bluuebunny/crossref_metadata_2025 huggingface dataset:
Using Deep Learning to Recognize Therapeutic Effects of Music Based on Emotions
Authors: Modran Horia Alexandru , Chamunorwa Tinashe , Ursuțiu Doru , Samoilă Cornel , Hedeșiu Horia
Published: January 2023

Music is important in everyday life, and music therapy can help treat a variety of health issues. Music listening is a technique used by music therapists in various clinical treatments. As a result, music therapists must have an intelligent system at their disposal to assist and support them in selecting the most appropriate music for each patient. Previous research has not thoroughly addressed the relationship between music features and their effects on patients. The current paper focuses on identifying and predicting whether music has therapeutic benefits. A machine learning model is developed, using a multi-class neural network to classify emotions into four categories and then predict the output. The neural network developed has three layers: (i) an input layer with multiple features; (ii) a deep connected hidden layer; (iii) an output layer. K-Fold Cross Validation was used to assess the estimator. The experiment aims to create a machine-learning model that can predict whether a specific song has therapeutic effects on a specific person. The model considers a person’s musical and emotional characteristics but is also trained to consider solfeggio frequencies. During the training phase, a subset of the Million Dataset is used. The user selects their favorite type of music and their current mood to allow the model to make a prediction. If the selected song is inappropriate, the application, using Machine Learning, recommends another type of music that may be useful for that specific user. An ongoing study is underway to validate the Machine Learning model. The developed system has been tested on many individuals. Because it achieved very good performance indicators, the proposed solution can be used by music therapists or even patients to select the appropriate song for their treatment.
Review of Sensor Technology to Support Automated Air-to-Air Refueling of a Probe Configured Uncrewed Aircraft
Authors: Parry Jonathon , Hubbard Sarah
Published: January 2023

As technologies advance and applications for uncrewed aircraft increase, the capability to conduct automated air-to-air refueling becomes increasingly important. This paper provides a review of required sensors to enable automated air-to-air refueling for an uncrewed aircraft, as well as a review of published research on the topic. Automated air-to-air refueling of uncrewed aircraft eliminates the need for ground infrastructure for intermediate refueling, as well as the need for on-site personnel. Automated air-to-air refueling potentially supports civilian applications such as weather monitoring, surveillance for wildfires, search and rescue, and emergency response, especially when airfields are not available due to natural disasters. For military applications, to enable the Air Wing of the Future to strike at the ranges required for the mission, both crewed and uncrewed aircraft must be capable of air-to-air refueling. To cover the sensors required to complete automated air-to-air refueling, a brief history of air-to-air refueling is presented, followed by a concept of employment for uncrewed aircraft refueling, and finally, a review of the sensors required to complete the different phases of automated air-to-air refueling. To complete uncrewed aircraft refueling, the uncrewed receiver aircraft must have the sensors required to establish communication, determine relative position, decrease separation to astern position, transition to computer vision, position keep during refueling, and separate from the tanker aircraft upon completion of refueling. This paper provides a review of the twelve sensors that would enable the uncrewed aircraft to complete the seven tasks required for automated air-to-air refueling.
Conditional Generative Adversarial Networks for Data Augmentation of a Neonatal Image Dataset
Authors: Lyra Simon , Mustafa Arian , Rixen Jöran , Borik Stefan , Lueken Markus , Leonhardt Steffen
Published: January 2023

In today’s neonatal intensive care units, monitoring vital signs such as heart rate and respiration is fundamental for neonatal care. However, the attached sensors and electrodes restrict movement and can cause medical-adhesive-related skin injuries due to the immature skin of preterm infants, which may lead to serious complications. Thus, unobtrusive camera-based monitoring techniques in combination with image processing algorithms based on deep learning have the potential to allow cable-free vital signs measurements. Since the accuracy of deep-learning-based methods depends on the amount of training data, proper validation of the algorithms is difficult due to the limited image data of neonates. In order to enlarge such datasets, this study investigates the application of a conditional generative adversarial network for data augmentation by using edge detection frames from neonates to create RGB images. Different edge detection algorithms were used to validate the input images’ effect on the adversarial network’s generator. The state-of-the-art network architecture Pix2PixHD was adapted, and several hyperparameters were optimized. The quality of the generated RGB images was evaluated using a Mechanical Turk-like multistage survey conducted by 30 volunteers and the FID score. In a fake-only stage, 23% of the images were categorized as real. A direct comparison of generated and real (manually augmented) images revealed that 28% of the fake data were evaluated as more realistic. An FID score of 103.82 was achieved. Therefore, the conducted study shows promising results for the training and application of conditional generative adversarial networks to augment highly limited neonatal image datasets.
An Efficient Hybrid Linear Clustering Superpixel Decomposition Framework for Traffic Scene Semantic Segmentation
Authors: Zhong Dan , Li Tiehu , Dong Yuxuan
Published: January 2023

Superpixel decomposition could reconstruct an image through meaningful fragments to extract regional features, thus boosting the performance of advanced computer vision tasks. To further optimize the computational efficiency as well as segmentation quality, a novel framework is proposed to generate superpixels from the perspective of hybridizing two existing linear clustering frameworks. Instead of conventional grid sampling seeds for region clustering, a fast convergence strategy is first introduced to center the final superpixel clusters, which is based on an accelerated convergence strategy. Superpixels are then generated from a center-fixed online average clustering, which adopts region growing to label all pixels in an efficient one-pass manner. The experiments verify that the integration of this two-step implementation could generate a synergistic effect and that it becomes more well-rounded than each single method. Compared with other state-of-the-art superpixel algorithms, the proposed framework achieves a comparable overall performance in terms of segmentation accuracy, spatial compactness and running efficiency; moreover, an application on image segmentation verifies its facilitation for traffic scene analysis.
Energy Optimization of Wireless Sensor Embedded Cloud Computing Data Monitoring System in 6G Environment
Authors: Yang Huaiyuan , Zhou Hua , Liu Zhenyu , Deng Xiaofan
Published: January 2023

With the construction and development of modern and smart cities, people’s lives are becoming more intelligent and diversified. Surveillance systems increasingly play an active role in target tracking, vehicle identification, traffic management, etc. In the 6G network environment, facing the massive and large-scale data information in the monitoring system, it is difficult for the ordinary processing platform to meet this computing demand. This paper provides a data governance solution based on a 6G environment. The shortcomings of critical technologies in wireless sensor networks are addressed through ZigBee energy optimization to address the shortage of energy supply and high energy consumption in the practical application of wireless sensor networks. At the same time, this improved routing algorithm is combined with embedded cloud computing to optimize the monitoring system and achieve efficient data processing. The ZigBee-optimized wireless sensor network consumes less energy in practice and also increases the service life of the network, as proven by research and experiments. This optimized data monitoring system ensures data security and reliability.
Excitation of Mechanical Resonances in the Stationary Ring of a Mechanical Seal by a Continuously Operated Electromagnetic Acoustic Transducer
Authors: Siegl Alexander , Leithner Stefan , Schweighofer Bernhard , Wegleiter Hannes
Published: January 2023

Acoustic/ultrasonic testing is now a common method in the field of nondestructive testing for detecting material defects or monitoring ongoing mechanical changes in a structure during operation. In many applications, piezoelectric transducers are used to generate mechanical waves inside the specimen. Their actual operating frequency is highly dependent on the dimensions of the transducer. Larger dimensions of the piezoelectric transducer allow for a lower operating frequency. However, these dimensions limit the use of piezoelectric transducers in certain applications where the size of the transducer is restricted due to limited installation space and when low-frequency excitation is required. One application that places these requirements on the transducer is the monitoring of mechanical seals. Here, the transducer must be mounted on the stationary ring of the seal. In this paper, a continuously operated electromagnetic acoustic transducer (EMAT) is presented as an alternative to piezoelectric transducers as a transmitter. The advantage of a EMAT is that it meets the requirements of limited sensor size (sensor area < 10 × 6 mm) and can excite mechanical waves with frequencies below 10 kHz. A structural analysis of the stationary ring shows that the first two mechanical resonances occur around 4 and 5.5 kHz. An experimental study meterologically demonstrates the ability of the EMAT to excite these first two mechanical resonances of the ring. A comparative simulation agrees well with the measurement.
Inferential Composition Control of a Distillation Column Using Active Disturbance Rejection Control with Soft Sensors
Authors: Al Kalbani Fahad , Zhang Jie
Published: January 2023

This paper presents the integration of active disturbance rejection control (ADRC) with soft sensors for enhancing the composition control performance in a distillation column. Static and dynamic soft sensors are developed to estimate the top and bottom product compositions using multiple tray temperatures. In order to cope with the collinearity issues in tray temperature measurements, static and dynamic principal component regression is used in developing the soft sensors. The soft sensor outputs are introduced as the feedback signals to ADRC. This control scheme is termed as “inferential ADRC control”. Static control offsets are eliminated through mean updating in the soft-sensor models. The effectiveness of the proposed control scheme is demonstrated on a benchmark simulated methanol-water distillation column.
Lead-Free Piezoelectric Acceleration Sensor Built Using a (K,Na)NbO3 Bulk Ceramic Modified by Bi-Based Perovskites
Authors: Lee Min-Ku , Kim Byung-Hoon , Lee Gyoung-Ja
Published: January 2023

Piezoelectric accelerometers using a lead-free (K,Na)NbO3 (KNN) piezoceramic modified by a mixture of two Bi-based perovskites, Bi(Na,K,Li)ZrO3 (BNKLZ) and BiScO3 (BS), were designed, fabricated and characterized. Ring-shaped ceramics were prepared using a conventional solid-state reaction method for integration into a compression-mode accelerometer. A beneficial rhombohedral–tetragonal (R–T) phase boundary structure, especially enriched with T phase, was produced by modifying intrinsic phase transition temperatures, yielding a large piezoelectric charge coefficient d33 (310 pC/N) and a high Curie temperature Tc (331 °C). Using finite element analyses with metamodeling techniques, four optimum accelerometer designs were obtained with high magnitudes of charge sensitivity Sq and resonant frequency fr, as evidenced by two key performance indicators having a trade-off relation. Finally, accelerometer sensor prototypes based on the proposed designs were fabricated using the KNN-BNKLZ-BS ceramic rings, which exhibited high levels of Sq (55.1 to 223.8 pC/g) and mounted fr (14.1 to 28.4 kHz). Perfect charge-to-acceleration linearity as well as broad flat frequency ranges were achieved with excellent reliability. These outstanding sensing performances confirm the potential application of the modified-KNN ceramic in piezoelectric sensors.
Fast Triacylglycerol Fingerprinting in Edible Oils by Subcritical Solvent Chromatography
Authors: Salerno Tania Maria Grazia , Oteri Marianna , Arena Paola , Trovato Emanuela , Sciarrone Danilo , Donato Paola , Mondello Luigi
Published: January 2023

Supercritical fluid chromatography (SFC) has witnessed a resurge of interest in the last decade, motivated by substantial progress in hardware capabilities and the development of specifically tailored packing materials. Meanwhile, the technique has been transitioning to the use of mobile phases in which an organic co-solvent is mixed to carbon dioxide under subcritical conditions (subFC). The use of a mobile phase modifier will also affect the selectivity, and extend the range of SFC-amenable compounds, including lipids. In this research, a subFC method was developed for the separation of triacylglycerols (TAGs) in edible oils of vegetable origin, namely borage, corn, hazelnut, olive, palm, peanut, and soybean oil. For all the samples investigated, elution of the TAG species was achieved within 8 min, the only exception being borage oil (14 min run), characterized by TAGs spanning in a wide range of partition number (PN 36–56), as constituted by fatty acids differing for alkyl chain lengths (CN 14–24), and degree of unsaturation (DB 0–9). The coupling to mass spectrometry (MS) detection allowed for the average parameters of fatty acid composition to be derived in the oil TAG constituents. A total of 121 TAGs were identified by subFC-MS, with reduced analysis time and solvent consumption (1.5 mL per analysis) compared to common chromatographic approaches. Key features of the method developed hereby are low toxicity, costs, and environmental impact. Notably, the achieved separations were conducted at room temperature, which is beneficial in terms of column life.
Application of Walnut Shell Biowaste as an Inexpensive Adsorbent for Methylene Blue Dye: Isotherms, Kinetics, Thermodynamics, and Modeling
Authors: Farch Sabrina , Yahoum Madiha Melha , Toumi Selma , Tahraoui Hichem , Lefnaoui Sonia , Kebir Mohammed , Zamouche Meriem , Amrane Abdeltif , Zhang Jie , Hadadi Amina , Mouni Lotfi
Published: January 2023

This research aimed to assess the adsorption properties of raw walnut shell powder (WNSp) for the elimination of methylene blue (MB) from an aqueous medium. The initial MB concentration (2–50 mg/L), the mass of the biomaterial (0.1–1 g/L), the contact time (10–120 min), the medium’s pH (2–12), and the temperature (25–55 °C) were optimized as experimental conditions. A maximum adsorption capacity of 19.99 mg/g was obtained at an MB concentration of 50 mg/L, a medium pH of 6.93 and a temperature of 25 °C, using 0.2 g/L of WNSp. These conditions showed that the MB dye elimination process occurred spontaneously. Different analytical approaches were used to characterize the WNSp biomaterial, including functional groups involved in MB adsorption, the surface characteristics and morphological features of the WNSp before and after MB uptake, and identification of WNSp based on their diffraction pattern. The experimental isotherm data were analyzed by the Langmuir and Freundlich models for the adsorption of MB dye. The corresponding values of parameter RL of Langmuir were between 0.51 and 0.172, which confirmed the WNSp’s favorable MB dye adsorption. The experimental kinetic data were examined, and the pseudo-second-order model was shown to be more suitable for describing the adsorption process, with an excellent determination coefficient (R2 = 0.999). The exchanged standard enthalpy (H° = −22.456 KJ.mol−1) was calculated using the van ‘t Hoff equation, and it was proven that the adsorption process was exothermic. The spontaneous nature and feasibility of the MB dye adsorption process on WNSp were validated by negative standard enthalpy values (G°) ranging from −2.580 to −0.469 at different temperatures. It was established that WNSp may be employed as a novel, effective, low-cost adsorbent for the elimination of methylene blue in aqueous solutions.
Connected Driving in German-Speaking Social Media
Authors: Rykova Eugenia , Stieben Christine , Dostovalova Olga , Wieker Horst
Published: January 2023

Intelligent transportation systems (ITS) have been steadily becoming part of our reality. For their successful integration, studying and understanding public opinions and acceptance is important. Social media platforms offer an extensive opportunity for opinion mining. While there have been studies on people’s attitudes towards automated driving, another important ITS concept—connected driving—has received little to no attention. In the current study, data on how connected driving is represented and perceived were collected from German(-speaking) Reddit and Twitter. In relevant Reddit entries, the necessity of communication between vehicles was discussed almost exclusively in the context of automated driving. On Twitter, mostly shared news and information on the topic are presented, while the number of personal opinions is low. The most concerning subtopic seems to be cybersecurity, which reflects a general trend of data protection issues discussed in society.
A Framework Supporting Health and Safety Practices in the United Arab Emirates’ Construction Projects
Authors: Alhelo Abdelrahman Abdalla , Alzubaidi Radhi , Rashid Hamad
Published: January 2023

The construction business in the UAE has seen a significant increase in the type, amount, and complexity of structures, with safety and health being one of the most important tasks in order for projects to continue. A lack of sufficient health and safety rules in the construction industry is one of the key difficulties, based on which the aim of the current research is to develop an integrated framework for optimising H&S in the UAE’s construction industry. To meet this aim of the study, the present study conducted an exhaustive investigation of all current health and safety standards in the UAE construction industry across all Emirates. A total of 63 interviews were performed with construction and consulting organisations in Abu Dhabi, Dubai, and Sharjah to investigate the existing status and efficacy of safety and health standards in the UAE construction industry and to identify areas for improvement. Despite the fact that H&S laws and regulations are enforced across the UAE, the findings demonstrated that they are neither standardised nor universal. In addition, the findings revealed that there is no one entity accountable for implementing the safety and health standards. In accordance with this, a precise and innovative structure for the formation of a federal body to serve as the industry’s single H&S regulator is suggested.
Applicability of Integrated Project Delivery Principles Based on a Measurement Model in China
Authors: Mei Tingting , Guo Zeng , Li Peng , Fang Kaixian , Zhong Shuda
Published: January 2023

This paper explores a novel approach to clarify the applicability of the Integrated Project Delivery (IPD) principles in a certain region or country which has a specific cultural background, the paper further promotes the effective application of IPD principles. The method of combining qualitative and quantitative analysis is adopted, incorporating scientometric analysis, questionnaire survey, qualitative analysis, and a measurement model. On the basis of 310 sample data collected from various practitioners and researchers in China’s construction industry, the measurement models of IPD applicability analysis on the average level of sample (ALS) and the best level of sample (BLS) are established, respectively. The results show that these measurement models are essentially consistent with the composition of the conceptual model, including project performance, contractual principles, collaboration-related principles, behavioral principles, and catalysts. Thus, this paper provides a scientific and methodological basis for how to effectively apply the IPD principles. This study sheds light on project delivery system research in two aspects: it proposes a new idea to study the applicability of IPD principles and lays a foundation for the future quantitative study on the impact mechanism of IPD principles on project performance.
Has Secondary Science Education Become an Elite Product in Emerging Nations?—A Perspective of Sustainable Education in the Era of MDGs and SDGs
Authors: Alam Gazi Mahabubul
Published: January 2023

Education is considered the single most important tool that supports the achievement of a nation’s sustainable development. However, if a particular education program itself deprives students with a lower socioeconomic status (SES) to access it and subsequently restricts them from achieving a better performance, should such an education program be labelled as sustainable education, supporting the achievement of the SDGs (Sustainable Development Goals)? This question remains to be answered. Science education, which is also treated as an “international product”, is the most essential component in education required to ensure sustainable national development. Consequently, science education should be a “right-based education program” that every “capable student”, regardless of his/her SES, is able to obtain. This motive should ideally ensure the best practice mode of sustainable development in education. Keeping this view in mind, this research was conducted in an emerging nation, namely Bangladesh, to examine whether secondary science education has become an elite product and its consequential effect on sustainable education. A qualitative research method that adopts a descriptive analysis of secondary data was primarily used. The secondary data were collected from the public archive(s). Findings suggest that, mostly, students with a privileged SES can access science education programs. Moreover, these students perform well in major public examination(s). Primary data further collected by Focus Group Discussions (FGDs) summarise that science education is an international product. The following artificial perception has thus developed. To participate in such a program, a significant informal budget from parents’ pockets is required in order to perform well. This is an obvious conflict with the spirit of sustainable education and SDGs. Hence, policy reform guidelines for decent practice are provided to resolve this misleading perception.
Sustainable Total Reward Strategies for Talented Employees’ Sustainable Performance, Satisfaction, and Motivation: Evidence from the Educational Sector
Authors: Elrayah Musaddag , Semlali Yahdih
Published: January 2023

The importance of sustainable human resource practices is increasing yearly. During COVID-19, many benefits and compensation strategies became increasingly important for employees. Working environments are described as one of the main factors that affects people’s lives while they are at work. This empirical study explores the impact of sustainable total reward strategies on sustainable talented employee performance, satisfaction, and motivation in the education field, using a quantitative research method. Data were collected from an annual survey developed by the Organization for Economic Co-operation and Development (OECD). The participants of this survey were residents of 47 different countries and economies, and a total of 153,682 teachers participated. The annual survey’s main goal is to generate reliable, valid, and comparable population estimates based on sample data. Data were analyzed using Pearson’s correlation and SPSS version 24. The findings of this research show a positive correlation between total sustainable rewards and sustainable employee performance (B = 0.079, p < 0.01), satisfaction (B = 0.370, p < 0.01), and motivation (B = 0.427, p < 0.01). These results might have social and economic implications, especially in the educational sector.
Exploring the Impact of COVID-19 Pandemic on Food Choice Motives: A Systematic Review
Authors: Skalkos Dimitris , Kalyva Zoi C.
Published: January 2023

The economic crisis caused by the COVID-19 pandemic has effected the global economy, with the main changes expected to affect human life in the future, including food consumption. However, could this pandemic be assumed as a threshold for the suspension of the usual rules behind food choices? This review highlights the changes in food choice motivations before, during, and after the pandemic that have been reported in the literature to date to answer the research question on the changes in food choice motives caused by the pandemic to consumers worldwide. The review comes up with ten key food motives important for consumers, namely health, convenience, sensory appeal, nutritional quality, moral concerns, weight control, mood and anxiety, familiarity, price, and shopping frequency behavior; these motives continue to be significant in the post-pandemic era. Our findings indicate that it is too premature to give definite answers as to what food choice motives in the post-COVID-19 era will be like. Consumers’ perceptions and attitudes toward food in the new era are contradictory, depending on the country of the study, the average age, and the sex of the study group. These controversial results illustrate that, for food consumption, motives depend on the population being searched, with changes identified occurring in two directions. The definite answers will be given in three to five years when the new conditions will be clear and a number of studies will have been published. Even though it is too early to fully understand the definite food choice motive changes, defining a “new” index of consumer satisfaction is necessary since it can alter the food sale strategies of retail managers, food companies, and the other parties involved in the agri-food chain.
Assessment of Urban Green Open Spaces of Micro- and Meso-Level Zones, Based on the Growth Pattern: Case of Patna City
Authors: Kumar Sandeep , Rajak Fulena
Published: January 2023

India’s urban population increase is creating pressure on the urban green open spaces. The overall city-level per capita open space is considered as a benchmark of the open space. The open space of Patna is 2.43 sq m per capita, but at the community level or ward level, there is a lacuna. So, there is a significant gap in open space distribution at the city level and the micro level, that is, ward or block level. An assessment was carried out on three parameters, i.e., quantity, accessibility, and quality. Open space, catchment area, and vegetation cover were used as independent variables, and population density and ward area as dependent variables, to understand the distribution at the ward level, that is, community level. Distribution was analyzed by Pearson correlation between the independent and dependent variables within three parameters. The open space distribution between three meso-level areas based on the growth pattern was analyzed with the help of linear regression and R-squared tests to compare the distribution between the areas. The result shows that Patna has poor distribution in the old and new areas. The developed areas in between have good distribution at the micro level and meso level. Patna has 2.3 sq m per capita as per the proposed open space plan and projected population of 2030, which is less than the standard 3.16 sq m/capita at the community level and 3.66 sq m/capita at the district level.
Review of Data-Driven Approaches for Wind Turbine Blade Icing Detection
Authors: Cai Chang , Guo Jicai , Song Xiaowen , Zhang Yanfeng , Wu Jianxin , Tang Shufeng , Jia Yan , Xing Zhitai , Li Qing’an
Published: January 2023

Onshore wind turbines are primarily installed in high-altitude areas with good wind energy resources. However, in winter, the blades are easy to ice, which will seriously impact their aerodynamic performance, as well as the power and service life of the wind turbine. Therefore, it is of great practical significance to predict wind turbine blade icing in advance and take measures to eliminate the adverse effects of icing. Along these lines, three approaches to supervisory control and data acquisition (SCADA) data feature selection were summarized in this work. The problems of imbalance between positive and negative sample datasets, the underutilization of SCADA data time series information, the scarcity of high-quality labeled data, and weak model generalization capabilities faced by data-driven approaches in wind turbine blade icing detection, were reviewed. Finally, some future trends in data-driven approaches were discussed. Our work provides guidance for the use of technical means in the actual detection of wind turbine blades. In addition, it also gives some insights to the further research of fault diagnosis technology.
Can R&D Intensity Reduce Carbon Emissions Intensity? Evidence from China
Authors: Zhao Yan , Sun Hui , Xia Xuechao , Ma Dianyuan
Published: January 2023

Among the ways to reduce carbon emission intensity (CEI), increasing the intensity of research and development intensity (RDI) plays an important role in the process. In China, how RDI reduces CEI has attracted widespread attention. Most scholars have not considered spatial effects in the study of the correlation between RDI and CEI; therefore, this paper uses panel data of 30 Chinese provinces from 2007–2019 as a research sample to explore the spatial effects of RDI on CEI using spatial measures, analyzes the regulatory effects of the market and government in the process using the interaction effect model, and explores the role and mediating effects in the process of industrial upgrading, technological innovation and human capital effects using the mediating effect model. The empirical results illustrate that: (1) RDI and CEI have significant positive spatial autocorrelation. The spatial clustering characteristics of CEI have obvious regional differences. (2) RDI reduces the CEI of the local area while it has the same reducing effect on the CEI of the surrounding areas. The conclusion is robust. (3) The market and government play a facilitating role in RDI that affects CEI, but there are regional differences. (4) RDI can indirectly reduce CEI by promoting industrial upgrading, improving technological innovation, and increasing human capital. Finally, according to the research conclusions, the paper put forward policy suggestions: strengthen regional cooperation, guide funds into the research and development field, improve the business environment, promote technological innovation and train relevant talents. The research content and findings of this paper enrich the theories related to the influence of RDI on CEI, and have certain implications for future research on CEI based on spatial perspective.
College Students’ Attitude towards Waste Separation and Recovery on Campus
Authors: Qu Dongxu , Shevchenko Tetiana , Shams Esfandabadi Zahra , Ranjbari Meisam
Published: January 2023

As large communities, the efficiency and effectiveness of waste management on university campuses are of concern. This study aims to verify the variable relationship, influence path, and regulating factors of college students’ attitudes and behavior toward waste separation. A questionnaire survey was conducted at Henan Institute of Science and Technology, China, with 1300 respondents, among which 1213 questionnaires were valid. The SPSS software v23.0 was used to carry out the statistical analysis of the collected data by applying multiple analyses. The results showed that (i) females outperform males across attitudes and internal and external contextual factors, (ii) freshmen showed more positive waste separation behaviors, while upper-year students’ behaviors were more susceptible to contextual factors, (iii) college students’ attitudes, especially the knowledge factor, have a significant positive influence on behaviors, and (iv) the external contextual factors, as moderating variables, have a significant difference in the impact amplitude at different levels when attitudes affect behaviors. Our findings supplement the limited information available on the potential implications of applying the ABC model in exploring the factors influencing waste separation behaviors among college students. The provided insights can support college students, university administrators, policymakers, and government departments in more effectively optimizing, designing, and managing waste systems on campuses.
Value-Creation Efficiency as a Decision-Making Basis and Its Assessment in the Financial Management of Energy Companies: Evidence from the Polish Capital Market
Authors: Ćwięk Wojciech , Jaki Andrzej , Popławski Łukasz , Rojek Tomasz
Published: January 2023

A study of the efficiency of the energy companies that are listed on the Polish capital market, which will be the object of the analysis in this paper, is focused on assessing the degree of accomplishment of their basic financial objectives, namely, the maximization of their market values. The main research methods that are used in the article are methods for analyzing and evaluating the literature (in order to present the current scientific achievements in the field under study) and descriptive statistics and mathematical statistical methods for analyzing the interdependence of the phenomena (used to characterize and compare the analyzed energy-sector companies, as well as to quantify the determinants of the value-creation efficiency of these companies). This article is focused on the conditions and problems that are related to the decision-making processes that are aimed at increasing efficiency in the area of building enterprise-value. These require the use of tools for efficiency measurement that enable management to quantify and assess changes in an enterprise’s market value and the efficiency of its creation. Within the conducted research, it has also been proven that this is the market perspective that is of key significance from the point of view of the criteria of making financial management decisions. The market perspective reflects the expectations of the majority of company stakeholders, to the fullest. The study showed that the allocation of capital in the listed energy companies during the period of 2014–2020 was subject to a relatively high risk of losing the economic value of the invested capital. In terms of asset value, dividing the studied group of companies into portfolios of two groups of companies additionally showed that the volatility of the market and equity returns for the smaller companies was higher than it was for the larger companies.
GIS-Based Visitor Count Prediction and Environmental Susceptibility Zoning in Protected Areas: A Case Study in Plitvice Lakes National Park, Croatia
Authors: Jurišić Mladen , Plaščak Ivan , Rendulić Željko , Radočaj Dorijan
Published: January 2023

The most valuable protected natural areas, including national parks, are subjected to the increased visitors count and density, threatening the environmental sustainability and biodiversity conservation. To establish a basis for land management to mitigate these influences, the novel geographic information (GIS)-based environmental susceptibility zoning method was proposed. The study area covered the Plitvice Lakes National Park, as the oldest and largest national park in Croatia, using the historical 20-year visitor data with 19 tourist and hiking routes. Two geospatial analysis methods were evaluated as follows: (1) short-term prediction of visitors count data based on a 10-year historical intervals, and (2) the environmental susceptibility zones delineation method integrated two fundamental factors in the assessment of environmental impacts from route density and historical visitors count on a monthly basis. Four accuracy assessment metrics indicated a moderate accuracy of short-term visitors count prediction, with the coefficient of determination ranging from 0.700 to 0.951. The routes which continue from both entrances indicated the largest visitors load is in the central part of the park, mostly located in the moderately restricted zone. These observations indicated moderate present environmental susceptibility with stable outlook, providing an insight for the nature park management adjustment.
Development of Hybrid Titania/Polybenzoxazine Composite for Enhance Thermomechanical, Flame Retardancy and Dielectric Properties
Authors: Asrafali Shakila Parveen , Periyasamy Thirukumaran , Raorane Chaitany Jayprakash , Vanaraj Ramkumar , Raj Vinit , Kim Seong-Cheol
Published: January 2023

Polybenzoxazines (Pbzs) are a recently developed class of thermosetting polymeric materials possessing low surface free energy with nonfluorine or nonsilicon content. In the present study, a new type of Pbz-BN/TiO2 composite was fabricated using benzoxazine monomer bis(6-phenyl diazenyl-3-phenoxy-3,4-dihydro-2H-1,3-benzoxazinyl) benzonitrile and inorganic TiO2 fillers by a simple and inexpensive process. The thermal curing method was found to be effective for preparing superhydrophobic surfaces combining low surface energy and surface roughness. The presence of the benzonitrile group in the benzoxazine monomer paves the way for accelerating the curing of the benzoxazine monomer, as shown by the DSC analysis. The as-prepared Pbz/TiO2 surfaces containing 5 wt% of TiO2 generated a superhydrophobic surface exhibiting a static water contact angle (SWCA) of 146°. In addition, the effect of inorganic fillers on the thermal, mechanical and dielectric properties of the Pbz/TiO2 composites was investigated in detail.
Enhanced Sewage Sludge Disintegration and Nutrients Release by Catalytic Microbubbles Ozonation Using Sewage Sludge-Based Char as Catalyst
Authors: Zhang Xin , Li Guangming , Li Yijing , Ma Yan , Han Xiaomeng , Zhou Xinyu
Published: January 2023

Using microbubble ozonation (MO) technique to disintegrate sludge is a promising sludge treatment process. To enhance the lysis and reduction of sludge, the catalytic ozonation consisting of MO and sewage sludge derived char (SC) were combined. Total solids (TS), volatile solids (VS), total nitrogen and phosphate (TN and TP) were selected as main parameters for evaluating the treatment performance both in solids and supernatant. With the utilization of the catalytic MO, the ozone utilization and sludge reduction were largely improved. At a reaction time of 90 min, an ozone utilization efficiency exceeding 99% was achieved by using a MO system. The optical ozone and sludge char dosages of 150 mg/g suspended solids (SS) and 1 g/L were found for sludge lysis, respectively. TS and VS concentrations decreased by 43% and 56%, respectively, as compared to those of 16.7% and 17.9% obtained by the treatment with MO alone under the condition of sludge solution pH 4. The supernatant soluble chemical oxygen demand (SCOD), TN, TP, NH4+-N and NO3−-N increased by 1750%, 205%, 25%, 31% and 43%, respectively. A small amount of additional SC exhibited strong catalytic activity on dissolving organic matter of the sludge, demonstrating the positive effect caused by the heterogeneous catalytic ozonation on sludge disintegration.
Decomposition of Green Agriculture Productivity for Policy in Africa: An Application of Global Malmquist–Luenberger Index
Authors: Myeki Lindikaya W. , Matthews Nicolette , Bahta Yonas T.
Published: January 2023

Previous research on agricultural productivity in Africa has focused on conventional Total Factor productivity (TFP) growth rather than Green Total factor productivity (GATFP) growth, thus ignoring the effect of undesirable outputs such as emissions. This has raised concerns about the sustainability of agricultural productivity growth in the continent. The study was designed to examine GATFP growth in agricultural productivity for 49 African nations from 2000 to 2019. We apply the Global Malmquist–Luenberger (GML) Productivity Index, which complies with the sustainable development agenda that promotes greater production of desirable outputs and minimising unwanted outputs. This approach is also compared to Global Malmquist (GM) Productivity Index which ignores unwanted outputs, yielding to conventional TFP growth. We found an average GATFP growth of 0.6% and TFP growth at 0.9% suggesting that the actual agricultural productivity growth is overstated if agricultural emissions are disregarded. Both estimates fell short of the desired annual target of 7% from the Comprehensive African Agriculture Development Programme (CAADP). Regional growth is mostly characterised by high (low) GATFP and TFP except in Southern Africa and East Africa. The two regions represent an ideal situation where GATFP exceeds TFP. At country level growth can be divided into three scenarios: desired growth, where GATFP exceeds TFP; balanced growth with both estimates equivalent; and undesired growth, where TFP exceeds GATFP. Unfortunately, most African nations fall in the last scenario. We conclude that policies must be developed to encourage sustainable agricultural productivity growth in Africa.
Green Innovation Strategies, Innovation Success, and Firm Performance—Evidence from a Panel of Spanish Firms
Authors: Becker Bettina
Published: January 2023

This paper examines the effects of adopting types of green innovation strategies on a firm’s innovation success and performance. The empirical analysis applies propensity score and kernel matching to a Spanish firm panel during 2008–2016. The results provide robust evidence that the pursuit of green innovation strategies increases a firm’s innovation success in the form of higher turnover due to new-to-market, or radical product innovation compared with innovating firms that do not adopt green innovation strategies. However, despite this positive effect on the competitiveness of firms that adopt green innovation strategies, they are generally little able to benefit in terms of their performance. While the results suggest improvements in the labour productivity of firms that adopt general green innovation strategies, no effects are experienced by firms that adopt green product innovation strategies. Moreover, the results suggest the absence of any firm performance benefits in terms of turnover or employment growth. These findings indicate that markets do not provide ‘win-win’ situations, and policy intervention is critical to support green innovation strategies.
European Consumers’ Attitudes towards the Environment and Sustainable Behavior in the Market
Authors: Bassi Francesca
Published: January 2023

The scope of this paper is to analyze European consumers’ attitudes and behavior towards the environment. The paper has the following main objectives: measuring homogeneity and heterogeneity within and between European countries with reference to citizens’ involvement with environmental issues, verifying the relationship between attitude and behavior, and identifying factors that might favor sustainable actions and consumption. The hierarchical nature of the data requires the estimation of multilevel models, specifically multilevel latent class models to cluster citizens and countries and multilevel logistic regression models to correlate green actions with environmental attitudes and sociodemographic characteristics. Six homogeneous groups of citizens with different levels of sensibility towards environmental topics were identified, and four groups of European countries were identified with similar compositions in terms of clusters of citizens. The analyses indicate that there is a direct influence of attitude towards the environment on behavior. Estimation results also show significant effects of consumers’ sociodemographic characteristics.
Neural Network Based Approach for Steady-State Stability Assessment of Power Systems
Authors: Badrudeen Tayo Uthman , Nwulu Nnamdi I. , Gbadamosi Saheed Lekan
Published: January 2023

The quest for an intelligence compliance system to solve power stability problems in real-time with high predictive accuracy, and efficiency has led to the discovery of deep learning (DL) techniques. This paper investigates the potency of several artificial neural network (ANN) techniques in assessing the steady-state stability of a power system. The new voltage stability pointer (NVSP) was employed to parameterize and reduce the input data to the neural network algorithms to predict the proximity of power systems to voltage instability. In this study, we consider five neural network algorithms viz. feedforward neural network (FFNN), cascade-forward neural network (CFNN), layer recurrent neural network (LRNN), linear layer neural network (LLNN), and Elman neural network (ENN). The evaluation is based on the predictability and accuracy of these techniques for dynamic stability in power systems. The neural network algorithms were trained to mimic the NVSP dataset using a Levenberg-Marquardt (LM) model. Similarly, the performance analyses of the neural network techniques were deduced from the regression learner algorithm (RLA) using a root-mean-squared error (rmse) and response plot graph. The effectiveness of these NN algorithms was demonstrated on the IEEE 30-bus system and the Nigerian power system. The simulation results show that the FFNN and the CFNN possess a relatively better performance in terms of accuracy and efficiency for the considered power networks.
Impact-Asymmetric Analysis of Bike-Sharing Residents’ Satisfaction: A Case Study of Harbin, China
Authors: Zhao Lixuan , Fang Dewei , Cao Yang , Sun Shan , Han Liu , Xue Yang , Zheng Qian
Published: January 2023

Harbin, China, has a large population density and a large number of motor vehicles. To alleviate traffic congestion, based on the survey data of bike-sharing riders in the new and old urban areas of Harbin in May 2022, this paper uses an impact-asymmetric analysis and gradient enhancement decision tree to analyse the asymmetric relationship between bike-sharing travel environment elements and cyclists’ satisfaction, and the optimisation strategy for the bike-sharing riding environment was obtained so that more residents can choose to ride. This research shows that the infrastructure of the motorway in the old urban area had the greatest impact on the overall satisfaction, while the travel quality of the shared bikes in the new urban area had the greatest impact on the overall satisfaction. In addition, due to the differences in urban environments and satisfaction, planning directions are different when satisfying cyclists in the new and old urban areas. The old urban area should emphasise cycling comfort and road coherence to provide a good travel environment; however, the new urban area should focus on the operation of shared bikes to meet the needs of cyclists. Therefore, future research should formulate refined improvement strategies for different regions.