Browse Articles

A physics-informed neural network approach to eco-epidemiological dynamics in planktonic food webs

Mechanical Metamaterials with Reprogrammable Sequential Deformation for Analog‐to‐Digital Encoding and Computing

ABSTRACT The integration of computational logic into mechanical metamaterials enables the development of matter with intelligence that can sense and respond to environmental stimuli. While recent advances have demonstrated diverse mechanical logic systems, a challenge is bridging the gap between continuous physical inputs and discrete digital outputs. In this study, we propose a mechanical metamaterial capable of nearly arbitrary digital encoding and computing of continuous stimuli through reprogrammable sequential deformation. The metamaterial is built upon an engineered multistable architecture that supports a series of snap‐through events under uniaxial compression. Using an inverse design strategy, the deformation sequence can be tuned across a broad design space by tailoring the stiffness distribution of constituent units. Selective activation or deactivation of specific units in the metamaterial enables in situ reprogramming of the sequence without the need for remanufacturing. Experiments demonstrate that the inverse design and reprogramming allow a single material system to perform mechanical analog‐to‐digital conversion, signal processing, and field‐programmable gate array (FPGA)‐like logic operations. These capabilities open a new way for material‐based computing, showing a promising route toward intelligent mechanical metamaterials.

A fixed-time fault-tolerant tracking control for fractional-order UAV networks using adaptive fuzzy neural and event-triggered mechanisms

Abstract This paper investigates coordinated tracking control for fractional-order fixed-wing unmanned aerial vehicle (UAV) networks subject to actuator faults, input saturation, unknown nonlinear dynamics, external disturbances, and communication constraints. A dynamic memory event-triggered fixed-time fault-tolerant control framework is developed to improve tracking accuracy, fault accommodation, and communication efficiency. First, a fractional-order coordinated tracking model is formulated for networked fixed-wing UAVs. Then, an adaptive fuzzy neural network is used to approximate unknown nonlinear terms without requiring exact model information. To reduce unnecessary information exchange, a dynamic memory event-triggered mechanism is introduced by incorporating both the current triggering error and stored memory information. Moreover, a fault-tolerant compensation strategy is designed to handle actuator faults and saturation-induced nonlinearities. Based on fractional-order Lyapunov analysis and practical fixed-time stability theory, sufficient conditions are derived to guarantee that the tracking errors converge to a bounded neighborhood within a settling time independent of the initial conditions. Simulation results for networked fixed-wing UAVs verify the effectiveness, robustness, and communication-saving performance of the proposed control method.

Hydrophobic MFI‐Type Zeolites via Alkali‐Cation‐Induced Defect Healing: Implications for Adsorbent and Catalyst Design

ABSTRACT Here, we demonstrate that sub‐stoichiometric amounts of alkali cations (Na + and K + ) critically govern defect formation during the synthesis of Silicalite‐1 (MFI), enabling precise control over framework integrity and surface properties after calcination. Combining systematic synthesis studies with density functional theory (DFT) calculations and high‐resolution microscopy, we reveal a defect‐healing mechanism in which in situ generated NaOH or KOH species promote Si–O–Si bond rearrangement and enhance the mobility of Si(OH) 4 units. This process facilitates the effective healing of T‐site vacancies, yielding highly ordered, defect‐free MFI frameworks. The resulting Silicalite‐1 exhibits markedly enhanced hydrophobicity and superior selectivity in butanol/water separation, underscoring the decisive role of defect control in modulating adsorption and interfacial properties. Importantly, these insights are successfully extended to the synthesis of defect‐free TS‐1, affording highly hydrophobic Lewis acid catalysts with improved activity and selectivity in the epoxidation of 1‐hexene. This environmentally friendly, straightforward, scalable approach offers a versatile pathway to produce defect‐free zeolites with precisely tuned physicochemical properties, enabling the development of advanced catalytic and separation materials, especially for applications involving water or polar compounds.

The property rights index in forestry (PRIF): A new governance indicator with predictive capacity for forest status and dynamic across Europe

Abstract Understanding how forest governance shapes environmental outcomes is critical for sustainable land-use policies. Yet, existing governance indicators are often too broad to reflect sector-specific legal frameworks that govern natural resources. This study assessed the relevance of an existing governance index for forestry sector (Property Rights Index in Forestry - PRIF), correlating it with recognised governance metrics (e.g., rule of law, corruption perception, economic freedom) and forest status indicators (e.g., reforestation, afforestation, and deforestation rates). The PRIF was found to have strong associations with national governance quality, economic development, and forest dynamics, capturing both enabling and constraining aspects of owner freedom. Countries with higher PRIF scores tend to experience higher rates of both deforestation and reforestation, suggesting that increased owner autonomy drives more dynamic and potentially polarized forest outcomes. A Principal component analysis further reveals that PRIF aligns with major gradients in forest management intensity, ownership structure, and ecological change. These findings demonstrate that PRIF is a sensitive, interpretable, and scalable indicator for evaluating forest governance and its environmental implications. The index offers a valuable tool for policymakers seeking to balance property rights with sustainability goals across diverse institutional contexts.

A Hydro–Organo Biphasic Gel Electrolyte for Decoupled Interfacial Stability and Fast Ion Transport in Zinc Metal Batteries

ABSTRACT Organic and aqueous electrolytes offer complementary advantages in electrochemical stability and ion transport, but integrating both within a single electrolyte remains challenging. In this study, it is discovered that a distinct interphase can be spontaneously formed between the aqueous and organic phases through the synergy of amphiphilic monomers, Hofmeister effects, and phase partitioning. This aqueous–organic, mixed‐solvent region boosts ion transfer by smoothing solvation change across phases, resulting in an order‐of‐magnitude increase in overall conductivity over biphasic counterparts without such an interphase. Meanwhile, compartmentalized organo‐ and hydrogel domains decouple anodic and cathodic interfacial chemistries. Demonstrated in zinc metal batteries, this biphasic gel electrolyte thermodynamically stabilizes zinc metal anodes and inhibits parasitic ion crossover, while also enabling high‐rate operation comparable to aqueous systems. Accordingly, Zn||Zn symmetric cells demonstrate >3,600 h stable cycling at 5 mA cm −2 and 5 mAh cm −2 , and MnO 2 ||Zn full cells show high capacity retention after >3,000 cycles at 10 A g −1 . Overall, the findings establish organizing phase and solvation chemistry as a general materials design principle toward advanced electrolyte systems for high‐power, long‐duration electrochemical energy storage.

Bat communities of savanna biome in the Kruger National Park, South Africa

Enhanced K ⁺ Currents Contribute to Saltatory Conduction Impairment in Mechanically Demyelinated Aα-Fibers of Rats

Saltatory conduction of action potentials (APs) through nodes of Ranvier (NRs) is essential for the rapid and precise conduction of neuronal signals along heavily myelinated axons. However, in demyelinating diseases, saltatory conduction becomes impaired, leading to sensory and motor dysfunctions. At NRs of normal heavily myelinated nerves, APs are depolarized by voltage-gated Na + channels and repolarized mainly by K + currents flowing through two-pore-domain K + channels (K2P). Interestingly, although voltage-gated K + channels are present at and around NRs, they exhibit only limited activity and contribute minimally to nodal excitability and AP repolarization under physiological conditions. Here, we show that voltage-activated K + currents are significantly increased at NRs of motor Aα-fibers in the ventral roots of male and female rat lumbar spinal nerves following mechanical compression to induce acute demyelination. The increase in K + currents is associated with profound changes in intrinsic electrophysiological properties that reflect hypoexcitability at NRs and impairments of saltatory conduction. Voltage-gated K + channel blockers significantly reduce K + currents, restore excitability, and improve saltatory conduction at NRs of demyelinated Aα-fibers. Pharmacological profiling identifies Kv1.1 and Kv1.2 as the predominant voltage-gated K + channel subtypes contributing to the functional abnormality at NRs of demyelinated Aα-fibers. Collectively, our findings uncover a mechanistic link between abnormally enhanced K + currents via Kv1.1 and Kv1.2 channels and the impairment of saltatory conduction at NRs of demyelinated Aα-fibers, providing new insights into potential interventions for demyelinating disorders.

Programmable Functional Silicification of DNA Origami Nanostructures

ABSTRACT The silicification of DNA origami nanostructures offers a powerful strategy for enhancing their mechanical stability and resistance against detrimental environmental conditions. In the past years, several studies have investigated key aspects of the silicification process, resulting in a variety of established protocols. However, until now, the silica coating generally served as a passive protective layer or as the base for the further deposition of inorganic materials, but it did not carry any additional functionality itself. Here, we introduce two complementary, programmable approaches for the direct fabrication of functionalized silica coatings of DNA origami nanostructures. First, we synthesized a fluorescein‐bearing silica precursor which imparts fluorescence to the silica coating of both individual DNA origami nanostructures and crystals, enabling intracellular tracking of silica‐stabilized structures. Second, we employed a silica precursor containing a disulfide bridge to generate a redox responsive silica coating that degrades in a reducing environment. By introducing functionality at the precursor level, our approach establishes silicification as a modular platform for constructing responsive and traceable DNA‐based hybrid materials. These strategies expand the chemical scope of DNA nanotechnology and facilitate future applications in drug delivery and advanced materials science.

Electrophysiological, biochemical, and histopathological evidence of thymoquinone-mediated protection in cisplatin-induced cardiotoxicity

Different Learning Stabilization Processes between Wakefulness and Sleep

Visual perceptual learning (VPL) is initially fragile and must be stabilized after training to enable long-term retention. While sleep-dependent stabilization has been linked to changes in excitation/inhibition (E/I) balance, the neural mechanisms supporting stabilization during wakefulness remain unclear. Here, we investigated whether electrophysiological indices associated with sleep-based stabilization also characterize stabilization during posttraining wakefulness. Humans of both sexes completed visual training tasks with two competing training blocks separated by an awake rest period during which electroencephalography (EEG) was recorded. We conducted two studies targeting different stabilization states: one in which learning was vulnerable to retrograde interference and a control condition in which learning was largely stabilized through extended training and rest. Across studies, we estimated theta-band power and a criticality-based EEG index of E/I balance from posterior cortical sites. When stabilization was incomplete, elevated E/I balance during wakeful rest was associated with greater subsequent interference, whereas reduced E/I balance predicted stronger stabilization, paralleling findings previously reported during REM sleep. In contrast, when learning was fully stabilized, elevated E/I balance was associated with continued performance improvement rather than interference. Theta power showed a distinct, state-dependent pattern, predicting interference during wakefulness but not after stabilization. These findings indicate that wakeful stabilization of VPL shares a common inhibitory-dominant mechanism with REM sleep, while theta power is related to stabilization in different directions depending on whether the brain is wake or in REM sleep. Together, the results suggest that stabilization during wakefulness and REM sleep share partially common but not completely the same processing.

Engineering the Assembly Freedom of Donor–Acceptor Type Self‐Assembled Monolayers Toward Efficient and Stable Flexible Perovskite Photovoltaics

ABSTRACT Flexible perovskite solar cells (f‐PSCs) are promising contenders for portable and wearable photovoltaics, yet developing f‐PSCs that simultaneously achieve high power conversion efficiency (PCE) and superior operational stability, including mechanical robustness, remains challenging. Herein, we propose a strategy of modulating the assembly freedom of donor–acceptor type self‐assembled monolayers (SAMs) to address this issue. The newly designed 2FMPA‐BT‐PPA (PPA) SAMs exhibit higher assembly freedom on flexible ITO substrates compared to the previously reported 2FMPA‐BT‐BA (BA) SAMs, delivering two key benefits: first, they enable the formation of a higher‐quality monolayer via improved conformational adaptability and strengthened π–π stacking, which facilitates efficient carrier transport. Second, the SAMs’ conformational adaptability and uniformly tilted orientations can effectively dissipate interfacial strain under external mechanical loads, thereby enhancing the mechanical robustness of flexible devices. These synergies yield f‐PSCs with a champion PCE of 25.3% (26.3% for rigid device), alongside exceptional operational stability. Crucially, PPA‐based devices retain 98% initial PCE after 10 000 multidirectional bending cycles (3 mm radius) with no observable structural damage, outperforming BA‐based devices and all reported SAMs‐based f‐PSCs. This work offers donor‐acceptor SAMs design experiences for efficient, robust f‐PSCs, revealing assembly freedom's key role in interfacial carrier extraction and mechanical robustness.

BAASNet: boundary-aware deep learning for accurate polyp segmentation in colonoscopy

Abstract Colorectal polyps are primarily detected through colonoscopy, which plays a central role in early cancer prevention. Precise polyp segmentation supports treatment planning and diagnostic accuracy by providing masks that encode clinically relevant structures. Recent advancements in deep learning have led to several polyp segmentation models. However, performance remains hindered by challenges such as image noise, complex textures, indistinct boundaries, and diverse polyp morphologies. The high cost and time burden of manual annotation underscore the need for automated segmentation systems. To overcome these limitations, BAASNet, a Boundary-Aware Attention-Based Segmentation framework, is introduced for polyp segmentation. A boundary-aware loss function is integrated to improve performance, particularly in delineating polyp edges. The method is evaluated on nine publicly available datasets spanning five imaging modalities, including two center-wise polyp detection benchmarks, demonstrating strong generalization capability. On PolypDB, the model attains a mean Dice similarity coefficient (mDSC) of at least $$89.60\%$$ across all five modalities. Across all evaluated benchmarks, the proposed model achieves an average absolute improvement of approximately $$3.3\%$$ in Dice. Gains vary by dataset, ranging from approximately $$0.7\%$$ to $$4.7\%$$ relative improvement over the best previous results. These results demonstrate BAASNet’s potential for robust, real-time clinical deployment in automated colonoscopy workflows.

Machine‐Learning‐Guided Polarization‐Lattice Decoupling Enables Ultrahigh Energy Storage in Lead‐Free Dielectric Ceramics

ABSTRACT Achieving ultrahigh energy storage in lead‐free dielectric ceramics is fundamentally constrained by the intrinsic trade‐off between large polarization and high dielectric breakdown strength. Here, we establish an interpretable machine‐learning‐guided design framework that quantitatively links ionic descriptors with polarization behavior in ABO 3 ‐based dielectric matrices, enabling the rational identification of compositions with intrinsically high polarization potential. Guided by this strategy, a (Bi 0.275 Na 0.2255 K 0.0495 Ba 0.3 )(Ti 0.985 Hf 0.015 )O 3 ‐0.15(La 0.5 Sm 0.5 ) 2 Ti 2 O 7 (BNBT‐3) composition is discovered that exhibits an exceptional maximum polarization of 50.19 µC cm −2 . When processed via a viscous polymer process, the resulting BNBT‐3‐VPP capacitors achieve an ultrahigh breakdown strength of 1400 kV cm −1 and a recoverable energy density of 25.1 J cm −3 with high efficiency, placing them among the best‐performing lead‐free dielectric ceramics reported to date. Structural characterization combined with phase‐field simulations reveals that the outstanding performance originates from polarization‐lattice decoupling, where nanoscale polarization clusters and multiphase coexistence suppress long‐range ferroelectric order while enabling reversible polarization rotation. This work establishes a generalizable strategy that integrates interpretable machine learning with physically grounded materials design, providing a powerful route for discovering high‐performance dielectric energy storage materials.

Effect of mild hydrothermal modification on surface color, surface chemistry, UV-induced photodegradation and physico-mechanical performance of Pseudotsuga menziesii wood

Abstract Thermal modification at high temperatures improves the physical and surface properties of wood, but it often reduces its mechanical strength. This study examines mild hydrothermal treatment as an alternative method to enhance wood performance while limiting strength loss. Specimens of Pseudotsuga menziesii (Douglas fir) were treated with saturated steam at 140 ° C, 160 °C, and 180 °C for 0.5, 1, and 2 hours. The treated wood was analyzed for changes in colour, surface chemistry, dimensional stability, crystallinity index (CrI%), mechanical properties, and resistance to ultraviolet (UV) weathering. Mass loss increased from 0.86% to 19.61% with higher temperature and longer duration, indicating severe thermal degradation. Dimensional stability improved with treatment severity, reaching 33.39% at 180 °C for 2 hours. The crystallinity index also increased compared to the control, suggesting changes in cellulose structure. The wood became darker in color with increasing treatment intensity due to hemicellulose degradation, confirmed by FTIR analysis. Treated samples showed better resistance to UV-induced discoloration. In mechanical properties, surface hardness decreased by 7.41-68.81%, while bending modulus (MOE) and bending strength (MOR) declined by 8.36-61.76% and 5.26-81.84%, respectively, indicating reduced mechanical performance, particularly for samples modified at high temperature and for extended duration. Overall, mild hydrothermal treatment improved surface properties, dimensional stability, and UV resistance while causing less loss in strength compared to high-temperature treatments. This makes it a promising and sustainable method for enhancing wood performance.

Spatiotemporally Controlled Lysosomal Membrane Permeabilization Amplifies STING‐Driven Antitumor Immunity in Prostate Cancer

ABSTRACT Prostate cancer (PCa) remains a major clinical challenge due to therapeutic resistance and immunologically cold tumor microenvironment. Lysosomal membrane permeabilization (LMP)–induced lysosome‐dependent cell death offers an alternative route to eliminate resistant tumor cells and initiate immunogenic cell death, yet its efficacy is often limited by insufficient spatiotemporal control and immune activation. Here, we report a spatiotemporally programmable supramolecular nanoplatform (Cu‐P‐MSA) that integrates lysosome‐targeted sonodynamic therapy with tumor‐confined innate immune activation for PCa treatment. Cu‐P‐MSA is a modular self‐assembling peptide incorporating a PSMA‐targeting ligand, morpholine moiety, and cathepsin B–cleavable linker, enabling tumor‐selective uptake and in situ formation of fibrous sonosensitizer depots within lysosomes. Upon ultrasound irradiation, a glutathione‐responsive open‐shell sonosensitizer induces controlled LMP, simultaneously activating ferroptosis and pyroptosis and promoting immunogenic cell death. Meanwhile, tumor‐specific release of a STING agonist MSA‐2 elicits robust type I interferon responses, driving dendritic cell maturation and cytotoxic T‐cell infiltration. This coordinated lysosomal disruption–immune amplification strategy effectively reprograms the tumor immune microenvironment and suppresses both primary and distant tumors, with inhibition rates reaching 84.3% and 77.5%, respectively. Overall, this work establishes a spatiotemporally controlled supramolecular approach that integrates lysosomal disruption with innate immune activation to overcome therapeutic resistance and immunosuppression in PCa.

Therapeutic current estimation and leakage current safety of a cold air plasma jet on chronic wounds

Abstract Cold atmospheric air plasma jets (CAAPJs) are increasingly recognised for their efficacy in chronic wound treatment, with reactive oxygen and nitrogen species (RONS) traditionally cited as the primary therapeutic mechanism. However, their electromagnetic nature inevitably involves electrical interactions with wound tissue that have not yet been explicitly quantified. This work presents a quantitative framework distinguishing two coexisting electrical phenomena during CAAPJ treatment. First, the oscillating field at 30 kHz induces ionic currents in microscopic closed loops on the wound surface. Applying Ohm’s law with the measured electric field ( $$E \approx 10$$  V/mm) and wound exudate conductivity ( $$\sigma = 0.5$$  S/m), an induced current of 2–20 mA is obtained depending on exudate layer thickness, spanning and exceeding the therapeutic range of established Wound Healing Electrostimulation Devices (WHESDs). Second, the systemic patient leakage current — defined by IEC 60601-1 for Type B applied parts (limit: 100  $$\mu$$ A) — was measured under worst-case conditions using a brass target at zero resistance to earth, yielding values below 100 nA, more than three orders of magnitude below the normative limit. These results suggest that the long-standing RONS-versus-electric-field discussion in plasma medicine may be more productively framed as a question of complementary contributions: the therapeutic relevance of CAAPJs may lie in the co-delivery of both chemical and electrical mechanisms, while the device simultaneously guarantees full electrical safety. The two-current framework also provides a rigorous physical basis for the regulatory assessment of CAAPJ devices under IEC 60601-1.

Astrocyte TrkB.T1 Deficiency Disrupts Glutamatergic Synaptogenesis and Astrocyte–Synapse Interactions

Perisynaptic astrocyte processes (PAPs) contact pre- and postsynaptic elements to provide structural and functional support to synapses. Accumulating research demonstrates that the contact of synapses by PAPs is critical for synapse formation, stabilization, and plasticity. The specific signaling pathways that govern these astrocyte–synapse interactions, however, remain to be elucidated. Herein, we demonstrate the role of the astrocyte TrkB.T1 receptor, a truncated isoform of the canonical receptor for brain-derived neurotrophic factor (BDNF), in modulating astrocyte–synapse interactions and excitatory synapse development. Neuron–astrocyte coculture studies revealed that loss of astrocyte TrkB.T1 disrupts the formation of PAPs. To elucidate the role of TrkB.T1 in synapse development, we conditionally deleted TrkB.T1 in astrocytes in mice of either sex. Synaptosome preparations were employed to probe for TrkB.T1 localization at the PAP, and confocal three-dimensional microscopy revealed a significant reduction in synapse density and astrocyte–synapse interactions across development in the absence of astrocytic TrkB.T1. Furthermore, conditional knock-out of astrocyte TrkB.T1 alters motor learning and experience-dependent astrocyte–synapse interactions. These findings suggest that BDNF/TrkB.T1 signaling in astrocytes is critical for normal excitatory synapse formation in the cortex and that astrocyte TrkB.T1 serves a requisite role in astrocyte synapse interactions. Overall, this work provides new insights into the molecular mechanisms of astrocyte-mediated synaptogenesis.

Breaking the Permeability–Selectivity Trade‐Off With Irreversible‐Knot Rubbery Organic Frameworks

ABSTRACT The permeability–selectivity trade‐off fundamentally constrains polymeric membranes, rooted in the dichotomy between chain flexibility and precise molecular sieving. The emerging concept of rubbery organic frameworks (ROFs) aims to bridge this gap, yet its reliance on reversible covalent chemistry inherently compromises structural stability. Here, we introduce an irreversible‐chemistry paradigm by programming β ‐ketoenamine “irreversible knots” into flexible polydimethylsiloxane (PDMS) networks via enol–keto tautomerization. This approach synergistically co‐programs crosslinking density and chain rigidity, yielding a stabilized and optimized microstructure. The resulting membrane transcends the classic trade‐off, delivering a record‐high flux of 5.4 kg m −2 h −1 for ethanol/water separation—three times higher than conventional PDMS—while maintaining a separation factor of 9.2. The “rigidity‐programming” strategy demonstrates remarkable versatility, achieving top‐tier performance across diverse separations spanning representative organic/water and gas‐pair systems. Beyond performance, the membranes exhibit scalable fabrication, robust anti‐swelling stability, and long‐term operational durability, highlighting their practical potential for industrial deployment. This work establishes irreversible chemistry as a general paradigm for polymer network design, providing a robust platform to overcome traditional limitations from molecular separation to flexible functional materials.

Adaptive hybrid framework for low-latency DDoS defense in consumer-centric SDN architectures

Abstract Software-Defined Networking (SDN) increases networking flexibility, scalability, and programmability by separating the control plane from the data plane. Nevertheless, this structure is also vulnerable to DDoS, which may result in performance degradation and service unavailability. We propose a new adaptive hybrid real-time DDoS detection and mitigation framework designed for consumer applications with tight low latency constraints such as telemedicine, online gaming, and video streaming services. The suggested architectural model incorporates four well-known techniques (LSTM-based DeepPredict-DDoS, Reinforcement Learning-based Adaptive DeepPredict-DDoS, Genetic Algorithm-based DeepPredict-GA, and ARIMA-based DeepPredict-ARIMA) through an innovative decision-making engine. Experimental results show an average detection accuracy of 97.08%, reduced latency by 80%, and packet loss rate as low as 0.027%. These properties make the solution scalable, efficient, and effective for consumer-level SDN systems. Graphic Abstract