bluuebunny/crossref_metadata_2025 huggingface dataset:
Estimating the Benefits of Korea’s Intercity Rail Speed Increase Project: An Agent-Based Model Approach
Authors: Kim Chansung , Rim Heesub , Oh DongIk , Kang Dongwoon
Published: January 2022

In the cost–benefit analysis of urban transportation investment, a logsum-based benefit calculation is widely used. However, it is rarely applied to inter-regional transportation. In this study, we applied a logsum-based approach to the calculation of benefits for high-speed projects for inter-regional railways in Korea’s long-term transportation plan. Moreover, we applied a behavioral model in which an agent travels beyond the zones assumed by an aggregate model. In the case of South Korea, such a model is important for determining transportation priorities: whether to specialize in mobility improvement by investing in a high-speed railway project, such as the 300 km/h Korea Train eXpress (KTX), or to improve existing facilities, such as by building a relatively slower railroad (150–250 km/h) to enhance existing mobility and accessibility. In this context, if a new, relatively slow railroad were constructed adjacent to a high-speed railroad, the benefits would be negligible since the reduction in travel time would not sufficiently reflect accessibility improvements. Therefore, this study proposes the use of aggregate and agent-based models to evaluate projects to improve intercity railway service and conduct a case study with the proposed new methodology. A logsum was selected to account for the benefits of passenger cars on semi-high-speed and high-speed railroads simultaneously since it has been widely used to estimate the benefits of new modes or relatively slow modes. To calculate the logsum, this study used input data from both the aggregate and individual agent-based models, and found that an analysis of the feasibility of inter-regional railroad investment was possible. Moreover, the agent-based model can also be applied to inter-regional analysis. The proposed methods are expected to enable a more comprehensive evaluation of the transport system. In the case of the agent-based model, it is suggested that further studies undertake more detailed scenario analysis and travel time estimation.
Synthesis and Characterization of NiCoPt/CNFs Nanoparticles as an Effective Electrocatalyst for Energy Applications
Authors: Abdel-Hady Esam E. , Shaban Mohamed , Abdel-Hamed Mohamed O. , Gamal Ahmed , Yehia Heba , Ahmed Ashour M.
Published: January 2022

In this work, three nanoparticle samples, Ni4Co2Pt/CNFs, Ni5CoPt/CNFs and Ni6Pt/CNFs, were designed according to the molar ratio during loading on carbon nanofibers (CNFs) using electrospinning and carbonization at 900 °C for 7 h in an argon atmosphere. The metal loading and carbon ratio were fixed at 20 and 80 wt%, respectively. Various analysis tools were used to investigate the chemical composition, structural, morphological, and electrochemical (EC) properties. For samples with varying Co%, the carbonization process reduces the fiber diameter of the obtained electrospun nanofibers from 200–580 nm to 150–200 nm. The EDX mapping revealed that nickel, platinum, and cobalt were evenly and uniformly incorporated into the carbonized PVANFs. The prepared Ni-Co-Pt/CNFs have a face-centered cubic (FCC) structure with slightly increased crystallite size as the Co% decreased. The electrocatalytic properties of the samples were investigated for ethanol, methanol and urea electrooxidation. Using cyclic voltammetry (CV), chronoamperometry, and electrochemical impedance measurements, the catalytic performance and electrode stability were investigated as a function of electrolyte concentration, scan rate, and reaction time. When Co is added to Ni, the activation energy required for the electrooxidation reaction decreases and the electrode stability increases. In 1.5 M methanol, the Ni5CoPt/CNFs electrode showed the lowest onset potential and the highest current density (30.6 A/g). This current density is reduced to 28.2 and 21.2 A/g for 1.5 M ethanol and 0.33 M urea, respectively. The electrooxidation of ethanol, methanol, and urea using our electrocatalysts is a combination of kinetic/diffusion control limiting reactions. This research provided a unique approach to developing an efficient Ni-Co-Pt-based electrooxidation catalyst for ethanol, methanol and urea.
Preparation and Bolometric Responses of MoS2 Nanoflowers and Multi-Walled Carbon Nanotube Composite Network
Authors: Wang Qin , Wu Yu , Deng Xin , Xiang Liping , Xu Ke , Li Yongliang , Xie Yangsu
Published: January 2022

Due to their broadband optical absorption ability and fast response times, carbon nanotube (CNT)-based materials are considered promising alternatives to the toxic compounds used in commercial infrared sensors. However, the direct use of pure CNT networks as infrared sensors for simple resistance read-outs results in low sensitivity values. In this work, MoS2 nanoflowers are composited with CNT networks via a facile hydrothermal process to increase the bolometric performance. The thermal diffusivity (α) against temperature (T) is measured using the transient electro-thermal (TET) technique in the range of 320 K to 296 K. The α-T curve demonstrates that the composite containing MoS2 nanoflowers provides significant phonon scattering and affects the intertube interfaces, decreasing the α value by 51%. As the temperature increases from 296 K to 320 K, the relative temperature coefficient of resistance (TCR) increases from 0.04%/K to 0.25%/K. Combined with the enhanced light absorption and strong anisotropic structure, this CNT–MoS2 composite network exhibits a more than 5-fold greater surface temperature increase under the same laser irradiation. It shows up to 18-fold enhancements in resistive responsivity ((Ron − Roff)/Roff) compared with the pure CNT network for a 1550 nm laser at room temperature (RT).
Biostimulation of Anaerobic Digestion Using Iron Oxide Nanoparticles (IONPs) for Increasing Biogas Production from Cattle Manure
Authors: Singh Dilbag , Malik Kamla , Sindhu Meena , Kumari Nisha , Rani Vijaya , Mehta Shikha , Malik Karmal , Ranga Poonam , Sharma Kashish , Dhull Neeru , Malik Shweta , Arya Nisha
Published: January 2022

The effect of synthesised IONPs employing a nontoxic leaf extract of Azadirachta indica as a reducing, capping, and stabilizing agent for increasing biogas and methane output from cattle manure during anaerobic digestion (AD) was investigated in this study. Furthermore, the UV-visible spectra examination of the synthesized nanoparticles revealed a high peak at 432 nm. Using a transmission electron microscope, the average particle size of IONPs observed was 30–80 nm, with irregular, ultra-small, semi-spherical shapes that were slightly aggregated and well-distributed. IONPs had a polydisparity index (PDI) of 219 nm and a zeta potential of −27.0 mV. A set of six bio-digesters were fabricated and tested to see how varying concentrations of IONPs (9, 12, 15, 18, and 21 mg/L) influenced biogas, methane output, and effluent chemical composition from AD at mesophilic temperatures (35 ± 2 °C). With 18 mg/L IONPs, the maximum specific biogas and methane production were 136.74 L/g of volatile solids (VS) and 64.5%, respectively, compared to the control (p < 0.05), which provided only 107.09 L/g and 51.4%, respectively. Biogas and methane production increased by 27.6% and 25.4%, respectively using 18 mg/L IONPs as compared to control. In all treatments, the pH of the effluent was increased, while total volatile fatty acids, total solids, volatile solids, organic carbon content, and dehydrogenase activity decreased. Total solid degradation was highest (43.1%) in cattle manure + 18 mg/L IONPs (T5). According to the results, the IONPs enhanced the yield of biogas and methane when compared with controls.
Oxytocin, a Novel Treatment for Methamphetamine Use Disorder
Authors: Edinoff Amber N. , Thompson Elliot , Merriman Chandler E. , Alvarez Mark R. , Alpaugh E. Saunders , Cornett Elyse M. , Murnane Kevin S. , Kozinn Rachel L. , Shah-Bruce Mila , Kaye Adam M. , Kaye Alan D.
Published: January 2022

The treatment of substance abuse with oxytocin is a novel approach to a challenging public health issue that continues to contribute to a growing economic cost for societies worldwide. Methamphetamine addiction is one of the leading causes of mortality worldwide, and despite advances in understanding the neurobiology of methamphetamine addiction, treatment options are limited. There are no medications that the Food and Drug Administration currently approves for stimulant use disorder. Off-label use of therapies for stimulant misuse include antidepressants, anxiolytics, and milder stimulants as replacement agents. Due to the shortcomings of these attempts to treat a complicated psychiatric disorder, recent attention to oxytocin therapy (OT) has gained momentum in clinical studies as a possible therapy in the context of social stress, social anxiety, social cognition, and psychosis. Oxytocin produces enhanced connectivity between cortical regions. The results from studies in rodents with OT suggest that central neuromodulation of oxytocin may be beneficial across transition states of stimulant dependence and may alleviate intense withdrawal symptoms. Studies of oxytocin in the context of other drugs of abuse, including cocaine, cannabis, and alcohol, also support the potential of oxytocin to treat stimulant use disorder, methamphetamine type. Methamphetamine abuse continues to be a significant cause of distress and dysfunction throughout the world. The effects of oxytocin on methamphetamine use outlined in this review should act as a catalyst for further investigation into the efficacy of treating stimulant use disorder, methamphetamine type with oxytocin in humans. More human-based research should initiate studies involving the long-term efficacy, side effects, and patient selection.
Associations between Serum Vitamin A and Metabolic Risk Factors among Eastern Chinese Children and Adolescents
Authors: Tian Ting , Wang Yuanyuan , Xie Wei , Zhang Jingxian , Ni Yunlong , Peng Xianzhen , Sun Guiju , Dai Yue , Zhou Yonglin
Published: January 2022

Vitamin A, a fat-soluble essential vitamin, is implicated in a large range of physiological processes. Up to now, the associations between vitamin A and metabolic syndrome (MetS) or other metabolic risk factors are controversial in children and adolescents. Thus, we aimed to dig into the relationship of vitamin A with MetS and many other metabolic risk factors. This was a cross-sectional study derived from the China National Nutrition and Health Surveillance of Children and Lactating Mothers. A total of 3025 school-aged (7–17 years) children and adolescents were selected by applying multistage stratified cluster random sampling methods in the Jiangsu Province of eastern China. Through enquiry survey, anthropometric measurement and laboratory examination, relevant information and blood biochemical indexes of the participants were collected in this study. MetS was identified according to the modified criteria of the National Cholesterol Education Program–Adult Treatment Panel III (NCEP-ATP III). Multivariate logistic analysis and the generalized additive model (GAM) were used to analyze the relationship between vitamin A and various metabolic risk factors. The overweight, obesity and MetS prevalence of children and adolescents in this study was 14.0%, 11.9% and 5.1%, respectively. The risk of prevalent MetS, general obesity, high low-density lipoprotein (LDL), high total cholesterol (TC) and hyperuricemia increased with vitamin A in a dose-dependent way. Logistic regression analysis showed that serum vitamin A Z scores were positively associated with MetS and central obesity, elevated blood pressure (BP) and elevated triglyceride (TG). Sex stratification analysis showed that both in male and female participants, the risk of prevalent MetS, general obesity, high LDL, high TC and hyperuricemia still increased with vitamin A levels. MetS was at a high prevalence level in children and adolescents in Jiangsu that were 7–17 years old. Vitamin A was positively associated with obesity, MetS, dyslipidemia and hyperuricemia. More public health measures and new visions should focus on the effects of retinol on children and adolescents.
Metabolism and Health Effects of Rare Sugars in a CACO-2/HepG2 Coculture Model
Authors: van Laar Amar , Grootaert Charlotte , Van Nieuwerburgh Filip , Deforce Dieter , Desmet Tom , Beerens Koen , Van Camp John
Published: January 2022

Non-alcoholic fatty liver disease (NAFLD) has become the most prevalent liver disease worldwide and is impacted by an unhealthy diet with excessive calories, although the role of sugars in NAFLD etiology remains largely unexplored. Rare sugars are natural sugars with alternative monomers and glycosidic bonds, which have attracted attention as sugar replacers due to developments in enzyme engineering and hence an increased availability. We studied the impact of (rare) sugars on energy production, liver cell physiology and gene expression in human intestinal colorectal adenocarcinoma (Caco-2) cells, hepatoma G2 (HepG2) liver cells and a coculture model with these cells. Fat accumulation was investigated in the presence of an oleic/palmitic acid mixture. Glucose, fructose and galactose, but not mannose, l-arabinose, xylose and ribose enhanced hepatic fat accumulation in a HepG2 monoculture. In the coculture model, there was a non-significant trend (p = 0.08) towards higher (20–55% increased) median fat accumulation with maltose, kojibiose and nigerose. In this coculture model, cellular energy production was increased by glucose, maltose, kojibiose and nigerose, but not by trehalose. Furthermore, glucose, fructose and l-arabinose affected gene expression in a sugar-specific way in coculture HepG2 cells. These findings indicate that sugars provide structure-specific effects on cellular energy production, hepatic fat accumulation and gene expression, suggesting a health potential for trehalose and l-arabinose, as well as a differential impact of sugars beyond the distinction of conventional and rare sugars.
Effect of Probiotics on Psychiatric Symptoms and Central Nervous System Functions in Human Health and Disease: A Systematic Review and Meta-Analysis
Authors: Le Morvan de Sequeira Charlotte , Hengstberger Charlotte , Enck Paul , Mack Isabelle
Published: January 2022

Background: The gut microbiota impacts on central nervous system (CNS) function via the microbiota–gut–brain axis. Thus, therapeutics targeting the gut microbiota such as probiotics have the potential for improving mental health. This meta-analysis synthesizes the evidence regarding the impacts of probiotics on psychological well-being, psychiatric symptoms and CNS functioning. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were applied for executing this review using the databases PubMed, Web of Science and Cochrane Library. The data were summarized at qualitative and quantitative level. Results: Fifty-four randomized placebo-controlled studies were included, of which 30 were eligible for meta-analysis. If investigated, the probiotics mostly exerted effects on CNS function. Most probiotics did not affect mood, stress, anxiety, depression and psychiatric distress when compared to placebo at the qualitative level. At quantitative level, depression and psychiatric distress improved slightly in the probiotic condition (depression: mean difference −0.37 (95% CI: −0.55, −0.20); p ≤ 0.0001; psychiatric distress: mean difference −0.33 (95% CI: −0.53, −0.13); p = 0.001). Conclusions: To date it is unclear to which extent and in which specific areas next generation probiotics selected and developed for their ability to improve psychiatric condition and potentially other CNS functions are promising.
Structural Changes in Resin-Based Composites in Saliva of Patients with Leukemia before Starting Chemotherapeutic Regimen
Authors: Mester Alexandru , Moldovan Marioara , Cuc Stanca , Petean Ioan , Tomuleasa Ciprian , Piciu Andra , Dinu Cristian , Bran Simion , Onisor Florin
Published: January 2022

Background: The aim of this in vitro study was to assess the morphological characteristics and stability of dental composites immersed in saliva collected from patients with leukemia. Material and Methods: A total number of five patients without systemic disease and 20 patients with leukemia (acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), chronic lymphocytic leukemia (CLL), and chronic myeloid leukemia (CML)) were included for saliva sampling. Composite disks were immersed in the leukemia, control, and artificial environments for 7 days. At the end of the experiment, atomic force microscopy (AFM), color stability (ΔE), and saliva elements analysis were performed. Statistical significance was considered for a p-value under 0.05. Results: The most changed surface resulted for ALL with a roughness that was almost double that of the untreated sample and was significantly increased compared to the healthy saliva. The effect of CLL was not as intense as observed for acute leukemia, but was significantly over the control. ALL seemed to modify structural components of the saliva, which were able to deteriorate the surface of the composite. ALL saliva promoted a significant dissolution of the initial feature of the samples and promoted nano-particle clusterization. All dental composites showed clinically acceptable color change values (ΔE < 3.3) in all four-leukemia salivas; CLL and CML showed large color differences for all composites. The total concentrations of P, Na, and K showed wide ranges of variations, while the coefficient of variation in Fe, Cu, and Mg showed narrow variations between the salvias’ investigated. The salivary concentration of zinc decreased considerably in the CLL and CML environments compared to the ALL and AML environments. Fe and Cu were significantly increased in the CML environment. Conclusions: Control and artificial salivas have a mild erosive effect on the surface of dental composites. The acute stage of the disease seems to deteriorate the surface roughness rather than its morphology, however, in the chronic stage, it is the surface morphology that mostly deteriorates.
Partnership and Rescue Party and the Transformation of Political Opposition in Jordan
Authors: Bozkurt Abdulgani , Ünalmış Muhammed
Published: January 2022

In Jordan, the main regime, as a successful political survival strategy, while skillfully forming a tight pro-regime political coalition all along, has kept an even firmer grip on the political opposition. The political opposition in the country, the Muslim Brotherhood, and its political wing the Islamic Action Front (IAF) being the leading front, sometimes boycotted the elections as a response to or compromised with the regime. This latter approach has also been embraced by the parties which emerged out of the MB, including the National Congress Party and the Muslim Brotherhood Association; however, another splinter party, the Partnership and Rescue Party (PRP) criticized them for their incompetence in acting as a true opposition. This is the juncture this paper problematizes—the IAF seems to have lost its ability to act as the main opposition, and the newly emerged PRP prospectively stands out as the leading candidate to replace it. This paper examines the transformation of the political oppositional block in Jordan and elaborates on its consequences for the MB and the regime–opposition relations. In relation to this, in the conceptual level, the paper also reflects on the relevance of this transformation to the post-Islamism debate: in this instance, the PRP denouncing the political Islamic ideology and positioning itself in the center of the political spectrum while maintaining the claim that it has taken over the main opposition role/legacy of the MB evoke a post-Islamist tendency. The argumentation in the article is built on primary sources, including interviews with the opposition leaders and prominent opposition members.
Chlorophyll-a and Sea Surface Temperature Changes in Relation to Paralytic Shellfish Toxin Production off the East Coast of Tasmania, Australia
Authors: Wakamatsu Lael , Britten Gregory L. , Styles Elliot J. , Fischer Andrew M.
Published: January 2022

Toxic phytoplankton have been detrimental to the fishing and aquaculture industry on the east coast of Tasmania, causing millions of dollars in loss due to contaminated seafood. In 2012–2017, shellfish stocks were poisoned by Alexandrium catenella, a dinoflagellate species that produces paralytic shellfish toxins (PST). Remote sensing data may provide an environmental context for the drivers of PST events in Tasmania. We conducted spatial and temporal trend analyses of the Multi-Scale Ultra-High-Resolution Sea Surface Temperature (MUR SST) and Ocean Color Climate Change Initiative chlorophyll-a (OC-CCI chl-a) to determine if SST and chl-a correlated with the major toxin increases from 2012 to 2017. Along with the trends, we compare the remotely sensed oceanographic parameters of SST and chl-a to toxin events off the east coast of Tasmania to provide environmental context for the high-toxin period. Spatial and temporal changes for chl-a differ based on the north, central, and southeast coast of Tasmania. For sites in the north, chl-a was 5.3% higher from the pre-PST period relative to the PST period, 5.1% along the central part of the coast, and by 6.0% in the south based on deviations from the coastal study area time series. Overall, SST has slightly decreased from 2007 to 2020 (tau = −0.011, p = 0.827) and chl-a has significantly decreased for the east coast (tau = −0.164, p = 1.58 × 10−3). A negative relationship of SST and PST values occurred in the north (r = −0.530, p = 5.32 × 10−5) and central sites (r = −0.225, p = 0.157). The correlation between satellite chl-a (from OC-CCI, Visible Infrared Imaging Radiometer Suite (VIIRS), and Moderate-Resolution Imaging Spectrometer (MODIS) Aqua) and in situ data is weak, which makes it difficult to assess relationships present between chl-a and toxin concentrations. Moving forward, the development of a regional chl-a algorithm and increased in situ chl-a collection and plankton sampling at a species level will help to improve chl-a measurements and toxic phytoplankton production monitoring around Tasmania.
Decision Fusion of Deep Learning and Shallow Learning for Marine Oil Spill Detection
Authors: Yang Junfang , Ma Yi , Hu Yabin , Jiang Zongchen , Zhang Jie , Wan Jianhua , Li Zhongwei
Published: January 2022

Marine oil spills are an emergency of great harm and have become a hot topic in marine environmental monitoring research. Optical remote sensing is an important means to monitor marine oil spills. Clouds, weather, and light control the amount of available data, which often limit feature characterization using a single classifier and therefore difficult to accurate monitoring of marine oil spills. In this paper, we develop a decision fusion algorithm to integrate deep learning methods and shallow learning methods based on multi-scale features for improving oil spill detection accuracy in the case of limited samples. Based on the multi-scale features after wavelet transform, two deep learning methods and two classical shallow learning algorithms are used to extract oil slick information from hyperspectral oil spill images. The decision fusion algorithm based on fuzzy membership degree is introduced to fuse multi-source oil spill information. The research shows that oil spill detection accuracy using the decision fusion algorithm is higher than that of the single detection algorithms. It is worth noting that oil spill detection accuracy is affected by different scale features. The decision fusion algorithm under the first-level scale features can further improve the accuracy of oil spill detection. The overall classification accuracy of the proposed method is 91.93%, which is 2.03%, 2.15%, 1.32%, and 0.43% higher than that of SVM, DBN, 1D-CNN, and MRF-CNN algorithms, respectively.
Analysis of Canopy Gaps of Coastal Broadleaf Forest Plantations in Northeast Taiwan Using UAV Lidar and the Weibull Distribution
Authors: Chung Chih-Hsin , Wang Jonathan , Deng Shu-Lin , Huang Cho-ying
Published: January 2022

Canopy gaps are pivotal for monitoring forest ecosystem dynamics. Conventional field methods are time-consuming and labor intensive, making them impractical for regional mapping and systematic monitoring. Gaps may be delineated using airborne lidar or aerial photographs acquired from a manned aircraft. However, high cost in data acquisition and low flexibility in flight logistics significantly reduce the accessibility of the approaches. To address these issues, this study utilized miniature light detection and ranging (lidar) onboard an unmanned aircraft vehicle (UAVlidar) to map forest canopy gaps of young and mature broadleaf forest plantations along the coast of northeastern Taiwan. This study also used UAV photographs (UAVphoto) for the same task for comparison purposes. The canopy height models were derived from UAVlidar and UAVphoto with the availability of a digital terrain model from UAVlidar. Canopy gap distributions of the forests were modeled with the power-law zeta and Weibull distributions. The performance of UAVlidar was found to be superior to UAVphoto in delineating the gap distribution through ground observation, mainly due to lidar’s ability to detect small canopy gaps. There were apparent differences of the power-law zeta distributions for the young and mature forest stands with the exponents λ of 1.36 (1.45) and 1.71 (1.61) for UAVlidar and UAVphoto, respectively, suggesting that larger canopy gaps were present within the younger stands. The canopy layer of mature forest stands was homogeneous, and the size distributions of both sensors and methods were insensitive to the spatial extent of the monitored area. Contrarily, the young forests were heterogeneous, but only UAVlidar with the Weibull distribution responded to the change of spatial extent. This study demonstrates that using the Weibull distribution to analyze canopy gap from high-spatial resolution UAVlidar may provide detailed information of regional forest canopy of coastal broadleaf forests.
A Google Earth Engine Approach for Wildfire Susceptibility Prediction Fusion with Remote Sensing Data of Different Spatial Resolutions
Authors: Tavakkoli Piralilou Sepideh , Einali Golzar , Ghorbanzadeh Omid , Nachappa Thimmaiah Gudiyangada , Gholamnia Khalil , Blaschke Thomas , Ghamisi Pedram
Published: January 2022

The effects of the spatial resolution of remote sensing (RS) data on wildfire susceptibility prediction are not fully understood. In this study, we evaluate the effects of coarse (Landsat 8 and SRTM) and medium (Sentinel-2 and ALOS) spatial resolution data on wildfire susceptibility prediction using random forest (RF) and support vector machine (SVM) models. In addition, we investigate the fusion of the predictions from the different spatial resolutions using the Dempster–Shafer theory (DST) and 14 wildfire conditioning factors. Seven factors are derived separately from the coarse and medium spatial resolution datasets for the whole forest area of the Guilan Province, Iran. All conditional factors are used to train and test the SVM and RF models in the Google Earth Engine (GEE) software environment, along with an inventory dataset from comprehensive global positioning system (GPS)-based field survey points of wildfire locations. These locations are evaluated and combined with coarse resolution satellite data, namely the thermal anomalies product of the moderate resolution imaging spectroradiometer (MODIS) for the period 2009 to 2019. We assess the performance of the models using four-fold cross-validation by the receiver operating characteristic (ROC) curve method. The area under the curve (AUC) achieved from the ROC curve yields 92.15% and 91.98% accuracy for the respective SVM and RF models for the coarse RS data. In comparison, the AUC for the medium RS data is 92.5% and 93.37%, respectively. Remarkably, the highest AUC value of 94.71% is achieved for the RF model where coarse and medium resolution datasets are combined through DST.
Development of a Combined Orchard Harvesting Robot Navigation System
Authors: Mao Wenju , Liu Heng , Hao Wei , Yang Fuzeng , Liu Zhijie
Published: January 2022

Our research concerned the development of an autonomous robotic navigation system for orchard harvesting with a dual master-slave mode, the autonomous navigation tractor orchard transport robot being the master followed by a navigation orchard picking robot as the slave. This addresses the problem that in single master-slave navigation mode, agricultural combined harvesting equipment cannot stop repeatedly between rows of apple trees and drive continuously when turning. According to distances obtained from a global positioning system (GNSS), ground points were used to switch the navigation mode of the transport and picking robot. A cloth simulation filter (CSF) and random sample consensus (RANSAC) algorithm was used to obtain inter-row waypoints. The GNSS point was manually selected as the turn waypoint of the master and a kinematic model was used to compute the turn waypoints of the slave. Finally, we used a pure pursuit algorithm to track these waypoints sequentially to achieve master-slave navigation and ground head master-slave command navigation. The experimental results show that the data packet loss rate was less than 1.2% when the robot communicated in the orchard row within 50 m which meets the robot orchard communication requirements. The master-slave robot can achieve repeated stops in the row using follow navigation, which meets the demands of joint orchard harvesting. The maximum, minimum, mean and standard deviation of position deviation of the master robot were 5.3 cm, 0.8 cm, 2.4 cm, and 0.9 cm, respectively. The position deviations of the slave robot were larger than those of the master robot, with maximum, minimum, mean and standard deviation of 39.7 cm, 1.1 cm, 4.1 cm, and 5.6 cm, respectively. The maximum, minimum, mean and standard deviation of the following error between the master-slave robot were 4.4 cm, 0 cm, 1.3 cm, and 1 cm respectively. Concerning the ground head turn, the command navigation method allowed continuous turning, but the lateral deviation between robots was more than 0.3 m and less than 1 m, and the heading deviation was more than 10° and less than 90°.
Compact Sphere-Shaped Airflow Vector Sensor Based on MEMS Differential Pressure Sensors
Authors: Haneda Kotaro , Matsudaira Kenei , Noda Ryusuke , Nakata Toshiyuki , Suzuki Satoshi , Liu Hao , Takahashi Hidetoshi
Published: January 2022

This paper presents an airflow vector sensor for drones. Drones are expected to play a role in various industrial fields. However, the further improvement of flight stability is a significant issue. In particular, compact drones are more affected by wind during flight. Thus, it is desirable to detect air current directly by an airflow sensor and feedback to the control. In the case of a drone in flight, the sensor should detect wind velocity and direction, particularly in the horizontal direction, for a sudden crosswind. In addition, the sensor must also be small, light, and highly sensitive. Here, we propose a compact spherical airflow sensor for drones. Three highly sensitive microelectromechanical system (MEMS) differential pressure (DP) sensor chips were built in the spherical housing as the sensor elements. The 2D wind direction and velocity can be measured from these sensor elements. The fabricated airflow sensor was attached to a small toy drone. It was demonstrated that the sensor provided an output corresponding to the wind velocity and direction when horizontal wind was applied via a fan while the drone was flying. The experimental results demonstrate that the proposed sensor will be helpful for directly measuring the air current for a drone in flight.
The Erasmus+ Programme and Sustainable Development Goals—Contribution of Mobility Actions in Higher Education
Authors: Nogueiro Teresa , Saraiva Margarida , Jorge Fátima , Chaleta Elisa
Published: January 2022

Erasmus+ is an EU programme in the fields of education, training, youth and sport for the period 2014–2021 with a major impact at the international level. These areas are making important contributions to help address socioeconomic changes and the key challenges that Europe will face until the end of the decade as well as to support the implementation of the European policy agenda for growth, jobs, equity and social inclusion. The general objectives of the Erasmus+ Programme are intended to contribute to the overall achievement of the objectives of the Europe 2020 Strategy, among others related to sustainable development. Therefore, the main question is: “To which Sustainable Development Goals (SDG) do the Erasmus+ Programme and the mobility projects for higher education directly contribute to?” The answer to this question will allow us to start filling the knowledge gap at the borderline between SDG and Erasmus+. The purpose of this research is to identify, among the 17 SDGs, those that could be more relevant in the context of mobility projects in higher education within the Erasmus+ Programme and how these projects contribute to these identified SDGs. Through the analysis of the general objective of the Erasmus+ Programme, its most important characteristics and the objectives of Key Action 1 and mobility projects, we can conclude that, from the 2030 Agenda, the most relevant SDGs for the programme and for the action and mobility projects are 4 (quality education), 5 (gender equality) and 8 (decent work and economic growth).
Can Online Transparency Improve Accountability? The Case of Portuguese Private Social Solidarity Institutions
Authors: Ferreira Augusta , Bandeira Ana Maria , Santos Carlos , Ferreira Inês , Tomé Brízida , Costa Alberto J. , Joaquim Carla , Góis Cristina , Curi Denise , Meira Deolinda , Azevedo Graça , Inácio Helena , Jesus Mafalda , Teixeira Maria Goreti , Monteiro Patrícia , Duarte Rúben , Marques Rui Pedro
Published: January 2022

The development of the non-profit sector (NPS) in Portugal has been gaining relevance in recent times, particularly in the form of institutions whose purpose is to broaden and increase the response to the needs of the most needy and socially vulnerable citizens. The financing of Portuguese non-profit sector entities is essentially made up of income from their activity, donations and public or governmental support. Therefore, these entities face increasing pressure from their funders, users and citizens in general for a greater dissemination of good practices regarding the social impact they have on the community; in particular, they are increasingly required to be transparent in their activities. The main objective of this study was to analyse the level of accountability and transparency of the private social solidarity institutions (IPSS) of the municipality of Porto. To this end, the websites of these institutions were analysed, using a qualitative and quantitative methodology, using the application of the transparency index Enhancement of an Accountability Guide for Learning E-Government. This analysis allowed us to verify that there are still a considerable number of entities that do not have an institutional website, and those that do, have a low level of transparency.
Green Mortgages, EU Taxonomy and Environment Risk Weighted Assets: A Key Link for the Transition
Authors: Esposito Lorenzo , Mastromatteo Giuseppe , Molocchi Andrea , Brambilla Paola , Carvalho Maria , Girardi Pierpaolo , Marmiroli Benedetta , Mela Giulio
Published: January 2022

The need for a quick and radical green transition gives a key role to the financial system as the main source to fund the change. This debate also involves the development of banking regulation tools able to serve the transition. Building on previous works, we propose a method to weight banks’ assets that combines conventional financial risks and environmental risks to calculate prudential capital requirements, and we apply it to the EU Taxonomy’s technical screening criteria to build an environmental risk indicator based on the buildings’ energy consumptions. We show how to calculate the tool endogenously for the taxonomy sections related to buildings (new construction, purchase of building, renovation), thus proving its immediate enforceability, using data from the Lombardy’s housing stocks. Finally, we conduct a stress test for the Italian banking system showing that our proposal would be an effective incentive for the banks to fund the green transition of the construction sector. Disclaimer: The views expressed are those of the authors and do not involve the responsibility of the Bank of Italy or RSE.
The Right to Accessible COVID-19 Testing in the Post-Epidemic Period under the Urban–Rural Integration: Haishu District, Ningbo City, China
Authors: Liang Xianjun , Ma Renfeng , Cheng Yuxian , Gong Qianqian , Li Jiaming , Zhu Baoyu
Published: January 2022

The reasonable distribution of COVID-19 testing facilities is a crucial public necessity to protect the civil right of health and the proper functioning of society in the post-epidemic period. However, most of the current COVID-19 testing facilities are in large hospitals in China, partially overlooking the COVID-19 testing needs of rural dwellers. This paper used shortest-path analysis and the improved potential model to measure the accessibility of current and potential COVID-19 testing facilities, superimposing this with the testing demands of residents, as calculated by the population demand index, so as to comprehensively evaluate the equity of the spatial allocation of the current and potential testing facilities, with a particular focus on Haishu District, Ningbo City, China. The results revealed that the overall accessibility of the current testing facilities in Haishu District was high, while the internal spatial differentiation was considerable. The comprehensive accessibility of testing facilities gradually declined from the downtown areas towards the rural areas. Moreover, roughly half of the rural population needing COVID-19 tests encountered hindrances due to poor access to testing agencies. However, after fully exploiting the potential testing facilities, the comprehensive accessibility of testing facilities was significantly improved, and the inequity in the accessibility to testing facilities was effectively alleviated, which significantly improved the equity of the allocation of testing facilities in Haishu District. The leveraging of current medical facilities to boost the number of testing facilities in rural areas could eliminate the disparity of resource distribution caused by urban and rural binary opposition, and could quickly identify external sources of COVID-19 in rural areas in the post-epidemic period. Moreover, efficient COVID-19 testing combined with the travel records of infection carriers can effectively identify unknown infection cases and obviate large-scale infection outbreaks.
Role of Standards as an Enabler in a Digital Remanufacturing Industry
Authors: Pratapa Praneetha , Subramoniam Ramesh , Gaur Jighyasu
Published: January 2022

There is plenty of research describing remanufacturing (reman) as the ultimate form of recycling. However, few studies have shown how standards that provide universally accepted definitions and practices can shift towards digitization and how digital technology can act as a catalyst for digital reman. Furthermore, there is no clear direction as to why and how standards and digital technology should work together in reman. Only minimal research (one article from the SCOPUS database) has explored the intersection of these three areas: reman challenges, standards, and digital technology. Many challenges that reman companies face prevent them from successfully transitioning to sustainable production methods. The challenges include high cost of resources, complex parts design, limited core availability, lack of internationally accepted definitions and protocols, poor design of reverse logistics networks, and poor consumer perceptions. On the other hand, digital technology can act as an enabler fueling environmental resilience through innovation. This paper studies how standards can play a role in helping digital technology solve reman challenges, thereby achieving the United Nations Sustainable Development Goal and providing significant opportunities for innovation for small and large enterprises transitioning towards digital reman. The current study is validated by highly experienced reman professionals using the analytical hierarchical process. It is intended to help practitioners assess their organization’s current manufacturing practices and improve resource productivity and business growth using the identified standards and technologies. Three-dimensional printing was found to have the most potential in solving reman challenges. Surprisingly, the Internet of Things ranked low despite lacking information on used products or cores being a significant challenge for suppliers.
Aggregate Simulation with Statistical Approach Considering Substituting
Authors: Woo Byeong Hun , Lee Jeong Bae , Lee Hyunseok , Kim Hong Gi
Published: January 2022

This work focused on reflecting the substituting ratio of fine aggregate in an aggregate simulation. The existing simulation studies showed superior performance on generating the particles; however, the studies did not and could not reflect the substituting ratio of fine aggregate. Therefore, a statistical approach with the Monte Carlo simulation method was tried to improve the lacking part. According to the fitting of the distributions, the Cauchy distribution was best for the natural sand and the log-normal distribution was best for the substituting materials. The chosen two distributions were mixed and applied, using the Monte Carlo method with the mixed model, rather than the existing particle generation formula of the simulation. The substitution ratio was considered to be 0, 30, 50, 70, 100%. The fraction of small particles was gradually increased by the substituting ratio. As a result, the simulated particle distribution reflected well the statistical model. In addition, the simulation was almost the same as that of real particle distribution, according to the CT scanning.
Coupling Coordination of the Regional Economy, Tourism Industry, and the Ecological Environment: Evidence from Western China
Authors: Zhang Fengting , Sarker Md Nazirul Islam , Lv Yang
Published: January 2022

The economic–tourism–environment (ETE) is a complex system with extensive connotations and coupling characteristics. The exact understanding of these systems forms the prerequisite and basis for regional development. This study explores the impact of the coupling coordination of the ETE system on the level and influencing factors of sustainable development in western China. An evaluation index system has been developed for assessing the coupling coordination (CC) of the ETE system based on the context of 12 provinces and cities in western China. Entropy and spatial autocorrelation methods have been used to evaluate the comprehensive benefit value and influencing factors of the ETE systems in the region. The spatial Durbin model has been used to assess empirical data from 2010–2019. The coupling coordination degree (CCD) of each subsystem was used as the main explanatory variable to quantify the spatial spillover effect. The research results show that the ETE system of the provinces and cities in western China have a strong correlation. The three subsystems interact, restrict, and promote each other, operating together in contradictory unity. The degree of coupling and coordination of the ETE systems are mainly stable but fluctuate from the time perspective. From the spatial perspective, the level of coupling and coordination have clear spatial correlation and spatial dependence. However, since 2013, the spatial dependence has significantly weakened, indicating that the level of coupling coordination is moving towards a balanced direction. The ETE subsystems not only promote the improvement of the coupling coordination of the region itself, but also optimize the coupling coordination of neighboring areas. The promotion effect of each subsystem on the degree of self-coupling and coordination is greater than the promotion effect on neighboring areas.
Sustainability Analysis and Environmental Decision-Making Using Simulation, Optimization, and Computational Analytics
Authors: Kozlova Mariia , Yeomans Julian Scott
Published: January 2022

In practice, environmental analytics involves an integration of science, methods, and techniques involving a combination of computers, computational intelligence, information technology, mathematical modelling, and system science to address “real-world” environmental and sustainability problems [...]
The Concept of Integration between State and Provincial Sea Boundaries in Indonesia
Authors: Djunarsjah Eka , Putra Andika Permadi , Kusumadewi Difa , Yudistira Kevin , Julian Miga Magenika
Published: January 2022

The clarity of marine spatial status requires a coherency between the state (territorial) sea boundary and the provincial sea boundary because both have the same sea width of 12 nautical miles. However, the two sea boundaries use different references; the state sea boundary refers to the low-water line, whereas the provincial sea boundary refers to the high-water line, so that the outer limits of the two sea boundaries differ. From the applicable provisions, the provincial sea management area may not exceed the territorial sea area. The method used to detect the overlap between the state sea and the provincial sea is the overlay method. By taking the study area of the waters of the province of East Nusa Tenggara, a difference is produced between the position of the outermost boundary of the territorial sea of the state of Indonesia and the sea area of East Nusa Tenggara province. The results of this study show differences in the boundaries of the state and provincial seas. To prevent potential issues, in the process of implementing Marine Spatial Planning (MSP) and/or Integrated Coastal Zone Management (ICZM), there must be a clarity and a uniform reference between the state and provincial sea boundaries; otherwise, it will create an overlap of authorities, between the state (central) and the provincial level. This incoherency shows that this practice has not fulfilled one of the requirements in implementing ICZM, which requires the integration of all aspects, including political boundaries.
A Numerical Methodology to Predict the Maximum Power Output of Tidal Stream Arrays
Authors: Radfar Soheil , Panahi Roozbeh , Majidi Nezhad Meysam , Neshat Mehdi
Published: January 2022

Due to its high level of consistency and predictability, tidal stream energy is a feasible and promising type of renewable energy for future development and investment. Numerical modeling of tidal farms is a challenging task. Many studies have shown the applicability of the Blade Element Momentum (BEM) method for modeling the interaction of turbines in tidal arrays. Apart from its well-known capabilities, there is a scarcity of research using BEM to model tidal stream energy farms. Therefore, the main aim of this numerical study is to simulate a full-scale array in a real geographical position. A fundamental linear relationship to estimate the power capture of full-scale turbines using available kinetic energy flux is being explored. For this purpose, a real site for developing a tidal farm on the southern coasts of Iran is selected. Then, a numerical methodology is validated and calibrated for the established farm by analyzing an array of turbines. A linear equation is proposed to calculate the tidal power of marine hydrokinetic turbines. The results indicate that the difference between the predicted value and the actual power does not exceed 6%.