Browse Articles

Author Correction: Immediate effect of ice and dry massage during rest breaks on recovery in MMA fighters: a randomized crossover clinical trial study

Engineering aptamer-directed phosphatase recruiting chimeras: a strategy for modulating receptor function and overcoming drug resistance

Structural optimization of different truss designs using two archive multi objective crystal structure optimization algorithm

Abstract Optimizing a multi-objective structure is a challenging design problem that requires handling several competing goals and constraints. Despite their success in resolving such issues, metaheuristics can be difficult to apply due to their stochastic nature and restrictions. This work proposes the multi-objective crystal structure optimizer (MOCRY), a potent and effective optimizer, to address this problem. The MOCRY algorithm, also known as MOCRY2arc, is built on a two-archive idea centered on diversity and convergence, respectively. The efficacy of MOCRY2arc in solving five typical planar and spatial real-world structure optimization issues was assessed. Because of these problems, safety and size limits were put on discrete cross-sectional regions and component stress. At the same time, different goals were being pursued, such as making nodal points bend more and reducing the mass of trusses. Four recognized standard evaluators—Hypervolume (HV), Generational-Inverted Generational Distance (GD, IGD), Spacing to Extent Metrics (STE), convergence, and diversity plots—were utilized to compare the results with those of nine sophisticated optimization techniques, including MOCRY and NSGA-II. Moreover, the Friedman rank test and comparison analysis showed that MOCRY2arc performed better at resolving big structure optimization issues in a shorter amount of computing time. In addition to identifying and realizing effective Pareto-optimal sets, the recommended method produced strong variety and convergence in the objective and choice spaces. As a result, MOCRY2arc may be a useful tool for handling challenging multi-objective structure optimization issues.

Temperate forests can deliver future wood demand and climate-change mitigation dependent on afforestation and circularity

Abstract Global wood demand is expected to rise but supply capacity is questioned due to limited forest resources. Additionally, the global warming potential (GWP) impact of increased wood supply and use is not well understood. We propose a framework combining forest carbon modelling and dynamic consequential life-cycle assessment to evaluate this impact. Applying it to generic temperate forest, we show that afforestation to double productive forest area combined with enhanced productivity can meet lower-bound wood demand projections from 2058. Temperate forestry value-chains can achieve cumulative GWP benefit of up to 265 Tg CO 2 -equivalent (CO 2 e) by 2100 per 100,000 ha of forest (if expanded to 200,000 ha through afforestation). Net GWP balance depends on which overseas forests supply domestic shortfalls, how wood is used, and the rate of industrial decarbonisation. Increased wood-use could aid climate-change mitigation, providing it is coupled with a long-term planting strategy, enhanced forest productivity and efficient wood use.

Punicalagin relieves hepatic injury by antioxidation and enhancement of autophagy in diet-induced nonalcoholic steatohepatitis

Dissociable encoding of evolving beliefs and momentary belief updates in distinct neural decision signals

Abstract Making accurate decisions in noisy environments requires integrating evidence over time. Studies of simple perceptual decisions in static environments have identified two human neurophysiological signals that evolve with similar integration dynamics, with one - the centroparietal positivity - appearing to compute the running integral and continuously feed it to the other - motor beta lateralisation. However, it remains unknown whether and how these signals serve more distinct functional roles in more complex scenarios. Here, we use a volatile expanded judgement task that dissociates raw sensory information, belief updates, and the evolving belief itself. We find that motor beta lateralisation traces the evolving belief across stimuli, while the centroparietal positivity locally encodes the belief updates associated with each individual stimulus. These results suggest a flexible computational hierarchy where context-dependent belief updates can be computed sample-by-sample at an intermediate processing level to modify downstream belief representations for protracted decisions about discrete stimuli.

A stretchable and biomimetic polyurethane membrane for lung alveolar in vitro modelling

Abstract The lung alveolus constitutes a morphologically and mechanistically complex tissue that is constantly subjected to cyclic tension and exhibits unique elastic properties. Available materials used to mimic alveolar tissue often lack biomimicry and the mechanical properties required for cyclic tension. Here, we report a fully synthetic fibrous polyurethane scaffold that approximates tissue stiffness, is elastic under breathing simulations and supports long-term culture of alveolar epithelial-like cells. Using electrospinning a fibrous membrane of tuneable thickness, set fibre diameter and small pore size is prepared. When subjected to cyclic uniaxial tension the material retains its elasticity at both low and high frequency mimicking human and mouse breathing. Thanks to the small pore size, lung alveolar cells can be cultured on its apical surface forming an epithelial monolayer. This monolayer can be maintained long term (at least 15 days) and in an air–liquid interface. In the latter conditions, cells differentiate and exhibit expression of surfactant protein A, a constituent of the surfactant layer that plays a key role in lung physiology. Owing to its lung-mimicking characteristics, the electrospun membrane holds the potential to be adapted for breathing lung models.

Electrically-driven phase transition actuators to power soft robot designs

Leucine rich repeat containing 15 promotes triple-negative breast cancer proliferation and invasion via the ITGB1/FAK/PI3K signalling pathway

Quantum reservoir probing of quantum phase transitions

Natural averaging may complement known biological constraints in sexual reproduction’s advantages over asexual in conserving species quantitative traits

Growth of continental crust and lithosphere subduction in the Hadean revealed by geochemistry and geodynamics

Design of multiple-stage hydraulic cylinder for structural safety and sealing analysis

Adaptive mechanisms of social and asocial learning in immersive collective foraging

Abstract Human cognition is distinguished by our ability to adapt to different environments and circumstances. Yet the mechanisms driving adaptive behavior have predominantly been studied in separate asocial and social contexts, with an integrated framework remaining elusive. Here, we use a collective foraging task in a virtual Minecraft environment to integrate these two fields, by leveraging automated transcriptions of visual field data combined with high-resolution spatial trajectories. Our behavioral analyses capture both the structure and temporal dynamics of social interactions, which are then directly tested using computational models sequentially predicting each foraging decision. These results reveal that adaptation mechanisms of both asocial foraging and selective social learning are driven by individual foraging success (rather than social factors). Furthermore, it is the degree of adaptivity—of both asocial and social learning—that best predicts individual performance. These findings not only integrate theories across asocial and social domains, but also provide key insights into the adaptability of human decision-making in complex and dynamic social landscapes.

Gene expression analyses on Dickeya solani strains of diverse virulence levels unveil important pathogenicity factors for this species

This is not the new colour that scientists have created

Emergent clusteroluminescence from nonemissive molecules

Abstract Once considered the exclusive property of conjugated molecules, efficient and visible-light luminescence from non-conjugated and nonemissive molecules in the clustered state, known as clusteroluminescence (CL), has attracted much attention recently due to its special photophysical behaviors and behind electronic interactions. This perspective discusses the development of the CL phenomenon, followed by the typical photophysical features, examples, mechanisms, and potential applications of CL materials, to provide a comprehensive picture of this emerging field. Starting with organic clusters, inorganic, metallic, and hybrid clusters with CL properties are also introduced, and the perspective shift from covalent interactions at the molecular level to non-covalent interactions at the aggregate level is invoked.

Spatial and temporal modeling of conflict related fatality and public health implications in Nigeria

Daily briefing: Bite marks on bones hint that Romans really did fight lions

Multimodal gradients unify local and global cortical organization

Abstract Functional specialization of brain areas and subregions, as well as their integration into large-scale networks, are key principles in neuroscience. Consolidating both local and global perspectives on cortical organization, however, remains challenging. Here, we present an approach to integrate inter- and intra-areal similarities of microstructure, structural connectivity, and functional interactions. Using high-field in-vivo 7 tesla (7 T) Magnetic Resonance Imaging (MRI) data and a probabilistic post-mortem atlas of cortical cytoarchitecture, we derive multimodal gradients that capture cortex-wide organization. Inter-areal similarities follow a canonical sensory-fugal gradient, linking cortical integration with functional diversity across tasks. However, intra-areal heterogeneity does not follow this pattern, with greater variability in association cortices. Findings are replicated in an independent 7 T dataset and a 100-subject 3 tesla (3 T) cohort. These results highlight a robust coupling between local arealization and global cortical motifs, advancing our understanding of how specialization and integration shape human brain function.