bluuebunny/crossref_metadata_2025 huggingface dataset:
Secure Grasping Detection of Objects in Stacked Scenes Based on Single-Frame RGB Images
Authors: Xu Hao , Sun Qi , Liu Weiwei , Yang Minghao
Published: September 2023

Secure grasping of objects in complex scenes is the foundation of many tasks. It is important for robots to autonomously determine the optimal grasp based on visual information, which requires reasoning about the stacking relationship of objects and detecting the grasp position. This paper proposes a multi-task secure grasping detection model, which consists of the grasping relationship network (GrRN) and the oriented rectangles detection network CSL-YOLO, which uses circular smooth label (CSL). GrRN uses DETR to solve set prediction problems in object detection, enabling end-to-end detection of grasping relationships. CSL-YOLO uses classification to predict the angle of oriented rectangles, and solves the angle distance problem caused by classification. Experiments on the Visual Manipulate Relationship Dataset (VMRD) and the grasping detection dataset Cornell demonstrate that our method outperforms existing methods and exhibits good applicability on robot platforms.
A Game Model for Analyzing Wireless Sensor Networks of 5G Environment Based on Adaptive Equilibrium Optimizer Algorithm
Authors: Zheng Weimin , Meng Fanying , Liu Ning , Huang Shuo
Published: September 2023

Wireless sensors networks (WSNs) play an important role in life. With the development of 5G, its security issues have also raised concerns. Therefore, it is an important topic to study the offense and defense confrontation in WSNs. A complete information static game model is established to analyze the offense and defense confrontation problem of WSNs in 5G. An adaptive equilibrium optimizer algorithm (AEO) based on parameter adaptive strategy is proposed, which can jump out of the local optimal solution better. Experiments show that the optimization ability of AEO outperforms other algorithms on at least 80% of the 23 classical test functions of CEC. The convergence speed of AEO is better in the early stage of population iteration. The optimal offensive and defensive strategy under different offense and defense resources through simulation experiments is analyzed. The conclusion shows that when the offensive resources are large, the offender takes an indiscriminate attack. When the defense resources are small, the defender should defend the most important elements, and when the defense resources are large, the defender should allocate the same resources to defend each element to obtain the maximum benefit. This paper provides new solution ideas for the security problems under the offense and defense game in WSNs.
Examination of the Accuracy of Movement Tracking Systems for Monitoring Exercise for Musculoskeletal Rehabilitation
Authors: Obukhov Artem , Volkov Andrey , Pchelintsev Alexander , Nazarova Alexandra , Teselkin Daniil , Surkova Ekaterina , Fedorchuk Ivan
Published: September 2023

When patients perform musculoskeletal rehabilitation exercises, it is of great importance to observe the correctness of their performance. The aim of this study is to increase the accuracy of recognizing human movements during exercise. The process of monitoring and evaluating musculoskeletal rehabilitation exercises was modeled using various tracking systems, and the necessary algorithms for processing information for each of the tracking systems were formalized. An approach to classifying exercises using machine learning methods is presented. Experimental studies were conducted to identify the most accurate tracking systems (virtual reality trackers, motion capture, and computer vision). A comparison of machine learning models is carried out to solve the problem of classifying musculoskeletal rehabilitation exercises, and 96% accuracy is obtained when using multilayer dense neural networks. With the use of computer vision technologies and the processing of a full set of body points, the accuracy of classification achieved is 100%. The hypotheses on the ranking of tracking systems based on the accuracy of positioning of human target points, the presence of restrictions on application in the field of musculoskeletal rehabilitation, and the potential to classify exercises are fully confirmed.
Robust Localization for Underground Mining Vehicles: An Application in a Room and Pillar Mine
Authors: Inostroza Felipe , Parra-Tsunekawa Isao , Ruiz-del-Solar Javier
Published: September 2023

Most autonomous navigation systems used in underground mining vehicles such as load–haul–dump (LHD) vehicles and trucks use 2D light detection and ranging (LIDAR) sensors and 2D representations/maps of the environment. In this article, we propose the use of 3D LIDARs and existing 3D simultaneous localization and mapping (SLAM) jointly with 2D mapping methods to produce or update 2D grid maps of underground tunnels that may have significant elevation changes. Existing mapping methods that only use 2D LIDARs are shown to fail to produce accurate 2D grid maps of the environment. These maps can be used for robust localization and navigation in different mine types (e.g., sublevel stoping, block/panel caving, room and pillar), using only 2D LIDAR sensors. The proposed methodology was tested in the Werra Potash Mine located at Philippsthal, Germany, under real operational conditions. The obtained results show that the enhanced 2D map-building method produces a superior mapping performance compared with a 2D map generated without the use of the 3D LIDAR-based mapping solution. The 2D map generated enables robust 2D localization, which was tested during the operation of an autonomous LHD, performing autonomous navigation and autonomous loading over extended periods of time.
A Novel Deep Convolutional Neural Network Combining Global Feature Extraction and Detailed Feature Extraction for Bearing Compound Fault Diagnosis
Authors: Han Shuzhen , Niu Pingjuan , Luo Shijie , Li Yitong , Zhen Dong , Feng Guojin , Sun Shengke
Published: September 2023

This study researched the application of a convolutional neural network (CNN) to a bearing compound fault diagnosis. The proposed idea lies in the ability of CNN to automatically extract fault features from complex raw signals. In our approach, to extract more effective features from a raw signal, a novel deep convolutional neural network combining global feature extraction with detailed feature extraction (GDDCNN) is proposed. First, wide and small kernel sizes are separately adopted in shallow and deep convolutional layers to extract global and detailed features. Then, the modified activation layer with a concatenated rectified linear unit (CReLU) is added following the shallow convolution layer to improve the utilization of shallow global features of the network. Finally, to acquire more robust features, another strategy involving the GMP layer is utilized, which replaces the traditional fully connected layer. The performance of the obtained diagnosis was validated on two bearing datasets. The results show that the accuracy of the compound fault diagnosis is over 98%. Compared with three other CNN-based methods, the proposed model demonstrates better stability.
Beyond Human Detection: A Benchmark for Detecting Common Human Posture
Authors: Li Yongxin , Wu You , Chen Xiaoting , Chen Han , Kong Depeng , Tang Haihua , Li Shuiwang
Published: September 2023

Human detection is the task of locating all instances of human beings present in an image, which has a wide range of applications across various fields, including search and rescue, surveillance, and autonomous driving. The rapid advancement of computer vision and deep learning technologies has brought significant improvements in human detection. However, for more advanced applications like healthcare, human–computer interaction, and scene understanding, it is crucial to obtain information beyond just the localization of humans. These applications require a deeper understanding of human behavior and state to enable effective and safe interactions with humans and the environment. This study presents a comprehensive benchmark, the Common Human Postures (CHP) dataset, aimed at promoting a more informative and more encouraging task beyond mere human detection. The benchmark dataset comprises a diverse collection of images, featuring individuals in different environments, clothing, and occlusions, performing a wide range of postures and activities. The benchmark aims to enhance research in this challenging task by designing novel and precise methods specifically for it. The CHP dataset consists of 5250 human images collected from different scenes, annotated with bounding boxes for seven common human poses. Using this well-annotated dataset, we have developed two baseline detectors, namely CHP-YOLOF and CHP-YOLOX, building upon two identity-preserved human posture detectors: IPH-YOLOF and IPH-YOLOX. We evaluate the performance of these baseline detectors through extensive experiments. The results demonstrate that these baseline detectors effectively detect human postures on the CHP dataset. By releasing the CHP dataset, we aim to facilitate further research on human pose estimation and to attract more researchers to focus on this challenging task.
Metal Particle Detection by Integration of a Generative Adversarial Network and Electrical Impedance Tomography (GAN-EIT) for a Wet-Type Gravity Vibration Separator
Authors: Ibrahim Kiagus Aufa , Sejati Prima Asmara , Darma Panji Nursetia , Nakane Akira , Takei Masahiro
Published: September 2023

The minor copper (Cu) particles among major aluminum (Al) particles have been detected by means of an integration of a generative adversarial network and electrical impedance tomography (GAN-EIT) for a wet-type gravity vibration separator (WGS). This study solves the problem of blurred EIT reconstructed images by proposing a GAN-EIT integration system for Cu detection in WGS. GAN-EIT produces two types of images of various Cu positions among major Al particles, which are (1) the photo-based GAN-EIT images, where blurred EIT reconstructed images are enhanced by GAN based on a full set of photo images, and (2) the simulation-based GAN-EIT images. The proposed metal particle detection by GAN-EIT is applied in experiments under static conditions to investigate the performance of the metal detection method under single-layer conditions with the variation of the position of Cu particles. As a quantitative result, the images of detected Cu by GAN-EIT ψ̿GAN in different positions have higher accuracy as compared to σ*EIT. In the region of interest (ROI) covered by the developed linear sensor, GAN-EIT successfully reduces the Cu detection error of conventional EIT by 40% while maintaining a minimum signal-to-noise ratio (SNR) of 60 [dB]. In conclusion, GAN-EIT is capable of improving the detailed features of the reconstructed images to visualize the detected Cu effectively.
Low-Temperature 3D Printing Technology of Poly (Vinyl Alcohol) Matrix Conductive Hydrogel Sensors with Diversified Path Structures and Good Electric Sensing Properties
Authors: Zhao Qian , Liu Chang , Chang Yanjiao , Wu Han , Hou Yihao , Wu Siyang , Guo Mingzhuo
Published: September 2023

Novel and practical low-temperature 3D printing technology composed of a low-temperature 3D printing machine and optimized low-temperature 3D printing parameters was successfully developed. Under a low-temperature environment of 0–−20 °C, poly (vinyl alcohol) (PVA) matrix hydrogels including PVA-sodium lignosulphonate (PVA-LS) hydrogel and PVA-sodium carboxymethylcellulose (PVA-CMC) hydrogel exhibited specific low-temperature rheology properties, building theoretical low-temperature 3D printable bases. The self-made low-temperature 3D printing machine realized a machinery foundation for low-temperature 3D printing technology. Combined with ancillary path and strut members, simple and complicated structures were constructed with high precision. Based on self-compiling G-codes of path structures, layered variable-angle structures with high structure strength were also realized. After low-temperature 3D printing of path structures, excellent electrical sensing functions can be constructed on PVA matrix hydrogel surfaces via monoplasmatic silver particles which can be obtained from reduced reactions. Under the premise of maintaining original material function attributes, low-temperature 3D printing technology realized functionalization of path structures. Based on “3D printing first and then functionalization” logic, low-temperature 3D printing technology innovatively combined structure–strength design, 3D printable ability and electrical sensing functions of PVA matrix hydrogels.
Treatment of Produced Water Using Prepared Activated Carbon-Based Sewage Sludge
Authors: Al Dawery Salam K. , Al-Sawai Maroa K. , Al Muzami Ghatara M. S. , Annamareddy Sri Hari K. , Al Dawari Muataz S. , Harharah Ramzi H. , Harharah Hamed N. , Amari Abdelfattah
Published: September 2023

Removal of organic pollutants and metal ions from produced water by adsorption, using prepared activated carbon (AC) from sewage sludge, with chemical activations using NaOH, KOH and ZnCl2 separately and pyrolysis at different temperatures (500, 600 and 700 °C). Pure sludge and prepared ACs were analyzed using FTIR and XRD. The results showed 18% crystallinity compared to that of commercial AC, which has 44% crystallinity. The results of FTIR demonstrate that the properties of the post-treated affect the final products depending on the method used and that it contains similar functional groups to those present in the commercial AC, but at a higher peak intensity. Adsorption treatments were carried out at 25, 35 and 45 °C solution temperatures. The results showed that the removal of pollutants from produced water using prepared AC with all types of chemical activations reached 99.5%, such as commercial AC with 0.06 g dosage of adsorbent at pyrolysis temperatures of 500 and 600 °C and a solution temperature of 25 °C. The obtained results refer to the mechanism of exothermic reaction and physical adsorption. It was observed that despite the lower dosage of adsorbent of 0.01 g, a sufficient treatment of pollutants was achieved. This reveals the effectiveness of using sewage sludge as a cheap adsorbent. Also, using pure sewage sludge, the adsorption data showed a 95.2% removal of the pollutants. This result indicated that pure sludge has an efficient adsorption capacity and can be utilized as a cheap and environmentally friendly material. For the removal of manganese and cadmium metal ions from the produced water, the resultant data showed that more than 90% of manganese was adsorbed and more than 97% of cadmium was adsorbed, especially when using pure sewage sludge and prepared activated carbon with NaOH chemical activation at pyrolysis temperatures of 500 °C and 600 °C.
The Role of Techno-Stress and Psychological Detachment in the Relationship between Workload and Well-Being in a Sample of Italian Smart Workers: A Moderated Mediated Model
Authors: Mondo Marina , Pileri Jessica , Barbieri Barbara , Bellini Diego , De Simone Silvia
Published: September 2023

Well-being conditions at work are determined by the balance between the demands from the organizational context and the perception of people to possess resources concerning the ability to cope with such requests. The pandemic caused by COVID-19 has changed working conditions, and employees have had to adapt to smart working (SW) by bringing new resources into play to meet new demands. Many organizations are questioning how to implement SW after the pandemic. According to the JD-R model, the present study considered workload during smart working and Techno-stress (the perceived stress concerning the use of technologies) as new requests (i.e., demands) coming from the organization and Psychological Detachment (the ability to create psychological distancing from work) as a personal resource. We investigated the moderator role of Psychological Detachment in the relationship between workload in SW and Well-being, mediated by Techno-stress (in its three dimensions: Techno-Overload, Techno-Invasion, and Techno-Complexity). The sample is made up of 622 Italian public administration employees who completed a questionnaire containing the following scales: Quantitative Workload Inventory, Well-being Index, Psychological Detachment, Techno-stress Creator Scale. Mediation and moderate-mediation models have been tested with PROCESS Macro. Findings showed that Techno-Invasion and Techno-Complexity fully mediate the relationship between workload in SW and well-being. Psychological detachment moderates the effect of the workload on Well-being, which in turn is mediated by Techno-Invasion. Furthermore, findings suggest the importance of identifying protective factors that can mitigate the workload effects on the employees’ well-being in SW.
Access to Labor Market and Integration of Moroccan Women in Andalusia: The Two Sides of the Coin
Authors: Ortega-de-Mora Fabiola , Terrón-Caro Teresa
Published: September 2023

Given the multifactorial nature of the integration processes of migrants, this article analyzes the correlation between inclusion in the labor market and the integration of Moroccan women residing in Andalusia. An intersectional approach is used, addressing three key variables: youth, gender, and ethnicity. To this end, a qualitative methodology has been developed based on conducting twenty-nine in-depth interviews with Moroccan women residing in Andalusia. Non-probabilistic intentional sampling has been used through the snowball technique. The results have shown the ambivalence that insertion in the labor market implies for these women, being, on the one hand, an area of oppression, rejection, and discrimination, and on the other, one of the essential factors to achieve the full integration of the protagonists, granting them agency and resistance. It concludes by highlighting the importance of favoring the successful transition and inclusion in the labor market of these women, being fundamental to the development of strategies and political proposals aimed at reducing, even eliminating, the structural violence that continues to prevail in this area.
Explanatory Factors of School Climate and School Identification: An Analysis of Multilevel Latent Profiles
Authors: Gálvez-Nieto José Luis , Polanco-Levicán Karina , Navarro-Aburto Braulio , Béltran-Véliz Juan Carlos
Published: September 2023

School climate is a highly relevant variable that is associated with a series of positive results. However, there are still few studies that have statistically modelled the simultaneous influence of structural variables at the school level on the individual perception of the school climate and identification. This study had two objectives: (1) Identify school climate and school identification profiles at the individual and school levels. (2) Relate school climate and school identification profiles to factors located at the individual and school levels. The participants were selected from a probabilistic and stratified sample, n = 2070 adolescents (40.6% men, 59.4% women), aged between 13 and 18 years (M = 14.64, SD = 0.718), from 28 secondary schools in Chile. The results allowed us to identify four clusters at the student level and two classes of school climate at the school level. The explanatory factors at the individual level were Cognitive engagement (p < 0.001), Academic Expectations (p < 0.001), Positive Attitude to Authority (p < 0.001) and Family Conflict (p < 0.001). The explanatory factor at the school level was the school vulnerability index (p = 0.031). Finally, the explanatory effects of factors at individual and school levels on school climate are theoretically discussed.
Distribution Pattern of Urban Street Trees in Rome (Italy): A Multifactorial Evaluation of Selection Criteria
Authors: D’Amato Luca , Bartoli Flavia , Savo Valentina , Paiella Paolo Alfredo , Messina Francesco , Caneva Giulia
Published: September 2023

Street trees play a significant ecological role in modern urban ecosystems, but usually the selection criteria follow pragmatic reasons rather than bio-ecological suitability. Understanding the influence of such factors can be relevant, especially in cities having a certain complexity and area. This paper aims to analyze the variation in the distribution of street tree species within the city’s municipia of Rome to determine the influence of some factors in the selection process. Here, we have described the species of street trees in fourteen municipia of Rome, and we created five clusters of factors (bio-ecological, aesthetic, historical–cultural, health, and economic) that could constitute selection criteria for street trees. From our data analysis, the municipia of Rome were grouped into four main groups and the choice of trees was based on multiple selection criteria. Foliage type, longevity, fruit type, autochthony, and economic value were the primary criteria. In 90–100% of municipia, deciduous species dominate, with 50–150 years longevity, dry fruits, exotic species, and prices of <€500 per tree. Additionally, the flower type, allergenicity, size class, and cultural value were the secondary criteria. The biological and ecological characteristics of trees are key factors to consider in order to reduce the management of street trees and relative costs.
Optimized Power Management Approach for Photovoltaic Systems with Hybrid Battery-Supercapacitor Storage
Authors: Rekioua Djamila , Kakouche Khoudir , Babqi Abdulrahman , Mokrani Zahra , Oubelaid Adel , Rekioua Toufik , Azil Abdelghani , Ali Enas , Alaboudy Ali H. Kasem , Abdelwahab Saad A. Mohamed
Published: September 2023

The paper addresses the ongoing and continuous interest in photovoltaic energy systems (PESs). In this context, the study focuses on an isolated photovoltaic system with hybrid battery-supercapacitor storage (HBSS). The integration of supercapacitors (SCs) in this system is particularly important because of their high specific power density. In photovoltaic (PV) systems, multi-storage systems use two or more energy storage technologies to enhance system performance and flexibility. When batteries and supercapacitors are combined in a PV system, their benefits are maximized and offer a more reliable, efficient, cost-effective energy storage option. In addition, effective multi-storage power management in a PV system needs a solid grasp of the energy storage technologies, load power demand profiles, and the whole system architecture. This work establishes a battery-supercapacitor storage system (HBSS) by combining batteries and supercapacitors. The primary objective is to devise a novel management algorithm that effectively controls the different power sources. The algorithm is designed to manage the charge and discharge cycles of the hybrid battery-supercapacitor energy storage system (HBSS), thereby guaranteeing that the state of charge (SOC) for both batteries and supercapacitors is maintained within the specified range. The proposed management algorithm is designed to be simple, efficient, and light on computational resources. It efficiently handles the energy flow within the HBSS, optimizing the usage of both batteries and supercapacitors based on real-time conditions and energy demands. The proposed method ensures their longevity and maximizes their performance by maintaining the SOC of these energy storage components within the specified limits. Simulation results obtained from applying the management strategy are found to be satisfactory. These results show that the proposed algorithm maintains the SOC of batteries and supercapacitors within the desired range, leading to improved energy management and enhanced system efficiency.
Characterization and Resource Potential of Li in the Clay Minerals of Mahai Salt Lake in the Qaidam Basin, China
Authors: Pan Tong , Chen Jianzhou , He Mao-Yong , Ding Chengwang , Ma Yuliang , Liang Hui , Zhang Tao , Du Xiaochun
Published: September 2023

The strategic importance of lithium in global development has become increasingly prominent due to the rapid growth of the new energy automotive industry and the continuous advancements in controllable nuclear fusion technology. Lithium minerals in salt lakes possess advantageous characteristics, such as abundant reserves, environmental sustainability, and economic viability. Furthermore, with ongoing improvements in the lithium extraction process, the availability of lithium minerals in salt lakes is expected to further increase. The Qaidam Basin Salt Lake in China has served as the location for the establishment of numerous lithium carbonate production enterprises, resulting in a lithium carbonate production volume of 7 × 104 t/yr in 2022. How to meet the growing need for lithium resources has become an enterprise focus. Nevertheless, there are large amounts of clay minerals in and around the bottom and periphery of the salt lake in the Qaidam Basin, and whether these minerals are of exploitable value, regardless of the state of the occurrence of lithium resources, remains unexplored. To ascertain the attributes, extent, and distribution of the lithium occurrence within the clayey layer of the Qaidam Basin, as well as to assess its resource potential, a total of 87 drill holes were conducted within a designated area of the Mahai Basin, which is a secondary basin in the Qaidam Basin. The subsequent analysis encompassed the examination of the lithium content within the clay minerals, the mineral composition of the clay, and, ultimately, the evaluation of the resource potential within the region. Compared with Quaternary salt lake deposits, brine deposits in gravel pores, and the Paleogene–Neogene Li-bearing salt deposits that have been studied, it is suggested that this is a novel form of a clay-type sedimentary Li deposit within the Qaidam Basin. The findings of this research will serve as a fundamental basis for future endeavors pertaining to the exploration and exploitation of lithium deposits within salt lake areas.
The Role of the Government in Green Finance, Foreign Direct Investment, Technological Innovation, and Industrial Structure Upgrading: Evidence from China
Authors: Wang Chenggang , Qiao Guitao , Ahmad Mahmood , Ahmed Zahoor
Published: September 2023

This study utilizes data from China’s 31 provinces, collected from 2007 to 2021, to establish a green finance (GF) index and investigate its impact on industrial structure upgrading (IS). In addition to the direct impact, this study investigates the indirect influence of GF on industrial structure upgrading through technological innovation (Tech) and foreign direct investment (FDI). Furthermore, this study analyzes the moderating role of environmental regulation intensity (ERI) and government intervention on the relationship between GF and industrial structure upgrading. The empirical findings demonstrate a positive relationship between GF and industrial structure upgrading, which remains robust after conducting a robustness analysis and stability tests. Moreover, GF positively impacts industrial structure upgrading by stimulating Tech and attracting FDI. Furthermore, the ERI is observed to positively and significantly moderate the impact of GF on industrial structure upgrading, while high levels of government intervention hinder the promoting effect of GF on industrial structure upgrading. Lastly, the association between GF development and industrial structure upgrading exhibits regional and market heterogeneity, with the most notable impact observed in coastal areas and regions with higher levels of market orientation. This study presents comprehensive suggestions for facilitating the improvement of GF and the upgrading of industrial structures.
The Influence of the University Laboratory Safety Climate on Students’ Safety Behavior: The Parallel Mediating Effects of Ability and Motivation
Authors: Liu Yuan , Feng Wei , Zhang Guirong , Zhang Ying
Published: September 2023

Students’ unsafe behavior is the main factor related to accidents in university laboratories. The safety climate is an important factor that affects individual safety behavior on the organizational level. Therefore, to improve the effect of university laboratory safety management, based on the theoretical framework of AMO and the SEM method, the influence of the laboratory safety climate on the safety compliance behavior and safety participation behavior of 500 university students in China was investigated and analyzed. The results show that safety ability and safety motivation play parallel mediating roles, and their synergistic effect promotes the generation of safety behavior: the safety climate in the laboratory has a direct positive effect on both safety compliance behavior and safety participation behavior; safety knowledge and safety skills have significant mediating effects on both safety compliance behavior and safety participation behavior in the laboratory safety climate; external safety motivation has a significant mediating effect on safety compliance behavior and safety participation behavior in the laboratory safety climate; and internal safety motivation does not have a mediating effect on safety compliance behavior and safety participation behavior in the laboratory safety climate. To improve students’ safety behavior performance, measures such as strengthening the construction of the dynamic improvement mechanism of the laboratory safety climate, optimizing the laboratory safety access system, and taking comprehensive measures to ensure the continuous positive influence of the safety climate on students’ safety behavior can be adopted.
Reliability Analysis of Nuclear Power Plant Electrical System Considering Common Cause Failure Based on GO-FLOW
Authors: Wang Zhijian , Sun Yao , Zhao Jie , Dong Xuzhu , Chen Chen , Wang Bo , Wu Haocheng
Published: September 2023

The reliability of nuclear power plant electrical systems is an important guarantee of nuclear safety, and the common fault failure problem arising from redundant design and intelligent control may greatly affect reliability assessment results. Combined with the features of repairability, multi-state characteristics, and common fault failure of nuclear power plant electrical systems, a reliability analysis method of nuclear power plant electrical systems based on the GO-FLOW method considering common fault failure is proposed. This study firstly constructs the algorithmic model of combining operators of repairable components and the equivalent model of reliability parameters of multi-mode repairable components, then establishes a probability calculation model of common fault failure for repairable systems by considering the quantitative computation of the common signaling system model, and finally, quantitatively calculates the reliability of nuclear power plant electrical systems and their influencing factors. The example simulation calculates the reliability of the external power supply system and the electrical system of the nuclear power plant, analyzes the influence of the common signal processing and the common fault failure factors on the reliability of the electrical system of the nuclear power plant, and verifies the validity of the proposed method. The results show that the common fault failure factors have a large impact on the system reliability analysis; the common fault failure of the standby diesel generator set will seriously reduce the reliability of the electrical system, which can be improved by installing additional standby diesel generators.
Low-Cost 3D Virtual and Dynamic Reconstruction Approach for Urban Forests: The Mesiano University Park
Authors: Chioni Chiara , Maragno Anna , Pianegonda Angelica , Ciolli Marco , Favargiotti Sara , Massari Giovanna A.
Published: September 2023

Urban forests, parks, and gardens are fundamental components of urban sustainability, resilience, and regenerative dynamics. Designers, architects, and landscape architects could smartly manage these dynamic ecosystems if efficiently provided with design-oriented digital tools, technologies, and techniques. However, practitioners lack knowledge and standardized procedures for their uses. The rise of low-cost sensors to generate 3D data (e.g., point clouds) in forestry can also effectively support monitoring, analysis, and visualization purposes for greenery in urban contexts. Adopting an interdisciplinary approach—involving the fields of forestry, geomatics, and computer science—this contribution addresses these issues and proposes a low-cost workflow for 3D virtual reconstructions of urban forests to support information management activities and thus landscape architecture applications. By connecting a wide range of methods (i.e., spherical photogrammetry, point cloud modeling), tools (i.e., 360° camera, tablet with lidar sensor), and software (i.e., Agisoft Metashape, CloudCompare, Autodesk AutoCAD), the proposed workflow is defined and tested in the development of dynamic virtual representations for a plot of the Mesiano University park in Trento (Italy). Finally, comparing acquisition, processing, and elaboration methodologies and their results, the possibility of developing digital twins of urban forests is envisioned.
A Study for the Improvement of the Energy Performance Certificate (EPC) System in Turkey
Authors: Yilmaz Didem Gunes , Cesur Fatma
Published: September 2023

This study aims to examine the current status of Turkey’s energy consumption and energy performance system and draw improvements. To this aim, this study adopted a qualitative research method. A literature review was conducted regarding the problems related to the EPC system. Following this, a series of research questions were derived, and answers were sought through expert group interviews. The problems were categorized into three headings: the EPC system and calculation problems, problems in the regulation and inspection process and, finally, the perspective on the construction industry to the EPC system is examined in the case of Turkey. Deficiencies in the rating system and calculation, regulation and inspection, and perspective of the EPC system in Turkey were identified. Suggestions for the development of EPC in Turkey were made to make it comparable with the systems in EU countries. As one of the outcomes of the study, Turkey should focus on the use of renewable energy, taking into account its geographical advantage. In addition, a more detailed micro-zoning that focuses on regional differences should be carried out, and the authorities should introduce a better control mechanism for the EPC system.
Assessing the Outcomes of Digital Transformation Smartization Projects in Industrial Enterprises: A Model for Enabling Sustainability
Authors: Bashynska Iryna , Mukhamejanuly Sabit , Malynovska Yuliia , Bortnikova Maryana , Saiensus Mariia , Malynovskyy Yuriy
Published: September 2023

Digital transformation and smartization projects in industrial enterprises have become increasingly prevalent in recent years, aiming to enhance operational efficiency, productivity, and sustainability. Assessing the outcomes of such projects is crucial to determine their effectiveness in enabling sustainability. In this context, a model for evaluating digital transformation smartization projects (DTSP) outcomes can be developed to provide a comprehensive assessment framework. This study aims to develop and test a model for diagnosing the results of implementing digital transformation smartization projects for industrial enterprises. The methodology presented in this article involves using statistical tests to detect multicollinearity and heteroskedasticity in regression models. It also proposes an economic–mathematical model with three objective functions to optimize the implementation of smartization projects, considering cost minimization, deviations from planned business indicators, and production rhythm disruptions. The most important results of the survey are (1) a proposed matrix for the selection of indicators for diagnosing the results of the implementation of digital transformation smartization projects for industrial enterprises, (2) a two-level model for the economic evaluation of diagnosed digital transformation smartization projects, which can be used at any stage of the digital transformation smartization project and based on it, conclusions can be drawn regarding the effectiveness of the implementation of both the entire project and its individual stages, objects, or elements. The advantage of the model is the possibility of its decomposition, that is, a division into separate parts with the possibility of introducing additional restrictions or, conversely, reducing the level of requirements for some of them. The results were tested at industrial enterprises in Ukraine and proved their practical significance.
Does Attitude or Intention Affect Behavior in Sustainable Tourism? A Review and Research Agenda
Authors: Wut Tai Ming , Lee Daisy , Lee Stephanie Wing
Published: September 2023

This study presents a critical literature review on the tourist attitude–behavior gap and intention–behavior gap in sustainable tourism research and proposes future research directions. A systematic review was conducted using preferred reporting items for systematic review and meta-analysis (PRISMA) on the existing literature from the Scopus and Web of Science databases. Key research topics in attitude–behavior gaps are the role of environmental knowledge, protected area management, the role of service quality, risk perception, moral licensing, sustainability communication, business owners in tourism, environmental concern, tourist psychology, and intervention. Key research topics in the intention–behavior gaps of sustainable tourism are green certification or label, value, rationality and social desirability, motivation, trust, inconvenience, and quality. Four emerging research trends were discovered in recent years: (1) increased use of mixed methods and surveys; (2) consideration of green or environmental knowledge; (3) role of green certification; and (4) consideration of tourist moral values. Recommended future research directions include theoretical development studies in the hospitality sector, cross-cultural comparisons, investigation, of under-researched tourism sectors, and new research methodologies. This review provides an overview of research on the attitude–behavior gap and the intention–behavior gap in sustainable tourism. Our study proposes a new framework for the attitude–behavior gap and the intention–behavior gap, departing from the theory of planned behavior. We identify direct and indirect factors that influence sustainable tourist behavior, with sustainable tourist attitude and intention serving as mediators. Overall, our findings offer valuable insights into the complex relationship between attitudes, intentions, and behaviors in sustainable tourism.
Comprehensive Analysis of Extreme Meteorological Conditions for the Safety and Reliability of Floating Photovoltaic Systems: A Case on the Mediterranean Coast
Authors: Korkmaz Mehmet Seren , Toker Emir , Şahin Ahmet Duran
Published: September 2023

In recent decades, renewable energy projects have required careful consideration of environmental factors. This study investigates the impact of a mid-latitude cyclone on planned floating photovoltaic (FPV) facilities in Antalya, Turkey, focusing on the severe thunderstorm events that brought heavy rainfall and tornadoes in January 2019. Synoptic analysis reveals a deep cut-off low over the Genoa Gulf, causing trough formation and vertical cloud development due to moisture convergence. Warm air advection pushed an unstable thunderstorm system northward along an occluded front. Using the Weather Research and Forecast (WRF) model, sensitivity analysis is conducted, highlighting regional variations in wind speeds. The model outputs are compared with observations, identifying the best configuration using statistical indicators. The Mellor–Yamada–Janjic (MYJ) planetary boundary layer (PBL) scheme and the Milbrandt microphysics scheme produced better results in the western and central regions. The model output of the best configurations is used to calculate regional wave characteristics with a modified Shore Protection Manual (SPM) method for water reservoirs. These findings offer invaluable insights for future FPV projects, providing a better understanding of how to address challenges posed by extreme weather conditions and how to enhance system safety and reliability.
Policy Perspective on Governmental Implicit Debt Risks of Urban Rail Transit PPP Projects in China: A Grounded Theory Approach
Authors: Zhang Yajing , Jin Weijian , Yuan Jingfeng
Published: September 2023

Public–private partnership (PPP) projects have the features of extended investment cycles, diminished returns, and high demand for technology. Inadequate utilization of these projects may result in an accumulation of new implicit debt for the government. Consequently, it becomes imperative for the government to manage and mitigate implicit debt risks associated with urban rail transit PPP projects, which is a crucial prerequisite for ensuring the progression of such projects and the unhindered functioning of the financial system. The objective of this study is to investigate the factors that influence government implicit debt risks in urban rail transit PPP projects from the perspective of policy. This study employs the grounded theory method to develop a comprehensive framework model that identifies the influencing factors of government implicit debt risk in urban rail transit public–private partnership (PPP) projects. The contributions of this study are twofold: (1) it highlights the role of policy as a significant determinant of implicit debt risks of urban rail PPP projects, which contain governmental subsidies, external environmental risk sharing, and supporting measures. Specifically, government subsidies directly contribute to the government’s implicit expenses, thereby impacting the level of implicit debt risks associated with urban rail transit PPP projects. Supporting measures exert an indirect influence on the implicit debt risks of the government, thereby imposing a significant burden on local fiscal expenditure. External environmental risk sharing, as an external factor, leads to an increase in fiscal expenditure due to the government’s social responsibility; and (2) it provides a qualitative method that examines the government implicit risk factors associated with urban rail trait PPP projects based on grounded theory. The model that examines the influencing factors of government implicit debt risk in urban rail transit PPP projects adopts a policy perspective, which can inform policymakers on a heretofore unexplored adverse effect of guarantee policy.
The Spatial Distribution of Taxi Stations in Bangkok
Authors: Weladee Suthikasem , Sanit Peamsook
Published: September 2023

Taxis play a crucial role as an on-demand transportation mode in developing countries due to perceived inefficiencies of cities’ public transportation systems. However, studies on the locational distribution of taxis in urban areas are limited, despite the need to improve passenger service quality by balancing the demand and supply of taxi services. Notably, taxi stations possess distinct characteristics compared with other public transport stations that serve passengers directly; in contrast, taxi stations solely support taxi drivers in locations where they begin and conclude their work. This study aims to determine the spatial distribution pattern and assess the agglomeration economies of taxi stations, using Bangkok as a case study, a city with a significant number of registered taxis and dispersed taxi stations. This research takes into account various spatial variables, including land price, land use mix index, population density, and gas station locations. The primary tool for analyzing the spatial distribution pattern was the spatial statistics model, employing ArcGIS 10.8 software. The analysis consisted of three steps: testing for clustered or dispersed patterns using Moran’s I, applying Anselin’s local Moran’s I (LISA) to examine the relationship between taxi station coordinates and spatial variables such as land price, land use mix index, and population density, and evaluating the relationship between taxi stations and energy service stations using the network analysis tool. The results revealed that taxi stations exhibited a spatially clustered pattern and were closely correlated with the land use mix index, land price, and population density, as indicated by Moran’s index values of 0.425, 0.328, and 0.373, respectively, especially those located within a 3000 m radius of gas stations. These findings elucidate the location selection of taxi stations, which tend to prioritize areas that can generate maximum profits for the taxi business rather than those with minimal location costs. They also tend to be situated in proximity to market areas. Additionally, the study recommends that the government consider promoting electric taxis as a sustainable mode of urban transport in the future to reduce the usage of natural gas (NGV) and liquefied petroleum gas (LPG).
The Impacts of COVID-19 on the Visitor Attendance of Cultural and Natural Heritage: A Case Study of the South Moravian Region
Authors: Tuzová Kristýna , Vaishar Antonín , Šťastná Milada , Urbanová Martina
Published: September 2023

Tourism is one of the world’s most affected sectors by the impact of the COVID-19 pandemic. This article deals with the assessment of the impact of COVID-19 on the visitation of the South Moravian Region, including important cultural and natural sites, based on the analysis of empirical statistical data in the last decade and the calculation of the year-on-year change in attendance between 2019 and 2022. According to the results, the number of visitors to the South Moravian Region in 2020 fell by almost half, including a decrease of a quarter of visitors to cultural monuments compared to 2019. On the other hand, visits to natural areas with no restricted access increased by a fifth after 2020, but natural areas with restricted access fell by more than 40%. From 2021, attendance of the South Moravian Region began to increase slightly, and in 2022, it reached ninety percent of the level before 2019, including attendance at cultural and natural sites. The results of the research confirmed the growing trend in visitors to the South Moravian Region, including cultural and natural monuments, which were significantly influenced by the impact of COVID-19 on tourism after 2020, with a recovery of tourism in 2022.
The Effects of Varying Combinations of Dietary Selenium, Vitamin E, and Zinc Supplements on Semen Characteristics and Antioxidant Enzyme Activity of Spermatozoa in 1-Year-Old Native Turkish Ganders
Authors: Taşkesen Hulüsi Ozan , Baş Hatice , Boz Mehmet Akif , Sarıca Musa , Erensoy Kadir , Dotas Vassilios , Symeon George
Published: September 2023

The aim of this study was to determine the effects of dietary Selenium (Se), Vitamin E (Vit E), and Zinc (Zn) and their various combinations on semen quantity, quality, and oxidative enzyme activities of spermatozoa in 1-year-old native Turkish ganders. In this study, 48 1-year-old native Turkish ganders were used. The ganders were randomly divided into 8 dietary treatment groups (Control, Se, Vit E, Zn, Se + Vit E, Se + Zn, Vit E + Zn, Se + Vit E + Zn) with 6 birds each. In addition to the control diet, specific amounts of 0.3 mg/kg Se, 100 mg/kg Vit E, and 100 mg/kg Zn were added to the diets of each treatment group. Semen volume, sperm concentration, sperm motility, sperm quality factor (SQF), and total live and normal sperm percentage were the lowest in the control group and highest in the ganders fed with the Se + Vit E + Zn combination. While the percentage of macro-cephalic and dead sperm was highest in the ganders fed with control feed, the lowest percentage of dead sperm was found in the sperm of the ganders fed with Vit E and Se + Vit E + Zn combinations. The lowest glutathione peroxidase enzyme (GPx) and glutathione-S-transferase (GST) and the highest amount of malondialdehyde (MDA) were determined in the spermatozoa of the control group ganders. This study revealed that the combined use of Se, Vit E, and Zn in the diet maintained higher semen quantity and quality in 1-year-old native Turkish gander despite the advancing reproduction season compared to the control group.