bluuebunny/crossref_metadata_2025 huggingface dataset:
Intake Levels of Fish in the UK Paediatric Population
Authors: Kranz Sibylle , Jones Nicholas , Monsivais Pablo
Published: April 2017

The United Kingdom (UK) is an island and its culture, including diet, is heavily influenced by the maritime resources. Dietary guidance in the UK recommends intake of fish, which provides important nutrients, such as long-chain omega-3 polyunsaturated fatty acids (n-3 PUFA). This study was designed to describe the fish intake habits of UK children using a nationally representative sample. Dietary and socio-demographic data of children 2–18 (N = 2096) in the National Diet and Nutrition Survey Rolling Program (NDNS) Years 1–4 (2008–2012) were extracted. Average nutrient and food intakes were estimated. Logistic regression models were used to predict the meeting of fish intake recommendations, controlling for age, sex, income, total energy intake, and survey year. All analyses were conducted using survey routines and dietary survey weights. In this nationally representative study, 4.7% of children met the fish and 4.5% the oily fish intake recommendations; only 1.3% of the population met both recommendations. Fish intake levels did not significantly change with children’s increasing age. Higher vegetable but lower meat consumption predicted meeting the fish intake recommendations, indicating that children eating fish have better diet quality than non-consumers. Further research is needed to explore how intake behaviours can be changed to improve children’s diet quality.
Comments to Article by Solah VA et al., Nutrients 2017, 9, 149
Authors: Vuksan Vladimir , Jovanovski Elena , Zurbau Andreea , Komishon Allison
Published: April 2017

Dear Editor, We read with interest the article published in the 16 February 2017 issue of The Journal, titled “Effect of Fibre Supplementation on Body Weight and Composition, Frequency of Eating and Dietary Choice in Overweight Individuals” by Solah VA et al. [1].[...]
Nutritional Status Predicts 10-Year Mortality in Patients with End-Stage Renal Disease on Hemodialysis
Authors: Kang Shin , Chang Jai , Park Yongsoon
Published: April 2017

Protein-energy wasting (PEW) is associated with mortality in patients with end-stage renal disease (ESRD) on maintenance hemodialysis. The correct diagnosis of PEW is extremely important in order to predict clinical outcomes. However, it is unclear which parameters should be used to diagnose PEW. Therefore, this retrospective observational study investigated the relationship between mortality and nutritional parameters in ESRD patients on maintenance hemodialysis. A total of 144 patients were enrolled. Nutritional parameters, including body mass index, serum albumin, dietary intake, normalized protein catabolic rate (nPCR), and malnutrition inflammation score (MIS), were measured at baseline. Fifty-three patients died during the study. Survivors had significantly higher nPCR (1.10 ± 0.24 g/kg/day vs. 1.01 ± 0.21 g/kg/day; p = 0.048), energy intake (26.7 ± 5.8 kcal/kg vs. 24.3 ± 4.2 kcal/kg; p = 0.009) and protein intake (0.91 ± 0.21 g/kg vs. 0.82 ± 0.24 g/kg; p = 0.020), and lower MIS (5.2 ± 2.3 vs. 6.1 ± 2.1, p = 0.039). In multivariable analysis, energy intake <25 kcal/kg (HR 1.860, 95% CI 1.018–3.399; p = 0.044) and MIS > 5 (HR 2.146, 95% CI 1.173–3.928; p = 0.013) were independent variables associated with all-cause mortality. These results suggest that higher MIS and lower energy intake are harmful to ESRD patients on maintenance hemodialysis. Optimal energy intake could reduce mortality in these patients.
Glycosaminoglycan Binding and Non-Endocytic Membrane Translocation of Cell-Permeable Octaarginine Monitored by Real-Time In-Cell NMR Spectroscopy
Authors: Takechi-Haraya Yuki , Aki Kenzo , Tohyama Yumi , Harano Yuichi , Kawakami Toru , Saito Hiroyuki , Okamura Emiko
Published: April 2017

Glycosaminoglycans (GAGs), which are covalently-linked membrane proteins at the cell surface have recently been suggested to involve in not only endocytic cellular uptake but also non-endocytic direct cell membrane translocation of arginine-rich cell-penetrating peptides (CPPs). However, in-situ comprehensive observation and the quantitative analysis of the direct membrane translocation processes are challenging, and the mechanism therefore remains still unresolved. In this work, real-time in-cell NMR spectroscopy was applied to investigate the direct membrane translocation of octaarginine (R8) into living cells. By introducing 4-trifluoromethyl-l-phenylalanine to the N terminus of R8, the non-endocytic membrane translocation of 19F-labeled R8 (19F-R8) into a human myeloid leukemia cell line was observed at 4 °C with a time resolution in the order of minutes. 19F NMR successfully detected real-time R8 translocation: the binding to anionic GAGs at the cell surface, followed by the penetration into the cell membrane, and the entry into cytosol across the membrane. The NMR concentration analysis enabled quantification of how much of R8 was staying in the respective translocation processes with time in situ. Taken together, our in-cell NMR results provide the physicochemical rationale for spontaneous penetration of CPPs in cell membranes.
High Harmonics with Controllable Polarization by a Burst of Linearly-Polarized Driver Pulses
Authors: Neufeld Ofer , Bordo Eliyahu , Fleischer Avner , Cohen Oren
Published: April 2017

We theoretically explore a scheme for generation of bright circularly and elliptically polarized high-order harmonics by bursts of linearly polarized pulses with a rotating polarization axis. Circularly polarized harmonics are formed if the bursts are comprised of N pulses that uphold an N-fold rotational symmetry, for N > 2. Rotating the polarization axes of the comprising pulses can generate elliptical harmonics with a collectively tunable ellipticity, from circular through elliptic to linear. The method preserves the single-cycle, single-atom and macroscopic physics of ‘standard’ linearly polarized high harmonic generation, with a high yield and cutoff energy. We investigate the method from a time-domain perspective, as well as a photonic perspective, and formulate the energy and spin-angular momentum conservation laws for this scheme. We find that the case of N = 4 is optimal for this method, resulting with the highest conversion efficiency of elliptical photons. The new features of this source offer new applications to helical ultrafast spectroscopy and ellipsometry.
The Relative Effectiveness of the Minimum Wage and the Earned Income Tax Credit as Anti-Poverty Tools
Authors: Quinn Joseph , Cahill Kevin
Published: April 2017

In the search for effective measures to combat poverty, two government policies have been given much attention. One is the establishment of a federal minimum wage to help workers secure a decent standard of living. The second measure is the Earned Income Tax Credit, which gives tax refunds to workers in households that fall below a set standard of income. Both policies have supporters and critics regarding the effectiveness of the policies. This essay provides an economic analysis of the two measures. Among the issues discussed are how the policies affect employment and poverty, and how well targeted they are at the population at risk.
Surface Motion and Structural Instability Monitoring of Ming Dynasty City Walls by Two-Step Tomo-PSInSAR Approach in Nanjing City, China
Authors: Chen Fulong , Wu Yuhua , Zhang Yimeng , Parcharidis Issaak , Ma Peifeng , Xiao Ruya , Xu Jia , Zhou Wei , Tang Panpan , Foumelis Michael
Published: April 2017

Spaceborne Multi-Temporal Synthetic Aperture Radar (SAR) Interferometry (MT-InSAR) has been a valuable tool in mapping motion phenomena in different scenarios. Recently, the capabilities of MT-InSAR for risk monitoring and preventive analysis of heritage sites have increasingly been exploited. Considering the limitations of conventional MT-InSAR techniques, in this study a two-step Tomography-based Persistent Scatterers (PS) Interferometry (Tomo-PSInSAR) approach is proposed for monitoring ground deformation and structural instabilities over the Ancient City Walls (Ming Dynasty) in Nanjing city, China. For the purpose of this study we utilized 26 Stripmap acquisitions from TerraSAR-X and TanDEM-X missions, spanning from May 2013 to February 2015. As a first step, regional-scale surface deformation rates on single PSs were derived (ranging from −40 to +5 mm/year) and used for identifying deformation hotspots as well as for the investigation of a potential correlation between urbanization and the occurrence of surface subsidence. As a second step, structural instability parameters of ancient walls (linear motion rates, non-linear motions and material thermodynamics) were estimated by an extended four-dimensional Tomo-PSInSAR model. The model applies a two-tier network strategy; that is, the detection of most reliable single PSs in the first-tier Delaunay triangulation network followed by the detection of remaining single PSs and double PSs on the second-tier local star network referring to single SPs extracted in the first-tier network. Consequently, a preliminary phase calibration relevant to the Atmospheric Phase Screen (APS) is not needed. Motion heterogeneities in the spatial domain, either caused by thermal kinetics or displacement trends, were also considered. This study underlines the potential of the proposed Tomo-PSInSAR solution for the monitoring and conservation of cultural heritage sites. The proposed approach offers a quantitative indicator to local authorities and planners for assessing potential damages as well as for the design of remediation activities.
Multispectral LiDAR Point Cloud Classification: A Two-Step Approach
Authors: Chen Biwu , Shi Shuo , Gong Wei , Zhang Qingjun , Yang Jian , Du Lin , Sun Jia , Zhang Zhenbing , Song Shalei
Published: April 2017

Target classification techniques using spectral imagery and light detection and ranging (LiDAR) are widely used in many disciplines. However, none of the existing methods can directly capture spectral and 3D spatial information simultaneously. Multispectral LiDAR was proposed to solve this problem as its data combines spectral and 3D spatial information. Point-based classification experiments have been conducted with the use of multispectral LiDAR; however, the low signal to noise ratio creates salt and pepper noise in the spectral-only classification, thus lowering overall classification accuracy. In our study, a two-step classification approach is proposed to eliminate this noise during target classification: routine classification based on spectral information using spectral reflectance or a vegetation index, followed by neighborhood spatial reclassification. In an experiment, a point cloud was first classified with a routine classifier using spectral information and then reclassified with the k-nearest neighbors (k-NN) algorithm using neighborhood spatial information. Next, a vegetation index (VI) was introduced for the classification of healthy and withered leaves. Experimental results show that our proposed two-step classification method is feasible if the first spectral classification accuracy is reasonable. After the reclassification based on the k-NN algorithm was combined with neighborhood spatial information, accuracies increased by 1.50–11.06%. Regarding identification of withered leaves, VI performed much better than raw spectral reflectance, with producer accuracy increasing from 23.272% to 70.507%.
Phenological Observations on Classical Prehistoric Sites in the Middle and Lower Reaches of the Yellow River Based on Landsat NDVI Time Series
Authors: Pan Yuqing , Nie Yueping , Watene Chege , Zhu Jianfeng , Liu Fang
Published: April 2017

Buried archeological features show up as crop marks that are mostly visible using high-resolution image data. Such data are costly and restricted to small regions and time domains. However, a time series of freely available medium resolution imagery can be employed to detect crop growth changes to reveal subtle surface marks in large areas. This paper aims to study the classical Chinese settlements of Taosi and Erlitou over large areas using Landsat NDVI time series crop phenology to determine the optimum periods for detection and monitoring of crop anomalies. Burial areas (such as the palace area and the sacrificial area) were selected as the research area while the surrounding empty fields with a low density of ancient features were used as reference regions. Landsat NDVI covering two years’ growth periods of wheat and maize were computed and analyzed using Pearson’s correlation coefficient and Euclidean distance. Similarities or disparities between the burial areas and their empty areas were computed using the Hausdorff distance. Based on the phenology of crop growth, the time series NDVI images of winter wheat and summer maize were generated to analyze crop anomalies in the archeological sites. Results show that the Hausdorff distance was high during the critical stages of water for both crops and that the images of high Hausdorff distance can provide more obvious subsurface archeological information.
Improving Fractional Impervious Surface Mapping Performance through Combination of DMSP-OLS and MODIS NDVI Data
Authors: Guo Wei , Lu Dengsheng , Kuang Wenhui
Published: April 2017

Impervious surface area (ISA) is an important parameter for many studies such as urban climate, urban environmental change, and air pollution; however, mapping ISA at the regional or global scale is still challenging due to the complexity of impervious surface features. The Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) data have been used for ISA mapping, but high uncertainty existed due to mixed-pixel and data-saturation problems. This paper presents a new index called normalized impervious surface index (NISI), which is an integration of DMSP-OLS and Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data, in order to reduce these problems. Meanwhile, this newly developed index is compared with previously used indices—Human Settlement Index (HSI) and Vegetation Adjusted Nighttime light Urban Index (VANUI)—in ISA mapping performance. We selected China as an example to map fractional ISA distribution through a support vector regression approach based on the relationship between the index and Landsat-derived ISA data. The results indicate that the proposed NISI provided better ISA estimation accuracy than HSI and VANUI, especially when the fractional ISA in a pixel is relatively large (i.e., >0.6) or very small (i.e., <0.2). This approach can be used to rapidly update ISA datasets at regional and global scales.
In-Field High-Throughput Phenotyping of Cotton Plant Height Using LiDAR
Authors: Sun Shangpeng , Li Changying , Paterson Andrew
Published: April 2017

A LiDAR-based high-throughput phenotyping (HTP) system was developed for cotton plant phenotyping in the field. The HTP system consists of a 2D LiDAR and an RTK-GPS mounted on a high clearance tractor. The LiDAR scanned three rows of cotton plots simultaneously from the top and the RTK-GPS was used to provide the spatial coordinates of the point cloud during data collection. Configuration parameters of the system were optimized to ensure the best data quality. A height profile for each plot was extracted from the dense three dimensional point clouds; then the maximum height and height distribution of each plot were derived. In lab tests, single plants were scanned by LiDAR using 0.5° angular resolution and results showed an R2 value of 1.00 (RMSE = 3.46 mm) in comparison to manual measurements. In field tests using the same angular resolution; the LiDAR-based HTP system achieved average R2 values of 0.98 (RMSE = 65 mm) for cotton plot height estimation; compared to manual measurements. This HTP system is particularly useful for large field application because it provides highly accurate measurements; and the efficiency is greatly improved compared to similar studies using the side view scan.
Efficient Actor Recovery Paradigm for Wireless Sensor and Actor Networks
Authors: Mahjoub Reem , Elleithy Khaled
Published: April 2017

The actor nodes are the spine of wireless sensor and actor networks (WSANs) that collaborate to perform a specific task in an unverified and uneven environment. Thus, there is a possibility of high failure rate in such unfriendly scenarios due to several factors such as power consumption of devices, electronic circuit failure, software errors in nodes or physical impairment of the actor nodes and inter-actor connectivity problem. Therefore, it is extremely important to discover the failure of a cut-vertex actor and network-disjoint in order to improve the Quality-of-Service (QoS). In this paper, we propose an Efficient Actor Recovery (EAR) paradigm to guarantee the contention-free traffic-forwarding capacity. The EAR paradigm consists of a Node Monitoring and Critical Node Detection (NMCND) algorithm that monitors the activities of the nodes to determine the critical node. In addition, it replaces the critical node with backup node prior to complete node-failure which helps balancing the network performance. The packets are handled using Network Integration and Message Forwarding (NIMF) algorithm that determines the source of forwarding the packets; either from actor or sensor. This decision-making capability of the algorithm controls the packet forwarding rate to maintain the network for a longer time. Furthermore, for handling the proper routing strategy, Priority-Based Routing for Node Failure Avoidance (PRNFA) algorithm is deployed to decide the priority of the packets to be forwarded based on the significance of information available in the packet. To validate the effectiveness of the proposed EAR paradigm, the proposed algorithms were tested using OMNET++ simulation.
Electrochemical Detection of Dopamine Using 3D Porous Graphene Oxide/Gold Nanoparticle Composites
Authors: Choo Sung-Sik , Kang Ee-Seul , Song Inbeom , Lee Donghyun , Choi Jeong-Woo , Kim Tae-Hyung
Published: April 2017

The detection of dopamine in a highly sensitive and selective manner is crucial for the early diagnosis of a number of neurological diseases/disorders. Here, a report on a new platform for the electrochemical detection of dopamine with a considerable accuracy that comprises a 3D porous graphene oxide (pGO)/gold nanoparticle (GNP)/pGO composite-modified indium tin oxide (ITO) is presented. The pGO was first synthesized and purified by ultrasonication and centrifugation, and it was then further functionalized on the surface of a GNP-immobilized ITO electrode. Remarkably, owing to the synergistic effects of the pGO and GNPs, the 3D pGO-GNP-pGO-modified ITO electrode showed a superior dopamine-detection performance compared with the other pGO- or GNP-modified ITO electrodes. The linear range of the newly developed sensing platform is from 0.1 μM to 30 μM with a limit of detection (LOD) of 1.28 μM, which is more precise than the other previously reported GO-functionalized electrodes. Moreover, the 3D pGO-GNP-pGO-modified ITO electrodes maintained their detection capability even in the presence of several interfering molecules (e.g., ascorbic acid, glucose). The proposed platform of the 3D pGO-GNP-pGO-modified ITO electrode could therefore serve as a competent candidate for the development of a dopamine-sensing platform that is potentially applicable for the early diagnosis of various neurological diseases/disorders.
Fuzzy System-Based Target Selection for a NIR Camera-Based Gaze Tracker
Authors: Naqvi Rizwan , Arsalan Muhammad , Park Kang
Published: April 2017

Gaze-based interaction (GBI) techniques have been a popular subject of research in the last few decades. Among other applications, GBI can be used by persons with disabilities to perform everyday tasks, as a game interface, and can play a pivotal role in the human computer interface (HCI) field. While gaze tracking systems have shown high accuracy in GBI, detecting a user’s gaze for target selection is a challenging problem that needs to be considered while using a gaze detection system. Past research has used the blinking of the eyes for this purpose as well as dwell time-based methods, but these techniques are either inconvenient for the user or requires a long time for target selection. Therefore, in this paper, we propose a method for fuzzy system-based target selection for near-infrared (NIR) camera-based gaze trackers. The results of experiments performed in addition to tests of the usability and on-screen keyboard use of the proposed method show that it is better than previous methods.
A Robust Crowdsourcing-Based Indoor Localization System
Authors: Zhou Baoding , Li Qingquan , Mao Qingzhou , Tu Wei
Published: April 2017

WiFi fingerprinting-based indoor localization has been widely used due to its simplicity and can be implemented on the smartphones. The major drawback of WiFi fingerprinting is that the radio map construction is very labor-intensive and time-consuming. Another drawback of WiFi fingerprinting is the Received Signal Strength (RSS) variance problem, caused by environmental changes and device diversity. RSS variance severely degrades the localization accuracy. In this paper, we propose a robust crowdsourcing-based indoor localization system (RCILS). RCILS can automatically construct the radio map using crowdsourcing data collected by smartphones. RCILS abstracts the indoor map as the semantics graph in which the edges are the possible user paths and the vertexes are the location where users may take special activities. RCILS extracts the activity sequence contained in the trajectories by activity detection and pedestrian dead-reckoning. Based on the semantics graph and activity sequence, crowdsourcing trajectories can be located and a radio map is constructed based on the localization results. For the RSS variance problem, RCILS uses the trajectory fingerprint model for indoor localization. During online localization, RCILS obtains an RSS sequence and realizes localization by matching the RSS sequence with the radio map. To evaluate RCILS, we apply RCILS in an office building. Experiment results demonstrate the efficiency and robustness of RCILS.
A 7.4 ps FPGA-Based TDC with a 1024-Unit Measurement Matrix
Authors: Zhang Min , Wang Hai , Liu Yan
Published: April 2017

In this paper, a high-resolution time-to-digital converter (TDC) based on a field programmable gate array (FPGA) device is proposed and tested. During the implementation, a new architecture of TDC is proposed which consists of a measurement matrix with 1024 units. The utilization of routing resources as the delay elements distinguishes the proposed design from other existing designs, which contributes most to the device insensitivity to variations of temperature and voltage. Experimental results suggest that the measurement resolution is 7.4 ps, and the INL (integral nonlinearity) and DNL (differential nonlinearity) are 11.6 ps and 5.5 ps, which indicates that the proposed TDC offers high performance among the available TDCs. Benefitting from the FPGA platform, the proposed TDC has superiorities in easy implementation, low cost, and short development time.
A Strain-Based Method to Estimate Slip Angle and Tire Working Conditions for Intelligent Tires Using Fuzzy Logic
Authors: Garcia-Pozuelo Daniel , Yunta Jorge , Olatunbosun Oluremi , Yang Xiaoguang , Diaz Vicente
Published: April 2017

Tires equipped with sensors, the so-called “intelligent tires”, can provide vital information for control systems, drivers and external users. In this research, tire dynamic strain characteristics in cornering conditions are collected and analysed in relation to the variation of tire working conditions, such as inflation pressure, rolling speed, vertical load and slip angle. An experimental tire strain-based prototype and an indoor tire test rig are used to demonstrate the suitability of strain sensors to establish relations between strain data and lateral force. The results of experiments show that strain values drop sharply when lateral force is decreasing, which can be used to predict tire slip conditions. As a first approach to estimate some tire working conditions, such as the slip angle and vertical load, a fuzzy logic method has been developed. The simulation and test results confirm the feasibility of strain sensors and the proposed computational model to solve the non-linearity characteristics of the tires’ parameters and turn tires into a source of useful information.
Intelligent Medical Garments with Graphene-Functionalized Smart-Cloth ECG Sensors
Authors: Yapici Murat , Alkhidir Tamador
Published: April 2017

Biopotential signals are recorded mostly by using sticky, pre-gelled electrodes, which are not ideal for wearable, point-of-care monitoring where the usability of the personalized medical device depends critically on the level of comfort and wearability of the electrodes. We report a fully-wearable medical garment for mobile monitoring of cardiac biopotentials from the wrists or the neck with minimum restriction to regular clothing habits. The wearable prototype is based on elastic bands with graphene functionalized, textile electrodes and battery-powered, low-cost electronics for signal acquisition and wireless transmission. Comparison of the electrocardiogram (ECG) recordings obtained from the wearable prototype against conventional wet electrodes indicate excellent conformity and spectral coherence among the two signals.
New Compact 3-Dimensional Shape Descriptor for a Depth Camera in Indoor Environments
Authors: Choi Hyukdoo , Kim Euntai
Published: April 2017

This study questions why existing local shape descriptors have high dimensionalities (up to hundreds) despite simplicity of local shapes. We derived an answer from a historical context and provided an alternative solution by proposing a new compact descriptor. Although existing descriptors can express complicated shapes and depth sensors have been improved, complex shapes are rarely observed in an ordinary environment and a depth sensor only captures a single side of a surface with noise. Therefore, we designed a new descriptor based on principal curvatures, which is compact but practically useful. For verification, the CoRBS dataset, the RGB-D Scenes dataset and the RGB-D Object dataset were used to compare the proposed descriptor with existing descriptors in terms of shape, instance, and category recognition rate. The proposed descriptor showed a comparable performance with existing descriptors despite its low dimensionality of 4.
A New Input Device for Spastics Based on Strain Gauge
Authors: Buchhold Niels , Baumgartner Christian
Published: April 2017

This article presents a new sensor for use by people with spastic disorders and similar conditions and enables them to steer and control medical devices such as electric powered wheelchairs. As spastic patients often suffer from cramping of their extremities, which can then no longer be controlled, using a standard joystick while operating a powered wheelchair can lead to dangerous situations. To prevent this, we designed a sensor based on strain gauges, which is shaped like a flat disc that can be operated using any body part. By shifting weight along the x- and y-axis, the disc tilts in all directions thereby generating proportionate output signals. The disc can also be pressed downward (z-axis), for example, to open a wheelchair’s menu. Thanks to the sensor’s flat disc-like construction and the option of mounting it into a control panel, users are not in danger of becoming stuck on the disc during spastic episodes. In the event of a spasm, body parts simply slide over the disc reducing risk of unintended actions. The sensor is adaptive and adjustable enabling it to fit a user’s range of strength and motion at any time. It was developed to ensure users can operate sensitive systems safely.
Carbon Nanotube-Based Chemiresistive Sensors
Authors: Tang Ruixian , Shi Yongji , Hou Zhongyu , Wei Liangming
Published: April 2017

The development of simple and low-cost chemical sensors is critically important for improving human life. Many types of chemical sensors have been developed. Among them, the chemiresistive sensors receive particular attention because of their simple structure, the ease of high precise measurement and the low cost. This review mainly focuses on carbon nanotube (CNT)-based chemiresistive sensors. We first describe the properties of CNTs and the structure of CNT chemiresistive sensors. Next, the sensing mechanism and the performance parameters of the sensors are discussed. Then, we detail the status of the CNT chemiresistive sensors for detection of different analytes. Lastly, we put forward the remaining challenges for CNT chemiresistive sensors and outlook the possible opportunity for CNT chemiresistive sensors in the future.
A Latency and Coverage Optimized Data Collection Scheme for Smart Cities Based on Vehicular Ad-hoc Networks
Authors: Xu Yixuan , Chen Xi , Liu Anfeng , Hu Chunhua
Published: April 2017

Using mobile vehicles as “data mules” to collect data generated by a huge number of sensing devices that are widely spread across smart city is considered to be an economical and effective way of obtaining data about smart cities. However, currently most research focuses on the feasibility of the proposed methods instead of their final performance. In this paper, a latency and coverage optimized data collection (LCODC) scheme is proposed to collect data on smart cities through opportunistic routing. Compared with other schemes, the efficiency of data collection is improved since the data flow in LCODC scheme consists of not only vehicle to device transmission (V2D), but also vehicle to vehicle transmission (V2V). Besides, through data mining on patterns hidden in the smart city, waste and redundancy in the utilization of public resources are mitigated, leading to the easy implementation of our scheme. In detail, no extra supporting device is needed in the LCODC scheme to facilitate data transmission. A large-scale and real-world dataset on Beijing is used to evaluate the LCODC scheme. Results indicate that with very limited costs, the LCODC scheme enables the average latency to decrease from several hours to around 12 min with respect to schemes where V2V transmission is disabled while the coverage rate is able to reach over 30%.
Liquid Chromatography Tandem Mass Spectrometry Analysis of Synthetic Coccidiostats in Eggs
Authors: Buiarelli Francesca , Di Filippo Patrizia , Riccardi Carmela , Pomata Donatella , Giannetti Luigi , Neri Bruno , Rago Daniela
Published: April 2017

Coccidiostats are synthetic drugs administered to animals, especially to poultry, to cure coccidiosis. In this paper, we present a selective liquid chromatography-tandem mass spectrometry (LC-MS/MS) method to analyze residues of five synthetic coccidiostats in eggs: clazuril, diclazuril, robenidine, nicarbazin, toltrazuril and its two metabolites. The extraction efficiency was evaluated by testing several solvents, pH, different volumes and time of extraction. The clean-up procedures were optimized using different solid phase extraction cartridges and different eluants. The chromatographic separation was achieved in reversed phase using a gradient of 0.1% formic acid in water and acetonitrile, whereas the MS detection was performed in negative electrospray ionization (ESI) for all the analytes, except for the robenidine. The developed method has been validated according to Commission Decision 2002/657/CE. The validation parameters, as linearity, precision, recovery, specificity, decision limit (CCα), detection capability (CCβ), and robustness have been determined. The proposed method resulted simple, fast, and suitable for screening and confirmation purposes.
Relating Knowledge and Perceptions of Sustainable Water Management to Preferences for Smart Irrigation Technology
Authors: Suh Dong , Khachatryan Hayk , Rihn Alicia , Dukes Michael
Published: April 2017

Water quantity and quality concerns in urban environments have prompted conservation groups, governmental agencies, and policy makers to develop and promote residential water conservation programs, including restrictions on residential landscape irrigation practices and incentives for the adoption of water-efficient appliances. Previous literature links household characteristics, financial incentives, and demographic characteristics to the adoption of water-efficient appliances and overall water use. However, relatively little attention has been given toward understanding how homeowners’ perceptions and knowledge of smart irrigation technologies affect their preferences or stated purchase likelihood of such irrigation equipment. To address this gap in the literature, this paper identifies perception- and knowledge-related factors that are correlated with the purchase likelihood of smart irrigation controllers. The generalized logit regression model results suggest that knowledge about irrigation systems and residential landscaping are positively correlated with purchase likelihood. Similarly, homeowners’ perceptions about conservation efforts, water restrictions, and their neighbors’ irrigation habits all increase purchase likelihood. Combined with statistically-significant correlations of several socio-demographic variables and purchase likelihood, these results have theoretical and practical implications, which are summarized in this paper.
The Implementation of Green Infrastructure: Relating a General Concept to Context and Site
Authors: Lindholm Gunilla
Published: April 2017

In the quest for more sustainable urban landscape development, the concept of “green infrastructure” (GI) has become central in policy documents and as a multifunctional general planning tool. GI is not, however, a simple and unambiguous solution. While in policy documents there are claims for more and connected GI, actual urban development takes another direction. The densifying imperative is hard to combine with an increased and more connected GI. This paper argues for a critical and diversified approach to the concept of GI, in order to facilitate its implementation in urban planning and management. Any kind of GI will not deliver all ecosystems services in any place, not without land use conflicts, investments and long term operating costs. This calls for a GI concept linked to actors and mediating conflicting values. Linguistic as well as spatial definitions of the two relevant dichotomies of “green-grey” and “public-private” are crucial in GI location, design, construction and management, it is argued. Overarching representations of GI will be needed, but not only pictured as a separate system, but also displayed with necessary integration to the whole urban landscape. Development over time will need an intersectorial implementation and management program. Some of the GI intentions may be implemented in planning processes, some through re-organization and redesign of public space, and some by agreements with landowners. To reach out to implementation in ordinary urban development, GI needs to be described in a way that establishes points of connection to a variety of relevant actors and organizations taking part in implementation of GI.
Improving the Diagnosis Accuracy of Hydrothermal Aging Degree of V2O5/WO3–TiO2 Catalyst in SCR Control System Using an GS–PSO–SVM Algorithm
Authors: Hu Jie , Zeng Jiawei , Wei Li , Yan Fuwu
Published: April 2017

Selective catalytic reduction (SCR) is one of the most effective technologies used for eliminating NOx from diesel engines. This paper presents a novel method based on a support vector machine (SVM) and particle swarm optimization (PSO) with grid search (GS) to diagnose the degree of aging of the V2O5/WO3–TiO2 catalyst in the SCR system. This study shows the aging effect on the performance of a NH3 slip based closed-loop SCR control system under different aging factors (α), which are defined by the SCR reaction rate ( R scr ). A diagnosis of the performance of GS–PSO–SVM has been presented as compared to SVM, GS–SVM and PSO–SVM to get reliable results. The results show that the average prediction diagnosis accuracy of the degree of catalytic aging is up to 93.8%, 93.1%, 92.9% and 92.0% for GS–PSO–SVM, PSO–SVM, GS–SVM and SVM respectively. It is demonstrated that GS–PSO–SVM is able to identify the SCR catalyst’s degree of aging, to ultimately assist with fault tolerance in the aging of the SCR catalyst.
A System-of-Systems Framework for Improved Human, Ecologic and Economic Well-Being
Authors: Genaidy Ash , Huston Ronald , Dionysiou Dionysios , Karwowski Waldemar
Published: April 2017

“Advances in technology and management not keeping pace with the ever-increasing urban problems” is attributed in this research to the poor understanding of person-focused governance of societal, environmental and economic entities. The objective of this paper is to present an adaptive institutional model of person-driven effectiveness and ineffectiveness. The model proposes that human, ecologic and economic outcomes are heavily influenced by a complex system of systems, spanning from individually unique “non-physical influencers” to a broader set of social and environmental influencers that have a common impact on the larger society-environment-economy (SEE) system. At the heart of the model is an analytic formulation that explains the phenomena of non-physical blocker, enhancer and indifferent, which are responsible for the adaptation and maladaptation of social agents and, accordingly, for the sustainability and unsustainability of SEE systems. Examples are provided to illustrate the model applications: (a) the non-physical and maladaptive syndromes as antecedents of multi-morbidity; and (b) the broadened and narrowed minds as sources of sustainability and unsustainability at the SEE system level within the context of emerging technologies such as engineered nanomaterials.
Energy R&D towards Sustainability: A Panel Analysis of Government Budget for Energy R&D in OECD Countries (1974–2012)
Authors: Sun Inkyoung , Kim So
Published: April 2017

Energy transition is one of the greatest challenges for sustainability. However, the overall composition of the world energy supply has not changed much since the late 1970s, with fossil fuels providing 81% of the world’s total primary energy supply. While political leaders increasingly call for proactive policies to innovate the energy sector in the face of climate change, governments around the world commit vastly different levels of budgets to energy R&D. This research examines the potential determinants of cross-national variations in government budget allocations for energy R&D with three perspectives. With the panel data analysis of OECD countries (1974–2012), we check the supply-side, demand-side, and institutional factors inducing government investment in R&D for energy in general as well as for renewable energy. Among the multitude of factors tested in our analysis, gross domestic R&D expenditure, refinery output, and the rightist orientation of the governing party show significantly positive influences on government R&D budgets for energy in general. However, refinery output shows the negative effect on government R&D budget for renewables. This contrasting finding about the impact of refinery output on government investment in energy R&D in general vs. renewable energy R&D suggests that policymakers and scholars need to better appreciate the complex roles of the oil sector in driving public R&D investment in energy. It also calls for more proactive renewable energy policy to make progress towards sustainable energy transition.
Effectiveness and Limitation of Coastal Dykes in Jakarta: The Need for Prioritizing Actions against Land Subsidence
Authors: Takagi Hiroshi , Fujii Daisuke , Esteban Miguel , Yi Xiong
Published: April 2017

Jakarta has been experiencing severe land subsidence over the last few decades. A questionnaire survey of local inhabitants revealed that seawater is already overtopping coastal dykes and flooding a vulnerable community along Jakarta’s waterfront. The present study projects coastal floods around Jakarta until the year 2050 to understand the long term effectiveness of proposed dykes under continuing rapid land subsidence scenarios. This is done through a hydrodynamic model that considers land subsidence, sea-level rise, and tides. The analysis confirms that, if high enough, coastal dykes will help to prevent flooding, though their effectiveness will eventually disappear as land subsidence continues. For example, a 3-m dyke, which is expected to be sufficiently high to cope with present-day conditions, could completely lose its ability to stop floods by the year 2040. Moreover, higher dykes can also bring about other problems, because if they are overtopped, they actually prolong flooding, essentially trapping a higher volume of water inland. On the other hand, a small 1-m dyke can be expected to stop coastal floods if land subsidence can be stopped. This study demonstrates that actions to stop land subsidence would be the most effective countermeasure to mitigate coastal floods from the middle of the 21st century onwards, emphasizing the need to prioritize such actions among the range of countermeasures being proposed for Jakarta.
Soil Respiration Response to Long-Term Freezing Saline Water Irrigation with Plastic Mulching in Coastal Saline Plain
Authors: Li Xiaoguang , Guo Kai , Feng Xiaohui , Liu Haiman , Liu Xiaojing
Published: April 2017

The technology of freezing saline water irrigation (FSWI) with plastic mulching has been regarded as an effective way to reclaim the highly saline soil in coastal plains, which enabled the growth of crops in heavy saline soil that was not suitable for any crop growth before. However, after long-term treatment with FSWI, the microenvironment of the soil has been found to be affected by the growth of crops, which will directly influence the balance of soil carbon emissions. In this study, the characteristics of soil respiration in a typical saline field (planted with cotton) under four treatments (FSWI in Winter with plastic mulching, FSWI + Mulch; FSWI in Winter without plastic mulching, FSWI; plastic mulching in Spring without FSWI, mulch; no plastic mulching and no FSWI, CK) were investigated between June and November from 2015 to 2016. The results suggested that the soil surface temperature was an important factor that affected the soil respiration rate in each treatment during the growth period of cotton. FSWI + Mulch can reduce the soil surface salinity to 0.4% during the seedling stage, which increased the survival rate and the abundance of bacteria, fungi, and actinomycetes in the cotton field and subsequently increased soil respiration. By examining the effects of FWSI and mulching on soil respiration and its influencing factors, this study provides practical and theoretical insight into the sustainable development of agriculture in coastal saline plains.
The Relationship between Firm Characteristics and the Disclosure of Sustainability Reporting
Authors: Wang Mao-Chang
Published: April 2017

Stakeholder theory is a major approach to research on sustainability management. Firm characteristics, including corporate governance and business characteristics, can be represented in terms of their effects on stakeholders. In this study, a multi-regression model is used to examine the relationship between firm characteristics and the disclosure of sustainability reporting for the Taiwan 50 Index-listed companies. Least-squares regression, panel data regression, and logistic regression analyses are applied. The results show that seven corporate governance and business characteristics, namely the size of the board of directors, ratio of independent directors, audit committee, ratio of export income, percentage of foreign shareholders’ holdings, fixed asset staleness, and firm growth are positively related to the disclosure of sustainability reporting, whereas the percentage of director holdings and stock price per share are negatively related to the disclosure of sustainability reporting. This study supports the notion that stakeholder involvement is related to the disclosure of sustainability reporting.
Cooperative Downlink Listening for Low-Power Long-Range Wide-Area Network
Authors: Kim Byoungwook , Hwang Kwang-il
Published: April 2017

Recently, the development of the Internet of Things (IoT) applications has become more active with the emergence of low-power wide-area network (LPWAN), which has the advantages of low-power and long communication distance. Among the various LPWAN technologies, long-range wide-area network (LoRaWAN, or LoRa) is considered as the most mature technology. However, since LoRa performs uplink-oriented communication to increase energy efficiency, there is a restriction on the downlink function from the network server to the end devices. In this paper, we propose cooperative downlink listening to solve the fundamental problem of LoRa. In particular, the proposed scheme can be extended to various communication models such as groupcasting and geocasting by combining with the data-centric model. Experiments also show that the proposed technology not only significantly reduces network traffic compared to the LoRa standard, but also guarantees maximum energy efficiency of the LoRa.
Identifying Irrigation Strategies for Improved Agricultural Water Productivity in Irrigated Maize Production through Crop Simulation Modelling
Authors: Greaves Geneille E. , Wang Yu-Min
Published: April 2017

Identifying irrigation strategies that improve agricultural water use efficiency (WUE) have a pivotal role to play in sustainable water development. In this study, the AquaCrop model was used to examine the impact of different irrigation scheduling options on yields to identify viable strategies to enhance WUE for irrigated maize. Two scheduling scenarios at water application depths ranging from 20 to 50 mm were investigated: schedules based on allowable depletion of total available water (TAW) in the root zone and interval schedules based on irrigating at predefined daily intervals. For both scenarios, simulated yields, seasonal water applied and percent percolation loss were within the range of 9.16 to 10.22 ton/ha, 180 to 950 mm and 0–61%, respectively. The WUE in terms of water applied (WUEIrr) and crop evapotranspiration (WUEET) ranged from 1.07 to 5.48 kg/m3 and 2.42 to 4.42 kg/m3, respectively. The results revealed that depletion levels of 40–50% TAW at water depths of 20–40 mm could be used to obtain high WUE without significant yield penalty. Moreover, a good balance between yield, improved WUEET and percolation reduction was observed at water depths of 30–40 mm for daily intervals with water applied during the vegetative-reproductive stage of 7–5, 10–5 and 10–7. The identified strategies can contribute to the development of best management practices for water conservation.
Analysis of Regional Inequality from Sectoral Structure, Spatial Policy and Economic Development: A Case Study of Chongqing, China
Authors: Ye Xiaosu , Ma Lie , Ye Kunhui , Chen Jiantao , Xie Qiu
Published: April 2017

Inequality is a large challenge to sustainable development, and achieving equity has already become one of the top goals in sustainable development of the UN’s post-2015 development agenda. Located in the western inland region of China, Chongqing is characterized by “big city, big countryside, big mountain area, big reservoir area” and its regional inequality is more serious. This paper is to explore Chongqing’s regional inequality from sectoral structure, spatial policy and economic development by constructing, decomposing, and calculating the inter-county per capita GDP Gini Coefficient. Through this study, it is mainly found that: (1) Chongqing has experienced a dynamic evolution from unbalanced development to balanced development, and its regional inequality has been decreasing steadily in recent years; (2) the Tertiary Sector gradually contributes most to regional inequality; (3) inequality between regions is the main section of regional inequality; (4) the spatial policy as per regional division of Five Function Areas is more rational than the division of the main urban and suburb areas; and (5) economic development is the best way to reduce the regional inequality. Based on the results of empirical study and the reality of Chongqing, targeted and systematic policy suggestions are proposed to reduce regional inequality and promote sustainable development.