bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of Bone Mineral Density And Treatment Initation Among Treatment-Naive Post-Menopausal Women with Distal Radius Fracture and Without: A Case-Control Study from Southern Europe
Authors: Giannatos Vasileios , Tatani Irini , Stathopoulos Konstantinos , Argyropoulou Evangelia , Galanos Antonios , Panagopoulos Andreas 
Published: February 2025

Abstract

Objectives
To compare bone mineral density (BMD), FRAX scores, comorbidities, risk factors and biochemical blood markers among postmenopausal women with distal radius fractures and those without such fractures.
Materials and Methods
63 postmenopausal women with distal radius fractures were compared to 64 postmenopausal women with no history of fractures. Primary objectives included comparing BMD at the femoral neck and lumbar spine, as well as FRAX scores between the two groups. Secondary goals involved assessing comorbidities, risk factors, and biochemical blood markers (Ca + 2, albumin, PTH, VItD) between the two groups.
Results
BMD and T-scores for the hip and lumbar spine were compared between groups, revealing no statistically significant differences. However, FRAX scores (Major & Hip) differed significantly in the fracture group (p = 0.005), aligning with expectations that a previous fracture elevates the FRAX risk for future fractures. Biochemical markers were similar between the two groups, except for Vitamin D. Among risk factors and comorbidities, only multi-drug regimens and epileptic seizures were significantly higher in the fracture group.
Conclusion
Our study found similar BMD between the two groups. Nonetheless, a lower FRAX in the fracture group necessitates increased consideration for osteoporosis treatment. Multiple-drug regimens and lower vitamin D levels were also linked to the fracture group.
Optimizing and Predicting Track Quality in Multilayer Laser Melting of Inconel 718: A Numerical, Experimental and Machine Learning Approach
Authors: KURIAN ANTONY , JOSE BIBIN , VARGHESE JINA , SHAH ADITHYA BHARATH , ANTONY GEORGE , CHRIS V S , AHAMMAD YASEEN 
Published: February 2025

Abstract

In this paper multilayer fabrication of Inconel 718 using SLM, a widely used additive manufacturing technique was conducted. The quality of the fabricated tracks is dependent on laser power, scanning speed and beam diameter. The effects of these parameters during SLM process were investigated by numerical analysis as well as by experimentation to determine the optimized set of parameters. However, process optimization using experimentation and simulation is expensive as well as time consuming. Therefore, in addition, two machine learning models have been trained to predict the width and height of the fabricated tracks based on the parameters. By numerical analysis, the variation in temperature distribution was determined by varying these parameters and the effect of these parameters was validated experimentally. The effect of these parameters on the geometry, morphology of the track was analyzed by utilizing tools such as macroscope, SEM and EDAX. Among the two ML models, linear regression models demonstrated superior predictive accuracy with less error compared to RNN models.
A Novel Approach to Glaucoma Detection: Leveraging Fourier Transform, Structural Similarity Index, and Self-Supervised Learning
Authors: Frasca Maria , Lin Jianyi , Torre Davide La 
Published: February 2025

Abstract

Glaucoma is one of the leading causes of irreversible blindness worldwide, affecting millions of people each year. Early diagnosis is crucial to prevent vision loss, but the often asymptomatic nature of the disease and the complexity of clinical signs make timely detection challenging. Advanced ocular imaging technologies, such as optical coherence tomography and fundus photography, offer new diagnostic opportunities but generate complex and voluminous data requiring significant expertise for interpretation. Artificial intelligence (AI) is revolutionizing this field, enabling efficient data analysis and supporting physicians in early risk identification and disease monitoring. In this article, we present a comprehensive approach that combines advanced image preprocessing techniques with artificial intelligence (AI) models to enhance the diagnostic accuracy of glaucoma. Using the REFUGE2 dataset, we implemented the Discrete Fourier Transform (DFT) for image preprocessing, leveraging the Fast Fourier Transform (FFT) algorithm for computational efficiency. This approach effectively preserved visual features, achieving SSIM values of 0.9225 for training, 0.8637 for validation, and 0.8247 for testing. For classification, we employed various models, including Masked Image Modeling (MIM) and Masked Autoencoder (MAE), combined with self-supervised learning techniques such as SimCLR. This multi-model approach allowed us to explore different perspectives in image analysis, achieving an accuracy of 90.06\% with MIM and 90.14\% with MAE on preprocessed images, surpassing the results obtained with non-preprocessed data. Moreover, the MIM model demonstrated a strong discriminative capability, highlighted by an AUC-ROC of 0.9298, a precision of 0.8154, and an F1-score of 0.6998. The results show that combining advanced preprocessing with Transformer neural networks can significantly improve efficiency and diagnostic accuracy in the early detection of glaucoma. This approach offers a scalable and robust method for disease management, contributing to improvements in traditional clinical practices.
Cross-sectional area of posterior extensor muscles of cervical spine in asymptomatic subjects: a 20-year longitudinal MRI study
Authors: Izumida Hiroyuki , Daimon Kenshi , Umezawa Hitoshi , Michikawa Takehiro , Fujiwara Hirokazu , Okada Eijiro , Nojiri Kenya , Katoh Hiroyuki , Shimizu Kentaro , Ishihama Hiroko , Nakamura Masaya , Matsumoto Morio , Watanabe Kota 
Published: February 2025

Abstract

Few studies have investigated long-term changes in the posterior extensor muscles of the cervical spine in healthy subjects. Therefore, we used MRI to investigate changes in the posterior extensor muscles in healthy subjects over 20 years. The subjects of this study were 55 volunteers with an average follow-up period of approximately 20 years. The axial images of the C3/4, C4/5, and C5/6 levels from the initial scan and scans taken 20 years later were evaluated and compared for the following: the cross-sectional areas (CSAs) of the multifidus, semispinalis cervices, semispinalis capitis, and splenius capitis muscles, along with left-right differences, gender differences, influence of age, and muscle fatty degeneration of each muscle. The mean CSAs of the posterior extensor muscles significantly increased at C3/4 and significantly decreased at C5/6 over 20 years. The CSA of posterior cervical extensor muscles always tended to be greater on the left side than on the right side and was significantly larger in men than in women at all levels. The fatty degeneration increased significantly at all intervertebral levels. The decrease in the CSA was significantly associated with smoking status (relative risk: 2.19, 95% confidence interval: 1.32–3.63, p < 0.01), but not with clinical symptoms.
Biomechanical Finite Element Analysis of Short and Long Implants In Resorbed Maxillary Posterior Region
Authors: Dinçer Nisa Nur , Dinçer Ammar Tarık , Öncü Elif 
Published: February 2025

Abstract

Objectives
This study aimed to analyze different implant treatment concepts in maxillary posterior region. The effects of using short or long implants, with or without bone graft, are investigated in terms of strength and integrity.
Materials and Methods
Three different 3D models were generated from a CBCT scan: SI (short implant), LISG (long implant after sinus lifting with graft) and LIS (long implant after sinus lifting without graft). After integrating necessary implant parts, models were analyzed by FEM. The resultant stress values in the cortical and cancellous bones are evaluated by applying vertical and oblique forces. Implant parts are also investigated in terms of integrity and stability. Treatment concepts are compared depending on the FEA results.
Results
FEA demonstrated that short implants resulted in higher stress concentrations within the peri-implant bone compared to long implants. The maximum principal stress values in cortical bone were 100 MPa (tensile) and 133 MPa (compressive), while cancellous bone exhibited 14 MPa (tensile) and 16 MPa (compressive), all within physiological limits. Long implants, with or without grafts, significantly reduced stress levels compared to short implants. There were significant reductions for both compression and tensile stresses in the long implant concepts. Stress distribution patterns indicated that oblique loading led to increased palatal stress concentration.
Conclusions
Although the stresses occurring in the short implant concept are higher under both masticatory loading conditions, the results obtained for both short and long implant concepts remain within physiological limits where the bone can maintain its continuity without deformation.
Clinical Relevance
Short implants are biomechanically viable alternatives when augmentation is not feasible, provided that stress thresholds remain within safe limits.
The Molecular Landscape of Non-functional Parathyroid Carcinoma
Authors: Jentus Maaia Margo , Corver Willem E , Snel Marieke , Haalen F. M. , Wezel Tom , Ruano Dina , Kapiteijn Ellen , Crobach Stijn , Appelman-Dijkstra Natasha M , Schepers Abbey , Morreau Hans 
Published: February 2025

Abstract

Non-functional parathyroid carcinoma (NFPC) is an exceptionally rare malignancy, with ± 50 reported cases since the description of the parathyroid glands in late 19th century. Unlike functional parathyroid carcinomas (PC), which present with extreme hyperparathyroidism (HPT) and are monitored using calcium and parathyroid hormone (PTH) levels, monitoring of patients with non-functional parathyroid carcinoma only relies on imaging. In this study, we present two novel cases of primary NFPC, alongside a comprehensive review of the literature including a detailed analysis of immunohistochemical and molecular testing. We discuss the potential causes of a non-functional state in PC. One primary NFPC showed no immunohistochemical PTH expression, however low positive PTH mRNA expression was repeatedly detected in the tumor. Furthermore, medullary thyroid carcinoma, non-medullary thyroid carcinoma, paraganglioma or other head and neck tumors were excluded. The second case showed patchy residual PTH expression immunohistochemically. Both tumors exhibited extensive whole chromosome losses, a near-haploid genome and subsequent endoreduplication/genome doubling. The diagnosis of primary non-functional parathyroid carcinoma PC can be challenging, especially in cases with negative PTH immunohistochemical staining.
Protein profiling of extracellular vesicles from the cerebrospinal fluid of patients with multiple sclerosis
Authors: Iwahara Naotoshi , Muraoka Satoshi , Saito Taro , Hirano Masayo , Yokokawa Kazuki , Tanemoto Masanobu , Oda Ryosuke , Nonaka Takayuki , Suzuki Shuuichirou , Adachi Jun , Hisahara Shin 
Published: February 2025

Abstract

Background
Extracellular vesicles (EVs) are membrane-bound particles that are released into the extracellular space and are thought to play a role in the pathogenesis of neuroinflammation and neurodegeneration. Nevertheless, the precise role of these vesicles in the context of multiple sclerosis (MS) remains uncertain. The objective of this study was to identify the distinctive characteristics of EVs associated with MS
Methods
EVs were isolated from CSF using phosphatidylserine affinity methods. Mass spectrometry was used to analyze cerebrospinal fluid (CSF) samples and EVs isolated from those CSF samples collected from a discovery cohort of 10 patients with other neurological diseases (OND) and 10 patients with MS. In addition, mass spectrometry was used to analyze EVs isolated from CSF samples in a validation cohort of 24 patients with OND, 38 patients with MS, and 14 patients with neuromyelitis optica spectrum disorders (NMOSD).
Resultes
The results revealed notable increases in the levels of 33 proteins in the CSF samples and 100 proteins in the CSF-derived EVs from patients with MS in the validation cohort. Increases in the levels of ITGA4, ITGAX, MS4A1 (CD20), CD3E, CD4, and CD8A, which are marker proteins of lymphocytes and myeloid cells, including activated microglia and dendritic cells, were observed in the CSF-derived EVs in discovery cohort. The results of the validation cohort revealed that the levels of four proteins, ITGA4, ITGAX, MS4A1, and CD3E, were significantly greater in MS patients than in OND patients. Furthermore, the level of ITGAX was greater in the patients with confirmed disability worsening (CDW) than that of without CDW. The results of the receiver operating characteristic (ROC) and Kaplan‒Meier analyses indicated that ITGAX levels in CSF-derived EVs may prove useful in predicting disease prognosis.
Conclusion
Our findings suggest that CSF-derived EVs reflect immunologic changes in MS and other neuroimmune diseases. In addition, these results raise the possibility that changing in myeloid cells as well as lymphocytes may also play a role in the pathogenesis of MS. CSF-derived EVs may serve as indicators of MS disease severity and could be utilized as biomarkers in the future.
Impact of belt conveyor systems on patient waiting time and productivity in outpatient pharmacy settings: a comparative study
Authors: Nasarudin Siti Nur Su'aidah , Latif Nurhairani Abdul , Shukri Saidatul Sheeda Ahmad , Hamdan Sharifah Shafawati Syed Mohd , Kadir Hajar Atiqah Abdul , Ali Muhamad Fuad , Yahaya Abdul Haniff Mohamad 
Published: February 2025

Abstract

Background
The implementation of belt conveyor (BC) systems in outpatient pharmacy departments (OPDs) has been a national policy since 2009, aiming to streamline the dispensing process. However, limited evidence exists on their impact on OPD operations. This study aims to evaluate and compare the waiting time and productivity of OPDs with and without BC systems.
Methods
A cross-sectional study was conducted in which 17 facilities with BC systems were compared with 17 facilities without BC systems. As pre-implementation data were unavailable, facilities were matched via propensity score matching (PSM) with a 1:1 matching technique without replacement. Post-matching data were analyzed via an independent t-test for productivity and a Mann-Whitney test for waiting time. A significance level of p < 0.05 was set to ensure reliable results.
Results
A total of 34 facilities were included in the analysis. For waiting time, there was no statistically significant difference between the groups (U = 136.00 OR z = -0.327, p = 0.744). Similarly, productivity was not significantly different between facilities with BC systems (M = 3.60, SD = 1.192) and those without BC systems (M = 3.64, SD = 1.273); t(32)=-0.109, p = 0.914. These findings suggested that the use of the BC system did not significantly ncrease the waiting time or productivity in OPDs.
Conclusion
The study concluded that the implementation of a BC system alone did not improve productivity or reduce patient waiting time. The study also highlighted the importance of comprehensive planning and consideration of multiple factors when new technologies are introduced into OPD workflows.
High-Speed SHDAC Design for Hybrid ADCs by Integrating 3-bit Flash and 8-bit Sigma-Delta for Improved Resolution
Authors: Aruna Tadigiri , Yarrabothu Ravi Sekhar 
Published: February 2025

Abstract

In the realm of rapid analog-to-digital conversion, it is not without its challenges to accomplish both high resolution and high sample rates to a satisfactory degree. The purpose of this work is to introduce a novel approach that involves combining a 3-bit Flash analog-to-digital converter (ADC) with an 8-bit Sigma-delta (ΣΔ) ADC. The overall goal of the proposed work is to develop a High-Speed and Sample Hold-Digital-Analog Converter (SHDAC), which can operate on different voltage sampled ranges from 4 to 32 scales and generate sample frequencies ranging from 3 giga-samples per second (Gsps) to 14 Gsps. The collaborative approach to two types of ADCs heavily relies on the 3-bit Flash ADC for high-speed designs with rapid conversion rates, and the 8-bit Sigma-Delta ADC for oversampling and enhanced resolution features with reduced noise compatibility. By combining these two methods, the SHDAC is able to achieve a balance between speed and resolution, which is suitable for tasks that need a high level of digital communication and signal processing. The implementation of a digital scaling mechanism that dynamically alters the SHDAC's bit resolution based on the specified scalar, which may be 4, 8, 16, or 32 bits from the beginning, is the key to the design. This versatility enables the SHDAC to meet the requirements of a wide variety of applications, ranging from lower resolution images with faster sampling to higher resolution images with slower sampling. The proposed work with SHDAC implements a novel technique with an integrated design based on a front-end model with Verilog, which provides high-precise functionality of the ADC's with better scalability and adaptability, indicating the efficient power and sampling rates achieved from 3–14 Gbps and a power of 0.01 dynamic power for the SHDAC design, as verified in the Vivado tool.
Level Measurement in Petrochemical Reactors Using Radiometric Gauge with Cobalt-60 Source
Authors: de Jesus Ycaro 
Published: February 2025

Abstract

Level measurement, in the industrial context, involves monitoring liquid or solid contents to enable continuous process control such as buffering, mixing, dosing, or resistance management. Among the various technologies available, radiometric level measurement has become prominent for its reliability in challenging conditions like high temperatures, pressure, and abrasion. This paper presents a case study on maintaining measurement accuracy with a Cobalt-60 radiometric source after reaching its first half-life. It proposes a solution that prolongs source usability without compromising process safety, highlighting challenges and adjustments necessary in petrochemical reactors.
A Compact and Effective DGS based Smart Watch Antenna for Wi-Max Applications with SAR Estimation
Authors: V Mariselvam , Anandan M. , p Rajeswari , Akilarasu G. , A Murugan 
Published: February 2025

Abstract

This study provides a low-profile efficient broad band antenna for smart watches and wearable devices. The proposed antenna has printed on a low-cost FR4 substrate with overall dimension 30 x 30 x 0. 8mm3.With this small dimension, the proposed antenna is able to cover the future 5G frequency spectrum ranging from 3.3-3.7 GHz in 2:1 VSWR. The designed antenna has been fabricated and measured experimentally with good agreement between simulated and measured results. The design insight of the proposed antenna is explored by providing parametric analysis for the various dimension of the proposed antenna. The placement analysis of the antenna has been done after incorporating hand phantom in the simulation and Specific Absorption Rate (SAR) for 1g and 10g of human tissues are found to be lower than the values recommended by Federal Communication Commission (FCC). The antenna has peak gain up to 4 dBi with maximum radiation efficiency around 85 – 89 % in the desired operating frequency.
Assessing variations in meteorological parameters using global climate model (GCM) outputs and artificial neural networks
Authors: Rahimi Niloufar , Maddah Mohammad Amin , Akhoond-Ali Ali Mohammad , Bahrami Mehdi 
Published: February 2025

ABSTRACT
The present research examines the impact of climate change on meteorological parameters using global climate models (GCMs) and artificial intelligence, with a case study in Fars Province, Iran. In this study, the meteorological parameters of minimum temperature, maximum temperature, precipitation, and solar radiation, as well as 12 GCMs from the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC), are utilized. A statistical downscaling model (multilayer perceptron neural network) is employed to extract climate change predictions under two scenarios, representative concentration pathway (RCP)4.5 and RCP8.5, for four synoptic stations (Shiraz, Abade, Fasa, and Lar), each representing different climatic regions. Correlation analysis is used to identify the most influential predictor variables for each meteorological parameter. The results indicate a projected increase in maximum temperature by up to 2.67 °C, which could significantly impact agricultural productivity in Fars Province. This finding is accompanied by minimum temperature ranges from 0.23 to 2.71 °C, solar radiation increasing by up to 1.91 MJ/m², and precipitation fluctuation between a decrease of 7% and an increase of 36.5%. These findings suggest that the region may face increased agricultural stress due to higher temperatures and variable precipitation patterns, necessitating adaptive strategies for sustainable water resource management.