbon Emission in Taiwan
Authors: Ding Yu-Jia , Wu Pi-Chu , Lian Yu-Hui
Published: July 2020

Since the Paris Agreement came into effect in 2016, governments worldwide have established goals for future carbon emission reduction. Enterprises and governments have begun to pay attention to the management of carbon emission. This study explored the dynamic relationship between business growth and carbon emission performance by constructing and using a time series model to predict the trend of carbon emission. The time series method (ADF unit root test, cointegration test and VAR model etc.) was adopted to investigate 805 companies listed on the Taiwan Stock Exchange from 2012 to 2017 as the sample of this study. The carbon emission performance variables include: total carbon emission, annual increase of carbon emission, and annual increase rate of carbon emission. The business growth variables include: growth rate, stability of growth, and years of establishment. The results showed a long-term dynamic relationship between business growth and carbon emission performance. Therefore, using the time series method can assist enterprises in developing green strategies, strengthen carbon emission prediction and management capacities, reduce operating costs and risks, and actively achieve the ideal of sustainable development.
The Statistical Damage Constitutive Model of the Mechanical Properties of Alkali-Resistant Glass Fiber Reinforced Concrete
Authors: Shi Xianzeng , Zhang Cong , Zhou Xingde
Published: July 2020

Alkali-resistant glass fiber reinforced concrete (AR-GFRC) has greatly improved in terms of tensile strength, toughness, durability, and reduction of cracking, which has been proven by testing. However, the constitutive relationship of fiber reinforced concrete under complicated stress represents a complex theoretical problem. In order to investigate the microscopic damage evolution and failure mechanism of AR-GFRC, the meso-statistical damage theory, microcontinuum theory, and composite material theory were considered, and uniaxial tensile tests of two types of AR-GFRC were conducted. A new damage variable expression of the AR-GFRC was proposed, and the stress-strain curve was redefined by considering the residual strength based on experimental fitting parameters and statistical parameters. A Weibull distribution was assumed and a statistical damage constitutive model was developed of the deformation process of the AR-GFRC while considering the residual strength effect; detailed calculation methods to determine the mechanical and statistical parameters of the concrete were developed. The validation results show that the theoretical stress-strain curve of the constitutive model is in good agreement with the experimental curve and the trend is consistent.
Durrmeyer-Type Generalization of Parametric Bernstein Operators
Authors: Kajla Arun , Mursaleen Mohammad , Acar Tuncer
Published: July 2020

In this paper, we present a Durrmeyer type generalization of parametric Bernstein operators. Firstly, we study the approximation behaviour of these operators including a local and global approximation results and the rate of approximation for the Lipschitz type space. The Voronovskaja type asymptotic formula and the rate of convergence of functions with derivatives of bounded variation are established. Finally, the theoretical results are demonstrated by using MAPLE software.
Biquaternionic Dirac Equation Predicts Zero Mass for Majorana Fermions
Authors: Nofech Avraham
Published: July 2020

A biquaternionic version of the Dirac Equation is introduced, with a procedure for converting four-component spinors to elements of the Pauli algebra. In this version, mass appears as a coefficient between the 4-gradient of a spinor and its image under an outer automorphism of the Pauli algebra. The charge conjugation operator takes a particulary simple form in this formulation and switches the sign of the mass coefficient, so that for a solution invariant under charge conjugation the mass has to equal zero. The multiple of the charge conjugation operator by the imaginary unit turns out to be a complex Lorentz transformation. It commutes with the outer automorphism, while the charge conjugation operator itself anticommutes with it, providing a second more algebraic proof of the main theorem. Considering the Majorana equation, it is shown that non-zero mass of its solution is imaginary.
On Certain Covering Properties and Minimal Sets of Bigeneralized Topological Spaces
Authors: Al Ghour Samer , Alhorani Abdullah
Published: July 2020

We introduce q-Lindelöf, u-Lindelöf, p-Lindelöf, s-Lindelöf, q-countably-compact, u-countably-compact, p-countably-compact, and s-countably-compact as new covering concepts in bigeneralized topological spaces via q-open sets and u-open sets in bigeneralized topological spaces. Relationships between them are studied. As two symmetries relationships, we show that q-Lindelöf and u-Lindelöf are equivalent concepts, and that q-countably-compact and u-countably-compact are equivalent concepts. We focus on continuity images of these covering properties. Finally, we define and investigate minimal q-open set, minimal u-open set, and minimal s-open sets as three new types of minimality in bigeneralized topological spaces.