bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Application of Biomaterial‐Based Spinal Cord Tissue Engineering
Authors: Ma Liang , Zhang Zhen , Mu Yulei , Liu Bangheng , Zhou Huiqun , Wang Dong‐An 
Published: October 2024

AbstractAdvancements in biomaterial‐based spinal cord tissue engineering technology have profoundly influenced regenerative medicine, providing innovative solutions for both spinal cord organoid development and engineered spinal cord injury (SCI) repair. In spinal cord organoids, biomaterials offer a supportive microenvironment that mimics the natural extracellular matrix, facilitating cell differentiation and organization and advancing the understanding of spinal cord development and pathophysiology. Furthermore, biomaterials are essential in constructing engineered spinal cords for SCI repair. The incorporation of biomaterials with growth factors, fabrication of ordered scaffold structures, and artificial spinal cord assemblies are critical insights for SCI to ensure structural integrity, enhance cell viability, and promote neural regeneration in transplantation. In summary, this review summarizes the contribution of biomaterials to the spinal cord organoids progression and discusses strategies for biomaterial‐based spinal cord engineering in SCI therapy. These achievements underscore the transformative potential of biomaterials to improve treatment options for SCI and accelerate future clinical applications.
Disjoint p$p$‐convergent operators and their adjoints
Authors: Botelho Geraldo , Garcia Luis Alberto , Miranda Vinícius C. C. 
Published: October 2024

AbstractFirst, we give conditions on a Banach lattice so that an operator from to any Banach space is disjoint ‐convergent if and only if is almost Dunford–Pettis. Then, we study when adjoints of positive operators between Banach lattices are disjoint ‐convergent. For instance, we prove that the following conditions are equivalent for all Banach lattices and : (i) a positive operator is almost weak ‐convergent if and only if is disjoint ‐convergent; (ii) has order continuous norm or has the positive Schur property of order . Very recent results are improved, examples are given and applications of the main results are provided.
Evaluation of forecasted wind speed at turbine hub height and wind ramps by five NWP models with observations from 262 wind farms over China
Authors: Jin Chenxi , Yang Yang , Han Chao , Lei Ting , Li Chen , Lu Bing 
Published: October 2024

AbstractAccurate wind speed forecasts are essential for optimizing the efficiency of wind energy operations. Currently, there is limited research on nationwide assessment of predictive performance in multiple numerical weather prediction (NWP) models for wind speed at turbine hub height over China, especially concerning wind ramp events. Utilizing observed measurements from 262 wind farms, this study evaluated the performance of five NWP models in forecasting the mean state and spatiotemporal variations of wind speed as well as wind ramps. The results indicated that the European Center for Medium‐Range Weather Forecast Integrated Forecasting System (ECMWF–IFS) performed the best in forecasting climatological wind speed with a temporal correlation coefficient (TCC) of 0.74 and root mean square error (RMSE) of 2.34 m s−1. Although not widely utilized in China, the model from Meteo‐France (MF–ARPEGE) showed promising potential for wind energy forecasting with a TCC of 0.72 and RMSE of 2.45 m s−1. In terms of temporal variations of wind speed, all the models could reasonably predict the seasonal variations of wind speed, whereas only three NWP models were able to capture the characteristics of the observed diurnal variation. An error decomposition analysis further revealed that the primary source of predicted error for wind speed was the sequence error component (SEQU), indicating the model errors were mainly attributed from the temporal inconsistency between forecasts and observations. Furthermore, the occurrences of wind ramps were generally underestimated by NWP models, while this shortcoming can be partly overcome by improving the time resolution of NWP models.
Electromagnetic Response of a Uniformly Moving Resistive Sheet
Authors: Marvasti Mohammad , Boutayeb Halim 
Published: October 2024

ABSTRACTBy using the finite‐difference time‐domain (FDTD) method and a two‐port network model, this letter investigates the response of a uniformly moving resistive sheet to illuminating electromagnetic plane waves, at normal incidence. The numerical Doppler frequency shifts and scattering matrix are matched with curve‐fitting expressions. The effects of motion on the impedance matrix, the chain matrix, and the continuity equations are analyzed. Moreover, the total energy of the transferred and reflected waves are studied for the cases of a resistive sheet moving toward or away from the plane wave source.
Diffusion network with spatial channel attention infusion and frequency spatial attention for brain tumor segmentation
Authors: Mi Jiaqi , Zhang Xindong 
Published: October 2024

AbstractBackgroundAccurate segmentation of gliomas is crucial for diagnosis, treatment planning, and evaluating therapeutic efficacy. Physicians typically analyze and delineate tumor regions in brain magnetic resonance imaging (MRI) images based on personal experience, which is often time‐consuming and subject to individual interpretation. Despite advancements in deep learning technology for image segmentation, current techniques still face challenges in clearly defining tumor boundary contours and enhancing segmentation accuracy.PurposeTo address these issues, this paper proposes a conditional diffusion network (SF‐Diff) with a spatial channel attention infusion (SCAI) module and a frequency spatial attention (FSA) mechanism to achieve accurate segmentation of the whole tumor (WT) region in brain tumors.MethodsSF‐Diff initially extracts multiscale information from multimodal MRI images and subsequently employs a diffusion model to restore boundaries and details, thereby enabling accurate brain tumor segmentation (BraTS). Specifically, a SCAI module is developed to capture multiscale information within and between encoder layers. A dual‐channel upsampling block (DUB) is designed to assist in detail recovery during upsampling. A FSA mechanism is introduced to better match the conditional features with the diffusion probability distribution information. Furthermore, a cross‐model loss function has been implemented to supervise the feature extraction of the conditional model and the noise distribution of the diffusion model.ResultsThe dataset used in this paper is publicly available and includes 369 patient cases from the Multimodal BraTS Challenge 2020 (BraTS2020). The conducted experiments on BraTS2020 demonstrate that SF‐Diff performs better than other state‐of‐the‐art models. The method achieved a Dice score of 91.87%, a Hausdorff 95 of 5.47 mm, an IoU of 84.96%, a sensitivity of 92.29%, and a specificity of 99.95% on BraTS2020.ConclusionsThe proposed SF‐Diff performs well in identifying the WT region of the brain tumors compared to other state‐of‐the‐art models, especially in terms of boundary contours and non‐contiguous lesion regions, which is clinically significant. In the future, we will further develop this method for brain tumor three‐class segmentation task.
To Gibbs or Not to Gibbs Effect of Entropic Contribution in the NMR Calculations of Flexible and Polar Molecules—Updating the DP4+App
Authors: Amichetti Milagros , Franco Bruno A. , Zanardi María Marta , Sarotti Ariel M. 
Published: October 2024

ABSTRACTThe application of quantum‐based NMR methods for the structural elucidation of natural and unnatural products has grown significantly. However, accurately calculating the conformational landscape of flexible molecules with intricate intramolecular hydrogen bonding (IHB) networks continues to be a major challenge. In this work, we thoroughly studied the effect of entropic contributions (trough Gibbs free energies calculations) in the DP4+ performance. Our results show that to solve biased systems with strong IHB interactions requires computing the Boltzmann contributions using Gibbs free energies computed with at least triple‐ξ basis set and SMD solvation model. In response to this finding, we have updated our DP4+App, a user‐friendly Python applet that automates the entire process of calculating DP4+ probabilities. In the new version, the program allows for calculating of conformational contributions at any selected theory level, using either SCF or Gibbs free energies.
Longitudinal relationships between free‐living activities, fatigue, and symptom severity in myasthenia gravis using cohort and individualized models
Authors: Dimmick Hannah L. , Jewett Gordon , Korngut Lawrence W. , Ferber Reed 
Published: October 2024

AbstractIntroduction/AimsFluctuating symptoms and fatigue are common issues in myasthenia gravis (MG), but it is unclear if these symptoms are related to physical activity or sleep patterns. This study sought to determine the day‐to‐day relationship between patient‐reported symptoms and physical activity and sleep over 12 weeks.MethodsSixteen participants with generalized MG wore a wrist‐mounted accelerometer continuously for the study duration and reported their symptoms and fatigue each evening. Cumulative link mixed models were used to analyze whether clinical and demographic characteristics, physical activity, and sleep were related to symptom severity and fatigue over the study period. Three types of models were constructed: a cohort model, a model in which data was scaled to each participant, and individual models.ResultsThe cohort model indicated that higher disease severity, female sex, more comorbidities, less physical activity, more inactive time, and lower quantity of sleep were significantly associated with increased symptom severity and fatigue (p < .05). However, in the within‐participant scaled model, there were almost no significant associations with physical activity or sleep. In the individual models, some participants showed similar results to the cohort model, but others showed no associations or the opposite response in some variables.DiscussionWhile physical activity and sleep were associated with self‐reported symptoms and fatigue within this population, this was not necessarily applicable to individuals. This demonstrates the importance of an individualized analysis for determining how physical activity and sleep may impact outcomes in MG, with implications for clinical and self‐management.
Limb‐girdle muscular dystrophies: A scoping review and overview of currently available rehabilitation strategies
Authors: D'Este Giorgia , Spagna Mattia , Federico Sara , Cacciante Luisa , Cieślik Błażej , Kiper Pawel , Barresi Rita 
Published: October 2024

AbstractLimb‐girdle muscular dystrophies (LGMDs) constitute a diverse group of inherited disorders primarily affecting skeletal muscle. Despite the absence of cures, rehabilitative treatments offer potential for preventing and mitigating loss of muscle strength. However, the role of exercise training in LGMD patients remains contentious. This review aims to provide an overview of the currently available motor rehabilitation strategies for the most common subtypes of LGMD. To identify relevant articles, we performed a systematic search in PubMed, Embase, Cochrane Library, and Web of Science, focusing on muscular and respiratory interventions. The search resulted in 560 potentially relevant articles, of which 16 were included in the review. Eight studies concentrated on neuromuscular functional rehabilitation therapy programs, seven combined both neuromuscular rehabilitation and interventions to maintain or enhance respiratory functionality and one focused on respiratory intervention only. Altogether, the papers examined offered a comprehensive view on the rehabilitative strategies available and provided an indication of the most valuable practices to deal with patients' health and needs. Upon analysis, we conclude that, when tailored to individual needs, muscle training can enhance strength and functional abilities, positively impacting psychological well‐being. However, generic protocols may lead to limited benefits, fatigue, pain, and compliance issues. Moreover, early management of respiratory symptoms and personalized respiratory physiotherapy can enhance patients' well‐being and their capability to participate in muscle training exercises. Future studies should not only refine rehabilitation approaches but also assess their impact on patients' quality of life, including psychological factors like depression and self‐esteem.
Modeling the Swelling Behavior of Clayey Geomaterials Across Scales: Advances and Challenges
Authors: Mhamdi Alaoui Hamza , Zhao Chaofa , Niu Wenbo , Hicher Pierre‐Yves 
Published: October 2024

ABSTRACTMost soils and rocks contain varying fractions of clay minerals within their solid matrix. These geomaterials can exhibit a significant swelling potential toward chemo‐thermo‐hydromechanical loadings. Several multiscale modeling techniques have been developed to ascertain their swelling behavior across various scales, with molecular dynamics (MD), micromechanics‐based approaches, and double‐porosity models being the most common. MD simulation is a computational technique that applies Newton's second law of motion to depict the movement of particles within a granular system. Micromechanics‐based approaches upscale the poro‐elasticity law from the clay layer level to the sample scale through homogenization. Dual‐porosity models are generally based on elasto‐plasticity, incorporating different hydro‐mechanical laws at two distinct scales. These models have been extensively used, particularly for clayey soils and bentonites, though their application to clayey rocks has not been reported in the literature. Although their significant contribution to the understanding of clay swelling behavior, these techniques have been insufficiently reviewed, compared, and discussed mutually in the literature. This paper aims to provide a cross‐look on these multiscale approaches by presenting the theoretical background of existing formulations, highlighting breakthrough results, discussing major differences and current challenges, and proposing future perspectives.
Dynamic Operational Planning in Warfare: A Stochastic Game Approach to Military Campaigns
Authors: McCarthy Joseph E. , Dahan Mathieu , White Chelsea C. 
Published: October 2024

ABSTRACTWe study a two‐player discounted zero‐sum stochastic game model for dynamic operational planning in military campaigns. At each stage, the players manage multiple commanders who order military actions on objectives that have an open line of control. When a battle over the control of an objective occurs, its stochastic outcome depends on the actions and the enabling support provided by the control of other objectives. Each player aims to maximize the cumulative number of objectives they control, weighted by their criticality. To solve this large‐scale stochastic game, we derive properties of its Markov perfect equilibria by leveraging the logistics and military operational command and control structure. We show the consequential isotonicity of the optimal value function with respect to the partially ordered state space, which in turn leads to a significant reduction of the state and action spaces. We also accelerate Shapley's value iteration algorithm by eliminating dominated actions and investigating pure equilibria of the matrix game solved at each iteration. We demonstrate the computational value of our equilibrium results on a case study that reflects representative operational‐level military campaigns with geopolitical implications. Our analysis reveals a complex interplay between the game's parameters and dynamics in equilibrium, resulting in new military insights for campaign analysts.
Long‐term monitoring of water table and saltwater intrusion dynamics through time‐lapse transient electromagnetic
Authors: Zamora‐Luria Juan Carlos , McLachlan Paul , Christiansen Anders Vest 
Published: October 2024

AbstractUnderstanding hydrogeological processes often requires continuous measurements, which in many cases are not cost‐efficient. Time‐lapse geophysical studies are invaluable for investigating dynamic subsurface processes. They offer several advantages over traditional borehole‐based monitoring methods, such as being cost‐efficient and non‐intrusive. However, to be effective as an early warning tool, these studies must provide real‐time information on the processes. This is often not feasible with traditional geophysical methods, which typically do not offer real‐time monitoring. In this study, we present a windowed inversion approach for time‐lapse transient electromagnetic (TEM) monitoring. The advantages of this approach include: (i) immediate and continuous results as each time‐step dataset is acquired; (ii) no limitations on the size of the monitoring period or dataset; and (iii) the use of model information from previous inversion results for robust and continuous outcomes. The results from a synthetic study are followed by two field case studies, demonstrating the advantages of the windowed inversion compared to the inversion of the full dataset. We monitored the water table dynamics of a shallow unconfined aquifer over 8 months and the saltwater intrusion in a confined aquifer over 10 months using a monitoring TEM (mTEM) system while collecting nearly continuous daily measurements. With the windowed approach, the water table dynamics was recovered with an accuracy of 10 cm, and the changes in salinity were tracked with results comparable to those of an EC data logger.
Rapid Synthesis of anti‐1,3‐Diamino‐4‐phenylbutan‐2‐ol Building Blocks via a Three‐Component Oxyhomologation and a Two‐Component Reducing System
Authors: Cabua Maria Chiara , He Xuefeng , Secci Francesco , Deloisy Sandrine , Aitken David J. 
Published: October 2024

AbstractN1‐substituted derivatives of anti‐(2R,3S)‐1,3‐diamino‐4‐phenylbutan‐2‐ol are important building blocks for the synthesis of therapeutically important molecules. We describe a simple protocol that allows transformation of N,N‐dibenzyl‐L‐phenylalaninal into such compounds in only two steps. The first step is a fully stereoselective three‐component MAC (Masked Acyl Cyanide) oxyhomologation reaction implicating different amines to give a panel of ten N,N‐dibenzyl‐O‐tert‐butyldimethylsilyl‐protected anti‐(2S,3S)‐allophenylnorstatin amides. The second step is a carbonyl‐activated hydride deprotection/reduction protocol using trimethylsilyl chloride and lithium aluminium hydride; the one‐pot two‐component system is more efficient than the alternative approach of isolating the deprotected amide intermediate before reduction.
Fast simulation of coronary in‐stent restenosis: A non‐intrusive data‐driven reduced order surrogate model
Authors: Shi Jianye , Manjunatha Kiran , Reese Stefanie 
Published: October 2024

AbstractModeling and simulation of coronary artery disease (CAD) is of great importance for supporting and predicting the outcome of percutaneous coronary intervention (PCI). However, an in silico model generally requires heavy computational resources. An effective reduced order surrogate model is indispensable in this context. This study aims to develop a non‐intrusive data‐driven reduced order surrogate model for coronary in‐stent restenosis (ISR) incorporating anti‐inflammatory drugs embedded in the drug‐eluting stents. The constitutive model includes a detailed multiphysics approach based on partial differential equations (PDEs), which include descriptions of platelet aggregation, growth‐factor release, cellular motility and drug deposition. Dimensionality reduction is carried out based on a 3D convolutional autoencoder, which comprises an encoder and decoder. The former condenses the full‐order solution into a lower‐dimensional latent space, while the latter recovers the full solution from the latent space. Special attention is paid to handle the multidimensional outputs and network architecture.
Tribological and mechanical endowments of polyoxymethylene by liquid‐phase exfoliated graphene nanofiller
Authors: Rustamov Ibrohim , Xiang Lehong , Xia Yinshui , Peng Wenfei 
Published: October 2024

AbstractIn this study, a viable route to the development of a high‐performance polyoxymethylene (POM)‐based nanocomposite is proposed to overcome tribomechanical‐related issues in high‐precision sliding parts. Prior to melt‐blending, graphene nanoplatelet (GNP) filler was processed via a series of liquid‐phase exfoliation and surface modification with 3‐aminopropyltriethoxysilane. Results indicate that GNP is successfully exfoliated with minimum defect ratio and improves interfacial bonding within the matrix. Uniform dispersion and stable load‐transfer capability of POM/GNP with 0.5 wt% loading significantly enhanced flexural, tensile and impact strength by overall 26.4%, in contrast to unfilled POM. Dry friction tests against a steel ball also showed the lowest reduction in friction coefficient and wear rate by 22% and 40.6%, respectively, at the same amount of GNP loading due to the large specific surface coverage and lubricious transfer film chelation onto the steel counterface. Furthermore, dissipated energy accumulation by friction work was calculated in the sliding interfaces based on friction force–displacement hysteresis loop where the POM/GNP 0.5 wt% wear surface consumed ca 21.7% less energy in a dry frictional shearing process compared to neat POM. However, lack or excess loading of processed GNP exhibited insufficient or poor matrix–filler adhesion and led to deterioration of the composite properties due to particle agglomeration which can cause stress concentration and serve as a failure site. The adoption of the proposed methodology would demonstrate excellent material characteristics in thin‐walled precision parts where both mechanical and tribological performances are the primary concern. © 2024 Society of Chemical Industry.