bluuebunny/crossref_metadata_2025 huggingface dataset:
A Novel 3-URU Architecture with Actuators on the Base: Kinematics and Singularity Analysis
Authors: Di Gregorio Raffaele
Published: August 2020

Translational parallel manipulators (TPMs) with DELTA-like architectures are the most known and affirmed ones, even though many other TPM architectures have been proposed and studied in the literature. In a recent patent application, this author has presented a TPM with three equal limbs of Universal-Revolute-Universal (URU) type, with only one actuated joint per limb, which has overall size and characteristics similar to DELTA robots. The presented translational 3-URU architecture is different from other 3-URUs, proposed in the literature, since it has the actuators on the frame (base) even though the actuated joints are not on the base, and it features a particular geometry. Choosing the geometry and the actuated joints highly affects 3-URU’s behavior. Moreover, putting the actuators on the base allows a substantial reduction of the mobile masses, thus promising good dynamic performances, and makes the remaining part of the limb a simple chain constituted by only passive R-pairs. The paper addresses the kinematics and the singularity analysis of this novel TPM and proves the effectiveness of the new design choices. The results presented here form the technical basis for the above-mentioned patent application.
A Survey of Change Detection Methods Based on Remote Sensing Images for Multi-Source and Multi-Objective Scenarios
Authors: You Yanan , Cao Jingyi , Zhou Wenli
Published: August 2020

Quantities of multi-temporal remote sensing (RS) images create favorable conditions for exploring the urban change in the long term. However, diverse multi-source features and change patterns bring challenges to the change detection in urban cases. In order to sort out the development venation of urban change detection, we make an observation of the literatures on change detection in the last five years, which focuses on the disparate multi-source RS images and multi-objective scenarios determined according to scene category. Based on the survey, a general change detection framework, including change information extraction, data fusion, and analysis of multi-objective scenarios modules, is summarized. Owing to the attributes of input RS images affect the technical selection of each module, data characteristics and application domains across different categories of RS images are discussed firstly. On this basis, not only the evolution process and relationship of the representative solutions are elaborated in the module description, through emphasizing the feasibility of fusing diverse data and the manifold application scenarios, we also advocate a complete change detection pipeline. At the end of the paper, we conclude the current development situation and put forward possible research direction of urban change detection, in the hope of providing insights to the following research.
Geolocation Correction for Geostationary Satellite Observations by a Phase-Only Correlation Method Using a Visible Channel
Authors: Takenaka Hideaki , Sakashita Taiyou , Higuchi Atsushi , Nakajima Teruyuki
Published: August 2020

This study describes a high-speed correction method for geolocation information of geostationary satellite data for accurate physical analysis. Geostationary satellite observations with high temporal resolution provide instantaneous analysis and prompt reports. We have previously reported the quasi real-time analysis of solar radiation at the surface and top of the atmosphere using geostationary satellite data. Estimating atmospheric parameters and surface albedo requires accurate geolocation information to estimate the solar radiation accurately. The physical analysis algorithm for Earth observations is verified by the ground truth. In particular, downward solar radiation at the surface is validated by pyranometers installed at ground observation sites. The ground truth requires that the satellite observation data pixels be accurately linked to the location of the observation equipment on the ground. Thus, inaccurate geolocation information disrupts verification and causes complex problems. It is difficult to determine whether error in the validation of physical quantities arises from the estimation algorithm, satellite sensor calibration, or a geolocation problem. Geolocation error hinders the development of accurate analysis algorithms; therefore, accurate observational information with geolocation information based on latitude and longitude is crucial in atmosphere and land target analysis. This method provides the basic data underlying physical analysis, parallax correction, etc. Because the processing speed is important in geolocation correction, we used the phase-only correlation (POC) method, which is fast and maintains the accuracy of geolocation information in geostationary satellite observation data. Furthermore, two-dimensional fast Fourier transform allowed the accurate correction of multiple target points, which improved the overall accuracy. The reference dataset was created using NASA’s Shuttle Radar Topography Mission 1-s mesh data. We used HIMAWARI-8/Advanced HIMAWARI Imager data to demonstrate our method, with 22,709 target points for every 10-min observation and 5826 points for every 2.5 min observation. Despite the presence of disturbances, the POC method maintained its accuracy. Column offset and line offset statistics showed stability and characteristic error trends in the raw HIMAWARI standard data. Our method was sufficiently fast to apply to quasi real-time analysis of solar radiation every 10 and 2.5 min. Although HIMAWARI-8 is used as an example here, our method is applicable to all geostationary satellites. The corrected HIMAWARI 16 channel gridded dataset is available from the open database of the Center for Environmental Remote Sensing (CEReS), Chiba University, Japan. The total download count was 50,352,443 on 8 July 2020. Our method has already been applied to NASA GeoNEX geostationary satellite products.
Species Monitoring Using Unmanned Aerial Vehicle to Reveal the Ecological Role of Plateau Pika in Maintaining Vegetation Diversity on the Northeastern Qinghai-Tibetan Plateau
Authors: Qin Yu , Sun Yi , Zhang Wei , Qin Yan , Chen Jianjun , Wang Zhiwei , Zhou Zhaoye
Published: August 2020

Plateau pika (Ochotona curzoniae, hereafter pika) is considered to exert a profound impact on vegetation species diversity of alpine grasslands. Great efforts have been made at mound or quadrat scales; nevertheless, there is still controversy about the effect of pika. It is vital to monitor vegetation species composition in natural heterogeneous ecosystems at a large scale to accurately evaluate the real role of pika. In this study, we performed field survey at 55 alpine grassland sites across the Shule River Basin using combined methods of aerial photographing using an unmanned aerial vehicle (UAV) and traditional ground measurement. Based on our UAV operation system, Fragmentation Monitoring and Analysis with aerial Photography (FragMAP), aerial images were acquired. Plot-scale vegetation species were visually identified, and total pika burrow exits were automatically retrieved using the self-developed image processing software. We found that there were significant linear relationships between the vegetation species diversity indexes obtained by these two methods. Additionally, the total number of identified species by the UAV method was 71, which was higher than the Quadrat method recognition, with the quantity of 63. Our results indicate that the UAV was suitable for long-term repeated monitoring vegetation species composition of multiple alpine grasslands at plot scale. With the merits of UAV, it confirmed that pika’s disturbance belonged to the medium level, with the density ranging from 30.17 to 65.53 ha−1. Under this density level, pika had a positive effect on vegetation species diversity, particularly for the species richness of sedge and forb. These findings conclude that the UAV was an efficient and economic tool for species monitoring to reveal the role of pika in the alpine grasslands.
Implementation and Performance Evaluation of Integrated Wireless MultiSensor Module for Aseptic Incubator of Cordyceps militaris
Authors: Lin Jen-Yung , Tsai Huan-Liang , Sang Wen-Chi
Published: August 2020

This paper originally proposes a wireless multisensor module with illuminance, temperature, relative humidity (RH) and carbon dioxide (CO2) sensors in an aseptic jar incubator for a solid-state fermentation (SSF) of Cordyceps militaris culture. The light intensity, ambient temperature, RH and CO2 are the critical cultivation factors of C. militaris. First, these sensors are integrated in a multisensor platform which is installed inside a lid and covered with a high-efficiency particulate air (HEPA) membrane of class H14 for sterilization of bacteria and viruses. The observations of sensors are then transmitted by a wireless XBee network where the slave sensor node is fixed at the top of jar lid and the master radio node receives data and uploads to an on-site monitoring node. The acquired information is further transmitted to an iCloud database and displayed in a web-based monitoring system. The results illustrate the proposed wireless multisensor module was validated with sufficient accuracy, reliable confidence and well-tolerance for C. militaris cultivation biotechnology under aseptic conditions.
Color Sensor Accuracy Index Utilizing Metamer Mismatch Radii
Authors: Roshan Emitis , Funt Brian
Published: August 2020

A novel method is described for evaluating the colorimetric accuracy of digital color cameras based on a new measure of the metamer mismatch body (MMB) that is induced by the change from the camera as an ‘observer’ to the human standard observer. In comparison to the majority of existing methods for evaluating colorimetric accuracy, the advantage of using the MMB is that it is based on the theory of metamer mismatching and, therefore, shows how much color error can arise in principle. A new measure of colorimetric accuracy based on the shape of the camera-induced MMB is proposed and tested. MMB shape is measured in terms of the moments of inertia of the MMB treated as a mass of uniform density. Since colorimetric accuracy is independent of any linear transformation of the sensor space, the MMB measure needs to be as well. Normalization by the moments of inertia of the object color solid is introduced to provide this independence.
An Edge Based Multi-Agent Auto Communication Method for Traffic Light Control
Authors: Wu Qiang , Wu Jianqing , Shen Jun , Yong Binbin , Zhou Qingguo
Published: August 2020

With smart city infrastructures growing, the Internet of Things (IoT) has been widely used in the intelligent transportation systems (ITS). The traditional adaptive traffic signal control method based on reinforcement learning (RL) has expanded from one intersection to multiple intersections. In this paper, we propose a multi-agent auto communication (MAAC) algorithm, which is an innovative adaptive global traffic light control method based on multi-agent reinforcement learning (MARL) and an auto communication protocol in edge computing architecture. The MAAC algorithm combines multi-agent auto communication protocol with MARL, allowing an agent to communicate the learned strategies with others for achieving global optimization in traffic signal control. In addition, we present a practicable edge computing architecture for industrial deployment on IoT, considering the limitations of the capabilities of network transmission bandwidth. We demonstrate that our algorithm outperforms other methods over 17% in experiments in a real traffic simulation environment.
A Mobility-Assisted Localization Algorithm for Three-Dimensional Large-Scale UWSNs
Authors: Luo Junhai , Yang Yang , Wang Zhiyan , Chen Yanping , Wu Man
Published: August 2020

As one of the important facilities for marine exploration, as well as environment monitoring, access control, and security, underwater wireless sensor networks (UWSNs) are widely used in related military and civil fields, since the sensor node localization is the basis of UWSNs’ application in various related fields. Therefore, the research of localization algorithms based on UWSNs has gradually become one of the research hotspots today. However, unlike terrestrial wireless sensor networks (WSNs), many terrestrial monitoring and localization technologies cannot be directly applied to the underwater environment. Moreover, due to the complexity and particularity of the underwater environment, the localization of underwater sensor nodes still faces challenges, such as the localization ratio of sensor nodes, time synchronization, localization accuracy, and the mobility of nodes. In this paper, we propose a mobility-assisted localization scheme with time synchronization-free feature (MALS-TSF) for three-dimensional (3D) large-scale UWSNs. In addition, the underwater drift of the sensor node is considered in this scheme. The localization scheme can be divided into two phases. In Phase I, anchor nodes are distributed in the monitoring area, reducing the monitoring cost. Then, we address a time-synchronization-free localization scheme, to obtain the coordinates of the unknown sensor nodes. In Phase II, we use the method of two-way TOA to locate the remaining ordinary sensor nodes. The simulation results show that MALS-TSF can achieve a relatively high localization ratio without time synchronization.
An Online Tea Fixation State Monitoring Algorithm Based on Image Energy Attention Mechanism and Supervised Clustering (IEAMSC)
Authors: Yu Zhiyong , Wang Jin , Zheng Tao , Lu Guodong
Published: August 2020

This study aimed at the shortcomings of existing fixation algorithms that are image-based only, and an effective tea fixation state monitoring algorithm was proposed. An adaptive filtering algorithm was used to automatically filter the ineffective information. Using the energy extractor, the complete energy information of each fixation image was extracted. The image energy attention mechanism was used to identify the prominent features, and based on these, the energy data was mapped to generate the data points as the training data. The cluster idea was adopted, and the training data feed the features trainer. The trend center data of the tea processing energy clustering was generated from different color channels. The corresponding decision function was designed which is based on the distance of the cluster center. The fixation degree of each monitoring image set was measured by the decision function. The Euclidean distance of the energy clustering center of the three channels with the same fixation time progressively approached. The triangle formed by these three points had a trend of gradually shrinking, which was first discovered by us. The detection results showed high accuracy compared with the common classification algorithms. It indicates that the algorithm proposed has positive guiding and reference significance.
Miniature Resistance Measurement Device for Structural Health Monitoring of Reinforced Concrete Infrastructure
Authors: Corva Dean M. , Hosseini Seyyed Sobhan , Collins Frank , Adams Scott D. , Gates Will P. , Kouzani Abbas Z.
Published: August 2020

A vast amount of civil infrastructure is constructed using reinforced concrete, which can be susceptible to corrosion, posing significant risks. Corrosion of reinforced concrete has various causes, with chloride ingress known to be a major contributor. Monitoring this chloride ingress would allow for preventative maintenance to be less intrusive at a lower cost. Currently, chloride sensing methods are bulky and expensive, leaving the majority of concrete infrastructures unmonitored. This paper presents the design and fabrication of a miniature, low-cost device that can be embedded into concrete at various locations and depths. The device measures localized concrete resistance, correlating to the chloride ingress in the concrete using equations listed in this paper, and calculated results from two experiments are presented. The device benefits from a four-probe architecture, injecting a fixed frequency AC waveform across its outer electrodes within the cement block. Voltage across the internal electrodes is measured with a microcontroller and converted to a resistance value, communicated serially to an external computer. A final test showcases the ability of the device for three-dimensional mass deployment.
Effect of Cathode Material and Its Size on the Abundance of Nitrogen Removal Functional Genes in Microcosms of Integrated Bioelectrochemical-Wetland Systems
Authors: Gadegaonkar Sharvari S. , Philippon Timothé , Rogińska Joanna M. , Mander Ülo , Maddison Martin , Etienne Mathieu , Barrière Frédéric , Kasak Kuno , Lust Rauno , Espenberg Mikk
Published: August 2020

Constructed wetland-microbial electrochemical snorkel (CW-MES) systems, which are short-circuited microbial fuel cells (MFC), have emerged as a novel tool for wastewater management, although the system mechanisms are insufficiently studied in process-based or environmental contexts. Based on quantitative polymerase chain reaction assays, we assessed the prevalence of different nitrogen removal processes for treating nitrate-rich waters with varying cathode materials (stainless steel, graphite felt, and copper) and sizes in the CW-MES systems and correlated them to the changes of N2O emissions. The nitrate and nitrite removal efficiencies were in range of 40% to 75% and over 98%, respectively. In response to the electrochemical manipulation, the abundances of most of the nitrogen-transforming microbial groups decreased in general. Graphite felt cathodes supported nitrifiers, but nirK-type denitrifiers were inhibited. Anaerobic ammonium oxidation (ANAMMOX) bacteria were less abundant in the electrochemically manipulated treatments compared to the controls. ANAMMOX and denitrification are the main nitrogen reducers in CW-MES systems. The treatments with 1:1 graphite felt, copper, plastic, and stainless-steel cathodes showed higher N2O emissions. nirS- and nosZI-type denitrifiers are mainly responsible for producing and reducing N2O emissions, respectively. Hence, electrochemical manipulation supported dissimilatory nitrate reduction to ammonium (DNRA) microbes may play a crucial role in producing N2O in CW-MES systems.
Payment Criteria and Mode for Watershed Ecosystem Services: A Case Study of the Heihe River Basin, Northwest China
Authors: Song Xiaoyu , Liu Yuqing , Zhong Fanglei , Deng Xiaohong , Qi Yuan , Zhang Jinlong , Zhang Rong , Zhang Yongnian
Published: August 2020

Quantitative evaluation of the relationship between payment criteria and the amount of additional ecosystem services can improve the cost-effectiveness of payment for ecosystem services (PES) projects. This paper simulated additional water conservation (AWC) using the Soil and Water Assessment Tool (SWAT) model, examined appropriate payment criteria, and matched different payment modes with local herders’ preferences in Northwest China. The results showed that if all the low-coverage grass areas were to be closed through PES projects, the actual payment criteria, 37 yuan/ha, would need to be increased eight times, which would be 302 yuan/ha. Along with that, annual AWC could reach 1.69 × 106 m3. If PES projects were implemented in all the low- and medium-coverage grass areas, payment criteria would need to be increased to 365 yuan/ha, and the annual AWC would reach 2.59 × 106 m3. There were scale economy effects in this range, because a 21% increase in the payment criteria would result in a 66% increase in the total AWC. The appropriate mode for herders above 40 years old is “cash + in-kind compensation” and “cash + capacity” for those below 40, due to the preferences varying in age.
Threshold or Limit? Precipitation Dependency of Austrian Landslides, an Ongoing Challenge for Hazard Mapping under Climate Change
Authors: Offenthaler Ivo , Felderer Astrid , Formayer Herbert , Glas Natalie , Leidinger David , Leopold Philip , Schmidt Anna , Lexer Manfred J.
Published: August 2020

Climate change is set to increase landslide frequency around the globe, thus increasing the potential exposure of people and material assets to these disturbances. Landslide hazard is commonly modelled from terrain and precipitation parameters, assuming that shorter, more intense rain events require less precipitation volume to trigger a slide. Given the extent of non-catastrophic slides, an operable vulnerability mapping requires high spatial resolution. We combined heterogeneous regional slide inventories with long-term meteorological records and small-scale spatial information for hazard modelling. Slope, its (protective) interaction with forest cover, and altitude were the most influential terrain parameters. A widely used exponential threshold to estimate critical precipitation was found to incorrectly predict meteorological hazard to a substantial degree and, qualitatively, delineate the upper boundary of natural conditions rather than a critical threshold. Scaling rainfall parameters from absolute values into local probabilities (per km²) however revealed a consistent pattern across datasets, with the transition from normal to critical rain volumes and durations being gradual rather than abrupt thresholds. Scaled values could be reverted into site-specific nomograms for easy appraisal of critical rain conditions by local stakeholders. An overlay of terrain-related hazard with infrastructure yielded local vulnerability maps, which were verified with actual slide occurrence. Multiple potential for observation bias in ground-based slide reporting underlined the value of complementary earth observation data for slide mapping and early warning.
Microcredits for Sustainable Development of Small Ukrainian Enterprises: Efficiency, Accessibility, and Government Contribution
Authors: Yemelyanov Olexandr , Petrushka Tetyana , Symak Anastasiya , Trevoho Olena , Turylo Anatolii , Kurylo Oksana , Danchak Lesia , Symak Dmytro , Lesyk Lilia
Published: August 2020

The purpose of the study was to assess the efficiency and accessibility of microcredits for small Ukrainian enterprises and to justify the feasibility of strengthening government contributions in lending to ensure the sustainable development of small businesses. Indicators for evaluating the efficiency and accessibility of microcredits are systematized. Methodological approaches to assessing the efficiency of lending for the creation and development of microenterprises have been improved. A model for evaluating the efficiency of microcredits aimed at the survival of microenterprises in a deteriorating environment was developed. It has been revealed that the level of efficiency of microcredit creation for firms in some time intervals depends quadratically on the share of microcredits in the total amount of funds directed to the creation of firms. A linear relationship between the relative amount of credit received and the growth rate of firms’ assets has also been established. However, there is no significant impact of the microcredit’s amount on labor productivity. A method has been developed for evaluating the budgetary efficiency of microcredits when such a lending is carried out using funds from state or local budgets. It was found that improving these lending conditions through budget financing can significantly increase its attractiveness for microenterprises without significantly reducing the budgetary efficiency of microcredits. This article substantiates the need to strengthen state support for microcrediting of small Ukrainian enterprises in the context of the COVID-19 pandemic.
The Quality of Ecologically and Conventionally Grown White and Brown Agaricus bisporus Mushrooms
Authors: Paulauskienė Aurelija , Tarasevičienė Živilė , Šileikienė Daiva , Česonienė Laima
Published: August 2020

Agaricus bisporus is a rich source of biologically active compounds with functional properties that have a positive effect on human health. White and brown A. bisporus mushrooms were grown both organically and conventionally. This study aimed to analyze chemical composition of the mushrooms, their electrochemical properties, and the composition of volatile compounds. The relationships between cultivation practices and the basic chemical composition, electrochemical properties, and aroma compounds of A. bisporus were examined. The results reveal that ecologically grown mushrooms accumulated higher amounts of ascorbic acid while conventionally grown mushrooms accumulated more crude protein and zinc. More substantial amounts of dry matter, crude protein, and crude ash were found in the brown mushrooms. The white mushrooms had a higher content of ascorbic acid, crude fat, and dietary fiber. Ten volatile compounds were tentatively identified in analyzed mushrooms, including five aldehydes, two esters, two alcohols, and one terpene. Conventionally grown mushrooms had a higher pH value, but eco mushrooms had significantly lower redox potential. White mushrooms had lower p-values than brown mushrooms. Eco mushrooms could not be distinguished by their qualitative characteristics. The chemical composition of white and brown mushrooms was somewhat different, and only the electrochemical properties of mushrooms differed significantly.
Elements of Sustainable Development in the Context of the Environmental and Financial Crisis and the COVID-19 Pandemic
Authors: Kapecki Tomasz
Published: August 2020

Sustainable development is the need of the hour today. For over three decades, since the term was used in public little has been done about it. Such important activities for the protection of our ecosystem have been mainly discussed at scientific conferences or in the comfort of academic lecture halls. Successive global crises, especially the ecological, economic, financial and now humanitarian one related to the COVID-19 pandemic have demolished global economies, sidelined the development of a sustainable economy and especially sustainable construction, treating it more as a whim of the rich than expedience. The construction sector accounts for up to 40 per cent of the global carbon dioxide emissions and generates more than 0.5 billion tonnes of waste every year. However, when it comes to improving macroeconomic indicators after another crisis, the easiest way to look for savings is to use the production of emerging markets, without considering their lower economic and environmental awareness. Each time, the lust for profit prevailed over environmental protection. Education, business, and institutional factors failed, as indicated in the conclusions. That was the case until November 17, 2019, when the first man was infected with the coronavirus. Will we draw the right conclusions from that while facing a crisis unprecedented in human history? Can we change priorities from having to being?
Wake Region Estimates of Artificial Reefs in Vietnam: Effects of Tropical Seawater Temperatures and Seasonal Water Flow Variation
Authors: Le Quynh Thi Ngoc , Jung Somi , Na Won-Bae
Published: August 2020

From the perspective of saving energy of marine species and creating feeding areas, the wake volume of an artificial reef (AR) should be considered as a parameter in any wake region estimation. Wake regions of AR modules (reef ball, cylinder reef, and cube reef) and sets were numerically estimated considering tropical seawater temperatures and water flow variation in Vietnamese coastal waters. In addition, we considered an efficiency index (i.e., total wake volume per reef volume) and wake volume diagram (i.e., wake volume dependency on water flow direction) to characterize wake volumes. From the results, first, it was found that the effect of temperature on the wake volumes was minor in comparison with the effect of flow direction. It was also found that the optimum installation angles were 30° (reef ball and its set), 30° (cylinder reef and its set), and 0° (cube and its set) along the major flow direction. Second, it was found that the cylinder reef and its set were attractive because they generated the maximum wake volumes, regardless of seawater temperature. Thus, the module and set showed better average efficiency indices (9.28 for module and 6.81 for set) than the other cases. We found that the wake volume was dominant in the efficiency index and, accordingly, wake volume diagrams are sufficient to indicate the dependence on flow direction.
Latent Profiles of Anxious Children and Their Differences in Aggressive Behavior
Authors: Fernández-Sogorb Aitana , Sanmartín Ricardo , Vicent María , García-Fernández José Manuel
Published: August 2020

Children tend to develop forms of anxiety that can be associated with school violence. However, the previous scientific literature on anxiety and aggression is scarce. In addition, it has only focused on examining differential relationships between both variables. This study aimed to analyze the relationships between three forms of anxiety (anticipatory anxiety, school-based performance anxiety, and generalized anxiety) and the components of aggression (physical and verbal aggression, anger, and hostility) by adopting a person-centered approach. The sample consisted of 1161 Spanish students from 8 to 11 years old (M = 9.72, SD = 1.14); 46.2% were boys. Informed written consent from the parents or legal guardians was obtained. The Visual Analogue Scale for Anxiety—Revised and the Aggression Questionnaire were used. The latent profile analysis technique identified three profiles of anxious children: Low Anxiety, High School-based Performance Anxiety, and High Anxiety. The High Anxiety group scored significantly higher than the Low Anxiety group in all components of aggression, with effect sizes ranging from moderate to large (d = 0.59 to 0.99). The High Anxiety profile showed significantly higher scores than the high school-based performance anxiety profile only in anger (d = 0.56) and hostility (d = 0.44). The results have relevant implications for practice, since there is evidence that different intervention strategies should be applied according to the risk profile.
Social Life-Cycle Assessment: A Review by Bibliometric Analysis
Authors: Huertas-Valdivia Irene , Ferrari Anna Maria , Settembre-Blundo Davide , García-Muiña Fernando E.
Published: August 2020

This study examined the literature on social life-cycle assessment (S-LCA) published in the last 15 years (2003–2018) using bibliometric methods. Applying scientific mapping and analyzing publication performance, the study describes the structure of and trends in S-LCA publications in terms of related subject categories, authors, journals, countries, and highly cited articles. Challenges and research gaps in the S-LCA literature were also explored. The content of related papers published in the ISI Web of Science databases was examined to identify the main themes investigated, evolution of publication activity, and most representative elements. Analyses were conducted with SciMAT software. This tool enables researchers to map research specialties by extracting qualitative information in the specialized literature and representing it using quantitative measures. The results show rapid and exponential growth of the S-LCA research line in the past ten years, with a clear upward trend in related publications (mostly case studies), especially after publication of the UNEP/SETAC Guidelines for Social Life Cycle Assessment of Products in 2009: 66% of all articles published on S-LCA were published during the period 2015–2018, primarily by European authors. The findings also delineate S-LCA as a highly fragmented research field that has been applied to diverse sectors (agriculture, bioenergy, transport, water management, chemical products, electronics, etc.), mainly in non-European countries. Critical questions concerning methods, framework, paradigms, and indicators remain to be resolved. This study provides insight into the publication performance of S-LCA, characterizing its intellectual structure and salient authors and works. In identifying hotspots in the S-LCA research, the study provides a useful state-of-the-art reference guide for academics and reveals critical research gaps and potential research avenues for future studies to advance in consolidating the discipline.
Evaluation of the SEdiment Delivery Distributed (SEDD) Model in the Shihmen Reservoir Watershed
Authors: Thomas Kent , Chen Walter , Lin Bor-Shiun , Seeboonruang Uma
Published: August 2020

The sediment delivery ratio (SDR) connects the weight of sediments eroded and transported from slopes of a watershed to the weight that eventually enters streams and rivers ending at the watershed outlet. For watershed management agencies, the estimation of annual sediment yield (SY) and the sediment delivery has been a top priority due to the influence that sedimentation has on the holding capacity of reservoirs and the annual economic cost of sediment-related disasters. This study establishes the SEdiment Delivery Distributed (SEDD) model for the Shihmen Reservoir watershed using watershed-wide SDRw and determines the geospatial distribution of individual SDRi and SY in its sub-watersheds. Furthermore, this research considers the statistical and geospatial distribution of SDRi across the two discretizations of sub-watersheds in the study area. It shows the probability density function (PDF) of the SDRi. The watershed-specific coefficient (β) of SDRi is 0.00515 for the Shihmen Reservoir watershed using the recursive method. The SY mean of the entire watershed was determined to be 42.08 t/ha/year. Moreover, maps of the mean SY by 25 and 93 sub-watersheds were proposed for watershed prioritization for future research and remedial works. The outcomes of this study can ameliorate future watershed remediation planning and sediment control by the implementation of geospatial SDRw/SDRi and the inclusion of the sub-watershed prioritization in decision-making. Finally, it is essential to note that the sediment yield modeling can be improved by increased on-site validation and the use of aerial photogrammetry to deliver more updated data to better understand the field situations.
Analysis of Social and Environmental Impact of Earth-Rock Dam Breaks Based on a Fuzzy Comprehensive Evaluation Method
Authors: Gu Hao , Fu Xiao , Zhu Yantao , Chen Yijun , Huang Lixian
Published: August 2020

A large proportion of the dams in China are earth-rock dams. Regarding the well-studied loss of life and economic consequences due to dam breaks, this paper introduces the causes and modes of earth-rock dam breaks and the corresponding dam-break losses in terms of the social and environmental aspects. This study formulates the evaluation index system and criteria of earth-rock dam breaks’ impact on society and the environment based on a fuzzy comprehensive evaluation method. The results show that the evaluation grade of the social and environmental impact of the dam break of the Liujiatai Reservoir was “serious”. Therefore, similar dams in China should take corresponding measures in advance to reduce the social and environmental impact of earth-rock dam breaks.
Machine Learning-Based Network Sub-Slicing Framework in a Sustainable 5G Environment
Authors: Singh Sushil Kumar , Salim Mikail Mohammed , Cha Jeonghun , Pan Yi , Park Jong Hyuk
Published: August 2020

Nowadays, 5G network infrastructures are being developed for various industrial IoT (Internet of Things) applications worldwide, emerging with the IoT. As such, it is possible to deploy power-optimized technology in a way that promotes the long-term sustainability of networks. Network slicing is a fundamental technology that is implemented to handle load balancing issues within a multi-tenant network system. Separate network slices are formed to process applications having different requirements, such as low latency, high reliability, and high spectral efficiency. Modern IoT applications have dynamic needs, and various systems prioritize assorted types of network resources accordingly. In this paper, we present a new framework for the optimum performance of device applications with optimized network slice resources. Specifically, we propose a Machine Learning-based Network Sub-slicing Framework in a Sustainable 5G Environment in order to optimize network load balancing problems, where each logical slice is divided into a virtualized sub-slice of resources. Each sub-slice provides the application system with different prioritized resources as necessary. One sub-slice focuses on spectral efficiency, whereas the other focuses on providing low latency with reduced power consumption. We identify different connected device application requirements through feature selection using the Support Vector Machine (SVM) algorithm. The K-means algorithm is used to create clusters of sub-slices for the similar grouping of types of application services such as application-based, platform-based, and infrastructure-based services. Latency, load balancing, heterogeneity, and power efficiency are the four primary key considerations for the proposed framework. We evaluate and present a comparative analysis of the proposed framework, which outperforms existing studies based on experimental evaluation.
Comparative Study of AI-Based Methods—Application of Analyzing Inflow and Infiltration in Sanitary Sewer Subcatchments
Authors: Zhang Zhe , Laakso Tuija , Wang Zeyu , Pulkkinen Seppo , Ahopelto Suvi , Virrantaus Kirsi , Li Yu , Cai Ximing , Zhang Chi , Vahala Riku , Sheng Zhuping
Published: August 2020

Inflow and infiltration (I/I) is a common problem in sanitary sewer systems. The I/I rate is also considered to be an important indicator of the operational and structural condition of the sewer system. Situation awareness in sanitary sewer systems requires accurate wastewater-flow information at a fine spatiotemporal scale. This study aims to develop artificial intelligence (AI)-based models (adaptive neurofuzzy inference system (ANFIS) and multilayer perceptron neural network (MLPNN)) and to compare their performance for identifying the potential inflow and infiltration of the sanitary sewer subcatchment of two pumping stations. We tested the performance of these AI models by using data gathered from two pumping stations through a supervisory control and data acquisition (SCADA) system. As a result, these two AI models produced similar inflow and infiltration patterns—both subcatchments experienced inflow and infiltration. On the other hand, the ANFIS had overall higher performance than that of the MLPNN model for modelling the I/I situation for the catchments. The results of the research can be used to support spatial decision making in sewer system maintenance.
Oscillation Properties of Singular Quantum Trees
Authors: Homa Monika , Hryniv Rostyslav
Published: August 2020

We discuss the possibility of generalizing the Sturm comparison and oscillation theorems to the case of singular quantum trees, that is, to Sturm-Liouville differential expressions with singular coefficients acting on metric trees and subject to some boundary and interface conditions. As there may exist non-trivial solutions of differential equations on metric trees that vanish identically on some edges, the classical Sturm theory cannot hold globally for quantum trees. However, we show that the comparison theorem holds under minimal assumptions and that the oscillation theorem holds generically, that is, for operators with simple spectra. We also introduce a special Prüfer angle, establish some properties of solutions in the non-generic case, and then extend the oscillation results to simple eigenvalues.
New Exact Solutions and Conservation Laws to the Fractional-Order Fokker–Planck Equations
Authors: Kadkhoda Nematollah , Lashkarian Elham , Inc Mustafa , Akinlar Mehmet Ali , Chu Yu-Ming
Published: August 2020

The main purpose of this paper is to present a new approach to achieving analytical solutions of parameter containing fractional-order differential equations. Using the nonlinear self-adjoint notion, approximate solutions, conservation laws and symmetries of these equations are also obtained via a new formulation of an improved form of the Noether’s theorem. It is indicated that invariant solutions, reduced equations, perturbed or unperturbed symmetries and conservation laws can be obtained by applying a nonlinear self-adjoint notion. The method is applied to the time fractional-order Fokker–Planck equation. We obtained new results in a highly efficient and elegant manner.
Rectus Femoris Characteristics in Post Stroke Spasticity: Clinical Implications from Ultrasonographic Evaluation
Authors: Cosenza Lucia , Picelli Alessandro , Azzolina Danila , Minetto Marco Alessandro , Invernizzi Marco , Bertoni Michele , Santamato Andrea , Baricich Alessio
Published: August 2020

In stroke survivors, rectus femoris (RF) spasticity is often implicated in gait pattern alterations such as stiff knee gait (SKG). Botulinum toxin type A (BoNT-A) is considered the gold standard for focal spasticity treatment. However—even if the accuracy of injection is crucial for BoNT-A efficacy—instrumented guidance for BoNT-A injection is not routinely applied in clinical settings. In order to investigate the possible implications of an inadequate BoNT-A injection on patients’ clinical outcome, we evaluated the ultrasound-derived RF characteristics (muscle depth, muscle thickness, cross-sectional area and mean echo intensity) in 47 stroke survivors. In our sample, we observed wide variability of RF depth in both hemiparetic and unaffected side of included patients (0.44 and 3.54 cm and between 0.25 and 3.16 cm, respectively). Moreover, our analysis did not show significant differences between treated and non-treated RF in stroke survivors. These results suggest that considering the inter-individual variability in RF muscle depth and thickness, injection guidance should be considered for BoNT-A treatment in order to optimize the clinical outcome of treated patients. In particular, ultrasound guidance may help the clinicians in the long-term follow-up of muscle quality.
Incidence of Guillain-Barré Syndrome Is Not Associated with Influenza Vaccination in the Elderly
Authors: Lee Hankil , Kang Hye-Young , Jung Sun-Young , Lee Young-Mock
Published: August 2020

We aimed to analyze the incidence of Guillain-Barré syndrome (GBS) and its association with influenza vaccination (IV) in the elderly population. This study included 2470 patients hospitalized with GBS (G61.0) between 2014 and 2016 based on the Korean National Health Insurance Service (NHIS) claims data. We reviewed every medical claim in the 42 days preceding GBS diagnosis looking for precedent causes of GBS. To assess the relationship between IV and the development of GBS, data from the NHIS and the National Vaccination Registry were combined and analyzed. Using a self-controlled case series (SCCS) approach, we calculated the incidence rate ratio by setting the risk period as 42 days following vaccination. The annual background incidence of GBS was estimated at 4.15 per 100,000 persons. More than half of the patients with newly developed GBS had a previous infection or surgery. The incidence of GBS within 42 days of IV was estimated at 0.32 per 100,000 vaccinated persons. SCCS analysis showed that the risk of GBS was not significantly higher. While GBS can potentially develop from various infections, no association was found between GBS and IV. These results will contribute to developing an evidence-based vaccine policy that includes a clear causality assessment of adverse events.
Resilience of Primary Food Production to a Changing Climate: On-Farm Responses to Water-Related Risks
Authors: Hess Tim , Knox Jerry , Holman Ian , Sutcliffe Chloe
Published: August 2020

Water is a fundamental component in primary food production, whether it be rainfall, irrigation used to water crops, or for supplying drinking water for animals, while the amount of water in the soil determines it capacity to support machinery and animals. We identify that UK agriculture is exposed to five main water-related risks: agricultural drought, scarcity of water resources, restrictions on the right to abstract water, excess soil water, and inundation. Projected milder, wetter winters and hotter, drier summers by the end of the century will change the frequency, persistence, or severity of each of these risks. This paper critically reviews and synthesizes the scientific literature on the impact of these risks on primary food production and the technological and managerial strategies employed to build resilience to these changing risks. At the farm scale, the emphasis has been on strategies to build robustness to reduce the impact of a water-related risk. However, collaborative partnerships allow for a more optimal allocation of water during times of scarcity. Enhancing cross-scale interactions, learning opportunities, and catchment-scale autonomy will be key to ensuring the agricultural system can build adaptive and transformational capacity.
Temporal Trend Analysis of Meteorological Variables and Reference Evapotranspiration in the Inter-mountain Region of Wyoming
Authors: Sharma Vivek , Nicholson Christopher , Bergantino Antony , Irmak Suat , Peck Dannele
Published: August 2020

Long-term trends in reference evapotranspiration (ETref) and its controlling factors are critical pieces of information in understanding how agricultural water requirements and water resources respond to a variable and changing climate. In this study, ETref, along with climate variables that directly and indirectly impact it, such as air temperature (T), incoming solar radiation (Rs), wind speed (u), relative humidity (RH), and precipitation (P), are discussed. All variables are analyzed for four weather stations located in irrigated agricultural regions of inter-mountain Wyoming: Pinedale, Torrington, Powell, and Worland. Non-parametric Mann−Kendall (MK) trend test and Theil–Sen’s slope estimator were used to determine the statistical significance of positive or negative trends in climate variables and ETref. Three non-parametric methods—(i) Pettitt Test (PT), (ii) Alexandersson’s Standard Normal Homogeneity Test (SNHT), and (iii) Buishand’s Range Test (BRT)—were used to check the data homogeneity and to detect any significant Trend Change Point (TCP) in the measured data time-series. For the data influenced by serial correlation, a modified version of the MK test (pre-whitening) were applied. Over the study duration, a statistically significant positive trend in maximum, minimum, and average annual temperature (Tmax, Tmin, and Tavg, respectively) was observed at all stations, except for Torrington in the southeast part of Wyoming, where these temperature measures had negative trends. The study indicated that the recent warming trends are much more pronounced than during the 1930s Dust Bowl Era. For all the stations, no TCPs were observed for P; however, significant changes in trends were observed for Tmax and Tmin on both annual and seasonal timescales. Both grass and alfalfa reference evapotranspiration (ETo and ETr) had statistically significant positive trends in at least one season (in particular, the spring months of March, April, and May (MAM) or summer months of June, July, and August (JJA) at all stations, except the station located in southeast Wyoming (Torrington) where no statistically significant positive trends were observed. Torrington instead experienced statistically significant negative trends in ETo and ETr, particularly in the fall months of SON and winter months of DJF. Over the period-of-record, an overall change of +26, +31, −48, and +34 mm in ETo and +28, +40, −80, and +39 mm in ETr was observed at Pinedale, Powell, Torrington, and Worland, respectively. Our analysis indicated that both ETo (−3.4 mm year−1) and ETr (−5.3 mm year−1) are decreasing at a much faster rate in recent years at Torrington compared to other stations. Relationships between climate variables and ETo and ETr on an annual time-step reveal that ETo and ETr were significantly and positively correlated to Tavg, Tmax, Rs, Rn, and VPD, as well as significantly and negatively correlated to RH.