bluuebunny/crossref_metadata_2025_split huggingface dataset:
To Share or Not to Share: Randomized Controlled Study of Misinformation Warning Labels on Social Media
Authors: Gruzd Anatoliy , Mai Philip , Soares Felipe B. 
Published: August 2024

AbstractCan warning labels on social media posts reduce the spread of misinformation online? This paper presents the results of an empirical study using ModSimulator, an open-source mock social media research tool, to test the effectiveness of soft moderation interventions aimed at limiting misinformation spread and informing users about post accuracy. Specifically, the study used ModSimulator to create a social media interface that mimics the experience of using Facebook and tested two common soft moderation interventions – a footnote warning label and a blur filter – to examine how users (n = 1500) respond to misinformation labels attached to false claims about the Russia-Ukraine war. Results indicate that both types of interventions decreased engagement with posts featuring false claims in a Facebook-like simulated interface, with neither demonstrating a significantly stronger effect than the other. In addition, the study finds that belief in pro-Kremlin claims and trust in partisan sources increase the likelihood of engagement, while trust in fact-checking organizations and frequent commenting on Facebook lowers it. These findings underscore the importance of not solely relying on soft moderation interventions, as other factors impact users’ decisions to engage with misinformation on social media.
Impact of international student mobility on international profile of jobs
Authors: Knutsen Tora Kjærnes , Wiborg Vegard Sjurseike , Wiers-Jenssen Jannecke 
Published: August 2024

AbstractWhile the impact of international student mobility (ISM) on vertical labour market outcomes, such as wages and employment, has been widely studied, less is known about the impact of ISM on horizontal outcomes, such as job characteristics. We contribute to filling this gap by studying whether ISM experience is associated with having a job with an international profile, in terms of job content in the domestic labour market or working abroad. We analyse a large-scale Norwegian survey, enabling us to compare mobile to non-mobile master’s graduates 3 years after graduation while controlling for a rich set of demographic and educational characteristics. We find that graduates who pursued their entire degree abroad and graduates who undertook a part of their degree abroad are respectively 19–22 and 3–5 percentage points more likely to work abroad than their non-mobile peers. Moreover, both groups of mobile students have jobs with more internationally oriented features in the domestic labour market. In contrast to expectation, however, there were no significant differences between graduates with a full degree abroad and graduates with a shorter stay abroad regarding the latter aspect.
Sustainability and financial performance in the banking industry of the United Arab Emirates
Authors: Raza Ali , Alavi Ain Bemisal , Asif Laiba 
Published: August 2024

AbstractToday's banking industry achieving sustainable profitability necessitates by integrating economic, environmental, and social factors due to pressing environmental concerns. This study investigates the impact of sustainability on financial performance in the United Arab Emirates (UAE) banking sector, using the Autoregressive Distributed Lag (ARDL) and Bootstrapping ARDL approaches on data from 2002 to 2022. The analysis revealed that economic sustainability, environmental and social sustainability exhibit a significant impact on financial performance in the short run and the long run at a (p < 0.05). 1% of economic sustainability activities increases Return on Assets (ROA) by 0.73 and Return on Equity (ROE) by 0.64. 1% of environmental sustainability activities decreases ROA by −0.28 and increases ROE by 0.35. 1% of social sustainability activities increases ROA by 0.47 and ROE by 0.42. To improve long-term profitability, this study emphasizes how crucial it is for the banking industry in the UAE to strategically integrate sustainability principles. These findings highlight the need to promote sustainability in the banking sector for environmental improvement, offering insights for UAE regulators and stimulating additional research.
Decision time: illuminating performance in India’s district courts
Authors: Aithala Varsha , Sachan Anushka , Sen Srijoni , Payal Himanshu , Bhattacharya Chiranjib 
Published: August 2024

Abstract
Studies on court administration in India have so far focused their attention largely on caseload management and judge strength of the higher judiciary. In-depth investigations of the performance of India’s lower courts, the primary loci of a citizen’s contact with the judiciary, are rarer, largely due to the lack of available data at scale. We conduct a quantitative analysis of a large dataset of more than 1700 Indian district courts between 2010 and 2018, to assess court performance through the measure of timeliness of case disposal. We use median days to decision—the median number of days it takes for a district court in India to decide a case. We aim to understand the impact of well-established factors—working strength and tenure of judges, case administration, age distribution of cases, and category or case type—against district courts’ performance. We find that court type and nature of cases are important predictors of a district court’s performance, and that the total number of judge working days and average bench strength are not good indicators of courts’ performance—the workload per judge being actually lower in low-performance district courts, compared to high-performing courts. Our study also reveals the strengths and weaknesses of the available judicial data platforms and points toward reforms in judicial administration to address these concerns.
Toward a trustworthy and inclusive data governance policy for the use of artificial intelligence in Africa
Authors: Effoduh Jake Okechukwu , Akpudo Ugochukwu Ejike , Kong Jude Dzevela 
Published: August 2024

Abstract
This article proposes five ideas that the design of data governance policies for the trustworthy use of artificial intelligence (AI) in Africa should consider. The first is for African states to assess their domestic strategic priorities, strengths, and weaknesses. The second is a human-centric approach to data governance, which involves data processing practices that protect the security of personal data and the privacy of data subjects; ensure that personal data are processed in a fair, lawful, and accountable manner; minimize the harmful effect of personal data misuse or abuse on data subjects and other victims; and promote a beneficial, trusted use of personal data. The third is for the data policy to be in alignment with supranational rights-respecting AI standards like the African Charter on Human and Peoples Rights, the AU Convention on Cybersecurity, and Personal Data Protection. The fourth is for states to be critical about the extent to which AI systems can be relied on in certain public sectors or departments. The fifth and final proposition is for the need to prioritize the use of representative and interoperable data and ensure a transparent procurement process for AI systems from abroad where no local options exist.
Decline of CO2 Release During the Evolution of the Thaw Slump on the Northern Qinghai‐Tibet Plateau
Authors: Mu Mei , Mu Cuicui , Liu Hebin , Zhang Chunling , Jia Yunjie , Lei Pengsi , Peng Xiaoqing 
Published: August 2024

AbstractAbrupt permafrost thaw accelerates the decomposition of soil organic carbon and might double the warming caused by the carbon release. However, the influence of thaw slump evolution on carbon dioxide (CO2) emission rates and its drives remains unclear, which induces large uncertainties in the prediction of permafrost carbon‐climate feedback. Here we collected soil samples in the thaw slump landscapes that happened 1–23 years ago on the northern Qinghai‐Tibet Plateau (QTP) and measured the CO2 release rates using a 189‐day aerobic laboratory incubation in the dark. The incubation results showed that thaw slump occurred 23 years ago reduced soil CO2–C release by 57 ± 19% compared with the undisturbed area. The relative contribution of O‐alkyl C and microbial abundance decreases with the thaw slump initiation time lengthens. We illustrate that soil carbon quality and microbial communities uniquely explained 41% and 13% of the variation in CO2–C release, respectively. We preliminary estimate that the carbon release for thaw slump landscapes on the QTP may be overestimated by approximately 50% if the declining soil CO2–C release is without consideration. Our study highlights the CO2–C release would decrease with the stability of thaw slumps on the warming and wetting QTP, which may weaken the mountain permafrost carbon‐climate feedback.
Fetal exposure to toxic metals (mercury, cadmium, lead, and arsenic) via intrauterine blood transfusions
Authors: Al-Saleh Iman , Alnuwaysir Hissah , Al-Rouqi Reem , Aldhalaan Hesham , Tulbah Maha 
Published: August 2024

Abstract
Background
Intrauterine blood transfusions (IUBTs) are critical for treating fetal anemia but may expose fetuses to toxic metals. This study assessed mercury (Hg), cadmium (Cd), lead (Pb), and arsenic (As) levels in red blood cell (RBC) transfusion bags used during pregnancy, examined metal exposure in maternal and cord blood, and evaluated fetal health risks.

Methods
Thirty pregnant women who underwent intrauterine blood IUBTs were enrolled in this study. Metal concentrations were measured in one to nine transfusion bags for each participant. These bags contained 8–103 mL volumes and were administered between gestational weeks 18 and 35. We also tested the mothers’ blood for metal levels in the final stages of pregnancy and the umbilical cord blood at birth. The assessment utilized the intravenous reference dose (IVRfD) and the hazard index (HI) to evaluate the non-carcinogenic health risks these metals might pose to the fetus.

Results
Metals were detectable in almost all transfusion bags. The IVRfD was exceeded for Hg in 16 fetuses, Cd in 8 fetuses, Pb in 30 fetuses, and As in 1 fetus. Significant correlations were found between the concentrations of Hg, Cd, and As in transfused RBCs and cord blood. No correlations were observed between these concentrations and maternal blood levels, except for Cd. The influence of multiple IUBTs was positively associated only with Cd levels in the cord (ß = 0.529, 95% confidence intervals (CI) between 0.180 and 0.879). The HI exceeded 1, indicating significant health risks, predominantly from Pb, followed by Hg and Cd.

Conclusion
The findings of this study highlight the significant risk of fetal exposure to toxic metals, mainly Pb, through IUBTs. This underscores the critical need for prescreening blood donors for toxic metals to minimize the potential for long-term adverse effects on the fetus. The research stresses the necessity of balancing the immediate benefits of IUBTs against the risks of toxic metal exposure, underscoring the importance of safeguarding fetal health through improved screening practices.

Impact

This study highlights the risk of toxic metal exposure through IUBTs, a treatment for fetal anemia.

Hg, Cd, Pb, and As levels were measured in transfusion bags and linked to fetal exposure through maternal and umbilical cord blood analysis.

The HI indicates significant Pb exposure risks, underscoring the need for mandatory blood donor screening.

Recommendations include shifting toward safer practices in managing fetal anemia to protect fetal health.
Linguistic borrowings in trade terminologies: an analysis of ancient Indian and Egyptian languages from 3300 BCE to 500 CE
Authors: Mohanan Pallavi , Prakash Nirupama 
Published: August 2024

AbstractThe research delves into the intricate web of linguistic borrowings in trade terminologies between Ancient Indian languages (Sanskrit, Prakrit) and Egyptian languages (Ancient Egyptian Hieroglyphs, Demotic script) spanning from approximately 3300 BCE to 500 CE. Through a meticulous analysis of selected literary texts and inscriptions, including the Hathigumpha Inscription, Rudradaman I Inscription, Junagadh Rock Inscriptions, Nasik Cave Inscriptions, Rosetta Stone, Satirical Papyrus, and Turin Taxation Papyrus, the study unravels the linguistic evolution and cultural exchanges embedded within ancient trade networks. Contextualizing these linguistic borrowings within the historical framework of trade routes, maritime activities, and economic exchanges, the research sheds light on the nuances of communication and adaptation in commercial interactions. By employing rigorous research methodologies and comparative studies, the findings offer a comprehensive understanding of how language served as a bridge for commerce, diplomacy, and cultural exchange between these ancient civilizations. This study not only contributes to the fields of linguistic history and ancient trade studies but also offers valuable insights into the dynamic interplay of language, trade, and cultural connectivity in the ancient world.
Stochastic thermodynamics of micromagnetics
Authors: Ding Mingnan , Wu Jun , Xing Xiangjun 
Published: August 2024

Abstract
In this work, we study the stochastic thermodynamics of micro-magnetic systems. We first formulate the stochastic dynamics of micro-magnetic systems by incorporating noises into the Landau–Lifshitz (LL) equation, which describes the irreversible and deterministic dynamics of magnetic moments. The resulting stochastic LL equation obeys detailed balance, which guarantees that, with the external field fixed, the system converges to thermodynamic equilibrium with vanishing entropy production and with non-vanishing probability current. We then discuss various thermodynamic variables both at the trajectory level and at the ensemble level, and further establish both the first and the second laws of thermodynamics. Finally, we establish the Crooks fluctuation theorem, and verify it using numerical simulations.
Autonomous Human-Robot Collaborative Assembly Method Driven by the Fusion of Large Language Model and Digital Twin
Authors: Chen Jianpeng , Luo Haiwei , Huang Sihan , Zhang Meidi , Wang Guoxin , Yan Yan , Jing Shikai 
Published: August 2024

Abstract
Human-robot collaboration (HRC) plays an important role in human-centric manufacturing, which requires cooperative robots to have the ability of collaborate with human autonomously. It is very complex to understand the intention of human during the assembly process, therefore, we proposed a method of autonomous HRC assembly driven by the fusion of large language model (LLM) and digital twin in this paper. The assembly state is recognized from two perspectives, including the perception of key parts based on transfer learning and YOLO, and perceive operator actions based on LSTM and attention mechanism. In order to improve the autonomy of HRC, a collaborative task decision method driven by fine-tuning LLM based on assembly domain knowledge is proposed. A case study of reducer assembly is presented to verify the effectiveness of the proposed method.
Target Threat Level Classification Based on Improved Three-way Decisions
Authors: Li Shikai , Long Xin , Zeng Yaoyuan , Wang Xueying 
Published: August 2024

Abstract
Air target threat assessment is of great importance in military decision-making, as it involves ranking enemy targets based on their threat level. Existing methods only provide rankings without offering decision support for combating, observing, or opting no action, which makes it difficult to deal with complex combat situations in real time. Therefore, we propose a method for threat level classification based on improved three-way decisions (TWD). In addition, considering that certain attribute information contains deviation, we introduce the theory of interval-valued intuitionistic fuzzy set (IVIFS) to address uncertain information. Meanwhile, in order to make full use of the interval numbers, we innovatively propose a loss function based on the attribute dominance degree to enhance accuracy of threat level classification. The experimental results show that our method can effectively handle uncertain information and provide decision support to the decision-makers, while the improvement of the classification ability is demonstrated through comparative experiment.
Research on Steel Surface Defect Detection Algorithm Based on Improved YOLOv8n
Authors: Zhong Weiming , Zhang Liangan , Li Pengfei , Gui Wenjun 
Published: August 2024

Abstract
Steel, as one of the most used materials, is of great importance for steel defect detection in industry. Aiming at the existing existing deep learning-based steel surface defect detection algorithms that have problems such as misdetection, leakage, low detection accuracy and speed, a steel surface defect detection algorithm YOLOv8n-CFP is proposed to improve YOLOv8n. Firstly, the CPCA attention mechanism module is added, which combines the channel attention mechanism with the spatial attention mechanism, to improve the model’s recognition accuracy and generalization ability. After that, the Faster module is used instead of Bottleneck to reduce the computational complexity of the C2f module and lighten the network structure. Finally, the PIoU loss function is used instead of CIoU to optimize the performance of anchor frame regression, which guides the anchor frame to regress efficiently and achieve faster convergence by combining the target size adaptive penalty factor and gradient adjustment function. The experiments show that compared with the basic YOLOv8n network, the YOLOv8n-CFP inspection network improves the mAP from 76.2% to 79.0% on the steel surface defects inspection dataset of YOLOv8n, which is an improvement of 2.8%, and the model volume, parameter count, and computational size are reduced by 17.5%, 18.3%, and 17.3%, respectively, and the FPS value is improved by 60.4. Compared with other YOLOv8n networks, the average accuracy mAP of YOLOv8n-CFP inspection network is increased to 79.0%. Compared with other YOLO algorithms, YOLOv8n-CFP has significant advantages in steel surface defect detection.
Design and Simulation of Low-temperature Cooling Structure for Intelligent Equipment
Authors: Shi Zhanli , Gong Yongjun , Chen Chen , Yang Yuxing , Bao Yongjie 
Published: August 2024

Abstract
The vortex tube has become a key component of intelligent equipment due to its unique energy separation effect. However, there are complex fluid motion and heat and cold exchange processes inside, which brings difficulties to the design. To improve the refrigeration efficiency, the structure of the pneumatic swirl generator was designed. Through numerical simulation and experiment, the law of energy separation with the change of structural parameters of the pneumatic swirl generator was studied. An experimental platform for vortex tubes was constructed to examine the impact of varying ratios of cold-end tube apertures on temperature. The results show that changing the structure of the pneumatic swirl generator can effectively improve the energy separation efficiency and realize the cooling of the intelligent equipment.
Growth Response and Yield of Porang (Amorphophallus muelleri Blume) on Differences in Polybag Size and Planting Media
Authors: Sakiroh  , Saefudin  , Wardiana E , Pranowo D , Listyati D 
Published: August 2024

Abstract
Porang (Amorphophallus muelleri Blume) is one of the food crops that has a substantial role in supporting the food security concept. However, many rural farmers do not have enough land to cultivate porang, so land-saving cultivation technology innovations are needed. One alternative is to grow porang in polybags, which can be practiced in narrow yards, such as urban farming, to support food security in urban areas. This study aims to determine the growth and yield response of porang to differences in polybag size and planting media composition. The study was conducted at the Pakuwon Experimental Station, Sukabumi, West Java, from September 2020 to June 2022, in a factorial randomized complete block design with six replications. The first factor is the two sizes of polybags: small (SSP) (25 x 25 cm) and large (LSP) (40 x 40 cm). The second factor was the three planting media compositions, the proportion of soil to chicken manure (SCM), such as 5:1, 10:1, and 15:1. The observed variables were the growth and tubers yield in the second growth period. The results showed that large polybags (40 x 40 cm) combined with the planting media proportion of soil to chicken manure (5:1) gave the best growth and tubers yield compared to other treatments.
Evaluation of airflow, temperature, and RH in the deep bed dryer for paddy grain with several combinations of floors and air distribution pipes using CFD
Authors: Nurba D , Mardjan S S , Wulandani D , Nelwan L O , Subrata I D M 
Published: August 2024

Abstract
The problem of the varying water content of the dried grain is a common problem in the drying process in the pile of grain. An uneven drying air distribution and reduced air pressure when penetrating the porosity and thickness of the grain pile cause that condition. A deep bed dryer is one of the dryers with a forced convection system to carry water content from the grain pile; the thickness of the pile and grain porosity strongly affect this process. The arrangement of the air distribution pipe in a pile of grain is an effort to facilitate air drying so that it is spread evenly in a grain pile and helps the airflow through the thickness of the pile of grains. The arrangement of the shape of the dryer floor is also essential for the effectiveness of the air input from the blower into the drying chamber so that there is minimal loss of air pressure in the plenum and the distribution of air drying becomes evenly distributed. CFD simulations were conducted for four scenarios using a combination of conical and sloping floor shapes, as well as input airflow pipe models in rectangle and circular formation; that combination arrangement is LT1PU1, LT1PU2, LT2PU1, and LT2PU2. The simulation output is analyzed using the SAW method to determine the best combination for constructing a deep bed dryer. The evaluation results on four design scenarios show that the fourth scenario, the LT2PU2 model, has an average distribution value of airflow velocity, air pressure, temperature, and RH of 0.061 m·s−1, 6.07 Pa, 39.35°C, and 44.30%, respectively. Moreover, it gets a preference value of 0.99 as the best model. So, it is worth developing as a Deep bed dryer prototype for paddy grain.