bluuebunny/crossref_metadata_2025 huggingface dataset:
SAR Backscatter and InSAR Coherence for Monitoring Wetland Extent, Flood Pulse and Vegetation: A Study of the Amazon Lowland
Authors: Canisius Francis , Brisco Brian , Murnaghan Kevin , Van Der Kooij Marco , Keizer Edwin
Published: March 2019

Synthetic aperture radar (SAR) data have been identified as a potential source of information for monitoring surface water, including open water and flooded vegetation, in frequent time intervals, which is very significant for flood mapping applications. The SAR specular reflectance separates open water and land surface, and its canopy penetration capability allows enhanced backscatter from flooded vegetation. Further, under certain conditions, the SAR signal from flooded vegetation may remain coherent between two acquisitions, which can be exploited using the InSAR technique. With these SAR capabilities in mind, this study examines the use of multi-temporal RADARSAT-2 C band SAR intensity and coherence components to monitor wetland extent, inundation and vegetation of a tropical wetland, such as Amazon lowland. For this study, 22 multi-temporal RADARSAT-2 images (21 pairs) were used for InSAR processing and the pairs in the low water stage (November, December) showed high coherence over the wetland areas. The three-year intensity stack was used for assessing wetland boundary, inundation extent, flood pulse, hydroperiod, and wetland vegetation. In addition to the intensity, derived coherence was used for classifying wetland vegetation. Wetland vegetation types were successfully classified with 86% accuracy using the statistical parameters derived from the multi-temporal intensity and coherence data stacks. We have found that in addition to SAR intensity, coherence provided information about wetland vegetation. In the next year, the Canadian RADARSAT Constellation Mission (RCM), will provide more data with frequent revisits, enhancing the application of SAR intensity and coherence for monitoring these types of wetlands at large scales.
UAV RTK/PPK Method—An Optimal Solution for Mapping Inaccessible Forested Areas?
Authors: Tomaštík Julián , Mokroš Martin , Surový Peter , Grznárová Alžbeta , Merganič Ján
Published: March 2019

Mapping hard-to-access and hazardous parts of forests by terrestrial surveying methods is a challenging task. Remote sensing techniques can provide an alternative solution to such cases. Unmanned aerial vehicles (UAVs) can provide on-demand data and higher flexibility in comparison to other remote sensing techniques. However, traditional georeferencing of imagery acquired by UAVs involves the use of ground control points (GCPs), thus negating the benefits of rapid and efficient mapping in remote areas. The aim of this study was to evaluate the accuracy of RTK/PPK (real-time kinematic, post-processed kinematic) solution used with a UAV to acquire camera positions through post-processed and corrected measurements by global navigation satellite systems (GNSS). To compare this solution with approaches involving GCPs, the accuracies of two GCP setup designs (4 GCPs and 9 GCPs) were evaluated. Additional factors, which can significantly influence accuracies were also introduced and evaluated: type of photogrammetric product (point cloud, orthoimages and DEM) vegetation leaf-off and leaf-on seasonal variation and flight patterns (evaluated individually and as a combination). The most accurate results for both horizontal (X and Y dimensions) and vertical (Z dimension) accuracies were acquired by the UAV RTK/PPK technology with RMSEs of 0.026 m, 0.035 m and 0.082 m, respectively. The PPK horizontal accuracy was significantly higher when compared to the 4GCP and 9GCP georeferencing approach (p < 0.05). The PPK vertical accuracy was significantly higher than 4 GCP approach accuracy, while PPK and 9 GCP approach vertical accuracies did not differ significantly (p = 0.96). Furthermore, the UAV RTK/PPK accuracy was not influenced by vegetation seasonal variation, whereas the GCP georeferencing approaches during the vegetation leaf-off season had lower accuracy. The use of the combined flight pattern resulted in higher horizontal accuracy; the influence on vertical accuracy was insignificant. Overall, the RTK/PPK technology in combination with UAVs is a feasible and appropriately accurate solution for various mapping tasks in forests.
Co-Segmentation and Superpixel-Based Graph Cuts for Building Change Detection from Bi-Temporal Digital Surface Models and Aerial Images
Authors: Pang Shiyan , Hu Xiangyun , Zhang Mi , Cai Zhongliang , Liu Fengzhu
Published: March 2019

Thanks to the recent development of laser scanner hardware and the technology of dense image matching (DIM), the acquisition of three-dimensional (3D) point cloud data has become increasingly convenient. However, how to effectively combine 3D point cloud data and images to realize accurate building change detection is still a hotspot in the field of photogrammetry and remote sensing. Therefore, with the bi-temporal aerial images and point cloud data obtained by airborne laser scanner (ALS) or DIM as the data source, a novel building change detection method combining co-segmentation and superpixel-based graph cuts is proposed in this paper. In this method, the bi-temporal point cloud data are firstly combined to achieve a co-segmentation to obtain bi-temporal superpixels with the simple linear iterative clustering (SLIC) algorithm. Secondly, for each period of aerial images, semantic segmentation based on a deep convolutional neural network is used to extract building areas, and this is the basis for subsequent superpixel feature extraction. Again, with the bi-temporal superpixel as the processing unit, a graph-cuts-based building change detection algorithm is proposed to extract the changed buildings. In this step, the building change detection problem is modeled as two binary classifications, and acquisition of each period’s changed buildings is a binary classification, in which the changed building is regarded as foreground and the other area as background. Then, the graph cuts algorithm is used to obtain the optimal solution. Next, by combining the bi-temporal changed buildings and digital surface models (DSMs), these changed buildings are further classified as “newly built,” “taller,” “demolished”, and “lower”. Finally, two typical datasets composed of bi-temporal aerial images and point cloud data obtained by ALS or DIM are used to validate the proposed method, and the experiments demonstrate the effectiveness and generality of the proposed algorithm.
Microwave Vegetation Index from Multi-Angular Observations and Its Application in Vegetation Properties Retrieval: Theoretical Modelling
Authors: Talebiesfandarani Somayeh , Zhao Tianjie , Shi Jiancheng , Ferrazzoli Paolo , Wigneron Jean-Pierre , Zamani Mehdi , Pani Peejush
Published: March 2019

Monitoring global vegetation dynamics is of great importance for many environmental applications. The vegetation optical depth (VOD), derived from passive microwave observation, is sensitive to the water content in all aboveground vegetation and could serve as complementary information to optical observations for global vegetation monitoring. The microwave vegetation index (MVI), which is originally derived from the zero-order model, is a potential approach to derive VOD and vegetation water content (VWC), however, it has limited application at dense vegetation in the global scale. In this study, we preferred to use a more complex vegetation model, the Tor Vergata model, which takes into account multi-scattering effects inside the vegetation and between the vegetation and soil layer. Validation with ground-based measurements proved this model is an efficient tool to describe the microwave emissions of corn and wheat. The MVI has been derived through two methods: (i) polarization independent ( MVI B P ) and (ii) time invariant ( MVI B T ), based on model simulations at the L band. Results show that the MVI B T has a stronger sensitivity to vegetation properties compared with MVI B P . MVI B T is used to retrieve VOD and VWC, and the results were compared to physical VOD and measured VWC. Comparisons indicated that MVI B T has a great potential to retrieve VOD and VWC. By using L band time-series information, the performance of MVIs could be enhanced and its application in a global scale could be improved while paying attention to vegetation structure and saturation effects.
Optimization Performance Comparison of Three Different Group Intelligence Algorithms on a SVM for Hyperspectral Imagery Classification
Authors: Zhu Xiufang , Li Nan , Pan Yaozhong
Published: March 2019

Group intelligence algorithms have been widely used in support vector machine (SVM) parameter optimization due to their obvious characteristics of strong parallel processing ability, fast optimization, and global optimization. However, few studies have made optimization performance comparisons of different group intelligence algorithms on SVMs, especially in terms of their application to hyperspectral remote sensing classification. In this paper, we compare the optimization performance of three different group intelligence algorithms that were run on a SVM in terms of five aspects by using three hyperspectral images (one each of the Indian Pines, University of Pavia, and Salinas): the stability to parameter settings, convergence rate, feature selection ability, sample size, and classification accuracy. Particle swarm optimization (PSO), genetic algorithms (GAs), and artificial bee colony (ABC) algorithms are the three group intelligence algorithms. Our results showed the influence of these three optimization algorithms on the C-parameter optimization of the SVM was less than their influence on the σ-parameter. The convergence rate, the number of selected features, and the accuracy of the three group intelligence algorithms were statistically significant different at the p = 0.01 level. The GA algorithm could compress more than 70% of the original data and it was the least affected by sample size. GA-SVM had the highest average overall accuracy (91.77%), followed by ABC-SVM (88.73%), and PSO-SVM (86.65%). Especially, in complex scenes (e.g., the Indian Pines image), GA-SVM showed the highest classification accuracy (87.34%, which was 8.23% higher than ABC-SVM and 16.42% higher than PSO-SVM) and the best stability (the standard deviation of its classification accuracy was 0.82%, which was 5.54% lower than ABC-SVM, and 21.63% lower than PSO-SVM). Therefore, when compared with the ABC and PSO algorithms, the GA had more advantages in terms of feature band selection, small sample size classification, and classification accuracy.
Combining Weighted Contour Templates with HOGs for Human Detection Using Biased Boosting
Authors: Huang Shih-Shinh , Ku Shih-Han , Hsiao Pei-Yung
Published: March 2019

This paper proposes a method to detect humans in the image that is an important issue for many applications, such as video surveillance in smart home and driving assistance systems. A kind of local feature called the histogram of oriented gradients (HOGs) has been widely used in describing the human appearance and its effectiveness has been proven in the literature. A learning framework called boosting is adopted to select a set of classifiers based on HOGs for human detection. However, in the case of a complex background or noise effect, the use of HOGs results in the problem of false detection. To alleviate this, the proposed method imposes a classifier based on weighted contour templates to the boosting framework. The way to combine the global contour templates with local HOGs is by adjusting the bias of a support vector machine (SVM) for the local classifier. The method proposed for feature combination is referred to as biased boosting. For covering the human appearance in various poses, an expectation maximization algorithm is used which is a kind of iterative algorithm is used to construct a set of representative weighted contour templates instead of manual annotation. The encoding of different weights to the contour points gives the templates more discriminative power in matching. The experiments provided exhibit the superiority of the proposed method in detection accuracy.
Two-Dimensional Frontier-Based Viewpoint Generation for Exploring and Mapping Underwater Environments
Authors: Vidal Eduard , Palomeras Narcís , Istenič Klemen , Hernández Juan David , Carreras Marc
Published: March 2019

To autonomously explore complex underwater environments, it is convenient to develop motion planning strategies that do not depend on prior information. In this publication, we present a robotic exploration algorithm for autonomous underwater vehicles (AUVs) that is able to guide the robot so that it explores an unknown 2-dimensional (2D) environment. The algorithm is built upon view planning (VP) and frontier-based (FB) strategies. Traditional robotic exploration algorithms seek full coverage of the scene with data from only one sensor. If data coverage is required for multiple sensors, multiple exploration missions are required. Our approach has been designed to sense the environment achieving full coverage with data from two sensors in a single exploration mission: occupancy data from the profiling sonar, from which the shape of the environment is perceived, and optical data from the camera, to capture the details of the environment. This saves time and mission costs. The algorithm has been designed to be computationally efficient, so that it can run online in the AUV’s onboard computer. In our approach, the environment is represented using a labeled quadtree occupancy map which, at the same time, is used to generate the viewpoints that guide the exploration. We have tested the algorithm in different environments through numerous experiments, which include sea operations using the Sparus II AUV and its sensor suite.
Laser-Assisted Printed Flexible Sensors: A Review
Authors: Han Tao , Nag Anindya , Afsarimanesh Nasrin , Mukhopadhyay Subhas Chandra , Kundu Sudip , Xu Yongzhao
Published: March 2019

This paper provides a substantial review of some of the significant research done on the fabrication and implementation of laser-assisted printed flexible sensors. In recent times, using laser cutting to develop printed flexible sensors has become a popular technique due to advantages such as the low cost of production, easy sample preparation, the ability to process a range of raw materials, and its usability for different functionalities. Different kinds of laser cutters are now available that work on samples very precisely via the available laser parameters. Thus, laser-cutting techniques provide huge scope for the development of prototypes with a varied range of sizes and dimensions. Meanwhile, researchers have been constantly working on the types of materials that can be processed, individually or in conjugation with one another, to form samples for laser-ablation. Some of the laser-printed techniques that are commonly considered for fabricating flexible sensors, which are discussed in this paper, include nanocomposite-based, laser-ablated, and 3D-printing. The developed sensors have been used for a range of applications, such as electrochemical and strain-sensing purposes. The challenges faced by the current printed flexible sensors, along with a market survey, are also outlined in this paper.
Evaluating the Potential of LJ1-01 Nighttime Light Data for Modeling Socio-Economic Parameters
Authors: Zhang Guo , Guo Xueyao , Li Deren , Jiang Boyang
Published: March 2019

The LJ1-01 satellite is the first dedicated nighttime light remote sensing satellite in the world and offers a higher spatial resolution than the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS) and the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor on the Suomi National Polar-orbiting Partnership (NPP) satellites of the United States. This study compared the LJ1-01 nighttime light data with NPP/VIIRS data in the context of modeling socio-economic parameters. In the eastern and central regions of China, 10 parameters from the four aspects of gross regional product (annual average population, electricity consumption, and area of land in use) were selected to build linear regression models. The results showed that the LJ1-01 nighttime light data offered better potential for modeling socio-economic parameters than the equivalent NPP/VIIRS data; the former can be an effective tool for establishing models for socio-economic parameters. There were significant positive correlations between the two types of nighttime light data and the 10 socio-economic parameters; that for the gross regional product was the highest.
How to Efficiently Determine the Range Precision of 3D Terrestrial Laser Scanners
Authors: Schmitz Berit , Holst Christoph , Medic Tomislav , Lichti Derek D. , Kuhlmann Heiner
Published: March 2019

As laser scanning technology has improved a lot in recent years, terrestrial laser scanners (TLS) have become popular devices for surveying tasks with high accuracy demands, such as deformation analyses. For this reason, finding a stochastic model for TLS measurements is very important in order to get statistically reliable results. The measurement accuracy of laser scanners—especially of their rangefinders—is strongly dependent on the scanning conditions, such as the scan configuration, the object surface geometry and the object reflectivity. This study demonstrates a way to determine the intensity-dependent range precision of 3D points for terrestrial laser scanners that measure in 3D mode by using range residuals in laser beam direction of a best plane fit. This method does not require special targets or surfaces aligned perpendicular to the scanner, which allows a much quicker and easier determination of the stochastic properties of the rangefinder. Furthermore, the different intensity types—raw and scaled—intensities are investigated since some manufacturers only provide scaled intensities. It is demonstrated that the intensity function can be derived from raw intensity values as written in literature, and likewise—in a restricted measurement volume—from scaled intensity values if the raw intensities are not available.
A Trust-Based Predictive Model for Mobile Ad Hoc Network in Internet of Things
Authors: Alnumay Waleed , Ghosh Uttam , Chatterjee Pushpita
Published: March 2019

The Internet of things (IoT) is a heterogeneous network of different types of wireless networks such as wireless sensor networks (WSNs), ZigBee, Wi-Fi, mobile ad hoc networks (MANETs), and RFID. To make IoT a reality for smart environment, more attractive to end users, and economically successful, it must be compatible with WSNs and MANETs. In light of this, the present paper discusses a novel quantitative trust model for an IoT-MANET. The proposed trust model combines both direct and indirect trust opinion in order to calculate the final trust value for a node. A Beta probabilistic distribution is used to combine different trust evidences and direct trust has been calculated. The theory of ARMA/GARCH has been used to combine the recommendation trust evidences and predict the resultant trust value of each node in multi-step ahead. Further, a routing protocol has been designed to ensure the secure and reliable end-to-end delivery of packets by only considering trustworthy nodes in the path. Simulation results show that our proposed trust model outperforms similar existing trust models.
Mass Surveilance of C. elegans—Smartphone-Based DIY Microscope and Machine-Learning-Based Approach for Worm Detection
Authors: Bornhorst Julia , Nustede Eike Jannik , Fudickar Sebastian
Published: March 2019

The nematode Caenorhabditis elegans (C. elegans) is often used as an alternative animal model due to several advantages such as morphological changes that can be seen directly under a microscope. Limitations of the model include the usage of expensive and cumbersome microscopes, and restrictions of the comprehensive use of C. elegans for toxicological trials. With the general applicability of the detection of C. elegans from microscope images via machine learning, as well as of smartphone-based microscopes, this article investigates the suitability of smartphone-based microscopy to detect C. elegans in a complete Petri dish. Thereby, the article introduces a smartphone-based microscope (including optics, lighting, and housing) for monitoring C. elegans and the corresponding classification via a trained Histogram of Oriented Gradients (HOG) feature-based Support Vector Machine for the automatic detection of C. elegans. Evaluation showed classification sensitivity of 0.90 and specificity of 0.85, and thereby confirms the general practicability of the chosen approach.
On-Farm Claw Scoring in Sows Using a Novel Mobile Device
Authors: van Riet Miriam M. J. , Vangeyte Jürgen , Janssens Geert P. J. , Ampe Bart , Nalon Elena , Bos Emilie-Julie , Pluym Liesbet , Tuyttens Frank A. M. , Maes Dominiek , Millet Sam
Published: March 2019

Claw lesions and lameness in sows are important problems in the industry as they impair sow welfare and result in economic losses. Available scoring techniques to detect claw lesions are all limited in terms of collecting data during all reproductive phases and recording all claws. The Mobile Claw Scoring Device (MCSD) was designed to address these limitations. After considering different practical situations and a design phase, two prototypes were constructed and tested. Improvements were incorporated into a final aluminium apparatus, consisting of two cameras with light-emitting diode (LED) lights mounted in a two-segment aluminium box and covered with laminated tempered glass plates. The operating system slides underneath the claws and takes video images. This final prototype was optimised and validated in an experiment with 20 hybrid sows, comparing scores for soiled claws using the MCSD against scores for clean claws using the Feet First© sow chute (as gold standard). Fifty percent of the scores differed between both scoring tools, with mainly medial claw digits deviating, but this seemed biologically irrelevant. The MCSD seems to be an appropriate alternative for on-farm claw scoring and is distinguishable from other claw scoring techniques; however, it needs further optimisation to improve the similarity between the two techniques.
Next Location Prediction Based on an Adaboost-Markov Model of Mobile Users
Authors: Wang Hongjun , Yang Zhen , Shi Yingchun
Published: March 2019

As an emerging class of spatial trajectory data, mobile user trajectory data can be used to analyze individual or group behavioral characteristics, hobbies and interests. Besides, the information extracted from original trajectory data is widely used in smart cities, transportation planning, and anti-terrorism maintenance. In order to identify the important locations of the target user from his trajectory data, a novel division method for preprocessing trajectory data is proposed, the feature points of original trajectory are extracted according to the change of trajectory structural, and then important locations are extracted by clustering the feature points, using an improved density peak clustering algorithm. Finally, in order to predict next location of mobile users, a multi-order fusion Markov model based on the Adaboost algorithm is proposed, the model order k is adaptively determined, and the weight coefficients of the 1~k-order models are given by the Adaboost algorithm according to the importance of various order models, a multi-order fusion Markov model is generated to predict next important location of the user. The experimental results on the real user trajectory dataset Geo-life show that the prediction performance of Adaboost-Markov model is better than the multi-order fusion Markov model with equal coefficient, and the universality and prediction performance of Adaboost-Markov model is better than the first to third order Markov models.
Context Definition and Query Language: Conceptual Specification, Implementation, and Evaluation
Authors: Hassani Alireza , Medvedev Alexey , Delir Haghighi Pari , Ling Sea , Zaslavsky Arkady , Prakash Jayaraman Prem
Published: March 2019

As IoT grows at a staggering pace, the need for contextual intelligence is a fundamental and critical factor for IoT intelligence, efficiency, effectiveness, performance, and sustainability. As the standardisation efforts for IoT are fast progressing, efforts in standardising context management platforms led by the European Telecommunications Standards Institute (ETSI) are gaining more attention from both academic and industrial research organizations. These standardisation endeavours will enable intelligent interactions between ‘things’, where things could be devices, software components, web-services, or sensing/actuating systems. Therefore, having a generic platform to describe and query context is crucial for the future of IoT applications. In this paper, we propose Context Definition and Query Language (CDQL), an advanced approach that enables things to exchange, reuse and share context between each other. CDQL consists of two main parts, namely: context definition model, which is designed to describe situations and high-level context; and Context Query Language (CQL), which is a powerful and flexible query language to express contextual information requirements without considering details of the underlying data structures. An important feature of the proposed query language is its ability to query entities in IoT environments based on their situation in a fully dynamic manner where users can define situations and context entities as part of the query. We exemplify the usage of CDQL on three different smart city use cases to highlight how CDQL can be utilised to deliver contextual information to IoT applications. Performance evaluation has demonstrated scalability and efficiency of CDQL in handling a fairly large number of concurrent context queries.
Monitoring Spatio-Temporal Changes of Terrestrial Ecosystem Soil Water Use Efficiency in Northeast China Using Time Series Remote Sensing Data
Authors: Qi Hang , Huang Fang , Zhai Huan
Published: March 2019

Soil water use efficiency (SWUE) was proposed as an effective proxy of ecosystem water use efficiency (WUE), which reflects the coupling of the carbon–water cycle and function of terrestrial ecosystems. The changes of ecosystem SWUE at the regional scale and their relationships with the environmental and biotic factors are yet to be adequately understood. Here, we aim to estimate SWUE over northeast China using time-series Moderate Resolution Imaging Spectroradiometer (MODIS) gross primary productivity data and European Space Agency climate change initiative (ESA CCI) soil moisture product during 2007–2015. The spatio-temporal variations in SWUE and their linkages to multiple factors, especially the phenological metrics, were investigated using trend and correlation analysis. The results showed that the spatial heterogeneity of ecosystem SWUE in northeast China was obvious. SWUE distribution varied among vegetation types, soil types, and elevation. Forests might produce higher photosynthetic productivity by utilizing unit soil moisture. The seasonal variations of SWUE were consistent with the vegetation growth cycle. Changes in normalized difference vegetation index (NDVI), land surface temperature, and precipitation exerted positive effects on SWUE variations. The earlier start (SOS) and later end (EOS) of the growing season would contribute to the increase in SWUE. Our results help complement the knowledge of SWUE variations and their driving forces.
An Approach to Understand Rural Advisory Services in a Decentralised Setting
Authors: Lamontagne-Godwin Julien , Dorward Peter , Ali Irshad , Aslam Naeem , Cardey Sarah
Published: March 2019

As populations increase, so do the challenges in feeding the world. Rural Advisory Services (RAS) contribute positively to food security by ensuring rural populations have access to vital knowledge increasing yields and rural incomes. For historical reasons however, national RAS have often developed into complex networks of stakeholders which can confuse, and even in some cases provide conflicting advice. In order to improve internal and external knowledge of an advisory service, this article investigates the benefits and limitations of an approach that combines qualitative and quantitative stakeholder perception activities at a local and national level. Local and national workshops were held using focus group and open fora techniques in order to portray and visualise a crop health advisory system in Pakistan, a dynamic and complex case study. The approach manages to expose key differences between local and national perceptions of a crop health RAS: whilst both local and national workshop participants decidedly agree on the importance of local (provincial and district level) extension departments, local perceptions clearly identified the strength and value of private sector and community level interactions. At the national workshop, interpretations of ground level activities were vague, yet their mentions of microcredit initiatives, large scale Non-Government Organisation activities and semi-autonomous institutions demonstrate knowledge at a different scale. This approach demonstrates the value of an accessible methodology to measure and understand RAS. Whilst this approach is a key component in assessing the system’s dynamism prior to any future development initiative, it needs to refine its integration of gendered perceptions.
Effects of a Combined High-Intensity Interval Training and Resistance Training Program in Patients Awaiting Bariatric Surgery: A Pilot Study
Authors: Picó-Sirvent Inés , Aracil-Marco Adolfo , Pastor Diego , Moya-Ramón Manuel
Published: March 2019

Bariatric surgery (BS) is considered the most effective treatment for morbid obesity. Preoperative body weight is directly associated with a higher surgical morbimortality and physical activity could be effective in the preparation of patients. The aim of this study is to determine the effects of a six-month exercise training program (ETP), combining high-intensity interval training (HIIT) and resistance training in patients awaiting BS. Six candidates awaiting BS (38.78 ± 1.18 kg·m−2; 38.17 ± 12.06 years) were distributed into two groups: the ETP group (experimental group (EG), n = 3) and a control group (CG, n = 3). Anthropometrical and blood pressure (BP), cardiorespiratory fitness and maximal strength were registered before and after the ETP. The EG participated in 93.25% of the sessions, showing reductions in body mass index (BMI) compared to the CG (34.61 ± 1.56 vs. 39.75 ± 0.65, p = 0.006, ANOVA). The inferential analysis showed larger effects on BMI, excess body weight percentage and fat mass, in addition to small to moderate effects in BP and the anthropometric measurements. Peak oxygen uptake normalized to fat-free mass showed likely positive effects with a probability of >95–99%. A six-month ETP seems to be a positive tool to improve body composition, cardiometabolic health, and fitness level in patients awaiting BS, but a larger sample size is needed to confirm these findings.
Influence of Aerobic Power on Youth Players’ Tactical Behavior and Network Properties during Football Small-Sided Games
Authors: Praça Gibson Moreira , Sousa Raphael Brito e , Greco Pablo Juan
Published: March 2019

(1) Background: This study aimed to compare the incidence of tactical principles, the percentage of successful tactical principles, and the network properties between higher and lower aerobic power in young football players during small-sided games. (2) Methods: Eighteen Under-17 Brazilian players were recruited. Firstly, they performed the Yo-Yo Intermittent Recovery Test Level 2, which was used to split them into two groups with higher and lower aerobic power. In the sequence, they played three vs three small-sided games within each group. The System of Tactical Assessment in Soccer was used to analyze the tactical behavior demonstrated by measuring the incidence of tactical principles and the percentage of successful principles, while the macro variables, density and clustering coefficient from social network analysis for team sports was used to analyze players’ interactions. (3) Results: No differences were reported for the incidence of tactical principles (p > 0.05, small or small-to-moderate effect sizes), the percentage of successful offensive principles (p = 0.122, small-to-moderate effect size), or the network variables (p > 0.05; small effect sizes). The lower aerobic power group demonstrated a higher percentage of successful defensive tactical principles (p = 0.043; small-to-moderate effect size). (4) Conclusions: We concluded that aerobic power has a limited impact on player behavior, indicating that players’ actions within a small-sided game are mostly constrained by other parameters.
Estimation of the Amount of Disposed Antibiotics
Authors: Cioca Gabriela , Munteanu Florentina-Daniela
Published: March 2019

The impact of the antibiotics in the environment is not well understood yet. Moreover, the total amount of antibiotics that are ending up in the environment as solid waste is not known and cannot be rigorously determined as many variables are influencing the determination of their concentration. The present article is focused on the estimation of the amount of non-prescribed antibiotics that are used in different European countries. Particular attention is paid to the class of beta-lactams, as they are responsible for a considerate share of the antimicrobial resistance. The primary purpose was the estimation of the quantity of non-prescribed antibiotics that might reach the environment as solid waste. For the present study, we used the ECDC and EUROSTAT reported data.
Attitudes of Voluntary Simplifier University Students in Hungary
Authors: Balsa-Budai Nikolett , Kiss Marietta , Kovács Bence , Szakály Zoltán
Published: March 2019

The Lifestyle of Voluntary Simplicity (LOVOS) segment is composed of consumers who attempt to achieve sustainable consumption. The segment has been examined by only a few research studies so far, and none of them were conducted among Hungarian consumers. Therefore, the aim of our exploratory research is to examine the occurrence of the LOVOS consumer group among university students from Debrecen, Hungary. To achieve our aim, we first identified the five main value groups of the LOVOS lifestyle with an expert focus group interview. Based on the interview, a questionnaire survey was conducted among university students from Debrecen (N = 500). Based on the results, four value-based segments were identified, of which the Voluntary simplifiers’ cluster (39.6% of respondents) reflected the characteristics of the LOVOS lifestyle to the greatest extent. Based on the literature, it seemed necessary to segment this group further in terms of their commitment to individual values. As a result, three further clusters were created, of which, the Holistic simplifiers’ group (9.8% of respondents) showed the greatest commitment to the values of the LOVOS lifestyle. We concluded that the characteristics of voluntary simplifiers have already appeared among university students from Debrecen, but further research is needed to reveal the value orientation of the whole of Hungarian society.
Uncovering Variations, Determinants, and Disparities of Multisector-Level Final Energy Use of Industries Across Cities
Authors: Liao Xianrui , Yang Wei , Wang Yichen , Song Junnian
Published: March 2019

With continuous industrialization and urbanization, cities have become the dominator of energy consumption, to which industry is making leading contribution among all sectors. Given the insufficiency in comparative study on the drivers of energy use across cities at multisector level, this study selected seven representative cities in China to quantify and analyze the contributions of factors to changes in final energy use (FEU) in industrial aggregate and sectoral levels by using Logarithmic Mean Divisia Index method. Disparities in the drivers of industrial FEU across cities were explicitly revealed within two stages (2005–2010 and 2010–2015). Some key findings are presented as follows. Alongside the increase in industrial output of seven cities within two stages, the variation trends in industrial FEU are different. Industrial output effect (contribution rate 16.7% ~ 184.0%) and energy intensity effect (contribution rate −8.6% ~ −76.5%) contributed to the increase in aggregate FEU positively and negatively, respectively. Beijing had the largest contribution share of industrial structure effect (−24.4% and −12.8%), followed by Shenyang and Xi’an. Contributions of energy intensity effect and industrial output effect for Chemicals, Nonmetals, Metals, and Manufacture of equipment were much larger than those of other sectors. The results revealed that production technological innovations, phase-out of outdated capacities of energy intensive industries, and industrial restructuring are crucial for reduction in industrial FEU of cities. This study also provided reference to reasonable industrial layout among cities and exertion of technological advantages from a national perspective.
Assessment of Aesthetic Preferences in Relation to Vegetation-Created Enclosure in Chinese Urban Parks: A Case Study of Shenzhen Litchi Park
Authors: Liu Mei , Schroth Olaf
Published: March 2019

Building on the mystery/complexity/legibility/coherence model of Kaplan and Kaplan (1989) and up-to-date landscape visualization techniques, this paper presents a case study analyzing people’s aesthetic preferences for scenes with varying levels of enclosure created through vegetation. Participants were asked to view 48 computer-generated urban park scenes with different levels of enclosure and to rate them for three aesthetic preference factors: coherence, complexity, and legibility. The results are as follows: (1) If the visual and/or physical setting is enclosed, participants will give lower ratings for legibility than in open scenes. (2) Physically open scenes are rated as more coherent than physically enclosed scenes. (3) Participants rate complexity for physically enclosed scenes lower than for physically open scenes. It is concluded that enclosure as a predictor variable for landscape preference has a practical significance for future urban landscape research and designs.
Reinterpreting the Connotation of “Sustainability” and the Expansion of Social Policy in China
Authors: Liu Tao , Li Yuxin , Tian Tong
Published: March 2019

This article examines the interplay between welfare ideas and institutional development and then seeks to explore the ideational background for social policy expansion in China. It focuses on the welfare semantics and narratives that underpin the grand social policy transformation since the millennium. The primary research question concerns whether the approach of “sustainability” is related to social policy in China, and, if yes, how and to what extent. Through the analysis of academic literatures and government documents on social policy in China, we explore the new “sustainability approach” to Chinese social policy that is constructed by social experts and international agencies. While the old sustainability approach overwhelmingly links the “sustainable development” of social policy to the issue of financial affordability and the adequacy of benefit levels, the newly interpreted approach highlights the significant meaning of social policy for long-term and inclusive development over the upcoming decades. Against this backdrop, a holistic national plan for socio-economic modernization has incorporated social policy. Beyond economic and ecological objectives, social development with a focus on social policy has become a key pillar of sustainable development in China.
Residential Greenery: State of the Art and Health-Related Ecosystem Services and Disservices in the City of Berlin
Authors: Battisti Luca , Pille Lauranne , Wachtel Thomas , Larcher Federica , Säumel Ina
Published: March 2019

Inclusively accessible green areas are essential for livable cities. The residential greenery on a door’s step of urban dwellers has rarely been the subject of research. Here we provide insights into the state of the art of residential greenery in Berlin, Germany. We focus on socially disadvantaged neighborhoods exposed to high loads of environmental stressors and belonging to four relevant building types of Central European cities. 32 plots in eight sample areas were randomly chosen and surveyed during 2017 and 2018. We surveyed the presence of structural elements, the presence and abundance of woody species and the health-related ecosystem (dis-)services (i.e., species’ air filtration and allergenic potential). We analysed the similarity among tree species to assess plant use patterns. The air cleaning and allergenic potential of woody species were assigned based on literature. In order to discuss strategies to improve residential greenery, we performed an analysis of strengths, weaknesses, opportunities and threats of these green spaces. We revealed a high dissimilarity of woody species assemblages across sites and within different building types, indicating no common plant use fashion. Recorded species provide moderate to high air filtering capacity. One to two third of all trees have a high allergenic potential that has to be addressed in future plant use decisions. Bike racks, benches, lights and playgrounds are common elements, whereas bioswales, facade-bound greening, atrium, fountains or ponds are rare. Their implementation can enhance the health and wellbeing of local residents. Building-attached greenery can improve densely built up areas of the Wilhelminian period, whereas space-intensive measures can be implemented in the spacious greenery of row–buildings settlements of the 1920s–1970s and of large housing estates of the 1970s–1980s. We revealed a high motivation for (co-)design and care by residents and discussed strategies on transformation towards multi-functional, healthy and biodiversity-friendly residential greeneries.
WIPO Re:Search: Catalyzing Public-Private Partnerships to Accelerate Tropical Disease Drug Discovery and Development
Authors: Manner Cathyryne K. , Graef Katy M. , Dent Jennifer
Published: March 2019

Tropical diseases, including malaria and a group of infections termed neglected tropical diseases (NTDs), pose enormous threats to human health and wellbeing globally. In concert with efforts to broaden access to current treatments, it is also critical to expand research and development (R&D) of new drugs that address therapeutic gaps and concerns associated with existing medications, including emergence of resistance. Limited commercial incentives, particularly compared to products for diseases prevalent in high-income countries, have hindered many pharmaceutical companies from contributing their immense product development know-how and resources to tropical disease R&D. In this article we present WIPO Re:Search, an international initiative co-led by BIO Ventures for Global Health (BVGH) and the World Intellectual Property Organization (WIPO), as an innovative and impactful public-private partnership model that promotes cross-sector intellectual property sharing and R&D to accelerate tropical disease drug discovery and development. Importantly, WIPO Re:Search also drives progress toward the United Nations Sustainable Development Goals (SDGs). Through case studies, we illustrate how WIPO Re:Search empowers high-quality tropical disease drug discovery researchers from academic/non-profit organizations and small companies (including scientists in low- and middle-income countries) to leapfrog their R&D programs by accessing pharmaceutical industry resources that may not otherwise be available to them.
Flood Susceptibility Mapping Using GIS-Based Analytic Network Process: A Case Study of Perlis, Malaysia
Authors: Dano Umar , Balogun Abdul-Lateef , Matori Abdul-Nasir , Wan Yusouf Khmaruzzaman , Abubakar Ismaila , Said Mohamed Mohamed , Aina Yusuf , Pradhan Biswajeet
Published: March 2019

Understanding factors associated with flood incidence could facilitate flood disaster control and management. This paper assesses flood susceptibility of Perlis, Malaysia for reducing and managing their impacts on people and the environment. The study used an integrated approach that combines geographic information system (GIS), analytic network process (ANP), and remote sensing (RS) derived variables for flood susceptibility assessment and mapping. Based on experts’ opinion solicited via ANP survey questionnaire, the ANP mathematical model was used to calculate the relative weights of the various flood influencing factors. The ArcGIS spatial analyst tools were used in generating flood susceptible zones. The study found zones that are very highly susceptible to flood (VHSF) and those highly susceptible to flood (HSF) covering 38.4% (30,924.6 ha) and 19.0% (15,341.1 ha) of the study area, respectively. The results were subjected to one-at-a-time (OAT) sensitivity analysis to verify their stability, where 6 out of the 22 flood scenarios correlated with the simulated spatial assessment of flood susceptibility. The findings were further validated using real-life flood incidences in the study area obtained from satellite images, which confirmed that most of the flooded areas were distributed over the VHSF and HSF zones. This integrated approach enables network model structuring, and reflects the interdependences among real-life flood influencing factors. This accurate identification of flood prone areas could serve as an early warning mechanism. The approach can be replicated in cities facing flood incidences in identifying areas susceptible to flooding for more effective flood disaster control.
Priorities and Interactions of Sustainable Development Goals (SDGs) with Focus on Wetlands
Authors: Jaramillo Fernando , Desormeaux Amanda , Hedlund Johanna , Jawitz James , Clerici Nicola , Piemontese Luigi , Rodríguez-Rodriguez Jenny , Anaya Jesús , Blanco-Libreros Juan , Borja Sonia , Celi Jorge , Chalov Sergey , Chun Kwok , Cresso Matilda , Destouni Georgia , Dessu Shimelis , Di Baldassarre Giuliano , Downing Andrea , Espinosa Luisa , Ghajarnia Navid , Girard Pierre , Gutiérrez Álvaro , Hansen Amy , Hu Tengfei , Jarsjö Jerker , Kalantari Zahra , Labbaci Adnane , Licero-Villanueva Lucia , Livsey John , Machotka Ewa , McCurley Kathryn , Palomino-Ángel Sebastián , Pietron Jan , Price René , Ramchunder Sorain , Ricaurte-Villota Constanza , Ricaurte Luisa , Dahir Lula , Rodríguez Erasmo , Salgado Jorge , Sannel A. , Santos Ana , Seifollahi-Aghmiuni Samaneh , Sjöberg Ylva , Sun Lian , Thorslund Josefin , Vigouroux Guillaume , Wang-Erlandsson Lan , Xu Diandian , Zamora David , Ziegler Alan , Åhlén Imenne
Published: March 2019

Wetlands are often vital physical and social components of a country’s natural capital, as well as providers of ecosystem services to local and national communities. We performed a network analysis to prioritize Sustainable Development Goal (SDG) targets for sustainable development in iconic wetlands and wetlandscapes around the world. The analysis was based on the information and perceptions on 45 wetlandscapes worldwide by 49 wetland researchers of the Global Wetland Ecohydrological Network (GWEN). We identified three 2030 Agenda targets of high priority across the wetlandscapes needed to achieve sustainable development: Target 6.3—“Improve water quality”; 2.4—“Sustainable food production”; and 12.2—“Sustainable management of resources”. Moreover, we found specific feedback mechanisms and synergies between SDG targets in the context of wetlands. The most consistent reinforcing interactions were the influence of Target 12.2 on 8.4—“Efficient resource consumption”; and that of Target 6.3 on 12.2. The wetlandscapes could be differentiated in four bundles of distinctive priority SDG-targets: “Basic human needs”, “Sustainable tourism”, “Environmental impact in urban wetlands”, and “Improving and conserving environment”. In general, we find that the SDG groups, targets, and interactions stress that maintaining good water quality and a “wise use” of wetlandscapes are vital to attaining sustainable development within these sensitive ecosystems.