bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigating the Role of Ethical Self-Identity and Its Effect on Consumption Values and Intentions to Adopt Green Vehicles among Generation Z
Authors: Bhutto Muhammad Yaseen , Khan Mussadiq Ali , Ertz Myriam , Sun Haowei
Published: March 2022

Consumption values and consumer identities have been widely explored as needed in the literature on sustainability, but they are mainly treated as separate predictors of sustainable behavior. Researchers are calling for further analysis of these variables’ combined impacts to investigate sustainable behavior. This research integrates consumption values theory (functional, social, conditional, epistemic, and emotional) and ethical self-identity to explore the intention to adopt green vehicles among Generation Z. The data in this paper were collected from 319 respondents through a structured questionnaire in two universities in Islamabad, Pakistan. We used the PLS-SEM approach to analyze the results; we found that functional value (quality), social value, conditional value, and emotional value significantly influenced the intention to adopt green vehicles among Generation Z. The study further demonstrated that ethical self-identity significantly mediates the relationship between consumption values and the intention to adopt green vehicles among Generation Z. Our findings indicate that ethical self-identity inferences are favorable when promoting green vehicles among Generation Z. Therefore, the results of this study provide novel understandings for marketers and policymakers in Pakistan to emphasize the improvement of consumer values and ethical self-identity, which will eventually contribute to the adoption of green vehicles. In addition, automakers should promote green ideas, to encourage Generation Z to replace their existing vehicles with alternative green options in Pakistan.
A Predictive Approach to Identify Geometrically Hazardous Road Segments and Evaluate the Relative Safety Effects of Design Alternatives
Authors: Tola Alamirew Mulugeta , Demissie Tamene Adugna , Saathoff Fokke , Gebissa Alemayehu
Published: March 2022

This study has two goals: First, to fill a gap in the use of the predictive approach for evaluating road safety performance in Ethiopia, the most recent analytical methods of the HSM predictive approach in IHSDM software were used to evaluate the safety and operational effects of the existing roadway geometric design. Second, to assure safety and a sustainable transportation system, the relative safety effects of design changes made to hazardous road segments were quantified. Based on the Crash Prediction Module (CPM) evaluation of IHSDM software, the study identified fifteen hazardous road segments on the existing rural two-lane roads of Addis Ababa to Chacha and Addis Ababa to Dillela. The design changes made to the hazardous road segments have resulted in a remarkable reduction in crash rate, especially on the first top five hazardous segments, where incredible improvements have been observed. The total safety benefits acquired by applying engineering mitigations to the fifteen identified hazardous segments are described as follows: 17.18% reduction in total crash frequency (crashes/year), 58.94% reduction in crash rate (crashes/km/year), and 58.86% reduction in travel crash rate (crashes/million veh-km). In general, the study’s findings underlined the effectiveness of performance-based road safety evaluation and design in providing safe, efficient, and economically-feasible roadway infrastructure. The IHSDM reports and graphical outputs assist decision-making in the roadway design process by providing a quantitative evaluation of the safety impact of various design features and identifying roadway segments with safety concerns. Additionally, IHSDM is a tool capable of saving time for Road Safety Audit (RSA) teams. The paper also outlined the need for a computerized crash database recording system in Ethiopia to develop jurisdiction-specific Safety Performance Functions (SPFs).
Evaluation of the Techno-Economic Feasibility for Excavated Soil Recycling in Shenzhen, China
Authors: Huang Tong , Kou Shicong , Liu Deyou , Li Dawang , Xing Feng
Published: March 2022

The existing recycling chain of construction and demolition waste generally considers soil inert solid waste to be sent to landfills. As the most significant component of C&D (construction and demolition) waste, excavated soil occupies approximately half of landfills. Currently, excavated soil is a big issue in China’s Pearl River Delta. This paper investigated the composition and quantity of excavated soil in Shenzhen, China. In particular, the potential market demand for critical recycled sand (a key recycled material extracted from the excavated soil) was estimated. Furthermore, the technical analysis for excavated soil recycling takes an entire excavated soil recycling process’s perspective, delving into the process flow for the excavated soil and the recycled sand’s physicomechanical properties. Then, two mainstream and legitimate models of excavated soil recycling were considered: stationary plant recycling and on-site recycling. Each model’s financial and economic viability was assessed. The financial analysis focuses on investors’ perspectives, whose primary goal is to assess their investment profitability. The economic feasibility of the excavated soil stationary plant recycling and on-site recycling models in Shenzhen were then compared via benefit and cost analysis during the lifetime of the recycling equipment. A comprehensive, complete cost calculation and investment analysis revealed that Shenzhen’s excavated soil recycling business is profitable under the current market conditions. This study investigates scaled and effective excavated soil recycling and gives a technically and economically viable reference to the global excavated soil issue.
Issues and Challenges in Short Food Supply Chains: A Systematic Literature Review
Authors: Bayir Bilgesu , Charles Aurélie , Sekhari Aicha , Ouzrout Yacine
Published: March 2022

Consumers increasingly prefer more direct and more transparent food distribution channels, such as short food supply chains (SFSCs). Nonetheless, SFSCs face a variety of issues and challenges in their creation and functioning, resulting in limited performance and sustainability, as well as in difficulties of upscaling. This study aims at improving our understanding of SFSCs’ issues/challenges through a systematic review of the most recent literature. We perform a full-text content analysis of 44 studies, looking for answers to the research questions: At which parts of the SFSCs do the issues/challenges occur? How can we characterize the issues/challenges in SFSCs? While doing so, we offer a holistic perspective on SFSCs. We make use of the SCOR model to define SFSC processes as well as to describe the nature of these issues/challenges. The findings of this study shed light on the nature and strategic-tactical-operational level of the issues/challenges in SFSCs and point out the limitations in the existing literature such as the SFSC processes that are neglected. The holistic approach we suggest and the insight on SFSCs’ issues/challenges we provide can help researchers offer effective solutions and strategies to support the overall development of SFSCs.
Generation Expansion Planning Based on Local Renewable Energy Resources: A Case Study of the Isolated Ambon-Seram Power System
Authors: Tumiran  , Putranto Lesnanto Multa , Sarjiya  , Wijaya Fransisco Danang , Priyanto Adi , Savitri Ira
Published: March 2022

Energy sustainability has become one of the main issues in power system planning in the Indonesian archipelago system, which has many small, isolated systems. For that purpose, green and sustainable generation expansion planning (GEP) procedures based on local energy resources is required. GEP is a necessary procedure for fulfilling electricity demand, which determines the generating units to be installed within a specified time horizon with minimal total costs as the objective function. This study uses GEP considering the interconnection option among the existing small scattered generation systems in Maluku: the isolated Ambon, Seram, Haruku, and Saparua systems. With interconnection, the utilization of local renewable energy sources would be increased, especially biomass, which has abundant potential in these areas. The GEP was simulated in the PLEXOS environment using mixed-integer linear programming (MILP). For comparison purposes, there were interconnection and isolated system scenarios. The results showed that the interconnection system would have a high share of a renewable energy source (RES) of up to 54% in 2050, most of which is biomass as the primary local energy source. The interconnection system scenario met the LOLP criteria and had a lower reserve margin and total costs than the isolated scenario, with USD 773.7 million.
What Is Quality in Research? Building a Framework of Design, Process and Impact Attributes and Evaluation Perspectives
Authors: Margherita Alessandro , Elia Gianluca , Petti Claudio
Published: March 2022

The strategic relevance of innovation and scientific research has amplified the attention towards the definition of quality in research practice. However, despite the proliferation of evaluation metrics and procedures, there is a need to go beyond bibliometric approaches and to identify, more explicitly, what constitutes good research and which are its driving factors or determinants. This article reviews specialized research policy, science policy and scientometrics literature to extract critical dimensions associated with research quality as presented in a vast although fragmented theory background. A literature-derived framework of research quality attributes is, thus, obtained, which is subject to an expert feedback process, involving scholars and practitioners in the fields of research policy and evaluation. The results are represented by a structured taxonomy of 66 quality attributes providing a systemic definition of research quality. The attributes are aggregated into a three-dimensional framework encompassing research design (ex ante), research process (in-process) and research impact (ex post) perspectives. The main value of the study is to propose a literature-derived and comprehensive inventory of quality attributes and perspectives of evaluation. The findings can support further theoretical developments and research policy discussions on the ultimate drivers of quality and impact of scientific research. The framework can be also useful to design new exercises or procedures of research evaluation based on a multidimensional view of quality.
Prescriptive Learning and Sustainable Employee Engagement in Selected Pharmaceutical Firms in Nigeria
Authors: Ogueyungbo Opeyemi Olunike , Moses Chinonye Love , Igbinoba Ebeguki Edith , Osibanjo Adewale , Falola Hezekiah , Salau Odunayo
Published: March 2022

Prescriptive learning is gradually gaining the attention of various industries in Nigeria, particularly on the issues and concerns surrounding sustainability. The existing literature shows that Nigerian pharmaceutical firms have not provided adequately researched prescriptive learning opportunities and sustainable employee engagement. Thus, this study explores the influence of prescriptive learning and sustainable employee engagement in selected pharmaceutical firms in Nigeria. Five hundred and forty-one (541) respondents were surveyed across all the selected pharmaceutical companies in Nigeria using a stratified and purposive sampling technique. Only four hundred and thirty-four (434) copies of the questionnaire, which represents an 80.2% rate of response. were analysed with Smart PLS 3.0. The results show that competitive differentiation, reflection, research and idea testing significantly influenced employee (cognitive, behavioral and affective) engagements. The study concludes that the adoption of prescriptive learning motivates sustainable employee engagement because employees become emotionally invested in work roles and functions. This study contributes to the strategic learning and development of human resource management practices, especially in the Pharmaceutical industry.
What Drives a Future German Bioeconomy? A Narrative and STEEPLE Analysis for Explorative Characterisation of Scenario Drivers
Authors: Richter Sören , Szarka Nora , Bezama Alberto , Thrän Daniela
Published: March 2022

A future bioeconomy pursues the transformation of the resource base from fossil to renewable materials in an effort to develop a holistic, sustainable production and provision system. While the significance of this change in the German context is not yet entirely explored, scenarios analysing possible pathways could support the understanding of these changes and their systemic implications. Bioeconomy in detail depends on respective framework conditions, such as the availability of biomass or technological research priorities. Thus, for scenario creation, transferable methods for flexible input settings are needed. Addressing this issue, the study identifies relevant bioeconomy scenario drivers. With the theoretical approach of narrative analysis, 92 statements of the German National Bioeconomy Strategy 2020 have been evaluated and 21 international studies in a STEEPLE framework were assessed. For a future German bioeconomy 19 important drivers could be determined and specific aspects of the resource base, production processes and products as well as overarching issues were exploratively characterised on a quantitative and qualitative basis. The developed method demonstrate an approach for a transparent scenario driver identification that is applicable to other strategy papers. The results illustrate a possible future German bioeconomy that is resource- and technology-driven by following a value-based objective, and which is supplied by biogenic residue and side product feedstocks. As such, the bioeconomy scenario drivers can be used as a starting point for future research like scenario development or modelling of a future German bioeconomy.
Facilitating Safe FFF 3D Printing: A Prototype Material Case Study
Authors: Karayannis Panagiotis , Saliakas Stratos , Kokkinopoulos Ioannis , Damilos Spyridon , Koumoulos Elias P. , Gkartzou Eleni , Gomez Julio , Charitidis Constantinos
Published: March 2022

Three-dimensional (3D) printing has introduced a paradigm shift in the manufacturing world, and it is increasing in popularity. In cases of such rapid and widespread acceptance of novel technologies, material or process safety issues may be underestimated, due to safety research being outpaced by the breakthroughs of innovation. However, a definitive approach in studying the various occupational or environmental risks of new technologies is a vital part of their sustainable application. In fused filament fabrication (FFF) 3D printing, the practicality and simplicity of the method are juxtaposed by ultrafine particle (UFP) and volatile organic compound (VOC) emission hazards. In this work, the decision of selecting the optimal material for the mass production of a microfluidic device substrate via FFF 3D printing is supported by an emission/exposure assessment. Three candidate prototype materials are evaluated in terms of their comparative emission potential. The impact of nozzle temperature settings, as well as the microfluidic device’s structural characteristics regarding the magnitude of emissions, is evaluated. The projected exposure of the employees operating the 3D printer is determined. The concept behind this series of experiments is proposed as a methodology to generate an additional set of decision-support decision-making criteria for FFF 3D printing production cases.
Investigating the Impact of Smart Tourism Technologies on Tourists’ Experiences
Authors: Zhang Yuwen , Sotiriadis Marios , Shen Shiwei
Published: March 2022

The adoption and implementation of smart technologies in tourism destinations and visitor attractions to enrich tourists’ experiences and improve their satisfaction has become a new trend. The main purpose of this study was to explore the influence of the dimensions/attributes of smart technologies on tourism experience in the context of visitor attractions and related outcomes (satisfaction and post-consumption behavioral intentions). The Liangzhu Museum, Zhejiang Province, China, was used as the study area, and data were collected from 486 visitors and analyzed with a regression model. The results show that accessibility and interactivity affect smart technology-enhanced experiences. Tourists’ perceived value of smart technologies is significantly related to their satisfaction. Smart technology positively impacts word-of-mouth recommendations, revisit intention, and willingness to pay a price premium. Therefore, visitor attractions could improve tourists’ experiences by designing better infrastructure and services that incorporate the key dimensions of smart technologies, which would also improve their competitiveness.
Evaluation of Selected Algorithms for Air Pollution Source Localisation Using Drones
Authors: Suchanek Grzegorz , Wołoszyn Jerzy , Gołaś Andrzej
Published: March 2022

Polluted air causes enormous damage to human health. There is a high demand to find a solution for locating the places of illegal waste incineration due to the persistent smog problem. The use of multi-rotor drones for that purpose has now become one of the important research topics. The aim of the work was to check the possibility of using simple algorithms to search for the source of pollution. The algorithms that require low computing power, which may be part of the robot’s measurement and the control system’s internal software, were considered. The focus was on building a system based on a single robot that independently searches an area of a certain size. The simulation of the accuracy and scalability of the three different search algorithms was analysed for areas up to 200 m × 200 m. Two multi-rotor robots were prepared for the fieldwork. The validation of the two selected algorithms was carried out in outdoor environmental conditions. The fieldwork tests were carried out in areas with a maximum size of 100 m × 100 m. The obtained results were different, in particular on the wind speed and direction and the intensity of the pollution source. The random influence of these factors can verify the operation of the proposed system in practical applications. The difference between the true and the position of the source indicated by the robot was up to 15 m. That difference depended on the mutual arrangement of the measurement points and the pollution source location.
The Interactive Relationships between the Tourism-Transportation-Ecological Environment System of Provinces along the ‘Silk Road Economic Belt’ in China
Authors: Zhang Zhiqiang , Li Ling , Guo Qiuyu
Published: March 2022

Taking nine provinces and cities along the ‘Silk Road Economic Belt’ as an example, this paper constructs an evaluation index system of the coupling coordination degree of the tourism–transportation–ecological environment system (TTE system), analyzes the spatial–temporal evolution and regional differences of the coupling coordination level of the TTE system from 2004 to 2016 using the mean square error index model and the scissor difference model, and uses the EKC curve model to further verify the interactive relationship between the tourism economy and the ecological environment. The results show the following. (1) The comprehensive evaluation values of the tourism subsystem and transportation subsystem are on an overall upward trend and the comprehensive evaluation value of the ecological environment subsystem is in constant flux. (2) The coupling coordination degree of the TTE system generally develops in a good coordination direction, but the conversion rate of the coupling coordination degree of each province is different. (3) Regarding the north–south region divergence, the degree of coupling and coordination within the region is “strong in the south and weak in the north”. (4) The tourism subsystem and the transportation subsystem are interdependent and mutually restrictive. (5) There is a strong correlation between tourism, economic growth, and environmental quality, but in most provinces, the relationship between them does not accord with the inverted U-shaped environmental Kuznets curve.
Lean Six Sigma Impact Analysis on Sustainability Using Partial Least Squares Structural Equation Modeling (PLS-SEM): A Literature Review
Authors: Barcia Kleber F. , Garcia-Castro Lizzi , Abad-Moran Jorge
Published: March 2022

The Lean Six Sigma (LSS) philosophy and sustainability have become topics of interest since the 1990s; they have generally been analyzed together since 2012. Numerous professionals, managers, and researchers have sought methodologies by which to assess their impact and know their effectiveness within companies. During the past decade, the application of partial least squares structural equation modeling (PLS-SEM) has been widely accepted in various modeling, prediction, or multivariate analyses as a way to measure the impact of LSS on sustainability. This study conducts a literature review to identify the use of PLS-SEM in measuring the impact of LSS on sustainability. A systematic review methodology has been employed, applying five search criteria to three scientific database platforms. This approach has been helpful to identify PLS-SEM as a valuable methodology for measuring the impact of LSS on sustainability. One of the research findings is that LSS practices positively impact 83% of economic indicators, 78% of environmental indicators, and 70% of social indicators. This article creates a theoretical foundation for future research on these issues, outlining research opportunities to generate future studies. It also allows researchers and managers who are interested in improving sustainability indicators to access valuable knowledge regarding what types of LSS tools could be used.
Novel Mobile Application System for Implementation of an Eco-Incentive Scheme
Authors: Huang Hua , Su Daizhong , Peng Wenjie
Published: March 2022

In order to incentivise consumers to engage in sustainable consumption, a mobile application system is developed to implement an eco-incentive scheme, in which eco-credits are awarded to consumers who recycle and reuse end-of-life products and in which they can use the eco-credits for discounts in shopping, exchange the eco-credits for museum/theatre tickets, or make donations for tree planting. In this paper, the related concept and eco-incentive scheme are introduced first; the infrastructure of the mobile application system is presented; and the process of system development is detailed. The mobile system infrastructure consists of three layers: a database server; communication and integration; and four functional modules including user registration and login, obtaining eco-credits, spending/donating eco-credits, and viewing eco-credit history. Multiple mobile development techniques are utilised to implement the mobile application system. A case study was conducted, demonstrating that the mobile application for eco-incentive can efficiently support consumers in recycling products and managing their reward records. The literature review and user survey revealed that there has not been a mobile application system with the eco-incentive functions of the mobile app presented in this paper, which indicates the novelty of this research.
Identifying Knowledge and Process Gaps from a Systematic Literature Review of Net-Zero Definitions
Authors: Loveday Jane , Morrison Gregory M. , Martin David A.
Published: March 2022

The use of the term ‘net zero’ has rapidly and recently become mainstream but is often not well-defined in the literature. A brief history of the term was researched, followed by a systematic literature review to consider the research question: how have the different net-zero terms been defined in the literature, and do they indicate knowledge or process gaps which identify future research opportunities? Academic research articles were searched for the term ‘net zero’ and filtered for the term ‘definition’, resulting in 65 articles. Definitions were analysed according to scale: single-building, community, urban-system, and country-wide scale. The search did not return any definitions concerning country-wide emissions (from agriculture, forestry, large-scale transportation, or industrial and mining processes), a surprising outcome given the emissions impact of these areas. The main knowledge and process gaps were found to be in four areas: governance, design, measurement and verification, and circular framework. A clear net-zero definition is required at the appropriate scale (single-building or urban-system scale), which includes explicit system boundaries and emission scopes, life-cycle energy and greenhouse gas (GHG) emissions and should incorporate a dynamic approach. The scale most likely to achieve net zero is the urban-system scale due to the potential synergies of its interacting elements and energy flows.
Public Policies for Sustainable Territorial Development in Brazil: Between Clientelism and Participation
Authors: Sabourin Eric
Published: March 2022

The article discusses the permanence of clientelistic practices and their tensions with the participatory approach adopted within the framework of the Brazilian public policy of rural territorial development. It examines, in particular, the case of local implementation of the National Program of Territorial Development. The results come from the study of the functioning of the Territorial Collegiate and the projects implemented in the Águas Emendadas Territory in the Midwest of Brazil. It uses a socio-anthropological approach of patronage and political participation through the analysis of the social configuration and the relations of instrumentalisation in both the participatory spaces and the projects of this territory. The results show the existence of a not only social but also an affective dimension of clientele practice that can be analyzed as an asymmetrical reciprocity relationship based on the principle of anthropological reciprocity or as a process of unequal political exchange, considering a political science approach.
Waste Management 4.0: An Application of a Machine Learning Model to Identify and Measure Household Waste Contamination—A Case Study in Australia
Authors: Zaman Atiq
Published: March 2022

Waste management directly and indirectly contributes to all sustainable development goals. Hence, the modernisation of the current ineffective management system through Industry 4.0-compatible technologies is urgently needed. Inspired by the fourth industrial revaluation, this study explores the potential application of waste management 4.0 in a local government area in Perth, Western Australia. The study considers a systematic literature review as part of an exploratory investigation of the current applications and practices of Industry 4.0 in the waste industry. Moreover, the study develops and tests a machine learning model to identify and measure household waste contamination as a waste management 4.0 case study application. The study reveals that waste management 4.0 offers various opportunities and sustainability benefits in reducing costs, improving efficiency in the supply chain and material flow, and reducing as well as eliminating waste by achieving holistic circular economy goals. The significant barriers and challenges involve initial investments in developing and maintaining waste management 4.0 technology, platform and data acquisition. The proof-of-concept case study on the machine learning model detects selected waste with considerable precision (over 70% for selected items). The number and quality of the labelled data significantly influences the model’s accuracy. The data on waste contamination are essential for local governments to explore household waste recycling practices besides developing effective waste education and communication methods. The study concludes that waste management 4.0 can be an effective tool for acquiring real-time data; however, overcoming the current limitations needs to be addressed before applying waste management 4.0 into practice.
The Investigation of Monthly/Seasonal Data Clustering Impact on Short-Term Electricity Price Forecasting Accuracy: Ontario Province Case Study
Authors: Pourhaji Nazila , Asadpour Mohammad , Ahmadian Ali , Elkamel Ali
Published: March 2022

The transformation of the electricity market structure from a monopoly model to a competitive market has caused electricity to be exchanged like a commercial commodity in the electricity market. The electricity price participants should forecast the price in different horizons to make an optimal offer as a buyer or a seller. Therefore, accurate electricity price prediction is very important for market participants. This paper investigates the monthly/seasonal data clustering impact on price forecasting. To this end, after clustering the data, the effective parameters in the electricity price forecasting problem are selected using a grey correlation analysis method and the parameters with a low degree of correlation are removed. At the end, the long short-term memory neural network has been implemented to predict the electricity price for the next day. The proposed method is implemented on Ontario—Canada data and the prediction results are compared in three modes, including non-clustering, seasonal, and monthly clustering. The studies show that the prediction error in the monthly clustering mode has decreased compared to the non-clustering and seasonal clustering modes in two different values of the correlation coefficient, 0.5 and 0.6.
Experiencing a Food Production Site Using Wearable Devices: The Indirect Impact of Immersion and Presence in VR Tours
Authors: De Canio Francesca , Martinelli Elisa , Peruzzini Margherita , Cavallaro Sara
Published: March 2022

Virtual reality (VR) is among the main technologies revolutionizing numerous sectors, including tourism. In the latter context, virtual tours (VTs) are finding increasing application. Providing an immersive and realistic human–machine interaction, VR tours can bring visitors to virtually experience destination areas. The proposed research presents a theoretical and empirical investigation of the role played by some technical VR features (i.e., presence, immersion, ease-of-use) on VR visitors’ enjoyment, satisfaction, and, accordingly, on the physical visit intention of the production site and neighboring areas. After having experienced a 360-degree VR tour of a food production site, created specifically for this study, 140 visitors were surveyed online. Results—emerging from a PLS structural equation model—show that immersion and presence both directly impact the enjoyment and indirectly the user’s VR tour satisfaction and visit intention. Further, if the VR tour is perceived as easy to use, it influences visitors’ satisfaction and physical visit intention. This study contributes to the novel VR literature, applied in the tourism sector, evidencing how immersive and enjoyable scenarios, experienced via widespread devices such as smartphones, may impact tourists’ choices. In food tourism, VR technologies can be fundamental in attracting new visitors to the production sites and neighboring areas.
Using Net Primary Productivity to Characterize the Spatio-Temporal Dynamics of Ecological Footprint for a Resource-Based City, Panzhihua in China
Authors: Zhang Shuhui , Li Fuquan , Zhou Yuke , Hu Ziyuan , Zhang Ruixin , Xiang Xiaoyu , Zhang Yali
Published: March 2022

An ecological footprint is a primary indicator in measuring the sustainability of regional development, especially in resource-based cities. Here, we built an ecological footprint-based framework to assess the sustainability for a resource-based city of Panzhihua, in China. In this framework, a suite of long-term ecological parameters (2000–2020), essentially including Net Primary Productivity (NPP), land cover, as well as social statistical data, was used as the input indices of a provincial hectare ecological footprint model. The model outputs are composed of the ecological footprint (EF), ecological footprint per capita (PEF), ecological capacity (EC), ecological capacity per capita (PEC), ecological deficit/surplus (ED/S), and per capita ecological deficit/surplus (PED/S). Then the sustainable development capability of the city was comprehensively evaluated using a suite of ecological indices, including the ecological pressure index (EPI), ecological footprint per ten thousand GDP (EFG), ecological sustainability index (ESI), and ecological coordination index (ECI). The study reveals that, from 2000–2020, (1) PEC and PED/S presented an increasing trend (0.2401 hm2/person and 2.1421 hm2/person, respectively), while PEF decreased by 1.9 hm2/person. In the case of the ecological deficit, fossil energy land and forest were the dominant land types in controlling the ecological footprint and ecological capacity, (2) EPI and EFG decreased by 6.6381 hm2/person and 2.2462 hm2/person, respectively, and ESI and ECI increased by 0.3436 hm2/person and 0.2897 hm2/person, respectively. These indices also reflect that the utilization rate of natural resources in Panzhihua City has been improved, with enhanced sustainability, as well as a decline in ecological pressure. This ecological footprint-based framework could work as a template for evaluating the sustainability of resource-based cities from positive and negative ecological footprint indices.
Comprehensive Diagnosis Method of the Health of Tailings Dams Based on Dynamic Weight and Quantitative Index
Authors: Dong Kai , Mi Zhankuan , Yang Dewei
Published: March 2022

As a dangerous source of man-made debris flow with high potential energy, tailings dams can cause huge losses to people’s lives and property downstream once they break, and their safety control problem is particularly prominent. The health diagnosis of tailings dams is a complex and nonlinear problem full of uncertainty. At present, the health diagnosis of tailings dams is mostly qualitative evaluation or quantitative analysis aiming at a single index, so this study puts forward a comprehensive quantitative diagnosis method of tailings dam health based on dynamic weight. Slope stability, deformation stability and seepage stability are taken as project layers, and the diagnosis index system of the tailings dam is constructed. The quantitative methods of diagnosis indexes of project layers are proposed. For the dam slope stability project, the safety factor and the reliability index of tailings dams are determined based on the Monte Carlo method, which can consider the uncertainty of tailings material parameters. For the deformation stability project, the normal operation values of deformation rate and deformation amount are determined by analyzing the in situ observation data and combining them with the numerical simulation results. For the seepage stability project, through the analysis of seepage and stability, the relationship curve between the depth of saturation line and the safety factor of anti-sliding stability is established. The norms method is used to determine the quantitative standards for the diagnosis indexes of the basic layer. Based on the analytical hierarchy process method and the penalty variable weight method, the method of dynamic weight of the project layer index is proposed. The proposed methods are applied to a practical engineering project. The results show that the methods can accurately reflect the health status of tailings dams. This study provides a new method for evaluating the safety of tailings dams.
Exogenous ABA Enhances the Antioxidant Defense System of Maize by Regulating the AsA-GSH Cycle under Drought Stress
Authors: Jiang Zizhu , Zhu Hengguang , Zhu Hanyu , Tao Yuzhao , Liu Changzhuang , Liu Jiaqi , Yang Fuqiang , Li Ming
Published: March 2022

When drought occurs during the maize-filling period, the probability of yield decline increases. Abscisic acid (ABA) plays a regulatory role in physiological and metabolic activities during plant development. However, its effect on the antioxidant system of maize leaves during the grain-filling stage is unclear. Maize plants (Zhengdan958) were used as an experimental material, and ABA was sprayed on the leaves during the grain-filling stage. The plants were placed under drought conditions to analyze the relationship between the ascorbate-glutathione (AsA-GSH) cycle and hydrogen peroxide (H2O2) removal. Exogenous ABA significantly reduced the malondialdehyde content, relative electrolyte leakage, and H2O2 under drought stress. This is similar to the exogenous ABA effect on the AsA-GSH cycle. Exogenous ABA upregulated the transcription of related genes and alleviated the inhibition of drought stress on the monodehydroascorbate reductase and dehydroascorbate reductase activities, thereby further increasing the ascorbate peroxidase and glutathione reductase activities. It contributed to an increase in the AsA and GSH levels and inhibited the decrease in the AsA/dehydroascorbic acid and GSH/oxidized glutathione ratios. Therefore, exogenous ABA plays an important role in improving the antioxidant capacity and drought resistance physiology of maize by enhancing antioxidant enzyme activity and stabilizing the AsA and GSH redox state.
Design of Experiment: A Rational and Still Unexplored Approach to Inorganic Materials’ Synthesis
Authors: Lamberti Francesco , Mazzariol Chiara , Spolaore Federico , Ceccato Riccardo , Salmaso Luigi , Gross Silvia
Published: March 2022

This review was devoted to outlining the use and potential increasing application of the Design of Experiment (DoE) approach to the rational and planned synthesis of inorganic nanomaterials, with a particular focus on polycrystalline nanostructures (metal and alloys, oxides, chalcogenides, halogenides, etc.) produced by sustainable wet chemistry routes based on a multi-parameter experimental landscape. After having contextualised the stringent need for a rational approach to inorganic materials’ synthesis, a concise theoretical background on DoE is provided, focusing on its statistical basis, shortly describing the different sub-methodologies, and outlining the pros and cons of each. In the second part of the review, a wider section is dedicated to the application of DoE to the rational synthesis of different kinds of chemical systems, with a specific focus on inorganic materials.
Removal and Recovery of the Human Invisible Region
Authors: Zhang Qian , Liang Qiyao , Liang Hong , Yang Ying
Published: March 2022

The occlusion problem is one of the fundamental problems of computer vision, especially in the case of non-rigid objects with variable shapes and complex backgrounds, such as humans. With the rise of computer vision in recent years, the problem of occlusion has also become increasingly visible in branches such as human pose estimation, where the object of study is a human being. In this paper, we propose a two-stage framework that solves the human de-occlusion problem. The first stage is the amodal completion stage, where a new network structure is designed based on the hourglass network, and a large amount of prior information is obtained from the training set to constrain the model to predict in the correct direction. The second phase is the content recovery phase, where visible guided attention (VGA) is added to the U-Net with a symmetric U-shaped network structure to derive relationships between visible and invisible regions and to capture information between contexts across scales. As a whole, the first stage is the encoding stage, and the second stage is the decoding stage, and the network structure of each stage also consists of encoding and decoding, which is symmetrical overall and locally. To evaluate the proposed approach, we provided a dataset, the human occlusion dataset, which has occluded objects from drilling scenes and synthetic images that are close to reality. Experiments show that the method has high performance in terms of quality and diversity compared to existing methods. It is able to remove occlusions in complex scenes and can be extended to human pose estimation.
Analysis and Estimation of Economic Influence of IoT and Telecommunication in Regional Media Based on Evolution and Electronic Markets in Romania
Authors: Nistor Andreea , Zadobrischi Eduard
Published: March 2022

The interconnection of devices, intended to collect and transmit data via the Internet, is called the Internet of Things (IoT). This technology has the potential to revolutionize both the economic and industrial sectors, especially in terms of data confidentiality and information security. New media, with a merger between those two, have increasingly replaced traditional media, but many researchers characterize them as two distinct but interconnected types of media. From the traditional media, with its technological evolution, the IoT has supported the development of the media through the emergence of applications, websites, and social networks designed to spread information worldwide. This research focuses on how the IoT has the ability to influence economic growth by trying to determine the impact of the IoT through theories and the evolution of economic growth. Thus, the concept of the IoT is interdependent on information and communications technology and, from an economic point of view, is correlated with productivity. In addition, the processes that have an impact on the media are those of an economic nature, all of which are interconnected with progress, innovation, and the promotion of goods and services. At the same time, this paper aims to determine the correlation between IoT and the economy, with a focus on the media, which has the main result of the development of new businesses. Thus, a bibliometric analysis of the scientific papers on the Web of Science platform regarding the IoT field was performed, in order to identify the current state of knowledge in this field. The results of this analysis highlighted that both the IoT and the economy are shaped by innovation, opportunities, and development.
Selection, Characterization, and Optimization of DNA Aptamers against Challenging Marine Biotoxin Gymnodimine-A for Biosensing Application
Authors: Zhang Xiaojuan , Gao Yun , Deng Bowen , Hu Bo , Zhao Luming , Guo Han , Yang Chengfang , Ma Zhenxia , Sun Mingjuan , Jiao Binghua , Wang Lianghua
Published: March 2022

Gymnodimines (GYMs), belonging to cyclic imines (CIs), are characterized as fast-acting toxins, and may pose potential risks to human health and the aquaculture industry through the contamination of sea food. The existing detection methods of GYMs have certain defects in practice, such as ethical problems or the requirement of complicated equipment. As novel molecular recognition elements, aptamers have been applied in many areas, including the detection of marine biotoxins. However, GYMs are liposoluble molecules with low molecular weight and limited numbers of chemical groups, which are considered as “challenging” targets for aptamers selection. In this study, Capture-SELEX was used as the main strategy in screening aptamers targeting gymnodimine-A (GYM-A), and an aptamer named G48nop, with the highest KD value of 95.30 nM, was successfully obtained by screening and optimization. G48nop showed high specificity towards GYM-A. Based on this, a novel aptasensor based on biolayer interferometry (BLI) technology was established in detecting GYM-A. This aptasensor showed a detection range from 55 to 1400 nM (linear range from 55 to 875 nM) and a limit of detection (LOD) of 6.21 nM. Spiking experiments in real samples indicated the recovery rate of this aptasensor, ranging from 96.65% to 109.67%. This is the first study to report an aptamer with high affinity and specificity for the challenging marine biotoxin GYM-A, and the new established aptasensor may be used as a reliable and efficient tool for the detection and monitoring of GYMs in the future.
Antimicrobial Resistance and Predisposing Factors Associated with Catheter-Associated UTI Caused by Uropathogens Exhibiting Multidrug-Resistant Patterns: A 3-Year Retrospective Study at a Tertiary Hospital in Mogadishu, Somalia
Authors: Mohamed Abdikarim Hussein , Sheikh Omar Nasteho Mohamed , Osman Marian Muse , Mohamud Hussein Ali , Eraslan Aşır , Gur Metin
Published: March 2022

Background: Widespread and rapidly emerging multidrug-resistant uropathogens, particularly carbapenem-resistant pathogens, are a public health concern that impairs the determination of empirical therapy. This study aims to evaluate the antimicrobial susceptibility profile and factors associated with catheter-associated urinary tract infection (CA-UTI). Method: This retrospective study was carried out on a total of 779 urine cultures over a 3-year period. Antimicrobial sensitivity tests were performed using the standard Kirby–Bauer disk diffusion method. Results: The prevalence of CA-UTI in our study was 12.7%; a total of 47% of cultures had multi-drug-resistant (MDR) uropathogens, and 13% of the cultures showed extended-spectrum beta-lactamase (ESBL)-producing pathogens. Elderly patients, intensive care unit admissions, and associated comorbidities were correlated with higher rates of CA-UTI caused by multidrug-resistant uropathogens (p < 0.021, 95% CI: 0.893–2.010), (p < 0.008, 95% CI: 1.124–5.600), (p < 0.006, 95% CI: 0.953–2.617). Latex catheters and prolonged catheterization time were associated with increased risk of CA-UTI (p < 0.0001, 95% CI: 0.743–1.929, p = 0.012, 95% CI: 0.644–4.195). Patients with MDR uropathogens had prolonged hospital stays, i.e., 49% in more than 2 weeks (p < 0.04, 95% CI: 0.117–3.084). E. coli was the most common pathogen (26.3%), followed by Acinetobacter baumannii (24.3%). Acinetobacter baumannii showed the highest MDR pattern (88.5%), followed by Pseudomonas aeruginosa (68%). Acinetobacter baumannii and Klebsiella pneumoniae were associated with prolonged hospital stays (>2 w at 73.1 and 69%, respectively). Higher antimicrobial resistance against ceftriaxone (85.7%), meropenem (54.3%), ertapenem (50%), ciprofloxacin (58.5%), amikacin (27%), tigecycline (7.6%), and colistin (4.6%), was revealed in the study. Conclusion: Aside from the higher antimicrobial resistance against cephalosporins and fluoroquinolones, the findings of this study revealed that carbapenems are facing increased rates of antimicrobial resistance and are associated with substantial morbidity, prolonged hospitalization times, and increased healthcare expenses.
Detection of SARS-CoV-2 Antigens in the AV-Node of a Cardiac Conduction System—A Case Report
Authors: Jakovac Hrvoje , Ferenčić Antun , Stemberger Christophe , Mohar Vitezić Bojana , Cuculić Dražen
Published: March 2022

Mounting evidence indicates that new arrhythmic events frequently occur during and after coronavirus disease (COVID-19), posing additional mortality risk in older-aged and critically ill patients. However, the underlying mechanisms and cardio pathological substrates of COVID-related arrhythmias have not been clarified yet. Here, we report findings of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antigens and genes in the atrioventricular node (AV-node) of a cardiac conduction system, pointing to its direct infection as a possible arrhythmogenic factor.