Recent discoveries, for example by JWST and DESI, have elevated the level of tension with inflationary Λ cold dark matter (ΛCDM). For example, the empirical evidence now suggests that the standard model violates at least one of the energy conditions from general relativity, which were designed to ensure that systems have positive energy, attractive gravity, and non-superluminal energy flows. We used a recently compiled Type Ia supernova sample to examine whether ΛCDM violates the energy conditions in the local Universe, and carried out model selection with its principal competitor, the R_ h =ct universe. We derived model-independent constraints on the distance modulus based on the energy conditions and compared them with the Hubble diagram predicted by both ΛCDM and R_ ̊m h =ct, using the Pantheon+ Type Ia supernova catalogue. We find that ΛCDM violates the strong energy condition over the redshift range z ⊂ (0, 2), whereas R_ ̊m h =ct satisfies all four energy constraints. At the same time, R_ h =ct is favoured by these data over ΛCDM with a likelihood of ∼ 89.5% versus ∼ 10.5%. The R_ h =ct model without inflation is strongly favoured by the Type Ia supernova data over the current standard model, while simultaneously adhering to the general relativistic energy conditions at both high and low redshifts.

Abstract The accelerated shift to green transportation demands new ideas to perform effective management of charging systems for electric vehicles (EVs). This paper explores the approaches of digital twins (DTs) to manage smart charging powered by renewable energy along with grid supply integration to EV fleets. DTs create a virtual environment that enables energy flow, charging times, and grid connections by modelling various parameters of charging stations. The DT also supports forecasting techniques, enhanced usage of renewable energy, and battery storage handling to improve performance and reduce operational costs to promote environmental friendliness. The work also gives important insights into the necessity of DTs in smart charging, related operational constraints, and the relevance of DTs in community-based sustainable development. This paper similarly emphasizes the crucial role of DTs in improving the management and control of EV fleets, resulting in greater independence and shorter payback periods while establishing the foundation for future and scalable applications. DTs offer ample opportunities in this domain, and this research aims to open new avenues to enable future developments that aim to expand the DTs’ functionality for wider energy applications by refining optimization tools with greater energy efficiency. This work comprehensively highlights the potential of DTs and their crucial role in promoting future transportation along with a few limitations like data latency and cybersecurity-related issues to enable seamless integration of EVs with the virtual counterparts.

The Chesapeake Bay, one of the largest estuaries in the United States, is an ecological system of great complexity and relevance. The food web is composed of thirty-six trophic components, all of which are functionally connected. In this work, the interactions among these components are numerically analyzed using complex network methods. An energy flow cutoff paradigm is applied to a weighted ecological network. The results reveal patterns characteristic of connectivity dynamics, evidencing both the initial robustness of the system and its tendency to fragmentation at higher values of the cutoff. From an applied perspective, the findings underscore the importance of conservation strategies that protect keystone species, such as carnivorous fish, which act as crucial connectors between the two main subnetworks. Although they are positioned at the top of the food web and are often assumed to be less critical to network stability, these species play a pivotal role in regulating populations of lower-level organisms, thereby maintaining the overall integrity of the ecosystem.

Microbial decomposers play a crucial role in detritus-based freshwater food webs, yet their disruption by antimicrobial contaminants and the subsequent bottom-up effects on aquatic food webs remain poorly understood. This study investigates how the fungicide Azoxystrobin and the antibiotic Ciprofloxacin affect microbial leaf conditioning, indirectly impact macroinvertebrate community structure, and thus cause shifts of functional feeding groups in stream mesocosms. To this end, black alder leaves were conditioned in the presence of increasing concentrations of either Azoxystrobin or Ciprofloxacin. Subsequently, the conditioned leaves were transferred to stream mesocosms, colonized by macroinvertebrate communities from a least-impacted stream, where such leaves served as the primary food source. Azoxystrobin significantly reduced fungal biomass on leaves by up to 80%, likely leading to lower detritus quality, impaired conditioning, and cascading shifts in macroinvertebrate communities (p = 0.04). Gammarus fossarum as a dominant species in the studied mesocosm, increased in abundance contributing 18% to community dissimilarity with increasing Azoxystrobin-treated leaves most likely through dietary flexibility and compensatory feeding of leaves or other sources. Chironomidae (Orthocladiinae, Chironomini, Tanytarsini), in contrast, declined (24% dissimilarity contribution), likely due to their reliance on well-conditioned detritus. Shredders (29%), predators (18%), and scrapers (14%) contributed most to macroinvertebrate community differentiation, indicating trophic propagation beyond primary consumers, that is, shredders. In contrast to the fungicide, the antibiotic Ciprofloxacin did not induce significant changes, suggesting fungal decomposers are the primary driver of detritivore-mediated energy flow. These findings emphasize the critical role of microbial-mediated leaf decomposition in structuring freshwater food webs and highlight potential ecological risks associated with fungicide contamination at microbial level, but with impacts well exceeding the microbial communities.

Transcriptomic insights into dynamically optimized batch feeding strategies for carbon fixation mechanisms in CO2 absorption-microalgae conversion system.

Unveiling the hidden impacts: A comprehensive review of microplastic effects on marine bivalves.

Biogeography and diversity of wetland soils bacterial communities across temperature zones based on independent studies.

This technical report documents a photovoltaic (PV) installation with self-consumption and surplus injection installed in Spain, which was designed for residential consumption and started up in an isolated single-family home with connection to the electricity distribution grid. Photovoltaic solar panels, inverter, lithium-ion batteries and a bidirectional meter have been integrated by this system. The report details the system’s technical requirements, energy flow, electrical calculations, economic analysis and compliance with Spanish regulations. Key words. Solar, battery, two-way, metering, self-consumption.

Lena-TRNN: Exploring energy flow for time series prediction.

Decarbonization Planning Based on Energy Flow Analysis: Supporting Energy Transition

Effects of eight-week backward walking training on mechanical energy flow pattern and Achilles tendon properties in older adults with dynapenia: An exploratory study.

Smart Grids (SGs) can be regarded as logistical networks that coordinate the transport and distribution of energy across interconnected systems. They manage the flow of energy between production and consumption points while integrating operational flexibility and reliability requirements. Despite these capabilities, SGs remain exposed to disruptions that may propagate through the network and affect both primary and substitution supply chains. This study examines how such disruptions spread by using the Independent Cascade Model (ICM) and how degradation mechanisms influence system performance through the Cox proportional hazards model. The proposed framework evaluates the resulting impacts on energy logistics and identifies conditions under which substitution channels can mitigate performance losses. The findings provide insights into the propagation of disruptions and offer a structured basis for assessing resilience-oriented operational strategies in Smart Grids.

Chemistry has evolved from empirical pattern recognition to a unified, physics-informed science governed by universal principles. This perspective traces the conceptual progression of chemical thought from Mendeleev’s periodic classification to thermodynamics, quantum mechanics and the emerging systems view of self-organisation and complexity. By dividing this trajectory into four historical phases viz. (i) thermodynamic and kinetic universality, (ii) nonideal solution theory and ionic interactions, (iii) quantum-mechanical interpretation of matter and bonding, and (iv) self-organisation in far-from-equilibrium systems. Each phase contributed to a deeper understanding of matter-energy relationships and strengthened the theoretical foundations of chemistry. Emphasis is placed on the interplay between the macroscopic laws and microscopic models, with recurring themes of order, symmetry and energy flow serving as unifying principles across both equilibrium and non-equilibrium phenomena. This conceptual synthesis illustrates the natural convergence of thermodynamics, statistical mechanics, and quantum theory, giving rise to systems chemistry and the modern study of emergent behaviour. Beyond its historical narrative, the work asserts that an analysis of chemistry through its evolving paradigms reveals a coherent scientific continuum integrating atomic theory, information and complexity, thereby positioning chemistry as a central discipline for elucidating organisational principles in natural systems.

Topological matter offers opportunities for control of charge and energy flow with implications for chemistry still incompletely understood. In this work, we study an ensemble of adsorbates with an empty frontier level (LUMO) coupled to the edges, domain walls (solitons), and bulk of a Su-Schrieffer-Heeger polyacetylene chain across its trivial insulator, metallic, and topological insulator phases. We find that two experimentally relevant observables, charge donation into the LUMO and the magnitude of adsorbate electronic friction, are significantly impacted by the electronic phase of the SSH chain and show clear signatures of the topological phase transition. Localized, symmetry-protected midgap states at edges and solitons strongly enhance electron donation relative to both the metallic and trivial phases, whereas, by contrast, the metal's extended states, despite larger total DOS near the Fermi energy, hybridize more weakly with a molecular adsorbate near a particular site. Electronic friction is largest in the metal, strongly suppressed in gapped regions, and intermediate at topological edges, where hybridization splits the midgap resonance. These trends persist with disorder, highlighting their robustness, and suggest engineering domain walls and topological boundaries as pathways for employing topological matter in molecular catalysis and sensing.

2D optical vortices and a reverse energy flow occurs near the intensity zeros

While dephasing noise often hinders quantum devices, it can become an asset for quantum thermal machines. Here we demonstrate a three-level thermal machine that leverages noise-assisted quantum transport to enable steady-state cooling of microwave modes. The device exploits symmetry-selective couplings between a superconducting artificial molecule and two physical heat baths. Each bath consists of a microwave waveguide populated with synthesized quasithermal radiation. Energy transport is enabled by injecting dephasing noise through a third channel longitudinally coupled to one artificial atom of the molecule. By varying the effective temperatures of the reservoirs and measuring photonic heat currents with sub-attowatt resolution, we demonstrate energy flow dynamics characteristic of a quantum heat engine, thermal accelerator, and refrigerator. Our work constitutes an experimental demonstration of the key operating principles of a noise-assisted three-level quantum refrigerator and opens new avenues for experiments in quantum thermodynamics using superconducting circuits coupled to physical heat baths.

ABSTRACT Connectivity is a multifaceted concept that has important implications for the management and conservation of marine and freshwater fishes. We developed a conceptual framework that encompasses multiple, interrelated categories of connectedness, including landscape (e.g., structural, functional) connectivity and ecological (e.g., trophic, genetic, demographic) connectivity, that together shape the flow of organisms, energy and information across ecosystems. We also synthesised six key methods that can be used to study connectivity of fishes: (1) telemetry, including satellite, acoustic, radio and passive integrated transponders (PIT), (2) mark‐recapture, (3) environmental tracers, including stable isotopes and otolith‐microchemistry, (4) genetics, (5) community structure analysis and (6) emerging technologies and tools (e.g., remote sensing and artificial intelligence). For each method, we describe the categories of connectivity it can assess and provide real‐world examples where they have been effectively used. We also identify limitations of each method. This article highlights the diverse and evolving toolbox of methods used to assess fish connectivity, underscoring the need for continued collaboration, innovation and integration of new approaches to refine our understanding and address remaining challenges in this critical area of aquatic ecology and fisheries management.

This contribution presents two experimental projects developed in the field of human-machine interaction (HMI), aimed at exploring how design-driven practices can act as catalysts for defining new paradigms of relationships between people, technological systems, information, and technical operations. Through transversal methodologies, the experimentation generated significant outcomes, leading to the redefinition of roles, tools, and initial objectives. AI is reinterpreted as a formative and cognitive resource, rather than a process optimization technology. The interface emerges as a collaborative, dialogic space, according to the implementation of hybrid feedback models and adaptable communication architectures. The active participation of users enables distributed forms of agency, contributing to the development of visual tools, prototypes, and simulation environments. Special attention is also given to the design of situated data visualizations, aiming to represent energy flows within automation systems in a legible and contextual way. The development of a tool for rapid prototyping of AI-based interactions further extended the design capability to non-technical profiles. The article highlights how design, beyond mediating between humans and machines, can activate strategic reorientation processes, generating innovation through the divergence between initial expectations and emergent results.

This issue of Smart and Green Materials Journal brings together a diverse yet coherent collection of studies that collectively advance sustainable materials and structural hydraulic performance for resilient infrastructure systems. The contributions span material innovation, performance optimization, and experimental validation across concrete technology, pavement engineering, masonry materials, timber structures, and open-channel hydraulics. Several articles address the sustainability and performance of cement-based systems through improved curing strategies, internal curing using super-absorbent polymers, optimized sand grading, and the incorporation of natural fibers as eco-friendly reinforcements. Complementing these efforts, the mechanical characterization of indigenous timber species and the reuse of reclaimed asphalt pavement as recycled aggregates highlight the role of locally sourced and recycled materials in reducing environmental burdens while maintaining structural reliability. Extending beyond material behavior, this issue also includes an experimental investigation into hydraulic jumps over rough and sloped beds, emphasizing the importance of boundary conditions in energy dissipation and flow stability. Together, these studies demonstrate how sustainable material choices and performance-oriented design can be synergistically applied to develop infrastructure systems that are both environmentally responsible and resilient to increasing operational demands.

This study aims to identify shrub insect species around the Bodogol Nature Conservation Education Center (PPKA Bodogol), Bogor, West Java. The research uses an exploratory descriptive approach by sampling through the free roaming method on shrub vegetation. Specimens were collected using sweeping net and hand collecting techniques from morning to noon, then analyzed descriptively based on the number of individuals, the number of species, and the composition of the order and family. The results of the study recorded 20 species from 8 orders, with the dominance of Orthoptera (7 species) and Lepidoptera (4 species). The families Acrididae and Scarabaeidae are the most abundant taxons, while Xylotrupes gideon is the species with the highest number of individuals. The dominance of these families and species indicates that the vegetation of the PPKA Bodogol bush provides habitat conditions that support herbivorous and detritivore insects that play an important role in energy flow and ecosystem stability. These findings show that shrub vegetation has a strategic role as a functional habitat for insects and can be used as basic data in planning, management, and conservation of insect biodiversity in conservation areas.