bluuebunny/crossref_metadata_2025_split huggingface dataset:
Potency–Magnitude Scaling Relations and a Unified Earthquake Catalog for the Western United States
Authors: Trugman Daniel T. , Ben-Zion Yehuda 
Published: September 2024

Abstract
Quantifying the size of earthquakes is a foundational task in seismology, and over the years several magnitude scales have been developed. Of these, only scales based on seismic moment or potency can properly characterize changes in event size without saturation. Here, we develop empirical potency–magnitude scaling relations for earthquakes in the western United States, allowing us to translate instrumental magnitude estimates into uniform measures of earthquake size. We use synthetic waveforms to validate the observed scaling relations and to provide additional insight into the differences between instrumental and physics-based magnitude scales. Each earthquake in our catalog is assigned a clustering designation distinguishing mainshocks from triggered seismicity, along with a potency-based magnitude estimate that is comparable to moment magnitude and that can be easily converted into other magnitude scales as needed. The developed catalog and associated scaling relations have broad applications for fundamental and applied studies of earthquake processes and hazards.
A clinical prospective study on the surgical management of zygomatico-maxillary complex fractures using two-point fixation
Authors: Reddy Kora Ramya , Abhinandan Patel K N , Girish G , Sneha TR , Nikhila G 
Published: September 2024

The ZMC fractures are one of the most frequently occurring maxillofacial injuries due to its prominence and facial contour. The ZMC forms a principle buttress of face and helps transmit occlusal forces to skull base. Fracture of zygomatic bone leads aesthetic and functional deformity. Restoration to premorbid condition is most predictable by ORIF. In this study was to evaluate efficacy of two-point internal fixation using conventional miniplates and screws for ZMC fractures. 35 patients with established unilateral isolated ZMC fractures were operated using two-point fixation method i.e. the maxillary buttress and the fronto-zygomatic suture, followed up for 3 months. Patients were assessed clinically and radiographically at different follow up intervals. Charts of patients were reviewed for age, gender, etiology, malar height analysis and vertical dystopia. 35 patients in this study, underwent ORIF under GA with two-point fixation. Preoperatively, mean malar height of the patients recorded was 66.55 ± 3.02. There was a significant increase in malar height postoperatively (P &#60; 0.0001). 70.24 ± 2.05, at 1st week, and 69.87 ± 1.98. in 3rd and 6th weeks. Preoperatively, mean vertical dystopia of patients was 2.24 ± 0.71. Postoperative resolution of vertical dystopia was statistically significant (P&#60;0.0001), with value of 0.52 ± 0.52.Integrity of ZMC is important in maintenance of normal facial width and prominence of cheek. Two‑point fixation shows satisfactory results functionally, esthetically and also provides additional advantage by eliminating another surgical site. Thus we conclude that our study provides a basis for further research.
Nasal Symptoms of Chronic Rhinosinusitis Were Related to Its Nasoendoscopic Findings: A Retrospective Cohort Study at Dr. Soetomo General Academic Hospital, Surabaya
Authors: Chandra Christopher Marcellino , Kristyono Irwan , Soegiarto Gatot , Nugroho Puguh Setyo 
Published: September 2024

Highlights:

Nasal congestion was the most common symptom presented in CRS patients.
Nasal symptoms of CRS were positively associated with nasoendoscopic findings.

Abstract
Introduction: Chronic rhinosinusitis (CRS) is often encountered in Indonesia. Nasal endoscopy, or nasendoscopy, is considered the gold standard for assessing the severity of CRS. However, as nasendoscopy is unavailable in Indonesia, only symptom assessments can be conducted at primary healthcare facilities. This study aimed to elucidate the relationship between nasoendoscopic findings based on the Lund-Kennedy score (LKS) and symptoms in CRS patients based on the visual analogue scale (VAS) score.
Methods: This retrospective analytic study evaluated CRS cases identified in the Ear, Nose, and Throat (ENT) Outpatient Clinic of Dr. Soetomo General Academic Hospital, Surabaya, from July 2021 to July 2022. Statistical analysis was conducted using Spearman’s rank correlation test to identify the correlation (R-value) between LKS and the VAS score. Statistical significance was achieved if p-value <0.05. All statistical tests were conducted using the International Business Machines Corporation (IBM) Statistical Package for the Social Sciences (SPSS) version 26.0 for Windows.
Results: A total of 57 CRS patients were included in this study, mostly females (64.9%) and those aged 50–59 years old (26.9%). Nasal congestion was the dominant nasal symptom (80.7%), with mostly moderate symptom severity (VAS 4-7) reported. Across both nasal cavities, the most frequent nasoendoscopic finding among CRS patients was nasal edema (82.4% and 93%). A positive and weak correlation existed between the total VAS score of all symptoms and the total LKS of both nasal cavities (r = 0.387, p < 0.05).
Conclusion: The nasal symptoms of CRS patients were significantly associated with its nasoendoscopic findings.
The diagnostic odyssey, clinical burden, and natural history of Barth syndrome: an analysis of patient registry data
Authors: Kenneson Aileen , Huang Yonglin , Lontok Erik , Marjoram Lindsay 
Published: September 2024

Aim: Barth syndrome (BTHS; OMIM 302060) is an ultra-rare, complex, multi-system X-linked disorder that arises from pathogenic mutations in the gene TAFAZZIN . BTHS is characterized by cardiomyopathy, skeletal myopathy, muscle weakness, and neutropenia. To better understand the natural history and lived experience of affected individuals, the Barth Syndrome Foundation maintains the patient-inputted Barth Syndrome Registry and Repository (BRR).
Methods: Available cross-sectional and longitudinal participant data (n = 115) were analyzed to illustrate the diagnostic odyssey, manifestations, and healthcare utilization across a broad range of affected individual age groups.
Results: Individuals who experienced cardiomyopathy or heart failure as the first manifestation had the shortest times to diagnosis compared to less appreciated manifestations (e.g., frequent infections, poor muscle tone, growth delay). The most frequently reported manifestations across all ages were due to cardiac disorders (80.7%), gastrointestinal (GI) disorders (68.7%), neutropenia or frequent infections (67.2%), and fatigue (60.9%), with 47.1% of participants scoring in the moderate-to-severe range of the Patient-Reported Outcomes Measurement Information System (PROMIS) Fatigue Short Form 8A survey. Participants saw, on average, 3.6 specialists in the previous year, with cardiologists (97.9%) and hematologists (58.2%) being the most commonly seen specialists.
Conclusion: The data suggest that cardiac disorders are the most common manifestations of BTHS, but also reveal a high frequency of feeding and GI-related issues that previous reports have not captured. Physician-targeted education on the lesser-known symptoms and population-based screening for BTHS may aid in timely diagnosis and improved clinical management.
FiCo-ITR: bridging fine-grained and coarse-grained image-text retrieval for comparative performance analysis
Authors: Williams-Lekuona Mikel , Cosma Georgina 
Published: September 2024

Abstract

In the field of Image-Text Retrieval (ITR), recent advancements have leveraged large-scale Vision-Language Pretraining (VLP) for Fine-Grained (FG) instance-level retrieval, achieving high accuracy at the cost of increased computational complexity. For Coarse-Grained (CG) category-level retrieval, prominent approaches employ Cross-Modal Hashing (CMH) to prioritise efficiency, albeit at the cost of retrieval performance. Due to differences in methodologies, FG and CG models are rarely compared directly within evaluations in the literature, resulting in a lack of empirical data quantifying the retrieval performance-efficiency tradeoffs between the two. This paper addresses this gap by introducing the \texttt{FiCo-ITR} library, which standardises evaluation methodologies for both FG and CG models, facilitating direct comparisons. We conduct empirical evaluations of representative models from both subfields, analysing precision, recall, and computational complexity across varying data scales. Our findings offer new insights into the performance-efficiency trade-offs between recent representative FG and CG models, highlighting their respective strengths and limitations. These findings provide the foundation necessary to make more informed decisions regarding model selection for specific retrieval tasks and highlight avenues for future research into hybrid systems that leverage the strengths of both FG and CG approaches.
Cold and humid climatic conditions over the last millennium decreased the carbon accumulation in peatlands of the subtropical monsoon region
Authors: Liu Hanxiang 
Published: September 2024

Abstract

Carbon accumulation in most northern peatlands is generally positively correlated with temperature under natural climate change. In the subtropical monsoon region of China, the climate differs from that of most northern peatlands, where a significant number of peatlands have developed in mountainous areas. However, it remains unclear how the carbon dynamics of these subtropical peatlands respond to climate change. Here, we reconstructed the net carbon fluxes of a typical mountainous peatland in Tianmu Mountain, eastern China, over the past millennium. Climate records in the subtropical monsoon zone indicate fluctuating and declining temperatures alongside increasing humidity over the past thousand years. Drought and higher winter temperatures have facilitated the terrestrialization of waterlogged depressions and triggered the peatland formation in this region. The net carbon accumulation in the peatland has generally shown a downward trend due to the progressively decreasing winter temperature and increasing humidity. When winter temperatures decrease, the growing season for vegetation is shortened, resulting in less litter production and reduced carbon accumulation. Increased humidity leads to greater surface waterlogging and prolonged flooding of surface vegetation, which hampers vegetation growth, reduces litter production, and consequently lowers carbon accumulation. Despite the decline in carbon accumulation over the last millennium, the peatland’s net carbon balance remains in a 'carbon sink' state. This suggests that the risk of carbon release from the peatland carbon pool under natural climate change conditions is not substantial in the subtropical monsoon area.
A neural network-based modeling approach for transient performance prediction of gas turbine engines
Authors: Wu Xiaohua , Hu Xiaoan , Xiang Xin , Lin Shengzhi 
Published: September 2024

Abstract

Considering the difficulties in obtaining the specific component maps and highly iterative performance requirements when analyzing the transient performance, modeling the transient process is quite a complicated task. With few but sufficient experimental data, this study establishes the dataset-driven neural network models to predict thrust and exhaust gas temperature for the transient process of gas turbine engines. In addition, the transient parameters calculated from GasTurb13 common models are performed. Three neural network models, including convolutional neural network (CNN), long-short term memory neural network (LSTM), and CNN-LSTM, are built, trained, and tested. Compared with the numerical and experimental results, the LSTM model established in this research has a quite significant performance and an ability for forecasting the key parameters by inputting the other relevant parameters. According to the overall validation analysis, the recommended method could donate accurate results using few experimental data and small hardware resources, demonstrating awesome potential that completes the intelligent control of the aircraft and engine, and evaluates the dangerous influence of transient mechanical stress.
Establishment and Characterization of Three Gemcitabine-Resistant Human Intrahepatic Cholangiocarcinoma Cell Lines
Authors: Li Jiandong , Hu Yanxin , Zhang Jiayao , Zhang Weiguang , Yu Jianhua , Lu Baochun 
Published: September 2024

Abstract

Intrahepatic cholangiocarcinoma (ICC) is a highly malignant liver tumor associated with a dismal prognosis, largely due to chemotherapy resistance. However, the mechanisms underlying gemcitabine (GEM) resistance in ICC remain poorly understood. In this study, we established three GEM-resistant cell models and evaluated their resistance by assessing cell proliferation, cell cycle arrest, and DNA damage. The results disclosed that GEM-resistant cells exhibited significant tolerance to GEM-induced growth inhibition, reduced cell cycle arrest, and decreased DNA damage compared to parental cells. We then explored potential resistance mechanisms and found that pathways and targets such as EMT, PI3K/Akt, p53R2, and IGF-1R did not show a significant correlation with ICC resistance. Interestingly, our findings suggested that reactive oxygen species (ROS) might promote GEM resistance in ICC. In conclusion, we characterized a GEM-resistant ICC model, which can be employed to investigate alternative resistance mechanisms and explore new treatment approaches.
Kinetic Liquid Metal Synthesis of Flexible 2D Conductive Oxides for Multimodal Wearable Sensing
Authors: Rahman Md Saifur , Agnew Simon A. , Ong Samuel , Scheideler William J. 
Published: September 2024

Abstract

Transparent conducting oxides (TCOs) are crucial for high-performance displays, solar cells, and wearable sensors. However, their high process temperatures and brittle nature have hindered their use in flexible electronics. We report an approach to overturn these limitations by harnessing the physics Cabrera Mott native oxidation to fabricate large-area, two-dimensional transparent electrodes via liquid metal printing. Our robotic, solvent-free and vacuum-free process deposits ultrathin (2–10 nm thick) 2D indium tin oxide (ITO) with exceptional flexibility, high transparency (> 95%) and superior conductivity (> 1300 S/cm) for wearable bioelectrodes. In a significant advance over previous work, we utilize hypoeutectic In-Sn alloys to print 2D ITO at < 140 ºC on flexible polymers. Our detailed materials characterization and microscopy reveal the efficacy of Sn-doping and high crystallinity with large, platelike grains formed by the liquid metal reaction environment. The ultrathin nature of 2D ITO yields significant enhancement to bending strain tolerance, scratch resistance exceeding durability of traditional PEDOT, and low contact impedance to skin comparable to Ag/AgCl. Finally, we utilize the conductivity and transparency of 2D ITO for synchronous, multimodal measurements via electrocardiography (ECG) and pulse plethysmography (PPG). This order-of-magnitude improvement to printed TCOs could enable new wearable biometrics and display-integrated sensors.
Exploring the Thermal and Mechanical Properties of Semi Metallic XCr₂S₄ (X: Ag, Au) Monolayers
Authors: Tagani Meysam Bagheri 
Published: September 2024

Abstract

The synthesis of non-layered two-dimensional materials is crucial due to the ability to precisely control their composition and structural features. Recently, a non-layered two-dimensional material with the empirical formula AuCrS₂ was synthesized [Nano Letters, 24 (2024) 2308]. Inspired by this experimental report, we predict two thermodynamically and dynamically stable two-dimensional materials with the empirical formula XCr₂S₄ (X=Ag, Au) using density functional theory. These materials are semi-metallic and exhibit high mechanical resistance, with a Young's modulus of 200 N/m. Utilizing machine learning, we calculated the phonon thermal conductivity of these materials. At room temperature, their thermal conductivity is approximately 45 W/mK, indicating a lower phononic thermal conductivity compared to transition metal dichalcogenide monolayers and Maxene. Given their semi-metallic nature, we also investigated their electronic thermal conductivity by calculating the transmission coefficient in the linear response regime. Our findings indicate that the electron contribution to heat transfer is about 5%. The combination of high mechanical flexibility, semi-metallic nature, and low thermal conductivity suggests these materials have significant potential for use in rechargeable ion batteries, electrodes, and sensors.
Association of a high-protein and low-glycemic-index diet during pregnancy with offspring growth and obesity until the age of 18 years – a target trial emulation
Authors: Mogensen Christina , Mølgaard Christian , Magkos Faidon , Geiker Nina , Bjerregaard Anne , Granström Charlotta , Halldorsson Thorhallur , Olsen SF 
Published: September 2024

Abstract

Background
Maternal pre-pregnancy BMI and excessive gestational weight gain (GWG) are associated with offspring obesity. Moreover, maternal dietary patterns, particularly protein intake and glycemic index, influence GWG and fetal development. This study aimed to investigate the association of a high-protein, low-glycemic-index (HPLGI) diet during pregnancy with offspring growth and obesity.
Methods
Using observational data from the Danish National Birth Cohort, a target trial emulation was conducted to investigate the association of an HPLGI diet during pregnancy on offspring growth up to 18 years of age. A cohort of 17,551 women who met the inclusion criteria were categorized into exposure groups based on their protein intake and glycemic index to emulate the groups in the APPROACH trial.
Results
Offspring outcomes were assessed at various ages and a linear mixed model was used including potential confounders. Offspring born to women following an HPLGI diet during pregnancy had 2.59 kg higher body weight and 0.72 kg/m2 higher BMI at 18 years compared to those from the moderate-protein, moderate-glycemic-index (MPMGI) group. Maternal characteristics varied between the exposure groups, with the HPLGI women exhibiting 1.67 kg higher pre-pregnancy weight and 0.49 kg/m2 BMI, with no differences in GWG.
Conclusion
Offspring born to women consuming an HPLGI diet during pregnancy had higher body weight and BMI at 18 years compared to offspring born to women on an MPMGI diet. These findings raise questions about the long-term implications of maternal dietary patterns on offspring health. Further research is needed to elucidate the mechanisms underlying these associations.
Prevalence of Intestinal Parasitic Infections and Associated Risk Factors Among Patients Attending Dejen Primary Hospital, Amhara National Regional State, Ethiopia
Authors: Demissie Simachew , Ameha Eyouel , Tigu Fitsum 
Published: September 2024

Abstract

Intestinal parasitic infections (IPIs) are the greatest worldwide cause of illness and disease. About 1.5 billion individuals have been infected by IPIs in 2023, of these the lion shares of the burden is found in Sub-Saharan African regions. This study aimed to assess the prevalence of IPIs and associated risk factors among patients attending Dejen primary Hospital. The study was conducted in the Amhara National Regional State of Ethiopia, East Gojjam Zone, Dejen town, Dejen primary hospital. Patients in all age groups attending the hospital during the study period were included in the study. A total of 414 study participants were determined by standard formula. The socio-demographics characteristics were collected by face-to-face interview using well-structured questionnaires. Stool samples were examined microscopically using a direct wet mount method. In this study, five known parasites identified including Entamoeba histolytica, Giardia lamblia, Hookworm, Taenia spp. and Strongyloides stercoralis. Among them, E. histolytica and G. lamblia belonged to the leading protozoan parasites with 26.1 and 9.2% prevalence, respectively. The rest, Hookworm, Taenia spp. and Strongyloides stercoralis, categorized as soil helminthic parasites and accounts 3.1, 0.7 and 0.2% prevalence, respectively. The prevalence of IPIs in the study area is highly associated with the occupation of the patients, consumption of raw vegetables, swimming practice in rivers and source of drinking water.
Broken Tooth Gear Fault Detection Using Vibration Signals Based on Convolutional Neural Network
Authors: Goswami Priyom , Rai Rajiv Nandan 
Published: September 2024

Abstract

Gear faults are a major concern in industrial settings, leading to performance degradation and potential system failures. This paper explores the use of Convolutional Neural Networks (CNNs) for broken tooth fault detection in gear systems. Traditional methods for fault detection rely on manual feature extraction from vibration signals, which can be time-consuming and may not capture all relevant information. CNNs, on the other hand, can automatically learn complex patterns from data, making them well-suited for this task. In this paper we develop a computationally tractable deep learning (DL) based CNN model that can be used for broken tooth fault diagnosis in various industrial settings, irrespective of the type of gearbox or gears being used. The authors further compare the performance of developed CNN model with traditional signal processing techniques and Support Vector Machine (SVM)-based classification. The CNN model achieved superior accuracy (98.6%) in distinguishing between broken and healthy teeth across various operating conditions for one experimental setup. For a second setup with a less severe broken tooth fault, the accuracy was 93%. In contrast, SVM models achieved a maximum accuracy of 90.7% using manually selected features. These findings underscore the superiority of the proposed deep learning (DL) based CNN model for broken teeth gear fault detection. Moreover, it exhibits greater resilience to fluctuations in operating conditions and fault types compared to conventional techniques. Comparisons with established deep learning models such as VGG16, AlexNet etc. demonstrate that the proposed model surpasses all others in terms of classification accuracy.