bluuebunny/crossref_metadata_2025_split huggingface dataset:
A framework to assess permafrost thaw threat for land transportation infrastructure in northern Canada
Authors: Fatolahzadeh Gheysari Ali , Maghoul Pooneh 
Published: March 2024

AbstractPrediction of permafrost stability is associated with challenges, such as data scarcity and climate uncertainties. Here we present a data-driven framework that predicts permafrost thaw threat based on present ground ice distributions and ground surface temperatures predicted via machine learning. The framework uses long short-term memory models, which account for the sequential nature of climate data, and predicts ground surface temperature based on several climate variables from reanalysis products and regional climate models. Permafrost thaw threat is then assessed for three cases in northern Canada: Hudson Bay Railway, Mackenzie Northern Railway, and Inuvik–Tuktoyaktuk Highway. The models predict ground surface warming in all studied areas under both moderate and extreme climate change scenarios. The results also suggest that all studied cases are already under threat, with the northern sections of the Hudson Bay Railway and Inuvik–Tuktoyaktuk Highway facing an increasing threat by the end of the century.
Increasing coastal exposure to extreme wave events in the Alaskan Arctic as the open water season expands
Authors: Henke Martin , Miesse Tyler , de Lima André de Souza , Ferreira Celso M. , Ravens Thomas M. 
Published: March 2024

AbstractDeclining Arctic sea ice over recent decades has been linked to growth in coastal hazards affecting the Alaskan Arctic. In this study, climate model projections of sea ice are utilized in the simulation of an extratropical cyclone to quantify how future changes in seasonal ice coverage could affect coastal waves caused by this extreme event. All future scenarios and decades show an increase in coastal wave heights, demonstrating how an extended season of open water in the Chukchi and Beaufort Seas could expose Alaskan Arctic shorelines to wave hazards resulting from such a storm event for an additional winter month by 2050 and up to three additional months by 2070 depending on climate pathway. Additionally, for the Beaufort coastal region, future scenarios agree that a coastal wave saturation limit is reached during the sea ice minimum, where historically sea ice would provide a degree of protection throughout the year.
ROSIC: Enhancing secure and accessible robot control through open‐source instant messaging platforms
Authors: Sadeghian Rasoul , Shahin Shahrooz , Sareh Sina 
Published: March 2024

AbstractEnsuring secure communication and seamless accessibility remains a primary challenge in controlling robots remotely. The authors propose a novel approach that leverages open‐source instant messaging platforms to overcome the complexities and reduce costs associated with implementing a secure and user‐centred communication system for remote robot control named Robot Control System using Instant Communication (ROSIC). By leveraging features, such as real‐time messaging, group chats, end‐to‐end encryption and cross‐platform support inherent in the majority of instant messenger platforms, we have developed middleware that establishes a secure and efficient communication system over the Internet. By using instant messaging as the communication interface between users and robots, ROSIC caters to non‐technical users, making it easier for them to control robots. The architecture of ROSIC enables various scenarios for robot control, including one user controlling multiple robots, multiple users controlling one robot, multiple robots controlled by multiple users, and one user controlling one robot. Furthermore, ROSIC facilitates the interaction of multiple robots, enabling them to interoperate and function collaboratively as a swarm system by providing a unified communication platform that allows for seamless exchange of data and commands. Telegram was specifically chosen as the instant messaging platform by the authors due to its open‐source nature, robust encryption, compatibility across multiple platforms and interactive communication capabilities through channels and groups. Notably, the ROSIC is designed to communicate effectively with robot operating system (ROS)‐based robots to enhance our ability to control them remotely.
Prompt guidance query with cascaded constraint decoders for human–object interaction detection
Authors: Liu Sheng , Guo Bingnan , Zhang Feng , Chen Junhao , Chen Ruixiang 
Published: March 2024

AbstractHuman–object interaction (HOI) detection, which localises and recognises interactions between human and object, requires high‐level image and scene understanding. Recent methods for HOI detection typically utilise transformer‐based architecture to build unified future representation. However, these methods use random initial queries to predict interactive human–object pairs, leading to a lack of prior knowledge. Furthermore, most methods provide unified features to forecast interactions using conventional decoder structures, but they lack the ability to build efficient multi‐task representations. To address these problems, we propose a novel two‐stage HOI detector called PGCD, mainly consisting of prompt guidance query and cascaded constraint decoders. Firstly, the authors propose a novel prompt guidance query generation module (PGQ) to introduce the guidance‐semantic features. In PGQ, the authors build visual‐semantic transfer to obtain fuller semantic representations. In addition, a cascaded constraint decoder architecture (CD) with random masks is designed to build fine‐grained interaction features and improve the model's generalisation performance. Experimental results demonstrate that the authors’ proposed approach obtains significant performance on the two widely used benchmarks, that is, HICO‐DET and V‐COCO.
State of health estimation of individual batteries through incremental curve analysis under parameter uncertainty
Authors: Zhao Yue , Li Qian , Li Xiaohui , Zhang Ge , Shi Hang , Li Qinghua 
Published: March 2024

AbstractThe assessment of State of Health (SOH) plays a decisive role in diagnosing the health condition of Lithium‐Ion Batteries (LIBs). However, SOH estimation, particularly for individual battery cells, remains underexplored, especially under working conditions and aging patterns where battery parameters cannot be fully determined. This research conducted a comparative analysis of the parameter sensitivity among three methods and proposed a novel approach to estimate the SOH in large‐capacity batteries. The proposed method integrates multi‐feature extraction with artificial intelligence techniques. Specifically, various Health Index sets (HIs) reflecting Incremental Capacity morphological features are extracted from the charging curves of LIBs. Subsequently, a method is proposed to fuse these HIs using an artificial neural network to achieve precise SOH estimation. The effectiveness of the proposed method is validated through extensive long‐term degradation experiments on Lithium Cobalt Oxide batteries. The results confirm significant attributes of the method, including high estimation accuracy, reliability, and robustness against small‐scale inconsistencies.
Open‐set recognition of compound jamming signal based on multi‐task multi‐label learning
Authors: Xiao Yihan , Zhang Rui , Yu Xiangzhen , Jiang Yilin 
Published: March 2024

AbstractIn the increasingly intricate electromagnetic environment, the radar receiver may simultaneously encounter multiple intentional or unintentional jamming signals, which results in temporal and spectral overlap of received signals and forms a composite jamming signal. The nature and extent of interference contained in the received signal are often unknown, while they significantly affect the accuracy of radar detection. AnOpen‐Set Compound Jamming Signal Recognition Framework based on Multi‐Task Multi‐Label (MTML‐OCJR) is proposed. Based on the time–frequency characteristic of compound jamming signals, the proposed framework employs multi‐label classification to identify components of compound jamming signals while incorporating an unknown signal detection task into the classification process. Time–frequency image reconstruction combined with extreme value model estimation is used to detect unknown types of jamming signals, enabling simultaneous signal recognition and anomaly detection. The obtained results show that the proposed approach has superior recognition performance for composite jamming signals in closed‐set environments and high anomaly detection ability for unknown signals in open‐set environments. This method has the potential to significantly enhance the effectiveness and reliability of jamming systems in battlefield scenarios.
Adaptive soft threshold transformer for radar high‐resolution range profile target recognition
Authors: Chen Siyu , Huang Xiaohong , Xu Weibo 
Published: March 2024

AbstractRadar High‐Resolution Range Profile (HRRP) has great potential for target recognition because it can provide target structural information. Existing work commonly applies deep learning to extract deep features from HRRPs and achieve impressive recognition performance. However, most approaches are unable to distinguish between the target and non‐target regions in the feature extraction process and do not fully consider the impact of background noise, which is harmful to recognition, especially at low signal‐to‐noise ratios (SNR). To tackle these problems, the authors propose a radar HRRP target recognition framework termed Adaptive Soft Threshold Transformer (ASTT), which is composed of a patch embedding (PE) layer, ASTT blocks, and Discrete Wavelet Patch Merging (DWPM) layers. Given the limited semantic information of individual range cells, the PE layer integrates nearby isolated range cells into semantically explicit target structure patches. Thanks to its convolutional layer and attention mechanism, the ASTT blocks assign a weight to each patch to locate the target areas in the HRRP while capturing local features and constructing sequence correlations. Moreover, the ASTT block efficiently filters noise features in combination with a soft threshold function to further enhance the recognition performance at low SNR, where the threshold is adaptively determined. Utilising the reversibility of the discrete wavelet transform, the DWPM layer efficiently eliminates the loss of valuable information during the pooling process. Experiments based on simulated and measured datasets show that the proposed method has excellent target recognition performance, noise robustness, and small‐scale range shift robustness.
Exploring the Mechanisms of Action of Quercetin for the Treatment of Cervical High-Risk-Human Papilloma Virus Using Network Pharmacology and Molecular Docking
Authors: Wang Shanyun , Hong Huisi , Yuan Yiming , Yin Yinhao , Zeng Jianfeng , Xiao Jing 
Published: March 2024

Abstract
Objective Our objective was to investigate the therapeutic mechanism of quercetin in the management of cervical HR-HPV through the integration of network pharmacology and molecular docking techniques.
Methods The GeneCard database was utilized to analyze and identify potential therapeutic targets in HR-HPV. Subsequently, a protein–protein interaction (PPI) network was constructed by employing the String database. The visualization and construction of PPI networks were accomplished using Cytoscape. The R language was utilized to conduct Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses.
Results A total of 154 active constituents of quercetin were identified through screening. Additionally, 139 target genes associated with the effects of quercetin on cervical HR-HPV were predicted. PPI analyses revealed that threonine kinase Akt1, mitogen-activated protein kinase1, human IL-6 protein, signal transducer and activator of transcription 3, and epidermal growth factor receptor (EGFR) may serve as potential targets for quercetin in the treatment of cervical HR-HPV. Furthermore, GO and KEGG analyses demonstrated that quercetin is involved in various functional pathways, biological processes, molecular categories, including the Th17 signaling pathway, tumor necrotizing factor (TNF) signaling pathway, EGFR signaling pathway, PI3K-Akt signaling pathway, among others.
Conclusion Quercetin exhibits multifaceted characteristics, targeting multiple components, pathways, and targets, in the therapeutic intervention of HR-HPV, primarily by modulating inflammatory responses, oxidation reactions, and apoptotic processes.
The Research Progress of the Application of Bioinformatics in the Diagnosis and Treatment of Alzheimer's Disease
Authors: Yu Zhiyang , Wang Wenpan , Qiao Qiong , Sun Yiran , Xie Zhishen , Song Junying , Zhang Zhenqiang , Ma Huifen 
Published: March 2024

AbstractAlzheimer's disease (AD) is characterized by a complex pathogenesis, limited diagnostic methods, and a lack of effective therapeutic drugs in clinical settings, posing significant challenges in modern medical research. Bioinformatics offers new perspectives for identifying key pathological biomarkers of AD, analyzing differentially expressed genes in AD, screening for effective drug targets against AD, studying the mechanisms of AD pathogenesis, and discovering novel anti-AD drugs. However, data preprocessing and statistical analysis methods in bioinformatics research can significantly impact results, and there is a lack of consistency and coordination in analysis methods across platforms and laboratories in practical studies, making it difficult to compare data between studies. Therefore, it is crucial to establish standardized operating procedures and quality control protocols, improve the reproducibility of methods across platforms, and promote data comparison between studies.
Research Progress on the Treatment of Benign Prostatic Hyperplasia with Classical Prescriptions
Authors: Zhang Lin , Wang Yang , Liu Mingze , Wang Zhenliang 
Published: March 2024

AbstractThe main pathogenesis of benign prostatic hyperplasia (BPH) includes deficiency of healthy qi, blood stasis, and fluid retention. The root cause of BPH is the deficiency of healthy qi, for which Jingui Shenqi Pill and Zhenwu Decoction are used to nourish kidney qi and warm yang to promote diuresis. Blood stasis is the key pathogeneses of BPH, for which Guizhi Fuling Pill and Didang Decoction are used to dissipate blood stasis, relieve obstruction of orifices and facilitate bowel movement. Fluid retention is the most urgent symptom of BPH, for which Wuling Powder and Danggui Shaoyao Powder are used to transform qi and promote diuresis, addressing the urgent symptoms.
Dorsal Intercarpal Ligament Tears: An Arthroscopic Classification and Clinical Outcomes Study
Authors: Merlini Lorenzo , Chung Sze Ryn , Caloia Martin 
Published: March 2024

Abstract
Background The dorsal intercarpal (DIC) ligament plays a significant role in carpal stability and is often associated with other carpal ligament injuries. Isolated DIC ligament injuries are rare and can present as a ligament avulsion, bony avulsion, or attenuation due to chronic injury. Previously, we described the first isolated DIC ligament avulsion and proposed an arthroscopic repair technique. This article presents an arthroscopic classification of DIC ligament complex injuries and outcomes in a larger series of patients.
Methods A retrospective review was conducted on 16 patients who had undergone arthroscopic repair of the DIC ligament from 2018 to 2022. Intraoperative arthroscopic findings were documented, leading to the proposal of a classification system for DIC ligament tears. Pre- and postoperative outcomes, including the range of motion, grip strength, visual analog scale (VAS) pain scores, and Quick Disabilities of the Arm, Shoulder, and Hand questionnaire (QuickDASH) outcomes, were assessed in this cohort.
Results At a mean follow-up of 17.8 months, there was a statistically significant improvement in wrist flexion (65.3 to 74.3 degrees), wrist extension (77.8 to 84.5 degrees), comparative grip strength (46.4 to 87% compared with contralateral wrist), VAS score (6.3 to 0.6), and QuickDASH score (54.8 to 4.5). Four out of 16 patients (25%) had isolated DIC ligament tears, and the remaining 12 (75%) had concomitant intercarpal ligament injuries.
Conclusion The study highlights the critical role of the DIC ligament in carpal stability and introduces an arthroscopic classification for evaluating this lesion. Surgical options for different types of DIC ligament tears were also discussed.
Level of Evidence Level III, Retrospective study.
Ready, set, go! Deploying the social listening stoplight activity to teach marketing analytics using qualitative techniques
Authors: Bryant Morgan M. , Riley Jen , Turner-Henderson Tiffanie , Purnell Dexter 
Published: March 2024

AbstractAnalytical skills are in high demand across business sectors and various positions. Therefore, it is pivotal for marketing students to have exposure and practice leveraging analytical methods and tools before graduation and entering the job market. However, qualitative techniques to gather marketing analytics and insights are rarely taught as an approach. As a result, the authors created the Social Listening Stoplight Activity to teach students how to qualitatively gather marketing analytics insights for actionable recommendations that can be used to adjust social media strategies for increased engagement. By leveraging data from the Social Listening Stoplight Activity, the authors qualitatively analyze undergraduate and graduate student assignment submissions to assess the activity as a method to teach students qualitative social listening, a growing industry skill. This research finds that students exhibit more difficulty with qualitative versus quantitative strategic social media marketing analysis skills, further justifying the need for an activity like this in marketing analytics and social media courses. Students must not only be able to assess numerical data, but they also must be able to interpret and communicate recommendations to truly contribute to organizations.
Greening China’s digital economy: exploring the contribution of the East–West Computing Resources Transmission Project to CO2 reduction
Authors: Xie Xuemei , Han Yuhang , Tan Hao 
Published: March 2024

AbstractChina’s East–West Computing Resources Transmission Project (EWCRT Project) is a unique and innovative path toward developing China’s green digital economy. The EWCRT Project consists of building transregional digital infrastructure, including eight data center hubs and 10 data center clusters across China. Our estimations indicate that the EWCRT Project could result in a reduction of 2125 metric tons (Mt) of CO2 between 2020 and 2050. Combined with other improvement measures, such as an increase in power usage effectiveness (PUE) and a boost in the use of green electricity in these data centers, the project could result in a reduction of 9500 Mt of carbon emissions over the next three decades. Recognizing the heterogeneous makeup of data centers in general, it is crucial to identify diverse strategies that can transform each into “green engines” for the digital economy. Therefore, in this study, we use fuzzy-set qualitative comparative analysis (fsQCA) to characterize the complex conditions of different data center configurations. By doing so, we highlight differentiated strategies for data centers to support the greening of the digital economy.
Associations of Ambulatory Blood Pressure Measurements With High-Sensitivity Troponin and Natriuretic Peptide Levels in SPRINT
Authors: Venishetty Nikit , Berry Jarett D , de Lemos James A , Wu Elaine , Lee MinJae , Drawz Paul E , Nambi Vijay , Ballantyne Christie M , Killeen Anthony A , Ix Joachim H , Shlipak Michael G , Ascher Simon B 
Published: March 2024

Abstract

BACKGROUND
Nighttime blood pressure (BP) has greater prognostic importance for cardiovascular disease (CVD) than daytime BP, but less is known about nighttime and daytime BP associations with measures of subclinical CVD.

METHODS
Among 897 Systolic Blood Pressure Intervention Trial Study (SPRINT) participants with 24-hour ambulatory BP monitoring obtained near the 27-month study visit, 849 (95%) had N-terminal pro-B-type natriuretic peptide (NT-proBNP) and high-sensitivity cardiac troponin T (hs-cTnT) measured at the 24-month study visit. Multivariable linear regression analyses were performed to evaluate the associations of nighttime and daytime BP with cardiac biomarker levels.

RESULTS
The mean age was 69 ± 12 years, 28% were African American, and mean nighttime and daytime SBP were 121 ± 16 mm Hg and 132 ± 14 mm Hg, respectively. In multivariable models, compared with the lowest tertile of nighttime systolic BP, the highest tertile was associated with 48% higher NT-proBNP levels (adjusted geometric mean ratio [GMR] = 1.48, 95% CI: 1.22, 1.79), and 19% higher hs-cTnT levels (adjusted GMR = 1.19, 95% CI: 1.07, 1.32). In contrast, the highest vs. lowest tertile of daytime systolic BP was not associated with NT-proBNP (adjusted GMR = 1.09, 95% CI: 0.88, 1.34), but was associated with 16% higher hs-cTnT levels (adjusted GMR = 1.16, 95% CI: 1.04, 1.30). Similar results were observed using diastolic BP.

CONCLUSIONS
In SPRINT, both higher nighttime and daytime BP were independently associated with higher hs-cTnT levels, but only higher nighttime BP was associated with higher NT-proBNP levels.
Pot-economical total synthesis of prostaglandins via organocatalyst-mediated asymmetric reactions
Authors: Hayashi Yujiro 
Published: March 2024

Abstract
Prostaglandins are a family of molecules that possess important biological properties, and some of the analogues are used as medicines. Many synthetic methods have been developed for the efficient synthesis of prostaglandins. In this review, we will describe recent advances in the synthesis of prostaglandins and our endeavors in the effective synthesis of prostaglandins. Our group has developed three [3 + 2] cycloaddition reactions catalyzed by diphenylprolinol silyl ether, affording chiral substituted cyclopentane frameworks with excellent diastereo- and enantioselectivities. By using these cyclopentanes as key intermediates and applying pot reactions, several prostaglandins were synthesized efficiently in a small number of pots.
Submissive behavior is affected by territory structure in a social fish
Authors: Ruberto Tommaso , Swaney William T , Reddon Adam R 
Published: March 2024

Abstract
Group living may engender conflict over food, reproduction, or other resources and individuals must be able to manage conflict for social groups to persist. Submission signals are an adaptation for establishing and maintaining social hierarchy position, allowing a subordinate individual to avoid protracted and costly aggressive interactions with dominant individuals. In the daffodil cichlid fish (Neolamprologus pulcher), subordinates may use submission signals to resolve conflicts with dominant individuals and maintain their social status within the group. The complexity of the physical environment may affect the value of submission signals compared with fleeing or avoidance, which may require certain physical features such as shelters to be effective. We investigated how the ecological context affected the expression of submission in subordinate daffodil cichlids by examining their behavior under different arrangements of the physical environment within their territories. We altered the number of shelters provided to daffodil cichlid groups and compared the interactions between dominant and subordinate individuals under each shelter condition by scoring the social and cooperative behaviors of the group members. We found that behaviors of group members were modulated by the environment: subordinates displayed fewer submission and fleeing behaviors in more structurally complex environments and dominants were more aggressive to subordinates when more shelters were present. Our results help to elucidate the role of the physical environment in the modulation of social interactions in group-living animals and may have implications for the welfare of captively housed social cichlid groups.