bluuebunny/crossref_metadata_2025 huggingface dataset:
Plant Soft Rot Development and Regulation from the Viewpoint of Transcriptomic Profiling
Authors: Tsers Ivan , Gorshkov Vladimir , Gogoleva Natalia , Parfirova Olga , Petrova Olga , Gogolev Yuri
Published: September 2020

Soft rot caused by Pectobacterium species is a devastating plant disease poorly characterized in terms of host plant responses. In this study, changes in the transcriptome of tobacco plants after infection with Pectobacterium atrosepticum (Pba) were analyzed using RNA-Seq. To draw a comprehensive and nontrivially itemized picture of physiological events in Pba-infected plants and to reveal novel potential molecular “players” in plant–Pba interactions, an original functional gene classification was performed. The classifications present in various databases were merged, enriched by “missed” genes, and divided into subcategories. Particular changes in plant cell wall-related processes, perturbations in hormonal and other regulatory systems, and alterations in primary, secondary, and redox metabolism were elucidated in terms of gene expression. Special attention was paid to the prediction of transcription factors (TFs) involved in the disease’s development. Herewith, gene expression was analyzed within the predicted TF regulons assembled at the whole-genome level based on the presence of particular cis-regulatory elements (CREs) in gene promoters. Several TFs, whose regulons were enriched by differentially expressed genes, were considered to be potential master regulators of Pba-induced plant responses. Differential regulation of genes belonging to a particular multigene family and encoding cognate proteins was explained by the presence/absence of the particular CRE in gene promoters.
Genome-Wide Identification, Characterization, and Regulation of RWP-RK Gene Family in the Nitrogen-Fixing Clade
Authors: Wu Zhihua , Liu Hong , Huang Wen , Yi Lisha , Qin Erdai , Yang Tiange , Wang Jing , Qin Rui
Published: September 2020

RWP-RK is a plant-specific family of transcription factors, involved in nitrate response, gametogenesis, and nodulation. However, genome-wide characterization, phylogeny, and the regulation of RWP-RK genes in the nodulating and non-nodulating plant species of nitrogen-fixing clade (NFC) are widely unknown. Therefore, we identified a total of 292 RWP-RKs, including 278 RWP-RKs from 25 NFC species and 14 RWP-RKs from the outgroup, Arabidopsis thaliana. We classified the 292 RWP-RKs in two subfamilies: the NIN-like proteins (NLPs) and the RWP-RK domain proteins (RKDs). The transcriptome and phylogenetic analysis of RWP-RKs suggested that, compared to RKD genes, the NLP genes were just upregulated in nitrate response and nodulation. Moreover, nodule-specific NLP genes of some nodulating NFC species may have a common ancestor (OG0002084) with AtNLP genes in A. thaliana. Further, co-expression networks of A.thaliana under N-starvation and N-supplementation conditions revealed that there is a higher correlation between expression of AtNLP genes and symbiotic genes during N-starvation. In P. vulgaris, we confirmed that N-starvation stimulated nodulation by regulating expression of PvNLP2, closely related to AtNLP6 and AtNLP7 with another common origin (OG0004041). Taken together, we concluded that different origins of the NLP genes involved in both N-starvation response and specific expression of nodulation would contribute to the evolution of nodulation in NFC plant species. Our results shed light on the phylogenetic relationships of NLP genes and their differential regulation in nitrate response of A. thaliana and nodulation of NFC.
RUST: A Robust, User-Friendly Script Tool for Rapid Measurement of Rust Disease on Cereal Leaves
Authors: Gallego-Sánchez Luis M. , Canales Francisco J. , Montilla-Bascón Gracia , Prats Elena
Published: September 2020

Recently, phenotyping has become one of the main bottlenecks in plant breeding and fundamental plant science. This is particularly true for plant disease assessment, which has to deal with time-consuming evaluations and the subjectivity of visual assessments. In this work, we have developed an open source Robust, User-friendy Script Tool (RUST) for semi-automated evaluation of leaf rust diseases. RUST runs under the free Fiji imaging software (developed from ImageJ), which is a well-recognized software among the scientific community. The script enables the evaluation of leaf rust diseases using a color transformation tool and provides three different automation modes. The script opens images sequentially and records infection frequency (pustules per area) (semi-)automatically for high-throughput analysis. Furthermore, it can manage several scanned leaf segments in the same image, consecutively selecting the desired segments. The script has been validated with nearly 900 samples from 80 oat genotypes ranging from resistant to susceptible and from very light to heavily infected leaves showing a high accuracy with a Lin’s concordance correlation coefficient of 0.99. The analysis show a high repeatability as indicated by the low variation coefficients obtained when repeating the measurement of the same samples. The script also has optional steps for calibration and training to ensure accuracy, even in low-resolution images. This script can evaluate efficiently hundreds of leaves facilitating the screening of novel sources of resistance to this important cereal disease.
Management of Infection by Parasitic Weeds: A Review
Authors: Fernández-Aparicio Mónica , Delavault Philippe , Timko Michael P.
Published: September 2020

Parasitic plants rely on neighboring host plants to complete their life cycle, forming vascular connections through which they withdraw needed nutritive resources. In natural ecosystems, parasitic plants form one component of the plant community and parasitism contributes to overall community balance. In contrast, when parasitic plants become established in low biodiversified agroecosystems, their persistence causes tremendous yield losses rendering agricultural lands uncultivable. The control of parasitic weeds is challenging because there are few sources of crop resistance and it is difficult to apply controlling methods selective enough to kill the weeds without damaging the crop to which they are physically and biochemically attached. The management of parasitic weeds is also hindered by their high fecundity, dispersal efficiency, persistent seedbank, and rapid responses to changes in agricultural practices, which allow them to adapt to new hosts and manifest increased aggressiveness against new resistant cultivars. New understanding of the physiological and molecular mechanisms behind the processes of germination and haustorium development, and behind the crop resistant response, in addition to the discovery of new targets for herbicides and bioherbicides will guide researchers on the design of modern agricultural strategies for more effective, durable, and health compatible parasitic weed control.
Mechanical and Optical Properties of Thermochromic Reversible Waterborne Primer Film on Tilia europaea with 1,2-Benzo-6-diethylaminofluorane Based Microcapsules
Authors: Wang Lin , Yan Xiaoxing
Published: September 2020

A waterborne thermochromic primer film containing thermochromic reversible microcapsules on the surface of Tilia europaea was prepared. The influences of different microcapsule concentrations on the reversible thermochromic, optical, mechanical and liquid resistance properties of the primer films were investigated. Not only were the morphology and structure of microcapsules and films observed, but also the chemical compositions of the microcapsules and films were analyzed. The results showed that for the primer film with microcapsules, the microcapsule concentration had a more significant influence on color difference. The primer film with microcapsules can achieve thermochromic reversibility. The temperature of color change was 32 °C and it had a good color recovery. The film gloss was negatively correlated with the microcapsule concentration, and the film with 5.0%–15.0% concentration had the best gloss. Adding an appropriate concentration of microcapsules can effectively improve the mechanical properties of the film. The film with 0–15.0% microcapsules had better liquid resistance to detergent, i.e., grade 1. The bonding form between the primer film added with microcapsules and Tilia europaea was physical bonding. This study provides a technical reference for the development of modern intelligent discoloration wood products.
Tracer Diffusion in Tightly-Meshed Homogeneous Polymer Networks: A Brownian Dynamics Simulation Study
Authors: Cho Hyun , Kim Haein , Sung Bong , Kim Jun
Published: September 2020

We report Brownian dynamics simulations of tracer diffusion in regularly crosslinked polymer networks in order to elucidate the transport of a tracer particle in polymer networks. The average mesh size of homogeneous polymer networks is varied by assuming different degrees of crosslinking or swelling, and the size of a tracer particle is comparable to the average mesh size. Simulation results show subdiffusion of a tracer particle at intermediate time scales and normal diffusion at long times. In particular, the duration of subdiffusion is significantly prolonged as the average mesh size decreases with increasing degree of crosslinking, for which long-time diffusion occurs via the hopping processes of a tracer particle after undergoing rattling motions within a cage of the network mesh for an extended period of time. On the other hand, the cage dynamics and hopping process are less pronounced as the mesh size decreases with increasing polymer volume fractions. The interpretation is provided in terms of fluctuations in network mesh size: at higher polymer volume fractions, the network fluctuations are large enough to allow for collective, structural changes of network meshes, so that a tracer particle can escape from the cage, whereas, at lower volume fractions, the fluctuations are so small that a tracer particle remains trapped within the cage for a significant period of time before making infrequent jumps out of the cage. This work suggests that fluctuation in mesh size, as well as average mesh size itself, plays an important role in determining the dynamics of molecules and nanoparticles that are embedded in tightly meshed polymer networks.
Lipase-Catalysed In Situ Transesterification of Waste Rapeseed Oil to Produce Diesel-Biodiesel Blends
Authors: Sendzikiene Egle , Santaraite Migle , Makareviciene Violeta
Published: September 2020

Rapeseed oil of high acidity, an agricultural industry by-product unsuitable for food, was used as an inexpensive raw material for the production of biodiesel fuel. The use of rapeseed oil that is unsuitable for food and lipase as a catalyst makes the biodiesel production process environmentally friendly. Simultaneous oil extraction and in situ transesterification using diesel as an extraction solvent was investigated to obtain a diesel-biodiesel blend. The diesel and rapeseed oil blend ratio was 9:1 (w/w). The enzymatic production of biodiesel from rapeseed oil with high acidity and methanol using eleven different lipases as biocatalysts was studied. The most effective biocatalyst, lipase—Lipozyme TL IM (Thermomyces lanuginosus), which is suitable for in situ transesterification—was selected, and the conversion of rapeseed oil into fatty acid methyl ester was evaluated. The influence of the amount of methanol and lipase, the reaction temperature and the reaction time were investigated to achieve the highest degree of transesterification. The optimal reaction conditions, when the methanol to oil molar ratio was 5:1, were found to be a reaction time of 5 h, a reaction temperature of 25 °C and a lipase (Lipozyme TL IM) concentration of 5% (based on oil weight). Under these optimal conditions, 99.90% (w/w) of the rapeseed oil was extracted from the seed and transesterified. The degree of transesterification obtained was 98.76% (w/w). Additionally, the glyceride content in the biodiesel fuel was investigated and met the requirements perfectly.
Marangoni Boundary Layer Flow and Heat Transfer of Graphene–Water Nanofluid with Particle Shape Effects
Authors: Rashid Umair , Baleanu Dumitru , Liang Haiyi , Abbas Muhammad , Iqbal Azhar , Rahman Jamshid ul
Published: September 2020

Graphene nanofluids have attracted the attention of many researchers because of a variety of remarkable properties such as extraordinary electronic transport properties, high thermal conductivity, and large specific surface areas. This paper investigates the shape effects of nanoparticles on the Marangoni boundary layer of graphene–water nanofluid flow and heat transfer over a porous medium under the influences of the suction parameter. The graphene–water nanofluid flow was contained with various shapes of nanoparticles, namely sphere, column, platelet, and lamina. The problem is modeled in form of partial differential equations (PDES) with boundary conditions. The governing transport equations are converted into dimensionless form with the help of some suitable nondimensional variables. The solution of the problem was found numerically using the NDSolve technique of Mathematica 10.3 software. In addition, the numerical solutions were also compared with analytical results. The homotopy analysis method (HAM) is used to calculate the analytical results. The results show that lamina-shaped nanoparticles have better performance on temperature distribution while sphere-shaped nanoparticles are more efficient for heat transfer than other shapes of nanoparticles.
Implementation of Common Rail Direct Injection System and Optimization of Fuel Injector Parameters in an Experimental Single-Cylinder Diesel Engine
Authors: Teoh Yew Heng , How Heoy Geok , Peh Ching Guan , Le Thanh Danh , Nguyen Huu Tho
Published: September 2020

The diesel engine is one of the solutions to slow down fossil fuel depletion due to its high efficiency. However, its high pollutant emission limits its usage in many fields. To improve its efficiency and emissions, a conventional mechanical fuel injection system (MFI) was be replaced with common rail direct injection (CRDI) system for the purpose of this study. In this way, injection parameters such as injection timing, injection pressure and multiple injection schemes can be tuned to enhance the engine performance. The rail pressure and engine speed response of the modified diesel engine was tested. It was found that by advancing the start of injection timing (SOI) timing or increasing the rail pressure, the brake torque generated can be increased. Multiple injection schemes can be implemented to reduce the peak heat release rate (HRR). Post injection was observed to increase the late combustion HRR. The maximum pressure rise rate (PRR) can be reduced by applying pilot injection. Further research was conducted on optimizing fuel injector parameters to improve the indicated mean effective pressure (IMEP) consistency and reduce injector power consumption. The consistency of IMEP was indicated by coefficient of variation (CoV) of IMEP. The injector parameters included open time, low time and duty cycle of injector signals. These parameters were optimized by carrying out response surface methodology. The optimized parameters were observed to be 230 µs for open time, 53µs for low time and 27.5% for duty cycle. The percentage of error of CoV of IMEP and injector power were found to be lower than 5% when the predicted results are compared with experimental results.
Special Issue on “Energy, Economy and Environment for Industrial Production Processes”
Authors: Cai Wei , Tian Guangdong , Zhou MengChu , Zhao Fu , Cunha Jorge
Published: September 2020

Facing significant natural resource consumption, environmental degradation, and climate warming, governments and international organizations have increased their focus on ecological modernization, green growth, and low carbon development, with various sustainable development strategies [...]
Spray Structure and Characteristics of a Pressure-Swirl Dust Suppression Nozzle Using a Phase Doppler Particle Analyze
Authors: Wang Junpeng , Xu Cuicui , Zhou Gang , Zhang Yansong
Published: September 2020

In order to understand the characteristics of the spray field of a dust suppression nozzle and provide a reference for dust nozzle selection according to dust characteristics, a three-dimensional phase Doppler particle analyzer (PDPA) spray measurement system is used to analyze the droplet size and velocity characteristics in a spray field, particularly the joint particle size–velocity distribution. According to the results, after the ejection of the jet from the nozzle, the droplets initially maintained some velocity; however, the distribution of particles with different sizes was not uniform. As the spray distance increased, the droplet velocity decreased significantly, and the particle size distribution changed very little. As the distance increased further, the large droplets separated into smaller droplets, and their velocity decreased rapidly. The distributions of the particle size and velocity of the droplets then became stable. Based on the particle size-velocity distribution characteristics, the spray structure of pressure-swirl nozzles can be divided into five regions, i.e., the mixing, expansion, stabilization, decay, and rarefied regions. The expansion, stabilization, and decay regions are the effective dust fall areas. In addition, the droplet size in the stabilization region is the most uniform, indicating that this region is the best dust fall region. The conclusions can provide abundant calibration data for spray dust fall nozzles.
Synthesis of Silicon Hybrid Phenolic Resins with High Si-Content and Nanoscale Phase Separation Structure
Authors: Yuan Wenjie , Chen Fenghua , Li Shan , Du Youpei , Luo Zhenhua , Sun Yanan , Li Hao , Zhao Tong
Published: September 2020

In this paper, a set of silicon hybrid phenolic resins (SPF) with high Si-content were prepared by mixing phenolic resins with self-synthesized silicon resins. In order to obtain the nanoscale phase structure, condensation degree and the amount of Si-OH groups in silicon resins were controlled by the amount of inhibitor ethanol in the hydrolytic condensation polymerization of siloxane. Increasing the amount of ethanol resulted in more silanol groups and a lower degree of condensation for silicon resins, which then led to more formation of Si-O-Ph bonds in hybrid resin and improved compatibility between silicon resin and phenolic resin. When 400% ethanol by weight of siloxane was used in the sample SPF-4, nanoscale phase separation resulted. The residual weight of the cured SPF-4 at 1000 °C (R1000) significantly increased compared to pure phenolic resins. The result of the oxyacetylene flame ablation and the Cone Calorimeter test confirmed the improved ablative property and flammability after the modification. The performance improvement of the cured SPF-4 was attributed to the nanoscale phase structure and high silicon content, which promoted the formation of dense silica protective layers during pyrolysis.
A Grid-Density Based Algorithm by Weighted Spiking Neural P Systems with Anti-Spikes and Astrocytes in Spatial Cluster Analysis
Authors: Kong Deting , Wang Yuan , Wu Xinyan , Liu Xiyu , Qu Jianhua , Xue Jie
Published: September 2020

In this paper, we propose a novel clustering approach based on P systems and grid- density strategy. We present grid-density based approach for clustering high dimensional data, which first projects the data patterns on a two-dimensional space to overcome the curse of dimensionality problem. Then, through meshing the plane with grid lines and deleting sparse grids, clusters are found out. In particular, we present weighted spiking neural P systems with anti-spikes and astrocyte (WSNPA2 in short) to implement grid-density based approach in parallel. Each neuron in weighted SN P system contains a spike, which can be expressed by a computable real number. Spikes and anti-spikes are inspired by neurons communicating through excitatory and inhibitory impulses. Astrocytes have excitatory and inhibitory influence on synapses. Experimental results on multiple real-world datasets demonstrate the effectiveness and efficiency of our approach.
Autonomous Indoor Scanning System Collecting Spatial and Environmental Data for Efficient Indoor Monitoring and Control
Authors: Park Dongwoo , Hwang Soyoung
Published: September 2020

As various activities related to entertainment, business, shopping, and conventions are done increasingly indoors, the demand for indoor spatial information and indoor environmental data is growing. Unlike the case of outdoor environments, obtaining spatial information in indoor environments is difficult. Given the absence of GNSS (Global Navigation Satellite System) signals, various technologies for indoor positioning, mapping and modeling have been proposed. Related business models for indoor space services, safety, convenience, facility management, and disaster response, moreover, have been suggested. An autonomous scanning system for collection of indoor spatial and environmental data is proposed in this paper. The proposed system can be utilized to collect spatial dimensions suitable for extraction of a two-dimensional indoor drawing and obtainment of spatial imaging as well as indoor environmental data on temperature, humidity and particulate matter. For these operations, the system has two modes, manual and autonomous. The main function of the systems is autonomous mode, and the manual mode is implemented additionally. It can be applied in facilities without infrastructure for indoor data collection, such as for routine indoor data collection purposes, and it can also be used for immediate indoor data collection in cases of emergency (e.g., accidents, disasters).
EM Estimation for the Poisson-Inverse Gamma Regression Model with Varying Dispersion: An Application to Insurance Ratemaking
Authors: Tzougas George
Published: September 2020

This article presents the Poisson-Inverse Gamma regression model with varying dispersion for approximating heavy-tailed and overdispersed claim counts. Our main contribution is that we develop an Expectation-Maximization (EM) type algorithm for maximum likelihood (ML) estimation of the Poisson-Inverse Gamma regression model with varying dispersion. The empirical analysis examines a portfolio of motor insurance data in order to investigate the efficiency of the proposed algorithm. Finally, both the a priori and a posteriori, or Bonus-Malus, premium rates that are determined by the Poisson-Inverse Gamma model are compared to those that result from the classic Negative Binomial Type I and the Poisson-Inverse Gaussian distributions with regression structures for their mean and dispersion parameters.
Proximity Operations and Three Degree-of-Freedom Maneuvers Using the Smartphone Video Guidance Sensor
Authors: Hariri Nasir , Gutierrez Hector , Rakoczy John , Howard Richard , Bertaska Ivan
Published: September 2020

This paper presents the first demonstration of NASA’s Smartphone Video Guidance Sensor (SVGS) as real-time position and attitude estimator for proximity and formation maneuvers. An optimal linear quadratic Gaussian controller was used, combining a linear quadratic regulator and a Kalman filter. The system was demonstrated controlling the 3-degree of freedom planar motion of the RINGS ground units (Resonant Inductive Near-field Generation Systems). A state-space model of the system’s 3-DOF motion dynamics was derived, and model parameters extracted using a system identification technique. The system’s motion control performance is experimentally demonstrated in both tracking and formation maneuvers. The results highlight the capabilities and performance of the Smartphone Video Guidance Sensor (SVGS) as a vision-based real-time position and attitude sensor for motion control, formation flight and proximity operations. A leader-follower formation maneuver approach is demonstrated, as well as position hold and path following.
Implementation of BFASTmonitor Algorithm on Google Earth Engine to Support Large-Area and Sub-Annual Change Monitoring Using Earth Observation Data
Authors: Hamunyela Eliakim , Rosca Sabina , Mirt Andrei , Engle Eric , Herold Martin , Gieseke Fabian , Verbesselt Jan
Published: September 2020

Monitoring of abnormal changes on the earth’s surface (e.g., forest disturbance) has improved greatly in recent years because of satellite remote sensing. However, high computational costs inherently associated with processing and analysis of satellite data often inhibit large-area and sub-annual monitoring. Normal seasonal variations also complicate the detection of abnormal changes at sub-annual scale in the time series of satellite data. Recently, however, computationally powerful platforms, such as the Google Earth Engine (GEE), have been launched to support large-area analysis of satellite data. Change detection methods with the capability to detect abnormal changes in time series data while accounting for normal seasonal variations have also been developed but are computationally intensive. Here, we report an implementation of BFASTmonitor (Breaks For Additive Season and Trend monitor) on GEE to support large-area and sub-annual change monitoring using satellite data available in GEE. BFASTmonitor is a data-driven unsupervised change monitoring approach that detects abnormal changes in time series data, with near real-time monitoring capabilities. Although BFASTmonitor has been widely used in forest cover loss monitoring, it is a generic change monitoring approach that can be used to monitor changes in a various time series data. Using Landsat time series for normalised difference moisture index (NDMI), we evaluated the performance of our GEE BFASTmonitor implementation (GEE BFASTmonitor) by detecting forest disturbance at three forest areas (humid tropical forest, dry tropical forest, and miombo woodland) while comparing it to the original R-based BFASTmonitor implementation (original BFASTmonitor). A map-to-map comparison showed that the spatial and temporal agreements on forest disturbance between the original and our GEE BFASTmonitor implementations were high. At each site, the spatial agreement was more than 97%, whereas the temporal agreement was over 94%. The high spatial and temporal agreement show that we have properly translated and implemented the BFASTmonitor algorithm on GEE. Naturally, due to different numerical solvers being used for regression model fitting in R and GEE, small differences could be observed in the outputs. These differences were most noticeable at the dry tropical forest and miombo woodland sites, where the forest exhibits strong seasonality. To make GEE BFASTmonitor accessible to non-technical users, we developed a web application with simplified user interface. We also created a JavaScript-based GEE BFASTmonitor package that can be imported as a module. Overall, our GEE BFASTmonitor implementation fills an important gap in large-area environmental change monitoring using earth observation data.
Displacements Monitoring over Czechia by IT4S1 System for Automatised Interferometric Measurements Using Sentinel-1 Data
Authors: Lazecký Milan , Hatton Emma , González Pablo J. , Hlaváčová Ivana , Jiránková Eva , Dvořák František , Šustr Zdeněk , Martinovič Jan
Published: September 2020

The Sentinel-1 satellite system continuously observes European countries at a relatively high revisit frequency of six days per orbital track. Given the Sentinel-1 configuration, most areas in Czechia are observed every 1–2 days by different tracks in a moderate resolution. This is attractive for various types of analyses by various research groups. The starting point for interferometric (InSAR) processing is an original data provided in a Single Look Complex (SLC) level. This work represents advantages of storing data augmented to a specifically corrected level of data, SLC-C. The presented database contains Czech nationwide Sentinel-1 data stored in burst units that have been pre-processed to the state of a consistent well-coregistered dataset of SLC-C. These are resampled SLC data with their phase values reduced by a topographic phase signature, ready for fast interferometric analyses (an interferogram is generated by a complex conjugate between two stored SLC-C files). The data can be used directly into multitemporal interferometry techniques, e.g., Persistent Scatterers (PS) or Small Baseline (SB) techniques applied here. A further development of the nationwide system utilising SLC-C data would lead into a dynamic state where every new pre-processed burst triggers a processing update to detect unexpected changes from InSAR time series and therefore provides a signal for early warning against a potential dangerous displacement, e.g., a landslide, instability of an engineering structure or a formation of a sinkhole. An update of the processing chain would also allow use of cross-polarised Sentinel-1 data, needed for polarimetric analyses. The current system is running at a national supercomputing centre IT4Innovations in interconnection to the Czech Copernicus Collaborative Ground Segment (CESNET), providing fast on-demand InSAR results over Czech territories. A full nationwide PS processing using data over Czechia was performed in 2017, discovering several areas of land deformation. Its downsampled version and basic findings are demonstrated within the article.
Spectroelectrochemical Determination of Isoprenaline in a Pharmaceutical Sample
Authors: Olmo Fabiola , Garoz-Ruiz Jesus , Carazo Julia , Colina Alvaro , Heras Aranzazu
Published: September 2020

UV/Vis absorption spectroelectrochemistry (SEC) is a multi-response technique that has been commonly used for the characterization of materials and the study of reaction mechanisms. However, it has been scarcely used for quantitative purposes. SEC allows us to obtain two analytical signals simultaneously, yielding a dual sensor in just one experiment. In the last years, our group has developed new devices useful for analysis. In this work, a SEC device in parallel configuration, based on optical fibers fixed on screen-printed electrodes, was used to determine isoprenaline in a commercial drug, using both, the electrochemical and the spectroscopic signals. In this commercial drug, isoprenaline is accompanied in solution by other compounds. Among them is sodium metabisulfite, an antioxidant that strongly interferes in the isoprenaline determination. A simple pretreatment of the drug sample by bubbling wet-air allows us to avoid the interference of metabisulfite. Here, we demonstrate again the capabilities of UV/Vis absorption SEC as double sensor for analysis and we propose a simple pretreatment to remove interfering compounds.
Research on the Enhancement of Laser Radar Range Image Recognition Using a Super-Resolution Algorithm
Authors: Zhai Yu , Lei Jieyu , Xia Wenze , Han Shaokun , Liu Fei , Li Wenhao
Published: September 2020

This work introduces a super-resolution (SR) algorithm for range images on the basis of self-guided joint filtering (SGJF), adding the range information of the range image as a coefficient of the filter to reduce the influence of the intensity image texture on the super-resolved image. A range image SR recognition system is constructed to study the effect of four SR algorithms including the SGJF algorithm on the recognition of the laser radar (ladar) range image. The effects of different model library sizes, SR algorithms, SR factors and noise conditions on the recognition are tested via experiments. Results demonstrate that all tested SR algorithms can improve the recognition rate of low-resolution (low-res) range images to varying degrees and the proposed SGJF algorithm has a very good comprehensive recognition performance. Finally, suggestions for the use of SR algorithms in actual scene recognition are proposed on the basis of the experimental results.
The Implications of Vertical Strategic Interaction on Green Technology Investment in a Supply Chain
Authors: Wang Simeng , Cheng Yongsheng , Zhang Xiaoxian , Zhu Chenchen
Published: September 2020

Numerous studies on supply chains have indicated that vertical strategic interactions usually involve the classical double marginalization problem, leading to a downward distortion in profitability. However, at present, the implications of vertical strategic interactions for green technology investment in a supply chain are not all that clear. In particular, such a vertical interaction not only can translate into profits between different parties, but usually also involves differentiated environmental performance. A question which arises is: who is the right undertaker for green technology investment in a supply chain, the supplier or retailer? To answer this question, we highlight the implications of vertical strategic interaction for green technology investment in a supply chain. To fill this gap, using a game-theoretic approach, we formulate two models: (a) Model M, in which an upstream manufacturer adopts technologies to meet consumer demand; and (b) Model R, where a retailer integrates environmental concerns into their supply chain decisions. We find that the retailer, who is closer to the customer, is the more effective undertaker for green technology investment, as this not only creates higher profitability for both parties, but also achieves a more sustainable scheme for our environment. When green technologies are invested in by the manufacturer, the double marginalization effect not only may downward-distort their economic performance but can also reduce the equilibrium of product greenness.
Schedules Optimization with the Use of Value Engineering and NPV Maximization
Authors: Rosłon Jerzy , Książek-Nowak Mariola , Nowak Paweł
Published: September 2020

Construction program, spatial, architectural, and structural decisions taken in the early stages of a project have a significant impact on meeting the goals and needs of the client. The use of principles and methods of value management allows for an in-depth analysis of the project assumptions from the investor’s perspective and leads to the best ratio of the project’s utility value/sustainability to the price of its implementation. However, analysis of literature sources allows to state that optimization of the economic value of the project takes place only in the preimplementation phase of the project. This paper presents the original concept of combining issues of construction project’s utility and economic value optimization. The model enables the maximization of the utility value of the subject of the project, taking into account its economic parameters. To support the implementation of the model, a schedule optimization procedure was developed using metaheuristic algorithm. The model was demonstrated on the basis of a case study. The presented proprietary approach to optimize the construction schedule taking into account the economic and sustainability of a construction project can be used in “design and build” projects, with particular emphasis on projects managed in the sustainable Project Management system.
Identifying the Factors That Increase the Probability of an Injury or Fatal Traffic Crash in an Urban Context in Jordan
Authors: Miqdady Tasneem , de Oña Juan
Published: September 2020

The lack of robust studies carried out on urban roads in developing countries makes it difficult to enhance traffic safety, ensuring sustainable roads and cities. This study analyzes the contribution of a number of explanatory variables behind crashes involving injuries on arterial roads in Irbid (Jordan). Five binary logistic regression models were calibrated for a crash dataset from 2014–2018: one for the full database, and the others for the four main crash causes identified by Jordanian Traffic Police reports. The models show that whatever the crash cause, the three most significant factors linked to an injury or fatality lie in urban road sections that are in large-scale neighborhood areas, have fewer than six accesses per kilometer, and have a low traffic volume (under 500 veh/h/ln). Some of these results agree with previous studies in other countries. Jordan’s governmental agencies concerned with urban road safety might use these results to develop appropriate plans and implement priority actions for each crash cause, in addition to undertaking further research for comparative purposes.
Effect of Triangular Baffle Arrangement on Heat Transfer Enhancement of Air-Type PVT Collector
Authors: Yu Ji-Suk , Kim Jin-Hee , Kim Jun-Tae
Published: September 2020

A Photovoltaic Thermal (PVT) Collector is a device that produces electricity and simultaneously uses a heat source transmitted to back side of the Photovoltaic (PV). The PVT collector is categorized into liquid-type and air-type according to the heating medium. As an advantage, air-type PVT system is easy to manage and can be directly used for heating purposes. The performance of air-type PVT collector is determined by various factors, such as the height of air gap and air flow path (by baffles) in the collector. Baffles are installed in the PVT collector to improve the thermal performance of the collector by generating turbulence. However, the air flow that affects the performance of the PVT collector can vary depending on the number and placement of the baffles. Thus, the flow design using baffles in the collector is important. In this study, the performance of an air-type PVT collector due to the arrangement of triangular baffles and air gap height at the back of the PV module is analyzed through a simulation program. For this purpose, Computational Fluid Dynamics (CFD) analysis was performed with an NX program to compare and analyze the optimum conditions to improve the performance of the collector.
Innovative Tools for Tourism and Cultural Tourism Impact Assessment
Authors: Kalvet Tarmo , Olesk Maarja , Tiits Marek , Raun Janika
Published: September 2020

The importance of data and evidence has increased considerably in policy planning, implementation, and evaluation. There is unprecedented availability of open and big data, and there are rapid developments in intelligence gathering and the application of analytical tools. While cultural heritage holds many tangible and intangible values for local communities and society in general, there is a knowledge gap regarding suitable methods and data sources to measure the impacts and develop data-driven policies of cultural tourism. In the tourism sector, rapid developments are particularly taking place around novel uses of mobile positioning data, web scraping, and open application programming interface (API) data, data on sharing, and collaborative economy and passenger data. Based on feedback from 15 European cultural tourism regions, recommendations are developed regarding the use of innovative tools and data sources in tourism management. In terms of potential analytical depth, it is especially advisable to explore the use of mobile positioning data. Yet, there are considerable barriers, especially in terms of privacy protection and ethics, in using such data. User-generated big data from social media, web searches, and website visits constitute another promising data source as it is often publicly available in real time and has low usage barriers. Due to the emergence of new platform-based business models in the travel and tourism sector, special attention should be paid to improving access and usage of data on sharing and collaborative economy.
Safety and Efficiency Analysis of Turbo Roundabout with Simulations Based on the Lujiazui Roundabout in Shanghai
Authors: Liu Qiujia , Deng Jiali , Shen Yifan , Wang Wenxin , Zhang Zhan , Lu Linjun
Published: September 2020

Traditional multilane roundabouts have many branch lanes without traffic signs and channelization, which leads to a high tendency for traffic collisions. Turbo roundabouts are a new design that has the potential to reduce lane-change conflicts using canalization to force drivers to keep in specific lanes based on their intended destination. This paper evaluates the safety and efficiency performance of turbo roundabouts for the case of a five-leg roundabout called Lujiazui in Shanghai and provides design and construction guidelines when applying the turbo design. The models for the Lujiazui roundabout and the reconstructed turbo version were built in Vissim, and a comprehensive series of experiments under different traffic volumes and central island radii was performed. Afterward, the conflict statistics extracted from the trajectory files in the Surrogate Safety Assessment Model (SSAM) were analyzed using the conflict severity index (CSI) and were then integrated to calculate the modified conflict frequency (MCF) for safety performance evaluation. A comparative efficiency analysis was also conducted as a supplement. Based on the results, the relative characteristics for safety and efficiency between the turbo and original designs of the Lujiazui roundabout were analyzed. Suggestions to apply the turbo design on a five-leg roundabout are introduced.
Does Chinese FDI, Climate Change, and CO2 Emissions Stimulate Agricultural Productivity? An Empirical Evidence from Pakistan
Authors: Ahmad Shakeel , Tariq Muhammad , Hussain Touseef , Abbas Qasir , Elham Hamidullah , Haider Iqbal , Li Xiangmei
Published: September 2020

Pakistan’s agricultural sector growth is dwindling from the last several years due to insufficient foreign direct investment (FDI) and a drastic climate change-induced raise in temperature, which are severely affecting agricultural production. The FDI has paramount importance for the economy of developing countries as well as the improvement of agricultural production. Based on the time series data from 1984 to 2017, this paper aims to highlight the present situation of the agriculture sector of Pakistan and empirically analyze the short-run and long-run impact of Chinese foreign direct investment (CFDI), climate change, and CO2 emissions on agricultural productivity and causality among the variables. The Autoregressive Distributed Lag Model (ARDL) model and Granger Causality test were employed to find out the long-run, short-run, and causal relationships among the variables of interest. Furthermore, we have employed the Error Correction Model (ECM) to know the convergence of the equilibrium path. The bound test results verified the existence of a long-run association, and the empirical findings confirmed that Chinese FDI has a significant and positive impact, while climate change and CO2 emissions has negative impact on the agricultural growth of Pakistan both in the short-run and long-run. Granger Causality test results revealed that variables of interest exhibit bi-directional and uni-directional causality. The sector-wise flow of FDI reveals that the agriculture sector of Pakistan has comparatively received a less amount of FDI than other sectors of the economy. Based on the findings, it was suggested to the Government of Pakistan and policymakers to induce more FDI in the agriculture sector. Such policies would be helpful for the progress of the agriculture sector as well as for the economic growth of Pakistan.
The Impact of Workplace Disability Facilities on Job Retention Wishes among People with Physical Disabilities in South Korea
Authors: Kim Eun Jung , Kim Inhan , Kim Mi Jeong
Published: September 2020

The 2030 UN Agenda for Sustainable Development aims to end poverty “in all forms” and achieve sustainable development by 2030, while ensuring that “no one is left behind”, including people with disabilities. Disability is referenced eleven times in the Agenda. Disabled people face high risks of poverty because of barriers such as lack of workplace disability facilities. The goal of the study was to examine how workplace disability facilities affect job retention plans among workers with physical disabilities in South Korea and how perceived workplace safety and work satisfaction act as mediators. The 2018 Panel Survey of Employment for the Disabled was used, and we examined 1023 workers with physical disabilities. Path analysis was used to examine the relationships. Results showed that workers whose workplaces provided more disability facilities were significantly more likely to perceive their workplaces as safe and had higher work satisfaction; hence, they were more likely to wish to maintain their present jobs than those whose workplaces offered fewer facilities. However, many workplaces in Korea did not provide any disability facilities. The study provides empirical evidence to support development of policies for improved workplace facilities and work environments for disabled people, in accordance with the UN Agenda.
Do Spanish Students Become More Sustainable after the Implementation of Sustainable Practices by Universities?
Authors: Hamón Leyla Angélica Sandoval , Martinho Ana Paula , Ramos M. Rosário , Aldaz Cecilia Elizabeth Bayas
Published: September 2020

Higher Education Institutions (HEIs) are a critical component to develop and promote sustainable solutions for both society and the planet. A challenge to HEIs is to provide students with the knowledge and skills required to achieve Sustainable Development (SD), as they are important stakeholders. In order for a person to take responsibility for a sustainable future, it is not only important to implement SDs in higher education, but to follow the progress of the individuals’ awareness of the sustainable world and lifestyle. This study aimed to analyze students of Universidad Autónoma de Madrid (UAM), focusing on their attitudes, behaviors, and level of knowledge concerning education for sustainable development (ESD), to better understand the situation of students in terms of learning and applying sustainability. The students’ perception of the University practices and initiatives, as well as pedagogical methodologies for promoting and learning SD, were also examined. An online survey was applied to undergraduate students from several faculties at UAM, and a sample of 504 students returned from a total population of 30,000 students. Descriptive and inferential analyses were carried out and included Chi-square tests, correlation analyses, and ANOVA analyses for independent and repeated measures. The results reveal good levels for the three dimensions (global Index > 3.5), with consistency demonstrating the highest correlation between attitudes and behaviors, although differences between faculties were identified. Knowledge has the highest score among all faculties. In addition, the results point to a need to better communicate the initiatives promoted, as well as to realign some learning methodologies with students’ preferences. The most important contributions of the paper are as follows: Shedding fresh light on the knowledge, attitudes, and behavioral dispositions of university students and improving strategies concerning education in higher education institutions. Furthermore, it is relevant to say that UAM has pushed sustainability in environmental management and education, so it is also important to assess the impact of these initiatives. Our research aimed to help understand how students incorporate sustainability into their attitudes and behaviors, and whether this incorporation depends on the type of faculty. It also makes it possible to verify whether the sustainability measures implemented by universities are identified and applied by their students.