bluuebunny/crossref_metadata_2025 huggingface dataset:
Motion Magnification Applications for the Protection of Italian Cultural Heritage Assets
Authors: Fioriti Vincenzo , Roselli Ivan , Cataldo Antonino , Forliti Sara , Colucci Alessandro , Baldini Massimiliano , Picca Alessandro
Published: December 2022

In recent years, the ENEA has introduced a novel methodology based on motion magnification (MM) into the Italian cultural heritage protection and monitoring field. It consists of a digital video signal processing technique able to amplify enormously the tiny movements recorded in conventional videos, while preserving the general topology of the acquired frames. Though the idea of such a methodology is not new, it has recently been provided with an efficient algorithm that makes possible a viable and low-cost magnification. Applications are extremely varied in almost every field of science and technology; however, we are interested in its application to the safeguarding of architectural heritage, a sector of the utmost importance for Italy. As ancient buildings can be extremely sensitive to even minimally invasive instrumentation, most common monitoring sensors can be replaced by contactless tools and methods, such as video-based techniques like MM. It offers many advantages: easy to use, contactless devices, virtual sensors, reusability of the videos, practicality, intuitive graphical results, quantitative analyses capability and low costs. These characteristics are well suited to the monitoring of large ancient monuments; on the other hand, historical sites have peculiarities of their own, requiring careful approaches, proper tools and trained personnel. Moreover, outdoor applications of MM present quite notable difficulties from a practical point of view, e.g., the dimensions of the studied objects, uncontrolled environmental conditions, spurious vibrations, lighting change/instability, etc. Here we give a general idea of the potential of MM and related issues, using some relevant in-the-field case studies in Italian heritage protection.
Performance of the SABAT Neutron-Based Explosives Detector Integrated with an Unmanned Ground Vehicle: A Simulation Study
Authors: Silarski Michał , Nowakowski Marek
Published: December 2022

The effective and safe detection of illicit materials, explosives in particular, is currently of growing importance taking into account the geopolitical situation and increasing risk of a terrorist attack. The commonly used methods of detection are based predominantly on metal detectors and georadars, which show only the shapes of the possible dangerous objects and do not allow for exact identification and risk assessment. A supplementary or even alternative method may be based on neutron activation analysis, which provides the possibility of a stoichiometric analysis of the suspected object and its non-invasive identification. One such sensor is developed by the SABAT collaboration, with its primary application being underwater threat detection. In this article, we present performance studies of this sensor, integrated with a mobile robot, in terms of the minimal detectable quantity of commonly used explosives in different environmental conditions. The paper describes the functionality of the used platform considering electronics, sensors, onboard computing power, and communication system to carry out manual operation and remote control. Robotics solutions based on modularized structures allow the extension of sensors and effectors that can significantly improve the safety of personnel as well as work efficiency, productivity, and flexibility.
Methodology for Designing an Optimal Test Stand for Camera Thermal Drift Measurements and Its Stability Verification
Authors: Nimura Kohhei , Adamczyk Marcin
Published: December 2022

The effects of temperature changes on cameras are realized by observing the drifts of characteristic points in the image plane. Compensation for these effects is crucial to maintain the precision of cameras applied in machine vision systems and those expected to work in environments with varying factors, including temperature changes. Generally, mathematical compensation models are built by measuring the changes in the intrinsic and extrinsic parameters under the temperature effect; however, due to the assumptions of certain factors based on the conditions of the test stand used for the measurements, errors can become apparent. In this paper, test stands for thermal image drift measurements used in other works are assessed, and a methodology to design a test stand, which can measure thermal image drifts while eliminating other external influences on the camera, is proposed. A test stand was built accordingly, and thermal image drift measurements were performed along with a measurement to verify that the test stand did eliminate external influences on the camera. The experiment was performed for various temperatures from 5 °C to 45 5 °C, and as a result, the thermal image drift measured with the designed test stand showed its maximum error of 16% during its most rapid temperature change from 25 °C to 5 °C.
Damage Assessment in Rural Environments Following Natural Disasters Using Multi-Sensor Remote Sensing Data
Authors: Havivi Shiran , Rotman Stanley R. , Blumberg Dan G. , Maman Shimrit
Published: December 2022

The damage caused by natural disasters in rural areas differs in nature extent, landscape, and structure, from the damage caused in urban environments. Previous and current studies have focused mainly on mapping damaged structures in urban areas after catastrophic events such as earthquakes or tsunamis. However, research focusing on the level of damage or its distribution in rural areas is lacking. This study presents a methodology for mapping, characterizing, and assessing the damage in rural environments following natural disasters, both in built-up and vegetation areas, by combining synthetic-aperture radar (SAR) and optical remote sensing data. As a case study, we applied the methodology to characterize the rural areas affected by the Sulawesi earthquake and the subsequent tsunami event in Indonesia that occurred on 28 September 2018. High-resolution COSMO-SkyMed images obtained pre- and post-event, alongside Sentinel-2 images, were used as inputs. This study’s results emphasize that remote sensing data from rural areas must be treated differently from that of urban areas following a disaster. Additionally, the analysis must include the surrounding features, not only the damaged structures. Furthermore, the results highlight the applicability of the methodology for a variety of disaster events, as well as multiple hazards, and can be adapted using a combination of different optical and SAR sensors.
Flexible IoT Agriculture Systems for Irrigation Control Based on Software Services
Authors: Palomar-Cosín Eva , García-Valls Marisol
Published: December 2022

IoT technology applied to agriculture has produced a number of contributions in the recent years. Such solutions are, most of the time, fully tailored to a particular functional target and focus extensively on sensor-hardware development and customization. As a result, software-centered solutions for IoT system development are infrequent. This is not suitable, as the software is the bottleneck in modern computer systems, being the main source of performance loss, errors, and even cyber attacks. This paper takes a software-centric perspective to model and design IoT systems in a flexible manner. We contribute a software framework that supports the design of the IoT systems’ software based on software services in a client–server model with REST interactions; and it is exemplified on the domain of efficient irrigation in agriculture. We decompose the services’ design into the set of constituent functions and operations both at client and server sides. As a result, we provide a simple and novel view on the design of IoT systems in agriculture from a sofware perspective: we contribute simple design structure based on the identification of the front-end software services, their internal software functions and operations, and their interconnections as software services. We have implemented the software framework on an IoT irrigation use case that monitors the conditions of the field and processes the sampled data, detecting alarms when needed. We demonstrate that the temporal overhead of our solution is bounded and suitable for the target domain, reaching a response time of roughly 11 s for bursts of 3000 requests.
Leadership Styles, Organizational Climate, and School Climate Openness from the Perspective of Slovak Vocational School Teachers
Authors: Barnová Silvia , Treľová Silvia , Krásna Slávka , Beňová Eleonóra , Hasajová Lívia , Gabrhelová Gabriela
Published: December 2022

The aim of the proposed study is to present the partial results of a research study on the organizational climate in vocational schools as perceived by teachers. Special attention is paid to the applied leadership style by school leaders, and the existence of associations between school leaders’ and teachers’ behaviour in schools. Organizational climate was measured by the standardized OCDQ-RS adapted to the conditions of the Slovak educational environment on the sample of 474 vocational schoolteachers. The scale measures five dimensions: Supportive principal behaviour; Directive principal behaviour; Engaged teacher behaviour; Frustrated teacher behaviour; and Intimate teacher behaviour, allowing for calculation of the Index of school climate openness, which is an indicator of the quality of the organizational climate. The obtained results confirmed the existence of associations between teacher and principal behaviour and school climate openness. It can be assumed that the applied leadership style in an institution can affect the quality of interpersonal relationships and teacher behaviour both in positive and negative directions. Therefore, it is important to pay attention to building favourable organizational climate in schools, which represents a challenge for school leaders and educational systems that should provide school leaders with sufficient learning opportunities in the field of school leadership.
Perceived Pain in Athletes: A Comparison between Endurance Runners and Powerlifters through a Cold Experimental Stimulation and Two Sessions of Various Physical Activation
Authors: Diotaiuti Pierluigi , Rodio Angelo , Corrado Stefano , Mancone Stefania , Bellizzi Fernando , Siqueira Thais Cristina , Andrade Alexandro
Published: December 2022

Few studies in the literature have illustrated cold hypoalgesia induced by strength training. Objectives of this contribution were to compare the ratings of perceived pain in endurance running (n = 22) and powerlifting (n = 22) male athletes and controls (n = 22) at baseline and after two bouts of 40 min aerobic/strength training respectively, using the Cold Pressor Test (CPT) and simultaneously monitoring changes in blood pressure (BP), heart rate (HR), and body temperature. A two-way repeated measures ANOVA was conducted to examine the effects of training sessions in endurance runners vs. powerlifting athletes vs. controls on the intensity of perceived pain at CPT. A statistically significant two-way interaction between the group and training resulted in p < 0.001, ηp2 = 0.513. A simple main effects analysis showed that as the participants went through the strength training session, pain perception at CPT was significantly lower in powerlifters compared to runners and controls. Considering the physiological parameters, powerlifters reported significantly higher values of BP and HR. This difference was present at baseline but after training as well, and before and after CPT, despite a slight hypotensive effect. The differences reported after CPT at baseline, but very significantly after the strength activation session in the powerlifters, provide interesting insights into the hypoalgesic effect of high-intensity strength training.
Statistical Analysis in the Presence of Spatial Autocorrelation: Selected Sampling Strategy Effects
Authors: Griffith Daniel A. , Plant Richard E.
Published: December 2022

Fundamental to most classical data collection sampling theory development is the random drawings assumption requiring that each targeted population member has a known sample selection (i.e., inclusion) probability. Frequently, however, unrestricted random sampling of spatially autocorrelated data is impractical and/or inefficient. Instead, randomly choosing a population subset accounts for its exhibited spatial pattern by utilizing a grid, which often provides improved parameter estimates, such as the geographic landscape mean, at least via its precision. Unfortunately, spatial autocorrelation latent in these data can produce a questionable mean and/or standard error estimate because each sampled population member contains information about its nearby members, a data feature explicitly acknowledged in model-based inference, but ignored in design-based inference. This autocorrelation effect prompted the development of formulae for calculating an effective sample size (i.e., the equivalent number of sample selections from a geographically randomly distributed population that would yield the same sampling error) estimate. Some researchers recently challenged this and other aspects of spatial statistics as being incorrect/invalid/misleading. This paper seeks to address this category of misconceptions, demonstrating that the effective geographic sample size is a valid and useful concept regardless of the inferential basis invoked. Its spatial statistical methodology builds upon the preceding ingredients.
Preliminary Analysis of Voluntary Information on Organic Milk Labels in Four European Union Countries
Authors: Woś Karolina , Borghoff Lisa Marie , Horvat Andrijana , Paoletti Flavio , Civitelli Eleonora Saggia , Rembiałkowska Ewa
Published: December 2022

The concern for the environment among European consumers is growing and in the future the need for sustainable shopping is expected to increase. Through transparent on-packaging communication with consumers, organic producers have the opportunity to show attributes of organic production system and build a strong market position. The aim of the study was to analyse voluntary packaging information on organic milk from four European markets in the context of organic food quality, i.e., Germany, the Netherlands, Italy and Poland. More specifically, the textual content of 106 organic milk packages was analysed and voluntary information on each package was categorized according to process- and product-related organic milk attributes. The assortment and content of voluntary packaging information varied across the four countries. The largest number of products was found on the German market (37) and the smallest on the Polish market (14). Dutch milk had the greatest amount of voluntary information on animal welfare, product locality, environmental protection, quality confirmation, naturalness and nutritional value. German milk had the most information on enjoyment and conditions of processing, while the Italian milk on the social perspective. The products available on the Polish market had the least voluntary information. Pasteurized organic milk had noticeably more information about organic quality attributes than micro filtrated and UHT milk.
Research on the Spatial-Temporal Distribution Characteristics and Influencing Factors of Carbon Emission Efficiency in China’s Metal Smelting Industry—Based on the Three-Stage DEA Method
Authors: Gao Linan , Liu Xiaofei , Mei Xinyi , Rui Guangwei , Li Jingcheng
Published: December 2022

The threat of global climate change has encouraged the international community to pay close attention to the levels of greenhouse gases, such as carbon dioxide, in the atmosphere. China has the world’s largest metal smelting industry, which is a major energy-consuming and carbon-emitting industry. Thus, this industry’s low-carbon transition is of great significance. Carbon emission efficiency (CEE) is a key indicator for the metal smelting industry to prioritize sustainable development. This paper applies a three-stage data envelopment analysis model with undesirable outputs to estimate CEE for 30 provinces from 2005 to 2020 in China, and analyzes the influencing factors using a spatial Durbin model. The results show that the CEE level generally improved in all Chinese provinces during the sample period, but the average CEE in the eastern region was 1.05 compared to 1.07 in the western and central regions, with the latter two regions progressing faster in terms of low carbon production capacity. The national average Malmquist–Luenberger (ML) index demonstrates a significant increase in technical efficiency across regions in 2010 and 2017, peaking in 2017. The study also suggests that current green credit and environmental regulations are not effective in promoting CEE improvements in the metal smelting industry, and that existing policies should be modified. Moreover, the spatial regression results indicate that the cross-regional transfer of low-carbon production technologies in China is largely complete. This study provides a more objective evaluation of the CEE levels of metal smelting across China, providing the government with a new perspective to guide the green transformation of energy-intensive industries.
Online Homework Intelligent Platform Based on Self-Regulated Learning (SRL): Essential for Sustainable Development of Online Higher Education
Authors: Liu Yiwen , Wen Wenkan , Gao Yanxia , Zhang Xian , Qu Taiguo , Yin Dong , Peng Xiaoning , Shi Yuanquan
Published: December 2022

Online higher education has become a steadily more popular way of learning for university students in the post-pandemic era. It has been emphasized that active learning and interactive communication are key factors in achieving effective performance in online learning. However, due to the lack of learning motivation of students and the lack of feedback data in online learning, there are numerous problems, such as the weak self-discipline of students, unsatisfactory learning experience, a high plagiarism rate of homework, and the low utilization of online teaching resources. In this study, an online homework intelligent platform implemented by information technology (IT) was proposed. It was based on the pedagogical self-regulated learning (SRL) strategy as a theoretical foundation, and information technology as a driver. Through setting online homework assignments, a sustainable means of promoting the four components of the SRL strategy, i.e., self-disciplinary control, independent thinking, reflective learning, and interest development, can be provided to university students. Therefore, this study explained the “4A” functions in the platform and analysed the details of their implementation and value, such as assistance in locating resources, assignment of differentiated homework, assessment of warning learning, and achievement of sharing. After three years of continuous improvements since COVID-19, this online platform has been successfully applied to students and teachers at our university and other pilot universities. A comparison of student teaching data, questionnaire responses and teacher interviews from the Computer Composition Principles course illustrated the sustainability as well as the effectiveness of the method.
Determinants and Consequences of Green Investment in the Saudi Arabian Hotel Industry
Authors: Abdou Ahmed Hassan , Hassan Thowayeb H. , Salem Amany E. , Elsaied Mohamed Ahmed , Elsaed Ahmed Anwar
Published: December 2022

Hotels in today’s business environment are no longer solely concerned with profit, but rather with profit, people, and the planet (3Ps). In corporate terms, green investment (GI) is regarded as a strategy that aims for maximum profit with minimal environmental impact. As a result, the current study primarily aims to empirically investigate the impact of internal and external drivers on GI adoption in Saudi Arabian eco-friendly hotels. Additionally, it explores to what extent GI affects eco-friendly hotels’ environmental, economic, and social performance. To achieve these objectives, a web-based questionnaire was developed and addressed to the senior manager/director in charge of environmental management in all four- and five-star eco-friendly hotels in Saudi Arabia. The total number of certified eco-friendly hotels in all regions of Saudi Arabia was 403. Only 298 forms were received and were valid for statistical analysis. A structural equation modeling (SEM) technique with maximum likelihood estimation was employed to test the study hypotheses. The findings of this study illustrate that GI is significantly positively affected by external as well as internal drivers. Adaptation to/mitigation of climate change was the highest perceived driver. Additionally, GI has a significant positive contribution to enhancing hotels’ environmental performance, increasing economic performance, and boosting social performance. Based on the study findings, eco-friendly hotel operators should consider GI in their strategic plans, as a corporate strategy aiming at maximizing profit and enhancing the quality of social life without harming the environment.
Accessing Synergies and Opportunities between Nature-Based Solutions and Urban Drainage Systems
Authors: Ramísio Paulo J. , Brito Rita Salgado , Beceiro Paula
Published: December 2022

Urban drainage systems face intrinsic constraints related to the deterioration of infrastructure, the interaction between systems, and increasing requirements and stresses that lower the quality of provided services. Furthermore, climate change and the need for the efficient use of resources are providing additional pressures that cannot be addressed solely with “Business-as-usual” solutions. In this paper, the consequences of such problems and limitations on the urban environment have been assessed through the identification of linked major impacts (e.g., urban flooding and pollution events) and societal externalities (e.g., economic losses, health and social issues, and environmental risks). Since Nature-based Solutions (NBS) consider human well-being, socio-economic development, and governance principles, they open new perspectives regarding urban sustainability, quality of life, and climate change adaptation. To highlight their added value to existing Urban Drainage Systems (UDS), the synergies that result from implementing NBS with traditional urban drainage systems were identified and assessed. Based on a comprehensive framework, for both wastewater and stormwater, the relevant opportunities for rethinking UDS and NBS were identified. Most relevant positive effects go beyond the mitigation of existing intrinsic constraints of traditional systems (e.g., dealing with the control of pollutants or stormwater management) since NBS also provide important economic, social, and environmental co-benefits by including water in urban planning and providing greener open spaces. This integrated and complementary solution not only represents a contribution to the sustainable management of urban water, but also enables an increase in the resilience of urban areas and, in particular, water services against climate change and for additional social co-benefits.
Study on Identification and Prevention of Traffic Congestion Zones Considering Resilience-Vulnerability of Urban Transportation Systems
Authors: Zhao Xueting , Hu Liwei , Wang Xingzhong , Wu Jiabao
Published: December 2022

In order to solve the problem of urban short-term traffic congestion and temporal and spatial heterogeneity, it is important to scientifically delineate urban traffic congestion response areas to alleviate regional traffic congestion and improve road network efficiency. Previous urban traffic congestion zoning is mostly divided by urban administrative divisions, which is difficult to reflect the difference of congestion degree within administrative divisions or traffic congestion zoning. In this paper, we introduce the Self-Organizing Feature Mapping (SOFM) model, construct the urban traffic congestion zoning index system based on the resilience and vulnerability of urban traffic systems, and establish the urban traffic congestion zoning model, which is divided into four, five, six, and seven according to the different structures of competition layer topology. The four vulnerability damage capacity indicators of traffic volume, severe congestion mileage, delay time and average operating speed, and two resilience supply capacity indicators of traffic systems, namely, road condition and number of lanes, are used as model input vectors; the data of Guiyang city from January to June 2021 are used as data sets to input four SOFM models for training and testing and the best SOFM model with six competitive topologies is constructed. Finally, the Support Vector Machine (SVM) is used to identify the optimal partition boundary line for traffic congestion. The results show that the four models predict the urban traffic congestion zoning level correctly over 95% on the test set, each traffic congestion zoning evaluation index in the urban area shows different obvious spatial clustering characteristics, the urban traffic congestion area is divided into six categories, and the city is divided into 16 zoning areas considering the urban traffic congestion control types (prevention zone, control zone, closure control zone). The spatial boundary is clear and credible, which helps to improve the spatial accuracy when predicting urban traffic congestion zoning and provides a new methodological approach for urban traffic congestion zoning and zoning boundary delineation.
Application and Optimization of the Parameters of the High-Level Boreholes in Lateral High Drainage Roadway
Authors: Shuang Haiqing , Meng Weitao , Zhai Yulong , Xiao Peng , Shi Yu , Tian Yu
Published: December 2022

The key parameters of high-level boreholes in high drainage roadways affect the gas treatment effect of the working face directly. Therefore, the layout parameters of high-level boreholes in the lateral high drainage roadway (LHDR) are determined and optimized as necessary. Based on the LHDR layout on the 2-603 working face of the Liyazhuang coal mine, the key technological requirements on high-level borehole parameters were analyzed and the distribution characteristics of the gas volume fraction in the coal roof were studied. The gas migration law in the mined-out areas was obtained and the layout locations of high-level boreholes were determined finally. The research demonstrates that the high-level boreholes lag the 2-603 working face distance and the position of the final borehole (the position of the final borehole in this paper refers to the distance between the final borehole and the roof) influence the stability of boreholes and the gas extraction effect. The distribution of the gas volume fraction from the intake airway to the return airway can be divided into the stable stage, slow growth stage, and fast growth stage. Influenced by the flow field in the mined-out areas, the mean volume fraction of the borehole-extracted gas has no obvious relationship with the gas volume fraction at the upper corner. According to the final optimization, the high-level borehole is determined as having a 15 m lag behind the working face and the position of the final borehole is 44 m away from the coal seam roof. These have been applied successfully in engineering practice.
Numerical Analysis and Experimental Study of Unsteady Flow Characteristics in an Ultra-Low Specific Speed Centrifugal Pump
Authors: Wei Yangyang , Shi Yuhui , Shi Weidong , Pan Bo
Published: December 2022

Low specific speed centrifugal pumps are widely used in urban water supply, agricultural irrigation, petrochemical and other fields due to their small flow rate and high head. Therefore, the study of unsteady flow characteristics plays a vital role in its safe and stable operation. In this paper, numerical simulation and experimental methods are used to explore the unsteady performance of the pump. The results show that the fluctuations of the external characteristic such as head, shaft power and energy loss are due to the periodic disturbance of the flow field of pump. But the transient performance of shaft power and head shows different changing trends due to different influencing factors. In this paper, the transient process of hydraulic performance is divided into three stages according to the causes and characteristics of hydraulic fluctuations. Most of the hydraulic losses occur inside the impeller, so the impeller flow field determines the level of time average hydraulic performance. Although the hydraulic loss of the spiral case is small, it is greatly affected by the rotor-stator interaction, which affects the strength of the hydraulic fluctuation. This study is of great significance to the mechanism of rotor-stator interaction and the stable operation of low specific speed centrifugal pumps.
Blockchain Changing the Outlook of the Sustainable Food Supply Chain to Achieve Net Zero?
Authors: Saha Aditi S. , Raut Rakesh D. , Yadav Vinay Surendra , Majumdar Abhijit
Published: December 2022

The food supply chain (FSC), being a complex network, faces major issues such as traceability, food security, safety and sustainability. Blockchain technology (BLCT) is regarded as an innovative technology that can transform FSC by means of its traceable, irrevocable, tamperproof network. BLCT being a new technology, little work has been carried out on the FSC domain. The purpose of the study is to examine the most recent trends, benefits, challenges, and application of BLCT in the FSC and explore the comprehensive adoption and application of BLCT, stating how it helps to achieve a triple bottom line (TBL) and net zero in the supply chain. The methodology used in this article is a systematic literature review (SLR) comprising 55 papers spanning the years 2018 to 2022. The findings of the study state that BLCT helps to achieve food safety, security, and traceability and increases the performance of the FSC. It also contributes to achieving the TBL of sustainability which can further help to achieve net zero. Based on this work’s insight and observations, practitioners and academics can better understand how companies can implement BLCT and achieve TBL benefits in the FSC, which could eventually provide a path to achieving net zero.
Trends in College–High School Wage Differentials in China: The Role of Cohort-Specific Labor Supply Shift
Authors: Wen Qiao
Published: December 2022

The wage gap between 4-year college (BA) and high school (HS) graduates narrows down among young workers from 2002 to 2009 in urban China, despite steadily increasing BA–HS wage gaps for older workers during the same time. This period corresponds to the labor market entry of a radically increasing number of college-educated labor stimulated by China’s higher education expansion program initiated in 1999. This study examines how cohort-specific relative supply of college-educated labor affects the cohort-specific college wage premiums and the overall BA–HS wage gaps in the labor market. Incorporating an aggregate labor supply model with imperfect substitution across labor with the same education level but in different age groups, changes in age-group-specific BA–HS wage gaps over time are decomposed into changes in aggregate and age-group-specific relative labor supply and demand factors. Findings suggest that the substantially expanded opportunities to attend college contribute to the falling BA–HS income inequality among young post-expansion cohorts: a 1-percent increase in the relative supply of BA-educated workers within one’s own cohorts depresses cohort-specific BA–HS wage gap by 0.2%. Policies that substantially boost educational attainment for certain cohorts could reduce education-related wage gaps for these cohorts and have spillover effects to the wage structure in the labor market.
An Analysis of the Dimensional Constructs of Green Innovation in Manufacturing Enterprises: Scale Development and Empirical Testing
Authors: Li Siqi , Li Xintao , Zhao Qingqing , Zhang Jun , Xue Haoyu
Published: December 2022

Green innovation has become an important way for manufacturing enterprises to achieve sustainable development. Existing research on green innovation mostly focuses on conceptual content, and relevant empirical studies only involve individual indicators. Systematic measurement tools are still lacking. Therefore, drawing on the theoretical framework provided by the social-ecological system, a clear definition of the connotations of green innovation and an exploration of the dimensional structure and scale development of green innovation in enterprises are the core objectives of this study. Strictly adhering to the process of scale development, four core dimensions of green innovation in enterprises are identified, and a scale with 18 items was established. The results show the following: (1) The connotations of corporate green innovation should be expanded to include not only technology and product innovation but also internal institutional innovation and external environmental innovation. (2) Green innovation in enterprises should be measured in a rigorous manner, and such measurements should follow the logic from goals to behavior. (3) The scale of green innovation should be refined, and questions should be designed to characterize specific green innovation behavior indicators. In summary, this study lays a foundation for quantitative research on green innovation in enterprises and provides a useful reference for manufacturing enterprises to improve their level of green innovation.
A New Integrated Multi-Criteria Decision-Making Model for Sustainable Supplier Selection Based on a Novel Grey WISP and Grey BWM Methods
Authors: Ulutaş Alptekin , Topal Ayşe , Pamučar Dragan , Stević Željko , Karabašević Darjan , Popović Gabrijela
Published: December 2022

Supplier selection is an important task in supply chain management, as suppliers have a vital role in the success of organisations in a supply chain. Sustainability has emerged as a solution to decreasing resources and increasing environmental and social problems in the past few decades. It has been applied to various industrial operations, one of them is supplier selection, to mitigate unwanted effects in the future. Sustainable supplier selection is a complicated multi-criteria decision making problem, including several criteria from economic, environmental, and social perspectives. To deal with subjective judgements of decision makers, fuzzy and grey methods are widely used in multi-criteria decision making, In the case of small, limited, and incomplete data, the grey theory provides satisfactory results, compared to fuzzy methods. Therefore, this study is an integrated method including grey Best-Worst Method (BWM) and grey Weighted Sum-Product (WISP) for choosing the most sustainable supplier for a textile manufacturer, which includes three main criteria and twelve sub-criteria. According to the result of the proposed model, the supplier with the best performance was determined to be the supplier with the SP2 coded. The results of the developed model were shown to the experts, and the accuracy of the results was confirmed. According to the experts, a higher amount of product can be purchased from the supplier with the SP2 code, and a tighter relationship can be worked with this supplier. The contributions of this study are: (1) Develop a new grey MCDM model called Grey WISP. (2) Create a new integrated MCDM model with grey theory, BWM, and WISP methods that can be applied to assess supplier sustainability using this hybrid model. The proposed model can be used not just for selecting sustainable suppliers, but also for any other decision problems that have multiple criteria and alternatives. The findings suggest that the Grey WISP method achieved accurate results.
Integrated Robust Optimization of Scheduling and Signal Timing for Bus Rapid Transit
Authors: Wang Jingwei , Han Yin , Li Peng
Published: December 2022

The unbalanced nature of passenger demand and the uncertainty of delay at intersections are considered critical factors in the efficiency of public transportation operations. Considering the controllable characteristics of the bus rapid transit system (BRT), an integrated optimization model that includes multi-mode transit scheduling and signal timing is proposed. The robust optimization model copes with the fluctuations in passenger demand and bus operation. A non-linear programming is developed to minimize the total passenger travel time and optimize the transit departure time, dwelling strategies at stations, and signal timings at intersections. The constraints on the signal control, degree of saturation, transit scheduling, and passenger waiting time at stations are intended to reflect real traffic conditions. A case study and extensive sensitivity analyses were conducted to evaluate the performance of the proposed model. The results show that the proposed integrated model can adjust the BRT dwelling strategies based on different passenger demands and coordinate transit departure time and signal timing adjustment to mitigate the passenger delay. Furthermore, experimental results demonstrate improvements of 5.3% and 8.1% in the mean and maximum values of passenger travel time, respectively, using the proposed model, compared to those obtained using the conventional operation strategy.
Assessment of the Chemical Reactivity of Brazilian Stone Cutting Plant Waste into Cementitious Matrices
Authors: Passos Anderson Batista , Onghero Lucas , de Matos Paulo Ricardo , Benvenuti Tatiane , Magalhães Laurence Colares , de Oliveira Antonio Pedro Novaes , Pessôa José Renato de Castro , Simão Lisandro , Souza Marcelo Tramontin
Published: December 2022

The problems generated by the ornamental stone extraction and processing industry caused by the inadequate disposal of this waste can negatively affect rivers, lakes, streams, and even natural water reservoirs. This study discusses and evaluates the potentiality and challenges of dimension stone waste (DSW) recycling generated from a Brazilian dimension stone processing industry in Portland cement formulations. Cement pastes with different amounts of DSW (10–30 wt.%), quartz (10 wt.%), and calcium carbonate (10 wt.%) were prepared and characterized in the fresh and hardened states. The results showed that DSW can be used in cement formulations, and its reactivity is governed by the size of the particles. With up to 10% DSW in place of cement, the samples had greater workability and compressive strength at 28 days compared with the reference mix. However, the strength was lower at early ages (3 and 7 days). When DSW is milled, the strength of the samples containing the waste matched the reference values at all ages, and the recommended replacement limit rose to 20%. On the other hand, the particle size reduction significantly decreased the workability. The use of DSW in cement-based formulations is encouraged due to the strong presence of stone processing and cement companies in Brazil and worldwide.
A Review on Superadsorbents with Adsorption Capacity ≥1000 mg g−1 and Perspectives on Their Upscaling for Water/Wastewater Treatment
Authors: Karunakaran Kannan , Usman Muhammad , Sillanpää Mika
Published: December 2022

An adsorbent’s properties, its adsorption chemistry, and treatment efficiency are all interlinked for water/wastewater treatment. This critical review focuses on superadsorbents possessing ultrahigh adsorption capacities of ≥1000 mg g−1 for an efficient water/wastewater treatment. Using Google Scholar, we reviewed about 63 prominent studies (2017–2022) on superadsorbents to evaluate their preparation, characteristics, adsorption chemistries, and mechanistic interactions in the removal of aqueous inorganic and organic contaminants. The major contribution of this article is to present a series of perspectives on the potential upscaling of these adsorbents in real-scale water/wastewater treatment. The main findings are as follows: (1) the current literature analysis suggests that superadsorbents hold reasonable promise to become useful materials in water treatment, (2) there is still a need to perform extensive pilot-scale adsorption studies using superadsorbents under quasi-real systems representing complex real aqueous systems, and (3) the technoeconomic analysis of their upscaling in industrial-scale water/wastewater treatments still constitutes a major gap which calls for further studies. Moreover, the mass production and effective application of these superadsorbents are the major issues for real-scale water treatments.
Can the Energy-Consumption Permit Trading Scheme Curb SO2 Emissions? Evidence from a Quasi-Natural Experiment in China
Authors: Liu Mengyao , Jiang Hongli
Published: December 2022

Energy and environmental pollution are major global challenges. This paper aims to examine the impact of China’s energy-consumption permit trading scheme (ECPT) on environmental pollution and the influence mechanisms. The study constructs provincial panel data for China from 2006 to 2020 and uses the difference-in-difference (DID) method to investigate the issue. Our results demonstrate that ECPT significantly curbs SO2 emissions, as confirmed by a series of statistical robustness tests. Specifically, the ECPT has significantly reduced SO2 by approximately 30.4%. Furthermore, the ECPT reduces SO2 emissions mainly by optimizing the structure of energy consumption and promoting technological innovation. In addition, the impact of the ECPT on SO2 emissions is more pronounced in the central and western provinces of China, and in provinces with lower levels of industrial structure and high environmental regulation intensity. This study provides a perspective from a developing country and makes an important contribution to the existing research by exploring the curbing effect of energy policy on SO2 emissions.
Urban Overheating Mitigation Strategies Opportunities: A Case Study of a Square in Rome (Italy)
Authors: Battista Gabriele , de Lieto Vollaro Emanuele , Evangelisti Luca , de Lieto Vollaro Roberto
Published: December 2022

It is well-known that the occurrence of urban heat islands (UHI) is related to climate change and urbanization. Urban locations experience local overheating throughout the summer, which is uncomfortable and it has a detrimental impact on buildings ability to consume energy. In this study, a methodology was developed to assess the urban heat island effect in a localized urban area and to evaluate the effects of different kind of mitigation strategies. The numerical model was developed using the ENVI_met tool and it was calibrated with weather data and albedo measured inside the examined area and near the simulated domain. The procedure adopted overtaking the limit of the software in reproducing accurate weather conditions without calibration. Finally, combination of extensive mitigation strategies (cool pavements, greenery, grass pavers) with local strategies (shading) were investigated. An experimental and numerical investigation of a square in Rome was exanimated to evaluate the possible solution for mitigating outdoor air temperatures. Results of the paper affirm that an intervention on the pavement albedo and the increase of vegetation inside the square, lead to an improvement of the air thermal conditions. In particular, the application of the grass pavers would lead to the greatest benefits. A maximum decrease in the air temperature of 1.2 °C was obtained through the application of cool material, while the reduction reaches up to 2.88 °C when a grass paver is applied. The improve of the vegetation can bring to a maximum decrease of 1.46 °C, while the use of shading projecting roof allows a reduction up to a maximum of 2.07 °C.
Does ESG Performance Affect Firm Value? Evidence from a New ESG-Scoring Approach for Chinese Enterprises
Authors: Yu Xiaoling , Xiao Kaitian
Published: December 2022

Proposing a new scoring method to evaluate the environmental, social, and corporate governance (ESG) performance of Chinese A-share listed companies over the period 2010–2019, this study investigates the impact of ESG on firm value, by taking Tobin’s Q, Return on Assets (ROA) and Market-to-Book ratio (MB) as proxy variables for firm value. We find a significantly positive relationship between ESG composite performance and firm value, which supports the stakeholder theory. This result can hold when we carry out robustness checks, i.e., changing dependent variable, instrument variable (IV) regression, and Heckman’s two-stage estimation. When an existing social responsibility rating (Hexun’s CSR scores) is taken as the proxy of ESG performance, the main conclusion also keeps in line. For the three sub-dimensions, the positive impact of environmental (E) and social (S) performance on firm value can hold, while that of corporate governance (G) cannot pass all the robustness tests. In terms of heterogeneity, there is evidence that the enhancement effect of ESG on firm value for state-owned companies is stronger than that for non-state-owned companies. Besides, the enhancement effect is significant for the non-key pollution-monitored firms but insignificant for the key pollution-monitored firms.
Energy Production from Cattle Manure within a Life Cycle Assessment Framework: Statistical Optimization of Co-Digestion, Pretreatment, and Thermal Conditions
Authors: Albalate-Ramírez Alonso , Alcalá-Rodríguez Mónica María , Miramontes-Martínez Luis Ramiro , Padilla-Rivera Alejandro , Estrada-Baltazar Alejandro , López-Hernández Brenda Nelly , Rivas-García Pasiano
Published: December 2022

Waste to energy processes from anaerobic digestion (WtE-AD) from cattle manure (CM) have low CH4 yields due to CM’s structural composition. The search for alternatives to increase the energy yields of these processes must consider the optimization of operating parameters within a framework of mitigating the environmental footprint. The goal of this paper is to provide a statistical optimization strategy based on experimental designs to improve CH4 yields and reduce the environmental profile of CM valorization through a WtE-AD process. Biochemical methane potential tests were conducted to determine the energetic and environmental effects that alkaline pretreatments, different AD temperatures, and co-digestion formulations with fruit and vegetable waste (FVW) have on the WtE-AD process from CM. The evaluation was conducted following a life cycle assessment approach through energy balances. The results indicate that the highest CH4 yield (384.3 mL CH4 g VS−1) and the lowest environmental impact (−0.06 kg CO2 eq kWh−1 of electricity production) were achieved with the co-digestion of CM with FVW 1:1, pretreatment with 10 g NaOH 100 g−1 of VS of CM, and a temperature of 45 °C. It was found that the CM pretreatment with NaOH substantially increases the energy profile of the WtE-AD process without compromising the environmental impact since greenhouse gas emissions in chemical production are negligible.
Spatial and Temporal Evolution Characteristics of China’s City Size Distribution Based on New Criteria
Authors: Hong Ge , Xie Shouhong , Li Hanbing
Published: December 2022

The distribution and evolution of city size are critical for town layout optimization. Based on the most recent classification standards and census data for 2010 and 2020, this paper aims to explore China’s city size distribution above the prefecture level. Using the rank-size law, Kernel density estimation, Spatial Gini coefficient, and Markov transition matrix, the newest city size distribution characteristics and spatial evolution patterns in China are shown from national and regional viewpoints. Our main findings are as follows: (1) Over the period from 2010 to 2020, China’s city size distribution follows the rank-size law but deviates from Zipf’s ideal. The distribution of city size is centralized in general. (2) China’s city-size hierarchy exhibits a good “olive” structure, with fewer megacities but larger populations. The growth rate of small and medium-sized cities is higher than the number of medium-sized cities. (3) China’s cities have grown greatly in size, with more than a third of them expanding. Over the last decade, high-ranking cities have become the primary driver of change. (4) There are disparities in city size between regions. A diminishing trend can be seen in three key economic zones.