bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Association Between Gestational Age and Type 1 Diabetes Mellitus in Children and Adolescents: A Systematic Review and Network Meta‐Analysis
Authors: Zhai Yiman , Gou Hao , Sun Xiangjuan 
Published: January 2025

ABSTRACTBackgroundWith genetics thought to explain a portion of the overall risk of type 1 diabetes mellitus (T1DM), environmental risk factors in early life have been proposed. Previous studies on the incidence of T1DM in children or adolescents by gestational age at birth have yielded inconsistent results.ObjectivesTo clarify the association between gestational age at birth and T1DM in childhood/adolescence and to offer evidence‐based support for the prevention or screening of T1DM.Data SourcesPubMed, Embase, Web of Science, and the Cochrane Library were searched from the inception of the databases to February 7, 2024.Study Selection and Data ExtractionData were extracted using a standardised form created a priori, and quality was assessed using the Newcastle‐Ottawa Scale (NOS).SynthesisDue to the diversity of gestational age groups in the original studies, a Bayesian network meta‐analysis was performed to discuss the association of different gestational ages with the risk of T1DM in childhood/adolescence.ResultsA total of 13 studies on children/adolescents with T1DM were included. Compared with the gestational age of 39–40 weeks, gestational ages of < 37 weeks (odds ratio [OR] 1.35, 95% credible interval [CrI] 1.19, 1.53), 33–36 weeks (OR 1.19, 95% CrI 1.11, 1.27), and 37–38 weeks (OR 1.26, 95% CrI 1.21, 1.30) were correlated with an increased risk of T1DM, whereas gestational ages of < 32 weeks (OR 0.61, 95% CrI 0.43, 0.88) and < 33 weeks (OR 0.72, 95% CrI 0.59, 0.87) were correlated with a lower risk.ConclusionsA higher risk of T1DM was observed in infants born early term or preterm compared to full‐term infants. However, the results of this network meta‐analysis indicate that extremely or very preterm infants were less likely to develop T1DM. Further studies are needed to validate this in the future.
Carbonates and microbialites record a dynamic lake basin evolution in the Late Cretaceous to Eocene Sheep Pass Formation, Nevada, USA
Authors: Olsen‐Valdez Juliana , Widlansky Sarah , Trower Elizabeth , Snell Kathryn , Clyde William 
Published: January 2025

ABSTRACTAncient terrestrial sediments provide critical information about the responses of continental environments to global scale climate and tectonic perturbations, which are vastly understudied relative to marine archives. The >1 km thick Sheep Pass Formation type section in east‐central Nevada preserves non‐marine carbonates, including microbialites, and lesser siliciclastics, deposited in a tectonically active, high‐elevation basin during the latest Cretaceous through to middle Eocene time, an interval spanning major global greenhouse climate states and warming events. This study combines outcrop and hand‐sample observations, thin section petrography and X‐ray diffraction mineralogical analyses to create a facies framework and interpreted environmental evolution for the Sheep Pass Basin. Together, these observations portray the Sheep Pass Formation type section as a dynamic and highly sensitive basin due to its small size. The dominance of thrombolite boundstones compared to metazoan fossils, which sets the Sheep Pass Formation type section apart from other Palaeogene‐aged lake basins in the western United States, reflects the resilience of microbial mats compared to metazoans in this dynamic setting. The major lacustrine phase of the Sheep Pass Basin records three intervals: a shallow lake with few microbialites, followed by abundant microbialites, before the transition to a marginal setting with evaporative conditions, marking the culmination of this major lacustrine phase. The transition to a microbialite‐dominated interval was likely driven by physicochemical conditions (for example, higher alkalinity), paired with lower competition from metazoan grazers. Although the Sheep Pass Formation type section preserves environmental change in response to both tectonics and climate, similar trends in facies, mineralogy and invertebrate abundance compared to other sedimentary basins from this time suggest that global climate influenced distinct environmental shifts in the Sheep Pass Basin. This work provides a detailed sedimentological framework for a new, high‐elevation palaeoclimate record during a pivotal geological climate interval.
Red blood cell utilization in patients with sickle cell disease: A Canadian single‐center experience
Authors: Uminski Kelsey , Perelman Iris , Mack Johnathan , Tinmouth Alan 
Published: January 2025

AbstractBackgroundRed blood cell (RBC) utilization in patients with sickle cell disease (SCD) in Canada is poorly defined. This study describes RBC utilization in an SCD cohort at a single Canadian center.Study Design and MethodsAll adults with SCD who received care at the Ottawa Hospital between January 2006 and May 2019 were included, and followed until December 2021. Data on hospital encounters and RBC transfusions were obtained from hospital databases.ResultsOverall, 273 patients were included (median age: 25 years; 53.8% female; median follow‐up: 8.1 years). During the study period, there were 23,127 hospital encounters (median: 45 [interquartile range (IQR) 18, 100] per patient), with 165 patients (60.4% of cohort) receiving 22,538 RBC units. Most RBC units (86.5%) were transfused in the outpatient setting. Although only 2.9% of patients had O‐negative blood type, O‐negative RBC units accounted for 29.1% of units transfused. One hundred forty‐seven patients received 2205 RBC units (9.8% of total) as simple transfusions (median: 5 [IQR 3, 13] per patient), and 88 patients received 20,333 RBC units (90.2% of total) during 2702 red cell exchange (RCE) sessions (median: 14.5 (IQR 1, 47.5) RCE per transfused patient). A median of 7 RBC units (IQR 6, 9) were transfused per RCE session, with a median of 30 days (IQR 28, 40) between sessions.DiscussionPatients with SCD at our center frequently received O‐negative units, and large RBC volumes were used for RCE. These results provide a utilization baseline for future education and quality improvement initiatives to optimize RBC stewardship.
SARS‐CoV‐2 IgG antibodies in COVID‐19 convalescent plasma and conventional plasma units
Authors: Sulaiman Andrew , Sengsouk Isabella , White Jodie L. , Marshall Christi , Fernandez Reinaldo E. , Redd Andrew D. , Eby Yolanda , Casadevall Arturo , Sullivan David , Gebo Kelly , Shoham Shmuel , Laeyendecker Oliver , Rai Herleen , Bloch Evan M. , Crowe Elizabeth P. , Tobian Aaron A. R. 
Published: January 2025

AbstractBackgroundThe Association for the Advancement of Blood and Biotherapies guidelines recommend the use of high‐titer COVID‐19 convalescent plasma (CCP) for patients with SARS‐CoV‐2 at high risk of disease progression, including those who are immunocompromised. We hypothesized that conventional plasma units have comparable neutralizing antibody levels to CCP.Study Design and MethodsConventional plasma and CCP units were obtained from blood suppliers. Quantitatively measured antibodies to SARS‐CoV‐2 were assessed using the MesoScale Discovery multiplex electrochemiluminescence immunoassay. Binding antibody distributions were compared with Wilcoxon rank‐sum tests. SARS‐CoV‐2 neutralizing antibodies were analyzed using the GeneScript ELISA‐based neutralization assay. The proportion of conventional and CCP units with a percent signal inhibition of ≥80% (as defined by the United States Food and Drug Administration for CCP in 2021) and exact binomial confidence intervals (CIs) were calculated.ResultsAmong 218 conventional plasma units and 74 CCP units collected between September 2023 and July 2024, the distribution of total antibody binding levels largely overlapped between conventional plasma and CCP, though statistically significant differences in median nucleocapsid and spike Omicron variant concentrations were observed. Median percent signal neutralization was 97.5% (range 3.4%–98.6%) among conventional plasma units and 97.7% (range 95.4%–98.6%) among CCP units. For conventional plasma, 95.0% (95% CI = 91.2%–97.5%) met the neutralization antibody threshold for high‐titer CCP. For CCP, 100% (95% CI = 95.1%–100.0%) met the neutralization threshold for high‐titer CCP.ConclusionConventional plasma units demonstrate similar median antibody concentration to CCP units. In countries or regions where licensed CCP is unavailable and titers are unknown, transfusion of multiple conventional plasma units may be of clinical utility.
Conducting Pairwise and Network Meta-analyses in Updated and Living Systematic Reviews: a Scoping Review Protocol
Authors: Konstantinidis Menelaos , Stratton Catherine , Tsokani Sofia , Elliott Julian , Simmonds Mark , McGowan Jessie , Moher David , Tricco Andrea C. , Veroniki Areti-Angeliki 
Published: January 2025

Objective:
The objective of this scoping review will be to describe existing guidance documents or studies reporting on the conduct of meta-analyses in updated systematic reviews (USRs) or living systematic reviews (LSRs).

Introduction:
The rapid increase in the medical literature poses a substantial challenge in keeping systematic reviews up to date. In LSRs, a review is updated with a pre-specified frequency or when some other signalling criterion is triggered. While the LSR framework is well-established, there is uncertainty regarding the most appropriate methods for conducting repeated meta-analyses over time, which may result in sub-optimal decision-making.

Inclusion criteria:
Studies of any design (including commentaries, books, manuals) providing guidance on conducting meta-analysis in USRs or LSRs.

Methods:
We will use the JBI methodology for scoping reviews. We will search multiple medical bibliographic databases (Cochrane Library, Embase, ERIC, MEDLINE, JBI Evidence Synthesis, and PsycINFO), statistical and mathematics databases (COBRA, Current Index to Statistics, MathSciNet, Project Euclid Complete, and zbMATH), pre-print archives (Arvix, BioRxiv, and MedRxiv), as well as difficult to locate/unpublished (or gray) literature. Two reviewers will independently screen titles, abstracts, and full-text documents, and extract data. Characteristics of recommendations for meta-analysis in USRs and LSRs will be presented using descriptive statistics and categorized concepts.

Details of this review project can be found in Open Science Framework: https://osf.io/9c27g
Accessible Digital Reconstruction and Mechanical Prediction of 3D-Printed Prosthetics
Authors: Lee Junghun , Nkama Chukwuemeka , Yusuf Hadiza , Maina Joseph , Ikuzwe Jean , Byiringiro Jean , Busogi Moise , Tucker Conrad 
Published: January 2025

Abstract
We identify two significant issues that render prosthetics inaccessible. First, obtaining a representation of the residual limb can be inaccessible. Conventional approaches require equipment or expertise often unavailable in resource-constrained communities. Second, it is challenging to determine the prosthetic design, filament material, and printing process that satisfies mechanical functionality requirements because it is difficult to predict the mechanical properties of 3D-printed prosthetics. Therefore, we propose a method to achieve a digital residual limb model from a smartphone video and predict the mechanical functionality of the 3D-printed prosthetic. We also present a case study that demonstrates the feasibility of the method. Digital reconstruction results show that the smartphone type influences reconstruction time and mesh quality, with correlation coefficients of 0.89 and 0.88, respectively. Also, the distance between the residual limb and the smartphone influences the reconstruction scale, with a correlation coefficient of –0.90. Seven of eight digital reconstruction results achieved an average deviation lower than 2 mm, which is viable for designing prosthetics. The XGBoost model trained to predict the effective material data of the 3D-printed part achieved an R2 over 0.99 for all predictions. The predicted effective material data are used to predict the mechanical functionality of a 3D-printed prosthetic. The mechanical functionality is evaluated following ISO-10328. The results reveal that different prosthetic designs, filament materials, and printing processes yield different mechanical functionality. These factors can be determined according to the predicted functionalities and the patient’s needs.
A Diagnostic Model to Verify Geometric Dimensioning & Tolerancing Specifications
Authors: Sun Wangping , Gao Yanqing 
Published: January 2025

Abstract
Geometric dimensioning and tolerancing (GD&T) is crucial for ensuring the quality and functionality of products. However, the absence of well-defined GD&T design rules often leads to errors in existing designs. These errors can result in a misunderstanding of the original design intent and hinder the development of new products. It has become imperative to verify and correct these errors. This paper introduces a diagnostic model aimed at checking and improving GD&T specifications, demonstrating its effectiveness through exemplary designs. The proposed diagnostic model employs a top-down approach to dissect GD&T callouts into six discrete layers until the datum setup is exposed. Each layer is verified against the Rule-based Specification, ensuring correct callouts are retained, incorrect ones are revised, redundant ones are eliminated, and missing ones are added where necessary. The significance of the research lies in its contribution to improving GD&T practices through a systematic diagnostic model that addresses errors in existing designs, facilitates learning among designers, and potentially sets a standard for GD&T verification in engineering practice. The model is the first of its kind in the public domain. The establishment of such a model represents an advancement in standardizing GD&T verification practices.
Many-Objective Optimization of Hybrid Control Systems for Quadrotor Unmanned Aerial Vehicles
Authors: Wu Xinhuang , Sardahi Yousef 
Published: January 2025

Abstract
This paper presents an optimal cascade control structure for a quadcopter unmanned aerial vehicle (UAV) that uses a blend of linear and nonlinear control algorithms. To control the UAV’s position, a mathematical model is developed first. This model, nonlinear in its initial form, is linearized based on an operating point of the UAV. With the nonlinear version of the model, a sliding mode control facilitates the formulation of the motor thrust control laws, which guide the UAV to its desired position. The linear model, meanwhile, is used to create two controllers: the XG-controller and the YG-controller, which compute the necessary roll and pitch to move the vehicle to the XG and YG global positions. Additionally, three attitude controllers are established to calculate the rotors’ desired angular rates, under the presumption of minimal Euler angles. An optimization problem is then developed with 21 design parameters and 10 objectives and is solved using HypE (Hypervolume Estimation) algorithm, a popular many-objective optimization algorithm, under stability and performance constraints. The optimization generates Pareto sets and fronts, indicating that the design objectives compete. Numerical simulations based on the nonlinear UAV model affirm the effectiveness of the proposed optimization approach.
Seat Angle Effects on Disc Degeneration for Pilots in High-G Environments
Authors: Reyes Kadozono Ann , DeWitt Timothy , Kraft Reuben H. 
Published: January 2025

Abstract
In aviation, pilots frequently encounter high-G environments, not only in operations but also in training. Pilots have reported high levels of injury to their neck and back as a result. It is hypothesized that this pain is linked to accelerated intervertebral disc degeneration, and research suggests that exposure to high G forces can accelerate intervertebral disc degeneration in the spine. Establishing a methodology to evaluate these effects is crucial to reduce the risk of spinal abnormalities in pilots. The impact of seat angle on disc degeneration during high-G maneuvers among F-16 pilots remains uncertain and requires further investigation to comprehend its role.
This study utilized the Toyota Human Model for Safety (THUMS) to investigate how seat angles affect intervertebral discs using a loading profile that mirrors the forces experienced during centrifuge training. Effective stress data is collected to calculate the fatigue damage that occurs over time in the disc under different seat angles. This understanding can help develop effective training programs and preventive measures to protect pilots’ health during training and operational missions.
Integration of IoT Network and Sensors With a Full-Sized Quadruped in a Simulated Human-Centered Environment
Authors: Ho Jonathan , Cajuste Jefferson , Schneidler Alexander , Tatoglu Akin , Sohn Kiwon 
Published: January 2025

Abstract
This paper presents the updated mechanical design, integrated IoT network, and developed inverse kinematics and gait models of HARQ (Human Assistive and Robust Quadruped). Based on the mechanical limitations of its predecessor, a new connector, foot, planetary gearbox, leg, and body design are presented. Due to additions and improvements to the mechanical design, new inverse kinematics and gait modes are developed to permit HARQ to navigate a physical workspace. To make use of these improvements, an IoT network is integrated with HARQ to allow the quadruped to wirelessly gather and respond to information in real-time. To evaluate HARQ, an indoor experimental space was designed to accommodate an isolated IoT network, sufficient workspace, and simulate a typical human environment. HARQ was able to respond to wireless motion sensor data proctored over an MQTT network. The results are promising steps towards IoT integration into robots.
Electromechanical Design and Vehicle Driving Capability Upgrade of a Full-Sized Humanoid, HART
Authors: Bickford Harry , Yang Jaesung , Esteves Andrew , Shen Xin , Sohn Kiwon 
Published: January 2025

Abstract
In this paper, the applicability of various gear designs and layouts that can increase manipulators’ joint torque outputs of a full-sized humanoid is studied first. The investigation encompasses an exploration of different configurations involving varied gearing, array arrangements, and magnet placements to optimize the resultant magnetic field of the magnetic gear. Then, a waypoint navigation control utilizing a monocular lane and intersection detection algorithm developed based on Region of Interest (RoI) Hough Transform and landmark detection built based on the Convolutional Neural Network (CNN) model is investigated to enable the humanoid to drive its assigned vehicle in an autonomous way. The RoI detection and CNN models are developed and trained using diverse intersections, enabling algorithms to determine the distance between the vehicle and the intersection. Lastly, testing and evaluation of the built gear mechanism and driving control system are implemented in real-world human-centered environments.
Force and Torque Synthesis of Four-Bar Linkages Using Geometric Constraint Programming
Authors: Chan Cody Leeheng 
Published: January 2025

Abstract
This paper proposes a method to synthesize four-bar linkages and crank sliders with a prescribed torque or force function for the output link. Based on the concept of virtual work, the force or torque generation problems are transformed into velocity ratio synthesis problems. In contrast to the traditional analytical method that requires solving numerous equations with complicated mathematical treatments, the proposed approach only needs basic drawing techniques of CAD software and basic kinematic knowledge of graphical analysis. Taking advantage of the geometric constraint in commercial CAD software, the velocity polygon of each desired precision position can be constructed, and the value of the objective velocity can be assigned to synthesize the linkage reversibly. This paper demonstrates the approach by synthesizing four-bar linkages and crank sliders that satisfy three or four precise positions of prescribed linear and nonlinear torque or force functions. The result shows that the output torque or the output force of the designed linkage can approximately trace the required function with small errors. With the aid of the CAD software, the linkage mechanical advantage of several positions can be assigned directly, creating and addressing a new category of dimensional synthesis different from traditional function, path, and motion generation. It may be called force generation or mechanical advantage generation. The approach may provide a new perspective to the linkage designer.
Rapid Manufacturing Solid Microneedle Array by Integrated Digital Light Processing With Machine Learning (DLP-ML)
Authors: Lestari Dwi Mardika , Chen Pin-chuan 
Published: January 2025

Abstract
Microneedle arrays (μNA) are gaining popularity in the field of drug delivery due to their potential to minimize side effects compared to conventional hypodermic needles. Generally, μNA is manufacturing through three or two stages which lack of flexibility in design. 3d printing is one of the powerful method that could be employed in three or two stages. However, it could be extended to single stage by directly manufacturing μNA from designated material. Digital light processing (DLP) is a kind of 3d printing which is using in this study. A further understanding of DLP printing parameters would be investigated such as LED current (mA), curing time (sec), z-thickness (μm), and grayscale level image (0 to 255). This study explores the integration of DLP technology and machine learning (ML), namely DLP-ML, to manufacture μNA with customizable size, rapid production process, and reduced material wastage. The initial process in developing ML model is preparing a dataset obtained from experimental approach. An orthogonal table is simplified the number of experiment. The orthogonal table is contained five factors and five levels, L25. The dataset is divided into input and output and substituted to ML system. In this approach, ML algorithms are employed to determine the optimal digital mask patterns and printing parameters for DLP-ML manufacturing. The study is employed various ML configurations in term of algorithm and number of hidden layer. Under different algorithm, the sort of larger to lower accuracy is arranged Bayesian regularization backpropagation (BR10), Levenberg-Marquardt backpropagation (LM10), and scaled conjugate gradient backpropagation (SCG10), respectively. It also notices that the deviation of BR10 is proving that μNA is manufactured uniformly on a substrate. It is ultimately selecting Bayesian regularization backpropagation for its superior accuracy, exceeding 90%. For different number of hidden layer, the default value, 10, is also resulting highest accuracy among others. Then, BR10 could be concluded as the best ML configuration in this case. This algorithm empowers DLP-ML manufacturing to produce μNA arrays with various aspect ratio (AR), representing the ratio between the height and base diameter of μNA. The AR of 15 is highest that could be performed and the critical AR of μNA bending is found at 7 (700/100). By harnessing the synergy of DLP-ML technologies, this research presents a promising avenue for the advancement of drug delivery systems, offering enhanced precision, scalability, and therapeutic efficacy in medical applications. Finally, DLP-ML is successfully developed a rapid μNA manufacturing with different dimensions very accurately.