bluuebunny/crossref_metadata_2025 huggingface dataset:
Air Pollution Detection Using a Novel Snap-Shot Hyperspectral Imaging Technique
Authors: Mukundan Arvind , Huang Chia-Cheng , Men Ting-Chun , Lin Fen-Chi , Wang Hsiang-Chen
Published: August 2022

Air pollution has emerged as a global problem in recent years. Particularly, particulate matter (PM2.5) with a diameter of less than 2.5 μm can move through the air and transfer dangerous compounds to the lungs through human breathing, thereby creating major health issues. This research proposes a large-scale, low-cost solution for detecting air pollution by combining hyperspectral imaging (HSI) technology and deep learning techniques. By modeling the visible-light HSI technology of the aerial camera, the image acquired by the drone camera is endowed with hyperspectral information. Two methods are used for the classification of the images. That is, 3D Convolutional Neural Network Auto Encoder and principal components analysis (PCA) are paired with VGG-16 (Visual Geometry Group) to find the optical properties of air pollution. The images are classified into good, moderate, and severe based on the concentration of PM2.5 particles in the images. The results suggest that the PCA + VGG-16 has the highest average classification accuracy of 85.93%.
Wireless Measurements Using Electrical Impedance Spectroscopy to Monitor Fracture Healing
Authors: Fukase Naomasa , Duke Victoria R. , Lin Monica C. , Stake Ingrid K. , Huard Matthieu , Huard Johnny , Marmor Meir T. , Maharbiz Michel M. , Ehrhart Nicole P. , Bahney Chelsea S. , Herfat Safa T.
Published: August 2022

There is an unmet need for improved, clinically relevant methods to longitudinally quantify bone healing during fracture care. Here we develop a smart bone plate to wirelessly monitor healing utilizing electrical impedance spectroscopy (EIS) to provide real-time data on tissue composition within the fracture callus. To validate our technology, we created a 1-mm rabbit tibial defect and fixed the bone with a standard veterinary plate modified with a custom-designed housing that included two impedance sensors capable of wireless transmission. Impedance magnitude and phase measurements were transmitted every 48 h for up to 10 weeks. Bone healing was assessed by X-ray, µCT, and histology. Our results indicated the sensors successfully incorporated into the fracture callus and did not impede repair. Electrical impedance, resistance, and reactance increased steadily from weeks 3 to 7—corresponding to the transition from hematoma to cartilage to bone within the fracture gap—then plateaued as the bone began to consolidate. These three electrical readings significantly correlated with traditional measurements of bone healing and successfully distinguished between union and not-healed fractures, with the strongest relationship found with impedance magnitude. These results suggest that our EIS smart bone plate can provide continuous and highly sensitive quantitative tissue measurements throughout the course of fracture healing to better guide personalized clinical care.
High-Precision Real-Time Detection of Blast Furnace Stockline Based on High-Dimensional Spatial Characteristics
Authors: Liu Pan , Chen Zhipeng , Gui Weihua , Yang Chunhua
Published: August 2022

The real-time, continuity, and accuracy of blast furnace stockline information are of great significance in reducing energy consumption and improving smelting efficiency. However, the traditional mechanical measurement method has the problem of measuring point discontinuity, while the radar measurement method exhibits problems such as weak anti-interference ability, low accuracy, and poor stability. Therefore, a high-dimensional, spatial feature stockline detection method based on the maximum likelihood radial basis function model (MLRBFM) and structural dynamic self-optimization RBF neural network (SDSO-RBFNN) is proposed. Firstly, the discrete time series joint partition method is used to extract the time dimension periodic features of the blast furnace stockline. Based on MLRBFM, the high-dimensional spatial features of the stockline are then obtained. Finally, an SDSO-RBFNN is constructed based on an eigen orthogonal matrix and a right triangular matrix decomposition (QR) direct clustering algorithm with spatial–temporal features as input, so as to obtain continuous, high-precision stockline information. Both the simulation results and industrial validation indicate that the proposed method can provide real-time and accurate stockline information, and has great practical value for industrial production.
ResNet-AE for Radar Signal Anomaly Detection
Authors: Cheng Donghang , Fan Youchen , Fang Shengliang , Wang Mengtao , Liu Han
Published: August 2022

Radar signal anomaly detection is an effective method to detect potential threat targets. Given the low Accuracy of the traditional AE model and the complex network of GAN, an anomaly detection method based on ResNet-AE is proposed. In this method, CNN is used to extract features and learn the potential distribution law of data. LSTM is used to discover the time dependence of data. ResNet is used to alleviate the problem of gradient loss and improve the efficiency of the deep network. Firstly, the signal subsequence is extracted according to the pulse’s rising edge and falling edge. Then, the normal radar signal data are used for model training, and the mean square error distance is used to calculate the error between the reconstructed data and the original data. Finally, the adaptive threshold is used to determine the anomaly. Experimental results show that the recognition Accuracy of this method can reach more than 85%. Compared with AE, CNN-AE, LSTM-AE, LSTM-GAN, LSTM-based VAE-GAN, and other models, Accuracy is increased by more than 4%, and it is improved in Precision, Recall, F1-score, and AUC. Moreover, the model has a simple structure, strong stability, and certain universality. It has good performance under different SNRs.
Silicon Cantilever for Micro/Nanoforce and Stiffness Calibration
Authors: Frühauf Joachim , Gärtner Eva , Li Zhi , Doering Lutz , Spichtinger Jan , Ehret Gerd
Published: August 2022

The paper deals with cantilevers made from monocrystalline silicon by processes of microtechnology. The cantilevers are passive structures and have no transducers. The application as a material measure for the inspection of stylus forces is in the center of investigations. A simple method is the measurement of the deflection of the cantilever at the position of load by the force if the stiffness of the cantilever at this position is known. Measurements of force–deflection characteristics are described and discussed in context with the classical theory of elastic bending. The methods of determining the stiffness are discussed together with results. Finally, other methods based on tactile measurements along the cantilever are described and tested. The paper discusses comprehensively the properties of concrete silicon chips with cantilevers to underpin its applicability in industrial metrology. The progress consists of the estimation of the accuracy of the proposed method of stylus force measurement and the extraction of information from a tactile measured profile along the silicon cantilever. Furthermore, improvements are proposed for approaches to an ideal cantilever.
Infrared Target Detection Based on Joint Spatio-Temporal Filtering and L1 Norm Regularization
Authors: Xu Enyong , Wu Anqing , Li Juliu , Chen Huajin , Fan Xiangsuo , Huang Qibai
Published: August 2022

Infrared target detection is often disrupted by a complex background, resulting in a high false alarm and low target recognition. This paper proposes a robust principal component decomposition model with joint spatial and temporal filtering and L1 norm regularization to effectively suppress the complex backgrounds. The model establishes a new anisotropic Gaussian kernel diffusion function, which exploits the difference between the target and the background in the spatial domain to suppress the edge contours. Furthermore, in order to suppress the dynamically changing background, we construct an inversion model that combines temporal domain information and L1 norm regularization to globally constrain the low rank characteristics of the background, and characterize the target sparse component with L1 norm. Finally, the overlapping multiplier method is used for decomposition and reconstruction to complete the target detection.Through relevant experiments, the proposed background modeling method in this paper has a better background suppression effect in different scenes. The average values of the three evaluation indexes, SSIM, BSF and IC, are 0.986, 88.357 and 18.967, respectively. Meanwhile, the proposed detection method obtains a higher detection rate compared with other algorithms under the same false alarm rate.
A Comprehensive “Real-World Constraints”-Aware Requirements Engineering Related Assessment and a Critical State-of-the-Art Review of the Monitoring of Humans in Bed
Authors: Kyamakya Kyandoghere , Tavakkoli Vahid , McClatchie Simon , Arbeiter Maximilian , Scholte van Mast Bart
Published: August 2022

Currently, abnormality detection and/or prediction is a very hot topic. In this paper, we addressed it in the frame of activity monitoring of a human in bed. This paper presents a comprehensive formulation of a requirements engineering dossier for a monitoring system of a “human in bed” for abnormal behavior detection and forecasting. Hereby, practical and real-world constraints and concerns were identified and taken into consideration in the requirements dossier. A comprehensive and holistic discussion of the anomaly concept was extensively conducted and contributed to laying the ground for a realistic specifications book of the anomaly detection system. Some systems engineering relevant issues were also briefly addressed, e.g., verification and validation. A structured critical review of the relevant literature led to identifying four major approaches of interest. These four approaches were evaluated from the perspective of the requirements dossier. It was thereby clearly demonstrated that the approach integrating graph networks and advanced deep-learning schemes (Graph-DL) is the one capable of fully fulfilling the challenging issues expressed in the real-world conditions aware specification book. Nevertheless, to meet immediate market needs, systems based on advanced statistical methods, after a series of adaptations, already ensure and satisfy the important requirements related to, e.g., low cost, solid data security and a fully embedded and self-sufficient implementation. To conclude, some recommendations regarding system architecture and overall systems engineering were formulated.
Cellulose Nanofiber Films and Their Vibration Energy Harvesting
Authors: Lee Seok-Hyun , Kim Jaehwan
Published: August 2022

Cellulose, the most abundant sustainable material on Earth, has excellent mechanical and physical properties, high optical transparency, biocompatibility, and piezoelectricity. So, it has many possibilities for future materials, and many researchers are interested in its application. In this paper, cellulose nanofiber (CNF) and CNF/polyvinyl alcohol (PVA) films are made, and their vibration energy harvesting is studied. CNF was isolated by chemical and physical methods, and the CNF suspension was cast on a flat substrate to make a film. A cast CNF wet film stayed in a 5 Tesla superconductor magnet for 7 days, which resulted in CNF alignment perpendicular to the magnetic field. To further improve the mechanical properties of the CNF film, mechanical stretching was applied. The CNF suspension was mixed with PVA, giving the film toughness. The cast CNF/PVA wet film was mechanically stretched and dried, which improved the CNF alignment. The fabricated CNF and CNF/PVA films were characterized using scanning electron microscopy and X-ray diffraction to verify the alignment. By stretching, the aligned CNF/PVA film exhibits the largest mechanical properties along the aligned direction. The maximum Young’s modulus and tensile strength of the 50% stretched CNF/PVA film are 14.9 GPa and 170.6 MPa, respectively. Finally, a vibration energy harvesting experiment was performed by invoking the piezoelectric behavior of the pure CNF, and 50% stretched CNF/PVA films. The harvester structure was innovated by adopting a cymbal structure, which was beneficial to producing large in-plane strain on the films. The designed cymbal structure was analyzed using ANSYS, and its natural frequency was experimentally verified. The CNF/PVA film performs better vibration energy harvesting than the pure CNF film. The CNF/PVA film is applicable for biocompatible and flexible vibration energy harvesting.
Spectral Reflectance Recovery from the Quadcolor Camera Signals Using the Interpolation and Weighted Principal Component Analysis Methods
Authors: Wen Yu-Che , Wen Senfar , Hsu Long , Chi Sien
Published: August 2022

The recovery of surface spectral reflectance using the quadcolor camera was numerically studied. Assume that the RGB channels of the quadcolor camera are the same as the Nikon D5100 tricolor camera. The spectral sensitivity of the fourth signal channel was tailored using a color filter. Munsell color chips were used as reflective surfaces. When the interpolation method or the weighted principal component analysis (wPCA) method is used to reconstruct spectra, using the quadcolor camera can effectively reduce the mean spectral error of the test samples compared to using the tricolor camera. Except for computation time, the interpolation method outperforms the wPCA method in spectrum reconstruction. A long-pass optical filter can be applied to the fourth channel for reducing the mean spectral error. A short-pass optical filter can be applied to the fourth channel for reducing the mean color difference, but the mean spectral error will be larger. Due to the small color difference, the quadcolor camera using an optimized short-pass filter may be suitable as an imaging colorimeter. It was found that an empirical design rule to keep the color difference small is to reduce the error in fitting the color-matching functions using the camera spectral sensitivity functions.
A Fast Point Cloud Recognition Algorithm Based on Keypoint Pair Feature
Authors: Ge Zhexue , Shen Xiaolei , Gao Quanqin , Sun Haiyang , Tang Xiaoan , Cai Qingyu
Published: August 2022

At present, PPF-based point cloud recognition algorithms can perform better matching than competitors and be verified in the case of severe occlusion and stacking. However, including certain superfluous feature point pairs in the global model description would significantly lower the algorithm’s efficiency. As a result, this paper delves into the Point Pair Feature (PPF) algorithm and proposes a 6D pose estimation method based on Keypoint Pair Feature (K-PPF) voting. The K-PPF algorithm is based on the PPF algorithm and proposes an improved algorithm for the sampling point part. The sample points are retrieved using a combination of curvature-adaptive and grid ISS, and the angle-adaptive judgment is performed on the sampling points to extract the keypoints, therefore improving the point pair feature difference and matching accuracy. To verify the effectiveness of the method, we analyze the experimental results in scenes with different occlusion and complexity levels under the evaluation metrics of ADD-S, Recall, Precision, and Overlap rate. The results show that the algorithm in this paper reduces redundant point pairs and improves recognition efficiency and robustness compared with PPF. Compared with FPFH, CSHOT, SHOT and SI algorithms, this paper improves the recall rate by more than 12.5%.
Scaled Sea Surface Design and RCS Measurement Based on Rough Film Medium
Authors: Guo Chenyu , Ye Hongxia , Zhou Yi , Xu Yonggang , Wang Longxiang
Published: August 2022

The electromagnetic (EM) scattering characteristics of the rough sea surface is very important for target surveying and detection in a sea environment. This work proposes a scaled sea surface designing method based on a rough thin-film medium. For the prototype sea surface, the permittivity is calculated with the seawater temperature, salinity, and EM wave frequency according to the Debye model. The scale film material is mixed with carbon black and epoxy, whose volume ratio is optimized with the genetic algorithm through the existing electromagnetic parameter library. This method can overcome the previous difficulties of adjusting the same permittivity of the prototype sea water. According to the EM scaled theory, the scaled geometric sample is numerically generated with the D-V spectrum for the given wind speed, and is fabricated using 3D printing to keep the similar seawater shape. Then, the sample is sprayed with a layer of film material for EM scattering measurement. The simulated and measured radar cross-section (RCS) results show good consistency for the prototype seawater and scaled materials, which indicates the proposed scaled method is a more efficient method to get the seawater scattering characteristics.
Reported User-Generated Online Hate Speech: The ‘Ecosystem’, Frames, and Ideologies
Authors: Šori Iztok , Vehovar Vasja
Published: August 2022

The spread of hate speech challenges the health of democracy and media systems in contemporary societies. This study aims to contribute to a better understanding of user-generated online hate speech reported by Internet users to national monitoring organizations, in particular its ‘ecosystem‘, discursive elements, and links to political discourses. First, we analyzed the main characteristics of the reported statements (source, removal rate, and targets) to reveal the media and political context of reported user-generated online hate speech. Next, we focused on hate speech statements against migrants and analyzed their discursive elements with the method of critical frame analysis (frames, actors, metaphors, and references) to understand the corresponding discourse. The main discursive feature of these statements is the prognosis, which calls for death and violence, so we could label this communication as ‘executive speech.’ Other key features are references to weapons and Nazi crimes from WWII, indicating the authors’ extreme-right ideological convictions, and the metaphors, employed to provoke disgust from migrants, present them as culturally inferior and raise fears about their supposed violent behavior. The corresponding diagnoses frame migrants as a threat in a similar way to populist political discourses of othering and complement these in providing ‘final’ solutions in prognoses.
Poland on the Path towards Sustainable Development—A Multidimensional Comparative Analysis of the Socio-Economic Development of Polish Regions
Authors: Barska Anetta , Jędrzejczak-Gas Janina , Wyrwa Joanna
Published: August 2022

The aim of the paper is to conduct research and present the results of a taxonomic analysis assessing the 2019 and 2020 implementations of socio-economic sustainability goals in the Lubuskie Province as compared with other Polish regions. To this end, a multidimensional comparative analysis was performed to determine the level of socio-economic development of the Lubuskie Province and then benchmark it against other regions in the context of sustainable development. The research was based on independent indicators developed with the use of linear ordering methods and accounting for aspects of socio-economic development such as the economic potential, innovation of the economy, sustainable production patterns, demographic changes, job market, and social integration. Synthetic measures were developed with the use of the proposed partial indicators (independent variables), which, according to the authors, best illustrate the socio-economic development and sustainability at the regional level. The regions were then grouped by level of economic development, and the groupings were assessed for their performance. The research shows that in 2020, compared to 2019, the overall level of economic development deteriorated in all Polish regions, but the pandemic has so far had significantly less impact on the social area.
Strategic Entrepreneurship Mindset, Strategic Entrepreneurship Leadership, and Entrepreneurial Value Creation of SMEs in East Java, Indonesia: A Strategic Entrepreneurship Perspective
Authors: Farida Florentina Anif , Hermanto Yustinus Budi , Paulus Ardianus Laurens , Leylasari Herdina Tyas
Published: August 2022

This study investigates theories from the strategic entrepreneurship literature related to strategic entrepreneurship mindset, strategic entrepreneurship leadership, and entrepreneurial value creation. A sample of 85 SMEs was taken from the SME sector in East Java, Indonesia, using a non-probability sampling method with a purposive sampling technique. The data collection process was a survey with questionnaires distributed directly to the SME owners. The data analysis was carried out using a structural equation measurement model (PLS-SEM) and included outer model analysis, inner model analysis, mediation testing, and hypothesis testing. This study contributes to the strategic entrepreneurship leadership variable, which is a mediating variable. The study confirms this theory for SMEs to provide broader scientific ideas related to strategic entrepreneurship theory. The small and medium-sized enterprises (SMEs) that were looked at can create entrepreneurial value through benefits and added value for individuals, organizations, and the social environment. This can contribute to progress and sustainability, which will help the economy in Indonesia and give decision-makers more information.
On Using Deep Artificial Intelligence to Automatically Detect Apple Diseases from Leaf Images
Authors: Fraiwan Mohammad , Faouri Esraa , Khasawneh Natheer
Published: August 2022

Plant diseases, if misidentified or ignored, can drastically reduce production levels and harvest quality. Technology in the form of artificial intelligence applications has the potential to facilitate and improve the disease identification process, which in turn will empower prompt control. More specifically, the work in this paper addressed the identification of three common apple leaf diseases—rust, scab, and black rot. Twelve deep transfer learning artificial intelligence models were customized, trained, and tested with the goal of categorizing leaf images into one of the aforementioned three diseases or a healthy state. A dataset of 3171 leaf images (621 black rot, 275 rust, 630 scab, and 1645 healthy) was used. Extensive performance evaluation revealed the excellent ability of the transfer learning models to achieve high values (i.e., >99%) for F1 score, precision, recall, specificity, and accuracy. Hence, it is possible to design smartphone applications that enable farmers with poor knowledge or limited access to professional care to easily identify suspected infected plants.
Integrating Citizens’ Importance-Performance Aspects into Sustainable Plastic Waste Management in Danang, Vietnam
Authors: Phan Thi Thanh Thuy , Nguyen Van Viet , Nguyen Hong Thi Thu , Lee Chun-Hung
Published: August 2022

Plastic pollution is a matter of deep concern that requires an urgent and international response, involving stakeholders at all levels. The rapid increase of single-use plastic and medical waste, especially in the context of COVID-19, has caused a drastic progression in the plastic pollution crisis on a global scale. To identify an efficient plastic waste management (PWM) system to tackle this major environmental problem, this study adopted importance-performance analysis and used logistic regression to identify key factors affecting citizens’ behavior to participate in PWM strategies in Vietnam. The results indicate that while the importance of all PWM solutions was considered to be high, their performance was rated at a low level, implying a sizable gap between perceived importance and performance of eleven solutions for PWM. The findings also show that solutions such as “offering zero-waste lifestyle seminars to citizens”, “having community engagement”, “using eco-friendly products”, and “imposing a ban on single-use plastics” are useful for the development of an effective environmental policy. Furthermore, it was found that the following characteristics have a significant influence on citizens’ participation in PWM solutions: (1) gender, (2) education level, (3) residential area, (4) employment status, and (5) citizens’ awareness and behavior towards plastic reduction. This study is expected to provide theoretical and empirical evidence for policymakers and authorities who are in charge of promulgating the necessary mechanisms and policies to promote the socialization of PWM.
Understanding the Effects of Virtual Reality System Usage on Spatial Perception: The Potential Impacts of Immersive Virtual Reality on Spatial Design Decisions
Authors: Azarby Sahand , Rice Arthur
Published: August 2022

The main component of any Virtual Reality (VR) system is the human user. The ways in which a VR system shapes human experience can affect design outcomes. This research explores the differences in spatial perception between an immersive Virtual Reality Interactive Environment (IVRIE) and traditional Virtual Reality (also known as a desktop-based Virtual Reality system, abbreviated herein as the DT system). Spatial perception and the cognition of the spatial factors of virtual spaces were studied based on different features of the two systems, including the sense of immersion, forms of interaction, experience of human scale, and movement through virtual spaces. This study focused on determining how users’ spatial decision making and performance were affected by differences in spatial perception created by the IVRIE and DT systems. Factors examined included the differences between and within the two virtual systems, based on differences in texture, system usage sequence, and the complexity of the experiential/spatial guidelines. Descriptive and inferential statistical testing using quantitative and qualitative data were used to find differences in spatial perception and decision making. The results showed significant space size variations produced by participants between and within the two different VR systems.
Treatment of Wastewater from a Grass Carp Pond with Multiple-Batch Forward Osmosis by Using Sucrose as a Draw Solution
Authors: Xu Yuliang , Cheng Xia , Du Jianghui
Published: August 2022

Forward osmosis (FO), a green and economical membrane technology driven by a natural concentration gradient, has attracted increasing attention for wastewater treatment because it consumes less energy and removes large amounts of pollutants. In this research, an approach based on an FO mechanism that could improve the concentration of organic pollutants in wastewater collected from grass carp ponds was proposed. The wastewater serving as a feed solution (FS) was concentrated by FO, and sucrose was used as a draw solution (DS). The multiple chemical oxygen demand (COD) variation, the water flux, and the reverse solute flux during the FO process were investigated. The results indicated that the water flux and the reverse solute flux had similar trends in the processing of batch experiments 1–8, and the concentrating multiple of organic contaminants reached a maximum of 3.5 in the whole study. In addition, membrane fouling was studied via a scanning electron microscope (SEM), and a loose cake layer was deposited on the membrane surface. Moreover, findings from energy dispersive scanning (EDS) analysis showed that the fouling substances in the support layer of the membrane were mainly organic compounds and silica. In contrast, the dominant contaminants of the active layer contained several microelements (such as K and Ca) in addition to organic compounds. Three-dimensional (3D) fluorescence analysis confirmed that the FS components could enter the DS and the chemical components of the sucrose solution could also enter the FS. The findings of this study provide a new view on selecting a DS and protecting the aquaculture environment.
Multidisciplinary and Transdisciplinary Collaboration in Nature-Based Design of Sustainable Architecture and Urbanism
Authors: Butt Anosh Nadeem , Dimitrijević Branka
Published: August 2022

Multidisciplinary, interdisciplinary, and transdisciplinary collaboration (TDC) continue to address complex societal problems such as sustainable development, global environmental change, and public health challenges. Nature-based design (NBD) methods including biomimicry, biomorphism, biophilia, bio-utilization and zoomorphism are essential for the design of the sustainable built environment (SBE). Currently, there is no transdisciplinary collaboration framework (TCF) to support the NBD of the SBE. The first step to fill this gap is through systematically exploring the applications of multidisciplinary research (MDR) in building design and by conducting a case study on the challenges to the MDR in the application of NBD methods for the SBE in the Faculty of Engineering and the Faculty of Science at the University of Strathclyde, Glasgow, UK. The systematic literature review and the survey results of academics on MDR collaboration showed a lack of transdisciplinary research (TDR) due to limited communication between disciplines. The research findings showed a lack of communication between academia and the Architecture, Engineering, and Construction (AEC) industry to advance NBD innovations for the SBE. The findings indicated that a TCF for research on NBD is needed to support knowledge exchange within academia and with industry for reducing the negative impacts of the building industry. Findings from the current research and future research will be used to develop and test a general TCF and then to develop a TCF for the NBD of the SBE aligned with the RIBA Plan of Work.
Analysis of Countercyclical Policy Factors in The Era of the COVID-19 Pandemic in Financial Statement Fraud Detection of Banking Companies in Indonesia
Authors: Soepriyanto Gatot , Meiryani  , Ikhsan Ridho Bramulya , Rickven Leony
Published: August 2022

This research is motivated by the application of countercyclical policy, such as credit restructuring, by banking companies during the COVID-19 pandemic. The credit restructuring that the banks carried out had the potential to affect their financial performance and increase the tendency of financial statement manipulations. The purpose of this study is to review the significance of the changes in banks’ financial performance before and after the implementation of the credit restructuring, as well as its relationship to the potential for fraudulent financial statements. The population in this study was the financial sector companies listed on the Indonesia Stock Exchange in 2020, a total of 105 companies. The 96 samples consisted of 32 banking companies in the commercial banking category that have implemented countercyclical policies in the form of credit restructuring during the COVID-19 pandemic. The research method was a quantitative method using secondary data obtained from the official website of the Indonesia Stock Exchange and the official websites of the related companies. The results showed no significant change in the banks’ financial performance. Although the credit restructuring had an impact, such as a decrease in their profits, it did not encourage them to manipulate their financial statements.
A Coupling Mechanism and the Measurement of Science and Technology Innovation and Rural Revitalization Systems
Authors: Guo Caiyun , Zhang Yujing , Liu Zhiqiang , Li Na
Published: August 2022

Under the concept of scientific and technological progress and new rural development, the relationship between scientific and technological innovation and rural revitalization is becoming closer and closer. The purpose of this study is to reveal the coupling coordination mechanism between the two and promote agricultural and rural construction and regional high-quality development through quantitative analysis and scientific decision making. This paper analyzes the systematic coupling mechanism of scientific and technological innovation and rural revitalization. An evaluation index system coupled with a coordination measure model and grey prediction GM (1,1) model are constructed. We demonstrate the implementation process of these models using data from Hebei province from 2010 to 2019. According to the application results, some suggestions for policy and measures are put forward. The results verify the coupling and coordination relationship between the two and the feasibility of the method. The results show that the state of coupling coordination of scientific and technological innovation and rural revitalization systems in Hebei province has transitioned from a mild imbalance to the primary coordination stage, and it is predicted that it will reach good coordination in 2024. This study provides theoretical and methodological support for the coupling coordination between regional scientific and technological innovation and rural revitalization and can serve as a useful reference for similar regional rural construction.
Energy Consumption Analysis Using Measured Data from a Net-Zero Energy Commercial Building in a Cold and Dry Climate
Authors: Oh Sukjoon , Gardner John F.
Published: August 2022

Zero-energy buildings have a critical role in reducing global energy use and greenhouse gas emissions. However, few studies have analyzed net-zero energy commercial buildings using measured energy use such as whole-building level and end-use level data. This paper presents an energy consumption analysis for the first net-zero energy commercial building in Idaho, U.S., in a cold and dry climate using measured end-use data from this building as well as measured whole-building energy use. Monthly bill data analysis, end-use data analysis, and Energy Use Intensity (EUI) analysis were conducted. The combined analysis of this study shows that the HVAC system was the most sensitive to the outside air temperature, showing different energy use percentages of 48.4%, 35.1% (the heating period), 21.6% (the weather-independent period), and 33.4% (the cooling period), respectively. Lighting had the highest percentage of 35.2% for the weather-independent period. The PV electricity generation was higher than the building electricity use, except from December 2017 to February 2018, and the building was net-positive from an energy perspective. The calculated EUI of the building was 34.2 kWh/m2·y, which can be compared to the EUIs of other net zero energy buildings. The approaches developed in this study can be useful for analyzing several net zero buildings by different weather profiles.
Digital Ecosystem Model for GIAHS: The Barroso Agro-Sylvo-Pastoral System
Authors: Martins José , Gonçalves Catarina , Silva Jani , Gonçalves Ramiro , Branco Frederico
Published: August 2022

Globally Important Agricultural Heritage Systems (GIAHS) territories are highly relevant to achieving sustainable lifestyles with human subsistence in balance with the ecosystem. The Barroso agro-sylvo-pastoral system is a clear example of this alignment between existing society, nature and natural resources, the environment, landscapes, and contextual heritage. Moreover, the sustainable use of existing natural resources, excellent environmental conditions, and breath-taking untouched landscapes represent a truly relevant factor towards the development of a region economy that is still greatly influenced by an engraved cultural, patrimonial, and agricultural heritage. Given the GIAHS classification attributed to that territory, the need arises to guarantee the existing environmental conditions. This context will allow the maintenance of the GIAHS classification, ensuring the quality of life in the region and stimulating its socio-economic development and overall sustainability. The present article describes a proposal for a digital ecosystem model aimed at the Barroso GIAHS, composed of four main functional hubs that actively interact with each other: smart environment, smart government, smart economy, and smart people. Based on wireless sensor networks, IoT, artificial intelligence, data analytics, and other technological solutions, this solution will allow real-time control of the territory’s environmental conditions and develop more efficient and well-supported management and governance.
Convergence Evaluation of Sports and Tourism Industries in Urban Agglomeration of Guangdong–Hong Kong–Macao Greater Bay Area and Its Spatial-Temporal Evolution
Authors: Yuan Jun , Zhou Yaokai , Liu Yanhong
Published: August 2022

The convergence of sports and tourism industries is a vital direction for the coordinated development of industries, and a vital means to build a quality life circle suitable for living, working and traveling in the urban agglomeration of the Guangdong–Hong Kong–Macao Greater Bay Area (GBA). By using the coupling coordination degree model and exploratory spatial data analysis and establishing an evaluating indicator system for the converged development of sports and tourism industries, this paper measures and analyzes the convergence development level, spatial-temporal evolution, and spatial correlation of the two industries in 11 cities of GBA from 2011 to 2020. The results showed that the synthetical development level of the two industries in urban agglomeration of GBA was steadily rising, with significant differences in regional development, showing the east coast of GBA > the north coast of GBA > the west coast of GBA. The growth trend of industrial convergence degree is obvious, but the overall coupling coordination degree is not high, basically in the late maladjustment stage and transition stage. The convergence of the two industries shows a positive aggregation distribution in space, and the degree of agglomeration is rising. Cities around the Pearl River Estuary mostly belong to the “high-high” spatial association type, with obvious spillover effect, and become a significant growth pole for the converged development of the two industries in GBA. Cities in the periphery of GBA and the west coast of GBA mostly belong to the “low-low” and “low-high” spatial association types. Finally, sustainable development strategies are put forward from four aspects: spatial layout coordination, industrial division coordination, exchange platform coordination, and regional policy coordination, so as to promote the highly converged and coordinated development of the sports and tourism industries in the urban agglomeration of GBA.
A Study on the Classification of a Mirror Entry in the European List of Waste: Incineration Bottom Ash from Municipal Solid Waste
Authors: Bandarra Beatriz S. , Silva Sónia , Pereira Joana L. , Martins Rui C. , Quina Margarida J.
Published: August 2022

In the European Union (EU), waste is classified according to the List of Waste (LoW) and relying on the assessment of 15 hazardous properties (HPs). Incineration bottom ash (IBA) from municipal solid waste is a mirror entry in the LoW, which leads to extremely different management options within the EU. IBA has shown potential for different applications under a circular economy perspective, contributing both to avoiding waste landfilling and the consumption of natural resources, such as sand and gravel. In this context, IBA evaluation and classification play a significant role in understanding which protection measures should be taken. This work aims to present an assessment of the 15 HPs and the consequent classification of IBA using data from the industry. Each HP is assessed based on knowledge of waste, chemical composition considering concentration limits for hazardous substances, and/or through tests (chemical, physical, or biological). According to the criteria followed, 5 out of 6 samples from a Portuguese Waste-to-Energy plant were considered non-hazardous. Only one sample was classified as hazardous due to the assignment of HP 10, which resulted from Pb content (0.36%) above the concentration limit established for this property (0.3%). Nonetheless, although most hazardous entries in the LoW have this classification based on HP 14, the results obtained for the samples of this work seem to indicate IBA from this study is non-ecotoxic. Moreover, it has been suggested that IBA could possibly achieve the End-of-Waste status according to the Waste Framework Directive. For such purpose, clear criteria should be laid down to safely use the material, and testing is a crucial step.
The Spatial and Temporal Distribution of High-Quality Urbanization Development in Yellow River Basin Provinces
Authors: An Xiaowei , Li Ying , Wang Lunyan , Dong Guanghua , Dai Boxin , Liang Mengxuan
Published: August 2022

The high-quality development of urbanization is strategically important for the sustainable economic and social development in the Yellow River Basin. It is necessary to establish a system of indicators to evaluate the high-quality development in terms of five aspects: innovation, coordination, green, openness and sharing. Spatial autocorrelation, local Moran indices and cluster analysis are used to study the spatial–temporal distribution of high-quality urbanization development in each province. The results indicate that the urbanization level of nine provinces in the Yellow River Basin showed an increasing trend from 2010 to 2018. However, the development of the five dimensions is not balanced. At the same time, the level of high-quality urbanization development in the Yellow River Basin has not shown significant spatial clustering characteristics and has not formed a good interactive relationship and aggregation effects. It is of great practical importance to promote the coordinated development of urbanization and the high quality of urbanization. The problems existing in the current development are found, and effective measures are proposed to make the urbanization development adapt to the economic and social development.
Method for Assessing the Soundscape in a Marine Artificial Environment
Authors: Benocci R. , Asnaghi E. , Bisceglie A. , Lavorano S. , Galli P. , Roman H. E. , Zambon G.
Published: August 2022

We applied standard acoustic methods to record, analyze and compare anthropogenic and biological signals belonging to the soundscape of artificial marine habitats. The study was conducted on two tanks located at the Acquario di Genova (Italy), the “Red Sea” and the “Tropical Lagoon” tanks, which represent different living environments hosting a variety of species and background sounds. The use of seven eco-acoustic indices, whose time series spanned the entire period of study, allowed the characterization of the environments. We investigated the extent to which eco-acoustic indices might describe the soundscape in an artificial marine environment surrounded by a background of mechanical noise, overlapping the diurnal/nocturnal fish chorusing produced by soniferous species. Three specific types of sounds emerged: (1) mechanical ones produced by the life-support system of the tanks; (2) anthropic origin ones due to maintenance and introduction of food; and (3) temporal trends associated with day/night cycles, especially impacted by artificial lighting. We searched for selected spectral patterns that were correlated to the time series of the eco-acoustic indices. The observed activity was found to be consistent with the sound emission of three specific fish species hosted in the tanks. The power spectral density (PSD) confirmed the presence of correlated signals (at 95th and 99th percentiles) for the identified frequency intervals. We expect that this method could be useful for studying the behavior of aquatic animals without intruding into their habitats.
Convergence between Indicators for Measuring Sustainable Development and M&A Performance in the Energy Sector
Authors: Andriuškevičius Karolis , Štreimikienė Dalia , Alebaitė Irena
Published: August 2022

The energy sector is experiencing various transformations. Simultaneously, merger and acquisition (M&A) activities in the sector are surging globally. Extensive research has focused on and analyzed M&As from the perspective of acquirer- and target-level financial performance. In comparison, a significantly lower number of studies have analyzed the macroeconomic impact of M&A activities. The field of and interests in sustainability have also been expanding in recent decades. Sustainable development goal 7 (SDG7), which calls for “affordable, reliable, sustainable and modern energy for all” by 2030, is among other sustainable development goals that were established by the UN (United Nations). However, the synthesis of indicators for measuring sustainable development and M&A performance remains a relatively vaguely explored field. Here, we perform SALSA (search, appraisal, synthesis, and analysis) and analyze which M&A and sustainable development performance indicators may be used when analyzing M&A within the energy sector. The employment of an eligible set of indicators measuring sustainable development and M&A performance may be used by practitioners, governments, and scholars for the purpose of monitoring, tracking, and the communication of the progress. The results imply that most popular sustainability measurements are indicators for sustainable energy development (ISED). There is a growing number of studies focusing on and applying country-specific methodologies. The measurement of M&A and sustainability performance faces difficulties in practice implementation due to a lack of availability of data, information, and databases, etc.
Do the National Key Ecological Function Zones Promote Green Development? Evidence from the Yanshan–Taihang Mountainous Area in Hebei Province, China
Authors: Liu Meiyu , Zhang Guofeng , Yang Du
Published: August 2022

National key ecological function zones (NKEFZs) in China are critically important to maintain ecological security and accelerate the construction of the ecological civilization system. The quantitative impact of NKEFZs on green development at the county level has not received much attention. In this study, the county-level statistics of the Yanshan–Taihang Mountainous area in Hebei province from 2013 to 2018 were selected as samples. The symbiotic relationship between economy and ecology was measured and development patterns were identified using an improved Lotka–Volterra model. Then, a difference-in-differences (DID) model was used to empirically test the green development effects of establishing NKEFZs, as well as the dynamic changes of the effects and the heterogeneity of different development patterns. The results show that: (1) Green development in the sample area can be classified into four patterns: Low-High, High-Low, High-High, and Low-Low; (2) NKEFZs reduce the level of green development in the study interval and have a persistent negative effect on the level of green development; and (3) NKEFZs have a significant negative effect on areas of Low-High and High-Low development patterns, while the effect on areas of Low-Low development patterns is not significant. Overall, the results indicate that NKEFZs have a negative impact on the green development of the Yanshan–Taihang Mountainous area in Hebei Province. Finally, to promote green development in mountainous areas, the paper makes the following recommendations: Firstly, to improve the transfer payment system for NKEFZs and bring into play a long-term mechanism for the compensation effect of transfer payments. Secondly, to cultivate special industries to achieve the differentiated development of county economies. Thirdly, to accelerate the optimization and adjustment of industrial structures and promote the coordinated development of primary, secondary, and tertiary industries.