bluuebunny/crossref_metadata_2025 huggingface dataset:
Reducing inference cost of Alzheimer’s disease identification using an uncertainty-aware ensemble of uni-modal and multi-modal learners
Authors: Hagos Misgina Tsighe , Curran Kathleen M. , Mac Namee Brian ,   for the Alzheimer’s Disease Neuroimaging Initiative
Published: February 2025

While multi-modal deep learning approaches trained using magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG PET) data have shown promise in the accurate identification of Alzheimer’s disease, their clinical applicability is hindered by the assumption that both modalities are always available during model inference. In practice, clinicians adjust diagnostic tests based on available information and specific clinical contexts. We propose a novel MRI- and FDG PET-based multi-modal deep learning approach that mimics clinical decision-making by incorporating uncertainty estimates of an MRI-based model (generated using Monte Carlo dropout and evidential deep learning) to determine the necessity of an FDG PET scan, and only inputting the FDG PET to a multi-modal model when required. This approach significantly reduces the reliance on FDG PET scans, which are costly and expose patients to radiation. Our approach reduces the need for FDG PET by up to 92% without compromising model performance, thus optimizing resource use and patient safety. Furthermore, using a global model explanation technique, we provide insights into how anatomical changes in brain regions—such as the entorhinal cortex, amygdala, and ventricles—can positively or negatively influence the need for FDG PET scans in alignment with clinical understanding of Alzheimer’s disease.
Deciphering the code of resistance: a genomic and transcriptomic exploration of the Cystoisospora suis Holland-I strain
Authors: Cruz-Bustos Teresa , Eder Thomas , Ruttkowski Baerbel , Joachim Anja
Published: February 2025

Cystoisospora suis, a member of the apicomplexan order Coccidia and causative agent of neonatal porcine coccidiosis, poses a challenge to pig production due to the emergence of reduced efficacy of toltrazuril, the only EU-approved treatment. To address the critical gaps in understanding toltrazuril resistance and possibilities of early diagnostics, our study investigated the genetic basis of resistance through whole-genome DNA sequencing and transcriptome analysis of two C. suis strains, the toltrazuril-susceptible Wien-I and the resistant Holland-I. Additionally, we studied the mitochondrial genome and analysed mitochondrial gene expression in both strains. Our results show that genes encoding proteins involved in host-cell invasion displayed variable expression patterns and genetic mutations, suggesting adaptive changes in invasion mechanisms. Moreover, substantial fluctuations in the expression of genes linked to retrotransposons, accompanied by genetic alterations, were observed, highlighting their potential involvement in genomic rearrangements. Finally, our mitochondrial genome analyses revealed important insights into its genetic organization and conservation. Notably, the marked downregulation of CoI, CoIII and Cytb mRNA levels in the resistant strain Holland-I upon toltrazuril exposure highlights the dynamic response of mitochondrial genes to toltrazuril. These mitochondrial adaptations appear to be closely linked to the parasite drug resistance mechanism, potentially facilitating its survival under pharmacological stress. These findings enhance our knowledge of drug resistance mechanisms in Coccidia and highlight the need for novel management strategies, leading to the development of targeted treatments and controls.
Effects of Nanoscale precipitates on mechanical properties, corrosion resistance, and biocompatibility in Zn-Mn alloy
Authors: Dong Cuilan , Liao Zikun , Yin Yanyi , Yi Yinzhi , Zhu Guanghui , Zheng Tuquan , Tan Qian , Xie Yonghong
Published: February 2025

Controlling degradation rate is essential for the biomedical application of biodegradable Zn alloys. Alloying with soluble elements is an effective way to regulate formation of second phases, which differ in potential from the Zn matrix. The potential difference exhibits positive or negative effects on corrosion resistance. This study successfully forms MnZn13 phase with nano size by altering ECAP temperature. Subsequently, MnZn13 phase promotes grain refinement, improvement of elongation, and corrosion resistance. Higher elongation in Zn-Mn alloy with MnZn13 phase is attributed to the grain boundary sliding, deformation twins in MnZn13 phase. Meanwhile, grain boundary corrosion in Zn-Mn alloy with MnZn13 phase is incomplete. Corrosion mode of Zn-Mn alloys without MnZn13 phase is dominated by grain boundary corrosion, accompanied by pitting corrosion. The increased corrosion resistance from MnZn13 phase stems from its higher potential than Zn matrix. Zn-Mn alloys with and without MnZn13 phase show a comparable cytocompatibility and osteogenic properties. Our findings provide an effective way to regulating mechanical properties and corrosion resistance of Zn alloys via controlling precipitation.
Multiple long-term conditions as the next transition in the global diabetes epidemic
Authors: Gregg Edward W. , Holman Naomi , Sophiea Marisa , Misra Shivani , Pearson-Stuttard Jonathan , Valabhji Jonathan , Khunti Kamlesh
Published: February 2025

Several transitions, or new patterns and dynamics in the contributors and health outcomes, have altered the character and burden of the multi-decade, worldwide growth in prevalence of type 2 diabetes (T2DM). These changes have led to different needs for prevention and care. These dynamics have been driven by diverse demographic, socio-economic, behavioural, and health system response factors. In this Perspective, we describe these transitions and how their attributes have set the stage for multimorbidity, or multiple long-term conditions (MLTCs), to be the next major challenge in the diabetes epidemic. We also describe how the timing and character of these stages differ in high-, middle-, and low-income countries. These challenges call for innovation and a stronger focus on MLTCs across the spectrum of cause, effectiveness, and implementation studies to guide prevention and treatment priorities.
Political enablers of ambitious climate policies: a framework and thematic review
Authors: Montfort Simon , Fesenfeld Lukas , Ingold Karin , Lamb William F. , Andrijevic Marina
Published: February 2025

Currently, most research explaining why countries lead or lag in climate policy assumes a problem-oriented perspective, focusing on barriers to climate policy adoption. Here, we argue that correcting for past failures, solving problems, and bringing climate policies back on track for the Paris Agreement requires a solution-oriented perspective on the political enablers of ambitious climate policies. We unite a growing research community that has previously been scattered across disciplinary subfields with various ontological and epistemological assumptions. Rooted in a thematic review of the scientific literature, we introduce a framework with a typology of six political enablers for ambitious climate policy at its core. For each enabler, we summarize key policy implications. We illustrate our framework with a case study on the adoption of emission trading systems in the transport and building sectors in Germany and the European Union (EU) allowing future solution-oriented research to build on our effort.
Enhancing the efficiency of asymmetric supercapacitors using high-performance Fe-doped CoWO4 electrodes
Authors: Kamalesh T. , Rajkumar Palanisamy , Venkatesan Sethuraman , Rasappan Akshaya Subhramaniyan , El-marghany Adel , Asaithambi Sankaiya , Kim Jinho
Published: February 2025

Herein, the synthesis of iron-doped cobalt tungstate (Fe–CoWO4) nanostructures using a cost-effective hydrothermal method for application as electrodes in high-performance supercapacitors is reported.
Recent advances in fundamental research on photon avalanches on the nanometre scale
Authors: Aggarwal Shradha
Published: February 2025

Overview of photon avalanche upconversion: history, imaging applications, photonic applications, and challenges for frontier applications. Image created with BioRender.
The fate of nanoparticle surface chemistry during reductive electrosynthesis in aprotic media
Authors: Medvedeva Xenia V. , Medvedev Jury J. , Zhao Xingya , Smith Elena , Klinkova Anna
Published: February 2025

Reductive electrochemical coupling of carbon dioxide with organic molecules in aprotic media is affected significantly by the surface chemistry of the electocatalyst.
3D printing of superhydrophobic and multifunctional objects via simple and inexpensive vat photopolymerization
Authors: Rather Adil Majeed , Barrubeeah Mohammed , Zarei Mohammad Javad , Kim Young Jae , Vallabhuneni Sravanthi , Kota Arun Kumar
Published: February 2025

We fabricated superhydrophobic and multifunctional objects using a simple and inexpensive vat photopolymerization 3D printer with a 2-component ink and a 2-step process.
Persistent glutathione-depleting MFO@MIL nanoreactors enhance antitumor efficiency of skin scaffold
Authors: Yang Wenjing , Ji Yibing , Li Lang , Ding Chenhang , Aiyiti Wurikaixi , Xiong Feilong , Shuai Cijun
Published: February 2025

The efficacy of reactive oxygen species (ROS)-related skin tumor therapies is significantly restricted by intracellular overexpressed glutathione (GSH) which is a free radical scavenger. Herein, a GSH-depleting and high ROS...
Regulating the crystallization of tin oxide nanoparticles by an environmentally friendly poly-aluminum chloride additive for a high-quality electron transport film in perovskite solar cells
Authors: Zhang Xueqi , Yao Disheng , Dong Haiyue , Han Junzhe , Zheng Wenwen , Zhou Bing , Tian Nan , Peng Yong , Zheng Guoyuan , Long Fei
Published: February 2025

The film quality of the electron transport layers influences the photovoltaic performance of perovskite solar cells (PSCs) profoundly.
High‐speed dynamic sensing and analysis of high voltage circuit breaker spring‐operating mechanism
Authors: Yuan Quan , Deng Lei , Lyu Qishen , Guo Hao , Zhang Xin , Wu Jibin , Yan Nianping , Wang Xilin
Published: February 2025

Diagnosing the operational status of High‐voltage circuit breakers (HVCBs) is crucial for ensuring the safe and stable operation of the grid. Mechanical characteristic parameters are effective indicators for evaluating the performance of HVCBs. Recent studies have shown that the actions of the springs and cams in HVCBs can be used to detect the operational status of the mechanical mechanisms, which occur extremely quickly, usually in the speed of m/ms. In this paper, dynamic vision sensing technology was employed to rapidly and dynamically capture the movements of the springs and cam of the HPL245B1 HVCB. The data volume of a single experiment is less than 100 MB, whereas the data collected by a high‐speed camera at the same frame rate exceeds 1 GB. Action data streams of the springs and cam were obtained and images were reconstructed from the event streams. The Lucas–Kanade optical flow algorithm and the normalised cross‐correlation algorithm are applied to calculate the parameters of spring deformation characteristics and cam rotation characteristics for mechanical feature detection of HVCBs. This is the first attempt to utilize brain‐inspired hardware technology for the status monitoring of electrical equipment. The advantages of dynamic vision sensing technology, such as high dynamic range, low data transmission, and low energy consumption, also offer significant benefits for air discharge monitoring and status monitoring of electrical equipment.
ZTF SN Ia DR2: Exploring SN Ia properties in the vicinity of under-dense environments
Authors: Aubert M. , Rosnet P. , Popovic B. , Ruppin F. , Smith M. , Rigault M. , Dimitriadis G. , Goobar A. , Johansson J. , Barjou-Delayre C. , Burgaz U. , Carreres B. , Feinstein F. , Fouchez D. , Galbany L. , Ginolin M. , de Jaeger T. , Kasliwal M. M. , Kim Y.-L. , Lacroix L. , Masci F. J. , Müller-Bravo T. E. , Racine B. , Ravoux C. , Regnault N. , Riddle R. L. , Rosselli D. , Rusholme B. , Smith R. , Sollerman J. , Terwel J. H. , Townsend A.
Published: February 2025

Context. The unprecedented statistics of detected Type Ia supernovae (SNe Ia) brought by the Zwicky Transient Facility (ZTF) enable us to probe the impact of the large-scale structure (LSS) on the properties of these objects.

Aims. The goal of this paper is to explore the possible impact of the under-dense part of the LSS on the intrinsic SALT2 light-curve properties of SNe Ia and uncover possible biases in SN Ia analyses.

Methods. With a volume-limited selection of ZTF-Cosmo-DR2 SNe Ia overlapping with the SDSS-DR7 survey footprint, we investigated the distribution of their properties with regard to voids detected in the SDSS-DR7 galaxy sample. We further used Voronoi volumes as a proxy for local density environments within the LSS.

Results. We find a moderate dependency of the stretch on the localisation around the void centre and none when considering colour. The local Voronoi volumes mostly affect the fraction of low- and high-stretch supernovae.

Conclusions. With the presently available statistics, we consider that the impact of high- or low-local-density environment can be considered as a proxy for the colour of the host galaxy. Under-dense environments should not cause any biases in analyses of supernova.
Diversity Analysis of Endophytic Bacterial Resources in Plant Remediation of Heavy Metals
Authors: Sun Xiang-ping , Zeng Liang-bing , Li Jian-jun , Yan Li , Nie Chun-Wu , Wen Chuan-ru
Published: February 2025

Endophytic bacteria are bacteria that are designated to colonize various tissues and organs of healthy plants. Infected host plants do not exhibit external diseases, and heavy metal tolerant endophytic bacteria exist in various hyperaccumulating plants. In our study, the population density of endophytic bacteria is the highest in the root tissue, taken together, plant endophyte types are very rich in ramie. Our results showed that Proteobacteria are the primary microbial flora in the endophytic bacteria of all ramie varieties. The diversity of endophytic bacteria in two species of ramie, which is LSCM and 1407, was higher than that in other species. The results showed that there are differences among different species in ramie. There are differences in endophytic bacteria in different parts of the same species in ramie. provide support for Transfer patterns and persistence of endophytic bacteria after host plant colonization in the study. This paper expects to conduct simulation studies on the interaction between various endophytic bacteria and plant joint systems in natural environments, explore different endophytic bacteria and plant joint remediation systems, and provide guidance for practical applications.
Development Path of China’s Ports Under Carbon Peaking and Neutrality Goals
Authors: Li Luning , Lan Ru , Wang Hongyan , Duan Junya
Published: February 2025

Carbon peaking and neutrality goals constitute the major strategic decisions in ecological civilization construction in China. The port industry is characterized by intense carbon emissions, strong regional aggregation, and large emissions of single-used equipment. Port is an important battlefield for the transportation industry to promote carbon peaking and neutrality. Against this backdrop, it needs to intensify clean energy application by facilitating harbor machinery and vehicles powered by clean energy, elevating the equipment energy efficiency, improving the level of port automation and specialization, and developing means of green transportation. These initiatives are all bolstered to cultivate new and competitive industrial advantages in achieving carbon peaking and neutrality, thereby contributing to China’s constructive solutions to the low-carbon transitions of global transportation.
The Application of Support Vector Machine (SVM) in Industrial Carbon Accounting Prediction and Green Electricity Control Strategies
Authors: Xu Shasha , Wu Haipeng , Luo Junting , Chen Jian , Jia Huihan
Published: February 2025

In recent years, as global climate change has intensified, carbon emissions management in the industrial sector has become a critical area in addressing climate change. The application of intelligent algorithms in carbon emissions prediction and management offers new possibilities for implementing effective emission control strategies. This paper, based on the Support Vector Machine (SVM) model, explores its application in industrial carbon accounting, focusing on the interaction between carbon emissions prediction and optimization of control strategies. By analyzing the differences between predicted results and actual carbon emissions data, the paper proposes a series of emission control strategies driven by intelligent algorithms, and discusses them in the context of policy environments and production characteristics. The study shows that the SVM model demonstrates high accuracy in carbon emissions prediction, effectively supporting corporate carbon management decisions.
Construction and Application of Dual Carbon Integrated Management Service Platform Based on Industrial Carbon Credits
Authors: Luo Junting , Xu Shasha , Fang Huimin , Wu Haipeng , Chen Jian
Published: February 2025

Focusing on the construction of national carbon peak pilot parks, a “dual carbon integrated management service platform” with industrial carbon credits as the main body has been built. Building six scenarios: carbon monitoring, carbon accounting, carbon governance, carbon certification, carbon finance, carbon trading, a new model of carbon service integration digital management and control with accurate carbon data monitoring, regulatory decision-making visualization, and business behavior full recording has been built, enabling the government to build carbon regulatory service capacity, promoting enterprises to save energy and reduce carbon and explore carbon assets, providing diversified low-carbon scenarios for the public, helping to form a cooperative ecology across the carbon service industry chain, and enabling carbon market service capacity building. Accelerate the implementation of the dual-carbon integrated service management system with power as the core, and boost China’s “dual-carbon” digital transformation.
Research on a New Green and Low Carbon Degradation Test Scheme
Authors: Huang Jinfei , Liu Kaiyue , Zhang Xin , Chou Qin
Published: February 2025

With the rapid development of biodegradable plastics, the inspection and detection of degradable plastics is becoming more and more important, GB/T 19277.1 is the most commonly used degradable plastic compost detection method. However, there are some problems in this method, such as large differences among different decomposed composts, unstable compost between batches, subjective factors interfering greatly with the experimental results, and the nutrient composition of compost culture solution in vermiculite scheme is not clearly defined. In this paper, the effects of compost and vermiculite inoculants were compared by experiments. In addition, the formula of vermiculite culture solution was optimized, and the experimental results showed that the determination efficiency of product degradation rate could be effectively improved by adding specific microbial bacteria (potassium bacteria, bacillus group, lactic acid bacteria group, etc.). At the same time, the optimized culture solution formula can better control the nutrient composition, solve the problems of batch to batch instability, artificial factors, and improve the reproducibility and repeatability of detection. This is of great significance for promoting the application and development of biodegradable plastics testing standards. Through these improvements, the performance of biodegradable plastics can be more effectively assessed, the rational use of environmentally friendly materials and the control of plastic pollution can be promoted, the application of degradable materials in packaging materials, agriculture, medical care, textile and clothing, new energy and other fields can be promoted, the green transformation of the industry can also help “carbon peak” and “carbon neutral” realization.
Leaching Characteristics and Potential Ecological Risks of Typical Heavy Metals in Gangue-Based Composite Materials
Authors: Yang Yansheng , Qin Yu , He Ruimin , Zhang Jie , Yu Yan
Published: February 2025

Coal gangue can potentially release varying amounts of heavy metals under conditions such as soaking and leaching, posing a threat to ecological and environmental safety. This has become a research hotspot in recent years. Therefore, this study mainly focused on coal gangue and its composites, and studied the leaching behavior of typical heavy metals under different initial p H conditions and the potential ecological risk of leaching solution and its effect on alfalfa seed germination. The results show that the coal gangue has irregular block and flake structure, and the surface is rough, and its chemical composition mainly includes SiO2 and Al2O3. The leachates from both coal gangue and composite materials were alkaline, with relatively similar pH values. This is attributed to the leaching of alkaline compounds such as CaO and Fe2O3. As the initial pH decreased, the leaching amounts of Pb, Cr, Cd, and Hg increased, while the leaching amount of As decreased. In the leachate from coal gangue, the single-factor pollution index and Nemerow pollution index for Pb were 0.53 and 0.54, respectively. The composite materials demonstrated a good stabilization effect on heavy metals. These findings can provide a reference for the safe disposal of coal gangue in mining areas.
Temporal invariance of Sport Emotion Questionnaire scores using exploratory structural equation modelling
Authors: Levillain Guillaume , Martinent Guillaume , Vacher Philippe , Nicolas Michel
Published: February 2025

The goals of this study were: (a) to explore the most effective approach to represent the factor structure of SEQ scores by employing advanced methodological techniques recently introduced in the scientific literature, including bi-factor, exploratory structural equation modelling (ESEM) and bi-factor ESEM; and (b) to examine the temporal invariance of SEQ scores using the best-fitting model previously identified. 460 athletes completed the SEQ across three measurement times to assess their emotional states experienced during competitions. Data were analyzed with a series of confirmatory factorial analysis, bi-factor, ESEM and bi-factor-ESEM. Considering the fit indices and standardized factor loadings across the three measurement points, the results indicated that ESEM could be regarded as the most suitable model for describing the factorial structure of SEQ scores. Furthermore, the findings provided evidence for the partial factor mean longitudinal invariance of SEQ. Finally, we hope these results will encourage research on longitudinal evolution of emotions across a season of sports competitions or over several seasons.
A “five rights separation” framework for data rights confirmation in data element circulation
Authors: Zhao Jianbo , Liu Huailiang , Zhang Shanzhuang , Shu Kai , Fang Qisen , Zhang Weili , Tan Chufan , Zhang Xiaojin , Wang Yuehai , Qi Yanwei
Published: February 2025

Clarifying the rights subjects and their corresponding rights in data element circulation, and constructing a rational data rights confirmation framework,are crucial prerequisites for ensuring the smooth circulation of data elements. Employing an improved evidence-based model, this paper conducts evidence-based research on the traditional methodologies of data rights confirmation in the three major economic entities: the European Union, the United States, and China. The findings indicate that the European Union demonstrates strong systematicity and innovativeness in data rights confirmation, the United States exhibits strong specificity and adaptability, and China shows strong collectivism and developmental characteristics. As a result, this paper proposes a “five rights separation” framework for ternary data subjects, which balances the interests and needs of different data subjects while ensuring both efficiency and security in data element circulation. For the first time, this paper provides a new construction method and theoretical framework for data rights confirmation in data element circulation.Future research can expand the scope and depth of evidence-based studies, conduct empirical research, and implement pilot projects.
Deep operator network prediction method for electromagnetic thrust of linear propulsion electromagnetic energy equipment
Authors: Jin Liang , Ma Tianci , Yang Qingxin , Song Juheng
Published: February 2025

Linear propulsion electromagnetic energy equipment utilizes the Lorentz force to apply power to the emitter, achieving launch speeds and efficiencies that far surpass those of traditional chemical propulsion technologies. This capability has significant strategic and practical value in both defense and civilian applications. Analyzing and calculating the armature electromagnetic thrust is essential for studying the dynamic characteristics of linear propulsion electromagnetic energy equipment. However, high-speed scenarios often present challenges in obtaining numerical solutions due to “pseudo-oscillation.” To address this issue, we propose a novel prediction method for the armature electromagnetic thrust in linear propulsion electromagnetic energy equipment using deep operator networks. First, a finite element simulation model of the system was developed to generate stable numerical simulation data under varying excitation currents. This model is then used to analyze the dynamic characteristics of the armature electromagnetic thrust and evaluate the stability of the numerical solutions. Based on the simulation data, we introduce a deep operator network-based prediction method for armature electromagnetic thrust. Finally, the prediction performance of the model is validated using linear propulsion electromagnetic energy equipment as a computational example. The results showed that the prediction error for the electromagnetic thrust on the test set was within 1%. After training, the model can calculate the electromagnetic thrust under different excitation currents in a matter of seconds, providing a fresh perspective for analyzing the dynamic characteristics of linear propulsion electromagnetic energy equipment.
Time-domain analysis of oblique wave scattering by a forced floating elastic plate over porous bed
Authors: Alex Dona , Ashok R. , Balasubramani N. , Behera Harekrushna
Published: February 2025

This study examines the interaction of waves with a floating elastic plate subjected to a time-harmonic delta function force, taking into account oblique wave incidence over a porous seabed. The boundary value problem is addressed using the eigenfunction matching technique, while Fourier transforms are employed to study the time-dependent deflection. Numerical results are analyzed to understand the influence of three different edge conditions (built-in, free, and simply supported), as well as the properties of the wave, plate, and porous bottom. The analysis shows that for larger angles of incidence region, full reflection occurs with zero transmission. For smaller angles of incidence, however, the frequency of zero reflection and full transmission increases as the porous bottom parameter is increased. Additionally, a free-edge condition results in reduced reflection and increased transmission. The time-dependent deflection of the free surface is significantly influenced by the porous parameter and the angle of incidence, whereas the time-dependent deflection of the plate is notably affected by the Young's modulus of the plate along with the other parameters.
Review of smoothed particle hydrodynamics modeling of fluid flows in porous media with a focus on hydraulic, coastal, and ocean engineering applications
Authors: Luo Min , Su Xiujia , Kazemi Ehsan , Jin Xin , Khayyer Abbas
Published: February 2025

A comprehensive review is conducted on the application of Lagrangian mesh-free methods for simulating flows in various types of porous media, ranging from fixed structures like coastal breakwaters to deformable and transportable media. Deformable porous media refer to soil structures that may deform under the influence of currents and waves, while transportable media involve processes such as sediment transport and scour around hydraulic, coastal, and ocean structures. This review addresses problem dimensionality, governing equations, domain discretization schemes, interaction mechanisms, and applications. The literature analysis reveals that while various numerical techniques have been employed to model the complex interaction between fluid and solid phases, not all methods are physically or mathematically justifiable. However, some approaches have significantly advanced the modeling process over the past two decades. Based on these findings, a modeling framework is proposed to guide the construction of mesh-free models for simulating flow interactions with natural or engineered porous structures. It highlights two effective approaches: (i) Three-dimensional (3D) pore-scale microscopic modeling of flow through large-sized solid particles using coupled smoothed particle hydrodynamics (SPH) and discrete element method (DEM), and (ii) two-dimensional (2D) macroscopic modeling of flow in small-sized porous media using the mixture theory and SPH. The framework highlights the mixture-theory-based methods as particularly effective for large-scale simulations and the advanced SPH-DEM coupling techniques that enable precise simulations of complex fluid–solid interactions. The framework serves as a guide for researchers developing mesh-free numerical models to simulate fluid flows in porous media for hydraulic, coastal, and ocean engineering applications.
Active Brownian motion with inertia: The role of dimensionality
Authors: Lisin Evgeny A. , Lisina Irina I.
Published: February 2025

The joint influence of rotational inertia and dimensionality on the translational motion of a free self-propelled (active) Brownian particle is studied. When the reduced moment of inertia is not large, the three-dimensional particle dynamics is statistically described by the equations for the two-dimensional case only with the doubled rotational diffusion coefficient. However, for large reduced moment of inertia, the three- and two-dimensional dynamics of the particle differ dramatically. It is shown that the time-dependent mean square particle displacement can be described by the active Ornstein–Uhlenbeck particle model, where the orientational persistence and momentum relaxation times are effectively corrected by the particle rotational inertia.
Single-crystal thermoelastic behavior of magnetoplumbite-type (Mg,Zr):SrGa12O19 and Pr:SrAl12O19 between 103 and 1573 K
Authors: Münchhalfen Marie , Schreuer Jürgen , Rhode Christian , Guguschev Christo
Published: February 2025

The elastic behavior of Sr1.03Ga10.81Mg0.58Zr0.58O19 and Pr-doped SrAl12O19 single crystals grown by the top-seeded solution growth technique was investigated by resonant ultrasound spectroscopy at temperatures between 103 and 1573 K. The coefficients of thermal expansion were obtained by high-resolution dilatometry in the same temperature range. Values for bulk moduli at ambient temperatures are 206.5 and 181.0 GPa for Pr-doped SrAl12O19 and Sr1.03Ga10.81Mg0.58Zr0.58O19, respectively. The aluminate possesses higher values of the mean elastic stiffness compared to the gallate, which can be related to different oxygen packing densities. Apart from these differences, their elastic anisotropy is very similar, as expressed by the ratio of the maximum and minimum of the longitudinal elastic stiffness of 1.34 and 1.35, respectively. In the case of Pr-doped SrAl12O19, an unexpected, fully reversible softening of the stiffness coefficient c33 is noteworthy below 500 K, which is accompanied by a negative thermal expansion. In addition, Pr-doped SrAl12O19 possesses a well-reproducible strong ultrasound attenuation between 700 and 900 K, which can be interpreted as anelastic relaxation of point defects with an activation energy of 0.65 eV.
Shape deformation of a gas bubble forced by a dual frequency time-dependent pressure field
Authors: Shaw Stephen J.
Published: February 2025

The nonlinear volume oscillations and shape deformation of a gas bubble in water driven by a spatially uniform, time-dependent dual frequency acoustic source is considered. Employing a model that includes shape mode interactions to third order, the respective, distinct frequency values of the driving pressure are chosen in order to parametrically excite two different axisymmetric shape modes via the fundamental resonance. It is shown that the shape modes develop on different timescales with their relative growth rates controlling the resultant dynamics. For suitably chosen driving strengths, intermediate steady state shape oscillations are observed. In particular, for cases where the higher order shape mode grows fastest and subsequently saturates first, then steady state shape oscillations dominated by this mode are observed for a finite time. However, as the lower mode grows, the higher mode decays and if the lower mode saturates, the resultant steady state oscillations are dominated by the lower mode, indicating that this mode is a preferential oscillation state. For cases where the shape modes develop on similar timescales, the balance between the driving strengths results in either the lower mode growing unbounded or one of the shape modes suppressing the parametric growth of the other mode.
Solute dispersion in Phan-Thien–Tanner (PTT) fluid flows
Authors: Mahata Kartick , Rana Jyotirmoy , Patne Ramkarn
Published: February 2025

To understand the effect of viscoelasticity and finite extensibility of polymer chains on solute dispersion, the present study analyses the unsteady solute transport in a steady pipe flow of the exponential Phan-Thien–Tanner (PTT) fluid. We utilize Gill's procedure and homogenization method to determine the coefficients characterizing solute transport. In the large time limit, both methods yield the same result. The PTT fluid introduces two dimensionless parameters, viz., Deborah number (De) characterizing fluid elasticity and polymer chain extensibility (ϵ). An increasing De and ϵ leads to increasing shear-thinning of the PTT fluid. Owing to the average velocity scale for non-dimensionalization, the convection transport coefficient (K1) in Gill's procedure has unity magnitude. The diffusion transport coefficient (K2) in Gill's procedure or effective diffusivity predicted by the homogenization method drastically decreases with increasing De and ϵ. This prediction is explained on the basis of shear-thinning-induced reduction in the velocity gradient. Following the trend shown by K2, the mean concentration Cm(t,z) shows an increased tendency of a higher peak as De and ϵ increase, implying slower axial spreading. Additionally, contours obtained for the local concentration C(t,r,z) further confirm the reduction in the solute dispersion for increasing De and ϵ. Thus, the present study demonstrates a reduction in the solute dispersion due to fluid elasticity and shear-thinning.
The impact of traditional vs parallel venous–arterial extracorporeal membrane oxygenation on the intra-aortic hemodynamic environment: A numerical study
Authors: Xi Yifeng , Li Yuan , Wang Hongyu , Wang Xiaofei , Feng Wentao , Chen Zengsheng
Published: February 2025

To investigate the impacts of traditional and parallel venous–arterial extracorporeal membrane oxygenation (TVA and PVA-ECMO) cannulation modes on the aortic hemodynamic surroundings under differential cardiac conditions. Clinical imaging data were utilized to build the numerical models. Computational fluid dynamics methods were applied to analyze five aortic models with VA-ECMO implantation, including one TVA-ECMO and four PVA-ECMO configurations with distinct cannulation positions, under four conditions of cardiac insufficiency. Evaluation parameters included standard hemodynamic parameters, hyperoxic blood distribution, residence time, and shear stress. The distribution of oxygen saturation distribution, hemolysis risk, and thrombosis risk were assessed using our newly constructed numerical models. When cardiac function was partially recovered, the boundaries of the mixed zone of hyperoxic and hypoxic blood were all located in the upper limb of the aorta. The location of the mixing zone shifted toward the distal aorta when TVA-ECMO was converted to P1 VA-ECMO. Increasing the depth of cannula placement improved perfusion of hyperoxic blood in all aortic arch branches. Lower ECMO perfusion levels in the same cannulation model correlated with decreased wall shear stress and scalar shear stress in the aorta, alongside reduced hemolysis levels. Changing TVA-ECMO to P1 VA-ECMO increased intra-aortic thrombosis risk, which decreased with deeper additional cannula placements from P2 to P4 in PVA-ECMO configurations. Transitioning from TVA to PVA-ECMO enhances ECMO support and diminishes ECMO-related complications (hemolysis and thrombosis) when the PVA-ECMO cannula is appropriately positioned. Coronary aerobic hypoperfusion persists with both TVA and PVA-ECMO upon partial cardiac function recovery. This study can provide guidance for the selection of different annulation strategies in VAECMO treatment.
Fast Interpretable Greedy-Tree Sums
Authors: Tan Yan Shuo , Singh Chandan , Nasseri Keyan , Agarwal Abhineet , Duncan James , Ronen Omer , Epland Matthew , Kornblith Aaron , Yu Bin
Published: February 2025

Modern machine learning has achieved impressive prediction performance, but often sacrifices interpretability, a critical consideration in high-stakes domains such as medicine. In such settings, practitioners often use highly interpretable decision tree models, but these suffer from inductive bias against additive structure. To overcome this bias, we propose Fast Interpretable Greedy-Tree Sums (FIGS), which generalizes the Classification and Regression Trees (CART) algorithm to simultaneously grow a flexible number of trees in summation. By combining logical rules with addition, FIGS adapts to additive structure while remaining highly interpretable. Experiments on real-world datasets show FIGS achieves state-of-the-art prediction performance. To demonstrate the usefulness of FIGS in high-stakes domains, we adapt FIGS to learn clinical decision instruments (CDIs), which are tools for guiding decision-making. Specifically, we introduce a variant of FIGS known as Group Probability-Weighted Tree Sums (G-FIGS) that accounts for heterogeneity in medical data. G-FIGS derives CDIs that reflect domain knowledge and enjoy improved specificity (by up to 20% over CART) without sacrificing sensitivity or interpretability. Theoretically, we prove that FIGS learns components of additive models, a property we refer to as disentanglement. Further, we show (under oracle conditions) that tree-sum models leverage disentanglement to generalize more efficiently than single tree models when fitted to additive regression functions. Finally, to avoid overfitting with an unconstrained number of splits, we develop Bagging-FIGS, an ensemble version of FIGS that borrows the variance reduction techniques of random forests. Bagging-FIGS performs competitively with random forests and XGBoost on real-world datasets.
Detrimental influence of Arginase-1 in infiltrating macrophages on poststroke functional recovery and inflammatory milieu
Authors: Kim Hyung Soon , Jee Seung Ah , Einisadr Ariandokht , Seo Yeojin , Seo Hyo Gyeong , Jang Byeong Seong , Park Hee Hwan , Chung Won-Suk , Kim Byung Gon
Published: February 2025

Poststroke inflammation critically influences functional outcomes following ischemic stroke. Arginase-1 (Arg1) is considered a marker for anti-inflammatory macrophages, associated with the resolution of inflammation and promotion of tissue repair in various pathological conditions. However, its specific role in poststroke recovery remains to be elucidated. This study investigates the functional impact of Arg1 expressed in macrophages on poststroke recovery and inflammatory milieu. We observed a time-dependent increase in Arg1 expression, peaking at 7 d after photothrombotic stroke in mice. Cellular mapping analysis revealed that Arg1 was predominantly expressed in LysM-positive infiltrating macrophages. Using a conditional knockout (cKO) mouse model, we examined the role of Arg1 expressed in infiltrating macrophages. Contrary to its presumed beneficial effects, Arg1 cKO in LysM-positive macrophages significantly improved skilled forelimb motor function recovery after stroke. Mechanistically, Arg1 cKO attenuated fibrotic scar formation, enhanced peri-infarct remyelination, and increased synaptic density while reducing microglial synaptic elimination in the peri-infarct cortex. Gene expression analysis of fluorescence-activated single cell sorting (FACS)-sorted CD45
low
microglia revealed decreased transforming growth factor-β (TGF-β) signaling and proinflammatory cytokine activity in peri-infarct microglia from Arg1 cKO animals. In vitro coculture experiments demonstrated that Arg1 activity in macrophages modulates microglial synaptic phagocytosis, providing evidence for macrophage–microglia interaction. These findings present unique insights into the function of Arg1 in central nervous system injury and highlight an interaction between infiltrating macrophages and resident microglia in shaping the poststroke inflammatory milieu. Our study identifies Arg1 in macrophages as a potential therapeutic target for modulating poststroke inflammation and improving functional recovery.
Receptor clustering tunes and sharpens the selectivity of multivalent binding
Authors: Xie Zhaoping , Angioletti-Uberti Stefano , Dobnikar Jure , Frenkel Daan , Curk Tine
Published: February 2025

The immune system exploits a wide range of strategies to combine sensitivity with selectivity for optimal response. We propose a generic physical mechanism that allows tuning the location and steepness of the response threshold of cellular processes activated by multivalent binding. The mechanism is based on the possibility to modulate the attraction between membrane receptors. We use theory and simulations to show how tuning interreceptor attraction can enhance or suppress the binding of multivalent ligand-coated particles to surfaces. The changes in the interreceptor attraction less than the thermal energy
k

B

T
can selectively switch the receptor-clustering and activation on or off in an almost step-wise fashion, which we explain by near-critical receptor density fluctuations. We also show that the same mechanism can efficiently regulate the onset of endocytosis for,
e.g.
, drug delivery vehicles.
Structures and functions of the limited natural polyclonal antibody response to parvovirus infection
Authors: Adu Oluwafemi F. , Lee Hyunwook , Früh Simon P. , Schoenle Marta V. , Weichert Wendy S. , Flyak Andrew I. , Hafenstein Susan L. , Parrish Colin R.
Published: February 2025

Host antibody responses are key components in the protection of animals against pathogens, yet the defining properties of viral antigens and induction of B cell responses that result in varied protection are still poorly understood. Parvoviruses are simple molecular structures that display 60 repeated motifs on their capsid surface, and rapidly induce strong antibody responses that protect animals from infection. We recently showed that following canine parvovirus infection of its natural host, the polyclonal response in the sera contained only two or three dominant antibodies that bound two epitopes on the capsid. Here, we characterize key antibodies present in that immune response, identifying their sequences, defining their binding properties on the capsid by cryoelectron microscopic (cryoEM) analysis, and testing their effects on viral infectivity. Two antibodies sharing the same heavy chain bound to the side of the capsid threefold spike (B-site), while another distinct antibody bound close to the threefold axis (A-site). The epitopes of these antibodies overlapped the binding site of the host receptor, the transferrin receptor type-1, but to varying degrees. The antibodies varied widely in their neutralization efficiencies as either immunoglobulins (IgGs) or monomeric antigen-binding fragments (Fabs), which was consistent with their ability to compete for the receptor. The monoclonal antibodies characterized here matched the structures from the cryoEM analysis of polyclonal sera, including those present in a different dog than the monoclonal source. This shows that after infection, a focused response to the viral antigen is produced that protects against infection.
AI protocol for retrieving protein dynamic structures from two-dimensional infrared spectra
Authors: Ye Sheng , Zhu Lvshuai , Zhao Zhicheng , Wu Fan , Li Zhipeng , Wang BinBin , Zhong Kai , Sun Changyin , Mukamel Shaul , Jiang Jun
Published: February 2025

Understanding the dynamic evolution of protein structures is crucial for uncovering their biological functions. Yet, real-time prediction of these dynamic structures remains a significant challenge. Two-dimensional infrared (2DIR) spectroscopy is a powerful tool for analyzing protein dynamics. However, translating its complex, low-dimensional signals into detailed three-dimensional structures is a daunting task. In this study, we introduce a machine learning-based approach that accurately predicts dynamic three-dimensional protein structures from 2DIR descriptors. Our method establishes a robust “spectrum-structure” relationship, enabling the recovery of three-dimensional structures across a wide variety of proteins. It demonstrates broad applicability in predicting dynamic structures along different protein folding trajectories, spanning timescales from microseconds to milliseconds. This approach also shows promise in identifying the structures of previously uncharacterized proteins based solely on their spectral descriptors. The integration of AI with 2DIR spectroscopy offers insights and represents a significant advancement in the real-time analysis of dynamic protein structures.
Bioinspired energy-free temperature gradient regulator for significant enhancement of thermoelectric conversion efficiency
Authors: Tan Haohan , Zhao Yuqian , Jin Peng , Xu Xiang , Zhou Xinchen , Marchesoni Fabio , Huang Jiping
Published: February 2025

Enhancing thermoelectric conversion efficiency (TCE) is pivotal for advancing global energy conservation and emission reduction initiatives. Traditional approaches primarily focus on microscopic strategies such as bandgap engineering, chemical potential adjustments, and entropy engineering. However, these methods face substantial limitations in practical applications due to challenging material property requirements. Additionally, the efficiencies achieved remain modest, constrained by the interdependent nature of electrical and thermal conductivities, which typically vary concurrently. Inspired by the thermoregulation mechanisms in biological organisms, we propose here a macroscopic strategy based on an expanded-plane (EP) meta-structure. Such a meta-structure, of the thermal gradient regulator type, exploits the temperature gradient concentrating effect to significantly boost TCE. We prove, both numerically and experimentally, how the proposed device can achieve temperature gradient concentration under diverse conditions. Remarkably, under undistorted temperature background conditions, we measured an striking efficiency enhancement of

59.0
%

. This work highlights the EP thermal gradient regulator’s ability to boost thermoelectric efficiency, valuable across domains: aiding efficient chip cooling in microelectronics and powering wearable medical devices.