bluuebunny/crossref_metadata_2025 huggingface dataset:
Sosyal Bilgiler Öğretmenliği Öğrencilerinin Kahramanmaraş’ın Milli Tarih İçerisindeki Rolü ile İlgili Görüşleri
Authors: KAYA Ahmet , YILDIRIM Sevda Gülşah
Published: March 2020

Çalışma bir devlet üniversitesinin Sosyal Bilgiler Öğretmenliği Bölümü öğrencilerinin Kahramanmaraş’ın milli tarih içerisindeki rolü ile ilgili görüşlerini belirlemek amacıyla yapılmıştır. Araştırmada genel tarama modeli benimsenmiştir. Araştırmanın evreni, 2019-2020 Eğitim-Öğretim döneminde Eğitim Fakültesi Sosyal Bilgiler Öğretmenliği programına kayıtlı toplam 143 öğrencidir. Çalışmanın örneklemini ise evreni temsil ettiği düşünülen ve basit seçkisiz örneklemeye göre belirlenen 94 öğrenci oluşturmaktadır. Veriler, araştırmacılar tarafından geliştirilen yazılı form ile toplanmıştır. Form, iki kısımdan oluşmaktadır. İlk kısımda hem katılımcıların demografik bilgilerini hem de Maraş’ın tarihi rolüne ilişkin bilgilerini belirleyen kısa cevaplı sorular; ikinci kısımda ise onların farkındalıklarını ortaya çıkarmak amaçlı yoruma dayanan uzun cevaplı sorular yer almaktadır. Kısa cevaplı sorular için frekans ve yüzde gibi betimsel istatistikler tercih edilirken yoruma dayalı sorularda soru içeriklerine bağlı kalınarak oluşturulmuş temalara göre analizler gerçekleştirilmiştir. Araştırma sonucunda öğrencilerin %53’ünün Maraş’ın kaç yılında işgal edildiğini, %75’inin Maraş’ın kimler tarafından işgal edildiğini, %57’sinin Maraş’ın işgalinin ne kadar sürdüğünü ‘bilmediği’; %81 oranında öğrencinin ise konuyla ilgili herhangi bir etkinliğe katılmadığı tespit edilmiştir. Bulguların tamamı değerlendirildiğinde, öğrencilerin neredeyse yarısının Maraş’ın kurtuluş mücadelesinin milli tarih içerisindeki rolünün önemine ilişkin bilgilerinin yetersiz ve farkındalıklarının zayıf olduğu sonucuna ulaşılmıştır.
Evaluate Safety Practices of Malaysian Public Universities by using Balanced Scorecard
Authors: Arjunan Lingaswaran , Habidin Nurul Fadly , Mohamad Yusof Mohamad Suwardi , Muniandy Rasikumari
Published: March 2020

The aim of this paper is to debate the concept of the balanced scorecard (BSC) and the way it will be used for evaluating the performance of safety practice in Malaysia public universities. This idea paper is especially supported secondary resources on the balanced scorecard published by other researchers. The approach of balanced scorecard model helps to the assessment of quality and safety practice of public universities. It helps public universities to create decisions and to enhance services. It translates the mission and strategy of a security practice into a system of performance indicators. A useful model is proposed that may be adapted with appropriate modifications to evaluate/managing safety practice and organizational performance of public universities in Malaysia. The study may help to those universities, who are seriously inquisitive about evaluating/managing internal safety practice, customer satisfaction, finance of universities and innovation and learning growth. Keywords: Balanced scorecard; Safety practice; Organizational performance; Malaysian public universities
Beyond Newton: A New Root-Finding Fixed-Point Iteration for Nonlinear Equations
Authors: Aggarwal Ankush , Pant Sanjay
Published: March 2020

Finding roots of equations is at the heart of most computational science. A well-known and widely used iterative algorithm is Newton’s method. However, its convergence depends heavily on the initial guess, with poor choices often leading to slow convergence or even divergence. In this short note, we seek to enlarge the basin of attraction of the classical Newton’s method. The key idea is to develop a relatively simple multiplicative transform of the original equations, which leads to a reduction in nonlinearity, thereby alleviating the limitation of Newton’s method. Based on this idea, we derive a new class of iterative methods and rediscover Halley’s method as the limit case. We present the application of these methods to several mathematical functions (real, complex, and vector equations). Across all examples, our numerical experiments suggest that the new methods converge for a significantly wider range of initial guesses. For scalar equations, the increase in computational cost per iteration is minimal. For vector functions, more extensive analysis is needed to compare the increase in cost per iteration and the improvement in convergence of specific problems.
About Granular Rough Computing—Overview of Decision System Approximation Techniques and Future Perspectives
Authors: Artiemjew Piotr
Published: March 2020

Granular computing techniques are a huge discipline in which the basic component is to operate on groups of similar objects according to a fixed similarity measure. The first references to the granular computing can be seen in the works of Zadeh in fuzzy set theory. Granular computing allows for a very natural modelling of the world. It is very likely that the human brain, while solving problems, performs granular calculations on data collected from the senses. The researchers of this paradigm have proven the unlimited possibilities of granular computing. Among other things, they are used in the processes of classification, regression, missing values handling, for feature selection, and as mechanisms of data approximation. It is impossible to quote all methods based on granular computing—we can only discuss a selected group of techniques. In the article, we have presented a review of recently developed granulation techniques belonging to the family of approximation algorithms founded by Polkowski—in the framework of rough set theory. Starting from the basic Polkowski’s standard granulation, we have described further developed by us concept dependent, layered, and epsilon variants, and our recent homogeneous granulation. We are presenting simple numerical examples and samples of research results. The effectiveness of these methods in terms of decision system size reduction and maintenance of the internal knowledge from the original data are presented. The reduction in the number of objects in our techniques while maintaining classification efficiency reaches 90 percent—for standard granulation with usage of a kNN classifier (we achieve similar efficiency for the concept-dependent technique for the Naive Bayes classifier). The largest reduction achieved in the number of exhaustive set of rules at the efficiency level to the original data are 99 percent—it is for concept-dependent granulation. In homogeneous variants, the reduction is less than 60 percent, but the advantage of these techniques is that it is not necessary to look for optimal granulation parameters, which are selected dynamically. We also describe potential directions of development of granular computing techniques by prism of described methods.
Hierarchical-Matching-Based Online and Real-Time Multi-Object Tracking with Deep Appearance Features
Authors: Ji Qingge , Yu Haoqiang , Wu Xiao
Published: March 2020

Based on tracking-by-detection, we propose a hierarchical-matching-based online and real-time multi-object tracking approach with deep appearance features, which can effectively reduce the false positives (FP) in tracking. For the purpose of increasing the accuracy rate of data association, we define the trajectory confidence using its position information, appearance information, and the information of historical relevant detections, after which we can classify the trajectories into different levels. In order to obtain discriminative appearance features, we developed a deep convolutional neural network to extract the appearance features of objects and trained it on a large-scale pedestrian re-identification dataset. Last but not least, we used the proposed diverse and hierarchical matching strategy to associate detection and trajectory sets. Experimental results on the MOT benchmark dataset show that our proposed approach performs well against other online methods, especially for the metrics of FP and frames per second (FPS).
Algebraic Point Projection for Immersed Boundary Analysis on Low Degree NURBS Curves and Surfaces
Authors: Liao Huanyu , Vaitheeswaran Pavan Kumar , Song Tao , Subbarayan Ganesh
Published: March 2020

Point projection is an important geometric need when boundaries described by parametric curves and surfaces are immersed in domains. In problems where an immersed parametric boundary evolves with time as in solidification or fracture analysis, the projection from a point in the domain to the boundary is necessary to determine the interaction of the moving boundary with the underlying domain approximation. Furthermore, during analysis, since the driving force behind interface evolution depends on locally computed curvatures and normals, it is ideal if the parametric entity is not approximated as piecewise-linear. To address this challenge, we present in this paper an algebraic procedure to project a point on to Non-uniform rational B-spline (NURBS) curves and surfaces. The developed technique utilizes the resultant theory to construct implicit forms of parametric Bézier patches, level sets of which are termed algebraic level sets (ALS). Boolean compositions of the algebraic level sets are carried out using the theory of R-functions. The algebraic level sets and their gradients at a given point on the domain are then used to project the point onto the immersed boundary. Beginning with a first-order algorithm, sequentially refined procedures culminating in a second-order projection algorithm are described for NURBS curves and surfaces. Examples are presented to illustrate the efficiency and robustness of the developed method. More importantly, the method is shown to be robust and able to generate valid solutions even for curves and surfaces with high local curvature or G 0 continuity—problems where the Newton–Raphson method fails due to discontinuity in the projected points or because the numerical iterations fail to converge to a solution, respectively.
Fast Evaluation of Aircraft Icing Severity Using Machine Learning Based on XGBoost
Authors: Li Sibo , Qin Jingkun , He Miao , Paoli Roberto
Published: March 2020

Aircraft icing represents a serious hazard in aviation which has caused a number of fatal accidents over the years. In addition, it can lead to substantial increase in drag and weight, thus reducing the aerodynamics performance of the airplane. The process of ice accretion on a solid surface is a complex interaction of aerodynamic and environmental variables. The complex relationship makes machine learning-based methods an attractive alternative to traditional numerical simulation-based approaches. In this study, we introduce a purely data-driven approach to find the complex pattern between different flight conditions and aircraft icing severity prediction. The supervised learning algorithm Extreme Gradient Boosting (XGBoost) is applied to establish the prediction framework which makes prediction based on any set of observations. The input flight conditions for the proposed prediction framework are liquid water content, droplet diameter and exposure time. The proposed approach is demonstrated in three cases: maximum ice thickness prediction, icing area prediction and icing severity level evaluation. Performance comparison studies and error analysis are also conducted to verify the effectiveness and performance of the proposed method. Results show that the proposed method has reasonable capability in evaluating aircraft icing severity.
The Effect of Osmopriming on Seed Germination and Early Seedling Characteristics of Carum carvi L.
Authors: Mirmazloum Iman , Kiss Attila , Erdélyi Éva , Ladányi Márta , Németh Éva Zámboriné , Radácsi Péter
Published: March 2020

Two experiments (in Petri dishes and in soil) were conducted to investigate the effects of osmopriming on seed germination and the early seedling characteristics of caraway (Carum carvi L. var. annua). The priming treatments in the Petri dish experiment were: polyethylene glycol (5%, 10% and 20%), KNO3 (0.5%, 1% and 2%) and KCL (1%, 2% and 4%) with three different soaking times (12, 24 and 36 h) along with control (non-primed seeds). Only polyethylene glycol and H2O were applied in the cell tray experiment, which were then compared with the non-primed seeds. In the Petri dish experiment, all three priming reagents significantly enhanced seedling length, with the most effective treatments being 5% PEG, 2% KNO3 and 1% KCL for 12 h. The plumule dry weights were also increased significantly after PEG (20% for 36 h), KNO3 (2% for 24 and 36 h) and KCL (1% for 12 h) treatments in comparison with the control. In the soil experiment, osmopriming with PEG significantly improved the germination rate (GR) and percentage, the plumule dry and fresh weights and the plumule length of caraway seedlings when compared with the control. A 23% higher germination percentage was recorded for the seeds treated with 5% PEG for 24 h as compared with the non-primed seeds. The PEG-primed seeds produced significantly longer seedlings when treated with 5% PEG for 24 h. All of the applied PEG treatments significantly enhanced the plumule fresh and dry weights, with the best outcomes being after 5% PEG (24 h) and 10% PEG (36 h) treatments, respectively. The 12-h hydro-priming also significantly enhanced all of the studied germination parameters when compared to the control. The results of the presented experiments show the significant positive effects of seed priming on caraway germination and how early seedling performance can easily be adopted by producers.
Changes in the Morphological Characteristics of Potato Plants Attributed to Seasonal Variability
Authors: Escuredo Olga , Seijo-Rodríguez Ana , Rodríguez-Flores M. Shantal , Meno Laura , Seijo M. Carmen
Published: March 2020

The development of a potato crop differs according to the environmental conditions and growing season of an area. Periods of high temperatures and drought have been frequent in recent years, and this has affected crops worldwide. The effect of meteorological factors on the plant morphology of potato cultivars growing in A Limia was analyzed for three consecutive years. The crop cycle with the highest temperatures and least accumulated rainfall (2016) showed plants with a higher number of leaflets, which were shorter in length. The crop cycle (2014) with a lower temperature and more rainfall had the tallest plants, the highest degree of flowering, fewer pairs of leaflets and the highest length of the floral peduncle. Kennebec and Fontane were the varieties that showed the least variability in morphological characteristics during the seasons analyzed. Considering the meteorological and morphological data, a principal component analysis was carried out, which explained 80.1% of the variance of the data. Spearman rank correlations showed higher significant coefficients between the temperature and foliar characteristics. The leaf size of plants was estimated using a multiple linear regression analysis, which included the mean temperature, explaining 64% of the variability of the data.
Reactive Oxygen Species and Male Fertility
Authors: O’Flaherty Cristian
Published: March 2020

Human infertility affects ~15% of couples worldwide, and it is now recognized that in half of these cases, the causes of infertility can be traced to men [...]
Water-Covered Roof Versus Inverted Flat Roof on the Mediterranean Coast: A Comparative Study of Thermal and Energy Behavior
Authors: Espinosa-Fernández Almudena , Echarri-Iribarren Víctor , Sáez Claudio A.
Published: March 2020

Reservoir, or water-collecting roofs present greater thermal inertia than inverted flat roofs due to the mass of water they contain. This feature gives them better thermal performance and leads to greater stability in the indoor air temperature Ti and the wall surface temperatures. In the summer, they can dampen the effect of solar radiation and regulate external thermal loads thanks to their greater effusivity and thermal capacity. This research compares the thermal behavior of the roofs of two buildings located in Alicante on the Spanish Mediterranean coast: a loft flat in the city center and a water-covered roof in the Museum of the University of Alicante (MUA). Values for effusivity, diffusivity, thermal capacity, decrement factor, time lag and internal, as well as external thermal admittance were obtained. After monitoring both roofs during 2014, behavior simulations were performed in Design Builder using 6 different scenarios reflecting different combinations in both buildings of water-covered, inverted and conventional roofs and marble or terrazzo paving. The water-covered roof led to a higher decrement factor and time lag, as well as to a reduction of annual energy demands between 8.86% and 9.03%.
Evaluation of the Antioxidant and Antimicrobial Activities of Porcine Liver Protein Hydrolysates Obtained Using Alcalase, Bromelain, and Papain
Authors: Borrajo Paula , Pateiro Mirian , Gagaoua Mohammed , Franco Daniel , Zhang Wangang , Lorenzo José Manuel
Published: March 2020

In order to make the by-products generated from the porcine industry more valuable, pig livers were used in this trial to obtain protein hydrolysates. Three proteases (alcalase, bromelain, and papain) were utilized for enzymatic hydrolysis with two different durations, 4 and 8 hours. Ultrafiltration process was used for the recovery of the extracts, employing three different membrane pore sizes (30, 10, and 5 kDa). The porcine livers contained considerable amounts of protein (19.0%), considering they are almost composed of water (74.1%). The antioxidant activity of the obtained hydrolysates was investigated using four antioxidant methods (2,2-Diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity, 2-2′-Azino-di-[3-ethylbenzthiazoline sulfonate] (ABTS) radical scavenging activity, ferric reducing antioxidant power assay (FRAP), and oxygen radical absorbance capacity assay (ORAC)). Antibacterial properties were also measured against Gram-negative and Gram-positive bacteria. Results indicated that the three studied factors (type of enzyme, membrane pore size, and time) significantly affected the parameters evaluated. Hydrolysates obtained at 8 hours with alcalase had the best antioxidant properties. The 30 kDa alcalase extracts exhibited the highest DPPH (562 µg Trolox/g), FRAP (82.9 µmol Fe2+/100 g), and ORAC (53.2 mg Trolox/g) activities, while for ABTS the 10 kDa alcalase showed the higher values (1068 mg ascorbic acid/100 g). Concerning the antibacterial activity, 30 kDa hydrolysates obtained with bromelain for 4 hours exhibited the highest antimicrobial capacity, providing an inhibition of 91.7%.
Effect of Plate Curvature on Heat Source Distribution in Induction Line Heating for Plate Forming
Authors: Chang Lichun , Zhao Yao , Yuan Hua , Hu Xiaocai , Yang Zhen , Zhang Hao
Published: March 2020

Line heating is an essential process in the formation of ship hull plates with a complex curvature. Electromagnetic induction heating is widely used in the line heating process. In electromagnetic induction heating, the shape of the coil and the air gap between the inductor and workpiece could influence the heat source distribution. Moreover, in the line heating process, the change of curvature of the plate will cause a change of the air gap of the inductor. Magnetic thermal coupling calculation is an effective method for simulating induction heating. This paper used the finite element method to calculate the distribution of heat sources in different initial plate curvatures and coil widths. The changes in heat source distribution and its laws were investigated. The results show that when the coil width is less than 100 mm, the effect of plate curvature on heat source distribution and strain distribution is not apparent; when the coil width is greater than 100 mm, the plate curvature has a visible effect on the heat generation distribution. In the case of a curvature increasing from 0 to 1 and a coil width equal to 220 mm, the Joule heat generation in the center of the heating area is reduced by up to 21%.
A Method to Generate Vector Beams with Adjustable Amplitude in the Focal Plane
Authors: Crăciun Alexandru , Dascălu Traian
Published: March 2020

We design and investigate an original optical component made of a c-cut uniaxial crystal and an optical system to generate cylindrical vector beams with an adjustable polarization state. The original optical component has a specific, nearly conical shape which allows it to operate like a broadband wave retarder with the fast axis oriented radially with respect to the optical axis. We show via numerical simulations, using the Debye–Wolf diffraction integral, that the focal spot changes depending on the polarization state, thus enabling the control of the focal shape. Non-symmetrical shapes can be created although the optical system and incoming beam are circularly symmetric. We explained, using Jones matrix formalism, that this phenomenon is connected with the Gouy phase difference acquired by certain modes composing the beam due to propagation to the focal plane. We present our conclusions in the context of two potential applications, namely, stimulated emission depletion (STED) microscopy and laser micromachining. The optical system can potentially be used for STED microscopy for better control of the point-spread function of the microscope and to decrease the unwanted light emitted from the surroundings of the focal point. We give an analytical expression for the shape of the original component using the aspherical lens formula for the two versions of the component: one for each potential application.
Study on the Carbon Emissions in the Whole Construction Process of Prefabricated Floor Slab
Authors: Kong Aisan , Kang Haibo , He Siyuan , Li Na , Wang Wei
Published: March 2020

The construction industry is characterized by high energy consumption and high carbon emissions. With growing concern about climate change, environmental protection is becoming increasingly important. In this paper, the whole construction process of prefabricated floor slab (PFS) is divided into three stages: production, transportation, and construction stages. Carbon emissions are calculated based on the life cycle assessment (LCA) method. A case study of PFS construction in Shaoxing city, China, was examined, and the calculation results were compared and evaluated with the traditional construction methods, which showed that in the production stage, carbon emissions increased due to mechanical operations during the prefabrication process. In the transportation stage, carbon emissions also increased due to the heavier prefabricated components during the transportation process. During the on-site construction stage, carbon emissions considerably decreased due to the lower hoisting frequency and less on-site pouring.
The Importance of Incorporating Denitrification in the Assessment of Groundwater Vulnerability
Authors: Busico Gianluigi , Kazakis Nerantzis , Colombani Nicolò , Khosravi Khabat , Voudouris Konstantinos , Mastrocicco Micòl
Published: March 2020

Human activities are deeply connected with groundwater reservoirs, so protecting them from pollution has become a priority in many regions of the world. Nitrate is considered the main groundwater pollutant since it is directly linked to many human activities. Agricultural activities and domestic wastewater have been identified as the main sources of nitrate in groundwater. Nevertheless, there are some natural processes that can mitigate nitrate pollution. Together with dilution processes, the degradation of nitrate through denitrification has been acknowledge as a process that can potentially reduce nitrogen loads, in both deep and shallow aquifers. Usually these processes were not properly quantified in vulnerability assessment methods, until the introduction of LOS indices. In this study, the application of the LOS indices on 4 agricultural areas is discussed, highlighting how the LOS indices can identify portions of the landscape with higher potential denitrification and how they directly enhance the groundwater vulnerability assessment. Previous studies have shown that LOS indices are a valuable tool for proper vulnerability assessment to nitrate, however they need to be coupled with other parameters that also describe nitrate behavior in groundwater. The SINTACS-SVN and DRASTIC-PA methods that include the LOS indices, were applied for the first time in the Epanomi coastal area to evaluate the reliably of the assessment and, despite the different classes range and the weights applied, similar groundwater vulnerability assessment maps were obtained. The nitrate vulnerability maps were comparable with the observed nitrate concentrations and were found to be highly comparable with original LOS maps. Nevertheless, it should be kept in mind that vulnerability methods are only screening tools and groundwater quality observations are pivotal information for environmental management.
Microphone and Loudspeaker Array Signal Processing Steps towards a “Radiation Keyboard” for Authentic Samplers
Authors: Ziemer Tim , Plath Niko
Published: March 2020

To date electric pianos and samplers tend to concentrate on authenticity in terms of temporal and spectral aspects of sound. However, they barely recreate the original sound radiation characteristics, which contribute to the perception of width and depth, vividness and voice separation, especially for instrumentalists, who are located near the instrument. To achieve this, a number of sound field measurement and synthesis techniques need to be applied and adequately combined. In this paper we present the theoretic foundation to combine so far isolated and fragmented sound field analysis and synthesis methods to realize a radiation keyboard, an electric harpsichord that approximates the sound of a real harpsichord precisely in time, frequency, and space domain. Potential applications for such a radiation keyboard are conservation of historic musical instruments, music performance, and psychoacoustic measurements for instrument and synthesizer building and for studies of music perception, cognition, and embodiment.
Combined Effects of Water Deficit, Exogenous Ethylene Application and Root Symbioses on Trigonelline and ABA Accumulation in Fenugreek
Authors: Irankhah Simin , Sillo Fabiano , Nerva Luca , Ganjeali Ali , Balestrini Raffaella , Chitarra Walter
Published: March 2020

Secondary metabolites (SMs) have high economic impact thanks to their exploitability in chemical, pharmaceutical and cosmetic industries. Trigonella foenum-graecum has an importance due to the production of bioactive compounds with pharmaceutical values. Among them, the alkaloid trigonelline is known for its role in the treatment of different human diseases. SM accumulation is influenced by environmental factors but is modulated by the application of exogenous compounds. Ethephon, a precursor of the phytohormone ethylene, was already used to influence SM accumulation. Our work is aimed at evaluating the accumulation of trigonelline and the phytohormone abscisic acid (ABA) when three factors were combined: i) two levels of water regimes (well-watered and water deficit), ii) ethephon treatments and iii) inoculation with an arbuscular mycorrhizal (AM)-based inoculum also leading to nodulation. The content of trigonelline and ABA was significantly affected by symbioses, showing high accumulation in AM-colonized plants irrespective of the water regimes applied. In terms of trigonelline accumulation with respect to ethephon treatments, while symbiotic plants showed a dose-dependent trend, non-symbiotic plants showed a significantly difference only when 550 ppm of ethephon was applied. In conclusion, our work provides new information on the effects of both ethephon and symbioses on plant growth and accumulation of valuable compounds, such as trigonelline, in fenugreek.
An Evaluation of Vegetation Health in and around Southern African National Parks during the 21st Century (2000–2016)
Authors: Herrero Hannah , Southworth Jane , Muir Carly , Khatami Reza , Bunting Erin , Child Brian
Published: March 2020

Roughly 65% of the African continent is classified as savanna. Such regions are of critical importance given their high levels of biological productivity, role in the carbon cycle, structural differences, and support of large human populations. Across southern Africa there are 79 national parks within savanna landscapes. Understanding trends and factors of vegetation health in these parks is critical for proper management and sustainability. This research strives to understand factors and trends in vegetation health from 2000 to 2016 in and around the 79 national parks across southern Africa. A backward stepwise regression was used to understand the factors (e.g., precipitation, population density, and presence of transfrontier conservation areas) affecting the normalized difference vegetation index (NDVI) during the 21st century. There was a statistically significant positive (p < 0.05) relationship between mean annual precipitation and NDVI, and a significant negative relationship between population density and NDVI. To monitor vegetation trends in and around the parks, directional persistence, a seasonal NDVI time series-based trend analysis, was used. Directional persistence is the net accumulation of directional change in NDVI over time in a given period relative to a fixed benchmarked period. Parks and buffer zones across size classes were compared to examine differences in vegetation health. There was an overwhelmingly positive trend throughout. Additionally, national parks, overall, had higher amounts of positive persistence and lower amounts of negative persistence than the surrounding buffer zones. Having higher positive persistence inside of parks indicates that they are functioning favorably relative to the buffer zones in terms of vegetation resilience. This is an important finding for park managers and conservation overall in Southern Africa.
Bionic Structure on Complex Surface with Belt Grinding for Electron Beam Welding Seam of Titanium Alloy
Authors: Xiao Guijian , Zhang Youdong , He Yi , Huang Yun , He Shui , Song Kangkang
Published: March 2020

Electron beam welding (EBW) is widely used to weld titanium alloy parts such as aero-engine casing and blades. The surface quality after EBW has a significant influence on the aero-engine performance of those parts. We propose a surface treatment method with grinding on a titanium alloy electron beam weld. We analyze the influence of grinding parameters on the characteristics of the grinding surface. The experiment shows the applicability of ground surface by belt grinding on EBW and its impact on aero-engine performance. After belt grinding, both the welded surface and the surface connected with the substrate are smooth. The extra height of the seam was less than 0.2 mm, and the surface roughness (Ra) of the weld after grinding can be less than 0.98 μm. The microstructure of the weld after grinding was analyzed. Two types of bionic shapes were obtained, a sawtooth shape with a width of 40 μm and a height of 10 μm and a wavy shape with a width of 20 μm and a height of 3 μm. From the analysis above, the bionic surface can be obtained by grinding on the weld with an abrasive belt.
Antioxidant Properties of a Supercritical Fluid Extract of the Halophyte Mesembryanthemum nodiflorum L. from Sicilian Coasts: Nutraceutical and Cosmeceutical Applications
Authors: Arena Rosaria , Manuguerra Simona , Collins Edward , Mahdhi Abdelkarim , Renda Giuseppe , Messina Concetta Maria , Santulli Andrea
Published: March 2020

The aim of this paper was to obtain different extracts from the aerial parts of Mesembryanthemum nodiflorum, comparing traditional extraction (using solvents with increasing polarity such as hexane, ethanol 80%, acetone 70% and water) with an eco-friendly technique (supercritical fluid extraction (SFE)); to evaluate which extract showed a higher amount of antioxidants and then evaluate the bioactive properties in vitro, in human fibroblast (HS68). From the six extracts obtained it was observed that the solvent with the highest extraction efficiency was water, but the extracts in ethanol, N-hexane and SFE are those that showed the highest antioxidant activity (polyphenols, 1,1-Diphenyl-2-picrylhydrazyl (DPPH) and reducing power). On the basis of these results, the SFE extract was chosen to evaluate the antioxidant and anti-aging activity in vitro, by assessing cell vitality and molecular markers (MTT and immunoblotting assays). The results showed that the SFE extract exerted antioxidant activity in vitro, protecting cells from mortality induced by oxidative stress; this protection was also confirmed at the molecular level, by the levels of the protein integrin -1, that is able to prevent the negative effects of a stress situation, such as oxidative stress, that could promote aging and related diseases. This extract, obtained with an eco-friendly technique, given its beneficial properties, could be used for application in nutraceuticals and cosmeceuticals.
ALCC-Glasses: Arriving Light Chroma Controllable Optical See-Through Head-Mounted Display System for Color Vision Deficiency Compensation
Authors: Tang Ying , Zhu Zhenyang , Toyoura Masahiro , Go Kentaro , Kashiwagi Kenji , Fujishiro Issei , Mao Xiaoyang
Published: March 2020

About 250 million people in the world suffer from color vision deficiency (CVD). Contact lenses and glasses with a color filter are available to partially improve the vision of people with CVD. Tinted glasses uniformly change the colors in a user’s field of view (FoV), which can improve the contrast of certain colors while making others hard to identify. On the other hand, an optical see-through head-mounted display (OST-HMD) provides a new alternative by applying a controllable overlay to a user’s FoV. The method of color calibration for people with CVD, such as the Daltonization process, needs to make the calibrated color darker, which has not yet been featured on recent commercial OST-HMDs. We propose a new approach to realize light subtraction on OST-HMDs using a transmissive LCD panel, a prototype system, named ALCC-glasses, to validate and demonstrate the new arriving light chroma controllable augmented reality technology for CVD compensation.
Cyclic Testing of a Composite Joint between a Reinforced Concrete Column and a Steel Beam
Authors: Dung Le Dang , Nguyen Xuan-Huy , Nguyen Quang-Huy
Published: March 2020

This paper presents an experimental study on the seismic performance of a novel composite joint between reinforced concrete columns and steel beams (RCSs) for frame structures. In the proposed RCS joint, an H steel profile totally embedded inside an RC column is directly welded to the steel beam. The H steel profile was covered by two supplementary plates to avoid the stirrups resisting the shear in the connection region. Two full-scale joints were built and tested under reversed-cyclic loading at the University of Transport and Communications of Vietnam. Seismic performance in terms of load-bearing capacity, story drift capacity, energy dissipation, and stiffness degradation were evaluated. The test specimen showed a good response to cyclic load reversals.
A Feature-Based Cost Estimation Model for Wind Turbine Blade Spar Caps
Authors: Clarke J. , McIlhagger A. , Archer E. , Dooher T. , Flanagan T. , Schubel P.
Published: March 2020

A problem for wind turbine operators is decreasing prices for wind-generated electricity. Many turbines are approaching their rated 20-year lives. A more economically viable and sustainable solution that reduces Levelized Cost of Energy (LCOE) and avoids expensive turbine replacement is retrofitting new spar caps blades. A new cost model assesses the feasibility of retrofitting 35 to 75 m turbines with GFRP (glass fiber reinforced polymer composite) and longer length CFRP (carbon fiber reinforced composite) spar caps. Spar cap cost scales with features such as mass, volume fraction and complexity. Organizational learning is a cost factor. Material and direct labor increase as proportions of total cost while tooling, capital, utilities, and indirect labor decrease. There is good agreement between a manufacturer and the model. Twenty-year turbines were compared with retrofitted spar caps over 25 years for LCOE. Same length GFRP and longer length CFRP spar cap retrofits decrease LCOE. Longer length CFRP spar caps decrease LCOE compared with GFRP retrofits over 25 years. CFRP material cost impacts CFRP retrofit feasibility. Retrofitted turbines must meet engineering, operational performance, and planning requirements criteria. Software algorithms may improve human learning and enable automatic updates from varying design and cost inputs, thereby increasing cost prediction accuracy.
Dynamical Networks Modelling Applied to Low Voltage Lines with Nonlinear Filters
Authors: Fazion Filho Mauro
Published: March 2020

The nonlinear dynamical behaviour of a network that is submitted to disturbances is the starting point of this work, where we consider a low voltage line (the network) with nonlinear varistor filters responding, dynamically, to those disturbances. Network models consider static measurements, and here we develop an iterative model to deal with dynamical measurements. We begin with the one-dimensional communication line model using reflected and incident signals, which are dependent on the node parameters, proceeding a time-step computation. Each node is a space representation that consolidates parameters for a specific vertex and its edges. Nonlinear functions are applied within the node and will contribute to the general process running on the structure. The idea of a structure and its related processes leads to a new concept of sustainability and system robustness. This concludes the work, along with several experimental and simulation results, with direct advantages to electromagnetic interference control and mitigation.
Source Apportionment of Fine Organic and Inorganic Atmospheric Aerosol in an Urban Background Area in Greece
Authors: Manousakas Manousos Ioannis , Florou Kalliopi , Pandis Spyros N.
Published: March 2020

Fine particulate matter (PM) originates from various emission sources and physicochemical processes. Quantification of the sources of PM is an important step during the planning of efficient mitigation strategies and the investigation of the potential risks to human health. Usually, source apportionment studies focus either on the organic or on the inorganic fraction of PM. In this study that took place in Patras, Greece, we address both PM fractions by combining measurements from a range of on- and off-line techniques, including elemental composition, organic and elemental carbon (OC and EC) measurements, and high-resolution Aerosol Mass Spectrometry (AMS) from different techniques. Six fine PM2.5 sources were identified based on the off-line measurements: secondary sulfate (34%), biomass burning (15%), exhaust traffic emissions (13%), nonexhaust traffic emissions (12%), mineral dust (10%), and sea salt (5%). The analysis of the AMS spectra quantified five factors: two oxygenated organic aerosols (OOA) factors (an OOA and a marine-related OOA, 52% of the total organic aerosols (OA)), cooking OA (COA, 11%) and two biomass burning OA (BBOA-I and BBOA-II, 37% in total) factors. The results of the two methods were synthesized, showcasing the complementarity of the two methodologies for fine PM source identification. The synthesis suggests that the contribution of biomass burning is quite robust, but that the exhaust traffic emissions are not due to local sources and may also include secondary OA from other sources.
Evaluating Temperature Measurements of the iMET-XQ, in the Field, under Varying Atmospheric Conditions
Authors: Kimball Sytske K. , Montalvo Carlos J. , Mulekar Madhuri S.
Published: March 2020

Temperature measurements of InterMET Inc. aluminum-coated iMET-XQ sensors were tested in an outdoor setting under a variety of solar radiation and wind speed conditions. Twelve unshielded sensors were mounted side-by-side on the tower of a South Alabama Mesonet weather station next to a reference sensor on the tower. The iMET-XQ temperatures were most precise and accurate in solar radiation values that were close to zero, regardless of wind speed. Under overcast conditions, wind speeds of 2 m s−1 were sufficient to obtain precise and accurate temperature measurements. During the day-time, aspiration of wind speeds higher than or equal to 3 m s−1 is sufficient. An iMET-XQ was placed in a radiation shield next to the tower reference sensor to test the need for a radiation shield. A second iMET-XQ was placed unshielded on the tower. The iMET-XQ sensors with aluminum coating do not need to be shielded, but they do need to be aspirated. It is recommended that, when taking temperature measurements using unmanned aerial vehicles (UAV) with iMET-XQ sensors, the UAV either fly at 3 m s−1, be embedded in winds of those speeds, or to use the propeller wash of the UAV to aspirate the sensors.
Chemical Compositions and Source Analysis of PM2.5 during Autumn and Winter in a Heavily Polluted City in China
Authors: Tian Shasha , Liu Yingying , Wang Jing , Wang Jian , Hou Lujian , Lv Bo , Wang Xinhua , Zhao Xueyan , Yang Wen , Geng Chunmei , Han Bin , Bai Zhipeng
Published: March 2020

As one of the biggest cities in North China, Jinan has been suffering heavy air pollution in recent decades. To better characterize the ambient particulate matter in Jinan during heavy pollution periods, we collected daily PM2.5 (particulate matter with aerodynamic diameters equal to or less than 2.5 μm) filter samples from 15 October 2017 to 31 January 2018 and analyzed their chemical compositions (including inorganic water-soluble ions (WSIs), carbonaceous species, and inorganic elements). The daily average concentration of PM2.5 was 83.5 μg/m3 during the sampling period. A meteorological analysis revealed that both low wind speed and high relative humidity facilitated the occurrence of high PM2.5 pollution episodes. A chemical analysis indicated that high concentrations of water-soluble ions, carbonaceous species, and elements were observed during heavy pollution days. The major constituents of PM2.5 in Jinan were secondary aerosol particles and organic matter based on the results of mass closure. Chemical Mass Balance (CMB) was used to track possible sources and identified that nitrate, sulfate, vehicle exhaust and coal fly ash were the main contributors to PM2.5 during heavy pollution days in Jinan, accounting for 25.4%, 18.6%, 18.2%, and 13.3%, respectively.
Implicit Equal-Weights Variational Particle Smoother
Authors: Wang Pinqiang , Zhu Mengbin , Chen Yan , Zhang Weimin
Published: March 2020

Under the motivation of the great success of four-dimensional variational (4D-Var) data assimilation methods and the advantages of ensemble methods (e.g., Ensemble Kalman Filters and Particle Filters) in numerical weather prediction systems, we introduce the implicit equal-weights particle filter scheme in the weak constraint 4D-Var framework which avoids the filter degeneracy through implicit sampling in high-dimensional situations. The new variational particle smoother (varPS) method has been tested and explored using the Lorenz96 model with dimensions N x = 40 , N x = 100 , N x = 250 , and N x = 400 . The results show that the new varPS method does not suffer from the curse of dimensionality by construction and the root mean square error (RMSE) in the new varPS is comparable with the ensemble 4D-Var method. As a combination of the implicit equal-weights particle filter and weak constraint 4D-Var, the new method improves the RMSE compared with the implicit equal-weights particle filter and LETKF (local ensemble transformed Kalman filter) methods and enlarges the ensemble spread compared with ensemble 4D-Var scheme. To overcome the difficulty of the implicit equal-weights particle filter in real geophysical application, the posterior error covariance matrix is estimated using a limited ensemble and can be calculated in parallel. In general, this new varPS performs slightly better in ensemble quality (the balance between the RMSE and ensemble spread) than the ensemble 4D-Var and has the potential to be applied into real geophysical systems.
Influence of the Background Nitrogen Oxides on the Tropospheric Ozone Depletion Events in the Arctic during Springtime
Authors: Zhou Jiashu , Cao Le , Li Simeng
Published: March 2020

Ozone depletion events (ODEs) in the springtime of the Arctic have been frequently observed since the early 1980s, and the correlation between the ozone mixing ratio during the ODEs and the nitrogen oxides (NOx) concentration is still unclear. In the present study, the role of the background level of NOx in ODEs was investigated by using a box model implementing a chemical reaction mechanism containing 49 chemical species and 141 related reactions. A concentration sensitivity analysis was also applied to discover the dependence of the ozone mixing ratio during the ODEs on each constituent of the initial air composition. The simulation results showed that a critical value of the NOx background level exists, with which the ozone depletion rate is independent of the initial concentration of NOx, and the critical value was found to be approximately 55 ppt (ppt = part per trillion, 10−12 mol/mol) in the present study. The concentration sensitivity analysis also showed that the existence of NOx has a two-sided impact on the depletion of ozone, depending on the initial amount of NOx. With a low background level of NOx (less than 55 ppt), the increase of the initial NOx can advance the ozone depletion. On the contrary, with a high initial NOx level (more than 55 ppt), NOx would delay the consumption of ozone during the ODEs.
A Hybrid Deep Learning Model to Forecast Particulate Matter Concentration Levels in Seoul, South Korea
Authors: Yang Guang , Lee HwaMin , Lee Giyeol
Published: March 2020

Both long- and short-term exposure to high concentrations of airborne particulate matter (PM) severely affect human health. Many countries now regulate PM concentrations. Early-warning systems based on PM concentration levels are urgently required to allow countermeasures to reduce harm and loss. Previous studies sought to establish accurate, efficient predictive models. Many machine-learning methods are used for air pollution forecasting. The long short-term memory and gated recurrent unit methods, typical deep-learning methods, reliably predict PM levels with some limitations. In this paper, the authors proposed novel hybrid models to combine the strength of two types of deep learning methods. Moreover, the authors compare hybrid deep-learning methods (convolutional neural network (CNN)—long short-term memory (LSTM) and CNN—gated recurrent unit (GRU)) with several stand-alone methods (LSTM, GRU) in terms of predicting PM concentrations in 39 stations in Seoul. Hourly air pollution data and meteorological data from January 2015 to December 2018 was used for these training models. The results of the experiment confirmed that the proposed prediction model could predict the PM concentrations for the next 7 days. Hybrid models outperformed single models in five areas selected randomly with the lowest root mean square error (RMSE) and mean absolute error (MAE) values for both PM10 and PM2.5. The error rate for PM10 prediction in Gangnam with RMSE is 1.688, and MAE is 1.161. For hybrid models, the CNN–GRU better-predicted PM10 for all stations selected, while the CNN–LSTM model performed better on predicting PM2.5.