bluuebunny/crossref_metadata_2025 huggingface dataset:
Continuous DeNOx Technology for Improved Flexibility and Reliability of 1000 MW Coal-Fired Power Plants: Engineering Design, Optimization, and Environmental Benefits
Authors: Yan Xinrong , He Jianle , Guo Dong , Zhang Yang , Ke Xiwei , Xiao Hongliang , Zheng Chenghang , Gao Xiang
Published: December 2023

This study endeavors to enhance the operational efficiency of extant coal-fired power plants to mitigate the adverse environmental impact intrinsic to the prevalent utilization of coal-fired power generation, which is particularly dominant in China. It focuses on the assessment and optimization of continuous denitrification systems tailored for a 1000 MW ultra-supercritical pulverized coal boiler. The extant denitrification framework encounters challenges during startup phases owing to diminished selective catalytic reduction (SCR) inlet flue gas temperatures. To ameliorate this, three retrofit schemes were scrutinized: direct mixing of high-temperature flue gas, bypass flue gas mixing, and high-temperature flue gas mixing with cold air. Each option underwent meticulous thermodynamic computations and comprehensive cost analyses. The findings elucidated that bypass flue gas mixing, involving the extraction and blending of high-temperature flue gas, emerged as the most financially prudent and practical recourse. This scheme optimizes fuel combustion heat utilization, significantly curtails fuel consumption, and fosters efficient internal heat transfer mechanisms within the boiler. The evaluation process meticulously considered safety parameters and equipment longevity. The insights derived from this investigation offer valuable guidance for implementing continuous denitrification system retrofits in industrial coal-fired power plants.
The Eternal Relations of Origin, Causality, and Implications for Models of God
Authors: Hollingsworth Andrew
Published: December 2023

The classical doctrine of the eternal relations or origin (ERO) claims that these relations are (1) atemporal and (2) causal. In this paper, I investigate the casual nature of the ERO, highlighting that the patristic and medieval Christian thinkers who developed this doctrine understood causality in terms of Aristotle’s efficient causality, highlighting that these are casual acts that produce an effect. I then provide an analysis of some of the major theories of efficient causation on offer in contemporary metaphysics to see which theory best comports with how the ancient and medieval Christian thinkers understood the efficient–causal aspect of the ERO, concluding that a powers theory of causation seems to work best. I conclude by discussing the implications the classical doctrine of the ERO has for models of God, arguing that they are compatible only with classical theism and neoclassical theism.
Commercial Discrimination as Religious Messaging in 303 Creative v. Elenis
Authors: Satta Mark
Published: December 2023

In 303 Creative LLC v. Elenis, a web designer sought a legal right to refuse to make wedding websites for same-sex couples while making wedding websites for other couples as a service provided by her business open to the public. The web designer also sought a legal right to post a notice on her business webpage stating that she would refuse to provide such services for same-sex couples’ weddings. Here, I argue that 303 Creative marks a fairly radical break from previous legal cases dealing with whether service providers have the legal right to deny services for same-sex weddings. This is because, if we take the web designer at her word, the web designer appears to have sought these legal rights, in significant part, in order to use an act of commercial discrimination as an act of religious message sending. In support of this conclusion, I argue that acts of selective commercial service constitute the primary means by which the web designer sought to promote her preferred religious messages and that these acts of selective commercial service are acts of discrimination. I also discuss some of the significance of this case for religion and politics in the United States.
The Confederation between the Kingdoms of Portugal and Kongo, 1511–1665
Authors: Gouveia Jaime Ricardo
Published: December 2023

In this study I propose rethinking the nature, purposes, and impacts of relations between the kingdoms of Portugal and Kongo in the period between 1511 and 1665. My main argument is that the Pact of Confederation formed by these two kingdoms was decisive, exceptional, and unprecedented. While covert attempts by the Portuguese to gain control of the Kingdom of Kongo were common during this period, the relations spelled out by the pact nevertheless endured for over a century and would have global repercussions. From the vantage point of historiography, the pact presents modern historians with serious difficulties, largely because it spells out modes of interaction that do not fit readily into recognized systems of European colonialism. Central to these modes of interaction is the significant role that religion played in defining Portuguese imperialist policies in Central Africa. In the end, the Pact of Confederation between the kingdoms of Portugal and Kongo forces historians to rethink Portuguese imperial dynamics and the modalities of their presence in Africa and beyond.
A Comparative Study of Medieval Religious Spirituality: Bonaventure’s Theory of Six Stages of Spirituality and Śaṅkara’s Sixfold Practice Theory of Advaita Vedānta
Authors: Liu Yixuan
Published: December 2023

In medieval India, the desire for “the unity of Brahman and Self” was present in the Vedānta tradition of Hinduism. Adi Śaṅkara, the master of Vedānta philosophy, proposed the six-fold sādhana: mind control, sense control, mental tranquility, endurance, potential faith, and concentration. These six-fold practices can help Vedānta followers realize unity with Brahman. In medieval Christianity, mysticism was regarded as an important path for Christians to seek a closer relationship with God. Pursuing “the unity of God and man” became the goal and direction of Christians at that time, which could be achieved through spirituality. Bonaventure, known as the Seraphic Doctor, was a representative figure of medieval Christian mysticism. He proposed six stages of spirituality: Sense, Imagination, Reason, Intelligence, Understanding, and Spark of Conscience, through which one can achieve unity with God. This article attempts to compare Bonaventure’s theory of six stages of spirituality with Śaṅkara’s idea of six-fold practice and discover the similarities and differences between Eastern and Western religious spirituality in the Middle Ages. Through this comparison, we can further explore the medieval religious believers’ desire for ultimate reality and try to find the possibility of dialogue between Christianity and Advaita Vedānta.
Unveiling the Environmental Impacts of Concentrated Latex Manufacturing in Sri Lanka through a Life Cycle Assessment
Authors: Dunuwila Pasan , Rodrigo V. H. L. , Daigo Ichiro , Goto Naohiro
Published: December 2023

Sri Lanka is a top producer of premium quality concentrated latex (CL), which becomes a base material for dipped rubber products such as gloves and condoms. The processing of CL is resource-intensive, requiring significant amounts of energy, fuel, water, and chemicals. This process leads to various environmental issues such as wastewater pollution, malodor, and greenhouse gas emissions. Several environmental life cycle assessments (LCA) have been conducted at international and local levels to address the aforesaid issues. However, LCAs encapsulating different environmental impact areas on CL processing in Sri Lanka are absent. The study revealed that electricity usage was the main hotspot of the environmental burden, significantly impacting abiotic depletion (fossil fuels), global warming potential, ozone layer depletion, photochemical oxidation, and acidification. Heavy reliance on coal in the Sri Lankan power grid was identified as the root of this trend. The study suggested two viable options to mitigate the environmental impact: installing inverters to centrifuge separators and solar systems in the factories. The second option was deemed more effective, reducing acidification, photochemical oxidation, and global warming potential by approximately 37%, 36%, and 28%, respectively. Relevant officials may immediately consider these improvement options and collaborate to pave the way to a sustainable natural rubber industry.
Retrieval of Desert Microwave Land Surface Emissivity Based on Machine Learning Algorithms
Authors: Li Jiangtao , Guan Yuanhong , Lu Qifeng , Bao Yansong , Wu Chunqiang , Xu Chaofan
Published: December 2023

Based on the community radiative transfer model, ensemble tree-based random forest algorithm, and extreme gradient boosting tree algorithm, this study established a random forest retrieval model (RF) and an extreme gradient boosting tree retrieval model (XGBoost) for the microwave land surface emissivity by using ERA5 reanalysis data and the observed brightness temperature of 10.65 GHz vertical polarization from FY3C Microwave Radiation Imager-I. In addition, an optimized Bayesian regularized neural network retrieval model (M2_30NN) has also been established on the basis of the original neural network land surface emissivity retrieval model (M1_20NN). The results show that compared with the simulated brightness temperature of the original land surface emissivity, the simulated brightness temperature of the land surface emissivity from each retrieval model is not only significantly improved in the correlation coefficient with the observed brightness temperature (5.92% (M1_20NN), 4.23% (M2_30NN), 14.21% (RF), 13.07% (XGBoost)), but also in the evaluation indexes of root mean square error, mean absolute error and explained variance regression score in the training datasets. Furthermore, in terms of testing datasets and spatiotemporal independence test datasets, the retrieval results of RF and XGBoost models can capture the spatial distribution patterns that are consistent with observations well, and also show great numerical improvement compared with the original model. In general, the XGBoost retrieval model is the best, followed by the RF retrieval model.
SSGAM-Net: A Hybrid Semi-Supervised and Supervised Network for Robust Semantic Segmentation Based on Drone LiDAR Data
Authors: Wu Hua , Huang Zhe , Zheng Wanhao , Bai Xiaojing , Sun Li , Pu Mengyang
Published: December 2023

The semantic segmentation of drone LiDAR data is important in intelligent industrial operation and maintenance. However, current methods are not effective in directly processing airborne true-color point clouds that contain geometric and color noise. To overcome this challenge, we propose a novel hybrid learning framework, named SSGAM-Net, which combines supervised and semi-supervised modules for segmenting objects from airborne noisy point clouds. To the best of our knowledge, we are the first to build a true-color industrial point cloud dataset, which is obtained by drones and covers 90,000 m2. Secondly, we propose a plug-and-play module, named the Global Adjacency Matrix (GAM), which utilizes only few labeled data to generate the pseudo-labels and guide the network to learn spatial relationships between objects in semi-supervised settings. Finally, we build our point cloud semantic segmentation network, SSGAM-Net, which combines a semi-supervised GAM module and a supervised Encoder–Decoder module. To evaluate the performance of our proposed method, we conduct experiments to compare our SSGAM-Net with existing advanced methods on our expert-labeled dataset. The experimental results show that our SSGAM-Net outperforms the current advanced methods, reaching 85.3% in mIoU, which ranges from 4.2 to 58.0% higher than other methods, achieving a competitive level.
Analysis of Earthquake-Triggered Landslides through an Integrated Unmanned Aerial Vehicle-Based Approach: A Case Study from Central Italy
Authors: Schilirò Luca , Massaro Luigi , Forte Giovanni , Santo Antonio , Tommasi Paolo
Published: December 2023

Landslides are one of the most hazardous(危险) secondary(二次) effects of earthquakes(地震) due(由于) to the potential(潜在) for large-scale(规模) damage(损伤) and long-term(学期) alterations to landscapes. During the 2016–2017 seismic sequence(序列) in Central Italy, many earthquake(地震)-triggered landslides (EQTLs) affected the road network(网络) and mountain trails. In this study, a methodological approach(方法) for analysing EQTLs, based on data(数据) derived from Unmanned Aerial Vehicle (UAV) surveys, is shown. The approach(方法) is applied to investigate(探讨) the geometric, structural(结构), geomechanical, and kinematic features of the Foce rockslide, which is introduced in the back analysis(分析). The investigation(调查) involved three main(主要) steps: (i) set up of UAV-based Virtual Outcrop Models (VOMs) of the slope(边坡), (ii) a geomechanical characterisation of the rock mass(大众) through the VOM interpretation(解释) and conventional(常规) field data(数据), and (iii) 3D Limit Equilibrium (LE) slope(边坡) stability(稳定性) analyses(分析). This study highlights the potential(潜在) of UAV surveys for providing valuable(宝贵) data(数据) for stability(稳定性) analyses(分析), especially in emergency(紧急) conditions such(这样) as in the aftermath of seismic events.
ADMM-Net for Beamforming Based on Linear Rectification with the Atomic Norm Minimization
Authors: Gong Zhenghui , Zhang Xinyu , Ren Mingjian , Su Xiaolong , Liu Zhen
Published: December 2023

Target misalignment can cause beam pointing deviations and degradation of sidelobe performance. In order to eliminate the effect of target misalignment, we formulate the jamming sub-space recovery problem as a linearly modified atomic norm-based optimization. Then, we develop a deep-unfolding network based on the alternating direction method of multipliers (ADMM), which effectively improves the applicability and efficiency of the algorithm. By using the back-propagation process of deep-unfolding networks, the proposed method could optimize the hyper-parameters in the original atomic norm. This feature enables the adaptive beamformer to adjust its weight according to the observed data. Specifically, the proposed method could determine the optimal hyper-parameters under different interference noise matrix conditions. Simulation results demonstrate that the proposed network could reduce computational cost and achieve near-optimal performance with low complexity.
High-Frequency Microbarograph-Observed Pressure Variations Associated with Gust Fronts during an Extreme Rainfall Event
Authors: Zhang Jingjing , Bai Lanqiang , Li Zhaoming , Du Yu , Zhang Shushi
Published: December 2023

This study aims to explore the roles of multiple gust fronts (i.e., outflow boundaries) during a short-lived extreme rainfall that occurred in the Greater Bay Area of South China in the afternoon of 1 August 2021. Through the use of microbarographs and Doppler weather radars, the research highlights how the interactions of five gust fronts, approaching the region from different directions, have contributed to the high precipitation efficiency and damaging surface winds during the event. The close convergence of these gust fronts funneled unstable air masses into the region of interest, priming the mesoscale convective environment. Some isolated convection initiated before the gust fronts’ arrival. Preceding the arrival of these gust fronts, subtle wave-like pressure jumps were identified from the high-frequency (1 Hz) microbarograph observations. The amplitude of the pressure jump is approximately 40 Pa with minimal changes in air temperature. During the early stage of the gust front passages, very high-frequency oscillations in surface pressure are recognized, indicating interaction between the density currents and the low-level troposphere. As suggested through numerical simulations, the subtle pressure jumps are associated with upward displacements of isentropic surfaces aloft, deepening the moist layer and enhancing the lapse rate that are conducive to convective development. The simulated vertical profiles show no evident capping inversion above the dry neutral boundary layer, suggesting that the pressure jumps are likely to be dynamically induced through the collision of the outflows and environmental air masses. The findings of this study suggest the potential application of microbarographs in the nowcasting of the convective development associated with gust fronts.
Practical Applications of a Set-Based Camera Deployment Methodology
Authors: Parrott Edward , Pickard Joshua K. , Dubay Rickey
Published: December 2023

This work establishes a complete methodology for solving continuous sets of camera deployment solutions for automated machine vision inspection systems in industrial manufacturing facilities. The methods presented herein generate constraints that realistically model cameras and their associated intrinsic parameters and use set-based solving methods to evaluate these constraints over a 3D mesh model of a real part. This results in a complete and certifiable set of all valid camera poses describing all possible inspection poses for a given camera/part pair, as well as how much of the part’s surface is inspectable from any pose in the set. These methods are tested and validated experimentally using real cameras and precise 3D tracking equipment and are shown to accurately align with real imaging results according to the hardware they are modelling for a given inspection deployment. In addition, their ability to generate full inspection solution sets is demonstrated on several realistic geometries using realistic factory settings, and they are shown to generate tangible, deployable inspection solutions, which can be readily integrated into real factory settings.
Three-Dimensional Point Cloud Segmentation Algorithm Based on Depth Camera for Large Size Model Point Cloud Unsupervised Class Segmentation
Authors: Fang Kun , Xu Kaiming , Wu Zhigang , Huang Tengchao , Yang Yubang
Published: December 2023

This paper proposes a 3D point cloud segmentation algorithm based on a depth camera for large-scale model point cloud unsupervised class segmentation. The algorithm utilizes depth information obtained from a depth camera and a voxelization technique to reduce the size of the point cloud, and then uses clustering methods to segment the voxels based on their density and distance to the camera. Experimental results show that the proposed algorithm achieves high segmentation accuracy and fast segmentation speed on various large-scale model point clouds. Compared with recent similar works, the algorithm demonstrates superior performance in terms of accuracy metrics, with an average Intersection over Union (IoU) of 90.2% on our own benchmark dataset.
Advances and Challenges in Drone Detection and Classification Techniques: A State-of-the-Art Review
Authors: Seidaliyeva Ulzhalgas , Ilipbayeva Lyazzat , Taissariyeva Kyrmyzy , Smailov Nurzhigit , Matson Eric T.
Published: December 2023

The fast development of unmanned aerial vehicles (UAVs), commonly known as drones, has brought a unique set of opportunities and challenges to both the civilian and military sectors. While drones have proven useful in sectors such as delivery, agriculture, and surveillance, their potential for abuse in illegal airspace invasions, privacy breaches, and security risks has increased the demand for improved detection and classification systems. This state-of-the-art review presents a detailed overview of current improvements in drone detection and classification techniques: highlighting novel strategies used to address the rising concerns about UAV activities. We investigate the threats and challenges faced due to drones’ dynamic behavior, size and speed diversity, battery life, etc. Furthermore, we categorize the key detection modalities, including radar, radio frequency (RF), acoustic, and vision-based approaches, and examine their distinct advantages and limitations. The research also discusses the importance of sensor fusion methods and other detection approaches, including wireless fidelity (Wi-Fi), cellular, and Internet of Things (IoT) networks, for improving the accuracy and efficiency of UAV detection and identification.
Understanding Naturalistic Facial Expressions with Deep Learning and Multimodal Large Language Models
Authors: Bian Yifan , Küster Dennis , Liu Hui , Krumhuber Eva G.
Published: December 2023

This paper provides a comprehensive overview of affective computing systems for facial expression recognition (FER) research in naturalistic contexts. The first section presents an updated account of user-friendly FER toolboxes incorporating state-of-the-art deep learning models and elaborates on their neural architectures, datasets, and performances across domains. These sophisticated FER toolboxes can robustly address a variety of challenges encountered in the wild such as variations in illumination and head pose, which may otherwise impact recognition accuracy. The second section of this paper discusses multimodal large language models (MLLMs) and their potential applications in affective science. MLLMs exhibit human-level capabilities for FER and enable the quantification of various contextual variables to provide context-aware emotion inferences. These advancements have the potential to revolutionize current methodological approaches for studying the contextual influences on emotions, leading to the development of contextualized emotion models.
Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, and Mitigation Strategies
Authors: Ferrara Emilio
Published: December 2023

The significant advancements in applying artificial intelligence (AI) to healthcare decision-making, medical diagnosis, and other domains have simultaneously raised concerns about the fairness and bias of AI systems. This is particularly critical in areas like healthcare, employment, criminal justice, credit scoring, and increasingly, in generative AI models (GenAI) that produce synthetic media. Such systems can lead to unfair outcomes and perpetuate existing inequalities, including generative biases that affect the representation of individuals in synthetic data. This survey study offers a succinct, comprehensive overview of fairness and bias in AI, addressing their sources, impacts, and mitigation strategies. We review sources of bias, such as data, algorithm, and human decision biases—highlighting the emergent issue of generative AI bias, where models may reproduce and amplify societal stereotypes. We assess the societal impact of biased AI systems, focusing on perpetuating inequalities and reinforcing harmful stereotypes, especially as generative AI becomes more prevalent in creating content that influences public perception. We explore various proposed mitigation strategies, discuss the ethical considerations of their implementation, and emphasize the need for interdisciplinary collaboration to ensure effectiveness. Through a systematic literature review spanning multiple academic disciplines, we present definitions of AI bias and its different types, including a detailed look at generative AI bias. We discuss the negative impacts of AI bias on individuals and society and provide an overview of current approaches to mitigate AI bias, including data pre-processing, model selection, and post-processing. We emphasize the unique challenges presented by generative AI models and the importance of strategies specifically tailored to address these. Addressing bias in AI requires a holistic approach involving diverse and representative datasets, enhanced transparency and accountability in AI systems, and the exploration of alternative AI paradigms that prioritize fairness and ethical considerations. This survey contributes to the ongoing discussion on developing fair and unbiased AI systems by providing an overview of the sources, impacts, and mitigation strategies related to AI bias, with a particular focus on the emerging field of generative AI.
Polymorphisms in Drug Transporter and Metabolism Genes Associated with Resistance to Imatinib in Chronic Myeloid Leukemia: A Systematic Review and Meta-Analysis
Authors: Gómez Ana Marcela Arrieta , Díaz-Mendoza María Antonia , Lemus Yesit Bello , León-Mejía Grethel , Benitez Martha Lucia Ruiz
Published: December 2023

The aim of this study was to establish the relationship between different polymorphisms in drug transporter and metabolizer genes and resistance to imatinib in chronic myeloid leukemia (CML). For this purpose, an exhaustive search was carried out in the Scopus, Web of Science, and PubMed databases using different combinations of keywords with different inclusion and exclusion criteria. The meta-analysis included nine studies that met the established criteria. The results of the study showed that the polymorphic variants AG and GG of CYP3A5*3 are associated with response to treatment, presenting a significantly lower risk with resistance to imatinib. Likewise, the variants T1236C and G2677T/A of the ABCB1 gene show a significant association with treatment efficacy. In addition, the genetic polymorphism 1236T, homozygous CC of the MDR1 gene, significantly influences the increased risk of cytogenetic relapse and the polymorphic variant 361G>A GA of the SLCO1A2 gene significantly affects the complete molecular response.
“It’s like We’re Still in Slavery”: Stress as Distress and Discourse among Jamaican Farm Workers in Ontario, Canada
Authors: Mayell Stephanie
Published: December 2023

For more than fifty years, Jamaican farm workers have been seasonally employed in Canada under the Seasonal Agricultural Worker Program (SAWP). In Canada, these workers live and work in conditions that make them vulnerable to various health issues, including poor mental health. This ethnographic study investigated Jamaican SAWP workers’ mental health experiences in Southern Ontario. Several common factors that engender psychological distress among Jamaican workers, ranging from mild to extreme suffering, were uncovered and organised into five themes: (1) family, (2) work environments and SAWP relations, (3) living conditions and isolation, (4) racism and social exclusion, and (5) illness and injury. I found that Jamaican workers predominantly use the term ‘stress’ to articulate distress, and they associate experiences of suffering with historic plantation slavery. Analysis of workers’ stress discourses revealed their experiences of psychological distress are structured by the conditions of the SAWP and their social marginalisation in Ontario. This article presents and discusses these findings in the context of SAWP power dynamics and concludes with policy recommendations aimed at improving the mental health of all SAWP workers. In foregrounding the experiences of Jamaican workers, this study addresses the dearth of research on the health and wellbeing of Caribbean SAWP workers.
Stigma and Mental Well-Being among Teenage Mothers in the Rural Areas of Makhado, Limpopo Province
Authors: Moganedi Shonisane Emily , Mudau Tshimangadzo Selina
Published: December 2023

Adolescent mothers experience psychological challenges, such as social withdrawal and rejection by their communities. Assuming the role of motherhood is associated with emotional and mental distress, such as fear and worry, regret and frustration, guilt and shame, and social isolation. This study adopted a qualitative critical participatory action research approach. Purposive and snowballing recruitment were employed to recruit 11 teenage mothers, and semi-structured face-to-face interviews and focus group discussions were employed to generate data. All sessions were audio recorded and transcribed verbatim. Data were analysed using qualitative thematic analysis. Teenage mothers in this study reported experiencing humiliation and being subjected to degrading remarks and judgement by schoolmates. The experience of being rejected, teased, and labelled made participants feel that they were not accepted as part of their community. It was concluded that teenage mothers experienced inconsistent support from parents and community members, which led to social isolation and feeling rejected; hence, teenage mothers lacked a sense of belonging to and acceptance by their communities. Policymakers and authorities in education and healthcare should encourage social change and transformative learning and address the issue of stigma and social isolation experienced by teenage mothers in rural communities.
Do Segmented Assimilation Theory and Racialized Place Inequality Framework Help Explain Differences in Deaths Due to COVID-19 Observed among Hispanic Subgroups in New York City?
Authors: Cuecuecha Alfredo
Published: December 2023

This article studies the differences in the correlation between deaths and the Hispanic share for different Hispanic subgroups in New York City. Such differences are predicted by Segmented Assimilation Theory as different assimilation paths. The study is carried out at the level of PUMAs, and it is argued that such geographic locations are macro-level factors that determine health outcomes, as the theory of Racialized Place Inequality Framework claims. The study presents a spatially correlated model that allows to decompose the spatial effects into direct and indirect effects. Direct effects are linked to the macro structure where the individual lives, while indirect effects refer to effects in the adjacent macro structures where the individual lives. The results show that both types of effects are significant. The importance of the direct effects is predicted by RPIF, while the importance of the indirect effects is a new result that shows the complexity of the effects of macro structures. The article also shows results for subsamples that allow to test the importance of different factors that have been linked to the excess deaths observed among Hispanics. The effects of such factors are also found to be heterogenous among the different Hispanic subgroups, which also provides evidence in favor of the Segmented Assimilation Theory. Access to health insurance and doctor density are found to be the most important elements that serve as protective factors for all Hispanic subgroups in New York City, signaling its importance in achieving assimilation for Hispanic immigrants to New York City.
Validation of the General Evaluation Scale for Measuring Ethnic and Religious Prejudice in an Indonesian Sample
Authors: Tondok Marselius Sampe , Suryanto Suryanto , Ardi Rahkman
Published: December 2023

The General Evaluation Scale (GES) has been widely employed to assess attitudes toward outgroups, including ethnic and religious prejudice. However, validation within the Indonesian context has not been conducted. Using two studies (Study 1, religious prejudice; Study 2, ethnic prejudice), we provide evidence of psychometric properties of a six-item GES for measuring ethnic and religious prejudice based on factor structure, composite reliability, and convergent validity in Indonesia. The results demonstrate an acceptable model fit for a single-factor structure characterized by high internal consistency (McDonald’s Omega/ω = 0.93 in Study 1, ω = 0.94 in Study 2). Furthermore, the scale exhibits solid convergent validity, as evidenced by its correlations with the blatant and subtle prejudice scale (r = −0.44 in Study 1, r = −0.74 in Study 2) and the feeling thermometer scale (r = 0.60 in Study 1, r = 0.78 in Study 2). In summary, this research unequivocally establishes the GES as a valuable instrument for measuring religious and ethnic prejudice in the Indonesian context, underpinned by its robust psychometric properties. Nevertheless, it underscores the need for further investigations with diverse samples and varying social contexts to bolster the scale’s reliability and applicability.
Elastic Stress Field beneath a Sticking Circular Contact under Tangential Load
Authors: Willert Emanuel
Published: December 2023

Based on a potential theoretical approach, the subsurface stress field is calculated for an elastic half-space which is subject to normal and uniaxial tangential surface tractions that—in the case of elastic decoupling—correspond to rigid normal and tangential translations of a circular surface domain. The stress fields are obtained explicitly and in closed form as the imaginary parts of compact complex-valued expressions. The stress state in the surface and on the central axis are considered in detail. As, within specific approximations that have been discussed at length in the literature, any tangential contact problem with friction can be understood as a certain incremental series of such rigid translations, the solutions presented here can serve as the basis of very fast superposition algorithms for the analysis of subsurface stress fields in general tangential contact problems with friction. This idea is demonstrated by means of the frictional tangential contact between an elastic half-space and a rigid cylindrical flat punch with rounded corners.
Insights into the Relative Abundance, Life History, and Ecology of Oceanic Sharks in the Eastern Bahamas
Authors: Talwar Brendan S. , Brooks Edward J. , Abercrombie Debra L. , Anderson Brenda , Bond Mark E. , Brooks Annabelle M. L. , Chapman Demian D. , Clementi Gina M. , Fields Candace Y. A. , Gelsleichter Jim , Grubbs R. Dean , Howey Lucy A. , Jordan Lance K. B. , Kiszka Jeremy J. , Knotek Ryan J. , Papastamatiou Yannis P. , Peterson Cheston T. , Schneider Eric V. C. , Shipley Oliver N. , Williams Sean , Winchester Maggie M. , Heithaus Michael R.
Published: December 2023

Fisheries-independent data on the diversity, relative abundance, and demographic structure of poorly studied, threatened oceanic sharks are absent from much of the western North Atlantic Ocean, where multiple oceanic shark species have experienced significant population declines. Resource-limited management approaches require the identification of critical habitats or aggregation sites worthy of protection and enforcement. Data were collected on oceanic sharks using pelagic longline surveys, targeted baiting, and opportunistic encounters in oligotrophic open-ocean habitats of north-eastern Exuma Sound (NES), The Bahamas. The oceanic epipelagic shark community was also characterized using targeted baiting off Columbus Point, Cat Island (CI), a seamount north of San Salvador (SSSM), and the northwestern tip of Mayaguana. Pelagic longline surveys suggested that the relative abundance of sharks at NES was low (shark catch-per-unit-effort: 0.0007 sharks hook−1 h−1; 2.3 sharks per 1000 hooks). Silky sharks Carcharhinus falciformis, particularly juveniles (134 ± 39 cm stretched total length; mean ± SD STL), were the most common. Targeted baiting suggested oceanic whitetip sharks C. longimanus were abundant at CI, where large adults (245 ± 23 cm STL), most of which were females (83.8%, n = 98 of 117) that were gravid (65.7%; n = 46 of 70 assessed for pregnancy), dominated the aggregation. Many (20.5–26.5%, n = 24–31 of 117 depending on assumptions regarding tag loss) were recaptured or resighted at CI for up to five years. Silky sharks dominated catches at SSSM. Oceanic sharks, particularly adults, were sometimes caught or observed alongside short-finned pilot whales Globicephala macrorhynchus or tunas. Although The Bahamas offers threatened oceanic sharks refuge from fishing across its entire jurisdiction, these data suggest that some fixed features, including sites such as CI and potentially SSSM, are important aggregation sites with high regional conservation value and should be prioritized by fisheries managers and enforcement officials.
Exploring the Acceptance and User Satisfaction of AI-Driven e-Learning Platforms (Blackboard, Moodle, Edmodo, Coursera and edX): An Integrated Technology Model
Authors: Saqr Raneem Rashad , Al-Somali Sabah Abdullah , Sarhan Mohammad Y.
Published: December 2023

As e-learning platforms gain traction globally, understanding students’ perceptions and intentions towards these platforms is paramount, especially within the context of Saudi universities, where e-learning is rapidly emerging as a transformative educational tool for sustainable development. This study examined the influence of different AI-based social learning networks, personal learning portfolios, and personal learning environments on Saudi university students’ perceived usefulness and ease of use regarding AI-driven platforms (Blackboard, Moodle, Edmodo, Coursera and edX). Furthermore, the study explored the direct effects of these perceptions on students’ satisfaction and intentions to use e-learning. The study also delved into the moderating effects of individual characteristics like readiness for self-directed e-learning, self-efficacy, and personal innovativeness on students’ e-learning intentions. A cross-sectional design was employed, collecting self-reported data from a strong sample of Saudi university students using stratified random sampling. The study targeted 500 students from different universities in Saudi Arabia. Results underscored the significant influence of AI-based social learning networks, personal learning portfolios, and personal learning environments on perceived usefulness and ease of use. Both perceived usefulness and ease of use also significantly and positively influenced satisfaction, influencing students’ attitudes toward e-learning but not their intention to use it. Student characteristics, especially self-efficacy, showed notable impacts on e-learning intentions. However, their interaction with satisfaction yielded insignificant effects on intentions.
The Symmetric and Asymmetric Impacts of Energy Consumption and Economic Growth on Environmental Sustainability
Authors: Alshehry Atef , Belloumi Mounir
Published: December 2023

Climate change has emerged as a global challenge because of its threat to sustainable development goals. Fossil fuels and economic growth are responsible for pollution and, thus, for climate change. In this context, this study explored the environmental Kuznets curve hypothesis for the case of 17 MENA countries over the period of 1990–2020. It investigated the symmetric and asymmetric impact of energy consumption and economic growth on CO2 emissions by controlling for population density, trade openness, and FDI inflows using panel linear and nonlinear ARDL models. The robustness of the results was checked using the fully modified OLS and dynamic OLS methods. Moreover, the Dumitrescu–Hurlin panel causality test was employed to determine the directions of causality between the variables. Overall, the empirical results of both panel linear and nonlinear ARDL models validate the environmental Kuznets curve hypothesis for the selected sample of MENA countries. Economic growth leads to environmental degradation only in the long run, whereas a rise in energy consumption leads to an increase in pollution in both the short and long run. These results are confirmed by the fully modified OLS and dynamic OLS methods. The findings of the Dumitrescu–Hurlin panel causality test also indicate the existence of bidirectional causality between energy consumption and CO2 emissions and between economic growth and CO2 emissions. Therefore, policy makers in the MENA region should invest in clean technologies and accelerate the transition to renewable energies such solar energy, wind power, and hydropower to align with sustainable development goals.
Experimental Study on Thermo-Mechanical Behavior of a Novel Energy Pile with Phase Change Materials Using Fiber Bragg Grating Monitoring
Authors: Cui Hongzhi , Shi Jiaxin , Li Haixing , Xiao Xiong , Peng Peng , Bao Xiaohua
Published: December 2023

The combination of phase change materials (PCMs) with building materials is a flourishing technology owing to the low-temperature change of the materials during phase change and the potential for enhanced heat storage and release. In this study, a new type of PCM energy pile, in which 20 stainless steel tubes (22 mm in diameter and 1400 mm in length) filled with paraffin were bound to heat exchange tubes, was proposed. An experimental system monitored by a fiber Bragg grating (FBG) to study the thermo-mechanical behavior of energy piles and surrounding soil was established. Both the PCM pile and the ordinary pile, with the same dimensions, were tested under the same experimental conditions for comparison. The results indicate that the temperature sensitivity coefficient calibration results of the FBG differ from the typical values by 8%. The temperature variation is more obvious in the ordinary pile and surrounding soil. The maximum thermal stress of the ordinary energy pile is 0.5~0.6 times larger than that of the PCM pile under flow rates ranging from 0.05 m3/h to 0.25 m3/h. The magnitudes of the pore water pressure and soil pressure variations were positively correlated with the flow rates.
Impacts of COVID-19 on Logistics Service Providers’ Operations: An Italian Empirical Study
Authors: Zenezini Giovanni , Cagliano Anna Corinna , Mangano Giulio , Rafele Carlo
Published: December 2023

The lockdowns caused by the COVID-19 pandemic between 2020 and 2021 resulted in a substantial increase in e-commerce purchases, with the consequent growth of logistics services. Thus, this paper is aimed at studying the effects of the pandemic on the operational processes of logistics service providers. To this end, a survey questionnaire was developed and administered to a sample of identified respondents. The collected data were quantitatively analyzed via the Kruskal–Wallis test. The outcomes point out that logistics operators faced an increase in the distances traveled to carry out pick-up and delivery activities, and larger companies added more light vehicles to their fleets, proving that the company size was a relevant aspect of ensuring a quick response to the pandemic. These results show an increased business-to-consumer market share that is leading to a redesign toward more sustainable operational strategies.
Application of Plant Ingredients for Improving Sustainability of Fresh Pasta
Authors: Zahorec Jana , Šoronja-Simović Dragana , Petrović Jovana , Šereš Zita , Sterniša Meta , Jozinović Antun , Šubarić Drago , Ačkar Đurđica , Babić Jurislav , Možina Sonja Smole
Published: December 2023

Pasta is a low-cost and easy-to-prepare food product. By using fresh pasta, the drying process is omitted, which represents significant energy and financial savings, but the durability of such pasta is very limited. The addition of plant materials (parsley, oregano, thyme, cinnamon, nettle, spinach, and carob) to the dough affects the microbiological stability and thus the durability of the fresh pasta, which can then be stored longer in the refrigerator without the need to freeze the product. With significant energy savings due to the omission of the drying and freezing processes, extending the shelf life of the pasta will contribute to the reduction of food waste and thus contribute to a more sustainable production system. The aim of this work was to examine the possibility of producing fresh pasta with the addition of plant materials from the perspectives of technological and sensory quality, as well as microbiological composition. The incorporation of plant materials (10 g/100 g) decreased water absorption and had no effect on optimal cooking time. Thyme-enriched pasta had significantly lower (p < 0.05) cooking loss (3.34%) than the control sample (4.12%). In cinnamon-, spinach-, and parsley-enriched pasta, an appealing colour and pleasant smell and taste were achieved. Cinnamon and carob proved to have the most favourable effect on the microbiological quality (reduction in mesophilic, Enterobacteriaceae, and yeast counts), followed by spinach (reduction in mould count). For cinnamon-enriched pasta, the best technological (optimal cooking time of 3.23 min; cooking loss of 4.41%; firmness of 531.94 g) and sensory and microbiological quality were achieved; thus, cinnamon proved to be the preferred natural preservative for the production of enriched pasta.
Re-Engineering Financial Resources through Development Finance in Africa: A Review of the Literature
Authors: Okunlola Abiodun F. , Aregbeshola Adewale R.
Published: December 2023

Most studies erroneously conclude that financial engineering occurs only within the purview of private institutions. This study defies this claim and affirms an equal public prerogative. It proceeds to innovate a financial re-engineering (F-Re) axiom expressed by the foundational, fundamental, and finance pillars (FFFps). This is encapsulated in a quadrant (Q), with which it is believed Africa’s accelerated development can be harnessed. Exploratorily, in addition to the visual and matching path analyses, this study provides a clear path in Q1–4, showing how Africa should re-engineer citizens’ priorities using deliberate development finance principal strategies going forward.
Sustainability Transition Framework: An Integrated Conceptualisation of Sustainability Change
Authors: Petrović Emina Kristina
Published: December 2023

Responding to calls for climate action, this article develops and introduces a Sustainability Transition Framework (STF), which is a high-level interpretation of the complex dynamics dominating the current historical moment characterised by an aspiration for accelerated climate action and challenges with implementing change. This STF brings together and integrates a set of theories about change which were developed in different disciplines and not commonly discussed at the same time. The four key theories are: (1) sustainability transitions, transition management and related theories which consider the necessary change in sociotechnical regimes; (2) diffusion of innovation theory, which provides a high-level overview of patterns with uptake of innovation; (3) a change curve which explains complex emotional experiences when facing organisational change; and (4) a conceptualisation of the style cycle, which is commonly used in the history of art and architecture. These are visually depicted and integrated into a novel STF diagram. The STF presents one of the most comprehensive integrations of currently available knowledge on how change happens, which is essential for accelerated climate action. The STF helps understand individual or social group experiences. Through an improved understanding of the sustainability transition, the STF empowers climate action.
Different Methods for Estimating Default Parameters of Alpha Power-Transformed Power Distributions Using Record-Breaking Data
Authors: Attwa Rasha Abd El-Wahab , Radwan Taha
Published: December 2023

The current study addresses the estimation of the default parameters of alpha power-transformed power (APTPO) distributions. For the location and scale parameters of the APTPO distributions, we provide coefficients for both the best linear unbiased estimators (BLUE) and the best linear invariant estimators (BLIE) methods. Furthermore, we establish a forecast for future records. The parameters of the APTPO distribution are estimated using the maximum likelihood estimation method (MLE). The goodness-of-fit test (using Akaike information criterion (AIC)) is computed using both the inter-record time sequence and the entire sample. Also, we utilize a simulation approach to demonstrate the practicality and benefits of our perspective. Finally, we demonstrate the accuracy of these parameters and the performance of estimators through a real-life example.
Exploring Global Polarization Splitting in Au+Au Collisions at sNN=19.6 GeV Using Viscous Hydrodynamic Model CLVisc
Authors: Ye Shasha , Yuan Xuefei , Jiang Zefang
Published: December 2023

We present a systematic study of the global polarization of Λ and Λ¯ hyperons in Au+Au collisions at sNN=19.6 GeV using the viscous hydrodynamic model CCNU-LBNL-Viscous hydrodynamic model (CLVisc) with a modified 3D optical Glauber model initial condition. The global polarization splitting as a function of transverse momentum and rapidity is investigated. It is shown that the magnitude of the net baryon density and its longitudinal titled geometry at the initial stage both have significant effects on the global polarization splitting of Λ and Λ¯ hyperons. Specifically, an increase in the magnitude of the net baryon density leads to a corresponding minor increase in the global polarization splitting. Similarly, alterations in the tilted geometry of net baryon density results in significant changes in the splitting of the global polarization.