bluuebunny/crossref_metadata_2025 huggingface dataset:
Surface Segregation of Cyclic Chains in Binary Melts of Thin Polymer Films: The Influence of Constituent Concentration
Authors: Gaitho Francis , Tsige Mesfin , Mola Genene , Pellicane Giuseppe
Published: March 2018

We carry out extensive molecular dynamics simulations of thin films of bead-spring models of binary mixtures composed of cyclic and linear polymer chains. We study the equilibrium behavior of the polymer chains for two very different chain lengths, which resemble short (10-mers) and long (100-mers) chains, at different concentrations of the binary mixture. We clearly show how the concentration variable affects the enrichment of either of the two polymer species at the interface, and also how the chain length influences this process.
An Assessment of Airport Sustainability, Part 1—Waste Management at Copenhagen Airport
Authors: Baxter Glenn , Srisaeng Panarat , Wild Graham
Published: March 2018

Airports play a vital role in the air transport industry value chain, acting as the interface point between the air and surface transport modes. However, substantial volumes of waste are produced as a by-product of the actors’ operations. Waste management is therefore becoming especially important to airports. Using a qualitative and quantitative case study research approach, this paper has examined the waste management strategies and systems at Copenhagen Airport, Scandinavia’s major air traffic hub, from 1999 to 2016. The two major sources of waste at Copenhagen Airport are the waste generated from aircraft serving the airport and the waste arising from ground activities undertaken in the land and airside precincts. The growth in passengers and aircraft movements has had a concomitant impact on the volume of waste generated. Swept waste and sludge are processed by an external provider. Waste generated in the passenger terminals and the airport operator’s facilities is handled at a central container station, where it is sorted for incineration, recycling or for landfill. The environmental impact of the waste produced at the airport is mitigated through the recycling of waste wherever possible.
An Efficient Maximum Likelihood Estimation Approach of Multi-Baseline SAR Interferometry for Refined Topographic Mapping in Mountainous Areas
Authors: Dong Yuting , Jiang Houjun , Zhang Lu , Liao Mingsheng
Published: March 2018

For InSAR topographic mapping, multi-baseline InSAR height estimation is known to be an effective way to facilitate phase unwrapping by significantly increasing the ambiguity intervals and maintaining good height measurement sensitivity, especially in mountainous areas. In this paper, an efficient multi-baseline SAR interferometry approach based on maximum likelihood estimation is developed for refined topographic mapping in mountainous areas. In the algorithm, maximum likelihood (ML) height estimation is used to measure the topographic details and avoid the complicated phase unwrapping process. In order to be well-adapted to the mountainous terrain conditions, the prior height probability is re-defined to take the local terrain conditions and neighboring height constraint into consideration in the algorithm. In addition, three strategies are used to optimize the maximum likelihood height estimation process to obtain higher computational efficiency, so that this method is more suitable for spaceborne InSAR data. The strategies include substituting a rational function model into the complicated conversion process from candidate height to interferometric phase, discretizing the continuous height likelihood probability, and searching for the maximum likelihood height with a flexible step length. The experiment with simulated data is designed to verify the improvement of the ML height estimation accuracy with the re-defined prior height distribution. Then the optimized processing procedure is tested with the multi-baseline L-band ALOS/PALSAR data covering the Mount Tai area in China. The height accuracy of the generated multi-baseline InSAR DEM can meet both standards of American DTED-2 and Chinese national 1:50,000 DEM (mountain) Level 2.
A Human Settlement Composite Index (HSCI) Derived from Nighttime Luminosity Associated with Imperviousness and Vegetation Indexes
Authors: Ma Ting , Xu Tao , Huang Lin , Zhou Alicia
Published: March 2018

Satellite-derived nighttime light data have been increasingly used for studying urbanization and socioeconomic dynamics, because there are notable quantitative relationships between anthropogenic nocturnal radiance and the degree of human activity over time and space at different scales. When considering the visible impacts of saturation and over-glow effects from original nighttime light images, several composite indexes, which mainly include the introduction of vegetation index, have been studied to improve the application of nighttime light data for investigating the spatial patterns in human settlements. To overcome the shortcomings of previous composite indexes, especially in areas of highly intensified human activity, such as urban, non-man-made surfaces, and low density human activity, such as in rural residential sites, we propose a new human settlement composite index (HSCI). The establishment of this proposed HSCI is based on a combination of three different remote sensing datasets: nighttime light brightness (derived from the Defense Meteorological Satellite Program, DMSP), the normalized difference vegetation index (NDVI, derived from the Moderate Resolution Imaging Spectroradiometer, MODIS), and the percent impervious surface area (PISA, derived from the GlobeLand30 land cover and land use dataset produced from Landsat data). We defined the calculation of HSCI as the arithmetic mean of the normalized difference urban index and normalized difference imperviousness index with respect to both the magnitude of socioeconomic activity and the distribution of artificial surface across human settlement, respectively. Analysis results clearly demonstrate the utility of HSCI in delineating spatial patterns for different kinds of human settlement, particularly for identifying non-man-made surfaces in urbanized areas, various densities of human activities in peripheral areas and small human settlements in rural and remote areas. Our method and findings provide an effective way to investigate human settlements with a nighttime brightness-based composite index, as well as valuable insights into further studies of the composite index related to nocturnal luminosity data.
Unmanned Aerial Vehicle-Based Traffic Analysis: A Case Study for Shockwave Identification and Flow Parameters Estimation at Signalized Intersections
Authors: Khan Muhammad , Ectors Wim , Bellemans Tom , Janssens Davy , Wets Geert
Published: March 2018

Owing to their dynamic and multidisciplinary characteristics, Unmanned Aerial Vehicles (UAVs), or drones, have become increasingly popular. However, the civil applications of this technology, particularly for traffic data collection and analysis, still need to be thoroughly explored. For this purpose, the authors previously proposed a detailed methodological framework for the automated UAV video processing in order to extract multi-vehicle trajectories at a particular road segment. In this paper, however, the main emphasis is on the comprehensive analysis of vehicle trajectories extracted via a UAV-based video processing framework. An analytical methodology is presented for: (i) the automatic identification of flow states and shockwaves based on processed UAV trajectories, and (ii) the subsequent extraction of various traffic parameters and performance indicators in order to study flow conditions at a signalized intersection. The experimental data to analyze traffic flow conditions was obtained in the city of Sint-Truiden, Belgium. The generation of simplified trajectories, shockwaves, and fundamental diagrams help in analyzing the interrupted-flow conditions at a signalized four-legged intersection using UAV-acquired data. The analysis conducted on such data may serve as a benchmark for the actual traffic-specific applications of the UAV-acquired data. The results reflect the value of flexibility and bird-eye view provided by UAV videos; thereby depicting the overall applicability of the UAV-based traffic analysis system. The future research will mainly focus on further extensions of UAV-based traffic applications.
Ground Deformations around the Toktogul Reservoir, Kyrgyzstan, from Envisat ASAR and Sentinel-1 Data—A Case Study about the Impact of Atmospheric Corrections on InSAR Time Series
Authors: Neelmeijer Julia , Schöne Tilo , Dill Robert , Klemann Volker , Motagh Mahdi
Published: March 2018

We present ground deformations in response to water level variations at the Toktogul Reservoir, located in Kyrgyzstan, Central Asia. Ground deformations were measured by Envisat Advanced Synthetic Aperture Radar (ASAR) and Sentinel-1 Differential Interferometric Synthetic Aperture Radar (DInSAR) imagery covering the time periods 2004–2009 and 2014–2016, respectively. The net reservoir water level, as measured by satellite radar altimetry, decreased approximately 60 m (∼13.5 km3) from 2004–2009, whereas, for 2014–2016, the net water level increased by approximately 51 m (∼11.2 km3). The individual Small BAseline Subset (SBAS) interferograms were heavily influenced by atmospheric effects that needed to be minimized prior to the time-series analysis. We tested several approaches including corrections based on global numerical weather model data, such as the European Centre for Medium-RangeWeather Forecasts (ECMWF) operational forecast data, the ERA-5 reanalysis, and the ERA-Interim reanalysis, as well as phase-based methods, such as calculating a simple linear dependency on the elevation or the more sophisticated power-law approach. Our findings suggest that, for the high-mountain Toktogul area, the power-law correction performs the best. Envisat descending time series for the period of water recession reveal mean line-of-sight (LOS) uplift rates of 7.8 mm/yr on the northern shore of the Toktogul Reservoir close to the Toktogul city area. For the same area, Sentinel-1 ascending and descending time series consistently show a subsidence behaviour due to the replenishing of the water reservoir, which includes intra-annual LOS variations on the order of 30mm. A decomposition of the LOS deformation rates of both Sentinel-1 orbits revealed mean vertical subsidence rates of 25 mm/yr for the common time period of March 2015–November 2016, which is in very good agreement with the results derived from elastic modelling based on the TEA12 Earth model.
Unified Partial Configuration Model Framework for Fast Partially Occluded Object Detection in High-Resolution Remote Sensing Images
Authors: Qiu Shaohua , Wen Gongjian , Liu Jia , Deng Zhipeng , Fan Yaxiang
Published: March 2018

Partially occluded object detection (POOD) has been an important task for both civil and military applications that use high-resolution remote sensing images (HR-RSIs). This topic is very challenging due to the limited object evidence for detection. Recent partial configuration model (PCM) based methods deal with occlusion yet suffer from the problems of massive manual annotation, separate parameter learning, and low training and detection efficiency. To tackle this, a unified PCM framework (UniPCM) is proposed in this paper. The proposed UniPCM adopts a part sharing mechanism which directly shares the root and part filters of a deformable part-based model (DPM) among different partial configurations. It largely reduces the convolution overhead during both training and detection. In UniPCM, a novel DPM deformation deviation method is proposed for spatial interrelationship estimation of PCM, and a unified weights learning method is presented to simultaneously obtain the weights of elements within each partial configuration and the weights between partial configurations. Experiments on three HR-RSI datasets show that the proposed UniPCM method achieves a much higher training and detection efficiency for POOD compared with state-of-the-art PCM-based methods, while maintaining a comparable detection accuracy. UniPCM obtains a training speedup of maximal 10× and 2.5× for airplane and ship, and a detection speedup of maximal 7.2×, 4.1× and 2.5× on three test sets, respectively.
Communication Architecture in Mixed-Reality Simulations of Unmanned Systems
Authors: Selecký Martin , Faigl Jan , Rollo Milan
Published: March 2018

Verification of the correct functionality of multi-vehicle systems in high-fidelity scenarios is required before any deployment of such a complex system, e.g., in missions of remote sensing or in mobile sensor networks. Mixed-reality simulations where both virtual and physical entities can coexist and interact have been shown to be beneficial for development, testing, and verification of such systems. This paper deals with the problems of designing a certain communication subsystem for such highly desirable realistic simulations. Requirements of this communication subsystem, including proper addressing, transparent routing, visibility modeling, or message management, are specified prior to designing an appropriate solution. Then, a suitable architecture of this communication subsystem is proposed together with solutions to the challenges that arise when simultaneous virtual and physical message transmissions occur. The proposed architecture can be utilized as a high-fidelity network simulator for vehicular systems with implicit mobility models that are given by real trajectories of the vehicles. The architecture has been utilized within multiple projects dealing with the development and practical deployment of multi-UAV systems, which support the architecture’s viability and advantages. The provided experimental results show the achieved similarity of the communication characteristics of the fully deployed hardware setup to the setup utilizing the proposed mixed-reality architecture.
A Non-Cooperative Satellite Feature Point Selection Method for Vision-Based Navigation System
Authors: Ning Mingfeng , Zhang Shijie , Wang Shiqiang
Published: March 2018

The number of feature points on the surface of a non-cooperative target satellite used for monocular vision-based relative navigation affects the onboard computational load. A feature point selection method called the quasi-optimal method is proposed to select a subset of feature points with a good geometric distribution. This method, with the assumption that all of the feature points are in a plane and have the same variance, is based on the fact that the scattered feature points can provide higher accuracy than that of them grouped together. The cost is defined as a function of the angle between two unit vectors from the projection center to feature points. The redundancy of a feature point is calculated by summing all costs associated with it. Firstly, the feature point with the most redundant information is removed. Then, redundancies are calculated again with the second feature point removed. The procedures above are repeated until the desired number of feature points is reached. Dilution of precision (DOP) represents the mapping relation between the observation variance and the estimated variance. In this paper, the DOP concept is used in a vision-based navigation system to verify the performance of the quasi-optimal method. Simulation results demonstrate the feasibility of calculating the relative position and attitude by using a subset of feature points with a good geometric distribution. It also shows that the feature points selected by the quasi-optimal method can provide a high accuracy with low computation time.
Two-Dimensional Layered Nanomaterial-Based One-Dimensional Photonic Crystal Refractive Index Sensor
Authors: Maurya Jitendra , François Alexandre , Prajapati Yogendra
Published: March 2018

One-dimensional photonic crystal (1DPC) sensors have emerged as contenders for traditional surface plasmon resonance sensors, owing to their potential for the detection of bigger molecules and particles due to their higher interaction volume in the sensing medium. Two-dimensional layered nanomaterials, most notably graphene and dichalcogenides (e.g., MoS2, MoSe2, WS2, and WSe2), have shown higher refractive index sensitivity because of their absorption as well as adsorption property. The proposed configuration of 1DPC presented consists of alternate layers of the aforementioned nanomaterials and silicon. The performance parameters, namely the sensitivity, resolution, quality factor, and the evanescent field penetration depth, are calculated and compared with 1DPC having poly methyl methacrylate (PMMA) in place of silicon. Increased shift in resonance angle and quality factor are observed by replacing PMMA with silicon, but at the cost of decreased resolution. Further, our results show that although the sensitivity and quality factor of the 1DPC sensor is less than that of the conventional surface plasmon resonance sensor (SPR) with a gold thin film, it has much higher resolution and penetration depth to make it suitable for large molecules.
Determination of Food Oxalates Using Silica–Titania Xerogel Modified with Eriochrome Cyanine R
Authors: Morosanova Maria , Samodelov Zahar , Morosanova Elena
Published: March 2018

The interaction of silica–titania xerogel with triphenylmethane dyes (pyrocatechol violet, chrome azurol S, eriochrome cyanine R) has been investigated to create a new sensor material for solid phase spectrophotometric determination of food oxalates. The complex forming reaction between xerogel incorporated titanium(IV) and triphenylmethane dyes has been studied; half-reaction periods, complex composition, equilibrium constants, and xerogel sorption capacity have been calculated for each dye. Eriochrome cyanine R (ECR) is characterized by the shortest half-reaction period, the smallest equilibrium constant, and the greatest capacity; it has been chosen for the sensor material construction because titanium(IV)-ECR complex is formed faster and can be destroyed easier than other studied complexes. The interaction of this sensor material with oxalates has been described: the presence of oxalates causes sensor material discoloration and the absorbance is used as analytical signal. The analytical range is 35–900 mg/L (LOD 10.5 mg/L, n = 7). High concentrations of interfering inorganic anions, organic acids, and sucrose did not affect oxalate determination. Proposed solid phase spectrophotometric procedure has been successfully applied for the determination of oxalates in food samples (sorrel, spinach, parsley, ginger, and black pepper) and the results are in good agreement with HPLC oxalate determination.
Energy Optimization Using a Case-Based Reasoning Strategy
Authors: González-Briones Alfonso , Prieto Javier , De La Prieta Fernando , Herrera-Viedma Enrique , Corchado Juan
Published: March 2018

At present, the domotization of homes and public buildings is becoming increasingly popular. Domotization is most commonly applied to the field of energy management, since it gives the possibility of managing the consumption of the devices connected to the electric network, the way in which the users interact with these devices, as well as other external factors that influence consumption. In buildings, Heating, Ventilation and Air Conditioning (HVAC) systems have the highest consumption rates. The systems proposed so far have not succeeded in optimizing the energy consumption associated with a HVAC system because they do not monitor all the variables involved in electricity consumption. For this reason, this article presents an agent approach that benefits from the advantages provided by a Multi-Agent architecture (MAS) deployed in a Cloud environment with a wireless sensor network (WSN) in order to achieve energy savings. The agents of the MAS learn social behavior thanks to the collection of data and the use of an artificial neural network (ANN). The proposed system has been assessed in an office building achieving an average energy savings of 41% in the experimental group offices.
A Novel Feature Optimization for Wearable Human-Computer Interfaces Using Surface Electromyography Sensors
Authors: Sun Han , Zhang Xiong , Zhao Yacong , Zhang Yu , Zhong Xuefei , Fan Zhaowen
Published: March 2018

The novel human-computer interface (HCI) using bioelectrical signals as input is a valuable tool to improve the lives of people with disabilities. In this paper, surface electromyography (sEMG) signals induced by four classes of wrist movements were acquired from four sites on the lower arm with our designed system. Forty-two features were extracted from the time, frequency and time-frequency domains. Optimal channels were determined from single-channel classification performance rank. The optimal-feature selection was according to a modified entropy criteria (EC) and Fisher discrimination (FD) criteria. The feature selection results were evaluated by four different classifiers, and compared with other conventional feature subsets. In online tests, the wearable system acquired real-time sEMG signals. The selected features and trained classifier model were used to control a telecar through four different paradigms in a designed environment with simple obstacles. Performance was evaluated based on travel time (TT) and recognition rate (RR). The results of hardware evaluation verified the feasibility of our acquisition systems, and ensured signal quality. Single-channel analysis results indicated that the channel located on the extensor carpi ulnaris (ECU) performed best with mean classification accuracy of 97.45% for all movement’s pairs. Channels placed on ECU and the extensor carpi radialis (ECR) were selected according to the accuracy rank. Experimental results showed that the proposed FD method was better than other feature selection methods and single-type features. The combination of FD and random forest (RF) performed best in offline analysis, with 96.77% multi-class RR. Online results illustrated that the state-machine paradigm with a 125 ms window had the highest maneuverability and was closest to real-life control. Subjects could accomplish online sessions by three sEMG-based paradigms, with average times of 46.02, 49.06 and 48.08 s, respectively. These experiments validate the feasibility of proposed real-time wearable HCI system and algorithms, providing a potential assistive device interface for persons with disabilities.
Detection of Matrix Metalloproteinase Activity by Bioluminescence via Intein-Mediated Biotinylation of Luciferase
Authors: Nguyen Duc , Kim Hanim , Kim Dasom , Lee Jin , Gye Myung , Kim Young-Pil
Published: March 2018

We report bioluminescence analysis of matrix metalloproteinase (MMP) activity in biological substances using a surface-bound luciferase probe. Intein-fused luciferase protein enables site-specific biotinylation of luciferase in the presence of N-terminus cysteine-biotin via intein-mediated splicing process, resulting in a strong association with high bioluminescence signal onto a NeutrAvidin-coated surface. When the peptide substrate for MMP-7 was inserted into a region between luciferase and intein, the biotinylated probe detected MMP-7 activity by cleaving the peptide, and surface-induced bioluminescence signal was strongly reduced in the MMP-secreted media or mouse tissue extracts, compared with that in MMP-deficient control set. Our approach is anticipated to be useful for generating biotinylated proteins and for their applications in diagnosing MMP activity in human diseases.
Compact Embedded Wireless Sensor-Based Monitoring of Concrete Curing
Authors: Cabezas Joaquín , Sánchez-Rodríguez Trinidad , Gómez-Galán Juan , Cifuentes Héctor , González Carvajal Ramón
Published: March 2018

This work presents the design, construction and testing of a new embedded sensor system for monitoring concrete curing. A specific mote has been implemented to withstand the aggressive environment without affecting the measured variables. The system also includes a real-time monitoring application operating from a remote computer placed in a central location. The testing was done in two phases: the first in the laboratory, to validate the functional requirements of the developed devices; and the second on civil works to evaluate the functional features of the devices, such as range, robustness and flexibility. The devices were successfully implemented resulting in a low cost, highly reliable, compact and non-destructive solution.
Exploring Clothing as a Barrier to Workplace Participation Faced by People Living with Disabilities
Authors: McBee-Black Kerri , Ha-Brookshire Jung
Published: March 2018

In response to research which argues that people living with a disability (PLWD) face societal barriers including workplace participation, this study explored how the barriers to social participation, specifically workplace participation, faced by PLWD are exacerbated by the lack of appropriate clothing and the role that stigma, self-efficacy, and clothing have in workplace participation. Finding appropriate clothing is a significant barrier to social participation for many PLWD. The social model of disability used in this study supports this by suggesting that it is society which places barriers to PLWD rather than their disability. A qualitative inquiry of semi-structured, in-depth interviews was used, and the results showcase six sub-themes of barriers: work defines me, disability as the barrier to workplace participation, work allows extra societal opportunities, stigma questions my self-efficacy, workplace accommodations diminish my stigma, and clothing builds my self-efficacy. The study found that, for PLWD, workplace participation is hindered because of occupational typecasting and lack of appropriate clothing, which increases their stigma and decreases their self-efficacy. The contributions of this study include theory support, policy, community, and educational enhancement.
Soil Processes, Pedofeatures and Microscale Metal Distributions: Relevant Study of Contaminant-Dynamics Calls for Pedology-Based Soil-Depth Sampling Strategies
Authors: Van OORT Folkert , Foy Eddy , Labanowski Jérôme , Leguédois Sophie , Jongmans Toine
Published: March 2018

Short-term variations of soil conditions affect the form, mobility and bioavailability of metal pollutants. Released metals migrate toward depth where they are intercepted or precipitate, leading to variable spatial metal distribution patterns, at a macro-, meso- and microscale. Studies at a mesoscale give access to trace metal (TM) associations induced by pedological processes. Although scarcely documented, such meso-scale studies represent an essential step for relevant environmental risk assessment, halfway between field- and molecular-scale investigations. We argued for such approach by performing optical microscopy and micro-X-ray fluorescence on thin sections from two soils, contaminated either by industrial zinc-smelter waste or by urban wastewater. Consistent correlation between key indicators of pedological processes (Fe, Mn, and Ca) and trace metals (Zn, Pb, and Cu) on some 20 elemental maps of TM-hosting soil constituents and pedofeatures reveal distinct coinciding localizations, illustrating TM-accumulation via interception or (co)-precipitation processes. Micromorphological interpretation of characteristic pedofeatures in subsurface horizons (crystals, argillans, ferrans, and mangans) containing significant amounts of TM provide valuable insight into the contaminant dynamics in terms of lixiviation, colloidal transport, redox conditions, or fungal activity. Our mesoscale approach stresses the importance of pedology-based sampling strategies, instead of systematic soil-depth sampling, for soil contamination research in natural ecosystems.
The Relationship between Firm Size and Age, and Its Social Responsibility Actions—Focus on a Developing Country (Romania)
Authors: Badulescu Alina , Badulescu Daniel , Saveanu Tomina , Hatos Roxana
Published: March 2018

The concept of Corporate Social Responsibility covers a wide range of actions which have been practiced for many years in Western countries. As well as in other developing and transitional countries, the concept of social responsibility emerged in Romania after 1990, concurrently with the set-up of many non-governmental organizations (NGOs) and the entrance of multinational companies and was rapidly adopted by several firms. The main purpose of our paper is to investigate practices and actions related to social responsibility, which are undertaken by small and medium enterprises (SMEs) in Romania and to reveal which factors really matter in determining different degrees of involvement in Corporate Social Responsibility (CSR) actions. The level of social responsibility actions undertaken by SMEs often depends on the decisions of their managers and the value orientation of the entrepreneur. Moreover, the younger a firm is, the less likely it is that it gets involved in CSR. This is our main assumption: young ventures display a weaker propensity for CSR actions. In order to validate this hypothesis, we used survey data, collected from 84 SMEs, operating in Oradea, Romania. Data were collected between July–September 2016 and analysed by the authors through correlations, independent sample T-tests and linear regression modelling. Our findings reveal that there are significant differences between newly established ventures and those with a longer history; however, age is not a determining factor of CSR. Although, in the literature, there is no clear consensus regarding whether there is a different model of implementation of CSR related practices in developing and transitional countries, especially in the case of SMEs, our results show there are no essential differences between the models of CSR involvement as these are known in the theory and practice of developed countries.
A European Project for Safer and Energy Efficient Buildings: Pro-GET-onE (Proactive Synergy of inteGrated Efficient Technologies on Buildings’ Envelopes)
Authors: Ferrante Annarita , Mochi Giovanni , Predari Giorgia , Badini Lorenzo , Fotopoulou Anastasia , Gulli Riccardo , Semprini Giovanni
Published: March 2018

The paper describes the progress of the four-year European project Pro-GET-onE currently under implementation. This research and innovation project is based on the assumption that greater efficiency, attractiveness, and marketable renovation can only be achieved through an integrated set of technologies where all the different requirements (energy, structural, functional) are optimally managed. Thus, the project focuses on the unprecedented integration of different technologies to achieve a multi-benefit approach that is provided by a closer integration between energy and non-energy related benefits. The project aims to combine different pre-fabricated elements in a unified and integrated system resulting in a higher performance in terms of energy requirements, structural safety, and social sustainability. The project attempts to achieve this goal through the introduction of innovative solutions for building envelopes to optimally combine the climatic, structural, and functional aspects through a significant architectural transformation and a substantial increase of the real estate value of the buildings. This augmented value obtained through the application of the inteGrated Efficient Technologies (GETs) is extremely important when considering the necessity of creating an innovative and attractive market in the energy renovation of existing buildings towards the target of nearly zero energy buildings (nZEBs).
Advanced Camera Image Cropping Approach for CNN-Based End-to-End Controls on Sustainable Computing
Authors: Sung Yunsick , Jin Yong , Kwak Jeonghoon , Lee Sang-Geol , Cho Kyungeun
Published: March 2018

Recent research on deep learning has been applied to a diversity of fields. In particular, numerous studies have been conducted on self-driving vehicles using end-to-end approaches based on images captured by a single camera. End-to-end controls learn the output vectors of output devices directly from the input vectors of available input devices. In other words, an end-to-end approach learns not by analyzing the meaning of input vectors, but by extracting optimal output vectors based on input vectors. Generally, when end-to-end control is applied to self-driving vehicles, the steering wheel and pedals are controlled autonomously by learning from the images captured by a camera. However, high-resolution images captured from a car cannot be directly used as inputs to Convolutional Neural Networks (CNNs) owing to memory limitations; the image size needs to be efficiently reduced. Therefore, it is necessary to extract features from captured images automatically and to generate input images by merging the parts of the images that contain the extracted features. This paper proposes a learning method for end-to-end control that generates input images for CNNs by extracting road parts from input images, identifying the edges of the extracted road parts, and merging the parts of the images that contain the detected edges. In addition, a CNN model for end-to-end control is introduced. Experiments involving the Open Racing Car Simulator (TORCS), a sustainable computing environment for cars, confirmed the effectiveness of the proposed method for self-driving by comparing the accumulated difference in the angle of the steering wheel in the images generated by it with those of resized images containing the entire captured area and cropped images containing only a part of the captured area. The results showed that the proposed method reduced the accumulated difference by 0.839% and 0.850% compared to those yielded by the resized images and cropped images, respectively.
Cooperation Modes of Operations and Financing in a Low-Carbon Supply Chain
Authors: Yang Lei , Chen Yufan , Ji Jingna
Published: March 2018

With the significant increase of fossil energy consumption and the ever-worsening pollution of environment, low-carbon development becomes an inevitable choice. Carbon finance can help firms alleviate the finance pressure from carbon emission reduction. This research explores two financing methods, delay-in-payment and bank loan; and two cooperation decisions, carbon emission reduction cooperation and price cooperation. Four scenarios are considered: non-cooperation, partial-cooperation delay-in-payment, supply chain carbon finance (SCCF), and full-cooperation. We discuss how firms make their pricing and carbon emission reduction decisions under different cooperative levels and financing methods. For a manufacturer-dominated supply chain, the results show that SCCF will help the small and medium enterprise seek cooperation with the monopoly manufacturer, and improve supply chain’s profit compared to green loan. What’s more, SCCF pattern can effectively control the total carbon emission. In addition, we extend the model to consider the retailer-dominated case. The results show that SCCF pattern can help increase the emission reduction rate of the whole supply chain. From the perspective of emission reduction efficiency, it is better for the government to promote the SCCF mode in the retailer-dominated supply chain.
The Effects of Land-Use Patterns on Home-Based Tour Complexity and Total Distances Traveled: A Path Analysis
Authors: De Abreu e Silva João
Published: March 2018

This work studies the relationships between the number of complex tours (with one or more intermediate stops) and simple home-based tours, total distances traveled by mode, and land-use patterns both at the residence and at the workplace using path analysis. The model includes commuting distance, car ownership and motorcycle ownership, which are intermediate variables in the relationship between land use, tour complexity and distances traveled by mode. The dataset used here was collected in a region comprising four municipalities located in the north of Portugal that are made up of urban areas, their sprawling suburbs, and surrounding rural hinterland. The results confirm the association between complex tours and higher levels of car use. Land-use patterns significantly affect travelled distances by mode either directly and indirectly via the influence of longer-term decisions like vehicle ownership and commuting distance. The results obtained highlight the role of socioeconomic variables in influencing tour complexity; in particular, households with children, household income, and workers with a college degree tend to do more complex tours. Land-use patterns mediate the effects of tour complexity on the kilometers travelled by different modes. Increasing densities in central areas, and particularly the concentration of jobs, have relevant benefits by reducing car kilometers driven.
Assessment of Groundwater Drought in the Mangyeong River Basin, Korea
Authors: Lee Jae , Park Jong , Chung Euijin , Woo Nam
Published: March 2018

When groundwater drought occurs, baseflow discharges to surface-water bodies will be reduced and then domestic and agricultural water usage becomes at risk of insufficient supply. Thus, in this study, several methods for groundwater drought assessment were tested with long-term monitoring water-level data in the study area to preserve groundwater sustainability from drought, principally caused by reduced precipitation and propagated through agricultural drought and groundwater drought. Because of the Monsoon climate on the Korean Peninsula, the groundwater storage (or water-level) is secured until the end of summer, then falls by natural discharge during the dry seasons of autumn, winter and the following spring. Thus, the rainfall in the wet season seems to mainly influence groundwater storage until the spring of the following year. As the groundwater level (GWL) declines due to natural drainage and the use of agricultural water increases by the end of the dry season (October–May), the GWL will become lowered below the critical level. Below this level, sufficient water supply is not secured. Using the Standardized Precipitation Index (SPI), threshold method and 95% probability occurrence method, drought detection and the frequency of drought are compared. Groundwater drought using the threshold method results in more frequent occurrence than using the SPI method. The 95% occurrence method responds to severe drought but it also has weakness in missing the man-induced GWL decline in every spring season. For groundwater drought assessment, an appropriate drought index should be utilized according to climatic conditions and catchment characteristics. In the study area, variations of the both natural and anthropogenic effects are mixed and the threshold method is more suitable as a measure for preventing water resources shortage.
Cadmium Nephrotoxicity Is Associated with Altered MicroRNA Expression in the Rat Renal Cortex
Authors: Fay Michael , Alt Lauren , Ryba Dominika , Salamah Ribhi , Peach Ryan , Papaeliou Alexander , Zawadzka Sabina , Weiss Andrew , Patel Nil , Rahman Asad , Stubbs-Russell Zyaria , Lamar Peter , Edwards Joshua , Prozialeck Walter
Published: March 2018

Cadmium (Cd) is a nephrotoxic environmental pollutant that causes a generalized dysfunction of the proximal tubule characterized by polyuria and proteinuria. Even though the effects of Cd on the kidney have been well-characterized, the molecular mechanisms underlying these effects have not been fully elucidated. MicroRNAs (miRNAs) are small non-coding RNAs that regulate cellular and physiologic function by modulating gene expression at the post-transcriptional level. The goal of the present study was to determine if Cd affects renal cortex miRNA expression in a well-established animal model of Cd-induced kidney injury. Male Sprague-Dawley rats were treated with subcutaneous injections of either isotonic saline or CdCl2 (0.6 mg/kg) 5 days a week for 12 weeks. The 12-week Cd-treatment protocol resulted in kidney injury as determined by the development of polyuria and proteinuria, and a significant increase in the urinary biomarkers Kim-1, β2 microglobulin and cystatin C. Total RNA was isolated from the renal cortex of the saline control and Cd treated animals, and differentially expressed miRNAs were identified using µParafloTM microRNA microarray analysis. The microarray results demonstrated that the expression of 44 miRNAs were significantly increased and 54 miRNAs were significantly decreased in the Cd treatment group versus the saline control (t-test, p ≤ 0.05, N = 6 per group). miR-21-5p, miR-34a-5p, miR-146b-5p, miR-149-3p, miR-224-5p, miR-451-5p, miR-1949, miR-3084a-3p, and miR-3084c-3p demonstrated more abundant expression and a significant two-fold or greater increased expression in the Cd-treatment group versus the saline control group. miR-193b-3p, miR-455-3p, and miR-342-3p demonstrated more abundant expression and a significant two-fold or greater decreased expression in the Cd-treatment group versus the saline control group. Real-time PCR validation demonstrated (1) a significant (t-test, p ≤ 0.05, N = 6 per group) increase in expression in the Cd-treated group for miR-21-5p (2.7-fold), miR-34a-5p (10.8-fold), miR-146b-5p (2-fold), miR-224-5p (10.2-fold), miR-3084a-3p (2.4-fold), and miR-3084c-3p (3.3-fold) and (2) a significant (t-test, p ≤ 0.05, N = 6 per group) 52% decrease in miR-455-3p expression in the Cd-treatment group. These findings demonstrate that Cd significantly alters the miRNA expression profile in the renal cortex and raises the possibility that dysregulated miRNA expression may play a role in the pathophysiology of Cd-induced kidney injury. In addition, these findings raise the possibility that Cd-dysregulated miRNAs might be used as urinary biomarkers of Cd exposure or Cd-induced kidney injury.
Indoxyl Sulfate Promotes Macrophage IL-1β Production by Activating Aryl Hydrocarbon Receptor/NF-κ/MAPK Cascades, but the NLRP3 inflammasome Was Not Activated
Authors: Wakamatsu Takuya , Yamamoto Suguru , Ito Toru , Sato Yoko , Matsuo Koji , Takahashi Yoshimitsu , Kaneko Yoshikatsu , Goto Shin , Kazama Junichiro , Gejyo Fumitake , Narita Ichiei
Published: March 2018

In chronic kidney disease (CKD) patients, accumulation of uremic toxins is associated with cardiovascular risk and mortality. One of the hallmarks of kidney disease-related cardiovascular disease is intravascular macrophage inflammation, but the mechanism of the reaction with these toxins is not completely understood. Macrophages differentiated from THP-1 cells were exposed to indoxyl sulfate (IS), a representative uremic toxin, and changes in inflammatory cytokine production and intracellular signaling molecules including interleukin (IL)-1, aryl hydrocarbon receptor (AhR), nuclear factor (NF)-κ, and mitogen-activated protein kinase (MAPK) cascades as well as the NLRP3 inflammasome were quantified by real-time PCR, Western blot analysis, and enzyme-linked immunosorbent assay. IS induced macrophage pro-IL-1β mRNA expression, although mature IL-1 was only slightly increased. IS increased AhR and the AhR-related mRNA expression; this change was suppressed by administration of proteasome inhibitor. IS promoted phosphorylation of NF-κB p65 and MAPK enzymes; the reaction and IL-1 expression were inhibited by BAY11-7082, an inhibitor of NF-κB. In contrast, IS decreased NLRP3 and did not change ASC, pro-caspase 1, or caspase-1 activation. IS-inducing inflammation in macrophages results from accelerating AhR-NF-κB/MAPK cascades, but the NLRP3 inflammasome was not activated. These reactions may restrict mature IL-1β production, which may explain sustained chronic inflammation in CKD patients.
A Tool for Assessment of Animal Health Laboratory Safety and Biosecurity: The Safety Module of the Food and Agriculture Organization’s Laboratory Mapping Tool
Authors: Mouillé Beatrice , Dauphin Gwenaelle , Wiersma Lidewij , Blacksell Stuart , Claes Filip , Kalpravidh Wantanee , Kabore Youssouf , Hietala Sharon
Published: March 2018

The Laboratory Management Tool (LMT) is a standardized spreadsheet-based assessment tool developed to help support national, regional, and global efforts to maintain an effective network of animal health and veterinary public health laboratories. The safety and biosecurity module of the LMT (LMT-S) includes 98 measures covering administrative, operational, engineering, and personal protective equipment practices used to provide laboratory safety and biosecurity. Performance aspects of laboratory infrastructure and technical compliance considered fundamental for ensuring that a laboratory is able to appropriately function in a safe and biosecure manner are systematically queried and scored for compliance on a four-point scale providing for a semi-quantitative assessment. Data collected is used to generate graphs and tables mapping levels of compliance with international standards and good practices, as well as for documenting progress over time. The LMT-S was employed by trained auditors in 34 laboratories located in 19 countries between 2015 and 2017. The tool is intended to help standardize animal health laboratory assessments, document compliance with recognized laboratory safety and biosecurity measures, serve as a self-help and training tool, and assist global laboratory development efforts by providing an accurate measurement of laboratory safety and biosecurity at local, national, and regional levels.
Comparison of Protein Gut Samples from Rhipicephalus spp. Using a Crude and an Innovative Preparation Method for Proteome Analysis
Authors: Karbanowicz Thomas , Nouwens Amanda , Tabor Ala , Rodriguez-Valle Manuel
Published: March 2018

Tick populations are controlled through the application of chemical pesticides. However, the rise in chemical resistance has prompted the investigation of other control methods such as the use of tick vaccines. Proteomic analysis provides valuable information about the possible function and localization of proteins, as candidate vaccine proteins are often either secreted or localized on the cell-surface membrane. Progress in the utilization of proteomics for the identification of novel treatment targets has been significant. However, their use in tick-specific investigations is still quite novel, with the continual development of tick-specific methodologies essential. In this study, an innovative sample preparation method was utilized to isolate epithelial cells from tick midguts to identify the membrane-bound proteins. Proteomic analysis was conducted comparing crude and innovative sample preparation methods with 692 and 1242 tick-specific proteins, 108 and 314 surface proteins respectively, isolated from the midguts of semi-engorged Rhipicephalus microplus adult female ticks. This research reports a novel preparation protocol for the analysis of tick midgut proteins which reduces host protein contamination.
Trend and Variability in Droughts in Northeast China Based on the Reconnaissance Drought Index
Authors: Yue Yuan , Shen Shuang-he , Wang Qi
Published: March 2018

Drought is a recurrent meteorological phenomenon that can be disastrous for humans; however, drought characteristics vary substantially in different regions. We use meteorological data from 140 stations in Northeast China for the period 1970–2014 to calculate the reconnaissance drought index (RDI) in order to examine droughts. We also analyze the strength of the relationships between the main large-scale atmospheric circulation patterns and RDI. Drought trends in the region are largely decreasing, but in the majority of cases, there is no statistical significance. Spatially, the pattern of droughts is a less frequent occurrence with greater severity and longer duration, mainly in the western part of the region. Severe droughts for the periods 1975–1979 and 2000–2004 were found, and most of these droughts occurred in the western part of Northeast China. The correlations between RDI and the atmospheric circulation indices POL, IAZC, and IEAT are negative, but the correlation between RDI and PDO is positive. The relationship between RDI and POL is stronger than the others, and the lagged effect is particularly obvious; thus POL can be recognized as the major driver of droughts over the period 1970–2014 in Northeast China.