bluuebunny/crossref_metadata_2025 huggingface dataset:
A Study of Some Mechanical Properties of a Category of Composites with a Hybrid Matrix and Natural Reinforcements
Authors: Stănescu Marius Marinel , Bolcu Dumitru
Published: March 2019

The current composite materials must meet a double challenge, one that involves obtaining mechanical properties suitable to the field of activity in which they are used and another one, equally important, that requires that they be renewable. In this paper, we have obtained a category of composite materials that have natural reinforcements (fabrics of flax, cotton, hemp, cattail leaves, and wheat straw). As a matrix, we have used three types of hybrid resin, in the composition of which we used the natural resin dammar, in different majority volume proportions. The differences, up to 100%, were represented by epoxy resin and its associated reinforcement, to generate a quick process of polymerization. We have measured certain mechanical properties and the damping properties of the three types of hybrid resin and of the composite materials under study. Based on these properties, we point out a few fields of activity where these composite materials can be used.
An Intelligent Fault Diagnosis Method Using GRU Neural Network towards Sequential Data in Dynamic Processes
Authors: Yuan Jing , Tian Ying
Published: March 2019

Intelligent fault diagnosis is a promising tool to deal with industrial big data due to its ability in rapidly and efficiently processing collected signals and providing accurate diagnosis results. In traditional static intelligent diagnosis methods, however, the correlation between sequential data is neglected, and the features of raw data cannot be effectively extracted. Therefore, this paper proposes a three-stage fault diagnosis method based on a gate recurrent unit (GRU) network. The raw data is divided into several sequence units by first using a moving horizon as the input of GRU. In this way, we can intercept the sequence to get information as needed. Then, the GRU deep network is established through batch normalization (BN) algorithm to extract the dynamic feature from the sequence units effectively. Finally, the softmax regression is employed to classify faults based on dynamic features. Thus, the diagnosis result is obtained with a probabilistic explanation. Two chemical processes validate the proposed method: Tennessee Eastman (TE) benchmark process as well as para-xylene (PX) oxidation process. In the case of TE, the diagnosis results demonstrate the proposed method is superior to conventional methods. Furthermore, in the case of PX oxidation, the result shows that the proposed method also has an exceptional effect with a little historical data.
Alignment between the New Zealand Health Star Rating System and the Chilean Warning Label System
Authors: Söderlund Fredrik , Eyles Helen , Mhurchu Cliona Ni
Published: March 2019

Background: Unhealthy diet is the leading preventable risk for poor health in New Zealand. [...]
Knowledge about Osteoporosis Risk Prevention in Young and Post-Menopausal Women in Palmerston North, New Zealand
Authors: Reynolds E. , Schraders K. , Zatta G. , Weber J. , Coad J. , Kruger M. , Thomson J.
Published: March 2019

Background: Critical determinants of bone health are genetics, diet and physical activity.Women face challenges to the modifiable risk factors [...]
Do Lactose Intolerant Individuals Efficiently Absorb Protein from Acute Milk Consumption?
Authors: Prodhan Utpal Kumar , Shrestha Aahana , Karlström Helga Josefin , Martinsson Jakob Andre , Nilsson Nils Jimmy , Barnett Mathew Philip Greig , Milan Amber Marie , Cameron-Smith David
Published: March 2019

Background: Lactose intolerance is due to the malabsorption of lactose, the predominant sugarpresent in milk [...]
A Retrospective and Cross-Sectional Study to Evaluate the Effect of Acculturation on the Dietary Calcium Intake and Predictors of Bone Mineral Density in Filipino Women Recently Immigrated to New Zealand
Authors: Monzales Rosario , Kruger M.C. , Burlingame B. , Norrish L. , Hurst P.R. von
Published: March 2019

Background: Filipinos in New Zealand have [...]
Feminist Theology, Plant Names, and Power
Authors: Craigo-Snell Shannon
Published: March 2019

Decades ago, feminist theologians emphasized the importance of “naming” in achieving justice. They argued not having a name for something makes it more difficult to understand its influence on our lives. Naming elements of our lived reality (including patriarchy, specific barriers to women’s flourishing, the patterns and values of relationships, and so forth) was seen as key to claiming the power to name ourselves and thereby claiming agency in a world of complex relations and interlocking injustices. Colonialist epistemologies and anthropologies that shape dominant culture in the U.S. prioritize universal over local knowledge, text-based propositions about objects rather than relational knowledge of subjects. While recent science draws attention to the interconnection and interdependence of human persons and our biological environment, there is little value given to local environmental knowledge of plant life. Feminist wisdom implies that this loss of naming for our own environment entails a loss of agency as well as a loss of understanding. Bringing feminist theology into conversation with science and indigenous ways of knowing, this paper argues that we cannot name ourselves if we do not have words for the plants with which we are interconnected on every level from basic sustenance to daily interaction to complex microbiology.
Deriving High Spatial-Resolution Coastal Topography From Sub-meter Satellite Stereo Imagery
Authors: Almeida Luís Pedro , Almar Rafael , Bergsma Erwin W. J. , Berthier Etienne , Baptista Paulo , Garel Erwan , Dada Olusegun A. , Alves Bruna
Published: March 2019

High spatial resolution coastal Digital Elevation Models (DEMs) are crucial to assess coastal vulnerability and hazards such as beach erosion, sedimentation, or inundation due to storm surges and sea level rise. This paper explores the possibility to use high spatial-resolution Pleiades (pixel size = 0.7 m) stereoscopic satellite imagery to retrieve a DEM on sandy coastline. A 40-km coastal stretch in the Southwest of France was selected as a pilot-site to compare topographic measurements obtained from Pleiades satellite imagery, Real Time Kinematic GPS (RTK-GPS) and airborne Light Detection and Ranging System (LiDAR). The derived 2-m Pleiades DEM shows an overall good agreement with concurrent methods (RTK-GPS and LiDAR; correlation coefficient of 0.9), with a vertical Root Mean Squared Error (RMS error) that ranges from 0.35 to 0.48 m, after absolute coregistration to the LiDAR dataset. The largest errors (RMS error > 0.5 m) occurred in the steep dune faces, particularly at shadowed areas. This work shows that DEMs derived from sub-meter satellite imagery capture local morphological features (e.g., berm or dune shape) on a sandy beach, over a large spatial domain.
Google Earth Engine Applications
Authors: Mutanga Onisimo , Kumar Lalit
Published: March 2019

The Google Earth Engine (GEE) is a cloud computing platform designed to store and process huge data sets (at petabyte-scale) for analysis and ultimate decision making [...]
Automatic Detection of Open and Vegetated Water Bodies Using Sentinel 1 to Map African Malaria Vector Mosquito Breeding Habitats
Authors: Hardy Andy , Ettritch Georgina , Cross Dónall E. , Bunting Pete , Liywalii Francis , Sakala Jacob , Silumesii Andrew , Singini Douglas , Smith Mark , Willis Tom , Thomas Chris J.
Published: March 2019

Providing timely and accurate maps of surface water is valuable for mapping malaria risk and targeting disease control interventions. Radar satellite remote sensing has the potential to provide this information but current approaches are not suitable for mapping African malarial mosquito aquatic habitats that tend to be highly dynamic, often with emergent vegetation. We present a novel approach for mapping both open and vegetated water bodies using serial Sentinel-1 imagery for Western Zambia. This region is dominated by the seasonally inundated Upper Zambezi floodplain that suffers from a number of public health challenges. The approach uses open source segmentation and machine learning (extra trees classifier), applied to training data that are automatically derived using freely available ancillary data. Refinement is implemented through a consensus approach and Otsu thresholding to eliminate false positives due to dry flat sandy areas. The results indicate a high degree of accuracy (mean overall accuracy 92% st dev 3.6) providing a tractable solution for operationally mapping water bodies in similar large river floodplain unforested environments. For the period studied, 70% of the total water extent mapped was attributed to vegetated water, highlighting the importance of mapping both open and vegetated water bodies for surface water mapping.
A Single Shot Framework with Multi-Scale Feature Fusion for Geospatial Object Detection
Authors: Zhuang Shuo , Wang Ping , Jiang Boran , Wang Gang , Wang Cong
Published: March 2019

With the rapid advances in remote-sensing technologies and the larger number of satellite images, fast and effective object detection plays an important role in understanding and analyzing image information, which could be further applied to civilian and military fields. Recently object detection methods with region-based convolutional neural network have shown excellent performance. However, these two-stage methods contain region proposal generation and object detection procedures, resulting in low computation speed. Because of the expensive manual costs, the quantity of well-annotated aerial images is scarce, which also limits the progress of geospatial object detection in remote sensing. In this paper, on the one hand, we construct and release a large-scale remote-sensing dataset for geospatial object detection (RSD-GOD) that consists of 5 different categories with 18,187 annotated images and 40,990 instances. On the other hand, we design a single shot detection framework with multi-scale feature fusion. The feature maps from different layers are fused together through the up-sampling and concatenation blocks to predict the detection results. High-level features with semantic information and low-level features with fine details are fully explored for detection tasks, especially for small objects. Meanwhile, a soft non-maximum suppression strategy is put into practice to select the final detection results. Extensive experiments have been conducted on two datasets to evaluate the designed network. Results show that the proposed approach achieves a good detection performance and obtains the mean average precision value of 89.0% on a newly constructed RSD-GOD dataset and 83.8% on the Northwestern Polytechnical University very high spatial resolution-10 (NWPU VHR-10) dataset at 18 frames per second (FPS) on a NVIDIA GTX-1080Ti GPU.
Fully Convolutional Networks and Geographic Object-Based Image Analysis for the Classification of VHR Imagery
Authors: Mboga Nicholus , Georganos Stefanos , Grippa Tais , Lennert Moritz , Vanhuysse Sabine , Wolff Eléonore
Published: March 2019

Land cover Classified maps obtained from deep learning methods such as Convolutional neural networks (CNNs) and fully convolutional networks (FCNs) usually have high classification accuracy but with the detailed structures of objects lost or smoothed. In this work, we develop a methodology based on fully convolutional networks (FCN) that is trained in an end-to-end fashion using aerial RGB images only as input. Skip connections are introduced into the FCN architecture to recover high spatial details from the lower convolutional layers. The experiments are conducted on the city of Goma in the Democratic Republic of Congo. We compare the results to a state-of-the art approach based on a semi-automatic Geographic object image-based analysis (GEOBIA) processing chain. State-of-the art classification accuracies are obtained by both methods whereby FCN and the best baseline method have an overall accuracy of 91.3% and 89.5% respectively. The maps have good visual quality and the use of an FCN skip architecture minimizes the rounded edges that is characteristic of FCN maps. Additional experiments are done to refine FCN classified maps using segments obtained from GEOBIA generated at different scale and minimum segment size. High OA of up to 91.5% is achieved accompanied with an improved edge delineation in the FCN maps, and future work will involve explicitly incorporating boundary information from the GEOBIA segmentation into the FCN pipeline in an end-to-end fashion. Finally, we observe that FCN has a lower computational cost than the standard patch-based CNN approach especially at inference.
Toward Content-Based Hyperspectral Remote Sensing Image Retrieval (CB-HRSIR): A Preliminary Study Based on Spectral Sensitivity Functions
Authors: Ben-Ahmed Olfa , Urruty Thierry , Richard Noël , Fernandez-Maloigne Christine
Published: March 2019

With the emergence of huge volumes of high-resolution Hyperspectral Images (HSI) produced by different types of imaging sensors, analyzing and retrieving these images require effective image description and quantification techniques. Compared to remote sensing RGB images, HSI data contain hundreds of spectral bands (varying from the visible to the infrared ranges) allowing profile materials and organisms that only hyperspectral sensors can provide. In this article, we study the importance of spectral sensitivity functions in constructing discriminative representation of hyperspectral images. The main goal of such representation is to improve image content recognition by focusing the processing on only the most relevant spectral channels. The underlying hypothesis is that for a given category, the content of each image is better extracted through a specific set of spectral sensitivity functions. Those spectral sensitivity functions are evaluated in a Content-Based Image Retrieval (CBIR) framework. In this work, we propose a new HSI dataset for the remote sensing community, specifically designed for Hyperspectral remote sensing retrieval and classification. Exhaustive experiments have been conducted on this dataset and on a literature dataset. Obtained retrieval results prove that the physical measurements and optical properties of the scene contained in the HSI contribute in an accurate image content description than the information provided by the RGB image presentation.
Robust Normal Estimation for 3D LiDAR Point Clouds in Urban Environments
Authors: Zhao Ruibin , Pang Mingyong , Liu Caixia , Zhang Yanling
Published: March 2019

Normal estimation is a crucial first step for numerous light detection and ranging (LiDAR) data-processing algorithms, from building reconstruction, road extraction, and ground-cover classification to scene rendering. For LiDAR point clouds in urban environments, this paper presents a robust method to estimate normals by constructing an octree-based hierarchical representation for the data and detecting a group of large enough consistent neighborhoods at multiscales. Consistent neighborhoods are mainly determined based on the observation that an urban environment is typically comprised of regular objects, e.g., buildings, roads, and the ground surface, and irregular objects, e.g., trees and shrubs; the surfaces of most regular objects can be approximatively represented by a group of local planes. Even in the frequent presence of heavy noise and anisotropic point samplings in LiDAR data, our method is capable of estimating robust normals for kinds of objects in urban environments, and the estimated normals are beneficial to more accurately segment and identify the objects, as well as preserving their sharp features and complete outlines. The proposed method was experimentally validated both on synthetic and real urban LiDAR datasets, and was compared to state-of-the-art methods.
Establishing SI-Traceability of Nanoparticle Size Values Measured with Line-Start Incremental Centrifugal Liquid Sedimentation
Authors: Kestens Vikram , A. Coleman Victoria , Herrmann Jan , Minelli Caterina , G. Shard Alex , Roebben Gert
Published: March 2019

Line-start incremental centrifugal liquid sedimentation (disc-CLS) is a powerful technique to determine particle size based on the principles of Stokes’ law. As most input quantities of the Stokes equation cannot be easily determined for typical instruments used for this method, an alternative method which depends on calibrating the sedimentation time scale with reference particles has become common practice. Unfortunately, most of these calibration materials (calibrants) come with limited information regarding their metrological reliability (e.g., lack of measurement uncertainties and traceability statements, incomplete measurand definitions). As a consequence, routine particle size results obtained by disc-CLS are mostly only traceable to the calibrant used, and effective comparisons can only be made for those results originating from measurements performed with the same types of calibrants. In this study, we discuss the concept of metrological traceability and demonstrate that particle size results obtained by disc-CLS can be traceable to the ultimate metrological reference, i.e., the unit of length in the International System of Units (SI), the meter. Using the example of two colloidal silica certified reference materials, we describe how laboratories can realize metrological traceability to the SI by simplifying complex traceability networks.
Policy Coherence and Social Protection in Ethiopia: Ensuring No One Is Left Behind
Authors: Lemma Melisew Dejene , Cochrane Logan
Published: March 2019

Ethiopia has made a strong commitment to strengthen its social protection system. However, resource constraints pose significant challenges in seeking to meet the basic needs of all people. We employ a qualitative research design to identify issues of policy incoherence, within the social protection policy and in relation to other sectoral policies. Policy incoherence has high costs. Strengthening policy coherence is necessary to improve the utilization of limited resources and set a pathway through which the government can ensure no one is left behind. We also present examples of implementation coherence, which provide insight into viable means through which improved policy coherence might be pursued.
Real-Time Early Warning System for Sustainable and Intelligent Plastic Film Manufacturing
Authors: Kim Jonghyuk , Hwangbo Hyunwoo
Published: March 2019

In this study, real-time preventive measures were formulated for a crusher process that is impossible to automate, due to the impossibility of installing sensors during the production of plastic films, and a real-time early warning system for semi-automated processes subsequently developed. First, the flow of a typical film process was ascertained. Second, a sustainable plan for real-time forecasting in a process that cannot be automated was developed using the semi-automation method flexible structure production control (FSPC). Third, statistical early selection of the process variables that are most probably responsible for failure was performed during data preprocessing. Then, a new, unified dataset was created using the link reordering method to transform the time sequence of the continuous process into one time zone. Fourth, a sustainable prediction algorithm was developed using the association rule method along with traditional statistical techniques, and verified using actual data. Finally, the overall developed logic was applied to new production process data to verify its prediction accuracy. The developed real-time early warning system for semi-automated processes contributes significantly to the smart manufacturing process both theoretically and practically.
Outcome-Driven Supply Chain Perspective on Dry Ports
Authors: Khaslavskaya Alena , Roso Violeta
Published: March 2019

The hinterland leg of maritime containerized transport as a part of supply chain has been increasingly pressured by larger volumes, as well as by a need to fulfill sustainability requirements that are expressed by social opinion and formal regulations. There is a potential to relieve this pressure through integration of a dry port, as a seaport’s inland interface, in the supply chain. Therefore, this paper aims to explain how a supply chain can benefit or enhance its outcomes of cost, responsiveness, security, environmental performance, resilience, and innovation, by the integration of a dry port. The data for this case study is collected through interviews and site visits from the privately owned Skaraborg dry port, Sweden; and the study is limited to the actors of the transport system involved in the development and operations of the dry port integrated setup. The results show that the six supply chain outcomes (cost, responsiveness, security, environmental performance, resilience, and innovation) are perceived by the actors as being desirable, and can be enhanced by the integration of a dry port in the supply chains. In particular, the enhancement of the supply chain outcomes can be achieved due to intermodality and reliability of rail transportation and customization of services associated with the dry port integrated setup, and by increasing the capacity of transportation system.
Sustainable Scheduling of an Automatic Pallet Changer System by Multi-Objective Evolutionary Algorithm with First Piece Inspection
Authors: Liao Qingmiao , Yang Jianjun , Zhou Yong
Published: March 2019

In this study, the machining center with the Automated Pallet Changer (APC) scheduling problem considering the disturbance of the first piece inspection is presented. The APC is frequently used in industry practice; it is useful in terms of sustainability and robustness because it increases the machine utilization rate and enhances the responsiveness to uncertainties in dynamic environments. An enhanced evolutionary algorithm for APC scheduling (APCEA) is developed by combining the multi-objective evolutionary algorithm with APC simulation. The dynamic factors in the simulation model include the pass rate of the first piece inspection (FPI) and the adjusted time when the FPI is unpassed. The proposed APCEA defines the non-robust gene based on the risk combination of the first piece inspection, and screens the non-robust gene in the genetic operation, thus improving the solution quality under the same computation times. Compared with the other three multi-objective evolutionary algorithms (MOEAs), it is demonstrated that the proposed APCEA produces the best result among the four methods. The proposed APCEA has been embedded into the manufacturing execution system (MES) and successfully applied in a manufacturing plant. The application value of the proposed method is verified by a practical example.
Evaluation of Transshipment Container Terminals’ Service Quality in Vietnam: From the Shipping Companies’ Perspective
Authors: Pham Thi Yen , Yeo Gi-Tae
Published: March 2019

Vietnam is a popular production base for multi-national companies and has become a hub for the global supply chain. Accordingly, to facilitate the increased demands on transportation and to satisfy customers’ complicated requirements, more attention has been paid to the service quality of container terminals. Thus, the aim of this paper is to investigate the service quality of transshipment container terminals in Vietnam from the perspective of shipping companies. The Consistent Fuzzy Preference Relation (CFPR) method has been introduced to solve multi-criteria service quality problems using both empirical data and expert knowledge. The results of this study illustrate that terminal accessibility and the proximity to a main trunk route are most important among the principal factors and sub-factors. Additionally, the TCIT terminal’s service quality ranks first among the top five container terminals in Vietnam. This study provides stakeholders with insight into competitive factors and risk factors for container terminals and their overall quality of service.
An Evaluation of the Quality and Microstructure of Biodegradable Composites as Contribution towards Better Management of Food Industry Wastes
Authors: Zdanowska Paulina , Florczak Iwona , Słoma Jacek , Tucki Karol , Orynycz Olga , Wasiak Andrzej , Świć Antoni
Published: March 2019

Biowastes from the food industry can be applied as a usable material after appropriate treatment (i.e., agglomeration). Biowastes are materials that could have better properties if they are mixed. Brewery and oilseed wastes were compressed and evaluated by their quality and microstructure. This article presents the influence of food wastes’ type on their biodegradable composite properties. Rapeseed cake and brewer’s threshing were used separately and mixed in three different proportions: 30:70, 50:50, 70:30. The data were obtained by mechanical testing on the Instron machine with different pressure forces of 30,000 N and 50,000 N. Strength and elasticity parameters, expansion after the test and in 24 h were estimated. The characteristics such as density, relaxation and compaction after the agglomeration process of biomass allows the selection of the best material and method for optimal composite quality. The results show an upward trend in composite density with decreasing content of brewery waste in a sample. Rapeseed cake can be considered as the material more susceptible to the compaction process. In addition to material properties and its lower density, the reason may be due to the granulometric composition of particles, density and particle size which was confirmed by SEM structure observations. Images of composites were analyzed on the basis of morphological plant tissue structures.
Effects of the Interfacial Structure on the Methanol Oxidation on Platinum Single Crystal Electrodes
Authors: Kamyabi Mohammad Ali , Martínez-Hincapié Ricardo , Feliu Juan M. , Herrero Enrique
Published: March 2019

Methanol oxidation has been studied on low index platinum single crystal electrodes using methanol solutions with different pH (1–5) in the absence of specific adsorption. The goal is to determine the role of the interfacial structure in the reaction. The comparison between the voltammetric profiles obtained in the presence and absence of methanol indicates that methanol oxidation is only taking place when the surface is partially covered by adsorbed OH. Thus, on the Pt(111) electrode, the onset for the direct oxidation of methanol and the adsorption of OH coincide. In this case, the adsorbed OH species are not a mere spectator, because the obtained results for the reaction order for methanol and the proton concentrations indicate that OH adsorbed species are involved in the reaction mechanism. On the other hand, the dehydrogenation step to yield adsorbed CO on the Pt(100) surface coincides with the onset of OH adsorption on this electrode. It is proposed that adsorbed OH collaborates in the dehydrogenation step during methanol oxidation, facilitating either the adsorption of the methanol in the right configuration or the cleavage of the C—H bond.
Technology-Powered Strategies to Rethink the Pedagogy of History and Cultural Heritage through Symmetries and Narratives
Authors: López-Nores Martín , Bravo-Quezada Omar Gustavo , Bassani Maddalena , Antoniou Angeliki , Lykourentzou Ioanna , Jones Catherine Emma , Kontiza Kalliopi , González-Soutelo Silvia , Reboreda-Morillo Susana , Naudet Yannick , Vlachidis Andreas , Bikakis Antonis , Pazos-Arias José Juan
Published: March 2019

Recent advances in semantic web and deep learning technologies enable new means for the computational analysis of vast amounts of information from the field of digital humanities. We discuss how some of the techniques can be used to identify historical and cultural symmetries between different characters, locations, events or venues, and how these can be harnessed to develop new strategies to promote intercultural and cross-border aspects that support the teaching and learning of history and heritage. The strategies have been put to the test in the context of the European project CrossCult, revealing enormous potential to encourage curiosity to discover new information and increase retention of learned information.
A Systems Thinking Approach to Corporate Strategy Development
Authors: Weissenberger-Eibl Marion A. , Almeida André , Seus Fanny
Published: March 2019

In an increasingly complex business environment, companies need to reassess their strategic choices on a regular basis. However, companies are struggling to collect and efficiently interpret the relevant information on their business environment. Whereas market information is often analyzed, influences from the broader environment (e.g., society) are often neglected. This paper argues that companies often lack a systemic approach to their strategy development process, and that environmental influences are only considered selectively. We suggest that companies themselves need to be seen as systems that are embedded in a complex environment. To develop a successful strategic orientation, a systematic screening of the environment must be coupled with a thorough analysis of the firm’s internal circumstances (e.g., competencies). Therefore, the paper proposes a holistic framework for conceiving companies as systems. Furthermore, we discuss how the scenario technique could support a systematic analysis of the company’s environment. The paper also aims to provide practical guidelines for managers and contributes to integrating a systems thinking approach into strategy development.
Designing a Model to Display the Relation between Social Vulnerability and Anthropogenic Risk of Wildfires in Galicia, Spain
Authors: de Diego Jaime , Rúa Antonio , Fernández Mercedes
Published: March 2019

Since the beginning of the 21st century, most of the forest fires that have occured in Spain have taken place in the northern region of Galicia. This area represents 5.8% of the Spanish territory, but compromises, in certain years, up to 50% of the total number of wildfires. Current research on forest fires is focused mostly on physical or meteorological characteristics, post-fire situations, and their potential destructive capacities (main areas burnt, type of vegetation, economic loses, etc.). However, the academic research to date has not delved into other socioeconomic factors (population structure, density, livestock farms, education, among others), which compromise the existing pre-fire situation in the affected territories, and subsequently reflect the prevailing vulnerability of the population. Indeed, these socioeconomic variables can influence fire occurrence, whether positively or negatively. To fill in this knowledge gap, this article analyzes the relationship between wildfire events and the socioeconomic variables that characterize the Galician municipalities affected. To that effect, first, a thorough examination and selection of the most relevant socioeconomic variables, and their subsequent justification will be carried out. Then, using IBM SPSS statistics 24, a linear regression is executed using the data of wildfires that occurred in Galicia between 2001–2015. The resulting model allows a better knowledge of the importance of the socioeconomic situation in Galician municipalities when wildfires occur. Therefore, this result identifies the existing relationship between the socioeconomic variables and wildfire events, and consequently will help to optimize the interventions that must be done. This may be the best way to carry out prevention actions in order to reduce vulnerability to forest fires.
Decoy Receptor Interactions as Novel Drug Targets against EKC-Causing Human Adenovirus
Authors: Chandra Naresh , Frängsmyr Lars , Arnberg Niklas
Published: March 2019

Epidemic keratoconjunctivitis (EKC) is a severe ocular disease and can lead to visual impairment. Human adenovirus type-37 (HAdV-D37) is one of the major causative agents of EKC and uses sialic acid (SA)-containing glycans as cellular receptors. Currently, there are no approved antivirals available for the treatment of EKC. Recently, we have reported that sulfated glycosaminoglycans (GAGs) bind to HAdV-D37 via the fiber knob (FK) domain of the viral fiber protein and function as decoy receptors. Based on this finding, we speculated that GAG-mimetics may act as artificial decoy receptors and inhibit HAdV-D37 infection. Repurposing of approved drugs to identify new antivirals has drawn great attention in recent years. Here, we report the antiviral effect of suramin, a WHO-approved drug and a widely known GAG-mimetic, against HAdV-D37. Commercially available suramin analogs also show antiviral effects against HAdV-D37. We demonstrate that suramin exerts its antiviral activity by inhibiting the attachment of HAdV-D37 to cells. We also reveal that the antiviral effect of suramin is HAdV species-specific. Collectively, in this proof of concept study, we demonstrate for the first time that virus binding to a decoy receptor constitutes a novel and an unexplored target for antiviral drug development.
Improvement of High Affinity and Selectivity on Biosensors Using Genetically Engineered Phage by Binding Isotherm Screening
Authors: Lee Jong-Min , Choi Eun Jung , Park Juyun , Devaraj Vasanthan , Kim ChunTae , Han Jiye , Kim Won-Geun , Kim Kyujung , Kang Yong-Cheol , Kim Kwang Ho , Oh Jin-Woo
Published: March 2019

The genetically engineered M13 bacteriophage (M13 phage), developed via directed evolutionary screening process, can improve the sensitivity of sensors because of its selective binding to a target material. Herein, we propose a screening method to develop a selective and sensitive bioreporter for toxic material based on genetically engineered M13 phage. The paraquat (PQ)-binding M13 phage, developed by directed evolution, was used. The binding affinities of the PQ-binding M13 phage to PQ and similar molecules were analyzed using isothermal titration calorimetry (ITC). Based on the isotherms measured by ITC, binding affinities were calculated using the one-site binding model. The binding affinity was 5.161 × 10−7 for PQ, and 3.043 × 10−7 for diquat (DQ). The isotherm and raw ITC data show that the PQ-binding M13 phage does not selectively bind to difenzoquat (DIF). The phage biofilter experiment confirmed the ability of PQ-binding M13 bacteriophage to bind PQ. The surface-enhanced Raman scattering (SERS) platform based on the bioreporter, PQ-binding M13 phage, exhibited 3.7 times the signal intensity as compared with the wild-type-M13-phage-coated platform.
Decline of Fine Suspended Sediments in the Madeira River Basin (2003–2017)
Authors: Ayes Rivera Irma , Armijos Cardenas Elisa , Espinoza-Villar Raúl , Espinoza Jhan Carlo , Molina-Carpio Jorge , Ayala José Max , Gutierrez-Cori Omar , Martinez Jean-Michel , Filizola Naziano
Published: March 2019

The Madeira River is the second largest Amazon tributary, contributing up to 50% of the Amazon River’s sediment load. The Madeira has significant hydropower potential, which has started to be used by the Madeira Hydroelectric Complex (MHC), with two large dams along the middle stretch of the river. In this study, fine suspended sediment concentration (FSC) data were assessed downstream of the MHC at the Porto Velho gauging station and at the outlet of each tributary (Beni and Mamoré Rivers, upstream from the MHC), from 2003 to 2017. When comparing the pre-MHC (2003–2008) and post-MHC (2015–2017) periods, a 36% decrease in FSC was observed in the Beni River during the peak months of sediment load (December–March). At Porto Velho, a reduction of 30% was found, which responds to the Upper Madeira Basin and hydroelectric regulation. Concerning water discharge, no significant change occurred, indicating that a lower peak FSC cannot be explained by changes in the peak discharge months. However, lower FSCs are associated with a downward break in the overall time series registered at the outlet of the major sediment supplier—the Beni River—during 2010.
Urban Drainage Network Rehabilitation Considering Storm Tank Installation and Pipe Substitution
Authors: Ngamalieu-Nengoue Ulrich A. , Iglesias-Rey Pedro L. , Martínez-Solano F. Javier , Mora-Meliá Daniel , Saldarriaga Valderrama Juan G.
Published: March 2019

The drainage networks of our cities are currently experiencing a growing increase in runoff flows, caused mainly by the waterproofing of the soil and the effects of climate change. Consequently, networks originally designed correctly must endure floods with frequencies much higher than those considered in the design phase. The solution of such a problem is to improve the network. There are several ways to rehabilitate a network: conduit substitution as a former method or current methods such as storm tank installation or combined use of conduit substitution and storm tank installation. To find an optimal solution, deterministic or heuristic optimization methods are used. In this paper, a methodology for the rehabilitation of these drainage networks based on the combined use of the installation of storm tanks and the substitution of some conduits of the system is presented. For this, a cost-optimization method and a pseudo-genetic heuristic algorithm, whose efficiency has been validated in other fields, are applied. The Storm Water Management Model (SWMM) model for hydraulic analysis of drainage and sanitation networks is used. The methodology has been applied to a sector of the drainage network of the city of Bogota in Colombia, showing how the combined use of storm tanks and conduits leads to lower cost rehabilitation solutions.
Water Footprint and Water Pinch Analysis in Ethanol Industrial Production for Water Management
Authors: Liu Heng , Ren Lijun , Zhuo Huimin , Fu Sanze
Published: March 2019

Fuel ethanol is considered to be a clean alternative fuel to meet increasing energy demands and mitigate environmental pollution. Faced with challenges in terms of energy security and environmental pollution, China is vigorously developing fuel ethanol. However, ethanol-manufacturing is a water-intensive industry; it consumes large volumes of fresh water and generates a corresponding amount of waste water. Expansion of this industry can reduce water quality and cause water stress. This study aims to combine the water footprint (WF) with a water pinch analysis technique to manage water consumption and sewage discharge systematically in an ethanol plant. A well-operated cassava ethanol plant in China was chosen as a case study. The WF of industrial ethanol production was evaluated. The total WF was 17.08 L/L ethanol, comprised of a 7.69 L blue water footprint (BWF), and a 9.39 L gray water footprint (GWF). The direct WF was 16.38 L/L ethanol, and the indirect WF was 0.70 L/L ethanol. Thereafter, a water pinch analysis was conducted, and the optimal direct water reuse scheme was studied. After the water network was optimized, the BWF was reduced by 0.98 L/L ethanol, while the GWF was reduced by 1.47 L/L ethanol. These results indicate that the combined use of WF and pinch analysis can provide the starch-based ethanol industry with an effective tool to improve its water management.
Apoio à decisão na prevenção de acidentes de trânsito:
Authors: Pereira João Vicente , Palmeira Rômulo De Medeiros , Reis Ana Carla Bittencourt
Published: March 2019

Uma das maiores causas de mortes no mundo é provocada por acidentes de trânsito envolvendo veículos e pedestres. Este artigo apresenta uma aplicação da metodologia multicritério para ordenação das Regiões Administrativas do Distrito Federal-DF, no Brasil, considerando os acidentes de trânsito com mortes e feridos. Identificou-se a variável natureza do acidente para criação dos critérios, tipo de acidente para subcritérios e a regiões administrativas (cidades) para alternativas. Aplicou-se os métodos AHP e PROMETHEE aos dados do Anuário Estatístico do DETRAN-DF de 2016. Os resultados obtidos foram comparados com a Unidade Padrão de Severidade (UPS), que é a medida utilizada pela maioria dos Detrans do país, indicando possibilidade de aperfeiçoamento nos critérios adotados pelos decisores para definição de estratégias, ações e medidas para melhoria da segurança no trânsito.
Analysis of chromosome karyotype and genome size in echiuran Urechis unicinctus Drasche, 1880 (Polychaeta, Urechidae)
Authors: Qin Zhenkui , Li Xueyu , Liu Danwen , Wang Qing , Lu Li , Zhang Zhifeng
Published: March 2019

Karyotype and genome size are two primary cytogenetic characteristics of species, which are of great significance to the study of cytogenetics, taxonomy, phylogenesis, evolution as well as molecular biology. However, this basic cytogenetic information in echiurans is lacking. Therefore, we analyzed characteristics of karyotype and genome size in the echiuran worm Urechisunicinctus Drasche, 1880. In this study, coelomic cells of U.unicinctus were used for analyzing the genome size by a flow cytometry with chicken erythrocytes as DNA standard, and the 2C DNA content was determined to be 1.85 pg, which was corresponded to the genome size of 904.58 Mbp approximately. Furthermore, trochophores of U.unicinctus were dissociated and cells were utilized for preparing the chromosomes stained with DAPI, and the karyotype was determined as 2n = 30 (10m + 6sm + 6st + 8t), FN=52. Our data provided the basic cytogenetic information of U.unicinctus, which could be utilized in taxonomic study and whole-genome sequencing in future.
Low and high input agricultural fields have different effects on pest aphid abundance via different invasive alien weed species
Authors: Szabó Attila-Károly , Kiss József , Bálint János , Kőszeghi Szidónia , Loxdale Hugh D. , Balog Adalbert
Published: March 2019

We conducted field surveys to detect the population density of the most important invasive weed species and their associated virus vectoring aphids in crops grown under high input field (HIF) vs low-input field (LIF) conditions, with and without fertilizers and pesticides. The most frequent invasive weed species wereStenactisannua,ErigeroncanadensisandSolidagocanadensis. These species were hosts predominantly for the aphidsBrachycaudushelichrysiandAulacorthumsolaniin both management systems. The 13% higher coverage ofS.annuaunder LIF conditions resulted in a 30% higherB.helichrysiabundance and ~85% higherA.solaniabundance compared with HIF conditions. Host plant quality was assessed by measuring peroxidase enzyme activity. There was a significantly increased POD activity at 10 μmol min−1mg protein−1unit inS.annuaunder LIF conditions, suggesting a higher stress by aphids under this management regime. The high colonization intensity ofB.helichrysion maize, potato and alfalfa crops were detected from bothS.annuaandE.canadensis. We conclude that new and faster methods need to be used to prevent colonization of such virus vectoring aphids and their host plants, even under low input regimes.
Population genetic structure of Marbled Rockfish, Sebastiscus marmoratus (Cuvier, 1829), in the northwestern Pacific Ocean
Authors: Liu Lu , Zhang Xiumei , Li Chunhou , Zhang Hui , Yanagimoto Takashi , Song Na , Gao Tianxiang
Published: March 2019

Sebastiscusmarmoratusis an ovoviviparous fish widely distributed in the northwestern Pacific. To examine the gene flow and test larval dispersal strategy ofS.marmoratusin Chinese and Japanese coastal waters, 421 specimens were collected from 22 localities across its natural distribution. A 458 base-pair fragment of the mitochondrial DNA (mtDNA) control region was sequenced to examine genetic diversity and population structure. One-hundred-six variable sites defined 166 haplotypes. The populations ofS.marmoratusshowed high haplotype diversity with a range from 0.8587 to 0.9996, indicating a high level of intrapopulation genetic diversity. Low non-significant genetic differentiation was estimated among populations except those of Hyogo, Behai, and Niiigata, which showed significant genetic differences from the other populations. The demographic history examined by neutrality tests, mismatch distribution analysis, and Bayesian skyline analysis suggested a sudden population expansion dating to the late Pleistocene. Recent population expansion in the last glacial period, wide dispersal of larvae by coastal currents, and the homogeneity of the environment may have important influences on the population genetic pattern. Knowledge of genetic diversity and genetic structure will be crucial to establish appropriate fishery management ofS.marmoratus.
Student-supervisor-university expectation alignment in the undergraduate engineering thesis
Authors: Stappenbelt Brad , Basu Abheek
Published: March 2019

Given the lack of student research experience, the undergraduate thesis is necessarily focussed primarily on development of research skills (i.e. it is process oriented). Since postgraduate supervision is research output focussed, the lessons learnt from this field are not always directly transferable. In contrast to the vast body of work in the field of doctoral research supervision, there exists a dearth of literature on undergraduate dissertation supervision. To address this shortcoming, the present study examined the alignment of university, supervisor and student expectations regarding responsibilities in the undergraduate engineering thesis. University expectations, having undergone rigorous review, outline the sound pedagogical practice that should be applied to undergraduate supervision. Expectations of academic staff supervisors and thesis students were obtained through the use of survey tools and post-survey discussions. The surveys used in the present study were adapted from the Role Perceptions Rating Scale (RPRS). Alignment between student and university expectations regarding undergraduate thesis responsibilities in the present study was generally poor. The discrepancy between supervisor and university expectations was even greater, with academic staff generally assuming the bulk of the responsibility for many core thesis tasks. Post-survey discussion indicated that the driver for this behaviour were supervisor expectations that that undergraduate thesis research would contribute to publications. Taking primary responsibility for core thesis tasks away from the student, although improving the likelihood of successful research output, diminishes the ability for an accurate assessment of adequate academic performance. The learning that is intended to result from the undergraduate thesis is devalued when research outcomes are prioritised over research process.
AN EXPERIMENTAL ANALYSIS AND VALIDATION OF ELECTRICAL IMPEDANCE TOMOGRAPHY TECHNIQUE FOR MEDICAL OR INDUSTRIAL APPLICATION
Authors: Kumar Ramesh , Kumar Sharvan , Sengupta A.
Published: March 2019

Electrical impedance tomography is a recently established technique by which impedance of an object (medical or nonmedical applications) is measured data from the surface of the object, and a numerically simulated reconstruction of the object internal shape of the image can be obtained. This imaging technique based on boundary or surface voltage is measured when the different current pattern is injected into it. For current pulse, we are creating a voltage controlled current source, which is based on the different RC circuits, according to current amplitude and frequency values. The current source used in inject the current pulse of the various phantoms. The current position and measuring voltage is controlled by the created control unit or programmable system on chip (PSOC) of the proposed EIT system. After that image reconstruction of the cross-sectional image of resistivity requires sufficient data collection from used phantoms, which is based on finite element method (FEM) method and Tikhonov regularization method with helps of graphical user interface (GUI) on MatLab. The objective of the GUI was to produce an image (2D/3D), impedance distribution graph, and the FEM mesh model according to used electrode combinations from the various phantoms. EIT system has a great potential for imaging modality, is non-invasive, radiation-free, and inexpensive for medical applications.