bluuebunny/crossref_metadata_2025_split huggingface dataset:
Long-term risk of cardiovascular mortality according to age group and blood pressure categories of the latest guideline
Authors: Satoh Michihiro , Ohkubo Takayoshi , Miura Katsuyuki , Harada Akiko , Tsutsui Anna , Hozawa Atsushi , Shimizu Yuji , Ishikawa Shizukiyo , Kokubo Yoshihiro , Okamura Tomonori , Murakami Yoshitaka ,   on behalf of the Evidence for Cardiovascular Prevention from Observational Cohorts in Japan (EPOCH–JAPAN) Research Group
Published: February 2025

Abstract
This study examined the association between the latest blood pressure (BP) classification and cardiovascular disease (CVD) mortality risk, using data from 70,570 individuals across 10 Japanese cohorts. Participants were stratified by age (40–64 and 65–89 years) and antihypertensive treatment use. BP was classified according to the 2019 Japanese Society of Hypertension Guidelines. During a follow-up period of approximately 10 years, 2304 CVD deaths occurred. Cox models demonstrated that CVD mortality risk increased stepwise with the BP category, with this association being especially pronounced in patients aged 40–64 years, where the Grade I hypertension group showed the highest population-attributable fraction (PAF). When the treated participants were included in the hypertension group, the overall PAF for CVD mortality was 41.1%. Similar patterns were observed for CVD subtype mortality risk, with hypertension showing particularly high PAFs for intracerebral hemorrhage. These findings highlight the importance of early-stage prevention and management of hypertension.
Chimpanzees adapt their exploration to key properties of the environment
Authors: Haux Lou M. , Engelmann Jan M. , Herrmann Esther , Hertwig Ralph 
Published: February 2025

Abstract
Exploration is an important strategy for reducing the uncertainty that pervades daily life. Yet the evolutionary roots of adaptive exploration are poorly understood. We harness and adapt the human decisions-from-experience paradigm to investigate exploration under uncertainty in chimpanzees. In our study, chimpanzees (N = 15; eight females) are simultaneously confronted with an uncertain option (with outcome variance) and a safe option (without outcome variance) and tested in both stable and changing environments. Results reveal that, as in human exploration, how and how much chimpanzees explore depends on the environment. One key environmental property is change: Chimpanzees explore more across trials in changing than in stable conditions. Consistent with the assumption of classic economic models that variance indicates risk, chimpanzees also explore more when they experience variance in the options’ outcomes. Individual risk and uncertainty preferences did not have a statistically significant effect on exploratory efforts. These findings suggest that chimpanzees and humans share key similarities in the way they respond to risk and uncertainty.
STANCE: a unified statistical model to detect cell-type-specific spatially variable genes in spatial transcriptomics
Authors: Su Haohao , Wu Yuesong , Chen Bin , Cui Yuehua 
Published: February 2025

Abstract
One of the major challenges in spatial transcriptomics is to detect spatially variable genes (SVGs), whose expression patterns are non-random across tissue locations. Many SVGs correlate with cell type compositions, introducing the concept of cell type-specific SVGs (ctSVGs). Existing ctSVG detection methods treat cell type-specific spatial effects as fixed effects, leading to tissue spatial rotation-dependent results. Moreover, SVGs may exhibit random spatial patterns within cell types, meaning an SVG is not always a ctSVG, and vice versa, further complicating detection. We propose STANCE, a unified statistical model for both SVGs and ctSVGs detection under a linear mixed-effect model framework that integrates gene expression, spatial location, and cell type composition information. STANCE ensures tissue rotation-invariant results, with a two-stage approach: initial SVG/ctSVG detection followed by ctSVG-specific testing. We demonstrate its performance through extensive simulations and analyses of public datasets. Downstream analyses reveal STANCE’s potential in spatial transcriptomics analysis.
Amphoteric chalcogen-bonding and halogen-bonding rotaxanes for anion or cation recognition
Authors: Tse Yuen Cheong , Docker Andrew , Marques Igor , Félix Vítor , Beer Paul D. 
Published: February 2025

Abstract
The ever-increasing demand in the development of host molecules for the recognition of charged species is stimulated by their fundamental roles in numerous biological and environmental processes. Here, capitalizing on the inherent amphoteric nature of anisotropically polarized tellurium or iodine atoms, we demonstrate a proof of concept in charged guest recognition, where the same neutral host structure binds both cations or anions solely through its chalcogen or halogen donor atoms. Through extensive 1H nuclear magnetic resonance titration experiments and computational density functional theory studies, a library of chalcogen-bonding (ChB) and halogen-bonding (XB) mechanically interlocked [2]rotaxane molecules, including seminal examples of all-ChB and mixed ChB/XB [2]rotaxanes, are shown to function as either Lewis-acidic or Lewis-basic multidentate hosts for selective halide anion and metal cation binding. Notably, the exploitation of the inherent amphoteric character of an atom for the strategic purpose of either cation or anion recognition constitutes the inception of a previously unexplored area of supramolecular host–guest chemistry.
Full-field Brillouin microscopy based on an imaging Fourier-transform spectrometer
Authors: Bevilacqua Carlo , Prevedel Robert 
Published: February 2025

Abstract
Brillouin microscopy is an emerging optical elastography technique that can be used to assess mechanical properties of biological samples in a three-dimensional, all-optical and hence non-contact fashion. However, the low cross-section of spontaneous Brillouin scattering produces weak signals that often necessitate prolonged exposure times or illumination dosages that are potentially harmful for biological samples. Here we present a new approach for highly multiplexed and therefore rapid spectral acquisition of the Brillouin-scattered light. Specifically, by exploiting a custom-built Fourier-transform imaging spectrometer and the symmetric properties of the Brillouin spectrum, we experimentally demonstrate full-field 2D spectral Brillouin imaging of phantoms as well as biological samples, at a throughput of up to 40,000 spectra per second, with a precision of ~70 MHz and an effective 2D image acquisition speed of 0.1 Hz over a ~300 × 300 µm2 field of view. This represents an approximately three-orders-of-magnitude improvement in speed and throughput compared with standard confocal methods, while retaining high spatial resolution and the capability to acquire three-dimensional images of photosensitive samples in biology and medicine.
Using a units ontology to annotate pre-existing metadata
Authors: Porter John H. , O’Brien Margaret , Frants Marina , Earl Stevan , Martin Mary , Laney Christine M. 
Published: February 2025

Abstract
Automated processing of environmental data is hindered by the wide array of unit representations provided in the metadata of digital datasets. For example, gm/m2, g/m2, gm-2, g/m^2, g.m-2 and gramPerMeterSquared are all representations of a single complex unit that might be human-readable but are not machine-interpretable. Connecting ad hoc units to a single unit concept in an ontology permits the identification of datasets sharing units and provides additional information regarding labels, definitions, dimensions and transformations provided in the ontology. Here we use successive string transformations to link ad hoc unit representations to units in the QUDT ontology (e.g., unit: GM-PER-M2). Although only 896 of 7,110 distinct units in a corpus of ecological metadata from DataONE, the Environmental Data Initiative and the U.S. National Ecological Observatory Network were matched, 324,811 unit uses (instances) out of 355,057 of total unit uses were successfully mapped to QUDT units (91%). The resulting lookup table was used to enable a web service and R functions for adding annotation elements to Ecological Metadata Language documents.
MRI-based analysis of thigh intramuscular fat and its associations with age, sex, and BMI using data from the osteoarthritis initiative data
Authors: Joseph Gabby B. , Akkaya Zehra , Sims Wynton M. , McCulloch Charles E. , Nevitt Michael C. , Lynch John A. , Lane Nancy E. , Link Thomas M. 
Published: February 2025

Abstract
The degree of thigh intramuscular fat in individuals without OA is fundamental for distinguishing natural variations in intramuscular fat from pathological changes. The goals of this study were to estimate the degree of thigh intramuscular fat in individuals without radiographic OA or frequent pain and assess the associations of age, sex, and BMI with the degree of intramuscular fat. Individuals without knee or hip radiographic OA, without total knee/hip arthroplasty, and without frequent knee/hip pain were selected from the OAI database (n = 710). Goutallier Grades (GGs) of the quadriceps and hamstring muscles were assessed based on 3 T MR images on a scale from 0 (normal muscle) to 4 (more fat than muscle). The associations between demographic variables and GG outcomes were evaluated using mixed effects models. The most prevalent GGs among the muscles were Grades 1 and 2; Grade 4 was infrequent (< 1%). Greater BMI (p < 0.001) and age (p < 0.001) were each associated with greater GG. Women had greater GG than men (greatest difference in the vastus medialis: coeff. = 0.214, p < 0.001). At lower BMI, women had greater intramuscular fat than men; at higher BMI, men had greater intramuscular fat than women (p = 0.029 for BMI-sex interaction). While individuals without radiographic OA or frequent pain generally had low thigh intramuscular fat, higher BMI and age were associated with greater intramuscular fat, and GGs were greater in women than men. The relationship between BMI and intramuscular fat was sex-dependent. Thus, demographic variables must be considered when evaluating intramuscular fat.
An extensive experimental analysis for heart disease prediction using artificial intelligence techniques
Authors: Rohan D. , Reddy G. Pradeep , Kumar Y. V. Pavan , Prakash K. Purna , Reddy Ch. Pradeep 
Published: February 2025

Abstract
The heart is an important organ that plays a crucial role in maintaining life. Unfortunately, heart disease is one of the major causes of mortality globally. Early and accurate detection can significantly improve the situation by enabling preventive measures and personalized healthcare recommendations. Artificial intelligence is emerging as a powerful tool for healthcare applications, particularly in predicting heart diseases. Researchers are actively working on this, but challenges remain in achieving accurate heart disease prediction. Therefore, experimenting with various models to identify the most effective one for heart disease prediction is crucial. In this view, this paper addresses this need by conducting an extensive investigation of various models. The proposed research considered 11 feature selection techniques and 21 classifiers for the experiment. The feature selection techniques considered for the research are Information Gain, Chi-Square Test, Fisher Discriminant Analysis (FDA), Variance Threshold, Mean Absolute Difference (MAD), Dispersion Ratio, Relief, LASSO, Random Forest Importance, Linear Discriminant Analysis (LDA), and Principal Component Analysis (PCA). The classifiers considered for the research are Logistic Regression, Decision Tree, Random Forest, K-Nearest Neighbors (KNN), Support Vector Machine (SVM), Gaussian Naïve Bayes (GNB), XGBoost, AdaBoost, Stochastic Gradient Descent (SGD), Gradient Boosting Classifier, Extra Tree Classifier, CatBoost, LightGBM, Multilayer Perceptron (MLP), Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), Bidirectional LSTM (BiLSTM), Bidirectional GRU (BiGRU), Convolutional Neural Network (CNN), and Hybrid Model (CNN, RNN, LSTM, GRU, BiLSTM, BiGRU). Among all the extensive experiments, XGBoost outperformed all others, achieving an accuracy of 0.97, precision of 0.97, sensitivity of 0.98, specificity of 0.98, F1 score of 0.98, and AUC of 0.98.
Development of a battery free, solar powered, and energy aware fixed wing unmanned aerial vehicle
Authors: Liller Jackson , Goel Rishabh , Aziz Abdul , Hester Josiah , Nguyen Phuc 
Published: February 2025

Abstract
Unmanned Aerial Vehicles (UAVs) hold immense potential across various fields, including precision agriculture, rescue missions, delivery services, weather monitoring, and many more. Despite this promise, the limited flight duration of the current UAVs stands as a significant obstacle to their broadscale deployment. Attempting to extend flight time by solar panel charging during midflight is not viable due to battery limitations and the eventual need for replacement. This paper details our investigation of a battery-free fixed-wing UAV, built from cost-effective off-the-shelf components, that takes off, remains airborne, and lands safely using only solar energy. In particular, we perform a comprehensive analysis and design space exploration in the contemporary solar harvesting context and provide a detailed accounting of the prototype’s mechanical and electrical capabilities. We also derive the Greedy Energy-Aware Control (GEAC) and Predictive Energy-Aware Control (PEAC) solar control algorithm that overcomes power system brownouts and total-loss-of-thrust events, enabling the prototype to perform maneuvers without a battery. Next, we evaluate the developed prototype in a bench-top setting using artificial light to demonstrate the feasibility of batteryless flight, followed by testing in an outdoor setting using natural light. Finally, we analyze the potential for scaling up the evaluation of batteryless UAVs across multiple locations and report our findings.
The beneficial effects of a probiotic mix on bone and lean mass are dependent on the diet in female mice
Authors: Ohlsson Claes , Lawenius Lina , Jiang Yiwen , Horkeby Karin , Wu Jianyao , Nilsson Karin H. , Koskela Antti , Tuukkanen Juha , Movérare-Skrtic Sofia , Henning Petra , Sjögren Klara 
Published: February 2025

Abstract
Bone mass and lean mass decrease with age and these changes are associated with increased fracture risk and sarcopenia. Previous studies demonstrated that a probiotic mixture of Lacticaseibacillus paracasei DSM13434, Lactiplantibacillus plantarum DSM 15312 and DSM 15313 (L. Mix) prevents bone loss in ovariectomized (ovx) female mice. The purpose of the present study is to test if the beneficial effect of L. Mix is modified by the diet. Female mice were fed either a high-fat (HFD, 60% kcal from fat) or a low-fat (LFD, 10% kcal from fat) diet and subjected to either sham or ovx surgery and treated with L. Mix for 12 weeks. L. Mix treatment increased total body bone mineral density (p ≤ 0.01), by increasing cortical bone area, and total body lean mass (p = 0.035) in mice on LFD but not in mice on HFD. Metagenome sequencing of cecal content showed that L. Mix treatment increased the relative abundance of Lacticaseibacillus paracasei and, Lactiplantibacillus plantarum, demonstrating successful treatment. In addition, the probiotic treatment affected the overall gut microbiota composition and functionality. These findings demonstrate that the L. Mix in combination with a healthy diet is beneficial for musculoskeletal health in female mice.
A risk uncertainty–based flexible dispatch method for pumped storage under extreme weather
Authors: Feng Miaoyong , Huang Zhanhong , Yu Tao , Pan Zhenning , Liu Qianjin , Wang Ziyao , Liu Shuangquan 
Published: February 2025

AbstractThe large‐scale integration of renewable energy into new power systems presents significant challenges in terms of controllability and predictability due to its inherent randomness and volatility. The uncontrollability is further compounded by the sudden impacts of extreme weather events, making multi‐scale power balance increasingly difficult. This paper proposes a two‐stage flexible dispatch method (TFDM) for measuring uncertainty under extreme weather. The model constructs probabilistic disaster impact assessments for wind farms and transmission lines using fuzzy sets and captures the associated uncertainties through chance constraints and risk costs. It provides more flexible disaster risk reduction methods by integrating uncertainty prediction errors and unit commitment plans into the interaction between two‐stage dispatch. An accelerated algorithm that combines historical scene learning with improved K‐nearest neighbours (KNN) dispatch is proposed. It is employed to obtain initial solutions for binary unit commitment variables, accelerating the resolution of frequent unit combination switching problems. Tests on the IEEE 39‐bus and IEEE 118‐bus systems show that the proposed method can effectively utilize the regulating capacity of pumped storage units to significantly improve the resilience of the system to cope with extreme weather. The improved KNN algorithm has stronger convergence and efficiency for large‐scale power grid scenarios.
FHIR Granular Sensitive Data Segmentation
Authors: Lee Preston , Mendoza Daniel , Kaiser Martha , Lott Eric , Singh Gagandeep , Grando Adela 
Published: February 2025

Abstract
Background Due to fear of stigma, patients want more control over the sharing of sensitive medical records. The Substance Abuse and Mental Health Administration (SAMHSA) and the Office of the National Coordinator (ONC) supported the development of standards-compliant, consent-respecting medical record exchange technology using metadata labeling (e.g., substance use information). Existing technologies must be updated with newer standards and support more than binary-sensitive categorizations to better align with how physicians categorize sensitive medical records.
Objectives Our goal was to deploy, pilot test, and share open-source Fast Healthcare Interoperability Resources (FHIR)-based data segmentation technologies. We pilot-tested the technologies using real-world patient electronic health record data in the context of substance use information. We involved physicians in designing a novel decision engine that supports various confidence levels.
Results We deployed a web-based Patient Portal and Clinical Decision Support (CDS) granular data segmentation Engine to allow patients to make consent-based granular data choices (e.g., not sharing substance use medical records). Compared with previous solutions, the Engine innovates by using the latest Health Level 7 (HL7) standards to support data sensitivity labeling and redaction: FHIR R5 and its Consent resource type and CDS Hooks. It also supports configurable floating point confidence threshold cutoffs as opposed to binary medical record categorizations. Multiple engineering choices were made to simplify software development and maintenance and to improve technology adaptability, reusability, and scalability.
Conclusion The resulting data segmentation technologies update SAMHSA and ONC software with the newest HL7 standards and better mimic how physicians categorize sensitive medical information with various confidence levels. To support reusability, we shared the resulting open-source code through the HL7 FHIR Foundry.
9.10.5 Thiophenes and Thiophene 1,1-Dioxides (Update 2024)
Authors: Harris P. A. 
Published: February 2025

AbstractMethods for the synthesis of thiophenes and the less-common thiophene 1,1-dioxides are reviewed in this chapter, covering the period from 2011 to 2022. This is a supplement to both the original Science of Synthesis review (Section 9.10) that covered the literature up to 2000, and the subsequent update covering from 2001 to 2010 (Section 9.10.4). Approximately half the cyclizations to form thiophenes reported during this period involved formation of one C—S and one C—C bond, with the formation of both S—C2 and C3—C4 bonds being the most common.
Squeezing across two harmonic generations utilizing coupled nonlinear waveguide systems
Authors: Zulkifpeli M Z K , Julius R , Ibrahim A-B M A 
Published: February 2025

Abstract
This study investigates the squeezing properties of light across a two-octave system consisting of multichannel single-mode nonlinear waveguides with evanescent coupling. The focus is on the first, second, and fourth harmonics generation. We analyze different input combinations and coupling setups to gain insight into how they impact the level of squeezing. The results show that multiple initial inputs amplify the squeezing effect, while certain initialization setups help maintain squeezing at higher harmonic levels. When the waveguides are fully coupled in the first octave, there is a large increase in squeezing at the first and second harmonic. Reduced coupling leads to a drop in the level of squeezing. At the fourth harmonic frequency, instability is observed in all configurations, which hinders the accurate detection of squeezing. By optimizing the quantity and arrangement of interconnected waveguides, it is possible to improve the nonlinear frequency conversion and thus the level of squeezing. This research may enhance the advancement of quantum optical systems by emphasizing the significance of coupling interactions across two harmonic generations.
An entangled squeezed state generated by an optical parametric amplifier and a beam splitter
Authors: Ren Gang , Zhang Chun-zao 
Published: February 2025

Abstract
We propose a method to generate an entangled squeezed state using an optical parametric amplifier (OPA) and a beam splitter (BS). This device can manipulate the output quantum light field by modulating two parameters: the intensity of the OPA and the transmittance of the optical BS. For the output quantum state associated with a symmetric BS, there is no quadrature squeezing. Moreover, neither photon correlation nor entanglement are observed. However, in terms of sum squeezing, the quantum state corresponding to the symmetric BS is the strongest. Therefore, an asymmetric BS and a highly squeezing OPA are the best choices for generating the quantum entangled squeezed states.
Introduction
Authors: Taylor James 
Published: February 2025

Abstract
The Introduction opens by placing the study of women in finance in historical context. Work on women as investors and as business owners has flourished since the 2000s, which has done much to reframe our understanding of women’s roles in the historical development of capitalism. There has been less research on women as financial intermediaries, however, with the result that the lives and careers of several generations of women working as stockbrokers between the late nineteenth and late twentieth centuries have been overlooked by historians. This book argues that focusing on these financial women yields important insights into histories of women’s work, the strategies of ‘professional closure’ deployed by men against women, and the gendering of financial markets. The Introduction goes on to discuss methodological approaches, including the uses and limitations of ‘additive’ approaches to women’s history, the sources used in the study, and the structure and periodization of the book.