bluuebunny/crossref_metadata_2025_split huggingface dataset:
Understanding the Landscape: A Review of Explainable AI in Healthcare Decision-Making
Authors: Ansari Zulfikar Ali , Tripathi Manish Madhava , Ahmed Rafeeq 
Published: September 2024

Abstract

Breast cancer remains a significant global health concern, impacting millions of women. Early and accurate diagnosis is crucial for improving treatment outcomes and reducing mortality rates. Machine learning (ML) has emerged as a powerful tool for breast cancer prediction, demonstrating its ability to identify complex patterns and relationships in large datasets. This paves the way for efficient collaboration between AI and healthcare professionals. This systematic review explores the diverse machine-learning techniques employed in breast cancer diagnosis. We comprehensively analyse and evaluate the effectiveness of various computational methodologies by synthesising findings from a wide range of peer-reviewed studies. Our analysis highlights the substantial advancements achieved in utilizing machine learning algorithms for breast cancer prediction. However, challenges remain in harnessing the full potential of machine learning for healthcare. These include the need for larger and more diverse datasets, the effective incorporation of imaging data, and the development of interpretable models. While AI offers immense potential for improving healthcare, ensuring transparency, interpretability, and trust is crucial, especially in complex domains like cancer diagnosis. This research emphasizes the importance of Explainable AI (XAI) for enhancing clinical decision-making and building trust between patients and healthcare providers. We advocate for fostering interdisciplinary collaboration among AI researchers, medical professionals, ethicists, and policymakers to ensure the responsible integration of AI in healthcare.
Comparative Morphological and Immunohistochemical Characteristics of the Human Fetal Organs of Zuckerkandl and Adrenal Medulla
Authors: Otlyga Ekaterina , Otlyga Dmitry , Junemann Olga , Krivova Yuliya , Proshchina Alexandra , Kharlamova Anastasia , Gulimova Victoria , Sonin Gleb , Saveliev Sergei 
Published: September 2024

Abstract

The adrenal medulla and organs of Zuckerkandl consist of chromaffin cells that produce, store, and secrete catecholamines. In humans, the adrenal medulla is known to function throughout postnatal life, while the organs of Zuckerkandl degenerate by 2–3 years of postnatal life. Although the history of investigation of chromaffin cells goes back more than a century, little is known about the interaction of the adrenal glands and organs of Zuckerkandl in human fetal development. In the current study, we attempted to compare these two organs using serial sectioning, routine histological staining, and immunohistochemical reactions in human embryos, prefetuses, and fetuses from 8 to 26 gestational weeks. In our study, we used antibodies for tyrosine hydroxylase, dopamine beta-hydroxylase, and phenylethanolamine N-methyltransferase, which are enzymes of catecholamine synthesis, β-III tubulin, and S100. We found two morphological cell types (large and small) in the developing ganglia, organs of Zuckerkandl, and adrenal medulla and two migration patterns of large cells and small cells from the developing paraganglia to the adrenal anlage. We determined the immunohistochemical characteristics of these migrating cells. We also determined that 12 gestational weeks was the age of the first appearance of phenylethanolamine N-methyltransferase reactivity in developing chromaffin cells, which is important data in the light of the controversial glucocorticoid theory of phenylethanolamine N-methyltransferase induction in humans.
Thirty-year changes in burden for refraction disorders in China, Japan, Korea and Singapore: a jointly prevention perspective analysis
Authors: Mao Xiuyu , Jia Wenchang , Ji Shunmei , Wu Lei , Chen Binghong , Li Xiaopan 
Published: September 2024

Abstract

Background
Refractive disorders are the primary causes of visual impairment; their impact and prevalence vary greatly throughout age groups and geographical locations. This study analyzes trends in the burden of refractive disorders from 1990 to 2021 and projects future trends to 2050, focusing on five Asian regions and different socio-demographic index (SDI) levels.
Methods
Data on the prevalence and YLDs of refractive disorders were obtained from the Global Burden of Disease Study 2021. Age-standardised rates were calculated for regions with different SDI levels and five Asian countries or regions including China (mainland), Taiwan (province of China), Japan, Republic of Korea, and Singapore. Trends were analyzed using jointpoint regression, and projections were made to 2050.
Results
From 1990 to 2021, the global age-standardised prevalence rate (ASPR) of refractive disorders decreased by 6.5%. The most significant declines were observed in low and low-middle SDI regions (11.8% and 20%, respectively). Among the Asian regions, Taiwan (province of China) showed the greatest decrease in both ASPR (10.1%) and age-standardized YLDs (ASYLDs) (15.2%). Projections indicate that the prevalence and impact of refractive disorders in Japan and Taiwan are expected to surpass those in mainland China by the 2030s.
Conclusion
The burden of refractive disorders varies considerably across regions and age groups, with socioeconomic factors playing a crucial role. Targeted interventions and public health initiatives are needed to address this growing concern, particularly in aging populations and regions with limited access to eye care services.
Improved catalytic stability of immobilized Candida antarctic lipase B on macroporous resin with organic polymer coating for biodiesel production
Authors: Liu Jiale , Zhao Shufan , Wei Wan , Yu Shupeng , Wang Zhao , Zheng Jianyong 
Published: September 2024

Abstract

Lipase is one of the most widely studied and applied biocatalysts. Due to the high enzyme leakage rate of the immobilization method of physical adsorption, we propose a new lipase immobilization method, which based on the combination of macroporous resin adsorption and organic polymer coating. The immobilized Candida antarctic lipase B (CALB@resin-CAB) was prepared by combining the macroporous resin adsorption with cellulose acetate butyrate coating, and its structure was characterized by various analytic methods. Immobilized lipase was applied for biodiesel production using acidified palm oil as the starting material, the conversion rate achieved as high as 98.5% in two steps. Furthermore, immobilized lipase displayed satisfactory stability and reusability in biodiesel production. When the aforementioned reaction was carried out in a continuous flow packed-bed system, the yield of biodiesel was 94.8% and space-time yield was 2.88 g/(mL∙h). CALB@resin-CAB showed high catalytic activity and stability, which has good potential for industrial application in the field of oil processing.
Artificial Intelligence Driven Integrated Wireless Sensor Network, Industrial Ethernet, and Non-Orthogonal Multiple Access for Secure Nuclear Power Plants
Authors: Aboshosha Ashraf 
Published: September 2024

Abstract

Wireless Sensor Networks (WSNs) have recently garnered attention for various applications in Nuclear Power Plants (NPPs), such as radiation monitoring, data acquisition, instrumentation, control, and fault diagnosis. This study suggests an integrated solution for NPP's WSN by combining WSN, Industrial Ethernet (IE), and Non-Orthogonal Multiple Access (NOMA) to enhance performance, prolong lifespan, and improve security. It also incorporates Artificial Intelligence (AI)-driven decision making to speed up routing of the NPP's WSN in both indoor and outdoor environments. This research work proposes the development of an international radiation monitoring network for robust international nuclear Defense in Depth (DiD). Evaluation with various simulated WSNs has shown the viability of the proposed approach, effectively monitoring data even in scenarios with similar response patterns across multiple process variables.
Stage-based Neural Network for Reflow Profile Prediction and Reflow Recipe Optimization for Quality and Energy Saving
Authors: Zhang Zhenxuan , Li Yuanyuan , Yoon Sangwon , Won Daehan 
Published: September 2024

Abstract

During the reflow process, solder joints are formed on the boards with the placed components, so the temperature settings in the reflow oven chamber are vital to the quality of the PCB. Inappropriate profiles cause various defects such as cracks, bridging, delamination, etc. Solder paste manufacturers have generally provided the ideal thermal profile (i.e., target profile), and PCB manufacturers have attempted to meet the given profile by fine-tuning the oven’s recipe. The conventional method tunes the recipe to gather thermal data with a thermal measurement device. It adjusts the profile, which relies on the trial-and-error method which takes much time and effort. This paper proposes (1) a recipe initialization method for determining the initial recipe for collecting training data, (2) a stage-based (ramp, soak, and reflow) input data segmentation method for data preprocessing, (3) a backpropagation neural network, (BPNN) model for predicting the required zone temperature to reduce the gap between the actual processing profile and the target profile, (4) a mixed-integer linear programming (MILP) algorithm for generates the optimal recipe to minimize the temperature settings. This paper aims to enable non-contact prediction of required air temperature from one experiment. The MILP optimization model utilized the constraints of the upper and lower bounds obtained from the prediction result. The model has been cross-validated with different initial recipes and different target profiles. As a result, within 10 minutes of starting the experiment, the generated optimal recipe improved the fitness to the targeted profile by 4.2%, which resulted in 99% and, in the meanwhile, lowered the energy cost by 23%.
Reaserch of the surface residual stress of TC4 titanium alloy under longitudinal-torsional ultrasonic grinding and nanofluid minimum quantity lubrication
Authors: Yan Yanyan , Zhang Qipeng , Ma Qianli , Yuan Dengke 
Published: September 2024

Abstract

The machining difficulty of TC4 titanium alloy is higher than that of other metal alloys because of its poor thermal conductivity, high chemical reactivity and so on. Under this background, a system of longitudinal-torsional ultrasonic grinding and nanofluid minimum quantity lubrication (LTUG&NMQL) was established to achieve the high-quality machining of titanium alloy, and its special machining mechanism is firstly analyzed, then the surface residual stress (SRS) model under LTUG&NMQL was built. The theoretical analysis shows that the total residual stress is related to the grinding arc length of single abrasive grain in longitudinal-torsional ultrasonic grinding (lc), the average contact area (sm), the friction coefficient (µ) and the heat flux density of workpiece (qw), especially, under LTUG&NMQL condition, lc is changed by ultrasonic vibration, and sm, µ and qw are altered by nanofluid minimum quantity lubrication. Subsequently, the SRS values are different from those of common grinding. Finally, the grinding experiments were carried out to investigate the influences of LTUG&NMQL on the SRC of titanium alloy, and the experimental results showed that the surface compressive residual stress of titanium alloy under LTUG&NMQL was higher than that under common grinding and longitudinal-torsional ultrasonic grinding when the same machining parameters were used, and it increased with the flow rates of nanofluids and the ultrasonic amplitudes, which showed that LTUG&NMQL may improve the service performance of the parts. This study provides a theoretical foundation and technical support for the high-performance machining of TC4 titanium alloy.
Evaluation criteria and dehydration method for EPB shield spoil in sandy gravel– mudstone composite stratum
Authors: Zhao Dongping , Wang Feng , Peng Yuelei , Tang Weichao , Xiao Li , Zhang Wei 
Published: September 2024

Abstract

Shield tunnels in composite strata of mudstone and pebble produce a large amount of high-water-content spoil during excavation using earth pressure balance machines. This spoil not only has high transportation costs but also poses environmental pollution. We evaluated the moisture content, liquid and plastic limits of the moisture content, and permeability coefficient of the shield slag in the shield tunnel project of the first phase of the Chengdu Metro Line 30. Shield spoil dehydration tests were performed in gravel–mudstone composite strata, and a spoil dehydration evaluation method using slump and fluidity as the indicators was proposed. The results of the self-weight dehydration test showed that the moisture content of the spoil was reduced by approximately 7% after 24 h and the dehydration effect on the spoil was poor. The results of a vacuum–electroosmotic dehydration orthogonal test showed that by controlling parameters such as voltage and electrode spacing, the moisture content of the spoil can be reduced to a value close to the liquid-limit moisture content. The fluidity and slump of the spoil after dehydration meet the requisite standards, indicating the potential for market application of this method.
Coal permeability evolution under coupled mining disturbance and gas extraction conditions: an experimental study
Authors: Zhang Lei , Kan Zi-Hao , Liu Xinyuan , Wang Chen , Hao Dingyi , Ye Zhiwei 
Published: September 2024

Abstract

A simplified stress path was designed based on decompression mining to explore coal seam permeability variation during stress relief gas extraction in protective layers. This involved axial, confining, and pore stress to simulate coal seamstress during mining and pore pressure during gas extraction. Experiments were conducted on intact and fractured coal samples from Huainan using gas flow and displacement testing equipment. Key findings include: The first unloading cycle significantly impacted fracture volume, with vertically fractured coal showing the greatest variation, followed by horizontally fractured and intact samples, with reductions of 29, 23, 21, and 20%, respectively. Irreversible permeability loss rate is directly proportional to porosity. Both intact and fractured samples showed a porosity decrease followed by an increase, with the third loading/unloading cycle having the greatest impact. As pore pressure decreases, its influence on permeability is greater in fractured samples than in intact samples. The correlation between pore pressure and permeability is stronger in fractured samples. With the increased number of cycles, intact samples' stress sensitivity to pore pressure increases, while that of fractured samples decreases. After three cycles, new fractures develop in both intact and fractured samples, enhancing gas extraction efficiency.
Beyond boundaries - genetic implications of urbanisation and isolation in eastern grey kangaroos (Macropus giganteus)
Authors: Brunton Elizabeth Ann , Levengood Alexis L , Brunton Aaron James , Clarke Neil , Coulson Graeme , Wimpenny Claire , Conroy Gabriel 
Published: September 2024

Abstract

Understanding the long-term influences that urbanisation and associated habitat fragmentation can have on wildlife species is increasingly important for biodiversity conservation. Habitat fragmentation and subsequent isolation of previously connected populations can lead to smaller populations that are more likely to experience loss of genetic diversity. However, there is still a paucity of research directed at the genetic implications for species exposed to urbanisation. Eastern grey kangaroos (Macropus giganteus) are large macropodid marsupials that occur across a vast range on the eastern coast of Australia, inhabiting landscapes often subject to processes of habitat fragmentation and urbanisation. Using single nucleotide polymorphism (SNP) data obtained from scat and tissue samples, we compared genetic characteristics of urban and non-urban kangaroo populations across three study regions. We assessed the influence of habitat isolation characteristics on genetic diversity and relatedness of kangaroos at 18 study sites within these regions. On average, urban populations did not exhibit lower genetic diversity than those in less built-up areas (p > 0.05, Urban mean HO = 0.196, Non-urban mean HO = 0.188), but populations that were fully isolated by physical structures (i.e., roads, buildings and fences) had lower genetic diversity and higher rates of inbreeding. Significant regional differences were also found in the kangaroo population genetic characteristics. This study provides important insights into how attributes of complex and expanding urban landscapes can impact the genetics of large terrestrial mammals and has implications for guiding effective urban planning and management practices at an appropriate spatial scale.
Precision Dosing Cylinder Gluing Operations Using Model Predictive Control-Enhanced Reinforcement Learning
Authors: Wu Liangshun , Zhu Huibiao , Liu Qinyuan , Ying Rendong , Zhang Bin , Qu Junsuo 
Published: September 2024

Abstract

This paper presents the development of an advanced servo system for gluing operations, which integrates a dosing cylinder enhanced by reinforcement learning algorithms to optimize efficiency and accuracy. The system consists of an upper computer, a programmable logic controller (PLC), a main controller (featuring a core board and an IO board), and a dosing cylinder equipped with a servo motor and a glue gun. A comprehensive system model was developed by 1 analyzing the interactions among mechanical, hydraulic, and servo motor subsystems. The implementation of an enhanced Deep Deterministic Policy Gradient (DDPG) reinforcement learning algorithm, augmented with Model Predictive Control (MPC), enables precise control over voltage inputs and glue gun temperature adjustments. The MPC component predicts future states of the system based on the current state and actions, refining the action selection process by considering the long-term effects of actions. Rigorous simulation testing of the enhanced DDPG algorithm, alongside other algorithms, in configurations involving single and dual cylinder setups, validates its effectiveness, demonstrating significant enhancements in the automated control of the gluing process. The real-world experimental results indicate high positioning accuracy, consistent glue dispensing , and overall stability, making this system suitable for industrial applications requiring precise and reliable gluing.
Rising Tides, Sinking Crops: Assessing the Impact of Extreme Sea Level Rise on Coastal Agriculture in Europe and North Africa
Authors: Martellozzo Federico , Vaglie Matteo Dalle , Randelli Filippo , Falaguasta Carolina , Tongeren Pim van , Negacz Katarzyna , Bruning Bas , Vellinga Pier 
Published: September 2024

Abstract

The accelerating impact of climate change on sea level rise (SLR) has intensified the examination of its effects on coastal regions. This study focuses on Extreme Sea Level Rise (ESLR) and its potential impacts on Europe and North Africa up to 2050, in particular for agriculture. Utilising Joint Research Centre (JRC) Global Extreme Sea Level projections and Copernicus GLO30 Digital Terrain Models (DTM), we mapped areas vulnerable to ESLR under Representative Concentration Pathway (RCP) scenarios 4.5 and 8.5. Through a topological approach, we generated spatially explicit maps of at-risk regions in the Mediterranean basin and northern coastal EU, overlaying them with data from FAO on crop locations, yields, and values (GAEZ). This method allowed us to estimate the magnitude of ESLR's impact on local agricultural systems. Findings reveal that ESLR can severely affect coastal agriculture, suggesting significant potential agricultural losses, impacting food security and economic stability. This research underscores the urgent need for adaptive strategies, including saline agriculture, to mitigate ESLR impacts.
The evolution of long-range hunting with stone-tipped weapons during the Afrotropic Middle Stone Age: A testable framework based on tip cross-sectional area
Authors: Sahle Yonatan , Lombard Marlize 
Published: September 2024

Abstract

In the Afrotropic biogeographic realm, with its diverse and high-density mammal population, early humans may have been hunting with stone-tipped weapons since ~ 500 000 years ago. Being able to hunt effectively from a distance has several important adaptive advantages. Yet, until now, African long-range javelin hunting remained unexplored as intermediate between short/medium-range, hand-delivered and long-range, mechanically projected weapons. Insights gained from a new Afrotropic comparative dataset with 950 weapon tips of known use – including several javelin types – provide a contextually appropriate middle-range tool for assessing the probable effective hunting ranges of Middle Stone Age points. We use a novel application of the ballistically relevant tip cross-sectional area (TCSA) statistic to define contact, short-, medium-, long- and maximum-range hunting and discuss the adaptive advantages for each. The approach is applied to suggest developments and variations in the best-fit hunting ranges of 5597 stone points from 62 Middle Stone Age Afrotropic assemblages. By aligning our results with the Marine Isotope Stage (MIS) record we hypothesize that long-range hunting with stone-tipped weapons at ~ 20–30 m was probably not practiced by ≥ MIS 8, and that experimentation with long-range javelins – similar to those used by contemporary Ethiopian hunters – over this distance may have started during MIS 6, becoming part of the everyday Afrotropic hunting arsenal by the end of MIS 5.