bluuebunny/crossref_metadata_2025 huggingface dataset:
Non-Spherical Droplet Dispersion in Homogeneous Isotropic Turbulent Flow
Authors: Lin Yushu , Palmore John
Published: January 2025

Motivated by the study of spray combustion in aviation gas turbine engines, this work addresses the dispersion of non-spherical droplets in turbulence. The most popular strategy for modeling spray is using the Lagrangian particle tracking (LPT) method, which represents the spray as consisting of discrete collection of spherical particles. One limitation of this approach is that it neglects the importance of droplet deformation on the dynamics of sprays. Several past works have discussed the importance of non-sphericity in modeling real droplets including works conducted by our research group. Some of our past work has demonstrated the importance of the deformation on droplet vaporization, combustion and drag. However, those works have investigated the effect of deformation on droplets in simple configurations such as isolated droplets in uniform flows. The purpose of this work is to investigate the effect of droplet deformation on spray dynamics in a more practical configuration of droplets in turbulent flows. By utilizing an in-house code developed for multiphase flows, this work uses homogeneous isotropic turbulence (HIT) as the framework to investigate how the trajectories of non-spherical particles differ from spherical ones. The temporal Lagrangian autocorrelation of non-spherical droplet velocity is higher than that of spherical droplet, showing a better dispersion of non-spherical droplet. The mean Stokes number shows the dominance of intertia effect of droplets, and a higher mean Stokes number for non-spherical droplets indicates a weaker droplet clustering or preferential concentration.
Enhancing Mechanical Properties of 3D Printed Polymers Through Metallic Surface Coating: A Finite Element Analysis
Authors: Kafle Bibek , Balsamy Kamaraj Abishek
Published: January 2025

Additive Manufacturing (AM) has enabled the production of intricate designs, such as lattices, with high geometric accuracy, reduced material wastage, and improved mechanical properties. However, 3D-printed structures made of polymers often lack the required mechanical strength. Coating 3D-printed polymer structures with metals can improve their thermal properties, conductivity, wear resistance, aesthetic appearance, and strength-to-weight ratio to address this issue. This study explores the linear finite element analysis of strut-based lattice structures with metal surface coatings under uniaxial load. The study used ASTM standard Type III dog-bone specimens with Diamond-type strut-based lattices. The base (substrate) materials considered were ABS (Acrylonitrile butadiene styrene) and vat photopolymerized resin, while common metals Copper (Cu) and Nickel (Ni) were used as coating materials. The thickness of the coating varied from 10 μm to 500 μm, and incremental load was applied to the model until it exhibited elastic yielding. The study results showed that the specimen’s modulus of elasticity improved with the application of metal coating. The modulus was observed to be maximum when the coating thickness was minimum (10 μm), and gradually decreased as the coating thickness increased. The mechanical properties, such as resilience and stiffness, improved with increased coating thickness. The maximum strength-to-weight ratio was obtained when the coating thickness was 200 μm. This study provides valuable insights into enhancing the structural performance of strut-based lattices through surface coatings. It contributes to advancements in lightweight and efficient engineering materials and designs.
Rheological Analysis of Stress and Strain Rate of Non-Spherical Bubble With Multi-Mode Interfacial Perturbation in a Single and Multi-Bubble Systems Under Pressure Waves
Authors: Isazadeh Amin , Bhaduri Sreetam , Ziviani Davide , Claridge David E.
Published: January 2025

This paper introduces a multi-mode perturbation model for non-spherical bubbles, developed using potential function theory and spherical harmonics. Employing a sophisticated numerical framework that integrates adaptive time advancement (ATA) and mesh refinement (AMR), the study rigorously solves coupled ordinary differential equations (ODEs) and partial differential equations (PDEs) in a non-dimensional framework. Analysis is split between Rayleigh collapse under constant external pressure and dynamic collapse influenced by acoustic pressure waves. The study systematically investigates the effects of initial particle size, perturbation amplitude, and mode degree on Rayleigh collapse dynamics, revealing that larger bubbles exhibit longer collapse and rebound times, while smaller bubbles rapidly reach equilibrium. In scenarios involving acoustic waves, the investigation focuses on the impact of wave frequency and medium compressibility. Results indicate that higher wave frequencies and fluid compressibility significantly reduce the time for system oscillations to synchronize with external pressure waves, enhancing damping effects. Specifically, compressibility was found to accelerate synchronization, reducing large-amplitude oscillation cycles more than twofold compared to incompressible conditions. Additionally, at higher perturbation modes, amplitude damping occurs more rapidly, underscoring the influence of mode degree on the damping characteristics. Spanning Reynolds numbers from 1.65 to 1.65E+7 for Rayleigh collapses and 9.98E−4 to 9.98E+3 for acoustic-driven scenarios, the research highlights the substantial impact of fluid compressibility and perturbation parameters on bubble dynamics, providing insights that contrast sharply between micro-scale and macro-scale particle behaviors.
Comparative Analysis of Different Void Shapes on Thermal Conductivity of Silicon Nanowires
Authors: Dey Aninda , Zim Nafis Sadik , Morshed A. K. M. Monjur , Paul Titan C.
Published: January 2025

Silicon nanowires (SiNWs) have great potential as efficient thermoelectric materials due to their significantly lower thermal conductivity compared to bulk silicon. In this study, we analyze the effect of different void shapes on the thermal conductivity of SiNWs using large-scale atomic/molecular massively parallel simulator (LAMMPS) simulations. For each vacancy arrangement, the thermal conductivity of silicon nanowires was measured for a different percentage of the removed atom. Our results show that voids have a big effect on the thermal conductivity of silicon nanowires. For different compositions, this reduction effect ranges from 50% to 75% compared to pure SiNWs. It has been found that cuboidal void reduces thermal conductance slightly more than spherical void. When the 2.80% atom is removed, thermal conductivity is reduced by 64.5% for cuboidal void, which is 9% more than spherical void. We also discovered that for the same volume of voids, different void orientations produce different results. To determine the cause of this significant decrease in thermal conductivity, an analysis of the vibrational density of states (VDOS) is undertaken. It is found that the high ratio of surface area to volume leads to multiple boundary inelastic scatterings of phonons, resulting in a substantial reduction in thermal conductivity. Also, the presence of voids leads to a greater disparity in mass, resulting in reduced heat conductivity. The results suggest that including vacancy defects is an effective strategy for enhancing the thermoelectric efficiency of silicon nanowires.
Verification and Validation of a Novel Miniaturized Kolsky Bar Using Published Polymethyl Methacrylate (PMMA) Data
Authors: Grube Ryan N. , Hannah Thomas W. , Martin Valerie A. , Ellis Stephen , Kraft Reuben H.
Published: January 2025

The Kolsky bar experiment is used to determine material properties of various materials at high strain rates. This paper aims to use published data of Kolsky bar experiment stress versus strain results to establish a benchmarking methodology to validate and verify a novel miniaturized Kolsky bar. Creations of a Johnson-Cook plasticity and damage model are implemented into an Abaqus Finite Element simulation of a novel miniaturized Kolsky bar to simulate the mechanical material properties of polymethyl methacrylate (PMMA) at high strain rates. The Finite Element simulation is proved to produce viable results through establishing proper wave propagation throughout the Kolsky bar system and replication of the Johnson-Cook plasticity model results. A comparison of experimental and simulation data will result in the declaration of the validity of the novel miniaturized Kolsky bar for PMMA and its material class. Due to the sensitivity of the experimental system, data analysis for statistical evidence is needed to prove that the experimental data matches the Johnson-Cook model prediction after a large population of properly setup experiments are performed. Future research is determined to be beneficial for establishing material properties of more elastic and ductile materials at high strain rates for biomedical purposes.
Optimization of Infill Percentage Versus Nozzle Diameter in Fused Deposition Modeling 3D Printing
Authors: Watson Olivia , Blake Boston , Pagano Steven , Eslami Babak
Published: January 2025

Fused Deposition Modeling (FDM) 3D printing has evolved from a prototyping tool to a multifaceted manufacturing technique. To fully harness its capabilities, improving production repeatability, efficiency, and material quality is essential. This study explores the relationship between nozzle diameters and two common filaments: polylactic acid (PLA) and acrylonitrile butadiene styrene (ABS). Nozzle diameter is crucial in FDM 3D printing, influencing print quality, speed, and material flow. However, the impact of varying nozzle diameters on different filaments is underexplored. Our research fills this gap, providing key insights. We found significant differences in print quality and mechanical properties across various nozzle diameters and materials. Smaller nozzles generally produce better quality prints and surface finishes but take longer. Material-specific nozzle selection is important, as some filaments work better with certain nozzle sizes. PLA performs well across various sizes, showing excellent print quality and robustness. ABS is sensitive to larger nozzles due to its high printing temperature needs.

Our findings offer valuable guidelines for selecting nozzle sizes tailored to specific filaments, enhancing 3D printing efficiency, precision, and quality. These insights are particularly beneficial for industries like automotive and consumer goods, where precision and customization are crucial. Understanding nozzle diameter and filament dynamics can also lead to advanced printing algorithms and material formulations, optimizing multi-material printing and other complex applications.
Investigating the Potential of Nanocellulose as an Additive in Liquid Fuels to Enhance Combustion Behavior
Authors: Mollick Rahat , Ratner Albert
Published: January 2025

A useful strategy for enhancing liquid fuels entails the introduction of nanoparticles to modify their properties. This method provides versatility in customizing fuels to suit current combustion systems or adapting them to meet the requirements of diverse types of combustion devices and operating conditions, leading to improved combustion efficiency and lower emissions. Over the years, researchers have investigated a wide variety of nanoparticles as fuel additives and these nanoparticles can be broadly classified into two types: metal-based nanoparticles and carbon-based nanoparticles. Metal-based nanoparticles have proven highly effective in improving the combustion performance of base fuels; however, they come with inherent issues, including environmental pollution, and clogging in combustion systems. Among carbon-based nanoparticles, Nanocellulose is particularly attractive as it is derived from renewable sources such as plants or agricultural waste, making it an environmentally friendly option compared to fossil fuel-based additives Nanocellulose additives can enhance combustion efficiency and reduce carbon monoxide and hydrocarbon emissions due to their high surface area, which promotes heat transfer and more complete combustion. This work provides a detailed investigation into the combustion behavior of liquid fuels enhanced with Cellulose Nanocrystals (CNC). Experimentation with single component surrogates has been demonstrated as an effective technique to mimic the burning behavior of complex hydrocarbons. For the investigations in this research article, Dodecane and Methyl Decanoate are the chosen surrogates representing Diesel and Biodiesel, respectively. Around 6.4% percent increase in quasi-steady burning rate is observed in Dodecane enhanced with 0.5 wt% CNC, while 4.85% increase in quasi-steady burning rate has been observed for 1 wt% Nanocellulose infused Methyl Decanoate compared to the quasi-steady burning rates achieved with burning the base fuel counterparts.
From Principles to Practice: Product Design Foundations for a Circular Economy
Authors: Hapuwatte Buddhika , Last Noah , Karsli Sami , Aher Gaurav , Morris K. C. , Ferrero Vincenzo
Published: January 2025

A circular economy moves from the current linear model of production and consumption, i.e., the take-make-use-dispose model, to one that uses resources efficiently, avoids pollution, and creates triple bottom line (i.e., economic, environmental, and social) sustainability benefits. The transition from a linear to circular economy needs actions to facilitate resource recovery, extend the effective use-life of resources, and improve the productivity of resource utilization in the economy. Product design decisions set and limit possibilities for future activities throughout the entire life cycle. A comprehensive transformation of current design practices is needed to adapt to the new model of production and consumption. However, circular product design is yet to become mainstream in design curricula in higher education and workforce development.

Building from a synthesis of literature related to circular product design principles, this paper identifies underlying themes that may be integrated into design curricula. Two distinct qualitative analysis methods were used: First, a Collaborative Thematic Analysis to assign codes to the source principles and subsequently use them to develop descriptive themes. Second, a Natural Language Processing approach to vectorize the same set of design principles and cluster them based on similarity. Ultimately, the resulting themes from both approaches are compared to each other. While the design principles target practitioners, these themes can teach the fundamentals of circular economy, including how to think about design decisions in a larger circular economy system. Designers will need this fundamental understanding to make use of the specific circularity principles. Future work will further refine the themes identified here and through collaboration with academia and industry narrow the set to provide a foundation for circular economy and circular product design education.
Lower Bound Eigenvalues of a Timoshenko-Ehrenfest Vibrating Beam Using the Wittrick-Williams Algorithm
Authors: Watson Andrew , Pellicano Francesco , Zippo Antonio , Howson W. Paul
Published: January 2025

The Wittrick-Williams algorithm excels in solving transcendental eigenvalue problems arising from the exact solutions of governing differential equations. Initially developed for structural mechanics, where eigenvalues are non-negative, the algorithm’s versatility extends beyond. The authors demonstrate that negative eigenvalues, present in other scientific disciplines, do not hinder the algorithm’s effectiveness.

The exact solution to the axially loaded free vibration of the Timoshenko-Ehrenfest vibrating model was formulated in the early 1970s, marking a groundbreaking milestone in the study of vibration of continuous systems. The exact solution approach utilises the dynamic stiffness matrix method, providing a precise means to converge with certainty upon any specific natural frequency of a plane frame. This work was further developed in the following decade to include the scenario of a beam on an elastic foundation modelled as a Winkler foundation. More recently subsequent research by the first and fourth authors explored the computation of negative eigenvalues for the Laplace operator, analogous to the axial vibration of a bar.

The analysis method presented is specifically tailored to the free vibration of structural systems that can be precisely analyzed through exact solutions of differential equations. This results in real eigenvalues that are bounded below. While this approach necessitates the first eigenvalue to be real, this paper illustrates that the first eigenvalue can be either positive (as commonly seen in structural mechanics) or negative. This property enables the utilization of the Wittrick-Williams algorithm to converge on any desired eigenvalue with machine accuracy.

An example is provided by computing the first eigenvalue of a Timoshenko-Ehrenfest beam supported by a negative stiffness spring. Since the first eigenvalue is negative, the problem is redefined as a vibrating beam on an elastic foundation, ensuring the first eigenvalue becomes positive. Solving this modified problem reveals the necessary eigenvalues through a straightforward mathematical operation. This methodology finds broad applicability in mathematical disciplines where negative eigenvalues arise, providing an efficient means to extract the necessary eigenvalues. The vibration behavior of frameworks is directly analogous to solving the problem of differential operators acting on graphs or quantum graphs, a topic of current interest in mathematics. The spectral properties of quantum graphs can be obtained by the methods put forward by this paper. Thus, this paper showcases the interdisciplinary nature of the work.
Biomimetic Design and Development of an Oryctodromeus-Inspired Robotic Dinosaur Skeleton
Authors: Bingham Kyler , Hafezi Amir , Thapa Anish , Sourani Yancheshmeh Sara , Zakrevski Christopher , Berry Matthew , Das Shaibal , Walker Payton , Cortez Lopez Juan , Thompson Dominik , Gay Robert J. , Deemyad Taher
Published: January 2025

This project presents the design and development of a robotic dinosaur skeleton in real size inspired by Oryctodromeus, aimed at achieving bipedal locomotion with minimal actuation. Emphasizing the upper body, the study addresses the complex control and balance challenges inherent in bipedal robots. Our objective is to precisely replicate the movement and biomechanics of Oryctodromeus, known for its distinctive long tail and limited arm mobility. Adopting a holistic approach, the robotic skeleton integrates various mechanisms and materials tailored to activate different segments, ensuring synchronized movement reminiscent of the dinosaur’s locomotion. The design prioritizes minimal actuation with substantial modifications and mimics the leg structure from the avian characteristics. A user-friendly control system facilitates the seamless operation of various parts of the robot. Beginning with a detailed CAD model, subsequent phases involve prototype construction and rigorous testing, validating the efficacy of the design approach. Meticulous analysis and optimization of critical components enable biomimetic movement, supported by advanced simulation techniques. Utilizing emerging technologies such as additive manufacturing, the project streamlines fabrication processes while upholding structural integrity. Despite ongoing development, the robotic dinosaur holds promise for diverse applications in research, education, and entertainment, underscoring the interdisciplinary collaboration among engineers, paleontologists, and robotics experts.
Enhancing Engine Sound Classification With a CNN Model
Authors: Palreddy Chandana , Purimetla Ujjwal , Vijayakumar Harshith , Loignon Tyler , Gurupatham Sathish
Published: January 2025

This study introduces a novel methodology for classifying engine sounds into distinct categories, including Exhaust Leak, Rod Knock, and Lifter Tick, utilizing advanced signal processing and machine learning techniques. Despite diligent efforts, the classification model achieved a modest accuracy of 60%. One contributing factor to this performance could be the limited size and diversity of the training dataset, potentially failing to capture the full range of real-world engine sound variations. Additionally, the feature representation and selection process may not have fully captured the unique characteristics of each engine sound category. The classification model was developed using a Convolutional Neural Network (CNN) architecture. The CNN model comprises multiple convolutional layers followed by fully connected layers, enabling spatial feature extraction from spectrogram-based representations of engine sound recordings. Hyperparameters such as the number of convolutional filters, filter sizes, dropout rates, and learning rate were fine-tuned through empirical testing and cross-validation.

To enhance training effectiveness, 500 files per class were utilized for training data, while 50 files per class were reserved for testing purposes. This expanded dataset aims to provide a more comprehensive representation of engine sound variations across different categories.

Future research directions could involve augmenting the training dataset with a wider range of samples and implementing advanced feature engineering techniques like deep feature learning or transfer learning to extract more informative representations from raw audio data. Additionally, ensemble learning methods that combine multiple classifiers or models could boost classification performance by leveraging diverse insights. Furthermore, integrating domain-specific knowledge and expert annotations into the model training process may enhance its ability to generalize across various engine sound scenarios.

In conclusion, while the CNN model presented in this study shows promise for engine sound classification, there is potential for improvement in model architecture, feature representation, dataset augmentation, and domain knowledge integration. Addressing these aspects could lead to more accurate automotive diagnostic systems capable of identifying mechanical issues based on acoustic signatures, thereby enhancing vehicle safety and reliability.
Temperature-Responsive Needles for Improved Hemodialysis Patient Care
Authors: Sarker Fayad , Sklavounos Petros
Published: January 2025

In the United States, hemodialysis treatments commonly use medical-grade stainless needles. However, their rigidity often causes patient discomfort and vascular injury, adversely affecting treatment compliance. This study presents a novel needle fabricated from a thermoplastic polymer blend of Poly(methyl methacrylate) (PMMA), Polypropylene carbonate (PPC), and Polyvinyl acetate (PVAc), designed to transition from a rigid to flexible state at body temperature. Tensile tests of our polymer blend produced a tensile modulus of 1.73 GPa at 24°C and 580 MPa at 37°C, corroborating that the needle remains sufficiently rigid during insertion and flexible to conform to the vasculature. This innovative needle design, with its dual-phase functionality, allows for vascular access and is seamlessly adoptable by practitioners accustomed to medical-grade stainless steel needles. Its glass transition behavior directly improves patient comfort, thereby improving patient adherence to regular hemodialysis treatments.
Lysosomal dysfunction and inflammatory sterol metabolism in pulmonary arterial hypertension
Authors: Harvey Lloyd D. , Alotaibi Mona , Tai Yi-Yin , Tang Ying , Kim Hee-Jung J. , Kelly Neil J. , Sun Wei , Woodcock Chen-Shan C. , Arshad Sanya , Culley Miranda K. , El Khoury Wadih , Xie Rong , Al Aaraj Yassmin , Zhao Jingsi , Hafeez Neha , Rao Rashmi J. , Jiang Siyi , Negi Vinny , Kirillova Anna , Perk Dror , Watson Annie M. , St. Croix Claudette M. , Stolz Donna B. , Lee Ji Young , Cheng Mary Hongying , Zhang Manling , Detmer Samuel , Guzman Edward , Manan Rajith S. , Saggar Rajan , Haley Kathleen J. , Waxman Aaron B. , Okawa Satoshi , Schwantes-An Tae-Hwi , Pauciulo Michael W. , Wang Bing , Webb Amy , Chauvet Caroline , Anderson Daniel G. , Nichols William C. , Desai Ankit A. , Lafyatis Robert , Nouraie S. Mehdi , Wu Haodi , McDonald Jeffrey G. , Cheng Susan , Bahar Ivet , Bertero Thomas , Benza Raymond L. , Jain Mohit , Chan Stephen Y.
Published: January 2025

Vascular inflammation regulates endothelial pathophenotypes, particularly in pulmonary arterial hypertension (PAH). Dysregulated lysosomal activity and cholesterol metabolism activate pathogenic inflammation, but their relevance to PAH is unclear. Nuclear receptor coactivator 7 (
NCOA7
) deficiency in endothelium produced an oxysterol and bile acid signature through lysosomal dysregulation, promoting endothelial pathophenotypes. This oxysterol signature overlapped with a plasma metabolite signature associated with human PAH mortality. Mice deficient for endothelial
Ncoa7
or exposed to an inflammatory bile acid developed worsened PAH. Genetic predisposition to NCOA7 deficiency was driven by single-nucleotide polymorphism rs11154337, which alters endothelial immunoactivation and is associated with human PAH mortality. An NCOA7-activating agent reversed endothelial immunoactivation and rodent PAH. Thus, we established a genetic and metabolic paradigm that links lysosomal biology and oxysterol processes to endothelial inflammation and PAH.
Atomic locations and adsorbate interactions of Al single and pair sites in H-ZSM-5 zeolite
Authors: Li Guangchao , Foo Christopher , Fan Raymond , Zheng Mingji , Wang Qiang , Chu Yueying , Li Jiasi , Day Sarah , Steadman Paul , Tang Chiu , Lo Tsz Woon Benedict , Deng Feng , Tsang Shik Chi Edman
Published: January 2025

The distribution of substitutional aluminum (Al) atoms in zeolites affects molecular adsorbate geometry, catalytic activity, and shape and size selectivity. Accurately determining Al positions has been challenging. We used synchrotron resonant soft x-ray diffraction (RSXRD) at multiple energies near the Al K-edge combined with molecular adsorption techniques to precisely locate “single Al” and “Al pairs” in a commercial H-ZSM-5 zeolite. This analysis depicts three distinct Al tetrahedral (T) sites: T8, T6, and T4. A combined suite of characterizations, including ammonia temperature-dependent desorption, neutron powder diffraction, solid-state nuclear magnetic resonance spectroscopy, and density functional theory calculations, reveal isolated ammonia adsorption on T8 as “single Al” in the straight channel and bridged ammonia adsorption on T6 and T4 as an “Al pair” (Al
T6
-O-Si
T5
-O-Al
T4
) in the straight-sinusoidal intersection.
Private fusion firms put bold claims to the test
Authors: Clery Daniel
Published: January 2025

Amid skepticism, companies bet that speed and innovation can realize fusion’s promise
‘Cataclysmic:’ Experts decry U.S. departure from WHO
Authors: Vogel Gretchen
Published: January 2025

Trump’s decision to leave would be a financial blow to the agency and “isolate” the U.S. from health intelligence
Canadian science girds for shift
Authors: Owens Brian
Published: January 2025

Conservative Party expected to win elections later this year
Minimally important change on the Columbia Impairment Scale and Strengths and Difficulties Questionnaire in youths seeking mental healthcare
Authors: Krause Karolin R , Lee Alina , Shan Di , Cost Katherine Tombeau , Hawke Lisa D , Cheung Amy H , Cleverley Kristin , de Oliveira Claire , Quinlan-Davidson Meaghen , Moretti Myla E , Henderson Jo L , Ma Clement , Szatmari Peter
Published: January 2025

Background

Evidence-based mental health requires patient-relevant outcome data, but many indicators lack clinical meaning and fail to consider youth perceptions. The minimally important change (MIC) indicator designates change as meaningful to patients, yet is rarely reported in youth mental health trials.

Objective

This study aimed to establish MIC thresholds for two patient-reported outcome measures (PROMs), the Columbia Impairment Scale (CIS) and the Strengths and Difficulties Questionnaire (SDQ), using different estimation methods.

Methods

A sample of 247 youths (14–17 years) completed the CIS and SDQ at baseline and at 6 months in a youth mental health and substance use trial. At 6 months, youths also reported perceived change. Three anchor-based (mean change, receiver operating characteristic analysis, predictive modelling) and three distribution-based methods (0.5 SD, measurement error, smallest detectable change) were compared.

Findings

Different methods yielded varying MIC thresholds. Predictive modelling provided the most precise anchor-based MIC: −2.6 points (95% CI −3.6, –1.6) for the CIS and −1.7 points (95% CI −2.2, –1.2) for the SDQ, indicating that score improvements of 12% for the CIS and 8% for the SDQ may be perceived as ‘important’ by youths. However, correlations between change score and anchor were below 0.5 for both measures, indicating suboptimal anchor credibility. Stronger correlations between the anchor and T2 PROM scores compared with T1 scores suggest the presence of recall bias. All MIC estimates were smaller than the smallest detectable change.

Conclusions

Predictive modelling offers the most precise MIC, but limited anchor credibility suggests careful anchor calibration is necessary.

Clinical implications

Clinicians may consider the MIC CI as indicative of meaningful change when discussing treatment impact with patients.

Trial registration number

NCT02836080.
Temperature and myocardial infarction among migrants in Kuwait
Authors: Wang Chenqing , Christiani David , Al-Hemoud Ali , Alahmad Barrak
Published: January 2025

Background

Kuwait, one of the world’s hottest countries, faces increasing temperatures due to climate change. With a large migrant population predominantly employed in physically demanding jobs, the exact effects and burdens of temperature exposure on cardiovascular risk among this population remain unknown. This study aimed to investigate the relationship between temperature and myocardial infarction (MI) risk among migrants in Kuwait.

Methods

MI hospital admissions data from 17 public hospitals in Kuwait from 2000 to 2017 were collected. Meteorological data, including daily temperatures and humidity, were obtained from monitoring stations. A time series analysis was conducted to examine the association between temperature and MI hospitalisation. A distributed lag non-linear model was used to study the lagged association of temperature. Seasonality, relative humidity and day of the week were adjusted for in the model. Excess hospitalisations attributed to temperature variations were calculated.

Results

A total of 26 839 MI cases were examined. The optimal temperature with the lowest MI cases was 39.2°C. Elevated MI risks were associated with both hot and cold temperatures above or below this threshold, particularly at shorter lag days. Hot temperatures showed a pronounced association at lag 0, while cold temperatures demonstrated a weak effect at lag 7. The cumulative risk of MI for cold temperatures was higher than the risk for hot temperatures. Annually, 300 (20.1%) MI cases can be attributed to all cool days (below 39.2°C). Very hot days (above 39.2°C) contributed to about 9 (0.6%) MI cases each year among migrants in Kuwait.

Conclusion

The study revealed a substantial burden of both hot and cold ambient temperatures and the risk of MI at shorter lag days among the migrant population in Kuwait. This study provides valuable insights for government officials to mitigate exposure to extreme temperatures, especially in occupational settings.
Homozygous missense variant inC2orf69causes early-onset neurodegeneration, leukoencephalopathy and autoinflammation
Authors: Oh Rachel Youjin , Maier Michael , Blaser Susan , Cameron Jessie , Hawkins Cynthia , Reversade Bruno , Yoon Grace
Published: January 2025

Biallelic pathogenic variants inC2orf69cause a fatal autosomal recessive multisystem disorder characterized by recurrent autoinflammation, hypomyelination, progressive neurodegeneration, microcephaly, failure to thrive, liver dysfunction, respiratory chain defects and accumulation of glycogen in skeletal muscle. No missense variants inC2orf69have been reported to date.

We report a 6-year-old boy with microcephaly, global developmental delays, lower limb spasticity with hyperreflexia, epilepsy, abnormal brain MRI, failure to thrive, recurrent fevers and transaminitis. Whole-exome sequencing identified a homozygous missense c.320 C>G, p.(Pro107Arg) variant of uncertain significance (VUS) inC2orf69. Skeletal muscle biopsy showed active and chronic muscle fibre degeneration with deposits of periodic acid–Schiff-positive material in affected tissues, consistent with abnormal glycogen storage. Mitochondrial respiratory assays were normal in muscle tissue. Primary patient fibroblasts showed normal levels of mRNA expression but significantly reduced levels of endogenous C2ORF69 protein and GBE1 by Western blot. We report a patient with a homozygous missense variant inC2orf69, causing loss of function. Depletion of endogenous GBE1 in affected cells can be considered a biomarker for this disorder and assist in the interpretation of VUS inC2orf69. This expands the clinical and genetic spectrum ofC2orf69-related disorder.
Impact of anesthetic methods on outcomes for patients with large core stroke undergoing endovascular treatment
Authors: Zhang Hongru , Fang Xing , Wu Mei , Fan Shitao , Guo Changwei , Yang Shihai , Shi Xiaolei , Huang Jia Cheng , Yang Jie , Li Linyu , Peng Zhouzhou , Xu Xu , Ma Jinfu , Yang Dahong , Zi Wenjie , Li Fengli , Mao Qingxiang , Wan Junfang
Published: January 2025

Background

The optimal anesthetic method for endovascular therapy in acute large core stroke remains unclear. This study aimed to evaluate the impact of anesthetic methods on outcomes in patients with large core stroke.

Methods

This study was a subanalysis of a prospective, multicenter registry at 38 stroke centers in China. Patients with large core stroke, defined as an Alberta Stroke Program Early CT Score (ASPECTS) of 0–5 within 24 hours of witnessed symptom onset, were analyzed. The primary outcome was favorable functional outcome (modified Rankin Scale score 0–3) at 90 days.

Results

484 eligible patients were included in this analysis. General anesthesia (GA) was used in 84 patients (17.4%), while non-general anesthesia (non-GA) was used in 400 patients (82.6%). Non-GA was comparable to GA in the primary outcome (37.8% vs 32.1%; adjusted odds ratio (aOR) 1.07, 95% confidence interval (95% CI) 0.60 to 1.91, P=0.83). Mortality at 90 days was 40% in the non-GA and 52.4% in the GA (aOR 0.71, 95% CI 0.41 to 1.22, P=0.21). The proportion of symptomatic intracranial hemorrhage at 48 hours was 13.8% in the non-GA and 11.9% in the GA (aOR 1.25, 95% CI 0.62 to 2.77, P=0.56). The results remained consistent in the propensity score-matched cohort and inverse probability of treatment weighting cohort.

Conclusion

In this cohort study of patients with large core stroke, no significant differences were found in functional and safety outcomes between non-GA and GA.
Where have all the rabies cases gone? Results of rabies virus surveillance in wildlife in the Yukon, Canada
Authors: Andrew Cassandra L , Henaff Maud , Fehlner-Gardiner Christine , Thang Cin , Knowles M Kimberly , Jung Thomas S , Harms N Jane
Published: January 2025

Rabies continues to affect wildlife and domestic animals in northern Canada and Alaska, but no cases have been reported in the Yukon since the 1970s. To better understand the presence of rabies in the territory, a surveillance program began in 2009, using opportunistically collected samples from 13 species of wild mammals. Samples were collected from trapped wildlife through carcass collection programs, from animals that were found dead by the public, and those involved in human-wildlife conflict or in vehicle collisions. All samples (n=763) were negative for rabies virus antigen. Five (<1% of individuals tested) Arctic foxes (Vulpes lagopus), the primary reservoir of the Arctic rabies strain, were tested. Canada lynx (Lynx canadensis; n=290; 38%), wolverine (Gulo gulo; n=108; 14%), wolf (Canis lupus; n=105; 14%), red fox (Vulpes vulpes; n=90; 12%), and little brown bats (Myotis lucifugus; n=55; 7%) comprised the majority of animals sampled. Shifts in distributional ranges of species and movements of migratory populations or dispersing individuals, especially from adjacent jurisdictions where rabies is reported, may rapidly alter rabies transmission dynamics in the Yukon. Thus, more targeted surveillance of reservoir species, especially at jurisdictional borders, is recommended to monitor for changes in rabies prevalence in the Yukon.
Coupled shifts in DOM composition and microbial community structure lead to variable biodegradation rates in thermokarst-affected permafrost stratigraphies
Authors: MacDonald Erin N , Saidi-Mehrabad Alireza , Lanoil Brian , Lech Gabriela , Tank Suzanne
Published: January 2025

Permafrost thaw can drastically alter dissolved organic matter (DOM) composition within fluvial networks, and simultaneously affect the microbial communities that degrade DOM. However, it is unclear how coupled thaw-induced change in DOM and microbes might affect microbial decomposition of permafrost-origin DOM (biodegradation), and therefore possible mineralization to carbon dioxide. Here, we use a series of incubations to explore how biodegradation varies with DOM and microbe source, and how microbial community composition changes following incubation with thaw-origin DOM. We undertake this work using leachates from different stratigraphic units across a series of retrogressive thaw slumps on the Peel Plateau, Canada, and microbial communities from upstream of, and draining, slumps. DOM composition and biodegradation varied by stratigraphic unit and across sites that were only tens of kilometers apart, but situated along different recessional fronts of the Laurentide Ice Sheet. Permafrost leachates from paleo-active layers were generally more biolabile than leachates from deeper, unmodified tills, and both were more labile than active layer leachates. Biodegradation also tended to be slightly greater for incubations inoculated with microbes from unimpacted stream water. These results emphasize that permafrost thaw-derived DOM composition and biolability will vary across stratigraphic, landscape, and regional scales, and that the composition of the recipient microbial community may play a role in determining immediate DOM fate.
Identifying Beluga Distribution in the Tarium Niryutait Marine Protected Area using Passive Acoustic Monitoring
Authors: Scharffenberg Kevin Charles , MacPhee Shannon A. , Mouy Xavier , Whalen Dustin , Wright Andrew , Loseto Lisa L.
Published: January 2025

Arctic estuaries are important summer habitats for beluga whales (Delphinapterus leucus) and many populations form seasonal aggregations at these locations. This study presents the first comprehensive long-term analysis of beluga distribution within the Mackenzie Estuary since the 1970s and 1980s. Leveraging eight years of passive acoustic monitoring data, we assess the consistency of beluga habitat use over time and space by comparing vocalization rates at select monitoring locations annually and providing a benchmark upon which to monitor ecological change in the Tarium Niryutait Marine Protected Area. Findings reveal temporal consistency in beluga distribution and demonstrate site fidelity in alignment with known habitat hotspots; however, results also highlight a degree of inter-annual variability in beluga habitat use, indicating that belugas may alter their distribution in response to environmental and anthropogenic factors. Additionally, we develop a suite of simple univariate metrics to define the timing of belugas movements to and from the estuary. Our data support previous aerial survey findings and Inuvialuit Knowledge that beluga entry into the estuary is closely tied to the timing of ice breakup. Characteristics of the annual beluga aggregation should be considered in the relation to ice breakup date when interpreting indicators of change in habitat use.
Microbial communities in Hudson Strait amidst rapid environmental changes
Authors: Loutet Samantha Jane Tanlimco , Sanger Alia , Strong Kallie , Collins Eric , Mahmoudi Nagissa
Published: January 2025

Climate change is rapidly altering Arctic marine environments, leading to warmer waters, increased river discharge, and accelerated sea ice melt. The Hudson Bay Marine System (HBMS) experiences the fastest rate of sea ice loss in the Canadian North resulting in a prolonged open water season during the summer months. We examined microbial communities in the Hudson Strait using high throughput 16s rRNA gene sequencing during the peak of summer, in which the bay was almost completely ice-free, and air temperatures were high. We found that salinity and temperature significantly affected the taxonomic composition among microbial communities across sites. We observed a higher relative abundance of specific Polaribacter sp. ASVs at more saline sites. Shannon diversity was not significantly impacted by salinity or temperature. These results contribute to our understanding of surface water microbial community composition in the Hudson Strait and shed light on how future salinity and temperature conditions may favour certain microbial populations.
“I don’t see anything specifically about Black/African Americans.” Testing an Alzheimer-specific generative AI tool tailored for African American/Black communities
Authors: Bosco Cristina , Shojaei Fereshtehossadat , Theisz Alec A. , Nguyen Vivian , Song Haoru , Han Ruixiang , Osorio Torres John A. , Chheda Darshil , Lin Jenny , Peng Xinran , Waseem Nawal Z. , Simpkins Chelsea , Cureton Bianca , Himes Anna K. , Jessup Nenette M. , Lu Yvonne , Hendrie Hugh C. , Barnes Priscilla A. , Hill Carl V. , Shih Patrick C.
Published: January 2025

Low levels of health literacy concerning Alzheimer's Disease and related dementias (ADRD) impact African American/Black communities access to appropriate ADRD care. Additionally, a legacy of mistrust in medical research due to systemic racism, has resulted in insufficient participation in ADRD clinical trials among African American/Black adults.

This study explores the potential of generative AI to improve ADRD literacy and encourage participation in clinical trials among African American/Black older adults. We designed a mobile health intervention featuring AI-driven conversational agents - a chatbot and a voice assistant - specifically developed for this population. We tested the quality of the intervention using heuristics methodology adapted to the target population along with inputs from African American/ Black medical professionals and UX designers.

Key findings highlight the unique needs of the African American/Black communities for culturally relevant content that is accessible to users with varying language levels and tailored to users’ geographical location. Concerning the interaction, high levels of personalization and control over the interaction can promote the use of the tool, by minimizing complexity and maximizing accessibility.

These findings show the novel contribution offered by our study in the domain of designing health technology with generative AI, particularly LLMS, for African American/Black communities.
Usefulness of Large Language Models (LLMs) for Student Feedback on H&P During Clerkship: Artificial Intelligence for Personalized Learning
Authors: Bany Abdelnabi Ahmad A , Soykan Bulent , Bhatti Danish , Rabadi Ghaith
Published: January 2025

Large Language Models (LLMs) notably GPT-4, demonstrate exceptional language generation and comprehension abilities, and they have potential uses in clinical practice, learning, and medical research. In this study, we explore practical use of Large Language Models (LLMs) in enhancing case-based learning in medical education. The study employes a designed mixed-methods approach, combining quantitative metrics with qualitative feedback from 100 medical students, providing comprehensive insights into both the technical performance and educational value of LLM-based feedback systems. Our results indicate that LLMs can enhance medical students’ History and Physical (H&P) skills by providing personalized insights, fostering critical thinking, and improving their abilities to analyze, diagnose, and present clinical cases. This study has surfaced significant insights into the potential benefits and limitations of integrating LLMs into medical education. Our findings show the positive impact of LLMs on enhancing personalized learning experiences, critical thinking, and the effectiveness of case-based learning aids and highlighting its limitations.
The Role of Deep Learning in Medical Image Inpainting: A Systematic Review
Authors: Santos Joana Cristo , Tomás Pereira Alexandre Hugo , Seoane Santos Miriam , Henriques Abreu Pedro
Published: January 2025

Image inpainting is a crucial technique in computer vision, particularly for reconstructing corrupted images. In medical imaging, it addresses issues from instrumental errors, artifacts, or human factors. The development of deep learning techniques has revolutionized image inpainting, allowing for the generation of high-level semantic information to ensure structural and textural consistency in restored images. This paper presents a comprehensive review of 53 studies on deep image inpainting in medical imaging, analyzing its evolution, impact, and limitations. The findings highlight the significance of deep image inpainting in artifact removal and enhancing the performance of multi-task approaches by localizing and inpainting regions of interest. Furthermore, the study identifies magnetic resonance imaging and computed tomography as the predominant modalities and highlights generative adversarial networks and U-Net as preferred architectures. Future research directions include the development of blind inpainting techniques, the exploration of techniques suitable for 3D/4D images, multiple artifacts, and multi-task applications, and the improvement of architectures.