bluuebunny/crossref_metadata_2025 huggingface dataset:
A Classification of Tidal Flat Wetland Vegetation Combining Phenological Features with Google Earth Engine
Authors: Wu Nan , Shi Runhe , Zhuo Wei , Zhang Chao , Zhou Bingchan , Xia Zilong , Tao Zhu , Gao Wei , Tian Bo
Published: January 2021

The composition and distribution of wetland vegetation is critical for ecosystem diversity and sustainable development. However, tidal flat wetland environments are complex, and obtaining effective satellite imagery is challenging due to the high cloud coverage. Moreover, it is difficult to acquire phenological feature data and extract species-level wetland vegetation information by using only spectral data or individual images. To solve these limitations, statistical features, temporal features, and phenological features of multiple Landsat 8 time-series images obtained via the Google Earth Engine (GEE) platform were compared to extract species-level wetland vegetation information from Chongming Island, China. The results indicated that (1) a harmonic model obtained the phenological characteristics of wetland vegetation better than the raw vegetation index (VI) and the Savitzky–Golay (SG) smoothing method; (2) classification based on the combination of the three features provided the highest overall accuracy (85.54%), and the phenological features (represented by the amplitude and phase of the harmonic model) had the greatest impact on the classification; and (3) the classification result from the senescence period was more accurate than that from the green period, but the annual mapping result on all seasons was the most accurate. The method described in this study can be applied to overcome the impacts of the complex environment in tidal flat wetlands and to effectively classify wetland vegetation species using GEE. This study could be used as a reference for the analysis of the phenological features of other areas or vegetation types.
Acoustic Mapping of Submerged Stone Age Sites—A HALD Approach
Authors: Grøn Ole , Boldreel Lars Ole , Smith Morgan F. , Joy Shawn , Tayong Boumda Rostand , Mäder Andreas , Bleicher Niels , Madsen Bo , Cvikel Deborah , Nilsson Björn , Sjöström Arne , Galili Ehud , Nørmark Egon , Hu Changqing , Ren Qunyan , Blondel Philippe , Gao Xing , Stråkendal Petra , Dell’Anno Antonio
Published: January 2021

Acoustic response from lithics knapped by humans has been demonstrated to facilitate effective detection of submerged Stone Age sites exposed on the seafloor or embedded within its sediments. This phenomenon has recently enabled the non-invasive detection of several hitherto unknown submerged Stone Age sites, as well as the registration of acoustic responses from already known localities. Investigation of the acoustic-response characteristics of knapped lithics, which appear not to be replicated in naturally cracked lithic pieces (geofacts), is presently on-going through laboratory experiments and finite element (FE) modelling of high-resolution 3D-scanned pieces. Experimental work is also being undertaken, employing chirp sub-bottom systems (reflection seismic) on known sites in marine areas and inland water bodies. Fieldwork has already yielded positive results in this initial stage of development of an optimised Human-Altered Lithic Detection (HALD) method for mapping submerged Stone Age sites. This paper reviews the maritime archaeological perspectives of this promising approach, which potentially facilitates new and improved practice, summarizes existing data, and reports on the present state of development. Its focus is not reflection seismics as such, but a useful resonance phenomenon induced by the use of high-resolution reflection seismic systems.
NOAA-20 and S-NPP VIIRS Thermal Emissive Bands On-Orbit Calibration Algorithm Update and Long-Term Performance Inter-Comparison
Authors: Wang Wenhui , Cao Changyong
Published: January 2021

The Visible Infrared Imaging Radiometer Suite (VIIRS) on board the National Oceanic and Atmospheric Administration-20 (NOAA-20) and the Suomi National Polar-orbiting Partnership Program (S-NPP) satellites were launched in late 2017 and 2011, respectively. This paper presents a recent update in the VIIRS thermal emissive bands (TEB) on-orbit calibration algorithm and inter-compares long-term instrument and TEB sensor data records (SDR) performances of the two VIIRS, to support user communities. The VIIRS TEB calibration algorithm was improved to mitigate calibration biases during the blackbody warm-up/cool-down (WUCD) events. Four WUCD bias correction methods were implemented in the NOAA operational processing in 2019: (1) the Nominal-F method, (2) the WUCD-C method, (3) the Ltrace method, and (4) the Ltrace-2 method. Our evaluation results indicate that the on-orbit performances of the two VIIRS instruments have been generally stable and comparable with each other, except that NOAA-20 VIIRS blackbody and instrument temperatures are lower than those of the S-NPP VIIRS. The degradations in the S-NPP TEB detector responsivities remain small after 9 years on-orbit. NOAA-20 detector responsivities have been generally stable after the longwave infrared degradation during its early mission was resolved by the mid-mission outgassing. NOAA-20 and S-NPP VIIRS TEB SDRs agree with co-located Cross-track Infrared Sounder observations, with daily averaged biases within 0.1 K at nadir. After the implementation of operational WUCD bias correction, residual TEB WUCD biases are similar for NOAA-20 and S-NPP, with daily averaged biases ~0.01 K in all bands.
Driven by Vision: Learning Navigation by Visual Localization and Trajectory Prediction
Authors: Leordeanu Marius , Paraicu Iulia
Published: January 2021

When driving, people make decisions based on current traffic as well as their desired route. They have a mental map of known routes and are often able to navigate without needing directions. Current published self-driving models improve their performances when using additional GPS information. Here we aim to push forward self-driving research and perform route planning even in the complete absence of GPS at inference time. Our system learns to predict in real-time vehicle’s current location and future trajectory, on a known map, given only the raw video stream and the final destination. Trajectories consist of instant steering commands that depend on present traffic, as well as longer-term navigation decisions towards a specific destination. Along with our novel proposed approach to localization and navigation from visual data, we also introduce a novel large dataset in an urban environment, which consists of video and GPS streams collected with a smartphone while driving. The GPS is automatically processed to obtain supervision labels and to create an analytical representation of the traversed map. In tests, our solution outperforms published state of the art methods on visual localization and steering and provides reliable navigation assistance between any two known locations. We also show that our system can adapt to short and long-term changes in weather conditions or the structure of the urban environment. We make the entire dataset and the code publicly available.
An Examination of the Strava Usage Rate—A Parameter to Estimate Average Annual Daily Bicycle Volumes on Rural Roadways
Authors: Camacho-Torregrosa Francisco Javier , Llopis-Castelló David , López-Maldonado Griselda , García Alfredo
Published: January 2021

In Spain, a new challenge is emerging due to the increase of many recreational bicyclists on two-lane rural roads. These facilities have been mainly designed for motorized vehicles, so the coexistence of cyclists and drivers produces an impact, in terms of road safety and operation. In order to analyze the occurrence of crashes and enhance safety for bicycling, it is crucial to know the cycling volume. Standard procedures recommend using data from permanent stations and temporary short counts, but bicycle volumes are rarely monitored in rural roads. However, bicyclists tend to track their leisure and exercise activities with fitness apps that use GPS. In this context, this research aims at analyzing the daily and seasonal variability of the Strava Usage Rate (SUR), defined as the proportion of bicyclists using the Strava app along a certain segment on rural highways, to estimate the Annual Average Daily Bicycle (AADB) volume on rural roads. The findings of this study offer possible solutions to policy makers in terms of planning and design of the cycling network. Moreover, the use of crowdsourced data from the Strava app will potentially save costs to public agencies, since public data could replace costly counting campaigns.
Gender Matters: A Gender Analysis of Healthcare Workers’ Experiences during the First COVID-19 Pandemic Peak in England
Authors: Regenold Nina , Vindrola-Padros Cecilia
Published: January 2021

The coronavirus (COVID-19) arrived in the United Kingdom (UK) in February 2020, placing an unprecedented burden on the National Health Service (NHS). Literature from past epidemics and the COVID-19 pandemic underscores the importance of using a gender lens when considering policy, experiences, and impacts of the disease. Researchers are increasingly examining the experiences of healthcare workers (HCWs), yet there is a dearth of research considering how gender shapes HCWs’ personal experiences. As the majority of HCWs in the UK and worldwide are women, research that investigates gender and focuses on women’s experiences is urgently needed. We conducted an analysis of 41 qualitative interviews with HCWs in the British NHS during the first peak of the COVID-19 pandemic in the Spring of 2020. Our findings demonstrate that gender is significant when understanding the experiences of HCWs during COVID-19 as it illuminates ingrained inequalities and asymmetrical power relations, gendered organizational structures and norms, and individual gendered bodies that interact to shape experiences of healthcare workers. These findings point to important steps to improve gender equality, the wellbeing of healthcare workers, and the overall strength of the NHS.
Civic Ecology Uplifts Low-Income Communities, Improves Ecosystem Services and Well-Being, and Strengthens Social Cohesion
Authors: Davids Rashieda , Rouget Mathieu , Burger Margaret , Mahood Kirsten , Ditlhale Ntswaki , Slotow Rob
Published: January 2021

Ecosystem services enhance well-being and the livelihoods of disadvantaged communities. Civic ecology can enhance social–ecological systems; however, their contributions to ecosystem services are rarely measured. We analysed the outcomes of civic ecology interventions undertaken in Durban, South Africa, as part of the Wise Wayz Water Care programme (the case study). Using mixed methods (household and beneficiary (community members implementing interventions) surveys, interviews, field observations, and workshops), we identified ecosystem service use and values, as well as the benefits of six interventions (solid waste management and removal from aquatic and terrestrial areas, recycling, invasive alien plant control, river water quality monitoring, vegetable production, and community engagement). Ecosystem services were widely used for agriculture, subsistence, and cultural uses. River water was used for crop irrigation, livestock, and recreation. Respondents noted numerous improvements to natural habitats: decrease in invasive alien plants, less pollution, improved condition of wetlands, and increased production of diverse vegetables. Improved habitats were linked to enhanced ecosystem services: clean water, agricultural production, harvesting of wood, and increased cultural and spiritual activities. Key social benefits were increased social cohesion, education, and new business opportunities. We highlight that local communities can leverage natural capital for well-being and encourage policy support of civic ecology initiatives.
Simulation Study of Dynamic Bus Lane Concept
Authors: Szarata Mateusz , Olszewski Piotr , Bichajło Lesław
Published: January 2021

Not many publications are available on using microsimulation models to analyze the feasibility of implementing the dynamic bus lane (DBL) concept. The paper presents the methodology and calibration process used for DBL modeling. For the selected four sites in Rzeszów (Poland), three options were analyzed: no bus lane, standard exclusive bus lane (XBL), and dynamic bus lane. The analyses were carried out using PTV Vissim software with an additional logic script to control the DBL activation. Simulation model parameters were calibrated using a genetic algorithm. The final assessment of individual options was based on the weighted average travel time for all transport modes. The results show that the dynamic bus lane could bring the same benefits to public transport and cause only a slight increase in travel times in private transport compared to XBL. The XBL solution, depending on the site, led to increasing the average travel time in private transport by 12% to 25%, while the dynamic bus lane increased by 1% to 12%. Weighted average travel time per person is proposed as the overall indicator of efficiency. Preliminary analyses show that the bus volume, bus occupancy, routing, and traffic conditions will affect the efficiency of the new solution.
The Relationship between Coordination Degree of the Water–Energy–Food System and Regional Economic Development
Authors: Xu Shasha , He Weijun , Yuan Liang , Degefu Dagmawi Mulugeta , Yang Yang , Li Hua
Published: January 2021

The sustainable development of the water–energy–food (WEF) system has gained global attention as a result of limited land resources, inadequate energy supply and growing water stress. Coordination degree is an important indicator to measure the sustainable development of the WEF system. Improving the coordination degree contributes to the sustainable development of the WEF system and affects regional economic development. The extended Cobb–Douglas function is applied to examine the relationship between coordination degree of the WEF system and regional economic development in 31 provinces of China during the period of 2007–2018. By using the system generalized method of moments (GMM) estimation, empirical results indicate that in the regions with low coordination degree, improved coordination degree of the WEF system will hinder regional economic growth. In the regions with high coordination degree, it will promote regional economic growth. The results indicate that there is a lag period for the influence of improved coordination degree on regional economic growth. When making resources management policies, shortening the lag period is conducive to achieving sustainable development and promoting regional economic development. Governments of various regions should formulate different resource management policies based on the conditions of each region and the different relationships between coordination degree of the WEF system and regional economic development.
Robo-Advising Risk Profiling through Content Analysis for Sustainable Development in the Hong Kong Financial Market
Authors: So Mike K. P.
Published: January 2021

Nowadays, we mainly depend on financial consultants or advisors to conduct risk assessments for individual investors before providing them with any investment advice or recommendations. Individual investors should understand the risk level of their investment choices and their investment decisions should match their risk profile. This process is usually conducted in face-to-face meetings. However, during the recent coronavirus disease 2019 pandemic, which has seriously impacted daily life with social distancing, in order to maintain sustainability, contact-free advising, such as robo-advising, becomes more important. The aim of this paper was to assess customers’ risk in regards to investment and identify important risk factors needed to profile individual risk preferences, in order to prepare for robo-advising. Inductive content analysis is applied to classify 180 questions from 20 risk assessment questionnaires, sourced from banks and investment service providers, into different types. Then, the number of types is reduced by collapsing similar areas into broader higher order categories (the important risk factors). This paper also makes specific recommendations for the implementation of risk profiling in robo-advising.
Joint Innovation Investment and Pricing Decisions in Retail Supply Chains with Customer Value
Authors: Qu Jiali , Hu Benyong , Meng Chao
Published: January 2021

In the retail industry, customer value has become the key to maintaining competitive advantages. In the era of new retail, customer value is not only affected by the product price, but it is also closely related to innovations, such as value-added services and unique business models. In this paper, we study the joint innovation investment and pricing decisions in a retailer–supplier supply chain based on revenue sharing contracts and customer value. We first find that, in the non-cooperative game, equilibrium only exists in the supplier Stackelberg game. However, revenue sharing contracts cannot coordinate the supply chain in the non-cooperative game. By considering supply chain members’ bargaining power, we find that there exists a unique equilibrium for the Nash bargaining product. In addition, revenue sharing contracts can coordinate the supply chain and achieve the optimal consumer surplus. When the supply chain is coordinated, supply chain profit is allocated to the supply chain members based on their bargaining powers.
Construction of Meteorological Simulation Knowledge Graph Based on Deep Learning Method
Authors: Xiao Ziwei , Zhang Chunxiao
Published: January 2021

With the maturity of meteorological simulation technology, the research literature in this field is undergoing a rapid increase. The published literature can provide useful guidance for current research to get scientific results; however, it tends to be rather time consuming to obtain exact knowledge from massive literature, and it is necessary to transform the literature into structured knowledge to meet the efficient management, sharing, and reuse of meteorological simulation knowledge. In this paper, methods of meteorological simulation knowledge extraction and knowledge graph construction are proposed. A deep learning model based on bilateral long short-term memory-conditional random field (BiLSTM-CRF) is used to extract the meteorological simulation knowledge from the massive literature. Then, the Neo4j graph database is used to construct the meteorological simulation knowledge graph. Based on the meteorological simulation knowledge graph, it can realize the structured storage and integration of meteorological simulation knowledge, which can bridge the gap in the transformation of massive literature to sharable and reusable knowledge. Furthermore, the meteorological simulation knowledge graph can be used as an expert resource and contribute to sustainable guidance and optimization for meteorological simulation research.
Self-Determined Motivation Mediates the Association between Self-Reported Availability of Green Spaces for Exercising and Physical Activity: An Explorative Study
Authors: Baceviciene Migle , Jankauskiene Rasa
Published: January 2021

The aim of the study was to test the associations between the self-reported access to exercise in green spaces (GS) and moderate-to-vigorous physical activity (MVPA) testing the mediating role of the motivation. Based on self-determination theory (SDT), we expected that self-determined motivation will mediate the associations between the self-reported availability of GS for exercising (GSE) and MVPA with the most self-determined exercise regulation forms (identified and intrinsic motivation) demonstrating the strongest positive associations between the variables. Method: The sample consisted of 2154 participants (74.7% women). The ages ranged from 18 to 79 years, with a mean age of 32.6 (SD = 12.2) years. Participants completed the Behavior Regulation in Exercise Questionnaire-2, the measures of self-reported distance to residential GS (RGS), availability of the GS for exercising (GSE), and physical activity (PA). Logistic regression and path analysis were used to test the associations between study variables. Results: Higher reported distance to RGS was associated with lower reported availability of GSE, but not PA. Availability of GSE was directly associated with more frequent MVPA. More autonomous forms of exercise behavior regulation (intrinsic and identified regulations) mediated the associations between self-reported availability of GSE and MVPA. Internal and identified exercise regulations were directly associated with more frequent MVPA. Conclusions: The results of the present study support the main tenets of SDT suggesting that self-determined behavioral exercise regulation is an important mediator between the self-reported availability of GSE and general MVPA. Practical implications of these findings are discussed herein.
Non-Financial Environmental Responsibility Information, Information Environment, and Credit Ratings: Evidence from South Korea
Authors: Yoo Youngtae
Published: January 2021

The purpose of this study was to analyze which dimensions of non-financial environmental responsibility information are more reflected in credit ratings. The non-financial environmental responsibility information used in this study was environmental strategy, environmental organization, environmental management, environmental performance, and stakeholder communication. Based on 1085 companies listed on the Korean capital market from 2013 to 2018, this study reports that the more companies engage in environmental responsibility activities, the better their credit ratings are. Specifically, it found that companies with higher environmental performance and stakeholder communication activities received better credit ratings, while higher environmental management and environmental strategy scores had a relatively weak influence. This indicates that among the corporate environmental responsibilities, the more activities requiring relatively little discretion from managers are performed, the more the reputation capital that is accumulated through corporate environmental responsibility (CER) activities, which leads to higher credit ratings. These associations were found to be strengthened in an information environment where there is a higher degree of information asymmetry and the lifecycle of a firm is at a maturity stage.
Earth Science Education as a Key Component of Education for Sustainability
Authors: Vasconcelos Clara , Orion Nir
Published: January 2021

Environmental insight has emerged as a new scientific concept which incorporates the understanding that the Earth is made up of interworking subsystems and the acceptance that humans must act in harmony with the Earth’s dynamic balanced cycle. This Earth system competency represents the highest level of knowing and understanding in the geosciences community. Humans have an important role as participative beings in the Earth’s subsystems, and they must therefore acknowledge that life on Earth depends on a geoethically responsible management of the Earth system. Yet, the world is far from achieving sustainable development, making the role of the Earth science education in promoting education for sustainability even more relevant. The Earth system approach to education is designed to be an effective learning tool for the development of the innovative concept of environmental insight. Through a holistic view of planet Earth, students realize that humans have the ability to enjoy a sustainable life on our planet while minimising detrimental environmental impacts. There is growing evidence that citizens value science and need to be informed about Earth system problems such as climate change, resource efficiency, pandemics, sustainable use of water resources, and how to protect bio-geodiversity. By moving away from both traditional practices and traditional perceptions, environmental insight and geoethics will lead towards an education for sustainability that provides the citizens of Earth with the tools they need to address the full complexity of its urgent environmental concerns.
A Permissioned Blockchain-Based Energy Management System for Renewable Energy Microgrids
Authors: Wang Longze , Jiao Shucen , Xie Yu , Mubaarak Saif , Zhang Delong , Liu Jinxin , Jiang Siyu , Zhang Yan , Li Meicheng
Published: January 2021

Peer-to-peer (P2P) energy management is one of the most viable solutions to incentivize prosumers in renewable energy microgrids. As the application of blockchain expends from the finance field to energy field, blockchain technology provides a new opportunity for distributed energy systems. However, a distributed energy system based on blockchains allows any node in the whole network to read data. In many application scenarios, user privacy cannot be effectively protected, and there is a security problem that the attack cannot be traced. In this paper, we propose an energy management mode based on a permissioned blockchain for a renewable energy microgrid. The novel permissioned blockchain framework uses entity mapping with a unique identity for each enterprise, natural person, or device, in order to avoid ineligible participants to join the microgrid. Each peer entity keeps the transaction information index of the whole network, but only keeps its own specific transaction information, so they can retrieve the transaction information of other peer entities but cannot obtain the details without permission. Moreover, this model could avoid communication delays and promote plug-and-play due to the distributed nature of the permissioned blockchain. The performance of the proposed method is evaluated with a demonstration program which is designed and deployed on a Hyperledger Fabric permissioned blockchain. Simulation results show the feasibility of the proposed method, and the model is conducive to the protection privacy and P2P energy management for decentralized energy systems.
Multi-Objective Optimization of a Microgrid Considering the Uncertainty of Supply and Demand
Authors: Geng Shiping , Wu Gengqi , Tan Caixia , Niu Dongxiao , Guo Xiaopeng
Published: January 2021

Starting from the perspective of the uncertainty of supply and demand, using the Copula function and fuzzy numbers a scenario generation method, considering the uncertainty of scenery, and a random fuzzy model of energy demand uncertainty are proposed. Then, through the energy flow direction and the energy supply, production, conversion, storage, and demand, a multi-objective model considering the economic and environmental protection of a park is constructed. Here, the park refers to a microgrid that gathers distributed energy such as wind and photovoltaics and has requirements for cooling, heat, and electricity at the same time. Next, combining the constraints of each link, the particle swarm algorithm is used to solve the model. Finally, an example is analyzed in a certain park. The results of the example show that, on the one hand, the proposed scenario generation method and fuzzy number method can reduce the uncertainty of supply and demand, effectively fitting the wind and photovoltaic output and various energy demands. On the other hand, considering the economy and environmental protection of the park at the same time, the configuration of energy storage equipment can not only improve the economy of the park, but also promote the consumption of renewable energy.
Students’ Innovation in Education for Sustainable Development—A Longitudinal Study on Interdisciplinary vs. Monodisciplinary Learning
Authors: Braßler Mirjam , Schultze Martin
Published: January 2021

Innovative ideas are essential to sustainable development. Students’ innovative potential in higher education for sustainable development (HESD) has so far been neglected. Innovation is often associated with an interdisciplinary approach. However, the results of research on diversity and its role in innovation are inconsistent. The present study takes a longitudinal approach to investigating student teams in project-based learning courses in HESD in Germany. This study examines how innovation develops in interdisciplinary student teams in contrast to monodisciplinary student teams. The results of the latent change approach from a sample of 69 student teams indicate significant changes in students’ innovation over time. Monodisciplinary student teams outperform interdisciplinary student teams in idea promotion (convincing potential allies) at the beginning, whereas interdisciplinary student teams outperform monodisciplinary student teams in idea generation (production of novel and useful ideas) in the midterm. There is no difference in the long term. The results indicate that interdisciplinary student teams have an advantage in the generation of novel ideas but need time to leverage their access to different discipline-based knowledge. We discuss practical implications for the design of interdisciplinary learning with strategies to support students in the formation phase in project-based learning in HESD.
Selection of Optimized Retaining Wall Technique Using Self-Organizing Maps
Authors: Kim Young-Su , Park U-Yeol , Whang Seoung-Wook , Ahn Dong-Joon , Kim Sangyong
Published: January 2021

Construction projects in urban areas tend to be associated with high-rise buildings and are of very large-scales; hence, the importance of a project’s underground construction work is significant. In this study, a rational model based on machine learning (ML) was developed. ML algorithms are programs that can learn from data and improve from experience without human intervention. In this study, self-organizing maps (SOMs) were utilized. An SOM is an alternative to existing ML methods and involves a subjective decision-making process because a developed model is used for data training to classify and effectively recognize patterns embedded in the input data space. In addition, unlike existing methods, the SOM can easily create a feature map by mapping multidimensional data to simple two-dimensional data. The objective of this study is to develop an SOM model as a decision-making approach for selecting a retaining wall technique. N-fold cross-validation was adopted to validate the accuracy of the SOM model and evaluate its reliability. The findings are useful for decision-making in selecting a retaining wall method, as demonstrated in this study. The maximum accuracy of the SOM was 81.5%, and the average accuracy was 79.8%.
Niche-Driven Socio-Environmental Linkages and Regional Sustainable Development
Authors: Liu Dandan , Huang Anmin , Yang Dewei , Lin Jianyi , Liu Jiahui
Published: January 2021

The changes in niche roles and functions caused by competition for survival resources have implications in various domains, with natural science and social science standing out. Currently, expanding the ecological niche concept and its practical interpretation in the fields of social ecology, geography and sustainable science is becoming a crucial challenge. This paper is based on niche theory to observe niche evolution and resulting socio-ecological effects of 1186 towns in 19 prefecture cities in Yangtze River delta. The results indicate that: Towns around the Taihu Lake displayed obvious spatial agglomeration, which was leading the development of the entire region. The town niche shows obvious characteristics of north-south differences and hierarchy distribution. The niche coordination degree of Jiangsu Province was higher than that of Zhejiang Province. The higher the subsystem coordination degree, the better the town development. Towns with poor ecological conditions are often subject to competition, while towns with better ecological conditions often benefit from cooperative development. The niche separation and collaboration could enhance niche competition of towns and cities in the region. The proposed framework can facilitate interdisciplinary exchanges among geography, sociology, landscape ecology and regional planning and provide insights for understanding regional co-opetition relationship and regional sustainable development.
Towards Effective Safety Cost Budgeting for Apartment Construction: A Case Study of Occupational Safety and Health Expenses in South Korea
Authors: Yang Kanghyeok , Kim Kiltae , Go Seongseok
Published: January 2021

The construction industry has experienced a lot of occupational accidents, and construction work is considered one of the most dangerous occupations. In order to reduce the number of occupational injuries from construction, the South Korean government legislated the occupational safety and health expense law, requiring companies to reserve a reasonable budget for safety management activities when budgeting for construction projects. However, safety budgets have not been spent based on the risk of accidents, and a large amount of the safety budget is spent either in the beginning or late stages of construction projects. Various accident risk factors, such as activity types, previous accident records, and the number of workers on a construction site, need to be considered when determining the safety budget. To solve such problems, this study investigated the expenditure trends of occupational safety and health expenses for 10 apartment construction projects in South Korea. This study also proposed an accident risk index that can be incorporated with the project costs, schedule, the number of workers, and historical accident records when budgeting for the safety costs. The results from the case study illustrate the limitations of the current planning strategy for safety expenditures and demonstrate the need for effective safety budgeting for accident prevention. The proposed safety cost expenditure guideline helps safety practitioners when budgeting for the occupational safety and health expenses while considering accident risk and the characteristics of safety cost expenditures in practice. The outcome of this research will contribute to the development of regulations for the budgeting of safety costs and help to prevent occupational injuries by providing a reasonable budget for safety management activities in an apartment construction project.
Research on Runoff Simulations Using Deep-Learning Methods
Authors: Liu Yan , Zhang Ting , Kang Aiqing , Li Jianzhu , Lei Xiaohui
Published: January 2021

Runoff simulations are of great significance to the planning management of water resources. Here, we discussed the influence of the model component, model parameters and model input on runoff modeling, taking Hanjiang River Basin as the research area. Convolution kernel and attention mechanism were introduced into an LSTM network, and a new data-driven model Conv-TALSTM was developed. The model parameters were analyzed based on the Conv-TALSTM, and the results suggested that the optimal parameters were greatly affected by the correlation between the input data and output data. We compared the performance of Conv-TALSTM and variant models (TALSTM, Conv-LSTM, LSTM), and found that Conv-TALSTM can reproduce high flow more accurately. Moreover, the results were comparable when the model was trained with meteorological or hydrological variables, whereas the peak values with hydrological data were closer to the observations. When the two datasets were combined, the performance of the model was better. Additionally, Conv-TALSTM was also compared with an ANN (artificial neural network) and Wetspa (a distributed model for Water and Energy Transfer between Soil, Plants and Atmosphere), which verified the advantages of Conv-TALSTM in peak simulations. This study provides a direction for improving the accuracy, simplifying model structure and shortening calculation time in runoff simulations.
Synthesis and Characterisation of a Boron-Rich Symmetric Triazine Bearing a Hypoxia-Targeting Nitroimidazole Moiety
Authors: Bünning Tobias Hartwig , Panza Luigi , Azab Abdel Kareem , Muz Barbara , Fallarini Silvia , Imperio Daniela
Published: January 2021

Boron Neutron Capture Therapy (BNCT) is a binary therapy that promises to be suitable in treating many non-curable cancers. To that, the discovery of new boron compounds able to accumulate selectively in the tumour tissue is still required. Hypoxia, a deficiency of oxygen in tumor tissue, is a great challenge in the conventional treatment of cancer, because hypoxic areas are resistant to conventional anticancer treatments. 2-Nitroimidazole derivatives are known to be hypoxia markers due to their enrichment by bioreduction in hypoxic cells. In the present work, 2-nitroimidazole was chosen as the starting point for the synthesis of a new boron-containing compound based on a 1,3,5-triazine skeleton. Two o-carborane moieties were inserted to achieve a high ratio of boron on the molecular weight, exploiting a short PEG spacer to enhance the polarity of the compound and outdistance the active part from the core. The compound showed no toxicity on normal human primary fibroblasts, while it showed noteworthy toxicity in multiple myeloma cells together with a consistent intracellular boron accumulation.
The Bipartite and Tripartite Entanglement in PT-Symmetric System
Authors: Le Duc Vinh , Nowotarski Mateusz , Kalaga Joanna K.
Published: January 2021

We consider a PT-symmetric system that involves three optical resonant elements coupled together. We investigate the quantum correlations between subsystems by calculating bipartite and tripartite entanglement. We show that when PT-symmetry is maintained, the correlations between subsystems strongly depend on the parameters describing the interaction between them and characterizing the gain and loss of energy in the system’s active and passive elements. We estimate the range of interaction parameter values for which the strongest bipartite and tripartite entanglement can be produced. Additionally, we show that the discussed system can be a source of stable entangled states.
Occurrence, Impact on Agriculture, Human Health, and Management Strategies of Zearalenone in Food and Feed: A Review
Authors: Mahato Dipendra Kumar , Devi Sheetal , Pandhi Shikha , Sharma Bharti , Maurya Kamlesh Kumar , Mishra Sadhna , Dhawan Kajal , Selvakumar Raman , Kamle Madhu , Mishra Awdhesh Kumar , Kumar Pradeep
Published: January 2021

Mycotoxins represent an assorted range of secondary fungal metabolites that extensively occur in numerous food and feed ingredients at any stage during pre- and post-harvest conditions. Zearalenone (ZEN), a mycotoxin categorized as a xenoestrogen poses structural similarity with natural estrogens that enables its binding to the estrogen receptors leading to hormonal misbalance and numerous reproductive diseases. ZEN is mainly found in crops belonging to temperate regions, primarily in maize and other cereal crops that form an important part of various food and feed. Because of the significant adverse effects of ZEN on both human and animal, there is an alarming need for effective detection, mitigation, and management strategies to assure food and feed safety and security. The present review tends to provide an updated overview of the different sources, occurrence and biosynthetic mechanisms of ZEN in various food and feed. It also provides insight to its harmful effects on human health and agriculture along with its effective detection, management, and control strategies.
The Cost of Lost Productivity Due to Premature Chagas Disease-Related Mortality: Lessons from Colombia (2010–2017)
Authors: Olivera Mario J. , Palencia-Sánchez Francisco , Riaño-Casallas Martha
Published: January 2021

Background: Economic burden due to premature mortality has a negative impact not only in health systems but also in wider society. The aim of this study was to estimate the potential years of work lost (PYWL) and the productivity costs of premature mortality due to Chagas disease in Colombia from 2010 to 2017. Methods: National data on mortality (underlying cause of death) were obtained from the National Administrative Department of Statistics in Colombia between 2010 and 2017, in which Chagas disease was mentioned on the death certificate as an underlying or associated cause of death. Chagas disease as a cause of death corresponded to category B57 (Chagas disease) including all subcategories (B57.0 to B57.5), according to the Tenth Revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10). The electronic database contains the number of deaths from all causes by sex and 5-year age group. Economic data, including wages, unemployment rates, labor force participation rates and gross domestic product, were derived from the Bank of the Republic of Colombia. The human capital approach was applied to estimate both the PYWL and present value of lifetime income lost due to premature deaths. A discount rate of 3% was applied and results are presented in 2017 US dollars (USD). Results: There were 1261 deaths in the study, of which, 60% occurred in males. Premature deaths from Chagas resulted in 48,621 PYWL and a cost of USD 29 million in the present value of lifetime income forgone. Conclusion: The productivity costs of premature mortality due to Chagas disease are significant. These results provide an economic measure of the Chagas burden which can help policy makers allocate resources to continue with early detection programs.
The Local Co-Working Hub: A Merging Solution
Authors: Motamed Bahareh , Shirvanimoghaddam Kamyar
Published: January 2021

The coronavirus pandemic has brought unprecedented challenges and has changed society; some of these changes seem temporary, and others seem permanent. The uncertainty of the duration of this pandemic has introduced changes without the knowledge of how permanent they are, and has raised awareness regarding a need for a shift to a new normal. This new normal will affect different aspects of our life routines and activities, such as travel behaviour, personal hygiene, socializing, and our working environment. In the wake of the global pandemic, which has been followed by lockdowns, curfews, social distancing, and working from home, the future of the office has turned into an open question, as COVID has changed our expectation of how, where, and when people can do their jobs. Big companies like Twitter and Facebook have announced that they are allowing employees to permanently work from home; however, some industry leaders are using the work-from-home experience to reimagine the role of the office in the future. What will the future office look like, and what can we expect of the workplace environment? In this paper, we propose a third solution, which is the merging of the current scenario of the classic office and working from home, which is entitled the ‘local co-working hub’. By studying the challenges and opportunities of each of the current approaches, the potential of the local co-working hub is highlighted.
Anthropogenic Infection of Cats during the 2020 COVID-19 Pandemic
Authors: Hosie Margaret J. , Hofmann-Lehmann Regina , Hartmann Katrin , Egberink Herman , Truyen Uwe , Addie Diane D. , Belák Sándor , Boucraut-Baralon Corine , Frymus Tadeusz , Lloret Albert , Lutz Hans , Marsilio Fulvio , Pennisi Maria Grazia , Tasker Séverine , Thiry Etienne , Möstl Karin
Published: January 2021

COVID-19 is a severe acute respiratory syndrome (SARS) caused by a new coronavirus (CoV), SARS-CoV-2, which is closely related to SARS-CoV that jumped the animal–human species barrier and caused a disease outbreak in 2003. SARS-CoV-2 is a betacoronavirus that was first described in 2019, unrelated to the commonly occurring feline coronavirus (FCoV) that is an alphacoronavirus associated with feline infectious peritonitis (FIP). SARS-CoV-2 is highly contagious and has spread globally within a few months, resulting in the current pandemic. Felids have been shown to be susceptible to SARS-CoV-2 infection. Particularly in the Western world, many people live in very close contact with their pet cats, and natural infections of cats in COVID-19-positive households have been described in several countries. In this review, the European Advisory Board on Cat Diseases (ABCD), a scientifically independent board of experts in feline medicine from 11 European Countries, discusses the current status of SARS-CoV infections in cats. The review examines the host range of SARS-CoV-2 and human-to-animal transmissions, including infections in domestic and non-domestic felids, as well as mink-to-human/-cat transmission. It summarises current data on SARS-CoV-2 prevalence in domestic cats and the results of experimental infections of cats and provides expert opinions on the clinical relevance and prevention of SARS-CoV-2 infection in cats.
COVID-19 Infection and Previous BCG Vaccination Coverage in the Ecuadorian Population
Authors: Garzon-Chavez Daniel , Rivas-Condo Jackson , Echeverria Adriana , Mozo Jhoanna , Quentin Emmanuelle , Reyes Jorge , Teran Enrique
Published: January 2021

The Bacillus Calmette–Guérin (BCG) is a well-known vaccine with almost a century of use, with the apparent capability to improve cytokine production and epigenetics changes that could develop a better response to pathogens. It has been postulated that BCG protection against SARS-CoV-2 has a potential role in the pandemic, through the presence of homologous amino acid sequences. To identify a possible link between BCG vaccination coverage and COVID-19 cases, we used official epidemic data and Ecuadorian Ministry of Health and Pan American Health Organization vaccination information. BCG information before 1979 was available only at a national level. Therefore, projections based on the last 20 years were performed, to compare by specific geographic units. We used a Mann–Kendall test to identify BCG coverage variations, and mapping was conducted with a free geographic information system (QGIS). Nine provinces where BCG vaccine coverage was lower than 74.25% show a significant statistical association (χ2 Pearson’s = 4.800, df = 1, p = 0.028), with a higher prevalence of cases for people aged 50 to 64 years than in younger people aged 20 to 49 years. Despite the availability of BCG vaccination data and the mathematical models needed to compare these data with COVID-19 cases, our results show that, in geographic areas where BCG coverage was low, 50% presented a high prevalence of COVID-19 cases that were young; thus, low-coverage years were more affected.
Current Advances of Nitric Oxide in Cancer and Anticancer Therapeutics
Authors: Mintz Joel , Vedenko Anastasia , Rosete Omar , Shah Khushi , Goldstein Gabriella , Hare Joshua M. , Ramasamy Ranjith , Arora Himanshu
Published: January 2021

Nitric oxide (NO) is a short-lived, ubiquitous signaling molecule that affects numerous critical functions in the body. There are markedly conflicting findings in the literature regarding the bimodal effects of NO in carcinogenesis and tumor progression, which has important consequences for treatment. Several preclinical and clinical studies have suggested that both pro- and antitumorigenic effects of NO depend on multiple aspects, including, but not limited to, tissue of generation, the level of production, the oxidative/reductive (redox) environment in which this radical is generated, the presence or absence of NO transduction elements, and the tumor microenvironment. Generally, there are four major categories of NO-based anticancer therapies: NO donors, phosphodiesterase inhibitors (PDE-i), soluble guanylyl cyclase (sGC) activators, and immunomodulators. Of these, NO donors are well studied, well characterized, and also the most promising. In this study, we review the current knowledge in this area, with an emphasis placed on the role of NO as an anticancer therapy and dysregulated molecular interactions during the evolution of cancer, highlighting the strategies that may aid in the targeting of cancer.