bluuebunny/crossref_metadata_2025_split huggingface dataset:
Associations between self‐reported parasomnias and psychiatric illness in 370,000 patients with sleep disorders
Authors: Hanif Umaer , Cairns Alyssa , Mysliwiec Vincent , Bettinardi Ruggero G. , Elbaz Maxime , Gimenez Ulysse , Mignot Emmanuel J. M. 
Published: August 2024

AimTo assess self‐reported parasomnias in patients with sleep disorders and explore relationships with psychiatric illness, comorbidities, subjective sleep assessments, and polysomnographic study results.MethodsResults from intake questionnaires and polysomnographic assessments, collected from 240 sleep centers across 30 US states between 2004 and 2019, were analyzed retrospectively. Of 540,000 total patients, 371,889 who answered parasomnia‐specific questions were included. Patients responding “often” or “always” to parasomnia‐specific questions were considered “symptom‐positive,” whereas a “few times” or “never” were considered “symptom‐negative” (controls).ResultsThe study sample was 54.5% male with mean age 54 years (range, 2–107 years). Frequencies for the different parasomnias were 16.0% for any parasomnia, 8.8% for somniloquy, 6.0% for hypnagogic hallucinations, 4.8% for sleep‐related eating disorder, 2.1% for sleep paralysis, and 1.7% for somnambulism. Frequent parasomnias were highly associated with diagnosed depression (odds ratio = 2.72). All parasomnias were associated with being younger and female and with symptoms of depression, anxiety, insomnia, restless legs, pain, medical conditions, fatigue, and sleepiness. Associations with objective sleep metrics showed characteristics of consolidated sleep and differentiated weakly between nonrapid eye movement sleep and rapid eye movement sleep parasomnias. Machine learning accurately classified patients with parasomnia versus controls (balanced accuracies between 71% and 79%). Benzodiazepines, antipsychotics, and opioids increased the odds of experiencing parasomnias, while antihistamines and melatonin reduced the odds. Z‐drugs were found to increase the likelihood of a sleep‐related eating disorder.ConclusionOur findings suggest that parasomnias may be clinically relevant, yet understudied, symptoms of depression and anxiety. Further investigation is needed to quantify the nature of multimorbidity, including causality and implications for diagnosis and treatment.
Outcomes of Pediatric Liver Transplantation in Glycogen Storage Disease Type 1b—A Single‐Center Experience
Authors: Rajasekaran Vivek , Santra Saikat , Kelgeri Chayarani , Johansen Lauren , Vijay Suresh , Sreekantam Sreevidya , Raiman Julian , Daly Anne , Sharif Khalid , Kitchen Steve , Gupte Girish 
Published: August 2024

ABSTRACTBackgroundLiver transplantation (LT) normalizes fasting tolerance in glycogen storage disease type (GSD) 1b. However, reported outcomes post‐LT with respect to correction of neutropenia, infection risk and growth are varied. Sodium‐glucose cotransporter‐2 (SGLT2) inhibitors have been recently shown to improve neutropenia in GSD1b patients.MethodsIn this single‐center retrospective study, we reviewed all children who underwent LT for GSD1b. Neutropenia, dose of granulocyte colony‐stimulating factor (G‐CSF), unplanned hospital attendance, anthropometrics, graft rejection, survival, and the effects of dapagliflozin were analyzed. Data from protocol biopsies obtained at 1, 5, and 10 years post‐LT and immunosuppression levels were collected.ResultsEight children (6 female), all on G‐CSF pre‐transplant, underwent cadaveric LT for GSD1b at median age 3.6 years (IQR 3.3–5.1) with mean follow‐up time of 10.3 years (95% CI 7.5–13.1). Neutrophil count and G‐CSF requirement did not improve post‐LT. Although a reduction in unplanned hospital attendance due to infection (0.98 [95% CI 0.76–1.26] vs. 0.49 [95% CI 0.41 to 0.57] per person‐year, p < 0.01) was observed, gastrointestinal complaints and graft dysfunction accounted for a similar hospitalization burden pre‐ versus post‐LT. Body mass index (BMI) reduced post‐LT (Z‐score 1.47 [95%CI 0.39–2.23] vs. 0.56 [95% CI −0.74 to 1.45], p = 0.02), with no significant change in height.Although all children and grafts have survived, 75% of recipients developed rejection, despite adequate immunosuppression levels, with two children having been found to have developed significant fibrosis on their 5‐year protocol biopsy. Although dapagliflozin allowed cessation of G‐CSF, no improvement in neutrophil count was observed. Despite this, a reduction in gastrointestinal and infection‐related morbidity was noted following dapagliflozin.ConclusionAlthough LT normalizes fasting tolerance in GSD1b and reduces hospital attendance due to infection, morbidity from infection and gastrointestinal manifestations persist. Children in our cohort experienced high rates of rejection necessitating titration of immunosuppression to balance risk of infection against organ rejection. Future studies should investigate whether early introduction of SGLT2 inhibitors post‐LT impact morbidity in this group.
Spectroscopic analysis of bacterial photoreactivation
Authors: Abady Keyvan Khosh , Karpourazar Negar , Krishnamoorthi Arjun , Li Runze , Rentzepis Peter M. 
Published: August 2024

AbstractWith the rise of bacterial infections and antibiotic resistance, spectroscopic devices originally developed for bacterial detection have shown promise to rapidly identify bacterial strains and determine the ratio of live to dead bacteria. However, the detection of the photoreactivated pathogens remains a critical concern. This study utilizes fluorescence and Raman spectroscopy to analyze bacterial responses to UV irradiation and subsequent photoreactivation. Our experimental results reveal limitations in fluorescence spectroscopy for detecting photoreactivated bacteria, as the intense fluorescence of tryptophan and tyrosine amino acids masks the fluorescence emitted by thymine molecules. Conversely, Raman spectroscopy proves more effective, showing a detectable decrease in band intensities ofE. colibacteria at 1248 and 1665 cm−1after exposure to UVC radiation. Subsequent UVA irradiation results in the partial restoration of these band intensities, indicating DNA repair and bacterial photoreactivation. This enhanced understanding aims to improve the accuracy and effectiveness of these spectroscopic tools in clinical and environmental settings.
Predicting pharmaceutical supply chain disruptions before and during the COVID‐19 pandemic
Authors: Hupman Andrea C. , Zhang Juan , Li Haitao 
Published: August 2024

AbstractDisruptions
to the pharmaceutical supply chain (PSC) have negative implications for patients, motivating their prediction to improve risk mitigation. Although data analytics and machine learning methods have been proposed to support the characterization of probabilities to inform decisions and risk mitigation strategies, their application in the PSC has not been previously described. Further, it is unclear how well these models perform in the presence of emergent events representing deep uncertainty such as the COVID‐19 pandemic. This article examines the use of data‐driven models to predict PSC disruptions before and during the COVID‐19 pandemic. Using data on generic drugs from the pharmacy supply chain division of a Fortune 500 pharmacy benefit management firm, we have developed predictive models based on the naïve Bayes algorithm, where the models predict whether a specific supplier or whether a specific product will experience a supply disruption in the next time period. We find statistically significant changes in the relationships of nearly all variables associated with product supply disruptions during the pandemic, despite pre‐pandemic stability. We present results showing how the sensitivity, specificity, and false positive rate of predictive models changed with the onset of the COVID‐19 pandemic and show the beneficial effects of regular model updating. The results show that maintaining model sensitivity is more challenging than maintaining specificity and false positive rates. The results provide unique insight into the pandemic's effect on risk prediction within the PSC and provide insight for risk analysts to better understand how surprise events and deep uncertainty affect predictive models.
Individual and cultural differences in compassion, noticing suffering, and well‐being: Consequences of wanting to avoid feeling negative
Authors: Koopmann‐Holm Birgit , Beccari Alexandra , Oosthuizen Monet 
Published: August 2024

AbstractAlthough people across the globe experience suffering, some individuals find it difficult to respond to others' distress because they might not know what would be most helpful to that person in that particular situation. For instance, would a response that focuses on the silver lining or one that acknowledges the suffering of the other person be more compassionate and helpful? In this paper, we demonstrate that the construct of avoided negative affect (ANA), the degree to which people want to avoid feeling negative, can predict individual differences and explain cultural variations in several aspects of compassion. Because ANA is a relatively new construct, we review research that focuses on concepts that are related to, but differ from ANA. Then, we summarize individual and cultural differences in ANA and their consequences for expressions of sympathy and compassion, conceptualizations of compassion, noticing suffering (including acknowledging suffering such as systemic racism), and well‐being. Across many studies conducted in various cultural contexts including Ecuador, Mexico, China, Japan, Germany, and the United States, ANA can partly explain cultural differences in different aspects of compassion. This work has important implications for cross‐cultural counseling, anti‐racism trainings, and conflict resolution. Noticing others' suffering and understanding what compassion entails for different people in different settings can result in treating others the way they want to be treated.
Reading graphic novels: A multiliteracies approach
Authors: Lynn Claudia Baska , Sayılı‐Hurley Sibel 
Published: August 2024

AbstractThis paper explores graphic novels that address issues of diversity and migration and enhance multiliteracies learning in the German classroom. By adopting a multiliteracies approach, the paper proposes a transformative learning approach that explores these issues within graphic novels. Examples of learning activities from an intermediate course illustrate how graphic novels amplify marginalized voices and facilitate candid inquiries into topics like racism and colonialism. The study highlights the relevance of graphic novels in addressing evolving teaching challenges and meeting the diverse demands of education in the context of global events and calls for social justice.
Life‐threatening hemorrhage as defined by the critical administration threshold in nontraumatic critical bleeding: A descriptive observational study
Authors: Matzek Luke J. , Hanson Andrew C. , Schulte Phillip J. , Cureton Kimberly D. , Kor Daryl J. , Warner Matthew A. 
Published: August 2024

AbstractBackgroundEvaluations of critical bleeding and massive transfusion have focused on traumatic hemorrhage. However, most critical bleeding in hospitalized patients occurs outside trauma. The purpose of this study was to provide an in‐depth description examining the critical administration threshold (CAT; ≥3 units red blood cells (RBCs) in a 1‐h period) occurrences in nontraumatic hemorrhage. This will assist in establishing the framework for future investigations in nontraumatic hemorrhage.MethodsThis is an observational cohort study of adults experiencing critical bleeding defined as being CAT+ during hospitalization from 2016 to 2021 at a single academic institution. A CAT episode started with administration of the first qualifying RBC unit and ended at the time of completion of the last allogeneic unit prior to a ≥4‐h gap without subsequent transfusion. The primary goal was to describe demographic, clinical and transfusion characteristics of participants with nontraumatic critical bleeding.Results2433 patients suffered critical bleeding, most often occurring in the operating room (71.1%) followed by the intensive care unit (20.8%). 57% occurred on the initial day of hospitalization, with a median duration of 138 (36, 303) minutes. The median number of RBCs transfused during the episode was 5 (4, 8), with median total allogeneic units of 9 (4, 9). Hospital mortality was 19.2%. The most common cause of death was multi‐organ failure (50.3%), however death within 24 h was due to exsanguination (72.7%).DiscussionThe critical administration threshold may be employed to identify critical bleeding in non‐trauma settings of life‐threatening hemorrhage, with a mortality rate of approximately 20%.
Modeling and Control of Strip Transport in Metal Peeling
Authors: Yalamanchili Aditya V. , Sagapuram Dinakar , Pagilla Prabhakar R. 
Published: August 2024

Abstract
Metal peeling refers to the process of forming a thin metal strip from the surface of a rotating feedstock using controlled material removal—machining under an applied strip tension. In this paper, the mechanics of strip formation process is described, while emphasizing the role of strip tension in ensuring uniformity and quality of the peeled strip. This includes an analysis of the deformation history in the peeling zone and the transport dynamics of the strip as it moves from the cutting edge to the coiler. Using conservation laws, governing equations for strip tension and velocity that incorporate dynamic spatiotemporal interactions between peeling and transport processes are developed. Experimental demonstration includes the setup of a lab-scale prototype metal peeling system designed to validate the proposed dynamic model describing the strip transport behavior and control approach. Peeling experiments are performed with steel to evaluate the proposed control approach. Comparisons between two control strategies, with and without tension feedback, are presented and discussed. The importance of real-time tension control for mitigating strip thickness variations and improving other dimensional features of the strip such as flatness and edge waviness is also briefly discussed.
Evolution Design of Multiple Metamorphic Mechanisms Inspired by the Concept of Assur Group
Authors: Gao Yuan , Kang Xi , Li Bing 
Published: August 2024

Abstract
Metamorphic mechanisms that can adapt to a variety of working conditions with distinct configurations, have gained widespread attention in recent years. However, it's always difficult to design metamorphic mechanisms with various motion branches. In this paper, the evolution design of a family of novel multiple metamorphic mechanisms is conducted by the inspiration from the concept of Assur group. Adopting some class II groups which are derived from the combination of three basic links, a novel 7R multiple metamorphic mechanism is first presented and analyzed. Kinematic analysis illustrates that the mechanism contains totally 11 motion branches including three types of effective joints, i.e., non-overconstrained 7R motion branches, overconstrained 6R motion branches, and planar 4R motion branches. Reconfiguration analysis of the mechanism is presented by the kinematic curves, and it shows that there are totally ten bifurcation points. Moreover, the transformations among all the motion branches are analyzed. Then, adopting different combinations of the elements, the evolution design of more 7R multiple metamorphic mechanisms is presented. This paper proposes a family of multiple metamorphic mechanisms which can achieve a large number of motion branches, and the construction process of the mechanisms in this paper provides a new reference for designing multiple metamorphic mechanisms.
A Novel One-Degree-of-Freedom Deployable Structure and Its Plate Form
Authors: Gao Yuan , Qi Jian , Li Lin , Zhang Jun , Yang Fufu 
Published: August 2024

Abstract
Deployable structures are widely utilized in various fields due to their ability to switch between a deployed working state and a folded storage state. This paper presents a new method for achieving plate forms in deployable structures, allowing the formation of closed surfaces suitable for covering purposes. Initially, a novel one-degree-of-freedom (one-DOF) deployable network is proposed, employing Bennett linkages and Bennett-based 6R linkages. Subsequently, the shape of the links in the network is modified to obtain a plate form consisting of equilateral triangular panels. The paper also conducts kinematic analysis, motion property examination, and bifurcation condition discussion to demonstrate the folding properties of the proposed mechanism. Additionally, a modified scheme is proposed to enable the structure to form a closed surface, and physical prototypes are used to validate all the results. Overall, the proposed method presents new possibilities for developing practical and versatile deployable structures with broader applications.
Gaidai Risk Evaluation Method for Lifetime Assessment for Offshore Floating Wind Turbine Gearbox
Authors: Gaidai Oleg 
Published: August 2024

Abstract
Renewable clean energy in some cases may be viewed as an alternative to limited fossil resources. Offshore floating wind turbines (FWTs) are among the most attractive green alternatives. However, FWTs, in particular their essential components, may sustain structural damages from cyclic loads brought on by torque, bending, longitudinal loadings, as well as twisting moments. Multibody simulation tool SIMPACK was utilized to assess structural bending moments and internal forces occurring within the FWT drivetrain during its field operation. The novel risk and damage evaluation method advocated in the current study is intended to serve contemporary FWT design, enabling accurate assessments of structural lifespan distribution, given in situ environmental/field conditions. The approach described in the current study may be utilized to analyze complex multidimensional sustainable energy systems, subjected to excessive stressors during their intended service life. Contemporary risk evaluation approaches, dealing with complex energy systems are not always well-suited for handling dynamic system's high dimensionality, aggravated by nonlinear cross-correlations between structural components, subjected to dynamic nonlinear nonstationary loadings. The current study advocates a novel general-purpose lifetime assessment methodology, having a wide area of potential engineering and design applications, not limited to offshore wind/wave renewable energy systems. Key advantages of the advocated methodology lie within its robust ability to assess damage risks of complex energy and environmental systems, with a virtually unlimited number of system components (dimensions), along with the further potential to incorporate nonlinear cross-correlations between system components in real time. Note that to the author's knowledge, there are no comparable risk evaluation methods that can deal with the system's high dimensionality, utilizing raw/unfiltered simulated/measured datasets, beyond one or two-dimensional dynamic systems—except for computationally expensive direct Monte Carlo (MC) simulations.
Deep Learning in Automating Breast Cancer Diagnosis from Microscopy Images
Authors: Gu Qiangqiang , Prodduturi Naresh , Hart Steven N. 
Published: August 2024

Abstract
Breast cancer is one of the most common cancers in women. With early diagnosis, some breast cancers are highly curable. Classifying normal versus tumor breast tissues from microscopy images is an ideal case to use for deep learning and could help diagnose breast cancer with higher reproducibility. Since data preprocessing and hyperparameter tuning have impacts on breast cancer classification accuracies, training a classifier with appropriate data preprocessing and optimized hyperparameters could improve breast cancer classification accuracy. Using 12 combinations of model architectures, data preprocessing, and hyperparameter configurations, the validation accuracy was calculated using the BreAst Cancer Histology (BACH) dataset. The DenseNet201, a non-specialized model architecture, with transfer learning approach achieved 98.61% validation accuracy compared to only 64.00% for the digital pathology (DP)-specialized model architecture. The combination of image data preprocessing and hyperparameters have a profound impact on the performance of deep neural networks for image classification. To identify a well-performing neural network to classify tumor versus normal breast histology, researchers should not only focus on developing new models specifically for DP, since hyperparameter tuning for existing deep neural networks in the computer vision field could also achieve a better prediction accuracy.
SCAN, AIM, GO: A Compact Brain Device Guide for Accelerating Minimally-Invasive Image Guided Neurosurgeries
Authors: Lilieholm Thomas , Oakes Terrence , Lake Wendell , Ahmed Azam , Alexander Andrew L , Block Walter F 
Published: August 2024

Abstract
Workflows for MRI-guided minimally-invasive neurosurgeries are often time-consuming and complex. Many minimally-invasive interventions utilize magnetic resonance imaging (MRI) to noninvasively visualize internal anatomy and pathologies. This, in conjunction with external trajectory guides, can be used to internally position devices to perform complex surgeries with minimal disruption to the patients’ healthy anatomy.
These trajectory guides are typically rigidly attached to the skull and feature adjustable channels through which drills, needles, and /or catheters may be introduced. Trajectories are oriented by iterating between imaging and manipulation of device settings. MRI scans, while offering a great deal of valuable anatomic information, are slow to acquire. Scans of a sufficient resolution for neurosurgery can take on the order of 10 minutes to acquire, depending on field of view. Noniterative approaches could reduce complexity and anesthesia time.
This work describes efforts to create and validate a new trajectory guide that enables faster, accurate trajectory guidance in minimally-invasive neurosurgeries. Using new hardware and software, a single scan approach was used to perform drill guidance and device insertion on phantoms and cadaver heads.
The proposed methodology accurately guided needles to targets within phantoms and human cadaver brains using a single targeting scan. The initial design produced a radial error of 1.4±0.8mm in phantoms and 1.5±0.8mm in cadaver brains.
The proposed device and software accelerate trajectory guidance in minimally-invasive neurosurgeries by reducing the number of acquired scans and procedural steps. This in turn minimizes time under anesthesia.
Multi-Platform Patient Monitor System
Authors: Ozturk Ertan , Yapıcı Ozan Emre , Unal Mehmet , Bozacı Ilgın , Çakıcı Osman 
Published: August 2024

Abstract
Patient Monitors (PM) provide momentarily display of the multiple physiological signals of patients interpreted by medical professionals for diagnostic purposes. Clinical Research and academic have brought new techniques for illness diagnosis, therefore traditional patient monitors are required to be adapted for new diagnosis techniques to help medical practitioners. Besides, it is required to access patient’s monitored data by medical doctors from anywhere, anytime.
In this paper, we present the state of art architecture of our, commercially available, multi-platform patient monitor system, which can run on various hardware and software platforms, meaning that the application software can run on all available personal computers and mobile devices. Moreover, we show its flexibility to include new algorithms for diagnosis of illnesses by presenting the detection of Sepsis disease. Consequently, our patient monitor system is also a research tool to implement new algorithms and observe the results in a full-scale system.