bluuebunny/crossref_metadata_2025 huggingface dataset:
Prevalence of Helicobacter pylori Infection and Diagnostic Methods in the Middle East and North Africa Region
Authors: Alsulaimany Faten A. S. , Awan Zuhier A. , Almohamady Ahmad M. , Koumu Mohammed I. , Yaghmoor Bassam E. , Elhady Sameh S. , Elfaky Mahmoud A.
Published: April 2020

Background and Objectives: Helicobacter pylori (H. pylori) infection is common worldwide and may cause gastroduodenal complications, including cancer. In this review, we examine the prevalence and distribution of various H. pylori genotypes and the risk factors for H. pylori infection, particularly in the Middle East and North Africa (MENA) region. We also introduce different global screening methods and guidelines and compare them to those currently in use in the MENA region. Materials and Methods: We searched the Google Scholar, PubMed, and Saudi Digital Library (SDL) databases for clinical trials and articles published in English. The data collection was mainly focused on MENA countries. However, for H. pylori genotypes and diagnostic methods, studies conducted in other regions or reporting global practices and guidelines were also included to allow a comparison with those in the MENA region. We also included studies examining the prevalence of H. pylori infection in healthy participants. Results: H. pylori infection is highly prevalent in the MENA region, mainly because of the accumulation of risk factors in developing countries. Herein, we highlight a lack of good quality studies on the prevalence of various H. pylori genotypes in the MENA region as well as a need for standard diagnostic methods and screening guidelines. Due to the complications associated with H. pylori, we recommend routine screening for H. pylori infection in all gastroenterology patients admitted in the MENA region. Conclusion: Concerted effort will first be required to validate affordable, non-invasive, and accurate diagnostic methods and to establish local guidelines with adapted cut-off values for the interpretation of the test results.
Genome-Scale Metabolic Network Reconstruction and In Silico Analysis of Hexanoic acid Producing Megasphaera elsdenii
Authors: Lee Na-Rae , Lee Choong Hwan , Lee Dong-Yup , Park Jin-Byung
Published: April 2020

Hexanoic acid and its derivatives have been recently recognized as value-added materials and can be synthesized by several microbes. Of them, Megasphaera elsdenii has been considered as an interesting hexanoic acid producer because of its capability to utilize a variety of carbons sources. However, the cellular metabolism and physiology of M. elsdenii still remain uncharacterized. Therefore, in order to better understand hexanoic acid synthetic metabolism in M. elsdenii, we newly reconstructed its genome-scale metabolic model, iME375, which accounts for 375 genes, 521 reactions, and 443 metabolites. A constraint-based analysis was then employed to evaluate cell growth under various conditions. Subsequently, a flux ratio analysis was conducted to understand the mechanism of bifurcated hexanoic acid synthetic pathways, including the typical fatty acid synthetic pathway via acetyl-CoA and the TCA cycle in a counterclockwise direction through succinate. The resultant metabolic states showed that the highest hexanoic acid production could be achieved when the balanced fractional contribution via acetyl-CoA and succinate in reductive TCA cycle was formed in various cell growth rates. The highest hexanoic acid production was maintained in the most perturbed flux ratio, as phosphoenolpyruvate carboxykinase (pck) enables the bifurcated pathway to form consistent fluxes. Finally, organic acid consuming simulations suggested that succinate can increase both biomass formation and hexanoic acid production.
Investigation of Heterologously Expressed Glucose-6-Phosphate Dehydrogenase Genes in a Yeast zwf1 Deletion
Authors: Heinisch Jürgen J. , Knuesting Johannes , Scheibe Renate
Published: April 2020

Glucose-6-phosphate dehydrogenase (G6PD) is a key enzyme of the oxidative part of the pentose phosphate pathway and serves as the major source of NADPH for metabolic reactions and oxidative stress response in pro- and eukaryotic cells. We here report on a strain of the model yeast Saccharomyces cerevisiae which lacks the G6PD-encoding ZWF1 gene and displays distinct growth retardation on rich and synthetic media, as well as a strongly reduced chronological lifespan. This strain was used as a recipient to introduce plasmid-encoded heterologous G6PD genes, synthesized in the yeast codon usage and expressed under the control of the native PFK2 promotor. Complementation of the hypersensitivity of the zwf1 mutant towards hydrogen peroxide to different degrees was observed for the genes from humans (HsG6PD1), the milk yeast Kluyveromyces lactis (KlZWF1), the bacteria Escherichia coli (EcZWF1) and Leuconostoc mesenteroides (LmZWF1), as well as the genes encoding three different plant G6PD isoforms from Arabidopsis thaliana (AtG6PD1, AtG6PD5, AtG6PD6). The plastidic AtG6PD1 isoform retained its redox-sensitive activity when produced in the yeast as a cytosolic enzyme, demonstrating the suitability of this host for determination of its physiological properties. Mutations precluding the formation of a disulfide bridge in AtG6PD1 abolished its redox-sensitivity but improved its capacity to complement the yeast zwf1 deletion. Given the importance of G6PD in human diseases and plant growth, this heterologous expression system offers a broad range of applications.
Using Real-Life Data to Strengthen the Education of Pharmacy Technician Students: From Student to Research Assistant
Authors: Abrahamsen Bjarke , Hansen Rikke Nørgaard , Bjørn-Christensen Marianne , Druskeit Tina , Rossing Charlotte
Published: April 2020

This commentary is based on the experience of teaching and observations of how pharmacy technician students can expand their perspective on patient safety by using real-life student-gathered patient data collected from community pharmacies. Pharmacy technicians in Denmark work extensively with counselling on the safe and efficient use of medications. Final-year pharmacy technician students can take the elective course in Clinical Pharmacy in Community Pharmacy, which targets the students who wish to work in depth with patient communication and quality assurance in counselling. One assignment that forms part of the course is for students to collect data about patients’ beliefs about medications. Teachers’ observations suggest that when students gather and work with their own data, they change their perspective on patients’ beliefs about medications. It also strengthens the students’ awareness of their responsibility for ensuring patient safety and contributes valid data to research in pharmacy practice.
Thermal Pyrolysis of Polystyrene Aided by a Nitroxide End-Functionality. Experiments and Modeling
Authors: Ordaz-Quintero Almendra , Monroy-Alonso Antonio , Saldívar-Guerra Enrique
Published: April 2020

The thermal pyrolysis of polystyrene (PS) is gaining importance as the social pressure for achieving a circular economy is growing; moreover, the recovery of styrene monomer in such a process is especially relevant. In this study, a simple thermal pyrolysis process in the temperature range of 390–450 °C is developed. A working hypothesis is that by using a nitroxide-end functionalized PS (PS-T or dormant polymer), the initiation process for the production of monomer (unzipping) during the PS pyrolysis could be enhanced due to the tendency of the PS-T to activate at the nitroxide end. Two types of PS were used in this work, the first one was synthesized by free-radical polymerization (FRP-dead polymer) and the second by nitroxide-mediated polymerization (NMP) using three levels of nitroxide to initiator ratio: 1.3, 1.1, and 0.9. Analysis of the recovered products of the pyrolysis by gas-mass spectroscopy shows that the yield of styrene increases from ∼33% in the case of dead polymer to ∼38.5% for PS-T. A kinetic and mathematical model for the pyrolysis of dead and dormant polymer is proposed and solved by the method of moments. After a parameter sensitivity study and data fitting, the model is capable of explaining the main experimental trends observed.
An Autonomous Power-Frequency Control Strategy Based on Load Virtual Synchronous Generator
Authors: Han Jiangbei , Liu Zhijian , Liang Ning , Song Qi , Li Pengcheng
Published: April 2020

With the increasing penetration of the hybrid AC/DC microgrid in power systems, an inertia decrease of the microgrid is caused. Many scholars have put forward the concept of a virtual synchronous generator, which enables the converters of the microgrid to possess the characteristics of a synchronous generator, thus providing inertia support for the microgrid. Nevertheless, the problems of active power oscillation and unbalance would be serious when multiple virtual synchronous generators (VSGs) operate in the microgrid. To conquer these problems, a VSG-based autonomous power-frequency control strategy is proposed, which not only independently allocates the power grid capacity according to the load capacity, but also effectively suppresses the active power oscillation. In addition, by establishing a dynamic small-signal model of the microgrid, the dynamic stability of the proposed control strategy in the microgrid is verified, and further reveals the leading role of the VSG and filter in the dynamic stability of microgrids. Finally, the feasibility and effectiveness of the proposed control strategy are validated by the simulation results.
Mathematical Model Based on the Shape of Pulse Waves Measured at a Single Spot for the Non-Invasive Prediction of Blood Pressure
Authors: Peter Lukas , Kracik Jan , Cerny Martin , Noury Norbert , Polzer Stanislav
Published: April 2020

Background: Continuous non-invasive blood pressure (BP) measurement is a desired virtue in clinical practice. Unfortunately, current systems do not allow one for continuous, reliable BP measurement for more than a few hours per day, and they often require a complicated set of sensors to provide the necessary biosignals. Therefore we investigated the possibility of proposing a computational model that would predict the BP from pulse waves recorded in a single spot. Methods: Two experimental circuits were created. One containing a simple plastic tube for model development and a second with a silicone molded patient-specific arterial tree model. The first model served for the measuring of pulse waves under various BP (70–270 mmHg) and heart rate (60–190 beats per minute) values. Four different computational models were used to estimate the BP values from the diastolic time. The most accurate model was further validated using data from the latter experimental circuit containing a molded patient-specific silicone arterial tree. The measured data were averaged over a window of one, three, and five cycles. Two models based on pulse arrival time (PAT) were also analyzed for comparison. Results: The most accurate model exhibits a correlation coefficient of r = 0.967. The Bland–Altman plot revealed standard deviations (SD) between the model predictions and measurement of 10, 8.3, and 7.5 mmHg for the systolic BP and 8.7, 7 and 6.3 mmHg for the diastolic BP (both pressures calculated for the averaging windows of one, three, and five cycles, respectively). The best of the used PAT based model exhibited a SD of 17, 16, and 15 mmHg for the systolic BP and 14, 13, and 12 mmHg for the diastolic BP for the same averaging windows. Discussion: The proposed model showed its capability to predict BP accurately from the shape of the pulse wave measured at a single spot. Its SD was about 50% lower compared to the PAT based models which met the requirements of the Association for the Advancement of Medical Instrumentation.
A Review of Methane Activation Reactions by Halogenation: Catalysis, Mechanism, Kinetics, Modeling, and Reactors
Authors: Bajec David , Grom Matic , Lašič Jurković Damjan , Kostyniuk Andrii , Huš Matej , Grilc Miha , Likozar Blaž , Pohar Andrej
Published: April 2020

Methane is the central component of natural gas, which is globally one of the most abundant feedstocks. Due to its strong C–H bond, methane activation is difficult, and its conversion into value-added chemicals and fuels has therefore been the pot of gold in the industry and academia for many years. Industrially, halogenation of methane is one of the most promising methane conversion routes, which is why this paper presents a comprehensive review of the literature on methane activation by halogenation. Homogeneous gas phase reactions and their pertinent reaction mechanisms and kinetics are presented as well as microkinetic models for methane reaction with chlorine, bromine, and iodine. The catalysts for non-oxidative and oxidative catalytic halogenation were reviewed for their activity and selectivity as well as their catalytic action. The highly reactive products of methane halogenation reactions are often converted to other chemicals in the same process, and these multi-step processes were reviewed in a separate section. Recent advances in the available computational power have made the use of the ab initio calculations (such as density functional theory) routine, allowing for in silico calculations of energy profiles, which include all stable intermediates and the transition states linking them. The available literature on this subject is presented. Lastly, green processes and the production of fuels as well as some unconventional methods for methane activation using ultrasound, plasma, superacids, and light are also reviewed.
Financial Bubbles: A Study of Co-Explosivity in the Cryptocurrency Market
Authors: Agosto Arianna , Cafferata Alessia
Published: April 2020

Cryptocurrencies have recently captured the interest of the econometric literature, with several works trying to address the existence of bubbles in the price dynamics of Bitcoins and other cryptoassets. Extremely rapid price accelerations, often referred to as explosive behaviors, followed by drastic drops pose high risks to investors. From a risk management perspective, testing the explosiveness of individual cryptocurrency time series is not the only crucial issue. Investigating co-explosivity in the cryptoassets, i.e., whether explosivity in one cryptocurrency leads to explosivity in other cryptocurrencies, allows indeed to take into account possible shock propagation channels and improve the prediction of market collapses. To this aim, our paper investigates the relationships between the explosive behaviors of cryptocurrencies through a unit root testing approach.
Flexible Hierarchical Gaussian Mixture Model for High-Resolution Remote Sensing Image Segmentation
Authors: Shi Xue , Li Yu , Zhao Quanhua
Published: April 2020

The Gaussian mixture model (GMM) plays an important role in image segmentation, but the difficulty of GMM for modeling asymmetric, heavy-tailed, or multimodal distributions of pixel intensities significantly limits its application. One effective way to improve the segmentation accuracy is to accurately model the statistical distributions of pixel intensities. In this study, an innovative high-resolution remote sensing image segmentation algorithm is proposed based on a flexible hierarchical GMM (HGMM). The components are first defined by the weighted sums of elements, in order to accurately model the complicated distributions of pixel intensities in object regions. The elements of components are defined by Gaussian distributions to model the distributions of pixel intensities in local regions of the object region. Following the Bayesian theorem, the segmentation model is then built by combining the HGMM and the prior distributions of parameters. Finally, a novel birth or death Markov chain Monte Carlo (BDMCMC) is designed to simulate the segmentation model, which can automatically determine the number of elements and flexibly model complex distributions of pixel intensities. Experiments were implemented on simulated and real high-resolution remote sensing images. The results show that the proposed algorithm is able to flexibly model the complicated distributions and accurately segment images.
Aerial LiDAR Data Augmentation for Direct Point-Cloud Visualisation
Authors: Bohak Ciril , Slemenik Matej , Kordež Jaka , Marolt Matija
Published: April 2020

Direct point-cloud visualisation is a common approach for visualising large datasets of aerial terrain LiDAR scans. However, because of the limitations of the acquisition technique, such visualisations often lack the desired visual appeal and quality, mostly because certain types of objects are incomplete or entirely missing (e.g., missing water surfaces, missing building walls and missing parts of the terrain). To improve the quality of direct LiDAR point-cloud rendering, we present a point-cloud processing pipeline that uses data fusion to augment the data with additional points on water surfaces, building walls and terrain through the use of vector maps of water surfaces and building outlines. In the last step of the pipeline, we also add colour information, and calculate point normals for illumination of individual points to make the final visualisation more visually appealing. We evaluate our approach on several parts of the Slovenian LiDAR dataset.
Rigorous Co-Registration of KOMPSAT-3 Multispectral and Panchromatic Images for Pan-Sharpening Image Fusion
Authors: Lee Changno , Oh Jaehong
Published: April 2020

KOMPSAT-3, a Korean earth observing satellite, provides the panchromatic (PAN) band and four multispectral (MS) bands. They can be fused to obtain a pan-sharpened image of higher resolution in both the spectral and spatial domain, which is more informative and interpretative for visual inspection. In KOMPSAT-3 Advanced Earth Imaging Sensor System (AEISS) uni-focal camera system, the precise sensor alignment is a prerequisite for the fusion of MS and PAN images because MS and PAN Charge-Coupled Device (CCD) sensors are installed with certain offsets. In addition, exterior effects associated with the ephemeris and terrain elevation lead to the geometric discrepancy between MS and PAN images. Therefore, we propose a rigorous co-registration of KOMPSAT-3 MS and PAN images based on physical sensor modeling. We evaluated the impacts of CCD line offsets, ephemeris, and terrain elevation on the difference in image coordinates. The analysis enables precise co-registration modeling between MS and PAN images. An experiment with KOMPSAT-3 images produced negligible geometric discrepancy between MS and PAN images.
Monitoring Winter Stress Vulnerability of High-Latitude Understory Vegetation Using Intraspecific Trait Variability and Remote Sensing Approaches
Authors: Ritz Elmar , Bjerke Jarle W. , Tømmervik Hans
Published: April 2020

In this study, we focused on three species that have proven to be vulnerable to winter stress: Empetrum nigrum, Vaccinium vitis-idaea and Hylocomium splendens. Our objective was to determine plant traits suitable for monitoring plant stress as well as trait shifts during spring. To this end, we used a combination of active and passive handheld normalized difference vegetation index (NDVI) sensors, RGB indices derived from ordinary cameras, an optical chlorophyll and flavonol sensor (Dualex), and common plant traits that are sensitive to winter stress, i.e. height, specific leaf area (SLA). Our results indicate that NDVI is a good predictor for plant stress, as it correlates well with height (r = 0.70, p < 0.001) and chlorophyll content (r = 0.63, p < 0.001). NDVI is also related to soil depth (r = 0.45, p < 0.001) as well as to plant stress levels based on observations in the field (r = −0.60, p < 0.001). Flavonol content and SLA remained relatively stable during spring. Our results confirm a multi-method approach using NDVI data from the Sentinel-2 satellite and active near-remote sensing devices to determine the contribution of understory vegetation to the total ecosystem greenness. We identified low soil depth to be the major stressor for understory vegetation in the studied plots. The RGB indices were good proxies to detect plant stress (e.g. Channel G%: r = −0.77, p < 0.001) and showed high correlation with NDVI (r = 0.75, p < 0.001). Ordinary cameras and modified cameras with the infrared filter removed were found to perform equally well.
Dynamic Hand Gesture Recognition Based on a Leap Motion Controller and Two-Layer Bidirectional Recurrent Neural Network
Authors: Yang Linchu , Chen Ji’an , Zhu Weihang
Published: April 2020

Dynamic hand gesture recognition is one of the most significant tools for human–computer interaction. In order to improve the accuracy of the dynamic hand gesture recognition, in this paper, a two-layer Bidirectional Recurrent Neural Network for the recognition of dynamic hand gestures from a Leap Motion Controller (LMC) is proposed. In addition, based on LMC, an efficient way to capture the dynamic hand gestures is identified. Dynamic hand gestures are represented by sets of feature vectors from the LMC. The proposed system has been tested on the American Sign Language (ASL) datasets with 360 samples and 480 samples, and the Handicraft-Gesture dataset, respectively. On the ASL dataset with 360 samples, the system achieves accuracies of 100% and 96.3% on the training and testing sets. On the ASL dataset with 480 samples, the system achieves accuracies of 100% and 95.2%. On the Handicraft-Gesture dataset, the system achieves accuracies of 100% and 96.7%. In addition, 5-fold, 10-fold, and Leave-One-Out cross-validation are performed on these datasets. The accuracies are 93.33%, 94.1%, and 98.33% (360 samples), 93.75%, 93.5%, and 98.13% (480 samples), and 88.66%, 90%, and 92% on ASL and Handicraft-Gesture datasets, respectively. The developed system demonstrates similar or better performance compared to other approaches in the literature.
Single-Coil Eddy Current Sensors and Their Application for Monitoring the Dangerous States of Gas-Turbine Engines
Authors: Borovik Sergey , Sekisov Yuriy
Published: April 2020

The creation and exploitation of gas turbine engines (GTE) often involve two mutually exclusive tasks related to ensuring the highest reliability while achieving a good economic and environmental performance of the power plant. The value of the radial clearance between the blade tips of the compressor or turbine and the stator is a parameter that has a significant impact on the efficiency and safety of the GTE. However, the radial displacements that form tip clearances are only one of the components of the displacements made by GTE elements due to the action of power loads and thermal deformations during engines’ operation. The impact of loads in conjunction with natural aging is also the reason for the wear of the GTE’s structural elements (for example, bearing assemblies) and the loss of their mechanical strength. The article provides an overview of the methods and tools for monitoring the dangerous states of the GTE (blade tips clearances, impellers and shafts displacements, debris detecting in lubrication system) based on the single-coil eddy current sensor, which remains operational at the temperatures above 1200 °C. The examples of practical application of the systems with such sensors in bench tests of the GTE are given.
High Sensitivity Refractive Index Sensor Based on the Excitation of Long-Range Surface Plasmon Polaritons in H-Shaped Optical Fiber
Authors: Gomez-Cardona Nelson , Reyes-Vera Erick , Torres Pedro
Published: April 2020

In this paper, we propose and numerically analyze a novel design for a high sensitivity refractive index (RI) sensor based on long-range surface plasmon resonance in H-shaped microstructured optical fiber with symmetrical dielectric–metal–dielectric waveguide (DMDW). The influences of geometrical and optical characteristics of the DMDW on the sensor performance are investigated theoretically. A large RI analyte range from 1.33 to 1.39 is evaluated to study the sensing characteristics of the proposed structure. The obtained results show that the DMDW improves the coupling between the fiber core mode and the plasmonic mode. The best configuration shows 27 nm of full width at half maximum with a resolution close to 1.3 × 10 − 5 nm, a high sensitivity of 7540 nm/RIU and a figure of merit of 280 RIU − 1 . Additionally, the proposed device has potential for multi-analyte sensing and self-reference when dissimilar DMDWs are deposited on the inner walls of the side holes. The proposed sensor structure is simple and presents very competitive sensing parameters, which demonstrates that this device is a promising alternative and could be used in a wide range of application areas.
Optical Fiber Temperature Sensors and Their Biomedical Applications
Authors: Roriz Paulo , Silva Susana , Frazão Orlando , Novais Susana
Published: April 2020

The use of sensors in the real world is on the rise, providing information on medical diagnostics for healthcare and improving quality of life. Optical fiber sensors, as a result of their unique properties (small dimensions, capability of multiplexing, chemical inertness, and immunity to electromagnetic fields) have found wide applications, ranging from structural health monitoring to biomedical and point-of-care instrumentation. Furthermore, these sensors usually have good linearity, rapid response for real-time monitoring, and high sensitivity to external perturbations. Optical fiber sensors, thus, present several features that make them extremely attractive for a wide variety of applications, especially biomedical applications. This paper reviews achievements in the area of temperature optical fiber sensors, different configurations of the sensors reported over the last five years, and application of this technology in biomedical applications.
New Global Referencing Approach in a Camera-LCD Micro Positioning System
Authors: de Francisco Ortiz Óscar , Ortiz Irene , Bueno Antonio
Published: April 2020

In any precision manufacturing process, positioning systems play a very important role in achieving a quality product. As a new approach to current systems, camera-LCD positioning systems are a new technology that can provide substantial improvements enabling better accuracy and repeatability. However, in order to provide stability to the system a global positioning system is required. This paper presents an improvement of a positioning system based on the treatment of images on an LCD in which a new algorithm with absolute reference has been implemented. The method is based on basic geometry and linear algebra applied to computer vision. The algorithm determines the spiral center using an image taken at any point. Consequently, the system constantly knows its position and does not lose its reference. Several modifications of the algorithm are proposed and compared. The simulation and test of the algorithm provide an important improvement in the reliability and stability of the positioning system providing errors of microns for the calculation of the global position used by the algorithm.
Position and Attitude Estimation Method Integrating Visual Odometer and GPS
Authors: Yang Yu , Shen Qiang , Li Jie , Deng Zilong , Wang Hanyu , Gao Xiao
Published: April 2020

The monocular visual odometer is widely used in the navigation of robots and vehicles, but it has defects of the unknown scale of the estimated trajectory. In this paper, we presented a position and attitude estimation method, integrating the visual odometer and Global Position System (GPS), where the GPS positioning results were taken as a reference to minimize the trajectory estimation error of visual odometer and derive the attitude of the vehicle. Hardware-in-the-loop simulations were carried out; the experimental results showed that the positioning error of the proposed method was less than 1 m, and the accuracy and robustness of the attitude estimation results were better than those of the state-of-art vision-based attitude estimation methods.
Study on Retrofitted Masonry Elements under Shear Using Digital Image Correlation
Authors: Torres Benjamín , Varona Francisco B. , Baeza F. Javier , Bru David , Ivorra Salvador
Published: April 2020

Architectural heritage is usually built with masonry structures, which present problems under lateral in-plane loading conditions, such as wind pressure or earthquakes. In order to improve the shear behavior of masonry, the use of a fabric-reinforced cementitious matrix (FRCM) has become an interesting solution because of its synergy of mechanical properties and compatibility with masonry substrates. For a proper structural evaluation, the mechanical behavior of reinforced masonry and the FRCM itself needs to be characterized. Hence, a numerical model to evaluate the FRCM reinforcement requires some mechanical parameters that may be difficult to obtain. In this sense, the shear behavior of masonry can be evaluated by means of diagonal tension tests on small specimens (71 × 71 cm). In this work, a digital image correlation (DIC) monitoring system was used to control displacements and cracking patterns of masonry specimens under shear stress (induced by diagonal tension with FRCM layers) applied to one or two sides. In addition, the mechanical behavior of FRCM coupons under uniaxial tensile tests was also registered with DIC. The displacement measurements obtained by DIC were validated with the measurements registered with LVDT. Unlike LVDT-based techniques, DIC monitoring allowed us to measure deformations in masonry during the full test, detecting crack initiation even before it was visible to the eye.
Detection and Differentiation of Volatile Compound Profiles in Roasted Coffee Arabica Beans from Different Countries Using an Electronic Nose and GC-MS
Authors: Marek Gancarz , Dobrzański Bohdan , Oniszczuk Tomasz , Combrzyński Maciej , Ćwikła Daniel , Rusinek Robert
Published: April 2020

This paper describes the possibility of electronic nose-based detection and discrimination of volatile compound profiles of coffee from different countries roasted in a Gothot roaster under identical time and thermal regimes. The material used in the study was roasted Arabica coffee beans from Brazil, Ethiopia, Guatemala, Costa Rica, and Peru. The analyses were carried out with the use of the Agrinose electronic nose designed and constructed at the Institute of Agrophysics of the Polish Academy of Sciences in Lublin. The results of the volatile compound profile analysis provided by the Agrinose device were verified with the GC-MS technique. Chemometric tests demonstrated a dominant role of alcohols, acids, aldehydes, azines, and hydrazides in the coffee volatile compound profile. The differences in their content had an impact on the odor profile of the coffees originating from the different countries. High content of pyridine from the group of azines was detected in the coffee from Peru and Brazil despite the same roasting conditions. The results of the Agrinose analysis of volatile substances were consistent and correlated with the GC-MS results. This suggests that the Agrinose is a promising tool for selection of coffees based on their volatile compound profile.
Surface Morphology Analysis of Metallic Structures Formed on Flexible Textile Composite Substrates
Authors: Korzeniewska Ewa , Sekulska-Nalewajko Joanna , Gocławski Jarosław , Rosik Radosław , Szczęsny Artur , Starowicz Zbigniew
Published: April 2020

This paper compares methods for measuring selected morphological features on the surface of thin metallic layers applied to flexible textile substrates. The methods were tested on a silver layer with a thickness of several hundred nanometers, which was applied to a textile composite with the trade name Cordura. Measurements were carried out at the micro scale using both optical coherent tomography (OCT) and the traditional contact method of using a profilometer. Measurements at the micro-scale proved the superiority of the OCT method over the contact method. The method of contactless measurement employs a dedicated algorithm for three-dimensional surface image analysis and does not affect the delicate surface structure of the measured layer in any way. Assessment of the surface profile of textile substrates and the thin films created on them, is important when estimating the contact angle, wetting behavior, or mechanical durability of the created metallic structure that can be used as the electrodes or elements of wearable electronics or textronics systems.
Mining Massive E-Health Data Streams for IoMT Enabled Healthcare Systems
Authors: Toor Affan Ahmed , Usman Muhammad , Younas Farah , M. Fong Alvis Cheuk , Khan Sajid Ali , Fong Simon
Published: April 2020

With the increasing popularity of the Internet-of-Medical-Things (IoMT) and smart devices, huge volumes of data streams have been generated. This study aims to address the concept drift, which is a major challenge in the processing of voluminous data streams. Concept drift refers to overtime change in data distribution. It may occur in the medical domain, for example the medical sensors measuring for general healthcare or rehabilitation, which may switch their roles for ICU emergency operations when required. Detecting concept drifts becomes trickier when the class distributions in data are skewed, which is often true for medical sensors e-health data. Reactive Drift Detection Method (RDDM) is an efficient method for detecting long concepts. However, RDDM has a high error rate, and it does not handle class imbalance. We propose an Enhanced Reactive Drift Detection Method (ERDDM), which systematically generates strategies to handle concept drift with class imbalance in data streams. We conducted experiments to compare ERDDM with three contemporary techniques in terms of prediction error, drift detection delay, latency, and ability to handle data imbalance. The experimentation was done in Massive Online Analysis (MOA) on 48 synthetic datasets customized to possess the capabilities of data streams. ERDDM can handle abrupt and gradual drifts and performs better than all benchmarks in almost all experiments.
What Should Be Considered when Developing ICT-Integrated Classroom Models for a Developing Country?
Authors: Cha Hyunjin , Park Taejung , Seo Jongwon
Published: April 2020

This study aims to identify factors to be considered when developing Information and Communication Technology (ICT)-integrated classroom models and to suggest a conceptual framework for considering more appropriate classroom models, tailored to the environments and needs of each developing country. In-depth interviews were conducted with experts, yielding many factors to be taken into account when integrating ICT in various educational contexts of developing countries. The factors are categorized into five domains: current status and relevant policies in ICT education, ODA (Official Development Assistance) goals and priority setting, infrastructure and technical challenges, pedagogical methods, and educational resources. Based on the recommendations elicited for the five categories, we suggest a conceptual framework that provides practical guidance on the criteria for selecting classroom models suited to each partner country’s environments and contexts. This study also draws implications from the interviews for classroom design guidelines related to hardware and infrastructure, to improve the sustainability of ICT-integrated classroom projects.
Buyer-Driven Knowledge Transfer Activities to Enhance Organizational Sustainability of Suppliers
Authors: Awan Usama , Khattak Amira , Rabbani Sajeela , Dhir Amandeep
Published: April 2020

Despite the significant contribution of buyer-driven knowledge transfer activities (BDKTAs) to innovation and operational performance, studies that analyze social sustainability in manufacturing (suppliers) firms are still scarce. This paper examines the mediation relationship of knowledge acquisition and investment in environmental management between BDKTAs and social performance improvements (SPIs). The paper contributes to the understanding of buyer knowledge transfer activities, with a focus on the knowledge acquisition capabilities and investments in environmental management, and the effect on SPIs. The hypotheses were examined with partial least squares structural equation modeling (PLS-SEM) with data collected from 239 firms. Buyer knowledge transfer activities are likely to increase the willingness of suppliers to make specific environmental investments into operations in waste reduction procedures, the recycling of materials, and pollution prevention training of employees. We proposed that buyer knowledge transfer activities are necessary to survive and grow and thus there is a need to acquire knowledge resources to achieve organizational sustainability. Buyer knowledge transfer activities are necessary to make investment decisions in environmental management programs. Firms that focus on buyer knowledge transfer activities and internal investments into environmental management can attain sustainability objectives.
Freight Mode Coordination in China: From the Perspective of Regional Differences
Authors: Gao Yuee , Zou Xin , Chen Rujia , Ma Yanli , Li Chengjiang , Zhang Yaping
Published: April 2020

Studying the coordination of varied freight modes from the perspective of geographic regions is conducive to understanding the regional differences, and this can provide effective countermeasures and suggestions for the sustainable and coordinated development of freight transport. To reflect on the effects of regional differences in the coordination of freight modes, we divided China into four regions: The East, Central, West, and Northeast. We examined freight mode coordination in terms of region and analysed the coordination of freight modes from three aspects: one within a single freight mode system, between varied freight modes, and among freight modes and the economy in different regions. We selected 19 freight indexes based on China’s freight data from 2008 to 2017, and determined the relationship between the freight index and economic index gross domestic product (GDP) growth rate by means of stability, co-integration, and the Granger causality test. The coordination models within a single freight mode and among varied freight modes were established, and we conducted spatial autocorrelation between the freight mode and the economy. The results demonstrated that in the four regions of China, the single-freight mode had coordination of over 0.80; the coordination between waterway and aviation freight transport was over 0.83; and the coordination of varied freight modes in the Eastern region exceeded 0.78, with good overall coordination. Among the four regions, the spatial correlation between the Eastern and Western regions was not significant, while the correlation between the Central and Northeast regions was significant. The model and analysis methods established in this study were feasible and effective. In view of the universality of the model, it can be easily applied and generalized in or out of China.
Improving Animal Health on Organic Dairy Farms: Stakeholder Views on Policy Options
Authors: Krieger Margret , Jones Philip J. , Blanco-Penedo Isabel , Duval Julie E. , Emanuelson Ulf , Hoischen-Taubner Susanne , Sjöström Karin , Sundrum Albert
Published: April 2020

Although ensuring good animal health is a stated aim of organic livestock farming and an important reason why consumers purchase organic products, the health states actually achieved are comparable to those in conventional farming. Unfortunately, there have been no studies to date that have assessed stakeholder views on different policy options for improving animal health on organic dairy farms. To address this deficit, stakeholder consultations were conducted in four European countries, involving 39 supply-chain stakeholders (farmers, advisors, veterinarians, inspectors, processors, and retailers). Stakeholders were encouraged to discuss different ways, including policy change, of improving organic health states. Acknowledging the need for further health improvements in organic dairy herds, stakeholders generally favoured establishing outcome-oriented animal health requirements as a way of achieving this. However, as a result of differing priorities for animal health improvement, there was disagreement on questions such as: who should be responsible for assessing animal health status on organic farms; and how to define and implement minimum health requirements. The results of the study suggest that future research must fully explore the opportunities and risks of different policy options and also suggest ways to overcome the divergence of stakeholders’ interests in public debates.
The Comparative Analysis of the Adaptability Level of Municipalities in the Nysa Kłodzka Sub-Basin to Flood Hazard
Authors: Dumieński Grzegorz , Mruklik Agnieszka , Tiukało Andrzej , Bedryj Marta
Published: April 2020

A municipality is a basic local government unit (LGU) in Poland. It is responsible for the safety of its citizens, especially in circumstances of flood hazard. A municipality is a unique social-ecological system (SES), distinguished by its ability to adapt to flood hazard. It is impossible to specify the conditions a municipality has to reach to achieve the highest adaptability to flood hazard, however, it is possible to assign a level of adaptability to a municipality, one that corresponds to the position of a given municipality among the population of assessed municipalities threatened by floods. Therefore, a tool was developed to rank municipalities by their adaptability on the assumption that the assessment of municipal adaptability was influenced by 15 selected features. The research was carried out using data from the period of 2010–2016 for 18 municipalities-SESs located in the Nysa Kłodzka sub-basin. It was indicated that municipalities located in the higher course of the river possess higher levels of adaptability. At the same time, the size of a flood stands for each municipality position with regards to the synthetic adaptability index (SAI).
Does High-Speed Rail Influence Urban Dynamics and Land Pricing?
Authors: Rungskunroch Panrawee , Yang Yuwen , Kaewunruen Sakdirat
Published: April 2020

At present, many countries around the world have significantly invested in sustainable transportation systems, especially for high-speed rail (HSR) infrastructures, since they are believed to improve economies, and regenerate regional and business growth. In this study, we focus on economic growth, dynamic land use, and urban mobility. The emphasis is placed on testing a hypothesis about whether HSRs can enable socio-economic development. Real case studies using big data from large cities in China, namely Shanghai province and Minhang districts, are taken into account. Socio-technical information such as employment rate, property pricing, and agglomeration in the country’s economy is collected from the China Statistics Bureau and the China Academy of Railway Sciences for analyses. This research aims to re-examine practical factors resulting from HSR’s impact on urban areas by using ANOVA analysis and dummy variable regression to analyse urban dynamics and property pricing. In addition, this study enhances the prediction outcomes that lead to urban planning strategies for the business area. The results reveal that there are various effects (i.e., regional accessibility, city development plans, and so on) required to enable the success of HSR infrastructure in order to enrich urban dynamics and land pricing. This paper also highlights critical perspectives towards sustainability, which are vital to social and economic impacts. In addition, this study provides crucial perspectives on sustainable developments for future HSR projects.
The Nexus between Credit Channels and Farm Household Vulnerability to Poverty: Evidence from Rural China
Authors: Sun Hong , Li Xiaohong , Li Wenjing
Published: April 2020

It is well known that finance is at the core of economic activities, and rural finance is an important force for agricultural development, rural economic growth, and farmer income growth, but how rural credit affects vulnerability to poverty of farm households is not yet known. The study on the nexus between the credit channels and vulnerability to poverty can not only realize targeted poverty alleviation but also promote sustainable rural development. This study measures vulnerability to poverty of Chinese farm households by three-stage feasible generalized least squares (FGLS) and tests for the impact of two credit channels on farm household’s vulnerability to poverty based on China Household Finance Survey data. We mainly found that the proportion of structural poverty in western areas is comparatively large, and risky poverty of farm households in eastern areas is relatively serious. The high education cost may be an important factor in farm household poverty; the cost-effectiveness of education is higher than that of earnings. Farm household vulnerability to poverty with folk loans is 0.2% higher than that of farm households without private credit; however, this is not significant. Farm household vulnerability to poverty with bank credit is 0.4% lower than households without bank credit, which is significant. For farm households who have a higher level of vulnerability to poverty, the effect of bank credit on reducing vulnerability to poverty is greater. Moreover, we replaced the vulnerability-to-poverty variable with a more rigid indicator to test the relationship between the credit channels and vulnerability to poverty and got the same results as before.
Spatial and Multicriteria Analysis of Dimension Stones and Crushed Rocks Quarrying in the Context of Sustainable Regional Development: Case Study of Lower Silesia (Poland)
Authors: Blachowski Jan , Buczyńska Anna
Published: April 2020

This study aimed to analyze and assess the spatial and temporal trends in distribution of reserves and production of igneous and metamorphic dimension stones and crushed rocks in the Lower Silesia region, which with 90% of total supply is the key source region of these rock raw materials in Poland. The research utilized descriptive statistics to examine temporal variations of production, as well as to determine sufficiency of these resources for four different scenarios and seven main lithological groups of rocks. Spatial statistics in the geographic information system was used to map changes in spatial distribution of production with the density function, as well as to determine areas of highest concentration in the 2010–2018 period. Then, 169 communes in the region were assessed using the multicriteria analytical hierarchy process (AHP) technique to identify local communities prospective for development of this mining sector. Strong, positive correlation (r = 0.645) between year to year production change with annual rate of gross domestic product was determined. Sufficiency of economic reserves was estimated, in four scenarios, as being the lowest for melaphyre and porphyry (25–49 years), and the highest for marble (380–389 years). Reserves of basalt and amphibolite should last for approximately 50 years (32–60 and 36–67 years, respectively), granite for 82 to 110 years, and gabbro and gneiss for over 100 years (78–159 and 76–189 years, respectively). Maps revealed a possible trend of increasing production in quarries located in the central and eastern parts of Lower Silesia, whereas multicriteria analysis allowed for the identification of nine communes with the highest potential for rock raw material quarrying. The practical outcome of this study is a knowledge database for authorities, upon which sustainable management of regional rock raw materials can be based in the context of economic, social, and environmental impacts of their extraction.