bluuebunny/crossref_metadata_2025 huggingface dataset:
Clothing Insulation Rate and Metabolic Rate Estimation for Individual Thermal Comfort Assessment in Real Life
Authors: Liu Jinsong , Foged Isak Worre , Moeslund Thomas B.
Published: January 2022

Satisfactory indoor thermal environments can improve working efficiencies of office staff. To build such satisfactory indoor microclimates, individual thermal comfort assessment is important, for which personal clothing insulation rate (Icl) and metabolic rate (M) need to be estimated dynamically. Therefore, this paper proposes a vision-based method. Specifically, a human tracking-by-detection framework is implemented to acquire each person’s clothing status (short-sleeved, long-sleeved), key posture (sitting, standing), and bounding box information simultaneously. The clothing status together with a key body points detector locate the person’s skin region and clothes region, allowing the measurement of skin temperature (Ts) and clothes temperature (Tc), and realizing the calculation of Icl from Ts and Tc. The key posture and the bounding box change across time can category the person’s activity intensity into a corresponding level, from which the M value is estimated. Moreover, we have collected a multi-person thermal dataset to evaluate the method. The tracking-by-detection framework achieves a mAP50 (Mean Average Precision) rate of 89.1% and a MOTA (Multiple Object Tracking Accuracy) rate of 99.5%. The Icl estimation module gets an accuracy of 96.2% in locating skin and clothes. The M estimation module obtains a classification rate of 95.6% in categorizing activity level. All of these prove the usefulness of the proposed method in a multi-person scenario of real-life applications.
Behavioral Data Analysis of Robot-Assisted Autism Spectrum Disorder (ASD) Interventions Based on Lattice Computing Techniques
Authors: Lytridis Chris , Kaburlasos Vassilis G. , Bazinas Christos , Papakostas George A. , Sidiropoulos George , Nikopoulou Vasiliki-Aliki , Holeva Vasiliki , Papadopoulou Maria , Evangeliou Athanasios
Published: January 2022

Recent years have witnessed the proliferation of social robots in various domains including special education. However, specialized tools to assess their effect on human behavior, as well as to holistically design social robot applications, are often missing. In response, this work presents novel tools for analysis of human behavior data regarding robot-assisted special education. The objectives include, first, an understanding of human behavior in response to an array of robot actions and, second, an improved intervention design based on suitable mathematical instruments. To achieve these objectives, Lattice Computing (LC) models in conjunction with machine learning techniques have been employed to construct a representation of a child’s behavioral state. Using data collected during real-world robot-assisted interventions with children diagnosed with Autism Spectrum Disorder (ASD) and the aforementioned behavioral state representation, time series of behavioral states were constructed. The paper then investigates the causal relationship between specific robot actions and the observed child behavioral states in order to determine how the different interaction modalities of the social robot affected the child’s behavior.
‘Health in All Policies’ and the Urge for Coordination: The Work of Public Health Coordinators and Their Impact and Influence in Local Public Health Policies: A Cross-Sectional Study
Authors: Karlsen Tor-Ivar , Kiland Charlotte , Kvåle Gro , Torjesen Dag Olaf
Published: January 2022

Building heavily on the Health in All Policies (HiAP) approach, Norway implemented the Public Health Act in 2012 to reduce social inequalities in health. Local public health coordinators (PHCs) at municipal levels were seen as tools to provide local intersectoral public health work. In this study, we examine factors related to intersectoral agency and if intersectoral work is understood as relevant to securing social justice in local policy outcomes. A national web-based survey in 2019 of all Norwegian PHCs (n = 428) was conducted with a response rate of 60%. Data were analysed through multiple linear regression, hierarchical regression modelling and structural equation modelling. Neither factors relating to community contexts nor individual characteristics were associated with intersectoral agency. Organisational factors, especially position size, being organised at the top level and having a job description, were significantly associated with perceptions of intersectoral agency. PHCs seeing themselves as intersectoral agents also found themselves able to affect annual budgets and policy outcomes. We conclude that municipal PHC positions can be important HiAP tools in local public health policies. However, organisational factors affect how PHCs perceive their influence and role in the municipal organisation and thereby their possibilities to influence local policymaking through intersectoral agency.
Landscape Changes in Protected Areas in Poland
Authors: Zbierska Anna
Published: January 2022

Land-Use Cover Changes (LUCCs) are one of the main problems for the preservation of landscapes and natural biodiversity. Protected Areas (PAs) do not escape this threat. Poland is among the European leaders in terms of the variety of landscapes and the share of an area designated as a protected area. However, as many as 78% of the habitats have poor or bad conservation status based on EEA reports. This article analyzes the LUCCs between 2000 and 2018 in various types of the Polish legal forms of nature protection areas and the European Natura 2000 network within the country. The research material was: the data of Corine Land Cover (CLC), the Central Register of Nature Protection Forms, and high-resolution layers, such as HRL and orthophotos. The results were compiled according to the CLC class and forms of protection. The matrix of transformations showed that the most frequently transformed CLC class was 312 (coniferous forest). It was transformed into class 324 (transitional woodland shrubs). The changes in PAs were usually smaller than in the surrounding buffer zones, which may indicate their effectiveness. The exception was the areas of the European Natura 2000 network. The scale of land-cover flows (LCFs) changed within particular forms of protected areas, though afforestation and deforestation predominating in all area types. National reserves and parks were the most stable in terms of land cover structures. However, human settlements increased around the protected areas, potentially increasing threats to their ecological integrity.
Assessing the Vulnerability of Rural Households to Floods at Pol-e Dokhtar Region in Iran
Authors: Ahmadi Somayeh , Ghanbari Movahed Rezvan , Gholamrezaie Saeed , Rahimian Mehdi
Published: January 2022

The agricultural sector in rural areas is seriously affected by climate change, affecting agricultural production and farming communities. This paper investigates rural households’ vulnerability to floods in the seven agricultural-based regions of Pol-e Dokhtar, south of Lorestan Province, Iran. The primary data for the vulnerability indicators were collected from 322 households. Three main components of vulnerability, including exposure, sensitivity, and adaptive capacity, were measured using the obtained data. The weighting of indicators was done by the MSF method and using MATLAB software. The results showed that the social and economic characteristics of households affect their vulnerability to floods. The Jayder, Mamolan, and Afrineh regions, which were more exposed to floods, had less capacity for adaptation. The results showed that the most vulnerable communities could be described by characteristics such as low levels of agricultural insurance, limited access to credit, low levels of income diversification, high levels of unemployment, low levels of social capital, higher dependency ratios, and poor infrastructure. This research showed that diversified livelihoods have a significant effect on reducing farmers’ sensitivity to floods. The study proposes policy implications to increase resilience and reduce farmers’ vulnerability to floods. The government and other development partners should prioritize the most vulnerable areas by improving their access to finance and providing the technical assistance required for increasing their coping capacity.
The Relationship between Climate Change, Variability, and Food Security: Understanding the Impacts and Building Resilient Food Systems in West Pokot County, Kenya
Authors: Obwocha Everlyne B. , Ramisch Joshua J. , Duguma Lalisa , Orero Levi
Published: January 2022

This study integrated local and scientific knowledge to assess the impacts of climate change and variability on food security in West Pokot County, Kenya from 1980–2012. It characterized rainfall and temperature from 1980–2011 and the phenology of agricultural vegetation, assessed land use and land cover (LULC) changes, and surveyed local knowledge and perceptions of the relationships between climate change and variability, land use decisions, and food (in)security. The 124 respondents were aware of long-term changes in their environment, with 68% strongly believing that climate has become more variable. The majority of the respondents (88%) reported declining rainfall and rising temperatures, with respondents in the lowland areas reporting shortened growing seasons that affected food production. Meteorological data for 1980–2011 confirmed high inter-annual rainfall variability around the mean value of 973.4 mm/yr but with no notable trend. Temperature data showed an increasing trend between 1980 and 2012 with lowlands and highlands showing changes of +1.25 °C and +1.29 °C, respectively. Land use and land cover changes between 1984 and 2010 showed cropland area increased by +4176% (+33,138 ha), while grassland and forest areas declined by –49% (–96,988 ha) and –38% (–65,010 ha), respectively. These area changes illustrate human-mediated responses to the rainfall variability, such as increased stocking after good rainfall years and crop area expansion. The mean Normalized Difference Vegetation Index (NDVI) values ranged from 0.36–0.54 within a year, peaking in May and September. For weather-related planning, respondents relied on radio (64%) and traditional forecasters (26%) as predominant information sources. Supporting continuous climate change monitoring, intensified early warning systems, and disseminating relevant information to farmers could help farmers adopt appropriate adaptation strategies.
The Effect of Bacteria on Early Age Strength of CEM I and CEM II Cementitious Composites
Authors: Hui Tsz Ying , Skevi Lorena , Reeksting Bianca , Gebhard Susanne , Paine Kevin
Published: January 2022

Despite being associated with lower carbon emissions, CEM II cementitious materials exhibit reduced early age strength compared to that of CEM I. Several studies have demonstrated early age strength improvements by incorporating bacterial cells in concrete. In this study, live vegetative bacteria and dead bacteria killed in two different ways were used to explore whether changes in strength are related to the bacteria’s viability or their surface morphology. Compressive and flexural strength tests were performed at mortars with and without bacteria for both CEM I and CEM II cement. Their microstructure, porosity and mineralogy were also examined. No net strength gain was recorded for either CEM I or CEM II bacterial mortars compared to non-bacterial controls, although changes in the porosity were reported. It is proposed that two phenomena, one causing strength-reduction and one causing strength-gain, took place in the bacterial specimens, simultaneously. It is suggested that each phenomenon is dependent on the alkalinity of the cement matrix, which differs between CEM I and CEM II mortars at early age. Nevertheless, in neither case could it be recommended that the addition of bacteria is an effective way of increasing the early age strength of mortars.
Determining the Level of Market Concentration in the Construction Sector—Case of Application of the HHI Index
Authors: Peleckis Kęstutis
Published: January 2022

Background—competitive conditions are often distorted in the construction sector, therefore this affects the market position of all participants. This paper seeks to find the tools for properly assessment of participants by Herfindahl-Hirschmann index (HHI) and to identify what parameters have the greatest impact in the competitiveness of the construction sector. Methods: in this article the DEMATEL method was used whereas tool for assessing the balance of market concentration as it may help to determine factor with the greatest influence on a firm’s HHI. Results in this work showed how different parameters affect each other and their impact on a value of a firms’s HHI. When the parameters are determined, they can be useful for assesment of mergers their influence on the HHI and alteration of the market’s power balance. Conclusions—The calculation of the HHI by using the DEMATEL method allowed to check the empirical implementation check of the multicriteria assessment method, on the market power of business entities, operating in the distorted market conditions of the construction sector.
Does Supply Chain Concentration Affect the Performance of Corporate Environmental Responsibility? The Moderating Effect of Technology Uncertainty
Authors: Liu Tingli , Gao Hongqiao
Published: January 2022

With the development of society and the improvement of environmental consciousness, the performance of corporate environmental responsibility (CER) has elicited increasing attention in recent years. In previous studies, the exploration of the antecedents of CER is far less evident than the exploration of its results, and only few studies have investigated what determines CER engagement from the perspective of supply chain concentration (SCC). Using data from 2413 firms in China from 2013 to 2019, our study uses the fixed effect model and performs multiple robustness tests to examine the impact of SCC on the fulfillment of CER, its transmission mechanism, and the moderating role of technology uncertainty (TU). Empirical results show that SCC has a pivotal negative impact on CER performance, wherein both supplier concentration (SUP) and customer concentration (CUS) are detrimental to CER performance. Further mechanism analysis shows that such negative effect can be explained by the adverse effect of SCC on the operating cash flow (OCF), in which OCF has a partial mediating effect. Moreover, the negative impact of SCC on CER performance is more significant when the uncertainty of firms’ technological environment is stronger. Our study opens the transmission “black box” between SCC and CER performance and incorporates the behaviors of firms, inter-firm relationships, and environmental factors into the same research framework, and provides a theoretical guidance for management practices.
Evaluation of Green Logistics Efficiency in Jiangxi Province Based on Three-Stage DEA from the Perspective of High-Quality Development
Authors: Gan Weihua , Yao Wenpei , Huang Shuying
Published: January 2022

The high-quality development of the logistics industry plays an important role in high-quality economic development. Green logistics is attracting more attention, owing to environmental concern. Based on the five concepts of “innovation, coordination, green, openness and sharing” of high-quality economic development, the input–output indicators of green logistics efficiency (GLE) have been designed. The correlation between the green logistics input and output indicators have been analyzed by Pearson, and the green logistics efficiency of 11 cities in Jiangxi Province has been calculated by three-stage DEA. The evolutionary characteristics of the high-quality development of green logistics efficiency in Jiangxi Province were analyzed and evaluated. The conclusions were achieved as follows: (1) Nanchang, Xinyu and Ganzhou city are at the forefront of efficiency, and are less affected by environmental factors. The logistics efficiency of other cities is obviously affected by environmental factors. (2) The comprehensive technical efficiency (TE) of green logistics in Jiangxi Province is strongly influenced by scale efficiency (SE). The poor scale efficiency reduces the comprehensive technical efficiency of green logistics. (3) There is a positive correlation between high-quality economic development and logistics efficiency. In these cities of Jiangxi province (Nanchang, Ganzhou, Jiujiang, etc.) the share of total economy and green logistics efficiency is high. This study proves that Jiangxi province is moving towards high-quality economic development due to good environmental protection. (4) In 2017, Jiangxi Province was recognized as one of the national ecological civilization pilot region by the State Council. Green logistics efficiency in Jiangxi Province showed an inflection point in 2017, indicating that the green concept is becoming more and more popular. From the government to enterprises, the province has achieved initial results in promoting the transformation of the economic development mode. It aims to provide reference for the high-quality development of other provinces.
Trends of Studies on Controlled Halogenated Gases under International Conventions during 1999–2018 Using Bibliometric Analysis: A Global Perspective
Authors: Wang Jing , Fu Hui-Zhen , Xu Jiaqi , Wu Danqi , Yang Yue , Zhu Xiaoyu , Wu Jing
Published: January 2022

A lot of research on international convention-controlled halogenated gases (CHGs) has been carried out. However, few bibliometric analyses and literature reviews exist in this field. Based on 734 articles extracted from the Science Citation Index (SCI) Expanded database of the Web of Science, we provided the visualisation for the performance of contributors and trends in research content by using VOSviewer and Science of Science (Sci2). The results showed that the United States was the most productive country, followed by the United Kingdom and China. The National Oceanic and Atmospheric Administration had the largest number of publications, followed by the Massachusetts Institute of Technology (MIT) and the University of Bristol. In terms of disciplines, environmental science and meteorological and atmospheric science have contributed the most. By using cluster analysis of all keywords, four key research topics of CHGs were identified and reviewed: (1) emissions calculation, (2) physicochemical analysis of halocarbons, (3) evaluation of replacements, and (4) environmental impact. The change in research substances is closely related to the phase-out schedule of the Montreal Protocol. In terms of environmental impact, global warming has always been the most important research hotspot, whereas research on ozone-depleting substances and biological toxicity shows a gradually rising trend.
Does Entrepreneur Moral Reflectiveness Matter? Pursing Low-Carbon Emission Behavior among SMEs through the Relationship between Environmental Factors, Entrepreneur Personal Concept, and Outcome Expectations
Authors: Cai Li , Kwasi Sampene Agyemang , Khan Adnan , Oteng-Agyeman Fredrick , Tu Wenjuan , Robert Brenya
Published: January 2022

The intensity and severe impact of carbon emissions on the environment has been witnessed globally. This study aims to unravel how environmental factors, personal factors, and entrepreneur outcome expectations affect entrepreneur low-carbon emission behavior (LCB) through the lens of social cognitive theory (SCT). To achieve the aims of this study, we gathered data from 1015 entrepreneurs and small, medium-sized enterprises (SMEs) in the Jiangsu province of China to analyze the predictors of entrepreneur low-carbon behavior. The proposed relationships were tested using the partial least square structural equation modelling (PLS-SEM) technique. The findings from the study indicate that environmental factors (i.e., climate change (CC), public media (PM), and corporate social responsibility (CSR) have a significant and positive relationship with entrepreneur LCB. Moreover, entrepreneur green production self-efficacy (GPS) is positively associated with entrepreneur LCB. The findings further revealed that entrepreneur personal concepts such as entrepreneur self-monitoring (SM), entrepreneur self-esteem (SE), and entrepreneur self-Preference (SP) significantly and completely affect entrepreneur GPS. Likewise, entrepreneur moral reflectiveness (EMR) substantially moderates the relationship between entrepreneur green production outcome expectation and LCB. This study concludes with recommendations for researchers interested in enhancing knowledge in this field. In summation, this study shows that a behavioral science viewpoint is critical for improving knowledge of low-carbon environment, CC drivers, mitigation strategies, and sustainable transition to our complex environment.
Cultural Heritage Storytelling, Engagement and Management in the Era of Big Data and the Semantic Web
Authors: Dimoulas Charalampos A.
Published: January 2022

Cultural heritage (CH) refers to a highly multidisciplinary research and application field, intending to collect, archive, and disseminate the traditions, monuments/artworks, and overall civilization legacies that have been preserved throughout the years of humankind [...]
Systematic Mapping of Long-Term Urban Challenges
Authors: Soe Ralf-Martin , Sarv Lill , Gasco-Hernandez Mila
Published: January 2022

This paper investigates on long-term challenges faced by local governments. Using empirical evidence from Estonia, this paper aims to help fill a research gap in that there is a lack of a systematic approach on how to analyze common urban challenges via direct involvement of local governments. In terms of conceptual framework, a unique combination of public value theory and mission-oriented innovation is proposed. The data is collected via questionnaire, interviews and workshops involving up to 35 local governments. It is important that instead of current problems relating only to one city, this study focuses on finding shared, long-term challenges and, from them, generates a list of top 10 challenges. This provides valuable input to initiating new research and innovation projects in the key, smart city domains (e.g., energy, mobility, built environment, governance and data).
Optimization of Humanitarian Aid Distribution in Case of an Earthquake and Tsunami in the City of Iquique, Chile
Authors: Ilabaca Antonia , Paredes-Belmar Germán , Alvarez Pamela P.
Published: January 2022

In this paper, we introduce, model, and solve a clustered resource allocation and routing problem for humanitarian aid distribution in the event of an earthquake and subsequent tsunami. First, for the preparedness stage, we build a set of clusters to identify, classify, sort, focus, and prioritize the aid distribution. The clusters are built with k-means method and a modified version of the capacitated p-median model. Each cluster has a set of beneficiaries and candidate delivery aid points. Second, vehicle routes are strategically determined to visit the clusters for the response stage. A mixed integer linear programming model is presented to determine efficient vehicle routes, minimizing the aid distribution times. A vulnerability index is added to our model to prioritize aid distribution. A case study is solved for the city of Iquique, Chile.
Cognitive Functioning Mediates the Association of Cognitive Reserve with Health-Related Quality of Life
Authors: Ihle Andreas , Gouveia Élvio R. , Gouveia Bruna R. , Marques Adilson , Marconcin Priscila , de Maio Nascimento Marcelo , Jurema Jefferson , Tinôco Maria A. , Kliegel Matthias
Published: January 2022

We investigated whether the relations of the cognitive reserve markers education and cognitive level of work to the physical and the mental component of health-related quality of life (HRQoL) were mediated via cognitive functioning in a large sample of 701 older adults (mean age = 70.36 years, SD = 6.87). HRQoL was measured with the 12-item Short-Form Health Survey. To measure cognitive functioning, we used the COGTEL, which is a cognitive test battery assessing prospective memory, verbal short-term memory, verbal long-term memory, working memory, verbal fluency, and inductive reasoning, combined into a composite score. Individuals reported information on their education and their main profession during their working life. Mediation analyses showed that better cognitive functioning mediated the association of higher values in the cognitive reserve markers (longer education and a high cognitive level of work) with higher HRQoL. In conclusion, the present study suggests that the sustainability of cognitive functioning in old age with the help of cognitive reserve is fundamental for the sustainability of quality of life, presumably particularly for the mental HRQoL component.
Measuring and Assessing Performance of Mobile Broadband Networks and Future 5G Trends
Authors: El-Saleh Ayman A. , Alhammadi Abdulraqeb , Shayea Ibraheem , Alsharif Nizar , Alzahrani Nouf M. , Khalaf Osamah Ibrahim , Aldhyani Theyazn H. H.
Published: January 2022

Mobile broadband (MBB) is one of the critical goals in fifth-generation (5G) networks due to rising data demand. MBB provides very high-speed internet access with seamless connections. Existing MBB, including third-generation (3G) and fourth-generation (4G) networks, also requires monitoring to ensure good network performance. Thus, performing analysis of existing MBB assists mobile network operators (MNOs) in further improving their MBB networks’ capabilities to meet user satisfaction. In this paper, we analyzed and evaluated the multidimensional performance of existing MBB in Oman. Drive test measurements were carried out in four urban and suburban cities: Muscat, Ibra, Sur and Bahla. This study aimed to analyze and understand the MBB performance, but it did not benchmark the performance of MNOs. The data measurements were collected through drive tests from two MNOs supporting 3G and 4G technologies: Omantel and Ooredoo. Several performance metrics were measured during the drive tests, such as signal quality, throughput (downlink and unlink), ping and handover. The measurement results demonstrate that 4G technologies were the dominant networks in most of the tested cities during the drive test. The average downlink and uplink data rates were 18 Mbps and 13 Mbps, respectively, whereas the average ping and pong loss were 53 ms and 0.9, respectively, for all MNOs.
Challenges and Benefits of Sustainable Industry 4.0 for Operations and Supply Chain Management—A Framework Headed toward the 2030 Agenda
Authors: Caiado Rodrigo Goyannes Gusmão , Scavarda Luiz Felipe , Azevedo Bruno Duarte , de Mattos Nascimento Daniel Luiz , Quelhas Osvaldo Luiz Gonçalves
Published: January 2022

Currently, Industry 4.0 (I4.0) represents a worldwide movement to improve the productivity and efficiency of operations and supply chain management (OSCM), which requires rethinking and changing the mindset of the way in which products are manufactured and services are used. Although the concept of I4.0 was not popularised in the ratification of the 2030 Agenda, I4.0 is a watershed in the implementation of the Sustainable Development Goals (SDGs). It can serve as a platform for the alignment of the SDGs with the ongoing digital transformation. However, the challenges to the integration of I4.0 and sustainability in OSCM, and the benefits of this integration, in line with the SDGs, remain unclear. Moreover, there is a lack of a standard structure that establishes links between these challenges and benefits to strategically guide organisations on the journey towards a sustainable OSCM 4.0 (S-OSCM4.0) aligned with the SDGs. Thus, the purpose of this paper is to propose an S-OSCM4.0 framework for organisations to attain sustainability and I4.0 in OSCM, in line with the 2030 Agenda. Based on a systematic literature review, 48 articles that complied with the selection criteria were analysed using content analysis. The research findings were synthesised into taxonomies of challenges and benefits, and these categories were linked into a step-by-step framework, following an inductive approach. The proposed framework represents a novel artefact that integrates taxonomies in order to holistically achieve sustainable digitalisation for people, prosperity and planet benefits, and sheds light on the potential contributions of S-OSCM4.0 to the SDGs.
Spatio-Temporal Impact of Global Migration on Carbon Transfers Based on Complex Network and Stepwise Regression Analysis
Authors: Gao Cuixia , Zhong Ying , Mensah Isaac Adjei , Tao Simin , He Yuyang
Published: January 2022

Considering the advancement of economic globalization, the reasons for migration together with the lifestyles of migrants will change the use of energy, environment of origin and destination. This study therefore explores the patterns of global trade-induced carbon emission transfers using “center-of-gravity” and complex network analysis. We further investigate the determinants of carbon transfers by integrating the impact of population migration through the STIRPAT framework for 64 countries over the period 2005–2015 using the stepwise regression approach. Our results unveil that higher levels of migration flow induce higher carbon flow. Specifically, every 1% increase in migration, triggers carbon transfers to increase within the range of 0.118–0.124%. The rising impact of migration cannot be ignored, even though the coefficients were not so high. Besides, for both male and female migrants, their impact on carbon transfers generated by the intermediate products were higher than those generated by the final products. However, the influence is more obvious in male migrants. With the aim of dividing the sample of countries into three income groups, the results generally show that the impacts of migration vary across levels of income. Therefore, the environmental pressure caused by immigration should be considered by destination countries in the formulating of migration policies. On the other hand, origin countries should take some responsibility for carbon emissions according to their development characteristics.
Human Health and Ecosystem Quality Benefits with Life Cycle Assessment Due to Fungicides Elimination in Agriculture
Authors: Tsalidis Georgios Archimidis
Published: January 2022

Industrial agriculture results in environmental burdens due to the overuse of fertilizers and pesticides. Fungicides is a class of pesticides whose application contributes (among others) to human toxicity and ecotoxicity. The European Union aims to increase organic agriculture. For this reason, this work aims to analyze climate change, freshwater ecotoxicity, terrestrial ecotoxicity, human toxicity, (terrestrial) acidification, and freshwater eutrophication impacts of fungicides and calculate expected benefits to human health (per European citizen) and ecosystem quality (terrestrial) with life cycle assessment (LCA) during crop production. The Scopus database was searched for LCA studies that considered the application of fungicides to specific crops. The analysis shows how many systemic and contact fungicides were considered by LCA studies and what was the applied dosage. Furthermore, it shows that fungicides highly contribute to freshwater ecotoxicity, terrestrial ecotoxicity, human toxicity, and freshwater eutrophication for fruits and vegetables, but to a low extent compared to all considered environmental impacts in the case of cereals and rapeseed. Expected benefits to human health and ecosystem quality after fungicides elimination are greater for fruits and vegetables, ranging between 0 to 47 min per European citizen in a year and 0 to 90 species per year, respectively.
Determining the Optimal Density of Phoebe bournei Plantations Based on Dynamic Programming under Close-to-Nature Management Measures
Authors: Wang Danmei , Li Jiping , Tang Tao
Published: January 2022

Close-to-nature management (CTNM) is the most promising option for plantation silviculture and has received widespread attention in recent years. Stand density is a key variable in CTNM, as it directly influences growth and yield. Research for the optimal density that maximizes the total harvest has been ongoing. In this paper, a dynamic programming model was applied to the CTNM of Phoebe bournei plantations for the first time to solve the problem of stand density and target tree density control. This paper took Phoebe bournei plantations in Jindong Forest Farm of Hunan Province as the research object. Based on the data of seven consecutive years from 2015 to 2021, Richard’s growth equation was used to fit the height growth equation and basal area growth equation of Phoebe bournei. Stand growth was divided into five development stages according to the forest growth process and characteristics. Stand density and basal area were selected as two-dimensional state variables, and the maximum total harvest in the entire stand growth process was used as the objective function to establish a dynamic programming model. The optimal stand density and target tree density at each growth stage of the stand under three different site conditions were determined. According to the results obtained, the objective forest shape was designed for the stand under three types of site conditions, which can provide a theoretical basis for the CTNM of Phoebe bournei plantations to make the stand achieve the maximum harvest.
Artificial Intelligence in the Water–Energy–Food Model: A Holistic Approach towards Sustainable Development Goals
Authors: D’Amore Gabriella , Di Vaio Assunta , Balsalobre-Lorente Daniel , Boccia Flavio
Published: January 2022

This study aims to analyze the role of artificial intelligence (AI) in the Water–Energy–Food (WEF) nexus under the lens of institutional, stakeholder, and innovation theories. Specifically, this study focuses on AI as the technology adopted by companies to promote Sustainable Development Goals (SDGs). A structured literature review has been conducted on 94 articles published from 1990 to 2021 in ISI Web of Science, Scopus, and Google Scholar. This study develops an in-depth review of the literature on the main articles arguing about these issues. The findings highlight the increasing relevance of AI in the water, energy, and food industries individually considered, but the study of AI as a connector between water, energy, and food to achieve SDGs is still under investigation. Research on AI for WEF nexus management has adopted mostly a technical perspective, neglecting the relevance of management tools and the business model concept. Most of the articles did not adopt a specific theoretical lens, but scholars recognize the need to adopt a multi-stakeholder approach and the important role played by AI and other digital technologies to address the WEF nexus challenge. This study proposes an integrated approach for managing the nexus through AI technologies to meet sustainable and responsible business models. The gap between research and policy making could be filled by combining scientific data and policy needs with inclusive tools that are technically viable for sustainable resource utilization.
Modeling a Practical Dual-Fuel Gas Turbine Power Generation System Using Dynamic Neural Network and Deep Learning
Authors: Alsarayreh Mohammad , Mohamed Omar , Matar Mustafa
Published: January 2022

Accurate simulations of gas turbines’ dynamic performance are essential for improvements in their practical performance and advancements in sustainable energy production. This paper presents models with extremely accurate simulations for a real dual-fuel gas turbine using two state-of-the-art techniques of neural networks: the dynamic neural network and deep neural network. The dynamic neural network has been realized via a nonlinear autoregressive network with exogenous inputs (NARX) artificial neural network (ANN), and the deep neural network has been based on a convolutional neural network (CNN). The outputs selected for simulations are: the output power, the exhausted temperature and the turbine speed or system frequency, whereas the inputs are the natural gas (NG) control valve, the pilot gas control valve and the compressor variables. The data-sets have been prepared in three essential formats for the training and validation of the networks: normalized data, standardized data and SI units’ data. Rigorous effort has been carried out for wide-range trials regarding tweaking the network structures and hyper-parameters, which leads to highly satisfactory results for both models (overall, the minimum recorded MSE in the training of the MISO NARX was 6.2626 × 10−9 and the maximum MSE that was recorded for the MISO CNN was 2.9210 × 10−4, for more than 15 h of GT operation). The results have shown a comparable satisfactory performance for both dynamic NARX ANN and the CNN with a slight superiority of NARX. It can be newly argued that the dynamic ANN is better than the deep learning ANN for the time-based performance simulation of gas turbines (GTs).
Increasing the Sustainability of the Hybrid Mold Technique through Combined Insert Polymeric Material and Additive Manufacturing Method Design
Authors: Fernandez Ellen , Edeleva Mariya , Fiorio Rudinei , Cardon Ludwig , D’hooge Dagmar R.
Published: January 2022

To reduce plastic waste generation from failed product batches during industrial injection molding, the sustainable production of representative prototypes is essential. Interesting is the more recent hybrid injection molding (HM) technique, in which a polymeric mold core and cavity are produced via additive manufacturing (AM) and are both placed in an overall metal housing for the final polymeric part production. HM requires less material waste and energy compared to conventional subtractive injection molding, at least if its process parameters are properly tuned. In the present work, several options of AM insert production are compared with full metal/steel mold inserts, selecting isotactic polypropylene as the injected polymer. These options are defined by both the AM method and the material considered and are evaluated with respect to the insert mechanical and conductive properties, also considering Moldex3D simulations. These simulations are conducted with inputted measured temperature-dependent AM material properties to identify in silico indicators for wear and to perform cooling cycle time minimization. It is shown that PolyJetted Digital acrylonitrile-butadiene-styrene (ABS) polymer and Multi jet fusioned (MJF) polyamide 11 (PA11) are the most promising. The former option has the best durability for thinner injection molded parts, and the latter option the best cooling cycle times at any thickness, highlighting the need to further develop AM options.
A Review on the CO2 Emission Reduction Scheme and Countermeasures in China’s Energy and Power Industry under the Background of Carbon Peak
Authors: Zheng Bin , Wang Sheng , Xu Jingxin
Published: January 2022

To reach the peak of carbon emission in China, the energy and power industry has the most arduous task and the heaviest responsibility. It should not only ensure efficient economic development, but also complete the arduous task of energy conservation and emission reduction. It is the main force in helping reach the peak of carbon emission. Taking the achievement of carbon peak in China’s power industry as the research object, this paper utilizes time series analyses to establish CO2 emission prediction models for China and its power industry under two scenarios: with and without a carbon peak target. The paper analyzes the current status of achieving carbon peak in China’s power industry and puts a forward CO2 emission reduction scheme for China and its power industry in the future. On this basis, countermeasures for China’s power industry to deal with carbon peak are explored.
A Hybrid ANP Method for Evaluation of Government Data Sustainability
Authors: Xu Jicang , Li Linlin , Ren Ming
Published: January 2022

The evaluation of government data sustainability is a multicriteria decision making problem. The analytic network process (ANP) is among the most popular methods in determining the weights of criteria, and its limitation is the un-convergence problem. This paper proposes a hybrid ANP (H-ANP) method, which aims to improve the ANP by combining the weights obtained from the analytic hierarchy process (AHP). The proposed method is proved to be convergent since the network of the H-ANP is strongly connected. According to the simulation experiments, H-ANP is more robust than ANP under different settings of parameters. It also shows a higher Kendall cor-relationship and lower MSE with respect to AHP, compared with the existing method (e.g., the averagely connected ANP method). An empirical example is also provided, which uses H-ANP to evaluate the government data sustainability of a city.
Blockchain Interoperability: Towards a Sustainable Payment System
Authors: Mohanty Debasis , Anand Divya , Aljahdali Hani Moaiteq , Villar Santos Gracia
Published: January 2022

The highly fragmented blockchain and cryptocurrency ecosystem necessitates interoperability mechanisms as a requirement for blockchain-technology acceptance. The immediate implication of interchain interoperability is automatic swapping between cryptocurrencies. We performed a systematic review of the existing literature on Blockchain interoperability and atomic cross-chain transactions. We investigated different blockchain interoperability approaches, including industrial solutions, categorized them and identified the key mechanisms used, and list several example projects for each category. We focused on the atomic transactions between blockchain, a process also known as atomic swap. Furthermore, we studied recent implementations along with architectural approaches for atomic swap and deduced research issues and challenges in cross-chain interoperability and atomic swap. Atomic swap can instantly transfer tokens and significantly reduce the associated costs without using any centralized authority, and thus facilitates the development of a sustainable payment system for wider financial inclusion.
Improved Path Planning for Indoor Patrol Robot Based on Deep Reinforcement Learning
Authors: Zheng Jianfeng , Mao Shuren , Wu Zhenyu , Kong Pengcheng , Qiang Hao
Published: January 2022

To solve the problems of poor exploration ability and convergence speed of traditional deep reinforcement learning in the navigation task of the patrol robot under indoor specified routes, an improved deep reinforcement learning algorithm based on Pan/Tilt/Zoom(PTZ) image information was proposed in this paper. The obtained symmetric image information and target position information are taken as the input of the network, the speed of the robot is taken as the output of the next action, and the circular route with boundary is taken as the test. The improved reward and punishment function is designed to improve the convergence speed of the algorithm and optimize the path so that the robot can plan a safer path while avoiding obstacles first. Compared with Deep Q Network(DQN) algorithm, the convergence speed after improvement is shortened by about 40%, and the loss function is more stable.
Harmonic Aggregation Operator with Trapezoidal Picture Fuzzy Numbers and Its Application in a Multiple-Attribute Decision-Making Problem
Authors: Shit Chittaranjan , Ghorai Ganesh , Xin Qin , Gulzar Muhammad
Published: January 2022

Picture fuzzy sets (PFSs) can be used to handle real-life problems with uncertainty and vagueness more effectively than intuitionistic fuzzy sets (IFSs). In the process of information aggregation, many aggregation operators under PFSs are used by different authors in different fields. In this article, a multi-attribute decision-making (MADM) problem is introduced utilizing harmonic mean aggregation operators with trapezoidal fuzzy number (TrFN) under picture fuzzy information. Three harmonic mean operators are developed namely trapezoidal picture fuzzy weighted harmonic mean (TrPFWHM) operator, trapezoidal picture fuzzy order weighted harmonic mean (TrPFOWHM) operator and trapezoidal picture fuzzy hybrid harmonic mean (TrPFHHM) operator. The related properties about these operators are also studied. At last, an MADM problem is considered to interrelate among these operators. Furthermore, a numerical instance is considered to explain the productivity of the proposed operators.
Worst-Case Higher Moment Coherent Risk Based on Optimal Transport with Application to Distributionally Robust Portfolio Optimization
Authors: Liu Wei , Liu Yang
Published: January 2022

The tail risk management is of great significance in the investment process. As an extension of the asymmetric tail risk measure—Conditional Value at Risk (CVaR), higher moment coherent risk (HMCR) is compatible with the higher moment information (skewness and kurtosis) of probability distribution of the asset returns as well as capturing distributional asymmetry. In order to overcome the difficulties arising from the asymmetry and ambiguity of the underlying distribution, we propose the Wasserstein distributionally robust mean-HMCR portfolio optimization model based on the kernel smoothing method and optimal transport, where the ambiguity set is defined as a Wasserstein “ball” around the empirical distribution in the weighted kernel density estimation (KDE) distribution function family. Leveraging Fenchel’s duality theory, we obtain the computationally tractable DCP (difference-of-convex programming) reformulations and show that the ambiguity version preserves the asymmetry of the HMCR measure. Primary empirical test results for portfolio selection demonstrate the efficiency of the proposed model.
Experimental Analysis of a Fuzzy Scheme against a Robust Controller for a Proton Exchange Membrane Fuel Cell System
Authors: Napole Cristian , Derbeli Mohamed , Barambones Oscar
Published: January 2022

Proton exchange membrane fuel cells (PEMFC) are capable of transforming chemical energy into electrical energy with zero emissions. Therefore, these devices had been a point of attention for the scientific community as to provide another solution to renewable sources of energy. Since the PEMFC is commonly driven with a power converter, a controller has to be implemented to supply a convenient voltage. This is an important task as it allows the system to be driven at an operative point, which can be related to the maximum power or an user desired spot. Along this research article, a robust controller was compared against a fuzzy logic strategy (with symmetric membership functions) where both were implemented to a commercial PEMFC through a dSPACE 1102 control board. Both proposals were analysed in an experimental test bench. Outcomes showed the advantages and disadvantages of each scheme in chattering reduction, accuracy, and convergence speed.
Modeling of Cross Work Hardening and Apparent Normality Loss after Biaxial–Shear Loading Path Change
Authors: Yang Yanfeng , Baudouin Cyrille , Balan Tudor
Published: January 2022

The specific loading-path change during sheet metal forming may lead to some abnormal deformation phenomena. Two-stage orthogonal loading paths without elastic unloading have revealed a phenomenon of apparent loss of normality, further modeled in the literature by non-normality theories. In this paper, a particular orthogonal strain-path change is investigated using the Teodosiu–Hu hardening rule within an associated plasticity framework. The results indicate that cross work-hardening has a significant contribution to the apparent loss of normality and subsequent asymmetric yield surface evolution. Detailed contributions of the model’s ingredients and features are clarified. The developed material model is intended for sheet metal forming simulation applications.