bluuebunny/crossref_metadata_2025 huggingface dataset:
Design and Implementation of a Three-Dimensional CAD Graphics Support Platform for Pumps Based on Open CASCADE
Authors: Liu Houlin , Wu Zhicai , Yuan Shuolei , Wang Yong , Dong Liang
Published: August 2023

In the pump industry, designers commonly utilize mainstream three-dimensional computer-aided design (CAD) software (Unigraphics NX 12.0 and SolidWorks 2023). However, these CAD packages are generic and not optimized for the specific requirements of the pump industry. This leads to a lack of flexibility and increased complexity in their usage, as well as higher computational demands, resulting in elevated learning and operational costs. Additionally, there are concerns about potential information leaks and software restrictions. In this paper, we studied the organization architecture of commercial three-dimensional CAD software, and compared and analyzed the geometric kernels and rendering engines of mainstream three-dimensional software. Using the Open CASCADE geometric kernel and OpenSceneGraph rendering engine, together with the Visual Studio 2021 development environment and Qt interface library, we developed an autonomous copyright three-dimensional CAD graphics support platform for pumps. Based on the three-dimensional platform, we tested the commonly used graphics elements and basic algorithms required for pump modeling, and successfully designed and modeled the impeller and volute casing of a centrifugal pump. Through computational simulations and experimental verifications, we demonstrated that the accuracy and precision of the pump model designed on this platform meets the design requirements, indicating that this platform has practical pump design and modeling capabilities. Compared to commercial three-dimensional CAD software, this platform exhibits superior flexibility and interactivity in three-dimensional modeling that is specifically tailored for pump products. Consequently, it fully satisfies the needs for three-dimensional parameterized modeling and visualization of pumps.
Nonlinear Adaptive Generalized Predictive Control for PH Model of Nutrient Solution in Plant Factory Based on ANFIS
Authors: Wang Yonggang , Zhang Ning , Chen Chunling , Jiang Yingchun , Liu Tan
Published: August 2023

A plant factory is typically considered to be an exceedingly advanced product management system characterized by higher crop yields and better quality control. The pH value of the nutrient solution is crucial for determining the health and productivity of crops. However, the nutrient solution process exhibits inherent complexity, such as parameters uncertainty, multi-disturbances, and strong nonlinearity. Therefore, the traditional control method cannot meet the necessary requirements. The main objective of this paper is to address the issues of parameter uncertainty, strong nonlinearity, and multiple disturbances in the regulation process of the nutrient solution while achieving accurate control of the nutrient solution pH in a plant factory. This is performed so that a dynamic model of a nutrient solution for pH is developed and a nonlinear adaptive controller is presented, which comprises a linear adaptive generalized predictive controller, a nonlinear adaptive generalized predictive controller, and a switching mechanism. The parameters of the controller are adjusted by generalized predictive control (GPC) laws. In this approach, an adaptive neuro-fuzzy inference system (ANFIS) is used to estimate the unmodeled dynamics to depress the influence of nonlinearity on the system. The experiments show that the mean errors and standard errors for gain-scheduling the proportional-integral-derivative (PID) control strategy are 0.1388 and 0.4784, respectively. The mean errors and standard errors for the nonlinear adaptive controller are 0.1046 and 0.3009, respectively. Simulation results indicate that the presented method can acquire a better control effect in the case of various complex situations. Therefore, by achieving precise control of the pH value, it is possible to provide a suitable growth environment for crops, promoting healthy crop growth and increasing crop yield.
Study on Mechanical Behavior and Mechanism of Sandstone under the Coupling Effect of Water Content and Dynamic Load
Authors: Chen Yang , Kang Ting , Wu Chao
Published: August 2023

In the process of underground engineering construction, rock mass often faces the dual influence of dynamic load disturbance and groundwater, it is therefore essential to investigate the mechanical response of the rock mass under the coupling effect of dynamic load disturbance and water content. In this paper, dynamic load impact tests were carried out on sandstone with bullet velocities of 5 m/s, 10 m/s, and 15 m/s and water content of 0, 0.3, 0.6, and 0.9, and the mechanical behavior and mechanism response of water content to sandstone were investigated. The research findings indicate that this study has made significant contributions in quantifying the along grain and trans-grain fractures of microcracks. It has explored the influence of water content and dynamic loading on the strength mechanism of sandstone. It was discovered that the dynamic loading and water content significantly affect the ratio of along grain and trans-grain fractures, thereby influencing the dynamic behavior of sandstone. The findings suggest a negative association between rock strength and water content and that its peak strength rises as the bullet velocity rises. The fracture characteristics of rock are influenced by water content and bullet velocity. The sample’s fracture degree increases with an increase in water content, its particle size distribution map is evident, and there is a positive relation between bullet velocity and fractal dimension. The energy conversion mechanism of the rock is influenced by the water content, as the bullet velocity increases, the absorbed energy density of the rock becomes higher. Furthermore, the correlation between the absorbed energy intensity and density and its fractal dimension is quantified. It is found that energy density and strength are positively correlated. The greater the fractal dimension, the higher the energy density absorbed.
Strain Field Evolution Analysis of Brittle Shale with Initial Fractures Based on DIC
Authors: Liu Weihang , Qu Zhan
Published: August 2023

Wellbore instability mainly occurs in shale formations, and it is of great significance to deeply analyze the characteristics of shale-failure behavior to evaluate the stability of the shale surrounding the well wall during drilling. Through a uniaxial compression experiment and DIC technology, the whole strain field of shale specimens with prefabricated holes and cracks under uniaxial compression is measured. The experimental data of load, displacement and strain field are analyzed comprehensively. The results show that the fracture location and expansion path of shale are closely related to the evolution of the strain field. The evolution of the strain field directly affects the failure behavior of the rock. Under the action of load, local high strain will first appear around the initial shale defects (pores and fractures), and stress concentration will occur. With the increase of load, cracks and failures will first appear in the local high-strain zone, and the failure will spread along the region and path and eventually lead to the overall failure of the rock. The establishment of a description method for shale-failure behavior through strain-field evolution can effectively analyze the crack behavior of shale with initial defects such as holes and cracks and provide theoretical and experimental bases for the stability evaluation of the shale surrounding the well wall, including shale-strength prediction and shale-failure mechanism.
The Tabernacle as a Sacred Feminine Space: The Development of Mythical Images from Biblical Literature to Medieval Kabbalah
Authors: Kara-Ivanov Kaniel Ruth
Published: August 2023

This article compares two biblical accounts: the description of the construction of the Tabernacle (Ex. 25–40), and its connection to the myth of Eve’s creation (Gen. 2). I aim to reveal the literary and symbolic links between “feminine” attributes in these two formative accounts, from their development in biblical literature to their appearances in rabbinic midrash and medieval Kabbalah. My reading seeks to combine gender, myth, and literary study, to explore how erotic images of the sacred were developed and proliferated over generations.
The Sacred Soundscapes of Mountain Wilderness
Authors: Zagorski Marcus
Published: August 2023

Sound and silence in nature intensify our perception of the non-anthropogenic world, of that which seems unaffected by humans and has been considered transcendent, eternal, and sacred. This is especially true in mountain settings. Mountain wilderness manifests a reality beyond anthropocentrism, and this reality becomes perceivable, in part, through sound. When described in the language of soundscape ecology, mountain soundscapes can be characterized by a lack or reduction of anthrophonic sounds and the presence or increase of geophonic and biophonic sounds. When described in the language of philosophy and religion, these soundscapes have been said to offer an ideal space beyond impermanence and rational explanation and contain that which is unchanging and inexplicable. The search for personal contact with that which is unchanging and inexplicable, and the attendant belief that these qualities reveal a higher form of reality, is a search for the sacred, and mountain soundscapes have played a significant but as yet unexamined role in this search. Across different religions and secular practices, in different cultures and historical periods, mountain soundscapes have acted as catalysts for sacred experience. This article uses the combined perspectives of philosophy, religion, and soundscape ecology to map some of the physical and intellectual terrain in which such experience has taken place.
New Muslim Generations: Shaping Self-Image, Reshaping Religion: A Theoretical and Empirical Study of Inter-Religiosity with Muslim Youth in the Alps-Adriatic Region
Authors: Donlic Jasmin
Published: August 2023

This paper focuses on the everyday religious practices of second-generation Muslims who have been born, raised, and socialized in the Alps-Adriatic region. These individuals are developing their own forms of religiousness and perspectives on religion. Religious practices are often regarded as a mere continuation of Islamic traditions in the countries from which their parent generation migrated. However, this generation practices religion in ways that are shaped by socialization in a largely secularized postmodern society and by inter-religiosity, i.e., interaction between people with different beliefs that provokes them to reflect on attitudes, altering their perspectives. Whereas their parents or grandparents more or less lived in their own bubble, mainly because they did not speak the language well enough, the new generation see inter-religious interaction and communication as a matter of course—part of the everyday practices that they take for granted. The empirical section of this paper looks at the experiences and everyday practices of the new Muslim generation. It draws on a participatory project focusing on the photovoice method, which involved Muslim youth not as the subjects of research but as co-researchers. In addition to this approach, the methodology incorporated phenomenological anecdotal research and reading. Adopting a participatory approach, the young people reported on their specific everyday experiences and everyday inter-religious practices. In the process, they described not only their experiences of foreignness and exclusion but also transcultural strategies and ways to address such experiences, such as adopting a self-confident position, taking action, and developing hybrid life plans.
A Techno-Economic Analysis of Natural Gas Valuation in the Amazon Region to Increase the Liquefied Petroleum Gas (LPG) Production in Ecuador
Authors: Ortiz Darwin , Calderón Damián , Viloria Alfredo , Ricaurte Marvin
Published: August 2023

Liquefied petroleum gas (LPG) is a C3/C4’s hydrocarbon mixture used as fuel gas, obtained through natural gas processing or crude oil refining. The Ecuadorian LPG production (~1.88 MMbbl/year) comes from the Shushufindi gas plant and the Esmeraldas refinery. However, LPG production cannot meet the Ecuadorian market demand, and over 90% of this commodity is imported. At the same time, the natural gas produced in the Amazon region is not fully valued. A significant quantity of the associated gas is flared (~100 MMscfd), representing wasted energy with a significant environmental impact. Therefore, this study aimed to develop a technical and economic assessment of the potential natural gas valuation in the Amazon region to increase LPG production. The study started with a detailed review of the associated gas produced in the Amazon region. The data were analyzed considering the geographic location of the hydrocarbon fields, molar composition, flowrates, and operational conditions. Then, a natural gas value chain visualization was proposed and technically analyzed. Finally, an economic feasibility (class V) study was conducted, considering a preliminary analysis of capital expenditure (CAPEX) and an economic balance. The outcome of this study showed that by processing 21.50 MMscfd of associated gas from the Sacha field, domestic LPG production could increase by 30.9%. The required infrastructure consists of conventional processes for natural gas processing, with an estimated CAPEX of 36.6 MMUSD. Furthermore, despite the domestic subsidies of commodities, the potential savings for the country would be 32.13 MMUSD/year, an alternative more economically viable than the current LPG imports. Thus, the investment cost will be justified.
Hyperspectral Target Detection Methods Based on Statistical Information: The Key Problems and the Corresponding Strategies
Authors: Ji Luyan , Geng Xiurui
Published: August 2023

Target detection is an important area in the applications of hyperspectral remote sensing. Due to the full use of information of the target and background, target detection algorithms based on the statistical characteristics of an image are always occupy a dominant position in the field of hyperspectral target detection. From the perspective of statistical information, we firstly presented detailed discussions on the key factors affecting the target detection results, including data origin, target size, spectral variability of target, and the number of bands. Further, we gave the corresponding strategies for several common situations in the practical target detection applications.
Assessment of Land Desertification and Its Drivers in Semi-Arid Alpine Mountains: A Case Study of the Qilian Mountains Region, Northwest China
Authors: Liu Zijin , Si Jianhua , Deng Yanfang , Jia Bing , Li Xinrong , He Xiaohui , Zhou Dongmeng , Wang Chunlin , Zhu Xinglin , Qin Jie , Ndayambaza Boniface , Wang Boyang
Published: August 2023

Land desertification associated with climate change and human activities significantly impacts ecosystem functioning in semi-arid alpine mountains. However, accurately revealing the state of desertification risk and the drivers of its evolution is frequently difficult, especially in the semi-arid alpine mountains. A new theoretical framework that combined qualitative and quantitative concepts has been developed to enhance ecological risk assessment in semi-arid alpine mountains and reveal the causes of desertification. The PSR model, multi-layer hierarchical theory, hierarchical analysis, inverse cloud generating principles, field surveys, structured questionnaires, and remote sensing techniques are all combined in this method. Our results showed that the risk of desertification in the study area exhibited a fluctuating trend between 2000 and 2020, with a period of decrease, followed by an increase, and then a subsequent decrease. However, the risk status remained overall stable, remaining at a light desertification level during the entire period. Desertification risk is driven primarily by climate warming and humidification, which can cause the melting of ice/snow. Additionally, increased rainfall and freeze–thaw cycles can enhance soil erosion, further exacerbating the risk. Conversely, the implementation of environmental protection projects, such as the establishment of protected areas, efforts to restore forests and grasslands, and initiatives to conserve soil and water, has been effective in limiting the increase in desertification risk. These efforts serve as a counterforce to the negative impacts of climate change and human activity, highlighting the beneficial effects of human intervention in preventing desertification. High-altitude, high-topographic relief places have considerable desertification risk, mainly in the alpine desert. Due to geography, grazing, rodent and pest infestation, and wildlife, there is still a risk of desertification expanding in low elevation areas. There will be a greater urgency in the future to enhance the management of anthropogenic activities in the local environment in order to handle the growing threat of desertification caused by climate change. This study combined the interactions of the natural environment and human activities, filled a research gap in assessing desertification risk, and revealed its driving mechanisms, as well as provided a theoretical foundation for improving the integrity and sustainability of ecosystems in semi-arid alpine regions and elsewhere.
Interpolating Hydrologic Data Using Laplace Formulation
Authors: Xu Tianle , Merwade Venkatesh , Wang Zhiquan
Published: August 2023

Spatial interpolation techniques play an important role in hydrology, as many point observations need to be interpolated to create continuous surfaces. Despite the availability of several tools and methods for interpolating data, not all of them work consistently for hydrologic applications. One of the techniques, the Laplace Equation, which is used in hydrology for creating flownets, has rarely been used for data interpolation. The objective of this study is to examine the efficiency of Laplace formulation (LF) in interpolating data used in hydrologic applications (hydrologic data) and compare it with other widely used methods such as inverse distance weighting (IDW), natural neighbor, and ordinary kriging. The performance of LF interpolation with other methods is evaluated using quantitative measures, including root mean squared error (RMSE) and coefficient of determination (R2) for accuracy, visual assessment for surface quality, and computational cost for operational efficiency and speed. Data related to surface elevation, river bathymetry, precipitation, temperature, and soil moisture are used for different areas in the United States. RMSE and R2 results show that LF is comparable to other methods for accuracy. LF is easy to use as it requires fewer input parameters compared to inverse distance weighting (IDW) and Kriging. Computationally, LF is faster than other methods in terms of speed when the datasets are not large. Overall, LF offers a robust alternative to existing methods for interpolating various hydrologic data. Further work is required to improve its computational efficiency.
Automatic Detection of Forested Landslides: A Case Study in Jiuzhaigou County, China
Authors: Li Dongfen , Tang Xiaochuan , Tu Zihan , Fang Chengyong , Ju Yuanzhen
Published: August 2023

Landslide detection and distribution mapping are essential components of geohazard prevention. For the extremely difficult problem of automatic forested landslide detection, airborne remote sensing technologies, such as LiDAR and optical cameras, can obtain more accurate landslide monitoring data. In practice, however, airborne LiDAR data and optical images are treated independently. The complementary information of the remote sensing data from multiple sources has not been thoroughly investigated. To address this deficiency, we investigate how to use LiDAR data and optical images together to develop an automatic detection model for forested landslide detection. First, a new dataset for detecting forested landslides in the Jiuzhaigou earthquake region is compiled. LiDAR-derived DEM and hillshade maps are used to mitigate the influence of forest cover on the detection of forested landslides. Second, a new deep learning model called DemDet is proposed for the automatic detection of forested landslides. In the feature extraction component of DemDet, a self-supervised learning module is proposed for extracting geometric features from LiDAR-derived DEM. Additionally, a transformer-based deep neural network is proposed for identifying landslides from hillshade maps and optical images. In the data fusion component of DemDet, an attention-based neural network is proposed to combine DEM, hillshade, and optical images. DemDet is able to extract key features from hillshade images, optical images, and DEM, as demonstrated by experimental results on the proposed dataset. In comparison to ResUNet, LandsNet, HRNet, MLP, and SegFormer, DemDet obtains the highest mean accuracy, mIoU, and F1 values, namely 0.95, 0.67, and 0.777. DemDet is therefore capable of autonomously identifying the forest-covered landslides in the Jiuzhaigou earthquake zone. The results of landslide detection mapping reveal that slopes along roads and seismogenic faults are the most crucial areas requiring geohazard prevention.
A Goal-Directed Trajectory Planning Using Active Inference in UAV-Assisted Wireless Networks
Authors: Krayani Ali , Khan Khalid , Marcenaro Lucio , Marchese Mario , Regazzoni Carlo
Published: August 2023

Deploying unmanned aerial vehicles (UAVs) as aerial base stations is an exceptional approach to reinforce terrestrial infrastructure owing to their remarkable flexibility and superior agility. However, it is essential to design their flight trajectory effectively to make the most of UAV-assisted wireless communications. This paper presents a novel method for improving wireless connectivity between UAVs and terrestrial users through effective path planning. This is achieved by developing a goal-directed trajectory planning method using active inference. First, we create a global dictionary using traveling salesman problem with profits (TSPWP) instances executed on various training examples. This dictionary represents the world model and contains letters representing available hotspots, tokens representing local paths, and words depicting complete trajectories and hotspot order. By using this world model, the UAV can understand the TSPWP’s decision-making grammar and how to use the available letters to form tokens and words at various levels of abstraction and time scales. With this knowledge, the UAV can assess encountered situations and deduce optimal routes based on the belief encoded in the world model. Our proposed method outperforms traditional Q-learning by providing fast, stable, and reliable solutions with good generalization ability.
What ChatGPT Tells Us about Gender: A Cautionary Tale about Performativity and Gender Biases in AI
Authors: Gross Nicole
Published: August 2023

Large language models and generative AI, such as ChatGPT, have gained influence over people’s personal lives and work since their launch, and are expected to scale even further. While the promises of generative artificial intelligence are compelling, this technology harbors significant biases, including those related to gender. Gender biases create patterns of behavior and stereotypes that put women, men and gender-diverse people at a disadvantage. Gender inequalities and injustices affect society as a whole. As a social practice, gendering is achieved through the repeated citation of rituals, expectations and norms. Shared understandings are often captured in scripts, including those emerging in and from generative AI, which means that gendered views and gender biases get grafted back into social, political and economic life. This paper’s central argument is that large language models work performatively, which means that they perpetuate and perhaps even amplify old and non-inclusive understandings of gender. Examples from ChatGPT are used here to illustrate some gender biases in AI. However, this paper also puts forward that AI can work to mitigate biases and act to ‘undo gender’.
National or Multicultural? A Common Narrative about History in the Baltic States after 1991
Authors: Halicka Beata
Published: August 2023

In this article, I describe common narratives of history in postcommunist Lithuania, Latvia, and Estonia and explore the intersection between multiculturalism and memory politics. I argue that dealing with history is a challenge in these countries and can be seen as part of a broader issue of memory politics in societies that have experienced trauma during the Nazi and Soviet eras. The hypothesis that I developed, based on my empirical analysis, is that it makes visible how a difficult process of negotiating competing memories can, under certain circumstances, lead to dialogical remembrance. The article also pays attention to unexpected events, such as the Russian invasion of Ukraine, which gives a new dynamic to this process. The original contribution of this article is an analysis of historical narratives in three national museums, with a special focus on how these museums deal with the injustices and traumas experienced by different ethnic groups in the Baltic states. The final section of the article is devoted to the reaction of people in these countries to the Russian invasion of Ukraine on 24 February 2022, and how this relates to the politics of history created in Lithuania, Latvia, and Estonia after 1991.
The Role of Redundancy of Infrastructures on the Seismic Resilience (SR) of Sustainable Communities
Authors: Forcellini Davide
Published: August 2023

Infrastructures are fundamental links in sustainable communities, and they need to remain at a level of functionality during and after natural events. In particular, assessing the seismic resilience of infrastructures has become an interesting topic in earthquake engineering. The estimation of indirect losses due to seismic events is still a topic under discussion, especially for infrastructures. In this regard, the paper focused on including the level of redundancy inside an analytical formulation of the seismic resilience (SR). The main idea is to explore the possibility of alternative infrastructures that allow the circulation of services and people when the flow on the original infrastructure is interrupted or reduced. This goal is fundamental for preserving the resilience for sustainable communities. Therefore, the proposed formulation consists of considering the reduction in losses when the infrastructure is redundant by introducing the concept of the level of redundancy. In particular, indirect costs were herein defined with a new formulation that includes the level of redundancy inside the calculation of SR. The paper presented a case study that implements the formulation with the aim to demonstrate the efficiency of the proposed methodology. Several levels of infrastructural redundancy have been applied in the calculation of the SR of an infrastructure subjected to an ensemble of 100 seismic motions in order to scope the role of redundancy in improving the SR of the system.
A Study on the Mechanism of Digital Technology’s Impact on the Green Transformation of Enterprises: Based on the Theory of Planned Behavior Approach
Authors: Gao Yi , Tang Yinkai
Published: August 2023

With the rapid development of the digital economy and the continuous improvement of the digital capabilities of enterprises, relying on digital technology (DT) to achieve green transformation (GT) has become the future development direction of enterprises. Based on the theory of planned behavior (TPB), this paper constructs a theoretical model of DT to determine the impact mechanism of corporate GT and empirically tests the research model using a structural equation model (SEM). The analysis of microdata from 406 manufacturing firms in China shows that DT has a positive contribution to corporate GT. DT mainly affects the intention of enterprises to pursue GT indirectly by influencing the perceived behavioral control for GT and thus, ultimately, the GT of enterprises. This paper reveals the model and mechanism of corporate GT through DT, which has important implications for relevant theoretical research and policy formulation.
Identification and Prediction Network Analysis Based on Multivariate Data of Urban Form: A Case Study of Shenzhen, China
Authors: Yu Zeyang , Huang Yuan , Wang Yang
Published: August 2023

The rapid growth of urban populations has resulted in a scarcity of land, thus making sustainable urban development an urgent matter. Although Shenzhen has implemented land policies and optimized its functional layouts, these measures have inadvertently contributed to a shortage of available land for development. The city’s exponential population growth and expansive urban expansion have outpaced the supply of land. This study endeavors to identify urban commercial patterns by employing multiple data sources and applying machine learning and network analysis to predict future commercial areas. The results demonstrated that the identification of commercial points of interest and analysis of land surface temperature distributions made Futian district the primary area for ongoing commercial development, while also revealing a positive correlation between these two datasets. By leveraging network analysis to thoroughly examine this data, Bao’an district was highlighted as the future focal point for Shenzhen’s commercial sector, with 22 core nodes identified in total. Finally, by assessing the network centrality within the spatial networks, and utilizing clustering algorithms to categorize nodes into groups, the economic clustering pattern was determined as the predominant model for Shenzhen’s commercial growth. This research represents a significant contribution to the realm of sustainable urban development and presents a valuable framework for other cities to adopt.
The Role of ‘Home School’ in Improving Sustainability for Rohingya Refugees in Bangladesh
Authors: Prodip Mahbub Alam , Roy Goutam
Published: August 2023

During the COVID-19 pandemic, most education providers could not offer face-to-face educational support to Rohingya children in the camp at Cox’s Bazar in Bangladesh; however, some sector partners provided education online, and ‘Home School’ was one of them. This article intends to examine and learn to what extent and how home school education produced new knowledge for Rohingya children and promoted the sustainability of Rohingyas in the camp during the COVID-19 pandemic. A qualitative research approach was used to discern the impact of online education on the sustainable livelihood of Rohingya refugees in Bangladesh. Using purposive sampling, data were collected through semi-structured interviews with Rohingya refugee children, key informant interviews with education providers, and teachers who worked in the camp during COVID-19. The conversation analysis technique was applied to analyse data. The findings of this study uncover that, regardless of some downsides, including the lack of endowment for formal education, the shortage of community mobilisers, the limited subjects offered, the limited duration of class time, and weak internet connection, home school education contributed enormously to ensuring the sustainable livelihood of Rohingya refugees in Bangladesh by ensuring a safe and securing learning space and upholding the equal participation of boys and girls, and contributed to recovery from trauma and fear of violence in the camp.
Loss and Damage from Climate Change: Knowledge Gaps and Interdisciplinary Approaches
Authors: Balzter Heiko , Macul Mateus , Delaney Beth , Tansey Kevin , Espirito-Santo Fernando , Ofoegbu Chidiebere , Petrovskii Sergei , Forchtner Bernhard , Nicholes Nicholes , Payo Emilio , Heslop-Harrison Pat , Burns Moya , Basell Laura , Egberts Ella , Stockley Emma , Desorgher Molly , Upton Caroline , Whelan Mick , Yildiz Ayse
Published: August 2023

Loss and damage from climate change have risen to a prominent position on the international agenda. At COP27 in 2022, the Conference of the Parties (COP) to the UN Framework Convention on Climate Change (UNFCCC) ratified a decision to establish a loss and damage fund to compensate low- and middle-income countries that are suffering negative impacts from climate change. The fund is meant to address the Global Adaptation Gap, which describes the rising cost of adaptation needed to cope with climate change impacts due to delayed action to curb greenhouse gas emissions and remove greenhouse gases from the atmosphere. This essay highlights issues around loss and damage from climate change from a variety of natural and social science perspectives. From three months of discussions, an interdisciplinary perspective and research agenda on this topic have crystallised, which is outlined here. Given that the implementation of the loss and damage fund still needs negotiation and commitment from signatories to the UNFCCC, it is timely now to address some important knowledge gaps on how loss and damage can be measured, quantified, valued, understood, communicated, and adapted to. Hence, it is necessary to understand the complex interactions between people, politics, nature, and climate in this interdisciplinary context.
Impact of Digital Economy on the High-Quality Development of China’s Service Trade
Authors: Di Changya , Tang Decai , Xu Yifan
Published: August 2023

High-quality development of service trade (HDST) is becoming increasingly important for China’s high-quality development (HD). This builds new development patterns and cultivates new competitive advantages. In the digital economy (DE) era, HDST ushers an important opportunity. The use of DE to promote HDST is the focus of China’s current economic development strategy. After theoretical analysis using panel data of 18 sample regions (municipalities, provinces, directly under the central government, and autonomous regions) in China from 2012 to 2021, this study empirically studies the impact and mechanism of DE on HDST. The research results indicate that DE has significantly promoted the HDST in China. Based on its mechanism, the HDST can also be promoted by improving the human capital level. Moreover, compared with the eastern region, DE plays a more significant role in promoting the HDST in the central and western regions. With the opening of the new process of “digital China” construction, DE has played a stronger role in promoting the HDST after 2015. Based on theoretical and empirical analysis, suggestions are put forward to promote the HDST through the development of DE considering three aspects: improve the DE level, promote the coordinated development of regions, and strengthen personnel training, which provides references for relevant departments to formulate policies. For the promotion of HDST in China, this study provides an important reference from the perspective of improving the level of DE.
Iran’s Regional Transnational Water Partnerships: Unclear Rules, Unstable Partnerships, and an Unsettled Future
Authors: Amiraslani Farshad , Dragovich Deirdre
Published: August 2023

Water resources are the most contentious, scarce, and contestable natural resources at any geographical scale. Where water resources cross international boundaries, additional uncertainties arise for access to and distribution of available water. Here, we examined three transnational water partnerships by focusing on Iran as a dryland country with a developing economy. Thus, Iran has a key interest in water policies and the development and governance of water resources. Within Iran’s regional context, we considered whether the country obtained a geopolitical advantage from three regional water partnerships, involving the Caspian Sea, the Helmand River, and the export of hydroelectricity. We used a global database and several years of Iranian newspaper articles to explore possible linkages between contemporary and historical challenges while looking at international laws and conventions. We highlighted (a) the transboundary Helmand River as the most unstable partnership; (b) the complexities of the relationships between the Caspian Sea’s beneficiaries, including Iran, in utilising its vast resources in an environment with unclear rules; and (c) the rainfall- and geopolitically dependent hydroelectricity exchange agreements with neighbouring countries. Although Iran pursued such international involvement through treaties and economic initiatives, its water-based geopolitical influence in the region remains constrained by domestic demand, hydrometeorological geography, and the involvement of major world powers.
Evolution of the Spatial Patterns of Global Egg Trading Networks in the 21 Century
Authors: Yu Aizhi , She Huiling , Cao Jingsheng
Published: August 2023

Global agriculture and food system is faced with increasing uncertainty from natural disasters, epidemics, financial crises, and wars. Agricultural trade can provide a powerful supplement to global food security. Eggs have been recognized as the most important protein source for many years as they contain the highest quality protein naturally available while the price is competitive. Egg trading plays an important role in enhancing the resilience of the global food system under uncertainty. We empirically investigate the evolution of global egg trading networks by social network analysis. And, the quadratic assignment procedure (QAP) is applied to detect factors that impact global egg trading networks. The results show that in the 21st century, global egg trading networks are becoming more complex and the clusters are undergoing dynamic differentiation and integration. Additionally, compared to cultural difference among countries, factors including geographical distances, natural endowments, economic developments, trade policies, and political stability have a more significant effect on the evolution of egg trading networks. Our work provides suggestions for participating countries to develop more resilient egg trading networks to resist external shocks.
Research on the Quality of Collaboration in Project-Based Learning Based on Group Awareness
Authors: Zhang Rui , Shi Ji , Zhang Jianwei
Published: August 2023

Project-based learning (PBL) is an important form of collaborative learning that has a significant positive impact on student capacity development. However, data generated during long periods of PBL are difficult to record in real time, and there is a dearth of specific empirical research on the relationship between the quality of collaboration and the effectiveness of collaboration. In this study, we employ text mining to measure and analyze process data from a college physics course that utilizes project-based learning at a university. Under the group awareness theory, we construct a project-based learning system and extract six multi-dimensional awareness data (including numbers of text, cognitive awareness, emotional awareness, behavioral awareness, social awareness of group members, and group leaders’ cognitive awareness of the project). These data are then utilized to build a multiple regression model, which enables the analysis of collaboration quality within collaborative groups. The results show that the group awareness information automatically processed by text mining can reflect the quality of collaboration, and the quality of collaboration can determine about 50% of the effectiveness of collaboration. The important factors affecting the collaboration quality of project-based learning were group leaders’ cognitive awareness of the project and the cognitive awareness of group members. Therefore, in order to improve the quality of collaboration in PBL, teachers should select responsible group leaders and encourage meaningful communication between group members, thereby fostering high-quality and sustainable collaboration development.
Predicting the Compressive Strength of Green Concrete at Various Temperature Ranges Using Different Soft Computing Techniques
Authors: Mohammed Ahmad Khalil , Hassan A. M. T. , Mohammed Ahmed Salih
Published: August 2023

To overcome the environmental impact of cement production in concrete, the construction industry is adopting eco-friendly approaches, such as incorporating alternative and recycled materials and minimizing carbon emissions in concrete production. One such material that has gained prominence is ground granulated blast furnace slag (GGBFS). This study focuses on investigating the compressive strength of concrete at 28 days of age by examining the influences of several factors, such as temperature, water-to-binder ratio (w/b), GGBFS-to-binder ratio (GGBFS/b), fine aggregate, coarse aggregate, and superplasticizer. A statistical modeling approach was employed to comprehensively analyze these parameters and assess their impact on compressive strength. To accomplish this, the study collected and analyzed data from the literature, resulting in a dataset of 210 observations. The dataset was divided into training and testing groups, and statistical analyses were performed to assess the relationships between the input parameters and compressive strength. The correlation analysis revealed insignificant relationships between the input parameters and compressive strength, indicating that multiple factors affect strength. Different models were employed to predict compressive strength, such as linear regression, nonlinear regression, quadratic, full quadratic models, and artificial neural networks (ANN). The findings of this study contribute to a better understanding of the factors that influence the compressive strength of concrete containing GGBFS. The results underscore the importance of considering multiple parameters to predict strength accurately.
Smokers’ Attitude and Behavior towards Cigarette Littering in Romania: A Survey-Based Approach
Authors: Lakatos Elena Simina , Cioca Lucian Ionel , Szilagyi Andrea , Bîrgovan Andreea Loredana , Rada Elena Cristina
Published: August 2023

Cigarette butts continue to be a significantly detrimental challenge for both human health and the quality of the environment and life in general. The escalating accumulation of inadequately discarded cigarette butts continues unabated, in spite of the myriad legislative procedures that have been instituted by authorities with the objective of incentivizing diminution of this phenomenon. For decades, the scientific literature has discussed the importance of smokers’ behavior and beliefs in contributing to the problem. Thus, the objective of this study is to analyze cigarette butt littering behavior using a survey-based questionnaire. A total of 1643 complete responses were collected from Romanian smokers addressing their knowledge, practices, and views regarding the disposal of cigarette butts. According to the findings, awareness about the impacts and characteristics of cigarette butts is problematic, as are smokers’ self-reported explanations for their conduct. Specifically, more than 30% of the sample stated that cigarette butts are biodegradable, and 31.5% believe that cigarette butts are not toxic to the environment. The results also showed that only 19.7% of the smokers strongly believed that they should be considered accountable for their behavior. Future study directions are provided to advance studies in this area and improve present approaches to lessen the frequency of this behavior.
Virtual-Simulation-Based Multi-Objective Optimization of an Assembly Station in a Battery Production Factory
Authors: Lind Andreas , Elango Veeresh , Hanson Lars , Högberg Dan , Lämkull Dan , Mårtensson Pär , Syberfeldt Anna
Published: August 2023

The planning and design process of manufacturing factory layouts is commonly performed using digital tools, enabling engineers to define and test proposals in virtual environments before implementing them physically. However, this approach often relies on the experience of the engineers involved and input from various cross-disciplinary functions, leading to a time-consuming and subjective process with a high risk of human error. To address these challenges, new tools and methods are needed. The Industry 5.0 initiative aims to further automate and assist human tasks, reinforcing the human-centric perspective when making decisions that influence production environments and working conditions. This includes improving the layout planning process by making it more objective, efficient, and capable of considering multiple objectives simultaneously. This research presents a demonstrator solution for layout planning using digital support, incorporating a virtual multi-objective optimization approach to consider safety regulations, area boundaries, workers’ well-being, and walking distance. The demonstrator provides a cross-disciplinary and transparent approach to layout planning for an assembly station in the context of battery production. The demonstrator solution illustrates how layout planning can become a cross-disciplinary and transparent activity while being automated to a higher degree, providing results that support decision-making and balance cross-disciplinary requirements.
Evaluating Supply Resilience Performance of an Automotive Industry during Operational Shocks: A Pythagorean Fuzzy AHP-VIKOR-Based Approach
Authors: Çalik Ahmet , Onifade Stephen Taiwo , Alola Andrew Adewale
Published: August 2023

An integral aspect of global businesses and economic activities is the supply chain networks. Importantly, the coronavirus (COVID-19) pandemic scenario has further shown that the outbreak of diseases can create a global network-scale disruption to supply chain or logistics, thereby damaging several aspects of economic activities and business life. Hence, this study aims to assess the resilient supplier selection (RSS) process in the wake of the COVID-19 outbreak. A two-stage hybrid decision model using Pythagorean fuzzy sets was proposed as a case study from the automotive industry to deal with RSS during the COVID-19 outbreak. In the first stage, significant criteria and their corresponding sub-criteria were determined through a vast review of the literature and nominal group technique, while the relative weights for RSS were obtained through the Pythagorean Fuzzy Analytic Hierarchy Process (PFAHP) method. In the second stage, nine suppliers were evaluated with Pythagorean Fuzzy VIKOR (PFVIKOR) method. The results of the hybrid approach revealed that flexibility is the most important criterion among resilience criteria that constitute the most significant dimensions for RSS. In many studies, strategic criteria such as quality, cost, and delivery are found to be the most important criteria in supplier selection, however, in the wake of the COVID-19 outbreak, the opinions of decision-makers were significantly changed as the present study reveals that flexibility is the most important criterion to improve the operations of the supply chain for RSS. Next to flexibility is process capabilities, while quality (Q), and cost (C) existed as the first and second in the category of influential criteria for strategic supplier selection criteria, respectively. The managerial and practical implication is that, in the wake of COVID-19 disruptions, suppliers need to be re-evaluated based on resilience-related indicators.