bluuebunny/crossref_metadata_2025 huggingface dataset:
Defense Stability and Ecosystem Sustainability in the Strait of Malacca: Maritime Security Challenges from an International Relations Perspective
Authors: Awal Syahrul , Sumadinata R. Widya Setiabudi , Yani Yanyan Mochamad , Sudirman Arfin
Published: January 2025

This study examines the challenges of defense stability and ecosystem sustainability in the Strait of Malacca, one of the most strategic shipping lanes in the world. The strait plays a crucial role in global trade and geopolitics; however, the high volume of maritime traffic has led to issues such as maritime security threats, including piracy, smuggling, and geopolitical tensions, as well as environmental threats like marine pollution and ecosystem degradation. Cooperation between coastal countries such as Indonesia, Malaysia, and Singapore through the Cooperative Mechanism has successfully reduced security threats and environmental impacts, though significant challenges remain. The research employs a qualitative approach through literature reviews and document analysis. It focuses on the interaction between defense stability and ecosystem sustainability from an international relations perspective, including the role of security actors and environmental diplomacy. The findings reveal that defense stability in the Strait of Malacca is closely linked to regional cooperation and international power support. The use of advanced technologies such as satellite monitoring has enhanced maritime security, yet stronger environmental protection policies are still needed. In conclusion, the stability of the Strait of Malacca requires effective mitigation through cross-border cooperation, international policies, and enhanced monitoring technologies to safeguard this vital route for the global economy and the environment.
Fatty acids from soybeans: compatibility with Panonychus citri (Acari: Tetranychidae) and its two predators
Authors: Qayyoum Muhammad Asif , Khan Bilal Saeed , Song Zi-Wei , Yi Tian-Ci , Inayat Rehan , Akram Muhammad Irfan , Mobarak Syed Husne , Li Dun-Song
Published: January 2025

Soybean oil is a significant alternative to synthetic chemicals for environmentally friendly and sustainable pest control. This study evaluated soybean oil and its fatty acids (palmitic, oleic, and stearic acids; individually) for their acaricidal and repellent effects against Panonychus citri (Tetranychidae) and its predators [Neoseiulus californicus and Neoseiulus barkeri [Phytoseiidae]) using laboratory foliar dipping and topical spray methods. The LC50 (Lethal Concentration) values for palmitic, oleic, stearic acids, and soybean oil against P. citri were 0.86%, 0.95%, 0.56%, and 0.05% for LDM (Leaf-dipping Method) and 11.92%, 5.34%, 1.46%, and 0.07% for TSM (Topical Spray Method). Soybean oil has maximum attraction (46.67 ± 3.6%) and significantly higher acaricidal effectiveness (46.25 ± 0.98%) compared to acids except oleic acid (50.83 ± 1.22%) against P. citri. Soybean oil showed the least toxicity, with the highest LT50 (Lethal Time) values for N. californicus (LDM: 1.19 h, TSM: 1.27 h). While soybean oil caused a less significant reduction in fertility and lower lethal efficacy (0.83 ± 0.83%) on predatory mites compared to P. citri. Compared to soybean oil, oleic acid reduces fertility rate (27 ± 1.60%) and is an effective repellent (65-75%) against N. californicus and N. barkeri and reduces prey consumption (15-16%) and laying eggs (0.75 ± 0.47) on treated surfaces compared to other treatments. Palmitic acid increases prey consumption (27.5 ± 3.28%) and fertility rates (5.00 ± 0.71) of N. californicus. Palmitic acid, despite being less toxic to P. citri, effectively repels predators, while soybean oil and oleic acid have stronger repellent effects. Leaf dipping was less effective than topical spray. Soybean oil, with its lower mortality rates and sublethal effects on reproduction and behavior, is a strong candidate for integrated pest management strategies. Oleic and palmitic acids, though effective, have repellency to beneficial predators.
Grisotti flap for central quadrant breast tumours: quick, cosmetic and easy to learn – a case series
Authors: Sharma Shivaji , Pao Karan
Published: January 2025

Background: Breast cancer surgery has moved away from mutilating mastectomies to organ preservation approach keeping in mind the cosmetic outcome. Centrally located tumours are particularly notorious as they often require resection of the nipple-areola complex (NAC) thus creating a gross cosmetic defect. However, cosmesis is possible even after such surgeries. Methods: Seven consecutive patients with centrally located breast tumours were subjected to breast conservation surgery – either upfront or after neoadjuvant chemotherapy – followed by reconstruction with Grisotti flap. All patients were followed up for a minimum period of 3 months after surgery. None of them had any flap related complications and reported satisfactory cosmetic outcome with no loss of body image. Interpretation: Lumpectomy with resection of the NAC with Grisotti flap reconstruction is a relatively fast procedure with a short learning curve. In our case series of 7 women, all underwent successful breast reconstruction with minimum morbidity and excellent cosmetic outcome.
The multinational enterprise, capabilities, and digitalization: governance and growth with world disorder
Authors: Teece David J.
Published: January 2025

This essay revisits my 2014 JIBS article about the potential for integrating international business internalization theory with a strategic management capabilities perspective. It recaps the capabilities framework with an emphasis on the learning required of emerging market multinationals and illustrates this with the case of Hyundai Motor Company’s internationalization and growth. It also discusses two aspects of the global economy that have become more prominent since 2014 in shaping international business: geopolitical uncertainty and digitalization. A rise in geopolitical tensions appears to be rebalancing the relationships between multinationals and home/host governments. Digitalization facilitates international business; but it adds new vulnerabilities by (further) accelerating competition, enabling new rivals, and introducing systemic risks into digital supply chains. Implications for managers, board members, and international business scholars are drawn.
Characterization of the upgraded photoinjector at the Chinese Academy of Engineering Physics Terahertz Free Electron Laser Facility
Authors: Xu Hanxun , Ma Shuai , Li Wenhao , Li Lanbin , Wang Weijun , Xiao Dexin , Wang Jianxin , Liu Yu , Yan Longgang , Chen Lijun , Shen Xuming , Liu Jie , Zhou Zheng , Li Peng , Zhou Kui , Yang Xinfan , Wu Dai , Li Ming
Published: January 2025

The Chinese Academy of Engineering Physics Terahertz Free Electron Laser Facility (CAEP THz FEL, CTFEL) has been operated as a user facility for over five years. To further meet the growing demands of modern science, an upgrade project for an infrared-terahertz free electron laser facility based on CTFEL has been proposed to broaden the frequency range from 0.1–4.2 to 0.1–125 THz. Recently we upgraded the CTFEL photoinjector in order to fulfill the beam injection requirements of the infrared-terahertz free electron laser facility. In this paper, we measured the beam parameters of the upgraded CTFEL photoinjector. A Michelson interferometer was constructed to measure the auto-correlation of the coherent transition radiation emitted by the electron bunch. Both the Kramers–Kronig reconstruction method and the time-domain fitting approach have been employed to estimate the bunch length, resulting in a root-mean-square bunch length of 0.30 ps. A normalized transverse emittance of 5.62 π mm mrad was determined by a quadrupole scan. The measured mean energy of the electron bunch is adjustable between 6 and 8 MeV with an energy spread of less than 0.5%. These measurements prove that the upgraded CTFEL photoinjector fulfills the injection requirements of the facility to be built.
Action potential-like modes as modulated waves in an extended soliton model for biomembranes and nerves
Authors: Onana Inouga J. A. , Mkam Tchouobiap S. E. , Siewe Siewe M. , Moukam Kakmeni F. M.
Published: January 2025

By extending the Heimburg–Jackson soliton model for neural signals that considers the effects of higher-order nonlinearities, the dynamics of modulated waves characterizing electromechanical density pulses is described in the form of soliton-like pulse signals representing nerve impulses, well-known as action potential pulses (Appulses). The investigation is performed both analytically and numerically, where a comprehensive picture of higher-order nonlinearities effects on the generation and evolution of nerve impulses is provided. Within the framework of a multiple-scale-expansion analysis and the reductive perturbation method, while considering third- and fourth-order nonlinearities, the electromechanical area-density pulse propagation is investigated, leading to the generation of a localized Appulse. Accordingly, the analytical theory uses a perturbative technique, and a damped cubic–quintic nonlinear Schrödinger equation is derived, which admits a single-pulse-type solitary solution that possesses different phase characteristics of the typical neuronal Appulse structure, representative of nerve impulse profiles. A modulational instability (MI) analysis demonstrates the increase of the modulation gain in the system with increasing fourth-order nonlinearity, indicating that the higher-order nonlinearities influence the MI in the proposed extended soliton model. Furthermore, a numerical analysis is performed, and consistent agreement with the analytical prediction is achieved, confirming a localized typical longitudinal single pulse-like solitary wave solution for the extended soliton model. Importantly, the appearance of a typical longitudinal single-solitary pulse-type structure can evolve uniformly with increasing fourth-order nonlinearity, leading to the splitting of the single-pulse-soliton signal and resulting in the appearance of a double asymmetric localized pulse-like mode or bisoliton-pulse structure, characteristic of a coupled Appulse.
Physics-informed genetic algorithms (PIGAs) facilitating LIBS spectral normalization with shockwave characteristics
Authors: Zhou Ying , Wu Jian , Shi Mingxin , Chen Minxin , Li Jinghui , Guo Xinyu , Hang Yuhua , Pei Cuixiang , Li Xingwen
Published: January 2025

Inspired by physics-informed neural networks (PINNs) inheriting both the interpretability of physical laws and the efficient integration capability of machine learning, we propose a framework based on stoichiometric ablation for LIBS spectral normalization, encoding physical constraints between LIBS intensities and shockwave characteristics (temperature Tshock and pressure P) into optimization algorithms with multiple independent objectives, named physics-informed genetic algorithms (PIGAs). It is characterized by its applicability to the wider laser energy range, covering laser-induced breakdown to significant plasma shielding and spectral lines undergoing self-absorption, outperforming the widely used physical linear or multivariate data-driven normalization methods. The home-made end-to-end LAP-RTE codes serve as the benchmark to validate the physical reciprocal-logarithmic transformation and its extensibility to self-absorption spectral lines for PIGAs. Next, experimental spectral lines are statistically used to validate PIGAs' correction effects; the median RSDs of spectral intensities can be effectively reduced by 85% (corrected by P) and 88% (corrected by Tshock) for 108 Fe I lines, while for 33 Fe II lines, reduced by 77% (corrected by P) and 86% (corrected by Tshock). Seventeen self-absorption lines are also corrected effectively, with RSDs being reduced by 78% (corrected by P) and 89% (corrected by Tshock). Our proposed idea of combining optimization methods to quantify unknown parameters in normalization strategies can also be extended to excavate the correlation between parameters for other low-temperature plasma fields with similar processes.
Deformation and reverse phase transformation mechanism of high-pressure HCP iron during unloading process
Authors: Yu Jinmin , Shao Jianli , Shu Hua , Ma Xuyang , Zhou Xichen , Huang Xiuguang , Fu Sizu
Published: January 2025

Iron will undergo the BCC to HCP transformation under pressure, but the reverse process during the unloading path has not been fully revealed on the atomic scale. This work investigated the unloading dynamics of a HCP single crystal of iron, focusing on the microstructure evolution and related mechanical characteristics. For unloading along the normal direction of the (1¯21¯0) and (101¯0) planes, a mechanism for coupling between twinning and phase transformation was reported. The HCP to BCC transformation with the rod-like structure and twinning was revealed, which was well supported by previous experiments. For unloading along the normal direction of the (0001) plane, the HCP–FCC–BCC transition was observed. Significant shear stress was generated internally, leading to significant dislocations. There are multiple transition paths of the HCP to FCC phase, resulting in the formation of grain boundaries and ultimately leaving the polycrystalline structures. This process was accompanied by coupled development of dislocations, grain mergers, and phase transitions. As the unloading process gradually evolves into the stretching process, detwinning and reconstruction will occur for unloading along the normal direction of the (1¯21¯0) and (101¯0) planes, accompanied by grain rotation.
Fracture propagation characteristics and energy evolution law of deep coal seam containing gangue based on discrete lattice method
Authors: Zhang Wang , Zhao Haifeng , Liu Zhiyuan , Shi Hongwei , Wang Tengfei
Published: January 2025

Hydraulic fracturing is a key technology for the development of deep coal-rock reservoirs. Gangue, a common rock type within coal-bearing strata, significantly influences fracture morphology after fracturing. Understanding fracture propagation in coal-rock containing gangue and effectively controlling artificial fractures remain critical challenges in fracturing operations. To address this, the study investigates the coal-bearing strata of the Benxi Formation in the Daning-Jixian area of the Ordos Basin, characterized by the presence of gangue. A three-dimensional discrete lattice model was developed to analyze the effects of gangue-related factors, including the number, thickness, dip angle, and type, on hydraulic fracturing. The fracture propagation patterns and stimulation effects under these factors were systematically compared. Using node path tracking and post-processing techniques, the study identified the fracturing characteristics and fracture propagation modes at different stages. The findings indicate that gangue characteristics significantly impact fracture morphology and propagation paths. Specifically, an increase in the number of gangue layers enhances fracture complexity but reduces the effective stimulation ratio. Gangue thickness positively correlates with fracture tortuosity and inversely correlates with the effective stimulation ratio. The dip angle of gangue determines the direction of fracture propagation but has minimal influence on the stimulation area. The gangue type also affects fracture morphology; for instance, sandstone gangue leads to narrower fractures and more interface fractures at the sandstone–coal boundary compared to mudstone gangue. Fracture propagation, characterized by energy changes, can be divided into four distinct stages: Stage I (initial injection phase), Stage II (onset of fracture propagation), Stage III (fluid energy storage within gangue), and Stage IV (fracture penetration through gangue). These stages are marked by variations in fluid injection energy, fluctuation energy, surface energy, and strain energy as the fracture penetrates the layer, deflects, and forms horizontal fractures. The simulation of fracture network evolution in coal-bearing strata containing gangue provides significant theoretical guidance for understanding, predicting, and controlling fracture network morphology in coal reservoirs. These findings are instrumental for the efficient development of deep coalbed methane.
Lost opportunities: How gendered arrangements harm men
Authors: Bareket Orly , Fiske Susan T.
Published: January 2025

Traditional gendered arrangements—norms, roles, prejudices, and hierarchies—shape every human life. Associated harms are primarily framed as women’s issues due to more severe consequences women face. Yet, gendered arrangements also shape
men
’s relationships, career paths, and health. Current work on gender equity overlooks men’s perspectives. Despite benefits they gain from out-ranking women, men’s position paradoxically entraps them in restrictive roles, compelling them to prioritize dominance. An inclusive framework challenges prevailing narratives by considering personal costs borne by men. Identifying with a man’s traditional role is a mixed privilege, as five gendered arrangements show for men who subscribe to them: 1.
Masculine norms
can restrict men’s choices and are associated with adverse health trajectories; 2. Some
men’s disengagement from communal roles
denies them positive outcomes associated with caring for others; 3.
Hostile sexism
fosters antipathy, fueling tension in some men’s interactions with women; 4.
Benevolent sexism
forces some men into scripted interactions, preventing genuine connections and burdening them with unrealistic breadwinner and protector roles; 5.
Societal shifts in gender hierarchies
can elicit threat responses in men, depending on intersections with social class and racial identities. Understanding costs to men calls for more empirical research. Gender equity for men, whose circumstances differ from those of women, would enable men to make informed choices and achieve better outcomes for themselves—paralleling the progress women have made in many areas of life. Striving for equity for
all
genders can ultimately enhance overall human well-being.
Diffusive topology preserving manifold distances for single-cell data analysis
Authors: Wei Jiangyong , Zhang Bin , Wang Qiu , Zhou Tianshou , Tian Tianhai , Chen Luonan
Published: January 2025

Manifold learning techniques have emerged as crucial tools for uncovering latent patterns in high-dimensional single-cell data. However, most existing dimensionality reduction methods primarily rely on 2D visualization, which can distort true data relationships and fail to extract reliable biological information. Here, we present DTNE (diffusive topology neighbor embedding), a dimensionality reduction framework that faithfully approximates manifold distance to enhance cellular relationships and dynamics. DTNE constructs a manifold distance matrix using a modified personalized PageRank algorithm, thereby preserving topological structure while enabling diverse single-cell analyses. This approach facilitates distribution-based cellular relationship analysis, pseudotime inference, and clustering within a unified framework. Extensive benchmarking against mainstream algorithms on diverse datasets demonstrates DTNE’s superior performance in maintaining geodesic distances and revealing significant biological patterns. Our results establish DTNE as a powerful tool for high-dimensional data analysis in uncovering meaningful biological insights.
Macromolecular interactions and geometrical confinement determine the 3D diffusion of ribosome-sized particles in live
Escherichia coli
cells
Authors: Valverde-Mendez Diana , Sunol Alp M. , Bratton Benjamin P. , Delarue Morgan , Hofmann Jennifer L. , Sheehan Joseph P. , Gitai Zemer , Holt Liam J. , Shaevitz Joshua W. , Zia Roseanna N.
Published: January 2025

The crowded bacterial cytoplasm is composed of biomolecules that span several orders of magnitude in size and electrical charge. This complexity has been proposed as the source of the rich spatial organization and apparent anomalous diffusion of intracellular components, although this has not been tested directly. Here, we use biplane microscopy to track the 3D motion of self-assembled bacterial genetically encoded multimeric nanoparticles (bGEMs) with tunable size (20 to 50 nm) and charge (−3,240 to +2,700 e) in live
Escherichia coli
cells. To probe intermolecular details at spatial and temporal resolutions beyond experimental limits, we also developed a colloidal whole-cell model that explicitly represents the size and charge of cytoplasmic macromolecules and the porous structure of the bacterial nucleoid. Combining these techniques, we show that bGEMs spatially segregate by size, with small 20-nm particles enriched inside the nucleoid, and larger and/or positively charged particles excluded from this region. Localization is driven by entropic and electrostatic forces arising from cytoplasmic polydispersity, nucleoid structure, geometrical confinement, and interactions with other biomolecules including ribosomes and DNA. We observe that at the timescales of traditional single molecule tracking experiments, motion appears subdiffusive for all particle sizes and charges. However, using computer simulations with higher temporal resolution, we find that the apparent anomalous exponents are governed by the region of the cell in which bGEMs are located. Molecular motion does not display anomalous diffusion on short time scales and the apparent subdiffusion arises from geometrical confinement within the nucleoid and by the cell boundary.
Representational geometry explains puzzling error distributions in behavioral tasks
Authors: Wei Xue-Xin , Woodford Michael
Published: January 2025

Measuring and interpreting errors in behavioral tasks is critical for understanding cognition. Conventional wisdom assumes that encoding/decoding errors for continuous variables in behavioral tasks should naturally have Gaussian distributions, so that deviations from normality in the empirical data indicate the presence of more complex sources of noise. This line of reasoning has been central for prior research on working memory. Here, we reassess this assumption and find that even in ideal observer models with Gaussian encoding noise, the error distribution is generally non-Gaussian, contrary to the commonly held belief. Critically, we find that the shape of the error distribution is determined by the geometrical structure of the encoding manifold via a simple rule. In the case of a high-dimensional geometry, the error distributions naturally exhibit flat tails. Using this insight, we apply our theory to visual short-term memory tasks, and find that it can account for a large array of experimental data with only two free parameters. Our results challenge the dominant view in the mechanisms and capacity constraints of working memory systems. They instead suggest that the Bayesian framework, which explains various aspects of perceptual behavior, also provides an excellent account of working memory. Overall, our results establish a direct connection between neural manifold geometry and behavior, and call attention to the geometry of the representation as a critically important, yet underappreciated factor in determining the character of errors in human behavior.
Co-option of mitochondrial nucleic acid–sensing pathways by HSV-1 UL12.5 for reactivation from latent infection
Authors: Krakowiak Patryk A. , Flores Matthew E. , Cuddy Sean R. , Whitford Abigail L. , Dochnal Sara A. , Babnis Aleksandra , Miyake Tsuyoshi , Tigano Marco , Engel Daniel A. , Cliffe Anna R.
Published: January 2025

Although viruses subvert innate immune pathways for their replication, there is evidence they can also co-opt antiviral responses for their benefit. The ubiquitous human pathogen, Herpes simplex virus-1 (HSV-1), encodes a protein (UL12.5) that induces the release of mitochondrial nucleic acid into the cytosol, which activates immune-sensing pathways and reduces productive replication in nonneuronal cells. HSV-1 establishes latency in neurons and can reactivate to cause disease. We found that UL12.5 is required for HSV-1 reactivation in neurons and acts to directly promote viral lytic gene expression during initial exit from latency. Further, the direct activation of innate immune-sensing pathways triggered HSV-1 reactivation and compensated for a lack of UL12.5. Finally, we found that the induction of HSV-1 lytic genes during reactivation required intact RNA- and DNA-sensing pathways, demonstrating that HSV-1 can respond to and active antiviral nucleic acid–sensing pathways to reactivate from a latent infection.
Automating alloy design and discovery with physics-aware multimodal multiagent AI
Authors: Ghafarollahi Alireza , Buehler Markus J.
Published: January 2025

The design of new alloys is a multiscale problem that requires a holistic approach that involves retrieving relevant knowledge, applying advanced computational methods, conducting experimental validations, and analyzing the results, a process that is typically slow and reserved for human experts. Machine learning can help accelerate this process, for instance, through the use of deep surrogate models that connect structural and chemical features to material properties, or vice versa. However, existing data-driven models often target specific material objectives, offering limited flexibility to integrate out-of-domain knowledge and cannot adapt to new, unforeseen challenges. Here, we overcome these limitations by leveraging the distinct capabilities of multiple AI agents that collaborate autonomously within a dynamic environment to solve complex materials design tasks. The proposed physics-aware generative AI platform, AtomAgents, synergizes the intelligence of large language models (LLMs) and the dynamic collaboration among AI agents with expertise in various domains, including knowledge retrieval, multimodal data integration, physics-based simulations, and comprehensive results analysis across modalities. The concerted effort of the multiagent system allows for addressing complex materials design problems, as demonstrated by examples that include autonomously designing metallic alloys with enhanced properties compared to their pure counterparts. Our results enable accurate prediction of key characteristics across alloys and highlight the crucial role of solid solution alloying to steer the development of advanced metallic alloys. Our framework enhances the efficiency of complex multiobjective design tasks and opens avenues in fields such as biomedical materials engineering, renewable energy, and environmental sustainability.
A tough soft–hard interface in the human knee joint driven by multiscale toughening mechanisms
Authors: Li Wenyue , Wang Xiaozhao , Mao Renwei , Li Dong , Meng Hongxu , Zhang Ru , Fang Jinghua , Kang Zhengzhong , Wu Boxuan , Ma Weiwei , Yao Xudong , Xie Chang , Li Rui , Wang Jin , Chen Xiao , Pan Xihao , Chen Weiqiu , Duan Wangping , Gao Huajian , Ouyang Hongwei
Published: January 2025

Joining heterogeneous materials in engineered structures remains a significant challenge due to stress concentration at interfaces, which often leads to unexpected failures. Investigating the complex, multiscale-graded structures found in animal tissue provides valuable insights that can help address this challenge. The human meniscus root–bone interface is an exemplary model, renowned for its exceptional fatigue resistance, toughness, and interfacial adhesion properties throughout its lifespan. Here, we investigated the multiscale graded mineralization structure and their strengthening mechanisms within the 30-micron soft–hard interface at the root–bone junction. This graded interface, featuring interdigitated structures and an exponential increase in modulus, undergoes a phase transition from amorphous calcium phosphate (ACP) to gradually matured hydroxyapatite (HAP) crystals, regulated by location-specific distributed biomolecules. In coordination with collagen fibril deformation and reorientation, the in situ tensile mechanical experiments and molecular dynamic simulations revealed that immature ACP particles debond from the collagenous matrix and translocate to dissipate energy, while the progressively matured HAP crystals with high stiffness pins propagating cracks, thereby enhancing both the toughness and fatigue resistance of the interface. To further validate our findings, we built biomimetic soft–hard interfaces with phase-transforming mineralization which exhibited boosted strength, toughness, and interface adhesion. This interface model is generalizable to other material joints and provides a blueprint for developing robust soft–hard composites across various applications.
Antiviral Mx proteins have an ancient origin and widespread distribution among eukaryotes
Authors: Langley Caroline A. , Dietzen Peter A. , Emerman Michael , Tenthorey Jeannette L. , Malik Harmit S.
Published: January 2025

Mx proteins, first identified in mammals, encode potent antiviral activity against a wide range of viruses. Mx proteins arose within the Dynamin superfamily of proteins (DSP), which mediate critical cellular processes, such as endocytosis and mitochondrial, plastid, and peroxisomal dynamics. Despite their crucial role, the evolutionary origins of Mx proteins are poorly understood. Through comprehensive phylogenomic analyses with progressively expanded taxonomic sampling, we demonstrate that Mx proteins predate the interferon signaling system in vertebrates. Our analyses find an ancient monophyletic DSP lineage in eukaryotes that groups vertebrate and invertebrate Mx proteins with fungal MxF proteins, the largely uncharacterized plant and algal Dynamin 4A/4C proteins, and representatives from several other eukaryotic lineages, suggesting that Mx-like proteins date back close to the origin of Eukarya. Our phylogenetic analyses also find host-encoded and nucleocytoplasmic large DNA viruses-encoded DSPs interspersed in four distinct DSP lineages, indicating recurrent viral theft of host DSPs. Our analyses thus reveal an ancient history of viral and antiviral functions encoded by the Dynamin superfamily in eukaryotes.
Can the Discriminative Lexicon Model account for the family size effect in auditory word recognition?
Authors: Müller Hanno , ten Bosch Louis , Ernestus Mirjam
Published: January 2025

Words with larger morphological families elicit shorter response times (RTs) in lexical decision experiments
(e.g., Bertram et al. 2000). One possible account for this family size (FS) effect draws on the Discriminative Lexicon Model (DLM; Chuang & Baayen 2021), positing that morphological family members strengthen relationships between forms and
meanings. While it has been shown that the DLM successfully explains FS effects in reading (Mulder et al. 2014), we investigated whether it does so in listening too. We trained the computational model LDL-AURIS
(Shafaei-Bajestan et al. 2023), which implements the DLM, on Dutch and show that a
measure derived from LDL-AURIS accounts for variance in auditory lexical decision RTs in Dutch, and also partially accounts for
the same variance in the RTs as the auditory FS effect. Future research should investigate whether some other measure derived from
the DLM can fully explain FS effects in listening.
RNase T2 restricts TLR13-mediated autoinflammation in vivo
Authors: Gomez-Diaz Carlos , Greulich Wilhelm , Wefers Benedikt , Wang Meiyue , Bolsega Silvia , Effern Maike , Varga Daniel P. , Han Zhe , Chen Minyi , Bérouti Marleen , Leonardi Natascia , Schillinger Ulrike , Holzmann Bernhard , Liesz Arthur , Roers Axel , Hölzel Michael , Basic Marijana , Wurst Wolfgang , Hornung Veit
Published: January 2025

RNA-sensing TLRs are strategically positioned in the endolysosome to detect incoming nonself RNA. RNase T2 plays a critical role in processing long, structured RNA into short oligoribonucleotides that engage TLR7 or TLR8. In addition to its positive regulatory role, RNase T2 also restricts RNA recognition through unknown mechanisms, as patients deficient in RNase T2 suffer from neuroinflammation. Consistent with this, mice lacking RNase T2 exhibit interferon-dependent neuroinflammation, impaired hematopoiesis, and splenomegaly. However, the mechanism by which RNase T2 deficiency unleashes inflammation in vivo remains unknown. Here, we report that the inflammatory phenotype found in Rnaset2−/− mice is completely reversed in the absence of TLR13, suggesting aberrant accumulation of an RNA ligand for this receptor. Interestingly, this TLR13-driven inflammatory phenotype is also fully present in germ-free mice, suggesting a role for RNase T2 in limiting erroneous TLR13 activation by an as yet unidentified endogenous ligand. These results establish TLR13 as a potential self-sensor that is kept in check by RNase T2.
PANX1 hexamers work but cells prefer heptamers
Authors: Harris Andrew L.
Published: January 2025

Gupta et al. (https://doi.org/10.1085/jgp.202413676) reconcile a disconnect between structural and functional data regarding stoichiometry of PANX1 channels and provide new insights about channel activation.
Mechanical metamaterial sensors: from design to applications
Authors: de Souza Oliveira Hugo , Saeedzadeh Khaanghah Niloofar , Elli Giulia , Petti Luisa , Cantarella Giuseppe , Milana Edoardo , Münzenrieder Niko
Published: January 2025

The integration of mechanical metamaterials with sensor technology has opened new frontiers in the design and application of advanced sensing systems due to their ability to impart unique mechanical properties that enhance sensor functionality. Mechanical metamaterials, with properties derived from their engineered structures rather than their material composition, offer unique advantages such as negative Poisson’s ratio, high strength-to-weight ratios, and programmable behaviors. This review explores the dual approaches of incorporating sensors with mechanical metamaterials: metamaterial-supported sensors, where metamaterials provide structural support and enhanced durability to traditional sensors, and metamaterial-integrated sensors, where the metamaterial itself serves as the sensing element. Incorporating metamaterials in sensor design can offer increased sensitivity and precision, enhanced structural integrity and durability, programmability and reconfigurability, as well as lightweight and compact design solutions. Key advancements in the field are presented, highlighting how metamaterials properties can enhance sensor performance in terms of sensitivity, precision, and operational versatility. The review covers the primary materials and fabrication techniques used, including additive manufacturing, molding, and physical vapor deposition, and discusses the challenges associated with the mechanical integration of metamaterials and sensors. Practical applications in pressure, strain, temperature, and biomedical sensing are examined, demonstrating the transformative potential of mechanical metamaterials in creating high-performance, multifunctional sensor systems. The discussion concludes with an outlook on future research directions and potential advancements in the field.
Field emission study on atomically heterogeneous micro-metallic emitters produced by ion beam from inert gas plasmas
Authors: Majumdar Jayashree , Bhattacharjee Sudeep
Published: January 2025

High doses of irradiation in extreme environments, such as space or fusion reactors, cause significant substrate modifications, requiring systematic experimental data to understand the underlying processes. This study explores the effects of ion irradiation on aluminum and titanium sheets used in spacecraft, with fluence levels ranging from 3.8 to 3.9 × 1018 cm−2, employing 2 keV ions of argon and krypton generated by 2.45 GHz microwave plasma to investigate surface modifications and atomic heterogeneity induced by ion implantation, while minimizing complications from chemical bond formation. This experimental investigation is further extended to understand the impact of implanted ions and surface modifications on electron emission properties in high electric fields. Notable field emission improvements are observed: for krypton irradiated aluminum, turn-on potential is 2.3 ± 0.6 kV, a maximum current is 3.4 ± 0.3 nA, and enhancement factor is 1059, with krypton incorporation at 76.9

%

; for argon irradiated titanium, turn-on potential is 1.6 ± 0.2 kV, a maximum current is 9.8 ± 0.8 nA, and enhancement factor is 2540, with argon content at 88.5

%

. This study thus systematically discusses the discernible variations in field emission properties with the morphological changes, ion implantation percentages, and local work function measurements, providing valuable insights into the effects of inert gas ion irradiation on metallic substrates.
Solvent-modulated preparation of lead-free Cs3Bi2I9 polycrystalline film for high-performance photodetectors
Authors: Song Yaoyao , Zhang Huiyin , Liu Mengfan , Wan Yubo , Sun Hao , Cao Yang
Published: January 2025

Lead-free cesium bismuth iodide (Cs3Bi2I9) perovskite exhibits extraordinary optoelectronic properties and attractive potential in various optoelectronic devices, especially the application for photodetectors (PDs). However, most Cs3Bi2I9 PDs demonstrated poor detection performance due to the difficulty in obtaining high-quality polycrystalline films. Therefore, it makes sense to modulate the preparation of high-quality Cs3Bi2I9 polycrystalline films and expand its applications. Here, a solvent-modulated method combining anti-solvent and precursor engineering has been developed to regulate the crystallization dynamics of Cs3Bi2I9. Anti-solvent treatment is to suppress the asynchronous separation out of CsI and BiI3 due to significant differences in solubility, promoting uniform nucleation and limiting flake-like growth. Precursor engineering is synchronously used to modulate the subsequent nucleation growth dynamics. Due to the synergistic modulation, smooth and compact Cs3Bi2I9 polycrystalline films with distinct grains and grain boundaries can be easily obtained. The as-prepared PD exhibits an excellent on/off ratio of 4.26 × 105 as well as the detectivity up to 6.49 × 1010 Jones at zero bias. And, the Cs3Bi2I9 PD indicates excellent device stability, maintaining about 70% of the original performance after being stored for 400 h in the air without encapsulation.
Optimizing TMS dosimetry: evaluating the effective electric field as a novel metric
Authors: Colella Micol , Liberti Micaela , Carducci Filippo , Leodori Giorgio , Russo Giacomo Maria , Apollonio Francesca , Paffi Alessandra
Published: January 2025

Objective. This study introduces the effective electric field (E
eff) as a novel observable for transcranial magnetic stimulation (TMS) numerical dosimetry. E
eff represents the electric field component aligned with the local orientation of cortical and white matter (WM) neuronal elements. To assess the utility of E
eff as a predictive measure for TMS outcomes, we evaluated its correlation with TMS induced muscle responses and compared it against conventional observables, including the electric (E-)field magnitude, and its components normal and tangential to the cortical surface. Approach. Using a custom-made software for TMS dosimetry, the E
eff is calculated combining TMS dosimetric results from an anisotropic head model with tractography data of gray and white matter (GM and WM). To test the hypothesis that E
eff has a stronger correlation with muscle response, a proof-of-concept experiment was conducted. Seven TMS sessions, with different coil rotations, targeted the primary motor area of a healthy subject. Motor evoked potentials (MEPs) were recorded from the first dorsal interosseous muscle. Main results. The E
eff trend for the seven TMS coil rotations closely matched the measured MEP response, displaying an ascending pattern that peaked and then symmetrically declined. In contrast, the E-field magnitude and its components tangential (E
tan) and normal (E
norm) to the cortical surface were less responsive to coil orientation changes. E
eff showed a strong correlation with MEPs (r = 0.8), while the other observables had a weaker correlation (0.5 for E
norm and below 0.2 for E-field magnitude and E
tan). Significance. This study is the first to evaluate E
eff, a novel component of the TMS induced E-field. Derived using tractography data from both white and GM, E
eff inherently captures axonal organization and local orientation. By demonstrating its correlation with MEPs, this work introduces E
eff as a promising observable for future TMS dosimetric studies, with the potential to improve the precision of TMS applications.
A two-branch framework for blood pressure estimation using photoplethysmography signals with deep learning and clinical prior physiological knowledge
Authors: Qiao Minghong , Chang Li , Zhou Zili , Jun Sam Cheng , He Ling , Zhang Jing
Published: January 2025

Objective. This paper presents a novel dual-branch framework for estimating blood pressure (BP) using photoplethysmography (PPG) signals. The method combines deep learning with clinical prior knowledge and models different time periods (morning, afternoon, and evening) to achieve precise, cuffless BP estimation. Approach. Preprocessed single-channel PPG signals are input into two feature extraction branches. The first branch converts PPG dimensions to 2D and uses pre-trained Mobile Vision Transformer-v2 (MobileViTv2) and Visual Geometry Group19 (Vgg19) backbones to extract deep PPG features based on the different mechanisms of systolic blood pressure (SBP) and diastolic blood pressure (DBP) formation. The second branch calculates multi-dimensional feature parameters based on the relationship between PPG waveforms and factors affecting BP. We fuse the features from both branches and consider diurnal BP variations, using AutoML strategy to construct specific SBP and DBP estimation models for the different periods. The algorithm was developed on the human resting state PPG and BP dataset (HRSD) and validated on the MIMIC-IV dataset for generalization performance. Main results. The mean absolute error (MAE) for BP estimation is 6.42 mmHg SBP and 4.96 mmHg DBP in the morning, 4.84 mmHg (SBP) and 3.73 mmHg (DBP) in the afternoon, and 2.65 mmHg (SBP) and 2.56 mmHg (DBP) in the evening. Performance on the MIMIC-IV database was 4.34 mmHg (SBP) and 3.11 mmHg (DBP). The method meets the standards of the Association for the Advancement of Medical Instrumentation and achieves Grade A of the British Hypertension Society (BHS) standards. Significance. This indicates that it is an accurate and reliable non-invasive BP monitoring technology, applicable for continuous health monitoring and cardiovascular disease prevention.
Optical interferometry of high-energy nanosecond pin-to-pin discharges in atmospheric air
Authors: Babusis Nicholas , Jeong Won Joon , Shashurin Alexey
Published: January 2025

This paper describes the construction and application of an optical-frequency Michelson interferometer for measuring electron number density within high-energy, high-power nanosecond pin-to-pin discharges (>10 mJ pulse energy, >1 MW pulse power). A 21 mJ, 11 ns spark across a 3 mm pin-to-pin electrode gap was analyzed at 7 ns into the discharge to demonstrate the operation of the interferometer. A peak electron density of 2.3 × 1017 cm−3 was observed at these conditions, and it was consistent with estimates of plasma channel resistance based on V–I measurements. This initial work paves the way for a larger parametric study of the spatial and temporal dynamics of electron number density in nanosecond pin-do-pin discharges under various conditions.
Investigation of plasma decay in BP-HiPIMS discharges
Authors: Luo Yang , Han Mingyue , Wu Yiyan , Gao Pu , Li Liuhe
Published: January 2025

Investigation of the plasma decay mechanism from energy and density temporal/spatial evolutions together is important and urgent in the novel bipolar-pulse high power impulse magnetron sputtering (BP-HiPIMS) discharge for adjusting the deposited ion energy flux. In this work, temporal and spatial characteristics of the electron energy distribution function (EEDF) have been systematically investigated using a time-resolved (250 ns) Langmuir probe to obtain the plasma decay process clearly. The plasma decay has a typical characteristic of three-step during the positive pulse. At the initial period of positive pulse (Step 1), the existence of hot electrons and potential gradient force can accelerate the plasma density decay even up to ∼1015 m−3
μs−1. As the electron energy are cooled to several eVs, the plasma decay is dominated by the density gradient pressure with an ion sound velocity (0.5–0.7 kms−1), which can increase the downstream electron density (Step 2). As the redistribution of plasma density in the whole discharge domain, the electron density decay is exponential (Step 3) and the maximum decay rate is near the target due to the higher density gradient, while the maximum electron temperature is away from the target. Along the density gradient diffusion, the relation between electron density and temperature in BP-HiPIMS satisfies the well-known Boltzmann relation n
e = n
0exp(eV
p/kT
e). In addition, the EEDF characteristics in the BP-HiPIMS operated with an auxiliary anode and solenoid coil have also been investigated in this work, where an increase in electron density and plasma diffusion mobility has been observed after applying the anode or solenoid coil. These temporal and spatial EEDFs allow us to understand the complex plasma physics in the emerged BP-HiPIMS discharge clearly, especially with the view of high-energy and low-energy electron loss and balance.
The elastic frontier: dielectric elastomer actuators in healthcare technology
Authors: Benouhiba Amine , Holzer Simon , Konstantinidi Stefania , Civet Yoan , Perriard Yves
Published: January 2025

This review presents a detailed survey of Dielectric Elastomer Actuators (DEAs) and their emerging role in medical applications. DEAs are distinguished by their flexibility, low weight, and excellent biocompatibility, making them well-suited for a wide range of medical devices. The review explores the fundamental electro-mechanical principles behind DEA operation, which enable their remarkable ability to replicate natural muscle movements. Key applications discussed include biomedical devices, rehabilitation systems, in-vivo implants, and wearable health monitors, where DEAs offer dynamic, lifelike movements and precise control. Their ability to provide highly flexible and responsive actuation is a major advantage in medical technologies. However, challenges persist, particularly in terms of material durability, the need for high-voltage activation, and the integration of DEAs with existing medical technologies. By synthesizing recent research and highlighting ongoing hurdles, this review emphasizes the transformative potential of DEAs, offering a comprehensive look at their current state and future impact on next-generation medical devices.
Unveiling hidden geometric phase of neutron spin rotation in the Bitter–Dubbers experiment
Authors: Cheng Jian-Jian , Zhang Lin
Published: January 2025

We propose a novel framework to describe geometric phases in quantum systems under non-adiabatic conditions by introducing the concept of a hidden geometric phase. Conventional geometric phases, such as the Berry phase, rely on adiabatic evolution, limiting their applicability in rapidly changing systems. Here, we remove this constraint by reinterpreting the geometric phase as arising from a dynamically evolving reference basis, independent of the external topological features. The hidden phase is revealed through transitionless quantum control techniques, ensuring pure geometric phase accumulation even in non-adiabatic regimes. Our method offers an exact solution to the neutron spin rotation phase in the Bitter–Dubbers experiment, aligning more closely with experimental data without depending on adiabatic approximations. This unexpected result broadens our understanding of the geometric phase observed in neutron spin rotation beyond the adiabatic conditions that are conventionally required.