bluuebunny/crossref_metadata_2025 huggingface dataset:
Model of the Relationship of Religiosity and Happiness of Multiple Sclerosis Patients from Poland: The Role of Mediating and Moderating Variables
Authors: Wnuk Marcin , Wilski Maciej , Szcześniak Małgorzata , Bartosik-Psujek Halina , Kapica-Topczewska Katarzyna , Tarasiuk Joanna , Czarnowska Agata , Kułakowska Alina , Zakrzewska-Pniewska Beata , Brola Waldemar , Żak Marek , Sobolewski Piotr , Morawiec Natalia , Adamczyk-Sowa Monika , Stępień Adam , Ratajczak Marcin , Ratajczak Anna , Zaborski Jacek , Kubicka-Bączyk Katarzyna , Szałachowski Roman Ryszard , Kroplewski Zdzisław , Lech Beata , Perenc Adam , Popiel Małgorzata , Potemkowski Andrzej
Published: September 2022

Religiosity and spirituality can be both beneficial and harmful to happiness. It depends on its operationalization and the measures of religiosity and sociodemographics used, together with cultural and psychosocial factors, still not comprehensively explored. This topic is especially important for religious-affiliated chronic patients such as those diagnosed with multiple sclerosis. Religion can deliver a sense of meaning, direction, and purpose in life and be an additional source of support to cope with the stress and limitations connected with the disease. The aim of the present study was to verify whether religiosity, directly and indirectly, through finding meaning in life, is related to one’s level of happiness and whether gender, the drinking of alcohol, financial status, and age are moderators in this relationship. In sum, 600 patients from Poland who suffered from multiple sclerosis were included in the study. Firstly, some gender differences were noticed. In women, religiosity was both directly and indirectly, through finding significance, positively related to happiness. Secondly, it was found that in women, the direct effect of age on happiness was generally negative but was positively affected by religiosity; however, among men, age was not correlated with happiness. In the group of women, religiosity and a lower propensity to drink alcohol in an interactive way explained happiness. Thirdly, both in men and women, financial status positively correlated with happiness, but in the group of wealthy men only, religiosity was negatively related to happiness. In conclusion, religion was found to show a positive correlation with the happiness of Roman Catholic multiple sclerosis patients from Poland. In this group of patients, religious involvement can be suggested and implemented as a factor positively related to happiness, with the one exception regarding wealthy men.
Modelling and Analysis of the Spital Branched Flexure-Hinge Adjustable-Stiffness Continuum Robot
Authors: Ma Nan , Monk Stephen , Cheneler David
Published: September 2022

Continuum robots are increasingly being used in industrial and medical applications due to their high number of degrees of freedom (DoF), large workspace and their ability to operate dexterously. However, the positional accuracy of conventional continuum robots with a backbone structure is usually low due to the low stiffness of the often-lengthy driving cables/tendons. Here, this problem has been solved by integrating additional mechanisms with adjustable stiffness within the continuum robot to improve its stiffness and mechanical performance, thus enabling it to be operated with high accuracy and large payloads. To support the prediction of the improved performance of the adjustable stiffness continuum robot, a kinetostatic model was developed by considering the generalized internal loads that are caused by the deformation of the flexure-hinge mechanism and the structural stiffening caused by the external loads on the end-effector. Finally, experiments were conducted on physical prototypes of 2-DoF and 6-DoF continuum robots to validate the model. It was found that the proposed kinetostatic model validates experimental observations within an average deviation of 9.1% and 6.2% for the 2-DoF and 6-DoF continuum robots, respectively. It was also found that the kinematic accuracy of the continuum robots can be improved by a factor of 32.8 by adding the adjustable stiffness mechanisms.
Pre-Launch Assembly, Integration, and Testing Strategy of a Hyperspectral Imaging CubeSat, HYPSO-1
Authors: Prentice Elizabeth Frances , Honoré-Livermore Evelyn , Bakken Sivert , Henriksen Marie Bøe , Birkeland Roger , Hjertenæs Martine , Gjersvik Amund , Johansen Tor Arne , Aguado-Agelet Fernando , Navarro-Medina Fermin
Published: September 2022

Assembly, Integration, and Verification/Testing (AIV or AIT) is a standardized guideline for projects to ensure consistency throughout spacecraft development phases. The goal of establishing such a guideline is to assist in planning and executing a successful mission. While AIV campaigns can help reduce risk, they can also take years to complete and be prohibitively costly for smaller new space programs, such as university CubeSat teams. This manuscript outlines a strategic approach to the traditional space industry AIV campaign through demonstration with a 6U CubeSat mission. The HYPerspectral Smallsat for Ocean observation (HYPSO-1) mission was developed by the Norwegian University of Science and Technology’s (NTNU) SmallSatellite Laboratory in conjunction with NanoAvionics (the platform provider). The approach retains critical milestones of traditional AIV, outlines tailored testing procedures for the custom-built hyperspectral imager, and provides suggestions for faster development. A critical discussion of de-risking and design-driving decisions, such as imager configuration and machining custom parts, highlights the consequences that helped, or alternatively hindered, development timelines. This AIV approach has proven key for HYPSO-1’s success, defining further development within the lab (e.g., already with the second-generation, HYPSO-2), and can be scaled to other small spacecraft programs throughout the new space industry.
Assessment of the Combined Risk of Drought and High-Temperature Heat Wave Events in the North China Plain during Summer
Authors: Wu Tianxiao , Li Baofu , Lian Lishu , Zhu Yanbing , Chen Yanfeng
Published: September 2022

Drought-induced risk has attracted the attention of many scholars, but the risk of combined events caused by drought and high-temperature heat waves still needs further study. Based on MODIS products and meteorological data, the spatiotemporal variation characteristics of summer drought and high-temperature heat waves in the North China Plain from 2000 to 2018 were analyzed by the standardized precipitation evapotranspiration index (SPEI), crop water stress index (CWSI) and high-temperature threshold, and their combined-events risk was evaluated. The results showed that (1) from 2000 to 2018, summer drought in the North China Plain became more severe. Especially in Henan, Anhui and Jiangsu Provinces, drought increased significantly. (2) From 2000 to 2018, the frequency and intensity of high-temperature heat wave events in the North China Plain gradually increased at rates of 0.28 times/10 year and 1.6 °C/10 year, respectively. (3) The slightly high risk and high risk caused by summer drought were mainly distributed in Hebei Province and Tianjin Municipality in the north, and the risk change was characterized by a decrease in the north and an increase in the south. (4) The combined-events risk of summer drought and high-temperature heat waves did not increase significantly, with an increase rate of approximately 0.01/10 year. Among them, the increase rate of combined-events risk in Henan Province was the largest (0.14/10 year), followed by the obvious increase in northern Anhui, Jiangsu and southern Shandong, while the risk in Beijing showed a decreasing trend. The research results have scientific guiding significance for formulating disaster prevention and reduction strategies.
Semi-Automated Segmentation of Geometric Shapes from Point Clouds
Authors: Honti Richard , Erdélyi Ján , Kopáčik Alojz
Published: September 2022

Building information models (BIM) in the civil industry are very popular nowadays. The basic information of these models is the 3D geometric model of a building structure. The most applied methodology to model the existing buildings is by generating 3D geometric information from point clouds provided by laser scanners. The fundamental principle of this methodology is the recognition of structures shaped in basic geometric primitives, e.g., planes, spheres, and cylinders. The basic premise of the efficiency of this methodology is the automation of detection, since manual segmentation of a point cloud can be challenging, time-consuming, and, therefore, inefficient. This paper presents a novel algorithm for the automated segmentation of geometric shapes in point clouds without needing pre-segmentation. With the designed algorithm, structures formed in three types of basic geometrical primitive can be identified and segmented: planar (e.g., walls, floors, ceilings), spherical (e.g., laser scanner reference targets), and cylindrical (e.g., columns, pillars, piping). The RANSAC paradigm partially inspires the proposed algorithm; however, various modifications must be made. The algorithm was tested on several point clouds and was compared with the standard RANSAC algorithm; this part is described in the last section of the paper. One of the tests was performed on a double cylinder-shaped test object, the parameters (radius and height) of this object were available with high accuracy (0.1 mm), and the differences between the known and estimated parameters were below 0.5 mm in each case, indicating the correctness of the proposed algorithm. Also, a comparison with the standard RANSAC algorithm was performed, where the algorithm proposed showed better results than the standard RANSAC algorithm. The segmentation quality was, on average, increased from 50% to 100%.
Preliminary Analysis of Intersystem Biases in BDS-2/BDS-3 Precise Time and Frequency Transfer
Authors: Zhang Pengfei , Tu Rui , Tao Linlin , Wang Bing , Gao Yuping , Lu Xiaochun
Published: September 2022

The Chinese BeiDou global satellite system (BDS-3) and regional system (BDS-2) are predicted to coexist over the next decade. Intersystem biases (ISBs) in BDS-2/BDS-3 play a key role in maintaining the consistency and continuity from the BDS-2 to BDS-3 time transfer. Here, we discuss the temporal characteristics, parameter composition, generation mechanism, and the effect of ISBs in BDS-2/BDS-3 on time and frequency transfer. The satellite orbits and clock products from three international GNSS service analysis centers, namely Wuhan University (WUM, China), GeoForschungsZentrum Potsdam (GFZ, Germany), and the Center for Orbit Determination in Europe (CODE), were employed to investigate the time-transfer stability of ISBs when BDS-2 and BDS-3 were used in combination. We analyzed the intrinsic characteristics of ISBs, the receiver types, antennas, and frequency standards. Our first results showed that ISBs are stable for different analysis center products, although the mean values of daily results differed markedly for the three analysis centers. With respect to the relationship between station attribution and ISB difference for a time link, the receiver type, antenna, and frequency standard influence the ISB differences in time and frequency transfer. The effect of three ISB stochastic models was evaluated with respect to time and frequency transfer. The “walk” and “constant” schemes were slightly superior to “noise”, with the improvement in their frequency stability being approximately 5% compared with that of “noise”.
Water Quality Retrieval from Landsat-9 (OLI-2) Imagery and Comparison to Sentinel-2
Authors: Niroumand-Jadidi Milad , Bovolo Francesca , Bresciani Mariano , Gege Peter , Giardino Claudia
Published: September 2022

The Landsat series has marked the history of Earth observation by performing the longest continuous imaging program from space. The recent Landsat-9 carrying Operational Land Imager 2 (OLI-2) captures a higher dynamic range than sensors aboard Landsat-8 or Sentinel-2 (14-bit vs. 12-bit) that can potentially push forward the frontiers of aquatic remote sensing. This potential stems from the enhanced radiometric resolution of OLI-2, providing higher sensitivity over water bodies that are usually low-reflective. This study performs an initial assessment on retrieving water quality parameters from Landsat-9 imagery based on both physics-based and machine learning modeling. The concentration of chlorophyll-a (Chl-a) and total suspended matter (TSM) are retrieved based on physics-based inversion in four Italian lakes encompassing oligo to eutrophic conditions. A neural network-based regression model is also employed to derive Chl-a concentration in San Francisco Bay. We perform a consistency analysis between the constituents derived from Landsat-9 and near-simultaneous Sentinel-2 imagery. The Chl-a and TSM retrievals are validated using in situ matchups. The results indicate relatively high consistency among the water quality products derived from Landsat-9 and Sentinel-2. However, the Landsat-9 constituent maps show less grainy noise, and the matchup validation indicates relatively higher accuracies obtained from Landsat-9 (e.g., TSM R2 of 0.89) compared to Sentinel-2 (R2 = 0.71). The improved constituent retrieval from Landsat-9 can be attributed to the higher signal-to-noise (SNR) enabled by the wider dynamic range of OLI-2. We performed an image-based SNR estimation that confirms this assumption.
Automatic Detection Method for Loess Landslides Based on GEE and an Improved YOLOX Algorithm
Authors: Yu Zhengbo , Chang Ruichun , Chen Zhe
Published: September 2022

The Loess Plateau is an ecologically fragile area in China; furthermore, loess landslides are typical forms of geological disasters, which severely limit the sustainable development of the local societies and the economy. Studying the automatic detection of landslides can facilitate disaster prevention and mitigation in the Loess Plateau, and help realize the climate action goal (SDG 13) of the United Nations Sustainable Development Goals (SDGs). This paper takes typical loess areas in China as the research object, and establishes a historical loess landslide sample database based on Google Earth (GEE) image data, with a total of 1451 loess landslides. The automatic detection of loess landslides is implemented by improving the You Only Look Once X (YOLOX) algorithm. The results show that the average accuracy of landslide detection in this method is 95.43%, and the accuracy rate is 96.32%, which effectively combines the earth’s big data to realize the automatic detection of loess landslides. The research results provide technical support for the promotion of disaster prevention and mitigation in China’s loess regions, the realization of sustainable development goals, and the improvement of natural disaster prevention–resistance–reduction systems.
Techniques to Improve the Performance of Planar Microwave Sensors: A Review and Recent Developments
Authors: Abdolrazzaghi Mohammad , Nayyeri Vahid , Martin Ferran
Published: September 2022

Planar microwave sensors have become increasing developed in recent decades, especially in material characterization (solid/liquid) as they provide regions highly sensitive to the surrounding medium. However, when it comes to deciphering the content of practical biological analytes or chemical components inside a host medium, even higher sensitivities are required due to their minute concentrations. This review article presents a comprehensive outlook on various methodologies to enhance sensitivity (e.g., coupling resonators, channel embedding, analyte immobilization, resonator pattern recognition, use of phase variation, using coupled line section, and intermodulation products), resolution (active sensors, differential measurements), and robustness (using machine learning) of arbitrary sensors of interest. Some of the most practical approaches are presented with prototype examples, and the main applications of incorporating such procedures are reported. Sensors with which the proposed techniques are implemented exhibit higher performance for high-end and real-life use.
Auto-Modal: Air-Quality Index Forecasting with Modal Decomposition Attention
Authors: Guo Yiren , Zhu Tingting , Li Zhenye , Ni Chao
Published: September 2022

The air-quality index (AQI) is an important comprehensive evaluation index to measure the quality of air, with its value reflecting the degree of air pollution. However, it is difficult to predict the AQI accurately by the commonly used WRF-CMAQ model due to the uncertainty of the simulated meteorological field and emission inventory. In this paper, a novel Auto-Modal network with Attention Mechanism (AMAM) has been proposed to predict the hourly AQI with a structure of dual input path. The first path is based on bidirectional encoder representation from the transformer to predict the AQI with the historical measured meteorological data and pollutants. The other path is a baseline to improve the generalization ability based on predicting the AQI by the WRF-CMAQ model. Several experiments were undertaken to evaluate the performance of the proposed model, with the results showing that the auto-modal network achieves a superior performance for all prediction lengths compared to some state-of-the-art models.
Repetition-Based Approach for Task Adaptation in Imitation Learning
Authors: Nguyen Duc Tho , Tran Chanh Minh , Bach Nguyen Gia , Tan Phan Xuan , Kamioka Eiji
Published: September 2022

Transfer learning is an effective approach for adapting an autonomous agent to a new target task by transferring knowledge learned from the previously learned source task. The major problem with traditional transfer learning is that it only focuses on optimizing learning performance on the target task. Thus, the performance on the target task may be improved in exchange for the deterioration of the source task’s performance, resulting in an agent that is not able to revisit the earlier task. Therefore, transfer learning methods are still far from being comparable with the learning capability of humans, as humans can perform well on both source and new target tasks. In order to address this limitation, a task adaptation method for imitation learning is proposed in this paper. Being inspired by the idea of repetition learning in neuroscience, the proposed adaptation method enables the agent to repeatedly review the learned knowledge of the source task, while learning the new knowledge of the target task. This ensures that the learning performance on the target task is high, while the deterioration of the learning performance on the source task is small. A comprehensive evaluation over several simulated tasks with varying difficulty levels shows that the proposed method can provide high and consistent performance on both source and target tasks, outperforming existing transfer learning methods.
Using Deep Learning to Predict Minimum Foot–Ground Clearance Event from Toe-Off Kinematics
Authors: Asogwa Clement Ogugua , Nagano Hanatsu , Wang Kai , Begg Rezaul
Published: September 2022

Efficient, adaptive, locomotor function is critically important for maintaining our health and independence, but falls-related injuries when walking are a significant risk factor, particularly for more vulnerable populations such as older people and post-stroke individuals. Tripping is the leading cause of falls, and the swing-phase event Minimum Foot Clearance (MFC) is recognised as the key biomechanical determinant of tripping probability. MFC is defined as the minimum swing foot clearance, which is seen approximately mid-swing, and it is routinely measured in gait biomechanics laboratories using precise, high-speed, camera-based 3D motion capture systems. For practical intervention strategies designed to predict, and possibly assist, swing foot trajectory to prevent tripping, identification of the MFC event is essential; however, no technique is currently available to determine MFC timing in real-life settings outside the laboratory. One strategy has been to use wearable sensors, such as Inertial Measurement Units (IMUs), but these data are limited to primarily providing only tri-axial linear acceleration and angular velocity. The aim of this study was to develop Machine Learning (ML) algorithms to predict MFC timing based on the preceding toe-off gait event. The ML algorithms were trained using 13 young adults’ foot trajectory data recorded from an Optotrak 3D motion capture system. A Deep Learning configuration was developed based on a Recurrent Neural Network with a Long Short-Term Memory (LSTM) architecture and Huber loss-functions to minimise MFC-timing prediction error. We succeeded in predicting MFC timing from toe-off characteristics with a mean absolute error of 0.07 s. Although further algorithm training using population-specific inputs are needed. The ML algorithms designed here can be used for real-time actuation of wearable active devices to increase foot clearance at critical MFC and reduce devastating tripping falls. Further developments in ML-guided actuation for active exoskeletons could prove highly effective in developing technologies to reduce tripping-related falls across a range of gait impaired populations.
A Digital Twin Case Study on Automotive Production Line
Authors: Mendi Arif Furkan
Published: September 2022

The manufacturing sector is one of the areas where the advantages of digital twin technology can benefit mostly. The product development, including its software, electronics, mechanics, and physical behavior, is included in the digital twin of the product. Furthermore, simultaneous data capturing from the sensors and data processing are also available in the digital twin. This enables each phase of the development cycle to be simulated, processed, and validated to discover the potential problems before the production of real components. In this study, the use of digital twin technology in the commercial production phase of the automotive production line with a case study is introduced. This study is one of the most comprehensive studies in the literature related to automotive production; therefore, it puts forth the power of using digital twin technology in that area. As the result of this case study, a 6.01% increase in the commercial production line efficiency and an 87.56% gain for downtime are achieved.
University Students’ Sexual Identity Development as a Determinant of Sexual Self-Hood
Authors: Rye B. J. , Hertz Steven
Published: September 2022

Sexual identity development was explored as a predictor of sexual self-concept and erotophobia–erotophilia using a student sample. Sexual identity development was operationalized using Worthington et al.’s Measure of Sexual Identity Development, which is theoretically based on Marcia’s identity model. Based on Worthington et al.’s scale, there are four sexual identity development domains: commitment to one’s sexual identity, exploration of one’s sexual identity, sexual orientation uncertainty, and synthesis/integration of one’s sexual identity. Several of Snell’s Sexual Self-Concept scales (e.g., sexual depression, sexual self-efficacy) and Tromovitch’s Comfort with Sexuality scales (e.g., comfort talking about sexuality, comfort with the sexual activities of others) were used to define sexual self-concept and erotophobia–erotophilia, respectively. A sample of students enrolled in an introductory psychology course at a Canadian university completed these instruments. Results suggest that sexual identity development was strongly predictive of sexual self-concept scales, multivariately. Sexual identity development was also predictive of comfort with sexuality. Sexual self-concept and erotophobia–erotophilia were also related to each other. These relationships supported the idea that a positive sexual identity development process contributes to a favorable view of the sexual self. However, the study was cross-sectional and correlational, so conclusions about directionality are preliminary and causality cannot be inferred.
Social Distancing Impact on Higher Education during COVID-19 Lockdown
Authors: Sava Ionel N.
Published: September 2022

During the COVID-19 pandemic, education online meant limited or no in-person interaction with professors and peers. In this article, research questions look for social distancing impact on subjects attending computer-mediated education. Educational technology factors were selected and exposed to students’ evaluation in a semi-structured questionnaire. Results confirm that online education increased students’ acceptance and positive attitude towards digital learning for 8 out of 10 subjects. On the other hand, factors that drive motivation showed diminished satisfaction with content for 4 out of 10 students and reduced capacity to stay focused for 7 out of 10 students. This research points toward factors that convert interaction with peers and instructors to such an extent that they impact basic educational fields such as motivation and satisfaction. There were interrogated social interactivity factors, as half of the subjects reported missing learner–learner and learner–instructor interaction. Results showed that up to one third of surveyed students showed diminished motivation alongside less satisfaction with content. The article concludes that digital education should multiply and adapt its own content and delivery routines and it suggests that the online education experience should serve development of computer-mediated learning as well augmenting of in-person education.
Banishment through Branding: From Montréal’s Red Light District to Quartier des Spectacles
Authors: Fiolka Rhianne , Marshall Zack , Kramer Anna
Published: September 2022

This paper analyzes how the City of Montréal employed tools of urban planning—including a district plan, street redesign, rezoning, selective public consultation, expropriation, policing and surveillance—to spatially banish sex work from its historic district, using the red light symbol as a branding strategy. This coincided with a change in federal law (Bill C-36) and a policy shift to reposition sex workers as passive victims of sex trafficking. Using a case study design, this work explores the state’s refusal to recognize the agency of those engaged in embodied socio-economic exchanges and the safety and solidarity possible in public space. In interviews, sex workers described strategies of collective organizing, resistance and protest to hold the city accountable during this process of displacement. We consider how urban planning might support sex work, sex workers and economic autonomy.
Investigating the Factors Affecting Rider’s Decision on Overtaking Behavior: A Naturalistic Riding Research in China
Authors: Wang Cheng , Wei Liyang , Wang Kun , Tang Hongya , Yang Bo , Li Mengfan
Published: September 2022

Overtaking behavior between non-motorized vehicles is one of the main characteristics of the cycling path, and unsafe overtaking behavior has a certain negative impact on riders’ safety. However, little is known about the factors affecting riders’ overtaking decisions. This study aimed to identify the influence of road facilities, types of non-motorized vehicles, and human factors on the characteristics of overtaking behavior on bicycle lanes. DJI drone-based naturalistic riding research was explored in China and a random parameter logit regression model was estimated to model the overtaking decisions of non-motorized vehicle riders. The results showed that gender, age, professional deliverer, type of lead non-motor vehicle, type of non-motorized vehicles, and width of cycling lane influence overtaking behavior significantly. The present study provides theoretical evidence to strengthen the safety design and evaluation of cycling lane infrastructure.
Innovative Framework for Assessing the Impact of Agile Manufacturing in Small and Medium Enterprises (SMEs)
Authors: Ali Abid , Wasim Ahmad
Published: September 2022

In the competitive manufacturing era, agile manufacturing has evolved as a revolutionary manufacturing strategy that manages quality, innovation, responsiveness, introduction time of product, and uncertainties to maximize profit and to satisfy fluctuating demands of customers. The decision of implementing agile manufacturing is always complicated for organizations because they fear failure during the implementation process. This paper presents an innovative framework that can help decision-makers well before the implementation of agile manufacturing practices by evaluating the potential impact on an organization. The framework is based on three components, including agility cost, agility fitness, and agility outcome. The framework has been developed after intensive literature investigation, field study of manufacturing SMEs, and interviews with experts. Based on the framework, a knowledge-based system (KBS) has been developed to aid SMEs in decision-making at the implementation stage. The system is validated by case studies and by industrial experts through detailed interviews.
Fifty Shades of Corporate Social Responsibility: A Conceptual Synthesis via a Decision Frame Lens
Authors: Hu Jinyu , Rong Yu , McKee-Ryan Frances M.
Published: September 2022

To address the question of why corporate executives adopt diverse corporate social responsibility (CSR) strategies, this conceptual paper proposes a decision-frame model to explain how differences in executives’ information-processing templates can lead to different strategic choices concerning CSR. Drawing on managerial cognition research and CSR literature, the CSR decision frame is conceptualized as a three-dimensional configuration. Each dimension depicts a continuum of responses to each of the three fundamental issues related to CSR (i.e., corporate’s objectives, corporate’s stakeholders, and leader’s responsibilities). The key premise is that the specific content and structure of a CSR decision-frame configuration define a leader’s unique stance on environmental and social issues, which, in turn, influence their sense-making process and shape CSR responses and strategies. This CSR decision-frame approach provides a process lens that highlights the cognitive mechanisms of how executives make critical CSR strategic decisions. Furthermore, this paper advances the understanding of the diversity in CSR strategy with a nuanced mental-configuration perspective: CSR means many different things to different leaders depending on the unique content and structure of his or her CSR decision frame; these varying subjective representations of CSR principles contribute to the diverse CSR responses across firms.
The Impact of Technology Innovation on Enterprise Capacity Utilization—Evidence from China’s Yangtze River Economic Belt
Authors: Liu Jun , Qian Yu , Chang Huihong , Forrest Jeffrey Yi-Lin
Published: September 2022

This paper analyzes the impact of technology innovation on capacity utilization of enterprises located in the Yangtze River Economic Belt through logic reasoning and empirical modeling. Our analysis shows that the mechanism of how technology innovation affects capacity utilization is that the former promotes the latter through meeting market demand, improving production and management efficiency, and optimizing industrial structures. Our empirical results indicate that the influence of technology innovation on the capacity utilization of enterprises in the Yangtze River Economic Belt evidently possesses positive “U” characteristics. Compared with the upstream and downstream regions of the river, the technology innovation of enterprises in the middle reaches can break the U-shaped inflection point earlier. Compared with light industrial enterprises, heavy industrial enterprises can also break the U-shaped inflection point earlier. Compared with non-overcapacity enterprises, those with overcapacity can break the U-shaped inflection point earlier. The technology innovation of non-state-owned enterprises has obvious positive “U” characteristics in the impact of capacity utilization, while the technology innovation of state-owned enterprises has no significant impact on capacity utilization.
Fuzzy Analytic Hierarchy Process Used to Determine the Significance of the Contributing Factors for Generalized Travel Satisfaction
Authors: Zhao Lin , Zhu Hongzhen , Liu Dongmei , Yang Liping , Zhao Xiaohua
Published: September 2022

This study develops the Generalized Satisfaction with Travel Scale covering travelers’ all-round emotional experience and cognitive evaluation. After checking the validity by factor analysis, the key influencing factors are extracted by optimal scale regression, and then the influence degree of key influencing factors is determined based on the Analytic Hierarchy Process. The reliability and validity of the developed Generalized Satisfaction with Travel Scale meet the requirements. The dynamic travel parameters (travel pattern, travel duration, etc.) (βs1 = 0.448) have the most important impact on generalized travel satisfaction, followed by the demographic information (age, occupation, etc.) (βs2 = 0.220) and static travel parameters (travel period, travel purpose, etc.) (βs3 = 0.178), whereas the main travel areas (residential area, work/study area) (βs4 = 0.154) have the weakest influence. This study aims at developing a Generalized Satisfaction with Travel Scale for Chinese travelers and exploring the influencing factors so as to provide an efficient travel experience survey mechanism for relevant departments.
Recreation Matters: Estimating Millennials’ Preferences for Native American Cultural Tourism
Authors: Fitch Ryan A. , Mueller Julie M. , Ruiz Rebecca , Rousse Wade
Published: September 2022

Millennials (persons born between 1981 and 1996) comprise a substantial and growing proportion of tourism consumers in the US. Rural economies, especially Native American communities, focused on casino revenue are faced with the challenge of sustainable economic growth in a millennial-dominant, post-COVID-19 pandemic economy. We estimate millennials’ willingness to pay for proposed cultural tourism scenarios using a discrete choice experiment on federally recognized tribal land in Arizona, US. We find strong preferences among millennials for guided recreational experiences, including horseback riding, hot spring visits, hiking, and cooking classes. With a changing demographic of potential visitors and a marked need to incorporate indigenous voices for the future of sustainable tourism, our results provide insight for future economic growth opportunities in cultural and natural resource tourism for Native American and rural communities.
Drone-Assisted Monitoring of Atmospheric Pollution—A Comprehensive Review
Authors: Jońca Justyna , Pawnuk Marcin , Bezyk Yaroslav , Arsen Adalbert , Sówka Izabela
Published: September 2022

Ambient air quality is a complex issue that depends on multiple interacting factors related to emissions coming from energy production and use, transportation, industrial processes, agriculture, and waste and wastewater treatment sectors. It is also impacted by adverse meteorological conditions, pollutants concentrations, their transport and dispersion in the atmosphere, and topographic constraints. Therefore, air pollutants distribution is not uniform and their monitoring at proper temporal and spatial resolution is necessary. Drone-borne analytical instrumentation can fulfill these requirements. Thanks to the rapid development in the drone manufacturing sector as well as in the field of portable detectors construction, applications of unmanned aerial vehicles (UAVs) for atmospheric pollution monitoring are growing. The purpose of this work is to give an overview of this matter. Therefore, this paper contains basic information on UAVs (i.e., description of different types of drones with their advantages and disadvantages) and analytical instrumentation (i.e., low-cost gas sensors, multi-sensor systems, electronic noses, high-accuracy optical analyzers, optical particle counters, radiation detectors) used for the monitoring of airborne pollution. Different ways of payload integration are addressed and examples of commercially available solutions are given. Examples of applications of drone-borne analytical systems for pollution monitoring coming from natural (i.e., volcanoes, thawing permafrost, wildfires) and anthropological (i.e., urbanization and industrialization; extraction, transport and storage of fossil fuels; exploitation of radioactive materials; waste and wastewater treatment; agriculture) sources are also described. Finally, the current limitations and future perspectives are discussed. Although there is a great potential for drones applications in the field of atmospheric pollution monitoring, several limitations should be addressed in the coming years. Future research should focus on improving performances of available analytical instrumentation and solving problems related to insufficient payload capacity and limited flight time of commonly used drones. We predict that applications of drone-assisted measurements will grow in the following years, especially in the field of odor pollution monitoring.
A Dynamic Road Network Model for Coupling Simulation of Highway Infrastructure Performance and Traffic State
Authors: Yang Zhen , Zheng Ruiping , Wang Gang , Zhou Kefu
Published: September 2022

The state of the road network contains both the infrastructure performance and the traffic operation state of the road network. There is a strong coupling between the decay of the infrastructure performance and the redistribution of the traffic flow on the road network. In this paper, a dynamic road network description model is proposed to apply to the couple simulation of highway network infrastructure performance and traffic state. First, a road network description model is constructed by associating the highway network topology with state attributes. The topology contains traffic information and is dynamically editable. Then, a dynamic road network model is proposed that can dynamically represent the changes in local connectivity relationships caused by traffic control, such as lane/ramp closures and turning restrictions in actual roads due to construction operations and access to the state of multi-scale spatio-temporal road networks. It overcomes the defects of the existing road network model, which is difficult to apply to the analysis of service performance and traffic state of the road network in different periods. Finally, the application of the dynamic road network model in the highway network coupled simulation system (HNCS) is completed, which provides a method for improving the efficiency and accuracy of large-scale highway network traffic simulation and highway infrastructure performance prediction.
Thermal Management of Solar Photovoltaic Cell by Using Single Walled Carbon Nanotube (SWCNT)/Water: Numerical Simulation and Sensitivity Analysis
Authors: Sharifpur Mohsen , Ahmadi Mohammad Hossein , Rungamornrat Jaroon , Malek Mohsen Fatimah
Published: September 2022

Despite the attractiveness of Photovoltaic (PV) cells for electrification and supplying power in term of environmental criteria and fuel saving, their efficiency is relatively low and is further decreased by temperature increment, as a consequence of absorption of solar radiation. In order to prevent efficiency degradation of solar cells due to temperature increment, thermal management is suggested. Active cooling of solar cells with use of liquid flow is one of the most conventional techniques used in recent years. By use of nanofluids with improved thermophysical properties, the efficiency of this cooling approach is improvable. In this article, Single Walled Carbon Nano Tube (SWCNT)/water nanofluid is used for cooling of a PV cell by considering variations in different factors such as volume fraction of solid phase, solar radiation, ambient temperature and mass flow rate. According to the findings, use of the nanofluid can lead to improvement in performance enhancement; however, this is not significant compared with water. In cases using water and the nanofluid at 0.5% and 1% concentrations, the maximum improvement in the efficiency of the cell compared with the cell without cooing were 49.2%, 49.3 and 49.4%, respectively. In addition, sensitivity analysis was performed on the performance enhancement of the cell and it was noticed that solar radiation has the highest impact on the performance enhancement by using the applied cooling technique, followed by ambient temperature, mass flow rate of the coolants and concentration of the nanofluid, respectively. Moreover, exergy analysis is implemented on the system and it is noticed that lower ambient temperature and solar radiation are preferred in term of exergy efficiency.
Geographic Variation in the Species Composition of Parrotfish (Labridae: Scarini) in the South China Sea
Authors: Quan Qiumei , Liu Yong , Wang Teng , Li Chunhou
Published: September 2022

Since parrotfish in coral reefs are involved in key ecological processes, this study compiled species presence-absence data across 51 sites in the South China Sea to identify and explore the distribution and relationship between species and large-scale factors. A total of 50 species of parrotfish were recorded during the compilation, of which Scarus ghobban Forsskål, 1775 was the most common and widespread. The Nansha Islands, having a vast area of coral reefs and great proximity away from human interference, had the highest abundance with 41 species. Nestedness analysis indicated that the parrotfish community had statistically significant nested patterns in the South China Sea, and the Nansha Islands were the topmost site for the nested matrix rank. Scleractinian coral species richness and log(reef area) both had a significant effect on the site nested matrix rank (p < 0.05), which supports the habitat nestedness hypothesis in the South China Sea. Compared with browsers and excavators, scrapers were determined to be the most important functional group composition, while browsers had a greater contribution to the species nested matrix rank. A linear regression model showed that parrotfish species’ richness increased with increasing longitude, scleractinian coral species richness, and reef area. Longitudinal variations in the parrotfish species richness were related to its distance from the biodiversity hotspot in the Indo-Australian Archipelago. Parrotfish were mainly distributed in the temperature range of 26–29 °C, similar to the optimum temperature for coral growth. The Nansha Islands should be considered biodiversity conservation priority areas for the conservation of parrotfish in degraded coral reef habitats, particularly in the context of increasing natural variability and anthropogenic disturbances.
Variation Characteristics of Particle Surface Electrochemical Properties during the Improvement of Reclaimed Soil from Hollow Village in Loess Area
Authors: Liu Zhe , Wang Huanyuan , Cao Shiliu , Sun Zenghui , Wang Na , Zhang Zhaoxin , Rong Yi
Published: September 2022

Soil surface electrochemical properties, such as specific surface area and surface charge number, are important indexes to evaluate the agricultural soil quality change. However, there is not enough focus on the effect of different improved materials on the reclaimed soil surface electrochemical characteristics. Therefore, we selected maturing agent (TM), fly ash (TF), organic fertilizer (TO), maturing agent + organic fertilizer (TMO), fly ash + organic fertilizer (TFO), and no modified material (CK) treatment for 5 years of field location experiments to study the effects of different improved materials on the surface electrochemical properties of reclaimed soil from abandoned homestead. The results showed that, compared with CK treatment, the specific surface area, surface charge number, and surface charge density of reclaimed soil increased to 11.36–14.05 m2 g−1, 13.49–18.58 cmol kg−1, and 1.14–1.76 C m−2 after five years of application of different improved materials, respectively, and the number of surface charge under TFO, TMO, and TO treatment increased by 28.9%, 25.2%, and 37.7% compared with CK, respectively. Meanwhile, the specific surface area increased significantly (p < 0.05), showing an order of TFO > TMO > TO > TF > TM > CK. The surface electric field strength can reach the order of 108 V m−1. The statistical analysis results suggest that the contents of soil organic matter (SOM), silt, and clay were positively correlated with the soil surface electrochemical properties, which were the main factors for the changes of reclaimed soil surface electrochemical properties. Our research conclusion shows that in the process of reclamation of abandoned homestead in Loess Plateau, the application of different materials is helpful to improve the soil surface electrochemical properties, among which the organic–inorganic TFO treatment was a suitable improved material treatment for improving the surface electrochemical properties and fertility of reclaimed soil.
The Impact of Corporate Innovation on Environmental Performance: The Moderating Effect of Financing Constraints and Government Subsidies
Authors: Deng Hui , Li Chuang , Wang Liping
Published: September 2022

As an essential means of reducing environmental stress, corporate innovation faces financial pressure and financial risk; so, whether corporate innovation contributes to environmental performance is related to the firm’s external capital environment (financing constraints and government subsidies). This study explores the relationships between corporate innovation, environmental performance, and the external capital environment using 1127 observations of China’s energy-intensive public companies from 2012 to 2020. The outcomes indicate that corporate innovation has a significant positive impact on environmental performance. Financing constraints provide a negative moderation of the relationship between corporate innovation and environmental performance, while government subsidies provide a positive moderation. That is, firms with high financing constraints are less likely to increase their environmental performance by innovation, while firms with high government subsidies enhance the positive influence of corporate innovation on environmental performance. The moderating effect of financing constraints varies at different levels of government subsidies, i.e., high levels of government subsidies diminish the negative moderating effect of the financing constraints between corporate innovation and environmental performance. This study’s conclusions provide a reference for the government in formulating corporate innovation subsidies and financial policies and a basis for the decision-making behaviors of enterprises regarding environmental protection and economic development.