Browse Articles

Chaos controlled and disorder driven phase transitions induced by breaking permutation symmetry

Abstract The effects of disorder and chaos on quantum many-body systems can be superficially similar, yet their interplay has not been sufficiently explored. This work finds a continuous phase transition when disorder breaks permutation symmetry, with details of the transition being controlled by the degree of chaos in the clean limit. The system changes from an area law entangled phase in the permutation symmetric subspace where collective variables exist to volume law entanglement in the full Hilbert space, beyond a critical strength of the disorder. This has potential implications for general many body physics, as well as technologies such as transmon qubits.

Evaluation of large language models within GenAI in qualitative research

Experimental and numerical investigation of flow through gate valve

A hybrid MARL clustering framework for real time open pit mine truck scheduling

Measuring particle charges in high electric fields of gas insulation systems using tracking velocimetry

Abstract The electric charges of particles are a decisive factor influencing their behavior in electric fields, particularly in high-voltage gas insulation systems. The performance of the latter can be significantly undermined by charged particles, which potentially cause equipment failure in the energy transmission system. This study presents a novel in-situ charge measurement approach using particle tracking velocimetry based on high-speed imaging. For the first time, charge polarities, magnitudes, and distributions are quantified in high electric fields of gas insulations. Characterizing metallic and dielectric particles covering a broad property spectrum allows for identifying decisive charge accumulation parameters. The results show that some particle materials exhibit no detectable charge, while others dynamically acquire broad charge distributions. Among the most influential parameters are the particle material density, the adhesive force between the particles and electrodes, and the applied electric field strength. Particle properties such as the electrical conductivity and relative permittivity appear negligible indicating the surface conductivity to be decisive. The observed minimum charge magnitudes align well with theoretical force-based expectations. Maximum charges, however, are not predictable using such approaches resulting in significant underestimations. Additionally, it is shown that the charge depends on the direction of the particle motion in the electric field. These findings validate the suitability and necessity of the developed measurement approach, highlight statistical charge variability, and inform our understanding of how metallic and dielectric particle dynamics influence the performance of gas insulation systems.

Associations of serum glucose/potassium ratio with short-term and long-term mortality in sepsis patients: a retrospective cohort study based on the MIMIC-IV database

Clinical comparison of TURP, PVP and holep for small volume BPH

Fallopian tubes influences sperm selection and fertilization success

Correction: Biophysical mechanism of animal magnetoreception, orientation and navigation

A scalable, and tunable braided yarn for micro and macro physiological sensing

Comparative assessment of conventional and hermetic storage facilities on wheat grain quality, pest infestation, and bread development

Correction: Effect of visceral fat on onset of metabolic syndrome

Prescribed biomass burning effects on soil NO emissions in South Carolina

Bioinspired Anti‐Freezing Hydrogel With Localized Ice Regulation for Subzero Soft Robotics

AbstractFreezing hydrogels at subzero temperatures severely compromises mechanical flexibility, ionic conductivity, and structural integrity, thereby limiting their application in low‐temperature environments. Hydrogel freezing involves both ice nucleation and ice growth; however, simultaneously inhibiting these two processes remains a significant challenge. In nature, freeze‐tolerant organisms do not rely on completely preventing ice formation to survive freezing conditions. Instead, they utilize bacterial membrane‐anchored ice nucleating protein (BMIP) to promote ice nucleation and ice binding protein (IBP) to regulate ice growth, thereby achieving freeze protection through precise ice management. Inspired by this biological strategy of “selective nucleation of small ice crystals with restricted growth,” we developed anti‐freezing hydrogels by incorporating both BMIP and IBP. The anti‐freezing hydrogels exhibit enhanced mechanical and electrical performance at low temperatures, with a non‐freezing matrix stable down to −30°C and excellent structural integrity over multiple freeze‐thaw cycles. When employed as a functional component of a robotic hand designed for low‐temperature operation and integrated with machine learning algorithms, the anti‐freezing hydrogels enable precise recognition of object stiffness and size under ultra‐low temperature conditions. This bioinspired approach provides a promising strategy for the development of next‐generation anti‐freezing hydrogels capable of supporting stable human‐robot‐environment interactions in harsh, low‐temperature environments.

Trends in the homogenization of macromoth assemblages (2016–2023) in a Seoul City park

Thrombin induces degradation of murine intervertebral discs via angiogenesis and M1-like polarization of macrophages

A single-cell transcriptomic study of milk cells from dairy cows with divergent lactation performance

Predicting the outcome of transarterial chemoembolization combined with targeted immunotherapy for unresectable hepatocellular carcinoma based on MRI radiomics

Community mitigation decisions in elephant conflict zones of southern India depend on environmental and socio-economic drivers

Abstract Human–elephant conflict is a major threat to people and elephants across Asia and Africa. Understanding the factors influencing people’s decision to implement mitigation measures is crucial to devise better conflict mitigation measures. We surveyed 507 rural communities in elephant dominated landscapes, across four districts in southern India using snowball and opportunistic sampling. Fourteen covariates were analysed through a mixed-methods approach, using Classification and Regression Trees (CART) for quantitative analysis, and thematic analysis for qualitative insights. Three key drivers: rainfall, land ownership and proximity to water bodies shaped mitigation decisions. The CART revealed two distinct decision paths. In Path 1, households with lower rainfall and smaller landholdings had a 68% likelihood of adopting mitigation measures. In Path 2, households experiencing higher rainfall and bigger landholdings, closer to water bodies, had a 7% likelihood of adopting mitigation measures. Notably, trenches were linked to elephant injuries, while solar and electric fencing were associated with elephant deaths, indicating poor design and maintenance of these mitigation measures resulting in elephant casualties. Despite the conflict, communities expressed sadness over elephant casualties, reflecting strong cultural ties. Our findings underscore the necessity for proactive measures, including early warning systems, patrolling networks and regenerative agricultural practices to promote biodiversity. As global interest in conflict mitigation grows, integrating local knowledge is essential for community-based management in shared landscapes.

Predicting crop disease severity using real time weather variability through machine learning algorithms