bluuebunny/crossref_metadata_2025_split huggingface dataset:
Low-temperature molten salt enabled synthesis of solid-state emissive carbon dots with high endurance and &gt;99% quantum yields
Authors: Lou Qing , Lan Yu , Zheng Guangsong , Song Run-Wei , Hao Jing-Nan , Liu Jia-Lu , Shen Cheng-Long , Zhu Jinyang , Cao Sheng , Zhao Jialong , Shan Chongxin 
Published: February 2025

Abstract

Fluorescent carbon dots (CDs) have garnered significant attention for their unique optoelectronic properties and applications, but their practical employment is hampered by the excessive synthesis temperature, tedious post-processing and limited solid-state luminescence efficiency. Herein, we develop a facile molten salt method to achieve the one-step synthesis of full-color CDs with efficient solid-state emission. Comprehensively, kilogram-scale solid-state CDs with a quantum yield of 90% can be readily synthesized via a salt-assisted approach under mild conditions (100–142°C) within 10 minutes. The spectral characterization and density functional theory calculation confirm that zinc ion coordination can occur in liquated environment, which facilitates the polymerization of precursors at lower temperatures, suppresses the formation of non-radiative recombination channels on their surface, and further enhances luminescence in solid. The machine learning is further used to optimize CDs’ luminous efficiency up to 99.86%, evoking excellent performance CDs-based light-emitting diodes with a maximum luminous efficiency of 156.29 lm W–1 to drive backlit display with a long-persistent lifetime (T95 at 100 cd m–2 = 45108.7 h). This work provides a pathway for the design and fabrication of advanced carbon-based solid-state luminescent materials, significantly contributing to the advancement of next-generation lighting and display technologies.
Evaluation of vestibular and sleep disturbances after the Kahramanmaraş earthquake
Authors: Hepkarsi Sevinc , Karataş Mehmet , Özmercan Yunus Emre 
Published: February 2025

Abstract

Objective
Major earthquakes are linked to a higher prevalence of dizziness and sleep disturbances. The impact of an earthquake on balance can disrupt individuals' daily activities. Dizziness and sleep disorders are frequently observed after traumatic events. This study aimed to examine the effects of significant earthquakes and recurring aftershocks on the human vestibular system and sleep patterns.
Methods
This study is cross-sectional and prospective. All participants were evaluated using the Dizziness Handicap Inventory, Visual Analogue Scale, and Epworth Sleepiness Scale. The patients were categorized into two groups: those who had experienced vertigo, dizziness, or balance disorders at least once prior to the earthquakes (Group 1), and those who developed these issues after the earthquake (Group 2).
Results
The mean VAS scores of patients in group 2 were significantly lower than those of patients in group 1 (p = 0.004). DHI scores of 167 total patients were 50.16 ± 21.21. The DHI scores of the patients were divided into three categories (mild, moderate and severe). Total ESS value of 167 patients was 6.79 ± 4.99. ESS values of the patients were divided into 5 categories (low normal, high normal, mild, moderate, severe). There were significant differences between ESS categories and VAS scores (p = 0.000). There were also significant differences between ESS categories and DHI scores (p = 0.000).
Conclusion
The results showed that the prevalence of balance disorder and sleep disturbance increased significantly after the major earthquakes.
Exploring intrinsic capacity assessment-driven patterns and its influence on unplanned readmission in patients after PCI: A prospective longitudinal study
Authors: Zhao Yuan , Tang Leiwen , Jiang Yueying , Guo Yunyu , Wanya Pan , Tian Wenhao , Feng Xiuqin 
Published: February 2025

Abstract

Introduction:
Intrinsic capacity is a new concept driven by functional medicine. Unplanned readmission is one of the most common and expensive adverse outcomes after percutaneous coronary intervention (PCI), and its predictors are complex. Whether the baseline intrinsic capacity level or longitudinal intrinsic capacity trajectories could predict unplanned readmission remains unclear.
Methods
Intrinsic capacity was assessed at discharge, 1 month, and 6 months after PCI. Latent class growth analysis was used to determine heterogeneous intrinsic capacity trajectories. We used logistic regression to explore the effect of intrinsic capacity on unplanned readmission.
Results
A total of 300 participants (mean ± SD age: 67.02 ± 9.42 years; 226 [75.3%] male) were included in the analysis. The unplanned readmission incidence was 24%. Unplanned readmission could be predicted by the baseline intrinsic capacity level (OR = 1.72, 95%CI: 1.23–2.39), NT-proBNP (OR = 0.24, 95%CI: 0.10–0.54), LVEF% (OR = 0.95, 95%CI: 0.91–0.98), CRP (OR = 1.04, 95%CI: 1.01–1.07), Ty-G index (OR = 2.08, 95%CI: 1.16–3.74) and chronic disease resource utilization (OR = 1.06, 95%CI: 1.00-1.11). At the prospective level, two intrinsic capacity trajectory classes were identified: “low then drop” and “high and stable”. Patients in the “low then drop” group have a higher risk of unplanned readmission (OR = 2.12, 95%CI: 1.10–4.10).
Conclusions
The findings capture two intrinsic capacity trajectories in middle-aged and older patients after PCI. Both the baseline intrinsic capacity level and intrinsic capacity trajectories could effectively predict unplanned readmission. The longitudinal association between cardiovascular markers and unplanned readmission requires further evidence.
Noise-resilient solid host for electron qubits above 100 mK
Authors: Jin Dafei , Li Xinhao , Wang Christopher , Dizdar Brennan , Huang Yizhong , Wen Yutian , Guo Wei , Zhang Xufeng , Han Xu , Zhou Xianjing 
Published: February 2025

Abstract

Cryogenic solid neon has recently emerged as a pristine solid host for single electron qubits. At ~10 mK temperatures, electron-on-solid-neon (eNe) charge qubits have exhibited exceptionally long coherence times and high operation fidelities. To advance this platform towards a scalable quantum information architecture, systematic characterization of its noise feature is imperative. Here, we show the remarkable resilience of solid neon against charge and thermal noises when eNe qubits are operated away from the charge-insensitive sweet-spot and at elevated temperatures. Without optimizing neon growth, the measured charge (voltage) noise on solid neon is already orders of magnitude lower than that in most stringently grown semiconductors, rivaling the best records to date. Up to 400 mK, the eNe charge qubits operated at ~5 GHz can maintain their echo coherence times over 1 microsecond. These observations highlight solid neon as an ideal host for quantum information processing at higher temperatures and larger scales.
China’s aerosol cleanup has contributed strongly to the recent acceleration in global warming
Authors: Samset Bjørn , Wilcox Laura , Allen Robert , Stjern Camilla , Lund Marianne , Ahmadi Sharar , Elling Maxwell , Fraser-Leach Luke , Griffiths Paul , Keeble James , Koshiro Tsuyoshi , Kushner Paul , Lewinschal Anna , Makkonen Risto , Merikanto Joonas , Nabat Pierre , Narazenko Larissa , O'Donnell Declan , Oshima Naga , Rumbold Steven , Takemura Toshihiko , Tsigaridis Kostas , Westervelt Daniel 
Published: February 2025

Abstract

Global surface warming has accelerated since around 2010, relative to the preceding half century1-3. This has coincided with China’s efforts to reduce air pollution through restricted atmospheric aerosol and precursor emissions4,5. A direct link between the two has, however, not yet been established. Here we show, using a large set of simulations from eight Earth System Models, how a time evolving 75% reduction in Chinese sulfate emissions partially unmasks greenhouse driven warming and influences the pattern of surface temperature change. We find a rapidly evolving global, annual-mean warming of 0.07 ± 0.05 ºC, sufficient to explain a majority of the uptick in global warming rate since 2010. We also find North-Pacific warming and a top-of-atmosphere radiative imbalance that are consistent with recent observations. China’s aerosol cleanup is thus likely a key contributor to recent global warming acceleration, and to Pacific warming trends.
Association between the dietary index for gut microbiota and constipation in American adults
Authors: Song Chunyan , Zhang Zhulin , Zhu Shanxiang , Tong Huacheng 
Published: February 2025

Abstract

Constipation, a common gastrointestinal disorder, significantly impacts quality of life. Its relationship with gut microbiota has garnered attention. Dietary factors play a crucial role in the development and management of constipation. The recently introduced dietary index for gut microbiota (DI-GM), a measure of gut microbiota diversity, offers insights into this connection. The relationship between dietary gut microbiota index and constipation is a critical public health issue. This study investigated the association between DI-GM and constipation prevalence in the American population using data from 11,819 individuals from the National Health and Nutrition Examination Survey (NHANES) between 2005 and 2010. Constipation was defined using Bristol stool form scale types 1 and 2. Dietary recall information was used to determine the DI-GM score, indicating the dietary influence on the gut microbiome. Multivariate weighted logistic regression, adjusted for confounders, was performed to analyze the association between DI-GM scores and constipation prevalence. Further analyses included a subgroup analysis and restricted cubic splines to explore this relationship [restricted cubic spline(RCS)]. An increased DI-GM index, indicating a healthier gut microbiome, was linked to a decreased risk of constipation. A similar association was observed with a more favorable score for beneficial gut microbiota. Non-linear relationships between DI-GM scores and constipation were identified through RCS analysis, and subgroup and interaction analyses confirmed the consistency of these findings across strata, suggesting no significant heterogeneity. These findings suggest that dietary adjustments may be an important method for preventing constipation.
HADOCR: A Hierarchical Attention-Driven Framework with Dynamic Sampling for Ancient Chinese Medical Literature Recognition
Authors: He Jia 
Published: February 2025

Abstract

The digitization of ancient Chinese medical literature faces significant challenges due to its complex typefaces, irregular layouts, degraded documents, and varied writing styles across dynasties. This research addresses the limitations of existing scene text recognition (STR) methods, which perform poorly on historical texts, especially medical manuscripts. The primary research question is how to design a robust and effective method for ancient Chinese medical text recognition.We propose HADOCR, a novel end-to-end framework for ancient Chinese medical text recognition. The model leverages a Vision Transformer (ViT) for visual feature extraction, followed by a Feature Fusion Block (FFB) to mix local and global features. Two innovative modules are introduced: Dynamic Ratio Sampling (DRS), which adapts to multi-scale sampling while preserving aspect ratios and structural features, and Dual-Attention Feature Rearrangement (DAFR), which applies hierarchical attention to improve handling of character deformation and irregular text arrangements.We propose HADOCR, a novel end-to-end framework for ancient Chinese medical text recognition. The model leverages a Vision Transformer (ViT) for visual feature extraction, followed by a Feature Fusion Block (FFB) to mix local and global features. Two innovative modules are introduced: Dynamic Ratio Sampling (DRS), which adapts to multi-scale sampling while preserving aspect ratios and structural features, and Dual-Attention Feature Rearrangement (DAFR), which applies hierarchical attention to improve handling of character deformation and irregular text arrangements.HADOCR demonstrates superior performance in ancient Chinese medical text recognition, significantly improving feature preservation and handling spatial deformations. The introduction of the ACML dataset, containing over 100,000 instances, provides a valuable resource for future research in historical document recognition. Our work paves the way for better digital preservation and knowledge mining of traditional Chinese medical literature and has broader applications in historical document recognition.
Nonlinear Feedback Linearization and LQG/LTR Control: A Comparative Study for a Single-Machine Infinite-Bus System
Authors: Vernekar Pratik 
Published: February 2025

Abstract

This paper presents a comparative study of three advanced control strategies for a single-machine infinite-bus (SMIB) system: the nonlinear feedback linearizing controller (NFLC), the integral-NFLC (INFLC), and the linear-quadratic-Gaussian/loop transfer recovery (LQG/LTR) control. The NFLC and INFLC techniques use exact feedback linearization to precisely cancel the SMIB system nonlinearities, enabling the use of decentralized, linear, and optimal controllers for the decoupled generator and turbine-governor systems while remaining unaffected by the SMIB system's internal dynamics and operating conditions. In contrast, the LQG/LTR approach employs an enhanced Kalman filter, designed using the LTR procedure and a detailed frequency-domain loop-shaping analysis, to achieve a reasonable trade-off between optimal performance, noise/disturbance rejection, robustness recovery, and stability margins for the SMIB system. We provide a control synthesis framework for constructing practical, verifiable, scalable, and resilient linear and nonlinear controllers for SMIB and multi-machine power systems by utilizing a high-fidelity plant model for validation, a reduced-order control-design model, and the correlations between the two models' control inputs. Rigorous simulations and comparative analysis of the proposed controllers and a full-state linear–quadratic regulator show the benefits, constraints, and trade-offs of each controller in terms of transient response, steady-state error, robustness, rotor angle stability, frequency control, and voltage regulation under different operating conditions. Ultimately, this study aims to guide the selection of appropriate control strategies for large-scale power systems, enhancing the overall resilience and reliability of the electric grid.
A Deep Learning-Augmented Density Functional Framework for Reaction Modeling with Chemical Accuracy
Authors: Xiao Jin , Zhang Yingfeng , Li Bowen , Zhang Shuwen , Gao Ya , Wang Han , Zhang John Z.H. , Zhu Tong 
Published: February 2025

Abstract

Accurate prediction of reaction energetics remains a fundamental challenge in computational chemistry, as conventional density functional theory (DFT) often fails to reconcile high accuracy with computational effi ciency. Here, we introduce Deep post-Hartree-Fock (DeePHF), a machine learning framework that synergistically integrates neural networks with quantum mechanical descriptors to achieve CCSD(T)-level precision while retaining the efficiency of DFT. By establishing a direct mapping between the eigenvalues of local density matrices and high-level correlation energies, DeePHF circumvents the traditional accuracy-scalability trade-off . Trained on a limited dataset of small-molecule reactions, our method demonstrates unprecedented performance across multiple benchmark datasets, exhibiting exceptional transferability. In fact, its accuracy even surpasses that of advanced double-hybrid functionals, all while maintaining O(N^3) scaling. DeePHF offers a promising pathway to bridge the gap between high-level quantum chemistry methods and the practical demands for scalable, accurate models in computational chemistry, and with further refinement, it is poised to make significant contributions to the advancement of chemical reaction modeling.
Optimizing Portfolio Performance through Clustering and Sharpe Ratio-Based Optimization: A Comparative Backtesting Approach
Authors: Park Keon Vin 
Published: February 2025

Abstract

Optimizing portfolio performance is a fundamental challenge in financial modeling, requiring the integration of advanced clustering techniques and data-driven optimization strategies. This paper introduces a comparative backtesting approach that combines clustering-based portfolio segmentation and Sharpe ratiobased optimization to enhance investment decision-making.
First, we segment a diverse set of financial assets into clusters based on their historical log-returns using K-Means clustering. This segmentation enables the grouping of assets with similar return characteristics, facilitating targeted portfolio construction.
Next, for each cluster, we apply a Sharpe ratio-based optimization model to derive optimal weights that maximize risk-adjusted returns. Unlike traditional mean-variance optimization, this approach directly incorporates the trade-off between returns and volatility, resulting in a more balanced allocation of resources within each cluster.
The proposed framework is evaluated through a backtesting study using historical data spanning multiple asset classes. Optimized portfolios for each cluster are constructed and their cumulative returns are compared over time against a traditional equal-weighted benchmark portfolio.
Our results demonstrate the effectiveness of combining clustering and Sharpe ratio-based optimization in identifying high-performing asset groups and allocating resources accordingly. The selected cluster portfolio achieved a total return of 140.98%, with an annualized return of 24.67%, significantly outperforming the benchmark portfolio, which achieved a total return of 107.59% and an annualized return of 20.09%. The Sharpe ratio of the selected portfolio (0.84) further highlights its superior risk-adjusted performance compared to the benchmark portfolio (0.73).
This methodology provides a systematic and data-driven approach to portfolio optimization, achieving superior returns while maintaining a reasonable level of risk.
Study On Structure Monitoring Using Laser Scanner Technology
Authors: Erdenenemekh Ganzorig 
Published: February 2025

Abstract

Ground Laser Scanning (TLS) is a reliable tool for high-precision structural deformation monitoring. Reinforced concrete and masonry structures require deformation monitoring to meet high safety requirements. As a result, it is important to monitor deformation and assess the safety of these structures against damage. It is desirable to predict the load displacement of the structure in terms of elastic and inelastic responses. For structures, measurements based on ground laser scanning technology are performed. This research work presents a comparison of the initial and optimized point cloud. The surface uncertainty of various orders is investigated by covering the surface approximation measurement area. Based on ground laser scanning measurements, the results of the structure surface are correlated with the test results and are monitored by subtracting them from the deformation calculation.
Green Innovations’ Differential Roles in Shaping Firm Productivity under Environmental Law via Optimized PSM-DID
Authors: Jiang Yi 
Published: February 2025

Abstract

This study utilizes both cross-sectional and year-by-year settings of Propensity Score Matching with Difference-in-Differences (PSM-DID) method to analyze the impact of the 2015 Environmental Protection Law (NEPL) on green innovations and total factor productivity in heavy polluting firms within manufacturing industries, spanning 2010–2018. Employing the Cobb-Douglas production function framework, it posits green innovation as a crucial technological resource augmenting tangible assets and technological productivity. The analysis reveals differentiated effects of NEPL on various types of green innovations: a negative impact on alternative energy and green transportation patents, while energy-saving and waste management patents remain largely unaffected. This suggests a crowding-out effect of environmental regulations on certain green innovations. Interestingly, heterogeneity analysis shows that smaller, less profitable heavy-polluting firms economically gain more from green innovations, particularly in waste management and energy-saving, while strict policies pose challenges for the alternative energy sector, highlighting the need for diverse, more supportive and adaptive policy approaches.
Представления английских дипломатово министрах Екатерины II
Authors: Лабутина Т.Л. 
Published: February 2025

В статье рассматриваются сведения английских послов при дворе Екатерины II о первых министрах императрицы — канцлере А.П. Бестужев-Рюмине, Н.И. Панине, Г.А. Потемкине. Их характеристики не всегда были объективными и непредвзятыми. Чаще всего на них влияли неудачи британской стороны в дипломатическом поединке с императрицей и русскими сановниками. В то же время в информации дипломатов содержится много новых и интересных фактов о жизни и деятельности первых лиц российского государства последней трети XVIII века, которые значительно расширяют наши представления о екатерининской эпохе.
The article deals with the testimonies of the British ambassadors at the court of Catherine II about the first Ministers of the Empress — Chancellor A.P. Bestuzhev-Ryumin, N.I. Panin, G.A. Potemkin. Their characteristics were not always objective and biased. Most often this was influenced by the failures of the British side in a diplomatic duel with the Empress and Russian dignitaries. At the same time, the information of diplomats contains many new and interesting facts about the life and activities of the first persons of the Russian state of the last third of the XVIII century, which significantly expands the views of our contemporaries about the Catherine era.
Brexit: обсуждение ситуации в Конгрессе США
Authors: Айриян Р.С. 
Published: February 2025

Представленная статья посвящена анализу обсуждения в стенах Конгресса США вопроса о выходе Соединенного Королевства из состава Европейского союза. Автор, используя в первую очередь стенограммы Конгресса США и материалы комитетских слушаний, выделяет три основные проблемы, которые вызывали обеспокоенность у американских законодателей в связи с Брекзитом: развитие англо-американских торговых отношений, угроза срыва Белфастского соглашения, а также проблема вмешательства России в проведение референдума в Великобритании. Делается вывод, что отношение к двум вопросам в значительной степени было связано с партийной принадлежностью законодателей, но при этом своеобразным исключением становится обсуждение проблемы сохранения Соглашения Страстной пятницы.
The article is devoted to the analysis of the discussion in the US Congress on the exit of the United Kingdom from the European Union. The author, using primarily transcripts of the US Congress and materials from committee hearings, identifies three main problems that US legislators were concerned about Brexit: the development of Anglo-American trade relations, the threat of disruption of the Belfast Agreement, and the problem of Russia's interference in the referendum In Great Britain. It is concluded that the attitude to the two issues was largely related to the party affiliation of the legislators, but the discussion of the problem of maintaining the Good Friday Agreement becomes a peculiar exception.