bluuebunny/crossref_metadata_2025 huggingface dataset:
LEARNING MARKOV PROCESSES WITH LATENT VARIABLES
Authors: Higgins Ayden , Jochmans Koen
Published: February 2025

We consider the problem of identifying the parameters of a time-homogeneous bivariate Markov chain when only one of the two variables is observable. We show that, subject to conditions that we spell out, the transition kernel and the distribution of the initial condition are uniquely recoverable (up to an arbitrary relabelling of the state space of the latent variable) from the joint distribution of four (or more) consecutive time-series observations. The result is, therefore, applicable to (short) panel data as well as to (stationary) time series data.
Trajectories of attention problems in autistic children and relations to social skills outcomes
Authors: Richard Annie Elise , Duku Eric , Bennett Teresa A. , Szatmari Peter , Vaillancourt Tracy , Zwaigenbaum Lonnie , Georgiades Stelios , Zaidman-Zait Anat , Kerns Connor M. , Bedford Rachael , Smith Isabel M.
Published: February 2025

Co-occurring autism and attention-deficit/hyperactivity disorder (ADHD) have been associated with poorer social skills. Most studies examining the association of ADHD symptoms and social skills in autism employ categorical and cross-sectional designs, which provide a narrow view of the development of ADHD symptoms. Using group-based trajectory modeling, we identified five trajectories of caregiver-reported attention problems in an inception cohort of autistic children (N = 393) followed from age 2–5 years (T1) to age 10.5–11 years (T8): Low-Stable (LS; 15.5% of participants), Low-Decreasing (LD; 25.2%), Low-Increasing (LI; 19.2%), Moderate-Decreasing (MD; 32.9%), and High-Stable (HS; 7.2%). Child FSIQ and caregiver age at baseline were lower and caregiver depression at baseline was higher for participants in the MD group than the LS group. Psychotropic medication use was associated with higher attention problems. The MD and HS groups had similar mean Vineland Adaptive Behavior Scales, Second Edition (VABS-II) Socialization standard scores at T8, which were lower than other groups. The LI group had lower Socialization scores than the LS group. Results support that a decline in caregiver-reported attention problems is common but not universal in autistic children and that even moderate/subclinical attention problems may relate to social skills outcomes in autism.
Intelligence and Individual Differences in Astrological Belief
Authors: Edwards Tobias , March Magdalena J. , Willoughby Emily A. , Giannelis Alexandros
Published: February 2025

Abstract: Astrology is a theory of individual differences. Owing substantially to the influence of Hans Eysenck, it has been taken seriously and tested scientifically by psychologists, but has nevertheless been found wanting of any predictive validity. Despite its appearance of being a pseudoscientific account of individual differences, astrology has millions of believers; who are they, and why do they believe it? In a sample of 8,553 Americans from the General Social Survey, we undertake a high-powered study of the correlates of astrological belief. Of our psychological measures we find intelligence, as measured with Wordsum, to have the largest effect size, negatively predicting belief in astrology. Education also predicts disbelief, supporting the “superficial knowledge” hypothesis. Measures of religiosity and spirituality had null effects, in contradiction of the “metaphysical uncertainty” hypothesis that a need for metaphysical beliefs causes one to believe in astrology. We find that right-wing individuals are less likely to believe in astrology, in contradiction to Theodore W. Adorno’s “authoritarian” of astrology. We also find no effect of scientific trust on astrological belief. Our research highlights how prior hypotheses poorly account for individual differences in astrological belief.
Molecular elucidation of cement hydration inhibition by silane coupling agents
Authors: Chen Binmeng , Wang Meng , Manzano Hegoi , Zhao Yuyang , Li Yunjian
Published: February 2025

Silane coupling agents are widely recognized to retard early hydration when incorporated into fresh cement paste, yet the atomic-level mechanisms underlying their effects on clinker dissolution, such as adsorption of silane monomer onto reactive surface sites and modification of ion detachment pathways, remain unexplored. Here we show dissolution behavior of tricalcium silicate (Ca3SiO5) under 3-aminopropyl triethoxysilane impact using ab initio metadynamics, with experimental validation of the retardation effects in silane-treated pastes. The shielding effect of silane induces shifts in free energy changes of stepwise calcium dissolution from negative to positive and alters the most stable Ca coordination state during dissolution, resulting in the transition of dissolution from spontaneous to non-spontaneous. Specifically, hydrolyzed silane adsorbs dissociatively onto the Ca3SiO5 surface by forming ionic Ca-O bonds, thereby occupying reactive sites and introducing steric hindrance. This, in turn, impedes coordination interactions between calcium ions and water molecules. Experimental results further corroborate these interactions, as evidenced by reduced calcium concentrations in silane-treated pastes, which in turn slowed the hydration process. These findings offer nanoscale insights into the role of SCAs in cement hydration and provide a foundation for future research into the complex interactions within organic/cement systems.
Combined immunization with SARS-CoV-2 spike and SARS-CoV nucleocapsid protects K18-hACE2 mice but increases lung pathology
Authors: Kim Jaekwan , Kachko Alla , Selvaraj Prabhuanand , Rotstein David , Stauft Charles Brandon , Rajasagi Naveen , Zhao Yangqing , Wang Tony , Major Marian
Published: February 2025

Vaccines against SARS-CoV-2 have targeted the spike protein and have been successful at preventing disease. However, with the emergence of variants, spike-specific vaccines become less effective. The nucleocapsid protein is relatively conserved among variants of SARS-CoV-2 and is a candidate for addition to spike in next generation vaccines for the induction of T cell protection. Previous studies on SARS-CoV have suggested that the induction of an immune response to nucleocapsid could result in enhanced disease. Using the K18-hACE2 mouse model we investigated immunization with a variant nucleocapsid, from SARS CoV (N1) alone or in combination with spike from SARS-CoV-2 and compared this to nucleocapsid from SARS-CoV-2 (N2). The spike-nucleocapsid-based vaccines conferred protection against SARS-CoV-2 in lungs and brain and decreased lung pathology compared to control mice. However, higher T and B cell immune responses were observed in N1-immunized mice prior to challenge, whether delivered alone or with spike, and immunization with N1 resulted in increased lung pathology compared to immunization with spike or N2. These findings suggest that spike-nucleocapsid-based vaccines are safe and effective, even with variant nucleocapsid sequences, but that viral control in this mouse model may be associated with higher lung pathology, compared to spike immunization alone, due to the immunogenic qualities of the nucleocapsid antigen.
A realworld pharmacovigilance study of trazodone based on the FDA adverse event reporting system
Authors: Yu Yong , Sun Xin , Hao Liqun , Zhang Xiaoyan , Guo Yankui
Published: February 2025

To explore and analyze the potential adverse event (AE) signals of trazodone, with reference to the safe clinical use of drugs. Based on the FDA Adverse Event Reporting System (FAERS), the AE data of trazodone were extracted from the first quarter of 2004 to the second quarter of 2024, and the extracted data were statistically analyzed using the method, to identify valid AE signals that met our judgment, compare them with those recorded in the authorized information for trazodone thereby identifying unexpected potential adverse reactions. A total of 5199 AE reports with trazodone as the main suspect were extracted, with a higher reported proportion of females (52.68%) than males (38.83%). Many reports (31.47%) did not provide age information, although for those reports with identifiable age data, the 50–60 years age group was the most common (14.20%), and the country of reporting was predominantly the United States (82.58%). A total of 179 significant AE signals were unearthed, with suicide, formulation toxicity, abnormal penile erection, insomnia, and cardiac and respiratory arrest reported with high frequency, which was not entirely consistent with the specification record. The study unearthed 156 new potential AEs on the basis of trazodone drug inserts and suggested precautions for overdosing and dose adjustment, which is conducive to safeguarding the safety of patients’ medication.
Immediate early splicing controls translation in activated T-cells and is mediated by hnRNPC2 phosphorylation
Authors: Dróżdż Mateusz , Zuvanov Luíza , Sasikumar Gopika , Bose Debojit , Bruening Franziska , Robles Maria S , Preußner Marco , Wahl Markus , Heyd Florian
Published: February 2025

The fast and transient induction of immediate early genes orchestrates the cellular response to various stimuli. These stimuli trigger phosphorylation cascades that promote immediate early gene transcription independent of de novo protein synthesis. Here we show that the same phosphorylation cascades also target the splicing machinery, inducing an analogous splicing switch that we call immediate early splicing (IES). We characterize hnRNPC2-controlled IES, which depends on the MEK-ERK pathway and the T cell-specific kinase PKCθ. This splicing switch mainly targets components of the translation machinery, such as mRNAs encoding ribosomal proteins and eIF5A. Inducing the eIF5A IES protein variant is by itself sufficient to reduce global translation, and consistently, we observe reduced de novo protein synthesis early after T cell activation. We suggest that immediate early splicing and the ensuing transient decrease in translation efficiency help to coordinate the extensive changes in gene expression during T cell activation. Together, these findings set a paradigm for fast and transient alternative splicing in the immediate cellular response to activation, and provide evidence for its functional relevance during T-cell stimulation.
Portimine A toxin causes skin inflammation through ZAKα-dependent NLRP1 inflammasome activation
Authors: Gorse Léana , Plessis Loïc , Wearne Stephen , Paradis Margaux , Pinilla Miriam , Chua Rae , Lim Seong Soo , Pelluz Elena , TOH Gee-Ann , Mazars Raoul , Bomfim Caio , Hervé Fabienne , Lhaute Korian , Réveillon Damien , Suire Bastien , Ravon-Katossky Léa , Benoist Thomas , Fromont Léa , Péricat David , Neil Mertens Kenneth , Derrien Amélie , Terre-Terrillon Aouregan , Chomérat Nicolas , Bilien Gwenaël , Séchet Véronique , Carpentier Liliane , Fall Mamadou , Sonko Amidou , Hakim Hadi , Sadio Nfally , Bourdeaux Jessie , Cougoule Céline , Henras Anthony K , Perez-Oliva Ana Belen , Brehmer Patrice , Roca Francisco J , Zhong Franklin L , Common John , Meunier Etienne , Hess Philipp
Published: February 2025

In 2020–2021, a “mysterious illness” struck Senegalese fishermen, causing severe acute dermatitis in over one thousand individuals following exposure through drift-net fishing activity. Here, by performing deep analysis of the environmental samples we reveal the presence of the marine dinoflagellate Vulcanodinium rugosum and its associated cyclic imine toxins. Specifically, we show that the toxin PortimineA, strongly enriched in environmental samples, impedes ribosome function in human keratinocytes, which subsequently activates the stress kinases ZAKα and P38 and promotes the nucleation of the human NLRP1 inflammasome, leading to the release of IL-1β/IL-18 pro-inflammatory cytokines and cell death. Furthermore, cell-based models highlight that naturally occurring mutations in the P38-targeted sites of human NLRP1 are unable to respond to PortimineA exposure. Finally, the development and use of human organotypic skins and zebrafish models of PortimineA exposure demonstrate that the ZAKα-NLRP1 axis drives skin necrosis and inflammation. Our results exemplify the threats to human health caused by emerging environmental toxins and identify ZAKα and NRLP1 as important pharmacological targets to mitigate PortimineA toxicity.
Nylon electrolyte chemistry in high-energy Li-metal batteries
Authors: Zhao Zhiming , Melinte Georgian , Guo Dong , Lei Yongjiu , Hedhili Mohamed N. , Guo Xianrong , Shi Zixiong , Wang Yizhou , El-Demellawi Jehad K. , Zhao Wenli , Alshareef Husam N.
Published: February 2025

Polyamide (PA, Nylon), a classical polymer featuring oxidation-resistant amide linkages, has been reengineered as high-voltage polymer electrolytes compatible with Li-metal batteries.
Controllable synthesis of cypress-derived hard carbon for high-rate sodium ion storage
Authors: Zhou Yan , Cen Meixiang , Pan Changlin , Hu Jiapeng , Liu Yongqi , Zhang Yun , Zhang Wenjie , Qian Gujie , Lian Jiabiao
Published: February 2025

The cypress-derived hard carbon (WC-1100) exhibits superior electrochemical performance, which can be attributed to its distinct pore architecture and interlayer spacing optimization.
Unified Odd‐Descent Regularization for Input Optimization
Authors: Zhou Zheng‐Sen , Lai Zhao‐Rong
Published: February 2025

Activation‐descent regularization is a crucial approach in input optimization for ReLU networks, but traditional methods face challenges. Converting discrete activation patterns into differentiable forms introduces half‐space division, high computational complexity, and instability. We propose a novel local descent regularization method based on a network of arbitrary odd functions, which unifies half‐space processing, simplifies expression, reduces computational complexity, and enriches the expression of the activation descent regularization term. Furthermore, by selecting an arbitrary differentiable odd function, we can derive an exact gradient descent direction, solving the non‐differentiability problem caused by the non‐smooth nature of ReLU, thus improving optimization efficiency and convergence stability. Experiments demonstrate the competitive performance of our approach, particularly in adversarial learning applications. This work contributes to both theory and practice of regularization for input optimization.
A modification of Random Forest investment assets selection algorithm
Authors: Zinenko Anna , Stupina Alena
Published: February 2025

The paper presents selecting stocks for an investment portfolio algorithm, alternative to standard mathematical programming optimal portfolio methods. To implement the algorithm, a modification of the Random Forest machine learning model is proposed. At the first step, the algorithm builds a decision tree based on forecasts using the naive method and the ARIMA method, and then it forms a “forest” of trees from random subsamples. The algorithm was tested on different time intervals on the instruments of two exchange indices. Its implementation showed good results - at least 78% of the selected stocks increased in price over the forecast period.
Hybrid approaches to optimizing online transformation of master's programs: A complex systems case study in software engineering and cybernetics
Authors: Kovalev Igor , Voroshilova Anna , Kuznetsov Alexander , Beshimov Yusuf
Published: February 2025

This paper explores effective practices for transforming Master's programs into an online format, focusing on the Software Engineering and Cybernetics program at Siberian Federal University. The study's relevance stems from the rapid digitalization of education and growing interest in online formats, making Master's programs more accessible to working students. We present an analysis of successful practices for implementing online courses, including structural elements, design, content, multimedia, teaching methods, student interaction, assessment, and feedback. Special attention is given to the selection of an online learning platform, with Moodle being justified as the most suitable system for implementing the Master's program. The paper also presents a portrait of an online master's student, helping to identify needs and expectations, which aids in optimizing the educational process. The study emphasizes the importance of applying hybrid methods and complex systems approaches to create a high-quality educational experience and achieve program goals.
Optimization of traffic light phases at adjacent intersections
Authors: Stupin Artem , Stupin Oleg , Makarchuk Ivan
Published: February 2025

The article studies the relationships between the time intervals of traffic light phases and intersections. Traffic light objects can be mutually useful in relation to each other if they are correctly adjusted and the existing load is distributed. The necessary frequency of updating and control of traffic light phases to improve their influence is also revealed. Counting cars on free exits and updating traffic light cycles based on the data obtained provides a field for analyzing and adapting neighboring intersections. The proposed algorithm can help improve the road situation in problem areas of urban connections in the presence of free roads ready for the redistribution of flows.
Application of modern hybrid technologies in the field of data analysis to struggle with spear phishing
Authors: Gordeev Dmitriy , Karaseva Margarita , Karaseva Tatiana
Published: February 2025

To develop techniques to combat spear phishing, it is necessary to constantly develop new ways to detect it. This requires studying the characteristics and factors that indicate spear phishing. The formation of these factors is based on the methods used in mature organizations and on the basis of statistical analysis over past years. This makes it possible to track trends in changes in the tactics and techniques of attackers over time and taking into account the information security systems used. The paper considers the possibility of classical solutions hybridization with neural networks.
Comparative analysis of engineering tools for modeling and analysis
Authors: Matygov Movsar , Ashkhotova Alina , Sokolov Vladislav
Published: February 2025

The paper presents a comparative analysis of engineering tools that are widely utilized in major industries. With the rapidly changing world, new tools emerge and advance, enabling their use for various tasks. Modeling and analysis of structures with complex and simple appearances are an essential part of the engineering world, and hence, choosing the right tool for a certain task can be beneficial in terms of quality and the precision of the end results. This reviews several engineering tools and defines their major advantages. Such tools as SolidWorks, Ansys, Abaqus, Inventor, and Fusion 360 were selected for the research. It is noted in the work that these tools are commonly used in the engineering world for various tasks. It was also found that each engineering tool has its own unique features that differentiate it from others.
Modelling and artificial intelligence technologies in modern approaches to automation of metallurgical industries
Authors: Gerashchenko Vladislav , Kulmurodova Nafisa , Kulmurodov Zarifjon
Published: February 2025

The article examines modern approaches to the automation of metallurgical production, focusing on increasing productivity, improving product quality, and minimizing costs. The main methodologies and implemented technologies are described, with particular emphasis on modeling and simulation techniques. The study highlights the application of industrial control systems, big data analytics, and artificial intelligence technologies in metallurgical processes. A key aspect of the research is the use of advanced modeling tools, such as digital twins and process simulation software, to optimize various stages of metallurgical production. The paper presents a detailed analysis of casting process modeling using ESI Group ProCast software, demonstrating how virtual experiments can predict temperature distribution, metal flow vectors, and potential defect formation in castings. The research also explores the integration of machine learning models for process control and quality assurance in real-world metallurgical operations. An analysis of the practical application of these technologies is conducted, discussing both the advantages and challenges of implementing such advanced systems in the metallurgical industry. The study concludes by emphasizing the transformative potential of modeling and AI technologies in modernizing traditional metallurgical processes and improving overall operational efficiency.
Object segmentation approach in image processing
Authors: Mamatov Narzullo , Fayziyev Vohid , Jalelova Malika , Samijonov Boymirzo
Published: February 2025

Image segmentation is a crucial and complex process in image processing, fundamental to object recognition. While neural network-based methods are widely used for segmentation, they require substantial resources and are vulnerable to noise and artifacts. This study addresses the need for improved segmentation approaches by proposing a novel four-step sequence with corresponding algorithms for object segmentation in images. The research methodology involves developing a systematic approach to image segmentation, implementing the proposed algorithms, and conducting computational experiments using three distinct image databases. The results of the proposed approaches are compared with those of the DeepLabV3+ Resnet50 model, a deep learning-based image segmentation technique. Our findings demonstrate that the proposed approaches outperform the deep learning model in segmenting untrained objects, while the latter excels only with trained objects. This research contributes to the field by offering a more versatile and robust segmentation method, potentially applicable to a wider range of image processing tasks without the need for extensive training data or computational resources. The study highlights the importance of developing adaptive segmentation techniques that can handle diverse object types efficiently.
Unsupervised feature selection in binarization of real attributes for conceptual clustering
Authors: Shkaberina Guzel , Masich Igor , Markushin Egor , Kraeva Ekaterina
Published: February 2025

This paper proposes an approach for processing noisy data to form homogeneous subgroups of objects based on Formal Concept Analysis (FCA). The approach involves binary encoding of heterogeneous features and unsupervised feature selection using the Laplacian Score. The selected feature set is then used to generate formal concepts. The main idea of our research is to use the concepts derived through FCA as new features for clustering. This process transforms the original feature space into a concept-driven space, where each feature corresponds to the extents of the derived concepts. The proposed approach enhances clustering performance in the presence of noise, outperforming the traditional K-means clustering algorithm in terms of cluster coherence and accuracy. By utilizing concept-based features, the method is able to better capture the underlying structure of the data, leading to more robust and meaningful groupings compared to conventional attribute-based clustering techniques.
Modification of software tool for human activity classification
Authors: Farafonov Maxim , Peresunko Evgeniye , Mymlikov Vladislav
Published: February 2025

The work is devoted to the modification and improvement of a neural network system for classifying human actions by changing the position of points of his skeleton. Within the framework of this paper, the description and results of some experiments on modification of the system developed by the authors several years ago will be presented. The experiments include new methods of augmenting the training data, removing some elements of the network, using a completely different representation of the data as a sequence of pictures rather than a set of points, using memory values and the state of the hidden LSTM cell as the output of the network instead of its direct output, and a variant of the network with the introduction of a new layer of feature encoding at the stage of sending skeletal point data to the recurrent LSTM network. The network with different layer configurations was trained multiple times, and the run data was averaged to remove the influence of randomness. In the end, the best network for the network was the one with pre-coded features.
Development and analysis of adaptive mutation techniques in genetic algorithms
Authors: Novikov Zakhar , Sopov Evgenii
Published: February 2025

The proposed adaptive genetic algorithm demonstrates competitive performance, occasionally outperforming the standard approach. Although it shows promising adaptability, further refinements in parameter adjustments and hybridization with other evolutionary techniques could enhance its efficiency, making it a more powerful optimization tool.
Optimization of regular expressions using competitive coevolutionary algorithm based on symbolic regression
Authors: Demidova Liliya , Moroshkin Nikita
Published: February 2025

The paper presents an algorithm for optimizing the structure of regular expressions of the Python programming language dialect of the re module. The optimization algorithm is implemented as a competitive coevolution algorithm based on the symbolic regression algorithm (the Gene Expression Programming algorithm will be used as an implementation of the symbolic regression algorithm). The paper proposes a pseudocode for the regular expression optimization algorithm as an abstract “black box” model, provides hyperparameters of competitive coevolution, as well as a function for assessing the suitability and reliability of individual algorithms within the coevolution. A comparative analysis of the results of running the GEP algorithms as part of coevolution and separately demonstrates the effectiveness of using coevolution as a method for optimizing regular expressions.
Thermo-orientation and anomalous rotational diffusion of cone-shaped particles under a temperature gradient
Authors: Shen Tianshun , Hou Yichen , Yang Jingbin , Yang Lijun , Dong Ruo-Yu
Published: February 2025

Thermophoresis, the translational motion of particles in response to temperature gradients, has been well-studied, but the rotational response remains less understood. This work investigates the thermo-orientation and rotational diffusion of non-spherical particles, with special focus on shape asymmetry, through non-equilibrium molecular dynamics simulations. Our results indicate that the degree of thermo-orientation of asymmetric particles (cone-shaped) is positively correlated with both the aspect ratio (R/H) and the temperature gradient; however, the Soret coefficient exhibits a negative correlation with thermo-orientation. To explore the underlying mechanisms further, we analyzed the variation in the torque experienced by the particles. We propose that the thermo-orientation of particles originates from the combined effects of thermophoretic torque and random torque, which in turn lead to anomalous rotational diffusion behavior. Consequently, we investigated the rotational diffusion characteristics of the particles, observing that the probability density functions of angular displacement transition from Gaussian to thin-tailed distributions, with the degree of non-Gaussianity increasing as the R/H values rise. These results could provide a new perspective based on rotational diffusion dynamics for studying the thermo-orientation of asymmetric particles.
Water intrusion in hydrophobic MOFs with complex topology: A glimpse of the intrusion mechanism of Cu2(tebpz)
Authors: Merchiori Sebastiano , Ballardini Daria , Le Donne Andrea , Bhatia Ribhu , Verziaggi Nicola , Gourmand Cléophée , Grosu Yaroslav , Meloni Simone
Published: February 2025

Despite water intrusion in microporous materials being extensively investigated, obtaining a detailed overview of the intrusion mechanism in materials with more complex morphology, topology, and physical–chemical characteristics, such as metal–organic frameworks (MOFs), is far from trivial. In this work, we present a qualitative study on the mechanism of water intrusion in a crystallite of hydrophobic Cu2(tebpz) (tebpz = 3,3′,5,5′-tetraethyl-4,4′-bipyrazolate) MOF. This MOF is characterized by a complex morphology; it consists of primary (main channels) and secondary (lateral apertures) porosities. This is similar to some zeolites, such as the so-called ITT-type zeolite framework, but it presents the additional characteristics of high flexibility of the material and non-uniform hydrophobicity. Interestingly, in Cu2(tebpz), water intrusion occurs first for some of the channels lying tangent to the surface of the MOF’s crystallite. This is due to hydrogen bonding bridging with bulk water across the (thin) lateral apertures of these channels. In macroscopic terms, this can be understood as a local reduction of hydrophobicity favoring intrusion. Temperature and pressure influence the average number of hydrogen bonds and the number of intruded water molecules, explaining the effect of these thermodynamic parameters on the intrusion/extrusion characteristics of this porous material. Molecular dynamics simulations allowed us to glimpse liquid intrusion in this complex hydrophobic material, highlighting how the classical models valid for mesoporous systems, namely, Young–Laplace’s law, are not quite appropriate to describe intrusion in such materials.
Non-radiating anapole state in dielectric nanostructures and metamaterials
Authors: Wang Junqiao , Yang Jinyuan , Mei Yewen
Published: February 2025

Plasmonic metamaterials and all-dielectric metamaterials, based on metallic or dielectric nanostructures, can concentrate light into subwavelength regions and manipulate light at nanometre length scales through the collective oscillation of free electrons in a metal (plasmon resonances) or from the oscillation of polarization charges and the circular displacement current that are excited inside dielectric mate¬rial (Mie resonances). However, the plasmonic nanostructures undergo large Joule losses and inevitable thermal heating. The all-dielectric metamaterials may overcome the critical issue of heat dissipation and could bridge the gap between fundamental nanoscience and devices. The dielectric resonance elements can be excited by electric and magnetic Mie resonances, and these Mie-type resonance modes can couple or interfere with each other or with other optical modes. Specially, while the radiation of the electric dipole and toroidal dipole modes are similar and in opposite phases, the total scattering cancelation in the far field is reduced to zero, i. e. non-radiating anapole dark state is generated. By manipulating of interaction of multipolar resonances in structured materials, the new field of all-dielectric resonant meta-optics has achieved rapid development. Here, we review the recent development of anapole dark state in dielectric metamaterials, including excitation, probing, coupling, and manipulation. We further discuss the potential applications of anapole state in nanophotonics. This review provides the new insight of anapole physics for achieving flexible and advanced control of light in dielectric nanostructures at the nanoscale.
Design of maneuver libraries for intelligent tactical decision systems
Authors: Qian Bangfei , Gong Zheng , Meng Hangbiao , Zhao Juncheng
Published: February 2025

For intelligent tactical decision systems, this paper establishes a maneuver library with unified output commands based on a three-degree-of-freedom model using a combination of qualitative and quantitative methods. Taking Split S and combat turn as examples, simulation results show that the designed maneuvers accurately reflect their geometric shapes and tactical significance, and can be effectively controlled through the control system.
Optimization of oil-cooled blade structures based on data-driven approaches
Authors: Cao Bo , Yu Yi , Sun Jingchuan , Zhang Lina
Published: February 2025

The continuous escalation of turbine inlet temperatures in aero-engine applications has rendered traditional air-cooling techniques insufficient to undertake the efficient cooling of turbine guide vanes solely. In this context, oil-cooling technology has emerged as a potent complement to air-cooling methods. The stable operating temperature limit of fuel, when used as a coolant, is merely 523 K. In contrast, turbine guide vanes operate at temperatures as high as 1, 900 K, with material allowable temperatures strictly constrained within 1, 373 K. Designing efficient and safe oil-cooled blade structures becomes paramount to the successful application of oil-cooling technology. This paper presents a layered oil-cooled turbine blade structural design scheme, which ingeniously integrates insulation and heat conduction mechanisms, effectively enhancing the oil-cooling system’s adaptability to complex thermal flow environments and notably optimizing the uniformity of temperature distribution on the blade surface. Leveraging commercial simulation software, reduced order models and high-fidelity response surface models of the oil-cooled blades were constructed to conduct a parametric analysis of the layered oil-cooling structure. Under the conditions of ensuring cooling effectiveness and preventing fuel overheating, optimal design parameters for the internal structure of the layered oil-cooled turbine blades were identified, thereby establishing a comprehensive data-driven optimization methodology framework that supports thermal protection design in aero-engine.
Effect of reynolds number on buffet loads of horizontal tail in civil aircraft
Authors: Chen Zhenyu , Zhang Lingfeng , Liu Yang , Wu Dawei , Wei Xiaorong
Published: February 2025

In this paper, the influence of the Reynolds number on the buffeting characteristics of the horizontal tail of a civil aircraft is investigated through CFD analysis and wind tunnel testing, providing valuable insights for the aerodynamic and structural strength design of horizontal tails in civil aircraft. The results indicate that the vibration response of the horizontal tail structure is driven by the separated flow from the main wing as well as the tail’s own separated flow. While the Reynolds number significantly affects the root mean square value of the buffet loads on the tail surface and the structural vibration response, it has no substantial impact on the frequency distribution of buffet load energy.
Design of a machine learning driven helicopter noise suppression system
Authors: Zhou Wenzheng , Du Dalong , Li Yang
Published: February 2025

Helicopter noise poses significant challenges to pilot health and flight safety. To address this issue, our research team has developed an intelligent noise recognition and suppression system. This system uses optimized sensor arrangements and efficient signal processing methods to accurately extract noise features. The deep learning model achieved an accuracy of 95.8% in noise classification tasks, and ensemble learning strategies further enhanced system robustness. The active noise control component achieved an average suppression effect of 18.7 dB in the 100-500Hz frequency range. The system demonstrated stable and reliable performance under various flight conditions and environmental settings, significantly improving the acoustic environment of the cockpit. This achievement provides technical support for improving helicopter pilot safety and comfort and offers valuable insights for other noise control applications.
The numerical simulation research of civil aviation engineer internal flow stability
Authors: Liu Zhenxiong
Published: February 2025

Steady three-dimensional numerical simulations have been used for the civil aviation engineer model to research internal flow stability. A comparison of the numerical method with empirical data validates the accuracy of CFD predictions, revealing a high level of agreement between the two. The simulation of the internal flow field indicates that the tip leakage vortex retains its form in the downstream area beyond the shock wave, achieving peak efficiency, while maintaining a stable vortex vector direction. When the vortex nears a stall condition, vigorous interaction between the vortex and the shock wave leads to the disintegration of the vortex, resulting in a spiral formation. The presence of a low-energy fluid region at the rotor blade’s tip is attributed to the intrusion of the leakage vortex, which may trigger flow instability. The characteristics of this phenomenon resemble those of rotational instability, highlighting the intricate nature of the flow dynamics.
Riveting deformation prediction of aircraft thin-walled parts based on BAS-BP neural network
Authors: Hu Yuanfan , Zhu Yongguo , Guo Feng
Published: February 2025

The contact surface is rough, which affects the riveting process. Firstly, the mechanical analysis of riveting deformation is carried out. Force and contact stiffness of joint surfaces are constructed by fractal contact theory. The fractal contact model of the rough surface of thin-walled parts is established. Based on the measured data of the riveting surface, the finite element analysis model of the rough surface of thin-walled parts is established. The interference uniformity of thin-walled parts is influenced by variables such as riveting force, riveting force action time, the length of the rivet, thin-walled part aperture, and fractal dimension. Finally, the BAS-BP is compared with the riveting deformation prediction data of thin-walled parts optimized by other algorithms.
Sliding mode guidance law with Field-of-view constraint and impact time control for missiles
Authors: Zhang Ziqi , Yin Zhongjie , Meng Wanli , Lu Zhengyu , Song Tianwei
Published: February 2025

This study introduces an innovative guidance law that allows for controlled impact time while meeting the missile’s field-of-view angle constraints. The equation that shows the missile-target relative movement is first established. A non-singular sliding mode guidance law is designed, leveraging sliding mode control theory. Under the field-of-view constraints, the impact time reaches the desired value, as proven according to the Lyapunov stability theory. The analyses derived from the numerical simulation support that the missile’s field-of-view angle remains within constraints throughout the attack process, and the control commands are smooth without singularities. The research findings hold significant value as a reference for designing multi-missile coordinated attack strategies.
Research on crosslink density testing method of GAP propellant based on swelling method
Authors: Wang Xueren , Chen Zebin , Qiang Hongfu , Fu Xiao
Published: February 2025

In order to determine the crosslink density of GAP (Glycidyl Azide Polymer) propellants more accurately and conveniently, and to explore the relationship between the performance of GAP propellants and the crosslink density and gel fraction, this paper proposes several key factors that should be paid attention to when selecting solvents for the determination of the crosslink density of GAP propellants by equilibrium dissolution method. The values of the crosslink density of GAP are determined, while the dissolution time required for the determination of the crosslink density of GAP by the equilibrium dissolution method is given. The changes in GAP propellant crosslink density and gel fraction with aging and the relationship with its mechanical properties were explored. The results showed that the interaction parameters between solvent and adhesive and the solubility of components such as solid filler should be considered when selecting the solvent for equilibrium swelling, and the solvent selected should not dissolve out the solid filler in order to calculate accurately; trichloromethane was selected as the solvent for the determination of cross-linking density of GAP by comparing the swelling degree and the mass fraction of dissolved material, and the swelling time should be around 48 h at 25°C; the results of the determination of the crosslink density of the GAP propellant were in the range of 5.1666×10−5−5.5957×10−5 mol·cm−3; the crosslink density and gel fraction of the GAP propellant did not change much with aging, and the changes in its mechanical properties due to aging should be considered in light of other factors such as dehumidification.
Research on Low-Pass filtering noise reduction method for Multi-Rotor Heavy-duty unmanned aerial vehicles based on fast fourier transform
Authors: Ji Liming , Huang Yunlong , Sun Jiaqiang , Shangguan Chunmei , Shi Fenghua , Tu Feng , Guo Wei
Published: February 2025

Heavy-duty unmanned aerial vehicles (UAVs) are poised to revolutionize the material transportation paradigm in overhead transmission line construction. Among the pivotal factors influencing the performance of multi-rotor UAVs, vibration emerges as a critical concern. Addressing vibration mitigation in heavy-duty UAVs is fundamental to enhancing flight quality and transportation capabilities. To effectively reduce UAV vibrations and stabilize flight conditions amidst excessive vibrations, this study employs a low-pass filtering approach grounded in Fast Fourier Transform (FFT) for noise reduction of the response signals from a designed hex-rotor heavy-duty UAV. The outcomes demonstrate that the FFT-based low-pass filtering method achieves notable noise reduction. By adjusting the cutoff frequency downward, the noise in the post-filtered heavy-duty UAV response signals is significantly attenuated.
Experimental research on attenuation and activation characteristics of molecular sieves
Authors: Wei Yuchen , Lan Yuqing , Yuan Bo , Zeng Yu , Lin Guiping
Published: February 2025

The attenuation and activation characteristics of a kind of zeolite molecular sieve were studied by using the control variable method. The experimental results showed that water absorption shortened the adsorption time and greatly reduced oxygen production, and the properties of sodium zeolite were relatively stable. Under the three activation methods, the peak oxygen concentration of the product gas increased by 0.62%~8.5%, but the oxygen production performance could not be completely restored. XRD results showed that high temperature and high humidity could cause irreversible changes in the internal structure of zeolites. Therefore, in practical application, the inlet temperature and humidity should be fully considered, and the water-absorbing molecular sieve should be treated in time.
Afterburning effect on the thermal environment of the launch pad during the rocket launching
Authors: Zhao Chengeng , Sun Zhongyi , Le Guigao
Published: February 2025

This study aims to investigate how afterburning affects the thermal environment of the launch pad during a rocket launch. The thermal environment and launch pad flow field are studied using numerical simulations during the vehicle lift-off phase to achieve this goal. The launch vehicle exhaust plume model is constructed during the lift-off phase using the reaction model, the Realizable k-ε two-equation turbulence model, and the three-dimensional compressible Navier-Stokes equations. The results of the investigation demonstrate that the temperature field of the rocket exhaust plume is higher in the gas chemical reaction flow scenario compared to the frozen flow scenario. In addition, considering both the frozen and gas chemical reaction flows causes the launch pad surface temperature to rise. The research approach used in this study sheds important light on the launch pad’s thermal protection design.
Numerical simulation of the effect of Faraday cage on the inductively coupled plasma discharge
Authors: Lei Fan , Zhang Zhaoyang , Wei Xiaolong , Han Xinmin , Wu Hongzhi , Liu Zhiwei
Published: February 2025

Taking inductively coupled plasma (ICP) as the research object, a method of increasing the electron density of ICP by Faraday cage electromagnetic shielding is proposed. At the same time, the introduction of the Faraday cage can effectively prevent the electromagnetic interference caused by the discharge coil, which is helpful in reproducing the real near-space plasma environment in the laboratory. Based on COMSOL Multiphysics, a two-dimensional inductively coupled plasma discharge model was constructed, and the effect of the Faraday cage on ICP discharge parameters was comparatively studied. The simulation results show that the Faraday cage can effectively shield the electromagnetic interference caused by the discharge coil. At the same time, the Faraday cage can increase the electron density and the electron temperature of the plasma to a certain extent, and the plasma is evenly distributed in this case. With the increase of discharge power, the electromagnetic shielding effect of the Faraday cage is still effective, and the effect on the plasma electron density is more obvious.
Metabolic byproduct utilization and the evolution of mutually beneficial cooperation in Escherichia coli
Authors: Ye Nan , Hou Beibei , Song Jianxiao , Dunn Derek W , Ma Zhanshan (Sam) , Wang Rui-Wu
Published: February 2025

Understanding how cooperation evolves in microbial populations, particularly under environmental stress such as antibiotic exposure, remains a key topic in evolutionary biology. Here, we investigate cooperative interactions between antibiotic-resistant and antibiotic-sensitive strains of Escherichia coli. Under antibiotic stress, a small number of antibiotic-sensitive strains rapidly evolve into antibiotic-resistant strains. Resistant E. coli produce indole, which induces a protective response in sensitive cells, enabling them to survive in antibiotic stress conditions. In turn, antibiotic-sensitive E. coli could help reduce toxic accumulation of indole, indirectly benefiting the resistant strain. Indole is harmful to the growth of the antibiotic-resistant strain but benefits the antibiotic-sensitive strain by helping turn-on the multi-drug exporter to neutralize the antibiotic. This mutual exchange leads to increased fitness for both strains in cocultures, demonstrating a mechanism by which mutually beneficial cooperation can evolve in bacterial communities. Our findings provide insight into how mutualism can emerge under antibiotic pressure through metabolic byproduct exchange, revealing new dynamics in the evolution of bacterial cooperation.
Nanopore Sequencing of Amoebophrya sp. Reveals Novel Collection of Bacteria Putatively Associated with Karlodinium veneficum
Authors: Tizabi Daniela , Hill Russell T , Bachvaroff Tsvetan
Published: February 2025

The dinoflagellate parasite Amoebophrya sp. ex Karlodinium veneficum plays a major role in controlling populations of the toxic bloom-forming dinoflagellate Karlodinium veneficum and is one of the few cultured representatives of Marine Alveolate Group II. The obligate parasitic nature of this Amoebophrya spp. precludes isolation in culture, and therefore, genomic characterization of this parasite relies on metagenomic sequencing. Whole genome sequencing of an Amoebophrya sp. ex Karlodinium veneficum-infected culture using Nanopore long reads revealed a diverse community of novel bacteria as well as several species previously reported to be associated with algae. In sum, 39 metagenome-assembled genomes (MAG) were assembled, and less than half of these required binning of multiple contigs. Seven were abundant but of unknown genera, thirteen were identifiable at the generic level by BLAST (eight of which were apparently complete single-contig genomes), and the remaining 19 comprised less abundant (individually accounting for < 2% of the total bacterial reads in the culture) and often rarer and/or novel species. Attempts to culture strains identified through sequencing revealed that only two of these bacterial isolates were readily amenable to cultivation, stressing the importance of a dual culture- and sequencing-based approach for robust community analysis. Functional annotations of MAGs are presented here to support the characterization of a microbial community associated with K. veneficum and/or Amoebophrya sp. ex K. veneficum cultured from the Chesapeake Bay and give preliminary insights into the nature of the associations these bacteria have with this parasite-host complex.