bluuebunny/crossref_metadata_2025_split huggingface dataset:
NSE protein detection in a microfluidic channel integrated an electrochemical biosensor
Authors: Nhu Chi Tran , Do Quang Loc , Jen Chun-Ping , Duc Trinh Chu , Bui Tung Thanh , Vu Ngoc Trung 
Published: December 2024

Abstract
This study proposed a microfluidic chip for the detection and quantification of NSE proteins, aimed at developing a rapid point-of-care testing system for early lung cancer diagnosis. The proposed chip structure integrated an electrochemical biosensor within a straight PDMS microchannel, enabling a significant reduction in sample volume. Additionally, a method was developed to deposit silver and silver chloride layers onto the reference electrode. Following fabrication, the working electrode was modified to immobilize NSE antibodies on its surface, facilitating specific protein detection. Electrochemical impedance spectroscopy (EIS) measurements were utilized to investigate the alterations in surface impedance resulting from the specific binding of anti-NSE on the electrode surface across varying concentrations of NSE, ranging from 10 ng ml−1 to 1000 ng ml−1. The experimental results demonstrated a direct correlation between NSE concentration and surface impedance. Specifically, the charge transfer resistance exhibited an increase from 24.54 MΩ to 89.18 MΩ as the NSE concentration varied from 10 ng ml−1 to 1000 ng ml−1. Moreover, the concentration of NSE can be quantified by relating it to the charge transfer resistance, which follows a logarithmic equation. The limit of detection (LoD) of the chip was evaluated to be approximately 1.005 ng ml−1. The proposed chip lays a crucial foundation for developing a Lab-on-a-chip platform dedicated to diagnosing NSE testing and lung cancer.
Stimuli-responsive actuators in water environment: a review and future research agenda
Authors: Zhao Xin , Tang Gangqiang , Mei Dong , Zhao Chun , Li Lijie , Wang Yanjie 
Published: December 2024

Abstract
Flexible underwater vehicles with high maneuverability, high efficiency, high speed, and low disturbance have shown great application potential and research significance in underwater engineering, ocean exploration, scientific investigation and other fields. The research and development of flexible stimulus-responsive actuators is key to the development of high-performance underwater vehicles. At present, the main drive methods for underwater devices include electric drive, magnetic drive, light drive, thermal drive, and chemical drive. In this work, the research progress of stimuli-responsive actuators in water environment is reviewed from the stimuli-responsive patterns, functional design, fabrication methods, and applications in water environment. Firstly, the actuation principles and characteristics of electro-responsive, magnetic-responsive, photo-responsive, thermo-responsive actuators, and chemically responsive actuators are reviewed. Subsequently, several design requirements for the desired flexible actuators are introduced. After that, the common fabrication methods are summarized. The typical application of the stimuli-responsive actuator in the water environment is further discussed in combination with the multi-stimuli-responsive characteristics. Finally, the challenges faced by the application of stimuli-responsive actuators in the water environment are analyzed, and the corresponding viewpoints are presented. This review offers guidance for designing and preparing stimulus-responsive actuators and outlines directions for further development in fields such as ocean energy exploration and surface reconnaissance.
RLGS-YOLO: an improved algorithm for metro station passenger detection based on YOLOv8
Authors: Qin YaoDong , Li XianWang , He Deqiang , Zhou Yucun , Li Liangjie 
Published: December 2024

Abstract
Passenger detection is a key component of guaranteeing the safe operation of the subway. Nevertheless, the issue of varying target sizes across subway scenarios impedes passenger detection. Additionally, there is the issue of occlusion overlap between passengers. To resolve these concerns, an improved model based on YOLOv8n is proposed. It consists of Reduced Channel Spatial Object Attention (RCSOSA) module, Large Separable Kernel Attention (LSK) module, Group Shuffle Convolution (GSConv) convolution, and other modules such as Small Detect Head (S-detect), and named RLGS-YOLO. Designed to facilitate the deployment of a variety of platforms, S-detect lightweight detection head module minimizes the number of parameters and the amount of model computation. A re-parameterized structure based on Re-param Visual Geometry Group (RepVGG) is proposed to address the issue of mutual occlusion between passengers. This structure is achieved by integrating RCSOSA module, which substantially improves the information exchange between various channels. The dynamic sensory field module of LSK has been incorporated. It improved the issue of model misdetection by wholeheartedly incorporating the background information. The model’s sophistication is decreased by integrating GSConv lightweight convolution. The experimental findings indicate that in comparison to YOLOv8n. In the passenger data set of Nanning Metro Line 1, RLGS-YOLO indicates superior performance. The Mean Average Precision (mAP) improved by 2.2%. RLGS-YOLO, on the other hand, attains superior performance on the public dataset VOC2007. This contains a 1.1% increase in mAP, a 13.79% increase in Frames Per Second (FPS), and a 0.5 G Floating Point Operations (FLOP) reduction in computation. In comparison to other prominent detection models, RLGS-YOLO also exhibits superior performance. The improved RLGS-YOLO model provides a precise and efficient solution for passenger detection methods.
Incorporating edge convolution and correlative self-attention into graph neural network for material properties prediction
Authors: Yang Zexi , Yu Qi , Zhan Yapeng , Liu Jiying 
Published: December 2024

Abstract
The prediction of material properties is a crucial challenge in the design of new materials. Traditional methods based on either trial-and-error experiments or large-scale density functional theory calculations are known to possess various limitations. Although recent machine learning (ML) methods have shed light on resolving this problem efficiently, the majority of ML models consider only the local atomic environment while ignoring the nonlocal correlations between atoms. Indeed, even the periodic patterns of the crystal structures are not seriously considered. Consequently, these issues lead to an insufficient understanding of the feature information of atoms and bonds. In this study, we propose a crystal graph convolutional neural network based on edge convolution (EdgeConv) and correlative self-attention, namely, EdgeConv-Graph attention neural network (GANN). This network is able to efficiently extract atomic and bonding feature information, while effectively learning the importance weights of all neighbouring nodes. Numerical experiments predicting the electronic structural properties of metal–organic frameworks show that the developed model achieves state-of-the-art performance. Moreover, the proposed model was applied to predict the heat capacity and thermal decomposition temperature of material, demonstrating the ability of this method to effectively generalise multiscale prediction tasks.
Closed-form interpretation of neural network classifiers with symbolic gradients
Authors: Wetzel Sebastian J 
Published: December 2024

Abstract
I introduce a unified framework for finding a closed-form interpretation of any single neuron in an artificial neural network. Using this framework I demonstrate how to interpret neural network classifiers to reveal closed-form expressions of the concepts encoded in their decision boundaries. In contrast to neural network-based regression, for classification, it is in general impossible to express the neural network in the form of a symbolic equation even if the neural network itself bases its classification on a quantity that can be written as a closed-form equation. The interpretation framework is based on embedding trained neural networks into an equivalence class of functions that encode the same concept. I interpret these neural networks by finding an intersection between the equivalence class and human-readable equations defined by a symbolic search space. The approach is not limited to classifiers or full neural networks and can be applied to arbitrary neurons in hidden layers or latent spaces.
Accounting for transience in the baseline climate state changes the surface climate response attributed to stratospheric aerosol injection
Authors: Duffey Alistair , Irvine Peter J 
Published: December 2024

Abstract
Stratospheric aerosol injection (SAI) is a proposed means of climate intervention that could halt global temperature rise, though it would imperfectly offset climate change. To estimate this imperfection, it is common to compare the simulated climate under SAI against that of a baseline state at the same global mean temperature without SAI. Here, we combine a recent set of SAI simulations (ARISE-SAI-1.5) in the earth system model UKESM1, with simulations of idealised abrupt and transient warming scenarios, to assess the impact of transient warming through this baseline state on surface climate changes attributed to SAI. We quantify the effect of temperature stabilisation as the expected change in surface climate between a climate state under warming and one in quasi-equilibrium at the same global mean temperature. We estimate that accounting for temperature stabilisation eliminates the land-sea warming ratio change attributed to SAI. However, relative to the hypothetical scenario with lower CO2 concentrations that would achieve a stabilised climate at the same temperature, SAI produces a 69% larger reduction in global precipitation. Accounting for stabilisation can also meaningfully change the spatial pattern of surface temperature response attributable to SAI. We repeat our analysis for the GeoMIP G6sulfur scenario, to show that effects qualitatively consistent with these findings are seen when comparing the SAI state against the faster and slower warming baselines of the SSP5-8.5 and SSP2-4.5 scenarios. The changes in climate state attributable to temperature stabilisation are generally small compared to changes due to warming since pre-industrial. However, these differences can be significant in the context of assessing residual changes under SAI because these residuals are themselves roughly an order of magnitude smaller than the effects of warming. Our findings have implications for the design and assessment of future SAI simulations, and for the attribution of changes in surface climate to SAI.
Leveraging built marine structures to benefit and minimize impacts on natural habitats
Authors: Paxton Avery B , Runde Brendan J , Smith Carter S , Lester Sarah E , Vozzo Maria L , Saunders Megan I , Steward D'amy N , Lemoine Hayley R , Valdez Stephanie R , Gittman Rachel K , Narayan Siddharth , Allgeier Jacob , Morris Rebecca L , Nowacek Douglas P , Seaman William , Halpin Patrick N , Angelini Christine , Silliman Brian R 
Published: December 2024

Abstract
Many natural marine habitats are decreasing in extent despite global conservation and restoration efforts. In contrast, built marine structures, such as hardened shorelines, offshore energy and aquaculture infrastructure, and artificial reefs, are increasing in extent—and, in some locations, represent over 80% of nearshore, structured habitat. When introduced into the seascape, built marine structures inevitably interact with natural habitats, but these structures are not typically designed to support natural systems. This approach often results in overall harm to natural systems, further impeding marine conservation goals. However, there is growing recognition within the ocean management and engineering community that built marine structures can be strategically designed to minimize their negative impacts and potentially support ecosystems and associated biota. We synthesize the best available science and provide bright spot examples of how leveraging built marine structures to mimic or facilitate natural habitats can help recover biodiversity, augment ecosystem services, and rehabilitate degraded habitats, providing positive outcomes for people and nature in a changing climate. Despite these bright spots, we caution that built structures typically have overall negative environmental consequences for natural habitats and should not be used in lieu of conventional habitat restoration or conservation or to justify the destruction of natural habitats.
Integrative functional screen of genomic loci uncovers CCND2 and its genetic regulatory mechanism in colorectal cancer development
Authors: Li Bin , Wu Mei , Geng Hui , Li Yan , Chen Zhirui , Lu Zequn , Chen Xu , Wang Qiuhong , Song Shuxin , Li Xiangpan , Zhu Xu , Wei Yongchang , Zhu Ying , Miao Xiaoping , Tian Jianbo , Liu Jiuyang , Huang Chaoqun , Yang Xiaojun 
Published: December 2024

Abstract
Although genome-wide association studies have identified dozens of loci associated with colorectal cancer (CRC) susceptibility, the causal genes or risk variants within these loci and their biological functions often remain elusive. Recently, the genomic locus 12p13.32, with the tag single-nucleotide polymorphism rs10774214, was identified as a crucial CRC risk locus in Asian populations. However, the functional mechanism of this region has not been fully elucidated. Here, we applied a high-throughput RNA interference approach in CRC cell lines to interrogate the function of genes in this genomic region. Multiple genes were found to affect cell functions, with CCND2 having the most significant effect as an oncogene. Moreover, overexpressed CCND2 could promote CRC cell proliferation. Subsequently, by integrating a fine-mapping analysis and multi-ancestry large-scale population cohorts consisting of 14 358 CRC cases and 34 251 healthy controls, we identified a regulatory variant rs4477507-T that contributed to an increased CRC risk in populations from China (odds ratio = 1.16, 95% confidence interval = 1.11–1.22, P = 4.45 × 10−10) and Europe (odds ratio = 1.17, 95% confidence interval = 1.12–1.21, P = 1.65 × 10−14). Functional characterization of the variant demonstrated that it could act as an allele-specific enhancer to distally facilitate the expression of CCND2 mediated by the transcription factor TEAD4. Overall, our study underscores the essential role of CCND2 in CRC development and delineates its regulatory mechanism mediated by rs4477507, establishing an epidemiological and biological link between genetic variation and CRC pathogenesis.
Global Space Governance of Remote Sensing and the Needs of Developing States
Authors: Mahmoudi S Hadi , Moradinasab Sima 
Published: December 2024

Abstract
Global space governance, having its unique features, refers to the complex of soft law and hard law rules, regulating the outer space activities, together with institutions involved in the space realm. Global space governance includes different space activities, including remote sensing. Remote sensing may play a vital role in the improvement of the socio-economic status of developing States. Given the inequality between developing States and developed ones on the one hand and due to the efforts made by the space law instruments to narrowing the gap between these two groups of States on the other hand, the approach of developing States to the role of remote sensing in the global space governance is to be taken into consideration. For this purpose, choosing the analytical research method, the main question is to what extent and how global space governance of remote sensing can serve the needs of developing States. In this respect, this article aims to mainly examine soft legal frameworks and mechanisms forming global space governance including the 2007 Space Debris Mitigation Guidelines and the 2018 Guidelines for the Long-term Sustainability of Outer Space Activities together with remote sensing trans-governmental networks.
Maritime Ambitions: China’s Emerging Great Power Identity and Its Strategies in BBNJ Agreement Negotiations
Authors: Xia Nan 
Published: December 2024

Abstract
This article examines China’s strategic maneuvers within the Biodiversity Beyond National Jurisdiction (BBNJ) agreement negotiations, highlighting its role as an emerging great power in shaping international maritime law and governance. The BBNJ initiative, crucial for the conservation and sustainable use of marine biodiversity in areas beyond national jurisdiction, presents an arena where China’s diplomatic, strategic, and legal tactics converge to enhance its influence on the global stage. Through a detailed analysis of the negotiation phases and China’s interactions with other states, this study explores how China, while operating under its status as a developing country—a stance recognized globally—effectively wields its ascending power to shape negotiation outcomes that serve its strategic national interests. China’s approach in the BBNJ agreement discussions demonstrates a sophisticated integration of traditional values, strategic alliances, and selective engagement with international norms, ensuring that new legal frameworks do not undermine existing agreements or its maritime ambitions. This article sheds light on China’s influence in shaping the BBNJ agreement while offering insights into the broader implications of its strategies for other emerging powers in international environmental governance. Although advancing national interests is a common goal for all nations in multilateral negotiations, this article emphasizes the distinctive strategies China employs—integrating traditional values, forging strategic alliances, and adopting selective engagement—to effectively shape outcomes and safeguard its strategic objectives.
Analysis and modeling of rumor spreading in social networks using status transmission mechanisms
Authors: Duan Xuan , Sun PengFei , Ma Ning 
Published: December 2024

Abstract
Normally, there is no limit for information sharing in social networks and this leads to the rapid propagation of information regardless of their validity. This process has resulted in a significant negative impact on social interactions, because the propagation of fake information may lead to the spread of harmful rumors. Hence, the importance of analyzing the rules of rumor spreading in social platforms is understood as a hot issue by the research society. Most of the rumor spreading models have been developed based on classical epidemic transmission models such as SIR (Susceptible-Infected-Removed). However, these models cannot properly apply the importance of topology structure and user differences in rumor propagation. To address this problem, this paper develops the ILSHR (Ignorant–Lurker–Spreader–Hibernator–Removal) rumor spreading model, which is designed based on a state transition mechanism considering the nodes degree. The ILSHR model overcomes the coarse-grained problem in describing rumor propagation by considering the role of different users. We carried out many experiments on real social networks to prove the rationality of the ILSHR model. Numerical simulations show that the accuracy of our model has achieved improvements compared to existing works.
Prognostic impact of left- and right-atrial strain in patients undergoing transcatheter aortic valve replacement
Authors: Stolz Lukas , Schmid Simon , Steffen Julius , Doldi Philipp M , Weckbach Ludwig T , Stocker Thomas J , Löw Kornelia , Fröhlich Carolin , Fischer Julius , Haum Magda , Theiss Hans D , Stark Konstantin , Rizas Konstantinos , Peterss Sven , Näbauer Michael , Hagl Christian , Massberg Steffen , Hausleiter Jörg , Deseive Simon 
Published: December 2024

Abstract

Aims
Data on the prognostic value of left- and right-atrial strain after transcatheter aortic valve replacement (TAVR) for severe aortic stenosis (AS) are limited. Aim of this study was to evaluate outcomes of patients undergoing TAVR stratified by left- and right-atrial strain.

Methods and results
Using data from a high-volume academic centre, left- and right-atrial reservoir strain (LASr and RASr) was obtained in patients who underwent TAVR for severe AS from 2018 until 2021. Patients were stratified into groups with normal atrial function (LASr and RASr normal), uni-atrial strain impairment (LASr or RASr impaired), and bi-atrial strain impairment (LASr and RASr impaired). Endpoints were 3 year survival, symptomatic improvement as assessed by New York Heart Association functional class (NYHA class) as well as technical and device success defined by the Valve Academic Research Consortium composite endpoints. The study included 1888 patients at a mean age of 81.0 ± 7.8 years (44.3% women). Mean LASr and RASr were 16.5 ± 9.4% and 21.6 ± 12.4%, respectively. Optimized cut-offs for mortality prediction were 15.5% for LASr and 15.0% for RASr. LASr and RASr were normal in 751 patients (39.8%). Impairment of either right-atrium (RA) or left-atrium (LA) strain was observed in 633 patients (33.5%) and 504 patients (26.7%) presented with reduced LA and RA strain. While impairment of either LASr or RASr was associated with a 1.7-fold increased risk of 3 year all-cause mortality after adjustment for multiple confounders (95% confidence interval [CI] 1.2–2.5, P = 0.005), bi-atrial strain impairment exhibited an even higher 3 year mortality risk (Hazard ratio 2.5, 95% CI 1.7–3.6, P &lt; 0.001).

Conclusion
Pre-procedural assessment of atrial strain is associated with increased 3 year mortality and might facilitate outcome prediction and patient selection in patients undergoing TAVR for severe AS.
Occupational Therapists’ Perspectives on Community Implementation of Interventions Unfamiliar to Older Adults
Authors: Mao Hui-Fen , Tsai Athena Yi-Jung , Yeh Hsin-Chun , Chang Ling-Hui 
Published: December 2024

Abstract

Background and Objectives
There is an increasing push for broad implementation of evidence-based interventions (EBIs) targeting older adults. Successful delivery of EBIs in communities requires therapists to adhere to protocols and to be responsive to contextual factors. This study explored the real-world implementation of an EBI, the Multiple-component Cognitive Intervention using Simulated Everyday Tasks (MCI-SET) in Taiwan from therapists’ perspectives on fidelity, challenges, and strategies for program delivery.

Research Design and Methods
We used a convergent mixed-methods design. Quantitative data were collected from the 13-item Perceived Fidelity Questionnaire (PFQ), assessing the perceived importance, proficiency, and adherence to the essential skills of MCI-SET. Qualitative data were collected via 2 World Café discussions on implementation challenges and strategies, which were recorded, transcribed verbatim, and analyzed using thematic analysis. Quantitative and qualitative findings were then compared and integrated to enrich the interpretation.

Results
47 occupational therapists completed the PFQ. They rated community-oriented skills as more important, demonstrated greater proficiency, and achieved higher adherence. Qualitative analysis revealed that therapists need to increase and sustain participation by strategically introducing the program, adapting the intervention protocol to make it engaging, relevant to everyday issues, and tailored to local needs, and building rapport. Both quantitative and qualitative findings highlighted the importance of community engagement skills and the adaptability of intervention to implementation and sustainability in communities.

Discussion and Implications
Real-world scale-up of EBIs requires tailored adaptations responsive to community contexts, especially when initially introducing an intervention unfamiliar to the community. This emphasizes the need for a dynamic fidelity concept.