bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association between Antibiotic Use and Subsequent Risk of Breast Cancer: A Nationwide Retrospective Cohort Study in South Korea
Authors: Hong Jaeyi , Park Sun Jae , Park Young Jun , Jeong Seogsong , Choi Seulggie , Chang Jooyoung , Kim Hye Jun , Song Jihun , Ko Ahryoung , Kim Su Gyeong , Han Minjung , Cho Yoosun , Kim Ji Soo , Oh Yun Hwan , Son Joung Sik , Park Sang Min 
Published: December 2024

Abstract
Several studies have revealed a possible association between antibiotic use and breast cancer in the Western population of women. However, its association with the Asian population remains unclear. Data utilized in this nationwide population-based retrospective cohort study were obtained from the Korean National Health Insurance Service database. The study population consisted of 4,097,812 women who were followed up from January 1, 2007, to December 31, 2019. Cox proportional hazards regression was utilized to calculate adjusted hazard ratio (aHR) and 95% confidence interval (CI) for the risk of breast cancer according to cumulative days of antibiotic use and the number of antibiotic classes used. It was discovered that women who used antibiotics for more than 365 days had a higher risk of breast cancer (aHR, 1.15; 95% CI, 1.09–1.21) in comparison with those who did not use antibiotics. In addition, an association was found among women who used five or more classes of antibiotics, showing a higher risk of breast cancer (aHR, 1.11; 95% CI, 1.05–1.17) compared with nonusers. Furthermore, compared with antibiotic nonusers, only users of cephalosporins (aHR, 1.09; 95% CI, 1.02–1.17) and lincosamides (aHR, 1.70; 95% CI, 1.20–2.42) had a higher risk of breast cancer. These findings support epidemiologic evidence that long-term use of antibiotics may be associated with a higher risk of breast cancer. This underscores the need for further studies to address the potential for residual confounding, confirm causation, and elucidate the underlying mechanisms.
Prevention Relevance: This study found a probable duration-dependent association between antibiotic prescriptions and breast cancer risk. The findings indicate that long-term antibiotic use could be associated with an increased risk of breast cancer and highlight the need for further research to confirm causality and mechanisms.
Enhancing prefrontal modulation by phase-locking intermittent theta burst stimulation to a concurrent transcranial alternating current stimulation
Authors: Zimmermann Nadja , Koenig Thomas , Riesen Andrea S. , Morishima Yosuke 
Published: December 2024

Abstract
Theta burst stimulation (TBS) modulates cortical excitability by applying bursts of transcranial magnetic stimulation (TMS) in theta rhythms. Individual responses to TBS vary however greatly due to various factors, such as anatomical differences or the phase of the ongoing oscillatory activity in which TBS pulses are applied. To combat this variability, we exploit the ability of transcranial alternating current stimulation (tACS) to shape the state of cortical excitability in a phase-dependent manner. While cortical excitability is increased at crests of the tACS-induced current, applying the TBS triplet pulses at these crests has the potential to produce larger neuronal responses and thus increase the likelihood of long-term potentiation (LTP). In our randomized sham-controlled study, we focused on enhancing prefrontal cortex excitability by phase-locking intermittent TBS (iTBS) to the crests of an induced 5 Hz tACS current. Twenty-seven healthy participants received two iTBS sessions, once paired with sham-tACS and once with active tACS in a cross-over design. We evaluated effects of our stimulation protocol on cortical excitability by comparing TMS-induced activity and resting-state Microstates in the EEG before and after the stimulation as well as between the two sessions. We found significant effects of iTBS on channel-wise, global, and oscillatory TMS-induced activity, as well as changes in Microstates. The concurrent, phase-locked tACS-iTBS protocol notably decreased the N100 amplitude of the Global Mean Field Power. We also found that baseline TMS-induced oscillatory activity was a key predictor of changes in TMS-related oscillatory activity. In the case of TMS-related gamma oscillations, a significant interaction between our stimulation protocols and baseline activity was observed, indicating that the relationship between baseline and post-iTBS oscillations was strengthened by the concurrent phase-locked tACS-iTBS stimulation protocol. These findings highlight the potential of phase-locked tACS to enhance the effects of iTBS on prefrontal cortical excitability.
Ahead of Evidence: Computer Simulation and Epistemic Risks in Particle Physics
Authors: van Panhuys Marianne , Hillerbrand Rafaela 
Published: December 2024

Abstract
In present-day particle physics, empirical reasoning is highly inferential as experiments rely on complex instruments and an intensive use of computer-based methods. This paper investigates how these methods impact the evidential status of the data produced, using an expanded epistemic risk framework. Based on a case study from a top-quark physics experiment, we clarify the relationship between inductive and other epistemic risks. We argue that various epistemic risks that arise ahead of evidence affect the inductive risk of the experimental results, and propose an understanding of epistemic risk in relation to different epistemic goals. Specifically, the case study shows how experimental tasks and their associated goals relate to the epistemic aim of the experiment, by revealing modalities of risk and risk dynamics throughout the experimental process.
Holmes ⌕ A Benchmark to Assess the Linguistic Competence of Language Models
Authors: Waldis Andreas , Waldis Andreas , Perlitz Yotam , Choshen Leshem , Choshen Leshem , Hou Yufang , Gurevych Iryna 
Published: December 2024

Abstract
We introduce Holmes, a new benchmark designed to assess language models’ (LMs’) linguistic competence—their unconscious understanding of linguistic phenomena. Specifically, we use classifier-based probing to examine LMs’ internal representations regarding distinct linguistic phenomena (e.g., part-of-speech tagging). As a result, we meet recent calls to disentangle LMs’ linguistic competence from other cognitive abilities, such as following instructions in prompting-based evaluations. Composing Holmes, we review over 270 probing studies and include more than 200 datasets to assess syntax, morphology, semantics, reasoning, and discourse phenomena. Analyzing over 50 LMs reveals that, aligned with known trends, their linguistic competence correlates with model size. However, surprisingly, model architecture and instruction tuning also significantly influence performance, particularly in morphology and syntax. Finally, we propose FlashHolmes, a streamlined version that reduces the computation load while maintaining high-ranking precision.
Capturing the Variability of the Nocturnal Boundary Layer through Localized Perturbation Modeling
Authors: Kaiser Amandine , Vercauteren Nikki , Krumscheid Sebastian 
Published: December 2024

Abstract
A single-column model is used to investigate regime transitions within the stably stratified atmospheric boundary layer, focusing on the role of small-scale fluctuations in wind and temperature dynamics and of turbulence intermittency as triggers for these transitions. Previous studies revealed abrupt near-surface temperature inversion transitions within a limited wind speed range. However, representing these transitions in numerical weather prediction (NWP) and climate models is a known difficulty. To shed light on boundary layer processes that explain these abrupt transitions, the Ekman layer height and its correlation with regime shifts are analyzed. A sensitivity study is performed with several types of perturbations of the wind and temperature tendencies, as well as with the inclusion of intermittent turbulent mixing through a stochastic stability equation. The effect of small fluctuations of the dynamics on regime transitions is thereby quantified. The combined results for all tested perturbation types indicate that small-scale phenomena can drive persistent regime transitions from very to weakly stable regimes, but for the opposite direction, no evidence of persistent regime transitions was found. The inclusion of intermittency prevents the model from getting trapped in the very stable regime, thus preventing the so-called “runaway cooling,” an issue for commonly used short-tail stability functions. The findings suggest that using stochastic parameterizations of boundary layer processes, either through stochastically perturbed tendencies or parameters, is an effective approach to represent sharp transitions in the boundary layer regimes and is, therefore, a promising avenue to improve the representation of stably stratified atmospheric boundary layers in NWP and climate models.
Macroeconomic Policy, Wage Gap and Asset Prices: A Dynamic Dependent Economy Model
Authors: Basu Moumita , Nag Ranjanendra Narayan 
Published: December 2024

The role of financial sector in general and macroeconomic policy in particular is a crucial issue in the study of macroeconomic behaviour of developing countries. This article addresses this issue in terms of a dynamic dependent economy model consisting of traded and non-traded sectors. We use perfect foresight and focus on wage gap between skilled and unskilled labour along with unemployment and movement of asset prices. Based on the structure of the model we examine multitude of transmission mechanisms with implications of monetary policy and decrease in oil subsidy. The several cross effects induced by change in system of parameters have their profound bearing on exchange rate, Tobin’s q, wage gap, level of employment and the sectoral composition output. JEL Codes: E31, E63, F32, F41
Evaluation of the therapeutic efficacy of renal artery stenting in patients with atherosclerotic renal artery stenosis
Authors: Shi Qiuyue , Mao Min , Chang Jing , Li Xin , Li Yanwei 
Published: December 2024

Purpose It is currently controversial whether renal artery stenting is beneficial for the clinical outcomes of atherosclerotic renal artery stenosis (ARAS) patients. The study aims to evaluate whether blood pressure (BP) and renal function improve in ARAS patients after stenting. Methods A retrospective study was conducted on 78 ARAS patients who underwent renal artery stenting at the First Affiliated Hospital of Chongqing Medical University from January 2013 to June 2024. BP, the number of oral antihypertensive medications, renal function, and adverse events were analyzed before and after stenting. Results A total of 90 stents were implanted. The median follow-up time was 1.59 years. From 24 hours post-operation, significant decline in BP were observed. During follow-up, systolic BP decreased by 24.27 mmHg (95% CI: 16.54–32.00; P < 0.0001) and diastolic BP by 12.27 mmHg (95% CI: 7.25–17.29; P < 0.0001), but the reduction in the number of oral antihypertensive medications was not significant ( P > 0.05). Serum creatinine also showed a significant decrease of 8.50 μmol/L at follow-up ( P < 0.05). Among the four subgroups, 30 patients with mild renal impaired [eGFR ≥ 60 mL/(min·1.73 m2) and <90 mL/(min·1.73 m2)] showed an increase of 10.68 mL/(min·1.73 m2) in eGFR during follow-up ( P < 0.01), while the eGFR of the remaining 48 patients with other renal function stages showed no significant change before and after stenting. Moreover, 24 patients experienced cardiovascular or/and renal adverse events. Conclusions Renal artery stenting might significantly reduce BP and improve renal function in ARAS patients, particularly those with mild renal impairment, which still requires prospective multicenter studies to confirm.
Coaching stroke survivors to persevere with practice: An observational behavioural mapping study
Authors: Neibling Bridee , Smith Moira , Barker Ruth N , Hayward Kathryn S 
Published: December 2024

Objective To quantitatively describe therapists’ use of coaching with stroke survivors, in a hospital-based rehabilitation setting, to promote perseverance with longer-term practice. Design Prospective observational behavioural mapping study. Setting Rehabilitation unit of a regional public hospital in Queensland, Australia. Main measures A custom-designed behavioural mapping tool was used to collect rehabilitation session contextual data and therapists' use of coaching. Data were captured in 3-minute epochs for a maximum of 30 minutes. Data were analysed using descriptive statistics. Results Thirty-six rehabilitation sessions, including 34 participants (therapists n = 22, stroke survivors n = 12) were observed. Rehabilitation sessions were mostly inpatient ( n = 33, 91.7%), one-on-one ( n = 30, 83.3%), and conducted in the physiotherapy ( n = 160, 45.5%) or occupational therapy ( n = 155, 44.0%) gym. Strategies to promote perseverance were used in 76.7% ( n = 267) of observed epochs. The most frequently used strategy was monitoring the quality of practice and the least frequently used strategy was utilising a support person to facilitate practice. Conclusion Coaching that may promote perseverance with practice was regularly used by therapists during hospital-based rehabilitation sessions. Coaching that may enable longer-term perseverance beyond a therapist-dependent rehabilitation model was less commonly observed.
Analysis of engineering performance of concrete comprising recycled crushed plastic waste and fly ash
Authors: Abirami Thuraisingam , Bandara Chaminda , Yapa Hiran , Dissanayake Ranjith 
Published: December 2024

This study investigated the attributes of blending of recycled crushed polypropylene plastic coarse aggregates (PPCA) and fly ash (FA) towards the fresh and hardened properties of concrete. Natural coarse aggregate was partially replaced with PPCA at volumetric replacement levels up to 30% and cement was replaced with FA up to 20%. Initially, the performance of PPCA and FA in concrete was investigated distinctly. The incorporation of 30% of PPCA in concrete rather impaired the workability (from 95 mm – 50 mm: 47%) and the compressive strength (from 44.6 MPa to 31.4 MPa: 29.7%). By appropriate using of a superplasticizer, the loss in the workability could be recovered. Microstructural investigation was conducted employing scanning electron microscope analysis; it showed that the formation of a weak interfacial transition zone between PPCA and cement paste to be the reason for strength reduction in PPCA concrete. In contrast, the addition of 10 – 20% of FA in concrete improved the workability by 63.2% – 100%, but yet again, the 28-day compressive strength reduced by 15.8 – 35.6%. Meanwhile, thermal conductivity results and constitutive relationships proved that the use of PPCA enhanced the thermal insulation property and ductility of PPCA concrete, respectively. Eventually, a total of six concrete batches with binary blended PPCA and FA were cast to find the optimum replacement levels. The optimum binary combination with reasonable strength and workability at a minimal cost was achieved to be 10% PPCA and 20% FA.
Enhancing brain tumor classification by integrating radiomics and deep learning features: A comprehensive study utilizing ensemble methods on MRI scans
Authors: Yin Liang , Wang Jing 
Published: December 2024

Background and objective This study aims to assess the effectiveness of combining radiomics features (RFs) with deep learning features (DFs) for classifying brain tumors—specifically Glioma, Meningioma, and Pituitary Tumor—using MRI scans and advanced ensemble learning techniques. Methods A total of 3064 T1-weighted contrast-enhanced brain MRI scans were analyzed. RFs were extracted using Pyradiomics, while DFs were obtained from a 3D convolutional neural network (CNN). These features were used both individually and together to train a range of machine learning models, including Support Vector Machines (SVM), Decision Trees (DT), Random Forests (RF), AdaBoost, Bagging, k-Nearest Neighbors (KNN), and Multi-Layer Perceptrons (MLP). To enhance the accuracy of these models, ensemble approaches such as Stacking, Voting, and Boosting were employed. LASSO feature selection and five-fold cross-validation were utilized to ensure the models’ robustness. Results The results demonstrated that combining RFs and DFs significantly improved the model's performance compared to using either feature set alone. The best performance was achieved using the combined RF + DF approach with ensemble methods, particularly Boosting, which resulted in an accuracy of 95.0%, an AUC of 0.92, a sensitivity of 88%, and a specificity of 90%. Conversely, models utilizing only RFs or DFs showed lower performance, with RFs reaching an AUC of 0.82 and DFs achieving an AUC of 0.85. Conclusion The integration of RFs and DFs, along with advanced ensemble methods, significantly improves the accuracy and reliability of brain tumor classification using MRI. This approach shows strong clinical potential, with opportunities for further enhancing generalizability and precision through additional MRI sequences and advanced machine learning techniques.
Detection of motor nervous disease using deep learning based Duple feature extraction network
Authors: S Sony Helen , S Joseph Jawhar 
Published: December 2024

Background A motor nervous disease (MND) is a debilitating nervous disease that affects motor neurons that regulates the muscular voluntary movements. The disease gradually destroys parts of the neurological system. Generally, MND develops owing to a grouping of genetic, behavioural, and natural features. Objective However, early detection of MND is challenging and manual identification requires a lot of time. Therefore, automated methods like deep learning structures are needed to detect MND quickly and more accurately than manual classification. In this work, a novel deep learning-based Duple feature extraction network is proposed for identifying MND in its early stages. Methods Initially, the input DTI images are pre-processed utilizing a Gaussian adaptive bilateral filter (GAB) to improve the quality of the image. Then the pre-processed DTI images are fed into the dual feature extraction phase for colour and structural conversion. The Colour Information Feature (CIF) with Local and Global sampling (LOG) is integrated into the LinkNet module to extract colour features. Moreover, the Local Binary Pattern (LBP) with Edge sampling models is integrated into the MobileNet module to extract edge features. Afterward, the extracted colour and texture features of images are flattered and given as the input to a Deep Neural Network for classifying the MND levels. Results From the test results, the proposed Duple feature extraction network has yielded a 99.62% accuracy rate. The proposed DNN improves its F1-score by 1.32%, 2.1%, and 3.18% better than FNN, GNN, and GRU respectively. The proposed Duple-feature extraction network improves overall accuracy by 6.15%, 5.56%, 5.96%, and 6.68% compared to CNN, SVM-RFE, MLP, and Tri-planar CNN respectively. Conclusion The novel deep learning-based Duple feature extraction framework shows promising results in early detection of motor nervous disease, significantly improving accuracy and f1-scores compared to existing models.
Management of Persistent Hypernasality After Pharyngeal Flap: A Novel V-to-Y Revision Procedure to Tighten the Lateral Ports
Authors: Best David L. , Yau Vicky , Mañon Victoria , Noto Shannon , Perry Robert J. 
Published: December 2024

Velopharyngeal insufficiency (VPI) is common in patients with a repaired cleft palate. 18% to 20% of patients who undergo superiorly based pharyngeal flap for VPI may require a revision procedure due to persistent hypernasality. One solution to persistent VPI is flap revision, but there is a paucity of revision techniques described in the literature. We present a novel technique for pharyngeal flap revision utilizing a V-to-Y procedure to tighten the lateral pharyngeal ports.
Outcome reporting in studies on critically ill obstetric patients: A systematic review
Authors: Viau-Lapointe Julien , Kfouri Julia , Thompson Mary , Ashraf Rizwana , D’Souza Rohan , Lapinsky Stephen 
Published: December 2024

Introduction This systematic review is the first step in the process of standardizing outcome reporting through the development of a core outcome set for research on critically ill obstetric patients (COSCO). Methods A five-database search was performed to identify randomized and non-randomized studies published before November 2017, on patients admitted to intensive care or high-dependency units during or immediately after pregnancy. Reported outcomes were categorized into domains and definitions were documented. Results Of the 12,581 citations reviewed, 136 studies were included. The most reported outcome domains were maternal all-cause mortality ( n = 128, 94.5%), resource use ( n = 116, 85.6%), and clinical/physiological outcomes ( n = 111, 82.8%). Outcomes related to functioning/life impact and adverse effects of treatment were only reported in four (2.9%) studies. There was inconsistency in outcome definitions. Conclusions This review identified considerable variation in outcome reporting and definitions and generated an outcome list to consider in COSCO development.
Assessment of genetic diversity and population structure of Corema album accessions from the Atlantic coastal dunes of Portugal
Authors: Brás de Oliveira Pedro , Varela Ana Rita , Silva Maria José , Guimarães Joana Bagoin , Valdiviesso Teresa , Trindade Cândida Sofia , Nóbrega Filomena 
Published: December 2024

Background Corema album, a wild shrub endemic to the Atlantic coastal dunes of Iberian Peninsula, has important ecological and medicinal value. Corema album has been listed as an endangered plant due to threats associated with anthropogenic events. Conservation of the species is therefore critically important. Objective The aim of this study was to assess the genetic diversity and population structure of four well-characterized populations to support pre-breeding programs aimed at enhancing species knowledge for a future berry crop culture, with the ultimate goal of protecting and conserving the threatened species C. album. Methods The set of 128 C. album accessions was genotyped using six EST-SSR primers and one genomic-SSR primer. Results A total of 65 alleles were obtained with a mean of 9.285 alleles per locus. The genetic diversity was found to be high, with mean values of observed heterozygosity ( Ho) and expected heterozygosity ( He) at 0.594 and 0.756, respectively. Moderate genetic differentiation among populations (FST = 0.095) was observed. STRUCTURE analysis and multivariate analyses roughly categorized the accessions into a complex mixed group. The STRUCTURE analysis revealed no correlation between genetic structure and geographical distribution; however, it facilitated the identification of pure accessions within each population. Conclusions The results aid in the understanding the population structure and genetic diversity and are crucial to optimize conservation strategies as well as the utilization of genetic resources of C. album for a deeper genetic study of the species.