bluuebunny/crossref_metadata_2025 huggingface dataset:
Combining Optical, Fluorescence, Thermal Satellite, and Environmental Data to Predict County-Level Maize Yield in China Using Machine Learning Approaches
Authors: Zhang Liangliang , Zhang Zhao , Luo Yuchuan , Cao Juan , Tao Fulu
Published: December 2019

Maize is an extremely important grain crop, and the demand has increased sharply throughout the world. China contributes nearly one-fifth of the total production alone with its decreasing arable land. Timely and accurate prediction of maize yield in China is critical for ensuring global food security. Previous studies primarily used either visible or near-infrared (NIR) based vegetation indices (VIs), or climate data, or both to predict crop yield. However, other satellite data from different spectral bands have been underutilized, which contain unique information on crop growth and yield. In addition, although a joint application of multi-source data significantly improves crop yield prediction, the combinations of input variables that could achieve the best results have not been well investigated. Here we integrated optical, fluorescence, thermal satellite, and environmental data to predict county-level maize yield across four agro-ecological zones (AEZs) in China using a regression-based method (LASSO), two machine learning (ML) methods (RF and XGBoost), and deep learning (DL) network (LSTM). The results showed that combining multi-source data explained more than 75% of yield variation. Satellite data at the silking stage contributed more information than other variables, and solar-induced chlorophyll fluorescence (SIF) had an almost equivalent performance with the enhanced vegetation index (EVI) largely due to the low signal to noise ratio and coarse spatial resolution. The extremely high temperature and vapor pressure deficit during the reproductive period were the most important climate variables affecting maize production in China. Soil properties and management factors contained extra information on crop growth conditions that cannot be fully captured by satellite and climate data. We found that ML and DL approaches definitely outperformed regression-based methods, and ML had more computational efficiency and easier generalizations relative to DL. Our study is an important effort to combine multi-source remote sensed and environmental data for large-scale yield prediction. The proposed methodology provides a paradigm for other crop yield predictions and in other regions.
Simulation and Analysis of Photogrammetric UAV Image Blocks—Influence of Camera Calibration Error
Authors: Zhou Yilin , Rupnik Ewelina , Meynard Christophe , Thom Christian , Pierrot-Deseilligny Marc
Published: December 2019

Unmanned aerial vehicles (UAV) are increasingly used for topographic mapping. The camera calibration for UAV image blocks can be performed a priori or during the bundle block adjustment (self-calibration). For an area of interest with flat scene and corridor configuration, the focal length of camera is highly correlated with the height of the camera. Furthermore, systematic errors of camera calibration accumulate on the longer dimension and cause deformation. Therefore, special precautions must be taken when estimating camera calibration parameters. In order to better investigate the impact of camera calibration errors, a synthetic, error-free aerial image block is generated to simulate several issues of interest. Firstly, the erroneous focal length in the case of camera pre-calibration is studied. Nadir images are not able to prevent camera poses from drifting to compensate for the erroneous focal length, whereas the inclusion of oblique images brings significant improvement. Secondly, the case where the focal length varies gradually (e.g., when the camera subject to temperature changes) is investigated. The neglect of this phenomenon can substantially degrade the 3D measurement accuracy. Different flight configurations and flight orders are analyzed, the combination of oblique and nadir images shows better performance. At last, the rolling shutter effect is investigated. The influence of camera rotational motion on the final accuracy is negligible compared to that of the translational motion. The acquisition configurations investigated are not able to mitigate the degradation introduced by the rolling shutter effect. Other solutions such as correcting image measurements or including camera motion parameters in the bundle block adjustment should be exploited.
Retrieving Foliar Traits of Quercus garryana var. garryana across a Modified Landscape Using Leaf Spectroscopy and LiDAR
Authors: Hacker Paul W. , Coops Nicholas C. , Townsend Philip A. , Wang Zhihui
Published: December 2019

Understanding the ecological effects of human activities on an ecosystem is integral to the implementation of conservation management plans. The plasticity of plant functional traits presents an opportunity to examine the capacity for intraspecific functional trait variations to be indicators of anthropogenic landscape modifications. The presence of intraspecific trait variation would indicate that plants of a single species could to be used to evaluate and map functional diversity, a common metric used to measure biodiversity. This study uses leaf spectroscopy, light detection and ranging (LiDAR) and partial least squares regression (PLSR) to examine the intraspecific variation of functional traits in a population of 40 Quercus garryana experiencing varying levels of anthropogenic influence at the site level (<0.3 km2) in Duncan, B.C., Canada. These individuals vary in their spatial relationship to roads, agricultural land use change and an encroaching Coastal Douglas-fir forest. A total of 14 functional traits were estimated using pre-determined PLSR coefficients from a multi-species dataset. LiDAR data for each tree and were organized into functional categories based on their influence of plant lifeform, leaf growth or leaf structure. Principal components analysis was performed on each functional category to determine the relative influence of each trait. Results show that leaf growth and lifeform functional trait categories express significant variation in relation to three anthropogenic landscape modifications, while traits associated to leaf structure only varied between land use types (p = 0.05). Diameter at breast height (DBH), mass-based chlorophyll and leaf mass per area (LMA) showed the strongest variation across treatments. These findings support the hypothesis that trait variation exists in small populations of the same species and illustrate that spectroscopy can be used to indirectly sense land use via the leaf functional traits of a single tree species.
Atmospheric Correction of Satellite Ocean Color Remote Sensing in the Presence of High Aerosol Loads
Authors: Mao Zhihua , Tao Bangyi , Chen Peng , Chen Jianyu , Hao Zengzhou , Zhu Qiankun , Huang Haiqing
Published: December 2019

The coverage of valid pixels of remote-sensing reflectance (Rrs) from ocean color imagery is relatively low due to the presence of clouds. In fact, it is also related to the presence of high aerosol optical depth (AOD) and other factors. In order to increase the valid coverage of satellite-retrieved products, a layer removal scheme for atmospheric correction (LRSAC) has been developed to process the ocean color data. The LRSAC used a five-layer structure including atmospheric absorption layer, Rayleigh scattering layer, aerosol scattering layer, sea surface reflection layer, and water-leaving reflectance layer to deal with the relationship of the components of the atmospheric correction. A nonlinear approach was used to solve the multiple reflections of the interface between two adjoining layers and a step-by-step procedure was used to remove effects of each layer. The LRSAC was used to process data from the sea-viewing wide field-of-view sensor (SeaWiFS) and the results were compared with standard products. The average of valid pixels of the global daily Rrs images of the standard products from 1997 to 2010 is only 11.5%, while it reaches up to 30.5% for the LRSAC. This indicates that the LRSAC recovers approximately 1.65 times of invalid pixels as compared with the standard products. Eight-day standard composite images exhibit many large areas with invalid values due to the presence of high AOD, whereas these areas are filled with valid pixels wusing the LRSAC. The ratio image of the mean valid pixel of the LRSAC to that of the standard products indicates that the number of valid pixels of the LRSAC increases with an increase of AOD. The LRSAC can increase the number of valid pixels by more than two times in about 33.8% of ocean areas with high AOD values. The accuracy of Rrs from the LRSAC was validated using the following two in situ datasets: the Marine Optical BuoY (MOBY) and the NASA bio-Optical Marine Algorithm Dataset (NOMAD). Most matchup pairs are distributed around the 1:1 line indicating that the systematic bias of the LRSAC is relatively small. The global mean relative error (MRE) of Rrs is 7.9% and the root mean square error (RMSE) is 0.00099 sr−1 for the MOBY matchups. Similarly, the MRE and RMSE are 2.1% and 0.0025 sr−1 for the NOMAD matchups, respectively. The accuracy of LRSAC was also evaluated by different groups of matchups according to the increase of AOD values, indicating that the errors of Rrs were little affected by the presence of high AOD values. Therefore, the LRSAC can significantly improve the coverage of valid pixels of Rrs with a similar accuracy in the presence of high AOD.
Sensing the Same Fishing Fleet with AIS and VIIRS: A Seven-Year Assessment of Squid Jiggers in FAO Major Fishing Area 41
Authors: Ruiz Javier , Caballero Isabel , Navarro Gabriel
Published: December 2019

Global Fishing Watch and VIIRS-DNB (visible infrared imaging radiometer suite day/night band) signals are compared for the jigger fleet in FAO (Food and Agriculture Organization of the United Nations) Major Fishing Area 41 during the maximum feasible time span (2012–2018). Both signals have shown a high degree of consistency at all temporal and spatial scales analyzed, including seasonal cycles, lack of signal for some years and interannual tendencies. This indicates that both signals are a fair representation of the fishing effort exerted by the jigger fleet in this zone. The high degree of consistency does not support views questioning satellite AIS (automatic identification system) as a reliable tool to survey fishing activities. Instead, our results add evidence supporting the value of remote sensing, in particular, when independent sources of information (such as VIIRS-DNB and AIS) are combined, as a relevant tool to add transparency and support compliance of fishing activities in vast and distant regions of the ocean.
An Incongruence-Based Anomaly Detection Strategy for Analyzing Water Pollution in Images from Remote Sensing
Authors: Dias Maurício Araújo , Silva Erivaldo Antônio da , Azevedo Samara Calçado de , Casaca Wallace , Statella Thiago , Negri Rogério Galante
Published: December 2019

The potential applications of computational tools, such as anomaly detection and incongruence, for analyzing data attract much attention from the scientific research community. However, there remains a need for more studies to determine how anomaly detection and incongruence applied to analyze data of static images from remote sensing will assist in detecting water pollution. In this study, an incongruence-based anomaly detection strategy for analyzing water pollution in images from remote sensing is presented. Our strategy semi-automatically detects occurrences of one type of anomaly based on the divergence between two image classifications (contextual and non-contextual). The results indicate that our strategy accurately analyzes the majority of images. Incongruence as a strategy for detecting anomalies in real-application (non-synthetic) data found in images from remote sensing is relevant for recognizing crude oil close to open water bodies or water pollution caused by the presence of brown mud in large rivers. It can also assist surveillance systems by detecting environmental disasters or performing mappings.
Statistical Analysis of Changes in Sentinel-1 Time Series on the Google Earth Engine
Authors: Canty Morton J. , Nielsen Allan A. , Conradsen Knut , Skriver Henning
Published: December 2019

Time series analysis of Sentinel-1 SAR imagery made available by the Google Earth Engine (GEE) is described. Advantage is taken of a recent modification of a sequential complex Wishart-based algorithm which is applicable to the dual polarization intensity data archived on the GEE. Both the algorithm and a software interface to the GEE Python API for convenient data exploration and analysis are presented; the latter can be run from a platform independent Docker container and the source code is available on GitHub. Application examples are given involving the monitoring of anthropogenic activity (shipping, uranium mining, deforestation) and disaster assessment (flash floods). These highlight the advantages of the good temporal resolution resulting from cloud cover independence, short revisit times and near real time data availability.
Ground Validation of GPM IMERG Precipitation Products over Iran
Authors: Maghsood Fatemeh Fadia , Hashemi Hossein , Hosseini Seyyed Hasan , Berndtsson Ronny
Published: December 2019

Accurate estimation of precipitation is crucial for fundamental input to various hydrometeorological applications. Ground-based precipitation data suffer limitations associated with spatial resolution and coverage; hence, satellite precipitation products can be used to complement traditional rain gauge systems. However, the satellite precipitation data need to be validated before extensive use in the applications. Hence, we conducted a thorough validation of the Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals (IMERG) product for all of Iran. The study focused on investigating the performance of daily and monthly GPM IMERG (early, late, final, and monthly) products by comparing them with ground-based precipitation data at synoptic stations throughout the country (2014–2017). The spatial and temporal performance of the GPM IMERG was evaluated using eight statistical criteria considering the rainfall index at the country level. The rainfall detection ability index (POD) showed that the best IMERG product’s performance is for the spring season while the false alarm ratio (FAR) index indicated the inferior performance of the IMERG products for the summer season. The performance of the products generally increased from IMERG-Early to –Final according to the relative bias (rBIAS) results while, based on the quantile-quantile (Q-Q) plots, the IMERG-Final could not be suggested for the applications relying on extreme rainfall estimates compared to IMERG-Early and -Late. The results in this paper improve the understanding of IMERG product’s performance and open a door to future studies regarding hydrometeorological applications of these products in Iran.
A Large-Scene Deceptive Jamming Method for Space-Borne SAR Based on Time-Delay and Frequency-Shift with Template Segmentation
Authors: Yang Kaizhi , Ye Wei , Ma Fangfang , Li Guojing , Tong Qian
Published: December 2019

Due to advantages such as its low power consumption and higher concealment, deceptive jamming against synthetic aperture radar (SAR) has received extensive attention during the past decades. However, large-scene deception jamming is still a challenge because of the huge computing burden. In this paper, we propose a new large-scene deceptive jamming algorithm. First, the time-delay and frequency-shift (TDFS) algorithm is introduced to improve the jamming processing speed. The system function of jammer (JSF) for a fake scatter is simplified to the multiplication of the scattering coefficient, a time-delay term in the range dimension and a frequency-shift term in the azimuth dimension. Then, in order to solve the problem that the effective region of the TDFS algorithm is limited, the scene deceptive jamming template is divided into several blocks according to the SAR parameters and imaging quality control factor. The JSF of each block is calculated by the TDFS algorithm and added together to achieve the large-scene jamming. Finally, the correction algorithm in squint mode is derived. The simplification and parallel-block processing could improve the calculation efficiency significantly. The simulation results verified the validity of the algorithm.
Joint Optimization of Transmit Waveform and Receive Filter with Pulse-to-Pulse Waveform Variations for MIMO GMTI
Authors: Lv Zhoudan , He Feng , Sun Zaoyu , Dong Zhen
Published: December 2019

Multi-input multi-output (MIMO) is usually defined as a radar system in which the transmit time and receive time, space and transform domain can be separated into multiple independent signals. Given the bandwidth and power constraints of the radar system, MIMO radar can improve its performance by optimize design transmit waveforms and receive filters, so as to achieve better performance in suppressing clutter and noise. In this paper, we cyclicly optimize the transmit waveform and receive filters, so as to maximize the output signal interference and noise ratio (SINR). From fixed pulse-to-pulse waveform to pulse-to-pulse waveform variations, we discuss the joint optimization under energy constraint, then extend it to optimizations under constant-envelope constraint and similarity constraint. Compared to optimization with fixed pulse-to-pulse waveform, the generalized optimization achieves higher output SINR and lower minimum detectable velocity (MDV), further improve the suppressing performance.
Enhanced Performance of Reagent-Less Carbon Nanodots Based Enzyme Electrochemical Biosensors
Authors: Bravo Iria , Gutiérrez-Sánchez Cristina , García-Mendiola Tania , Revenga-Parra Mónica , Pariente Félix , Lorenzo Encarnación
Published: December 2019

This work reports on the advantages of using carbon nanodots (CNDs) in the development of reagent-less oxidoreductase-based biosensors. Biosensor responses are based on the detection of H2O2, generated in the enzymatic reaction, at 0.4 V. A simple and fast method, consisting of direct adsorption of the bioconjugate, formed by mixing lactate oxidase, glucose oxidase, or uricase with CNDs, is employed to develop the nanostructured biosensors. Peripherical amide groups enriched CNDs are prepared from ethyleneglycol bis-(2-aminoethyl ether)-N,N,N′,N′-tetraacetic acid and tris(hydroxymethyl)aminomethane, and used as precursors. The bioconjugate formed between lactate oxidase and CNDs was chosen as a case study to determine the analytical parameters of the resulting L-lactate biosensor. A linear concentration range of 3.0 to 500 µM, a sensitivity of 4.98 × 10−3 µA·µM−1, and a detection limit of 0.9 µM were obtained for the L-lactate biosensing platform. The reproducibility of the biosensor was found to be 8.6%. The biosensor was applied to the L-lactate quantification in a commercial human serum sample. The standard addition method was employed. L-lactate concentration in the serum extract of 0.9 ± 0.3 mM (n = 3) was calculated. The result agrees well with the one obtained in 0.9 ± 0.2 mM, using a commercial spectrophotometric enzymatic kit.
Measurement of Switching Performance of Pixelated Silicon Sensor Integrated with Field Effect Transistor
Authors: Lee Hyeyoung , Jeon Jin-A , Kim Jinyong , Lee Hyunsu , Lee Moo Hyun , Lee Manwoo , Lee Seungcheol , Park Hwanbae , Song Sukjune
Published: December 2019

Silicon shows very high detection efficiency for low-energy photons, and the silicon pixel sensor provides high spatial resolution. Pixelated silicon sensors facilitate the direct detection of low-energy X-ray radiation. In this study, we developed junction field effect transistors (JFETs) that can be integrated into a pixelated silicon sensor to effectively handle many signal readout channels due to the pixelated structure without any change in the sensor resolution; this capability of the integrated system arises from the pixelated structure of the sensor. We focused on optimizing the JFET’s switching function, and simulated JFETs with different fabrication parameters. Furthermore, prototype JFET switches were designed and fabricated on the basis of the simulated results. It is important not only to keep the low leakage currents in the JFET but also reduce the current flow as much as possible by providing a high resistance when the JFET switch is off. We determined the optimal fabrication conditions for the effective switching of the JFETs. In this paper, we present the results of the measurement of the switching capability of the fabricated JFETs for various design variables and fabrication conditions.
Nonorthogonal Aerial Optoelectronic Platform Based on Triaxial and Control Method Designed for Image Sensors
Authors: Li Quanchao , Xu Shuyan , Xu Yulei , Li Lei , Zhang Liu
Published: December 2019

A traditional aerial optoelectronic platform consists of inside and outside multilayer gimbals, while an internal gimbal and drive components occupy the internal space where optical sensors are located. In order to improve the replaceability of optical sensors and to increase their available space, this paper introduces a nonorthogonal aerial optoelectronic platform based on three axes; we carried out research on its drive control method. A three-dimensional structure of an aerial optoelectronic platform was designed. A noncontact drive of a linear voice coil motor was introduced, and a drive control scheme of a proportional integral and a disturbance observer was adopted. Finally, simulations and experiments were carried out. Results showed that the aerial optoelectronic platform could effectively release three times the image sensor space, and the servo bandwidth was 60.2 Hz, which was much better than that of traditional two-axis and four-gimbal platforms. The stability accuracy of the system reached 4.9958 micron rad, which was obviously better than that of traditional gimbals. This paper provides a reference for the design of new optoelectronic platforms.
Crystal Habits and Biological Properties of N-(4-Trifluoromethylphenyl)-4-Hydroxy-2,2-Dioxo-1H-2λ6,1-Benzothiazine-3-Carboxamide
Authors: Ukrainets Igor V. , Petrushova Lidiya A. , Fedosov Andrii I. , Voloshchuk Natali I. , Bondarenko Pavlo S. , Shishkina Svitlana V. , Sidorenko Lyudmila V. , Sim Galina
Published: December 2019

In order to study polymorphic modifications of N-(4-trifluoromethylphenyl)-4-hydroxy-2,2-dioxo-1H-2λ6,1-benzothiazine-3-carboxamide, which is of interest as a promising analgesic, its three colorless crystal forms with different habitus have been obtained: sticks of ethyl acetate, plates of meta-xylene and blocks of ortho-xylene. However, the X-ray diffraction analysis has shown that all the forms studied have the identical molecular and crystal structure in spite of such significant differences in appearance. Moreover, pharmacological tests have revealed significant differences in the analgesic activity in these samples (a total of five experimental models were used: “acetic-acid-induced writhing”, “hot plate”, “thermal irritation of the tail tip” (tail-flick), “tail electric stimulation” and “neuropathic pain”), acute toxicity and the ability to cause gastric damage. As a result, only the plate crystal form of N-(4-trifluoromethylphenyl)-4-hydroxy-2,2-dioxo-1H-2λ6,1-benzothiazine-3-carboxamide is recommended for further studies. Thus, it has been proven that the habitus of crystals is an important characteristic of the drug substance and is able to have a noticeable effect on its biological properties. Changes in habitus should be considered as a guide to the mandatory verification of at least the basic pharmacological parameters of the new form regardless of whether the molecular and crystal structure changes.
Multiple Virtual Screening Strategies for the Discovery of Novel Compounds Active Against Dengue Virus: A Hit Identification Study
Authors: Hengphasatporn Kowit , Garon Arthur , Wolschann Peter , Langer Thierry , Yasuteru Shigeta , Huynh Thao N.T. , Chavasiri Warinthorn , Saelee Thanaphon , Boonyasuppayakorn Siwaporn , Rungrotmongkol Thanyada
Published: December 2019

Dengue infection is caused by a mosquito-borne virus, particularly in children, which may even cause death. No effective prevention or therapeutic agents to cure this disease are available up to now. The dengue viral envelope (E) protein was discovered to be a promising target for inhibition in several steps of viral infection. Structure-based virtual screening has become an important technique to identify first hits in a drug screening process, as it is possible to reduce the number of compounds to be assayed, allowing to save resources. In the present study, pharmacophore models were generated using the common hits approach (CHA), starting from trajectories obtained from molecular dynamics (MD) simulations of the E protein complexed with the active inhibitor, flavanone (FN5Y). Subsequently, compounds presented in various drug databases were screened using the LigandScout 4.2 program. The obtained hits were analyzed in more detail by molecular docking, followed by extensive MD simulations of the complexes. The highest-ranked compound from this procedure was then synthesized and tested on its inhibitory efficiency by experimental assays.
Dynamic Models for Exploring the Resilience in Territorial Scenarios
Authors: Assumma Vanessa , Bottero Marta , Datola Giulia , De Angelis Elena , Monaco Roberto
Published: December 2019

The present paper focuses on the role covered by dynamic models as support for the decision-making process in the evaluation of policies and actions for increasing the resilience of cities and territories. In recent decades, urban resilience has been recognized as a dynamic and multidimensional phenomenon that characterizes urban and metropolitan area dynamics. Therefore, it may be considered a fundamental aspect of urban and territorial planning. The employment of quantitative methods, such as dynamic models, is useful for the prediction of the dynamic behavior of territories and of their resilience. The present work discusses the system dynamics model and the Lotka–Volterra cooperative systems and shows how these models can aid technicians in resilience assessment and also decision makers in the definition of policies and actions, especially if integrated in wide evaluation frameworks for urban resilience achievements. This paper aims to provide an epistemological perspective of the application of dynamic models in resilience assessment, underlying the possible contribution to this issue through the analysis of a real case study and methodological framework. The main objective of this work is to lay the basis for future compared applications of these two models to the same case study.
The Influence of the Permeability of the Fractures Zone Around the Heading on the Concentration and Distribution of Methane
Authors: Tutak Magdalena
Published: December 2019

One of the main problems related to the excavation of dog headings in coal beds is the emission of methane during this process. To prevent the occurrence of dangerous concentration levels of this gas, it is necessary to use an appropriate ventilation system. The operation effectiveness of such a system depends on a number of mining, geological, technical and organizational factors. One of them includes the size and permeability of the fractures zone formed around the excavated dog heading. The primary objective of the paper is to determine the influence of this zone on the ventilation parameters, including the concentration and distribution of methane in the excavated dog heading. In order to achieve the assumed objective, multivariate model-based tests were carried out, which reproduce a real-world dog heading. Literature data and test results in actual conditions were used to determine the size and permeability of the fractures zone around the excavated heading. These data served as the basis to develop a model of the region under analysis and adopt boundary conditions. The analyses were carried out for four permeability values of the fractures zone and for two volumetric flow rates of the air stream supplied to the heading. The results were used to determine the influence of the fractures zone on the distribution and concentration of methane in the heading under analysis. The model-based tests were performed using ANSYS Fluent software. The idea to take into account the fractures zone around the heading represents a new approach to the analysis of ventilation parameters in underground mine headings. The results clearly indicate that this zone affects the ventilation parameters in the heading, including the distribution and concentration of methane. The knowledge obtained from the tests should be used to optimize the ventilation process of dog headings. All authors have read and agreed to the published version of the manuscript.
Joint Configuration and Scheduling Optimization of a Dual-Trolley Quay Crane and Automatic Guided Vehicles with Consideration of Vessel Stability
Authors: Yue Lijun , Fan Houming , Zhai Chunxin
Published: December 2019

This study proposes a formulation to optimize operational efficiency of a dual-trolley quay crane and automatic guided vehicles (AGVs) to reduce energy consumption at an automated container terminal. A two-phase model is used to minimize energy consumption during loading and discharging operations, as well as maximize the utilization rate of the AGVs, with consideration of relevant constraints such as the capacity of buffers for the quay crane (QC) and yard, the stability of vessel, the maximum endurance of an AGV, and the available laytime for handling. We propose a constrained partial enumeration strategy to construct quay crane schedules and a genetic algorithm to solve the AGV scheduling problem. Finally, Yangshan Phase IV automated container terminal’s data is used to verify the validity and applicability of the proposed model. The results of the tests provide evidence that the proposed method can improve energy efficiency.
Are Personal Electric Vehicles Sustainable? A Hybrid E-Bike Case Study
Authors: Machedon-Pisu Mihai , Borza Paul Nicolae
Published: December 2019

As the title suggests, the sustainability of personal electric vehicles is in question. In terms of life span, range, comfort, and safety, electric vehicles, such as e-cars and e-buses, are much better than personal electric vehicles, such as e-bikes. However, electric vehicles present greater costs and increased energy consumption. Also, the impact on environment, health, and fitness is more negative than that of personal electric vehicles. Since transportation vehicles can benefit from hybrid electric storage solutions, we address the following question: Is it possible to reach a compromise between sustainability and technology constraints by implementing a low-cost hybrid personal electric vehicle with improved life span and range that is also green? Our methodology consists of life cycle assessment and performance analyses tackling the facets of the sustainability challenges (economy, society, and environment) and limitations of the electric storage solutions (dependent on technology and application) presented herein. The hybrid electric storage system of the proposed hybrid e-bike is made of batteries, supercapacitors, and corresponding power electronics, allowing the optimal control of power flows between the system’s components and application’s actuators. Our hybrid e-bike costs less than a normal e-bike (half or less), does not depend on battery operation for short periods of time (a few seconds), has better autonomy than most personal electric vehicles (more than 60 km), has a greater life span (a few years more than a normal e-bike), has better energy efficiency (more than 90%), and is much cleaner due to the reduced number of batteries replaced per life time (one instead of two or three).
Capturing the Invisible Wealth in Nonprofits to Overcome Myopic Perceptions
Authors: Fuertes-Fuertes Iluminada , Cabedo J. David , Jimeno-García Inmaculada
Published: December 2019

Since nonprofits use third-party funds for their activities, they are often perceived as resource managers or spending units, instead of being considered as social wealth generating entities. The aim of this study is to help to overcome this myopic perception by showing how the invisible wealth generated by these organizations can be made visible. We use the SROI methodology to do so, by identifying stakeholders, outcomes (tangible, intangible) and social impacts in a drug addiction treatment centre. The results show that social impact in monetary terms exceeds that of the inputs used, confirming the idea that addiction-based nonprofits are social wealth generating units. The conclusion drawn is that social impact measurement should be widely used as a management tool and a mechanism for reinforcing the social image of nonprofits.
A Spatial Distribution Equilibrium Evaluation of Health Service Resources at Community Grid Scale in Yichang, China
Authors: Chen Jingyuan , Bai Yuqi , Zhang Pei , Qiu Jingyuan , Hu Yichun , Wang Tianhao , Xu Chengzhong , Gong Peng
Published: December 2019

Whether the supplies of health services and related facilities meet the demand is a critical issue when developing healthy cities. The importance of health services and related facilities in public health promotion has been adequately proved. However, since the community population and resource data are usually available at the scale of an administrative region; it is very difficult to perform further fine-scaled spatial distribution equilibrium evaluation studies. Such kinds of activities are highly expected for precise urban planning and management. Yichang is located in Hubei province, the central part of China, along the Yangzi River. It is leading both of China’s smart cities demonstration project and China’s healthy cities pilot project. Yichang has defined 1271 community grids for urban management and service, where each grid consists of 200 households generally with its population distribution data routinely updated. The research set the 15-min walking distances of the residents as impedance factors, and the numbers and the types of health service resources as attractiveness factors for accessibility evaluation. The resource ratio, richness and per capita number of various health service resources that can be reached within 15 min from the community grid building is used as spatial distribution equilibrium evaluation indicators. The entropy weight method is used to assign the indicator weight value. The obtained fine-scale evaluation results were analyzed. In this way, a community grid-scale spatial distribution equilibrium evaluation of health service resources in Yichang was performed. The proposed research could be of value for rapid and precise evaluation of spatial distribution equilibrium evaluation of a variety of healthy city resources, to support healthy city planning and management.
Physicochemical Analysis and Essential Oils Extraction of the Gorse (Ulex europaeus) and French Broom (Genista monspessulana), Two Highly Invasive Species in the Colombian Andes
Authors: Osorio-Castiblanco Diego F. , Peyre Gwendolyn , Saldarriaga Juan F.
Published: December 2019

Gorse (Ulex europaeus) and French broom (Genista monspessulana) are two highly invasive species that have become a threat to tropical countries, especially in Andean ecosystems. This research focused on providing a physicochemical characterization and essential oils extraction of both species to better understand their potential valorization and guide further environmental management efforts. For this purpose, the following analyses were conducted for both species: higher heat value (HHV), elemental analysis, proximate analysis, thermogravimetric analysis to obtain constituent natural polymers (hemicellulose, cellulose, and lignin), and extraction of essential oils and other interest chemical compounds through supercritical fluids. Ecological closeness was found between the two species mostly regarding HHV, fixed carbon, and volatile matter, which calls for similar potential uses. Both species were also found to be suitable for combustion processes, gasification, extraction of chemical compounds, and use of lignocellulosic content; however, only U. europaeus appeared suitable for activated carbon obtention. Therefore, this work provided relevant data that can be used as preliminary basis to establish strong scientifically-based management and control strategies for these two invasive species. We recommend focusing primarily on thermal processes such as pyrolysis, gasification, or combustion, and also essential oils extractions of acetic acid, dodecanoic acid, anagyrine, amylene hydrate, caulophylline, and maltol in the future.
China Eco-Wisdom: A Review of Sustainability of Agricultural Heritage Systems on Aquatic-Ecological Conservation
Authors: Li Maolin , Zhang Yongxun , Xu Ming , He Lulu , Liu Longteng , Tang Qisheng
Published: December 2019

The multiple problems of modern agriculture urge people to probe into sustainability of the traditional agriculture. As important representatives of Chinese traditional agriculture, the agricultural heritage systems on aquatic-ecological conservation (AHSAEC) are confronting threats and urgently needs to be protected. In this study, the functions and value of the AHSAECs are analyzed by multi-disciplinary methods including system analysis methods based on the review of old books and modern scientific research literature, and the nature of their sustainability are discussed, and the countermeasures against their current unsustainability are proposed. The results show that AHSAECs derive from the simple eco-agriculture models such as the Taihu Lake multi-industry compound ecoagriculture model in historical periods. These systems can integrate farming, forestry, animal husbandry, and aquaculture and make them a sustainable recycling system. Thus, they have strong ecological stability, rich cultural connotation, and good comprehensive benefits. Traditional eco-wisdom from Chinese traditional culture is the power to promote the sustainability and high-quality development of these systems. The key eco-wisdom of AHSAECs is to integrate aquaculture with livestock and poultry breeding and planting through the harmless treatment and recycling of agricultural wastes, which is conducive to the aquatic ecosystem conservation and sustainable resources utilization. Nowadays, it is urgent to preserve the eco-wisdom by establishing ecological museums to realize the productive protection and inheriting development of the heritage systems.
Corporate Social Responsibilities of Food Processing Companies in Vietnam from Consumer Perspective
Authors: Nguyen Phuong-Mai , D. Vo Nam , Phuc Nguyen Nguyen , Choo Yongshik
Published: December 2019

Corporate social responsibility (CSR) has been receiving increasing attention in the international community since the Sustainable Development Goals (SDGs) emphasise effective corporate partnership. CSR is one of the most critical instruments linking corporate activities to the SDGs. Among various stakeholders, consumers can play an essential role in motivating companies to become socially responsible. However, there is little evidence from developing countries about the linkage between CSR and consumers. This paper, therefore, examines the relationship between consumers’ perception of a company’s CSR practices and their attitudes towards and intentions on purchasing its goods with empirical evidence from the Vietnamese food industry. The primary data was collected from 622 consumers using processed food in a self-administered survey in Northern Vietnam. Based on the structural equation modelling (SEM) analysis, this study shows that perception of CSR toward community has the most substantial influence on consumers’ attitude, followed by the perception of CSR toward employees and perception of fair operating practices responsibility. Although Vietnamese consumers have knowledge of the CSR in the food processing industry, their response to either good or bad CSR practices is still insufficient. Hence, the Vietnamese government and civil society should actively intervene to strengthen CSR regulations and enhance consumers’ CSR awareness.
Waste Management in Green and Smart Cities: A Case Study of Russia
Authors: Mingaleva Zhanna , Vukovic Natalia , Volkova Irina , Salimova Tatiana
Published: December 2019

This article aims to investigate the role of waste management in the development of modern green and smart cities and to determine the existence of several key points in programs transforming cities into green cities with smart technologies. The relevance of the research is determined by the need to develop a theoretical and methodological basis for the green and smart city concepts. The research process involved the following methods: Scientific analysis, comparison, and synthesis. The research results of the case study of Russia determined that for urban territories with great distances between urban districts, waste sorting stations should be located as parts of so-called waste recycling complexes at intermunicipal landfills. This will allow a more fully implementation of the concept of recycling economy not only in Russian cities, but also in other cities with sparse populations across the world. Further, the authors conclude that the effectiveness of green technologies in modern cities, especially in waste management, depends on the level of participation of citizens. People are active participants in the life processes of cities and have a direct impact on the urban environment. Consequently, the introduction of green technologies can only be achieved in harmony with the well-established behavioral attitudes of city residents together with the implementation of green and smart urban technologies.
Predictive Factors of Task Interdependence in the University Context
Authors: Mendo Lázaro Santiago , León Del Barco Benito , Polo-Del-Río María-I , Rasskin-Gutman Irina
Published: December 2019

The aim of this research is to find out what type of task interdependence is generated in work teams in university contexts and to analyze the capacity to discriminate the type of task interdependence of some of the variables that are decisive for the team’s success. The sample consisted of 808 teaching students from six Spanish universities. Self-report measures were taken, such as task interdependence, attitudes towards teamwork, team potency, and social team skills. The results show that the students who carry out the tasks in teams with high interdependence are minority. However, those who work with high interdependence, present more positive attitudes towards teamwork, greater team potency, and more social skills in receiving information and self-assertion. Likewise, high interdependence would be characterized by high scores in both the attitudes and team potency. However, attitude is the variable that better discriminates the type of task interdependence, allowing for an excellent level of discrimination of high interdependence.
How a Transformation towards Sustainable Community Catering Can Succeed
Authors: Lopez Viviana , Teufel Jenny , Gensch Carl-Otto
Published: December 2019

Community catering or to use another common term especially in the American literature institutional foodservice plays a central role in changing our food system towards sustainability. Community catering establishments can bring about changes in this context at various levels. Hence, in the context of menu planning, they have a direct influence on the level of meat consumption. Indirectly, however, they can also support changes in eating habits by offering the guest an equally attractive alternative, thus giving him or her a sense of how tasty a low-meat cuisine can be. On the basis of this experience, the consumer may possibly change in turn his or her own purchasing behavior and menu planning at home. With the increasing importance of catering for day-care centers and schools, community catering also has a considerable influence on the nutritional status as well as on the development of people’s individual diet and the later eating habits of young people. By understanding socio-technical systems as embedded in ecological systems this paper takes a systemic view on innovations in transformation domains as the objects of desire for governance towards sustainability. The framework developed in the context of the BMBF-funded research project “Governance model for socio-ecological transformation processes in practice: development and testing in three areas of application” known by its acronym TRAFO 3.0 was applied to examine innovative approaches and actors in community catering and their contributions to more sustainable food systems. A number of studies show that a very large environmental relief potential can be achieved by reducing the quantity of meat and other animal products offered. However, the concrete implementation of this goal is associated with a multitude of challenges, since meat-containing meals are an important part of German food culture. How the transformation towards meals with fewer animal products in German community catering can succeed is an important question in the context of the transformation to sustainable food systems. To answer this question, we analyzed the status quo of the socio-technical system of German community catering using a developed governance model. One of the central results was that community catering stakeholders who have successfully reduced their offer of animal products died fundamental changes in meal planning. Cooks had to “reinvent” meals completely to be successful.
Mobile Apps for Helping Patient-Users: Is It Still Far-Fetched?
Authors: Siristatidis Charalampos , Pouliakis Abraham , Karageorgiou Vasilios , Vogiatzi Paraskevi
Published: December 2019

Emergence of health-related smartphone applications and their wide dissemination in public as well as healthcare practitioners has undergone criticism under the scope of public health. Still, despite methodological issues curbing the initial enthusiasm, availability, safety and, in certain cases, documented efficacy of these measures has secured regulatory approval. Bearing in mind these pitfalls, we describe the necessary steps towards implementation of deep learning techniques in the specific clinical context of women’s health and infertility in particular.
Artificial Neural Network-Based Residential Energy Consumption Prediction Models Considering Residential Building Information and User Features in South Korea
Authors: Kim Mansu , Jung Sungwon , Kang Joo-won
Published: December 2019

When researching the energy consumption of residential buildings, it is becoming increasingly important to consider how residents use energy. With the advancement of computing power and data analysis techniques, it is now possible to analyze user information using big data techniques. Here, we endeavored to integrate user information with the physical characteristics of residential buildings to analyze how these elements impact energy consumption. Regression analysis was conducted to accurately identify the impact of each element on energy consumption. It was found that six elements were influential in all seasons: the number of exterior walls, housing direction, housing area, number of years occupied, number of household members, and the occupation of the household head. The elements that had an impact in each period were then derived. Based on the results of the regression analysis, input variables for the training of an artificial neural network (ANN) model were selected for each period, and residential energy consumption prediction models were implemented based on actual consumption. The elements identified as those affecting energy consumption, through regression analysis, can be used for implementing prediction models with advanced forms. This study is significant in that we derived influential elements from an integrative perspective.