This is a study of some key properties of sustainable materials based on natural by-products (straw or hemp shives) and binders with zero CO2 emissions (natural clay or CO2-activated binders based on by-products), which can be used in the interiors of building structures in the form tiles and suspended ceilings to stabilize their thermal and moisture properties and to adjust the acoustic properties. It is specifically a study of the acoustic properties of these natural based ecological composites and a study of their reaction to fire. These properties are key, together with hygroaccumulation properties, for the use of these materials in the field of building structures. The aim of the work was to determine the dependence of the type and dosage of the binder on the resulting behavior of the composites from the point of view of fire, and then further reactions of the action of fire on organic particles during short-term exposure to a small flame. Furthermore, it is about the results of the study of acoustic properties, from the point of view of sound absorption, as well as on the adjustment/stabilization of the relative humidity or fluctuations in the production of water vapor in the room (e.g., different short-term occupancy of the spaces by people). The results of this study provide important insights for optimizing the use of ecological composites in construction applications.

The automotive industry is undergoing a significant transformation towards electric vehicles (EVs) with the main goal of reducing greenhouse gas emissions and for a sustainable and green environment. Different types of EVs are introduced every day in the market where selecting an optimal vehicle for purchase constitutes a complex decision-making. Therefore, the purpose of this research was to evaluate EVs in Albania using multi-criteria decision-making methods (MCDM). A total of 12 vehicles were analyzed based on 4 main criteria and 12 sub-criteria. The fuzzy Logarithm Methodology of Additive Weights (LMAW) method was applied to find the weights of the main criteria while the fuzzy Logarithmic Percentage Change-driven Objective Weighting (LOPCOW) method was applied to find the weights of the sub-criteria. For the EV ranking, the fuzzy Ranking of Alternatives with Weights of Criterion (RAWEC) method was applied. The findings showed that the most important criteria are the technical criteria and the Auto 11 vehicle showed the best results. The combination of Fuzzy LMAW-Fuzzy LOPCOW-Fuzzy RAWEC methods also constitutes the novelty of this research, which has not been applied before in this field. The contribution of this research consists in providing a comprehensive set of selection criteria to choose the best alternative of the EV fleet in Albania. Furthermore, the contribution of this research was the application of a hybrid methodology in the evaluation and selection of an electric vehicle as an ongoing choice faced by vehicle buyers.

Severe hypoglycemia increases the risk of cardiovascular disease (CVD) in people with diabetes. Large cohort studies and scientific statements show that severe hypoglycemia is linked to higher rates of coronary heart disease, cardiovascular events, and mortality in both type 1 and type 2 diabetes. This risk is especially high in individuals with significant vascular risk, such as older adults and those with multiple cardiovascular risk factors. Hypoglycemia triggers several pathophysiological changes that increase cardiovascular risk. These include activation of the sympathoadrenal system, promotion of proinflammatory and prothrombotic states, arrhythmogenic changes, and increased hemodynamic stress. Experimental evidence shows that recurrent hypoglycemia worsens microvascular dysfunction and promotes adverse cardiac remodeling, especially in people with diabetes. While the link between hypoglycemia and cardiovascular events is well established, the causality remains debated. Hypoglycemia may directly contribute to cardiovascular disease or indicate underlying vulnerability, especially in patients with advanced disease or comorbidities. Minimizing hypoglycemic episodes is recommended for all patients with diabetes, particularly those with established cardiovascular disease, due to the clear association with adverse outcomes.

Obesity is a global health challenge. According to the World Health Organization (WHO), between 1990 and 2022, adult obesity more than doubled. Weight management interventions (WMIs) support individuals in achieving and maintaining a healthy weight through dietary guidance, physical activity promotion and behavioural counselling. However, traditional WMIs often have limited accessibility. Digital WMIs or DWMIs are delivered via websites or smartphone applications and provide scalable and cost-effective alternatives. However, user needs for digital services and their prevalence in the existing commercial solutions remain underexplored. Hence, our study systematically identified 26 commercial DWMIs to identify their features, services, and data collection practices. Additionally, we performed a user needs analysis by recruiting 207 individuals involved in a real-life WMI. Our findings indicated that DWMIs integrated self-monitoring, goal setting, and behaviour change strategies, yet lack social support, virtual reality applications and adaptive personalisation. WMI clients prefer smartphone Apps and fitness trackers for tracking weight management progress and have varying levels of comfort in using digital resources. The presented results serve as recommendations for future directions in the design and implementation of services for DWMIs.

We address a practical variant of the triangle packing problem: reassembling triangles-originally derived from a Delaunay triangulation of a rectangle-after arbitrary translations and rotations, without overlap, to maximize the covered area. Since triangle packing is an NP-hard problem, we examine four lightweight heuristics that combine translation, rotation, and simple selection rules: (1) grid-guided adjacency, (2) decreasing-area edge joining, (3) random-order edge joining, and (4) length-matching edge joining. Experiments on Delaunaygenerated datasets with 20-60 points show that Strategy 4 achieves the highest average coverage but with greater variance, while Strategy 2 provides the most stable performance. Coverage, runtime, and efficiency metrics demonstrate that even simple geometric heuristics-particularly edge-length matching and edge joining-serve as effective baselines for fast reassembly of triangulated rectangular domains.

Background The IMPULSE trial investigated the effectiveness and implementation of a digital psychosocial intervention (DIALOG+) for people with psychosis in five Southeast European countries. DIALOG+ significantly improved patients’ quality of life after four treatment sessions. The process evaluation reported here aimed to assess contextual influences on intervention delivery during the trial, to explain the trial findings and generate hypotheses about mechanisms of action by exploring acceptability from the perspectives of clinicians who delivered it and trial participants who received it, and fidelity (was the intervention delivered and received as planned?). Method A mixed-methods process evaluation was conducted in accordance with the published protocol, guided by theoretical frameworks and the Medical Research Council’s guidance for complex interventions. To explore the role of context, data were analysed about the participating services, policy documents, and from focus groups with key stakeholders. Semi-structured interviews with clinicians and patients were conducted to explore acceptability. Process data (format and content of sessions) were analysed to assess intervention fidelity. Data analysis included descriptive methods, framework and content analysis, and triangulation. Results Several attributes of context related to health services, including resource limitations, funding priorities, reliance on paper records and lack of community support, potentially negatively impacted DIALOG+ acceptability, fidelity and outcomes. Contextual enablers were also identified, including an appetite for change among key stakeholders that can help overcome contextual barriers. Acceptability of the psychosocial intervention was moderate to high and fidelity was high. Conclusions Intervention acceptability is likely to have played a key role in ensuring high fidelity, which in turn likely contributed to the intervention’s positive impact on patients’ quality of life. The high fidelity confirms that the IMPULSE trial findings provide a valid assessment of the intervention as designed. While the identified contextual barriers appear not to have impaired intervention fidelity, acceptability and outcomes, they could pose challenges to the long-term sustainability of the intervention. Trial registration Retrospectively registered on 29 March 2021, ISRCTN11913964

Abstract By the directives of the European Union (EU), the Energy Community (EC) operates in the field of electricity production, distribution, supply, consumption management, aggregation, energy storage, provision of flexibility services, energy efficiency services, and charging services for electric vehicles. To achieve the above, it is necessary to clearly define the EC’s business models, technical design, and organizational structure. This paper will clarify the similarities and differences between the concepts of renewable energy communities and citizens’ energy communities through a comparative analysis. This paper provides an overview of the literature on ECs to create a picture of the current situation in this area. Likewise, the analysis of the literature gave a clear picture of who the possible members of the EC are, their mutual relations and the possible activities of the EC and the way of participating in the market. For an energy management system (EMS), the model of data exchange is given. This requires the exact mapping of EC within the SGAM, which includes communication and information standards. Also, the business models and functions of ECs are explained. For the selected use-cases, an analysis of the functionalities (activities) of the ECs is conducted.

In this paper, we investigate an open-access fishery model which is used to examine the dynamics of the resource and industry and to explain the current economic status of the anchovy fishery. We consider the local character of the interior and boundary equilibrium points. Also, we show that the considered system of difference equations exhibits Neimark-Sacker bifurcation under certain conditions. The existence of the repelling curve and invariant curve is demonstrated. We show that in a certain parameter region the corresponding map of the considered system is an area-preserving map, so the positive equilibrium point in that case is stable. Also, we produce numerical simulations to support our findings.

In this paper, we study the dynamics and bifurcation of a two-dimensional discrete-time predator-prey model. The existence and local stability of the equilibrium points of the model are analyzed algebraically. It is shown that the model can undergo a transcritical bifurcation at equilibrium point on the $x$-axis and a Neimark-Sacker bifurcation in a small neighborhood of the unique positive equilibrium point. Some numerical simulations are presented to illustrate our theoretical results.  

Steatosis extends beyond the liver to the pancreas, heart, and skeletal muscle, yet prevailing definitions remain narrowly organ-focused. This narrative review introduces the Metabolic Steatotic Axis (MSA) as a framework that captures the dynamic, bidirectional interactions among these organs, driving systemic metabolic dysfunction. We synthesize evidence linking lipotoxicity, inflammatory signaling, and endocrine cross-talk into a self-amplifying network accelerating insulin resistance, β-cell failure, and cardiometabolic risk. The MSA concept provides a rationale for axis-based staging systems and composite biomarker panels to quantify cumulative disease burden better and refine risk stratification. We highlight phenotypic heterogeneity within MSA stages, the possible hierarchy of organ vulnerability, and the implications for prognosis and therapy. Viewing pharmacological and lifestyle interventions through the MSA lens reframes them as systemic modulators rather than organ-specific treatments, underscoring the need for multi-organ endpoints in clinical trials. Finally, we outline priorities for longitudinal imaging, multi-omics integration, and global harmonization to translate the MSA from a conceptual construct to a clinically actionable paradigm. By unifying fragmented observations into a systemic model, the MSA has the potential to reshape disease classification, therapeutic strategies, and precision medicine in metabolic disorders.

In sustainable portfolio management, categorizing assets as “brown“ or “green“ based solely on ESG ratings can be misleading. A positive ESG score does not inherently indicate environmental responsibility unless it is evaluated relative to a meaningful benchmark. We propose a rescaled ESG rating system that measures each asset’s environmental standing relative to a threshold set by policymakers, reflecting the urgency of the current climate crisis. In this system, assets are assigned positive scores if they exceed the threshold (green) and negative scores if they fall below it (brown), enhancing the interpretability of sustainability metrics in portfolio construction. However, a challenge arises when aggregating these scores into an overall portfolio rating. Under sustainable portfolio optimization developed in [11], short positions in brown assets, otherwise effectively betting against polluting companies, can paradoxically improve the portfolio’s sustainability score. This creates a misleading incentive structure. To address this, we introduce a constraint that prohibits short positions in brown assets, ensuring that such investments do not positively impact the portfolio’s sustainability rating. While this restriction better aligns with environmental objectives, it also introduces complexity into the optimization process. To resolve this, we present an intuitive algorithm inspired by the active set method, which we refer to as Green Portfolio Optimization, capable of handling these constraints efficiently even in high-dimensional settings.

Central and Eastern United States (CEUS) earthquakes are less common than those in the tectonically active West Coast, but their significance is elevated due to higher population densities, less-attenuating bedrock geology, variable site-amplification effects, and a higher proportion of structures prone to damage from shaking. Associating CEUS earthquake focal mechanisms with causative crustal faults is challenging due to a lack of mapped faults. Aftershock productivity of CEUS earthquakes is difficult to predict because it is highly variable, displaying globally typical behavior in some regions (Wu et al., 2015; Wu and Chapman, 2017) and low decay rates (Stein and Liu, 2009; Calais et al., 2016; Toda and Stein, 2018) in others. Here, we study the aftershock sequence of an unusual Mw 4.24 CEUS earthquake that occurred below the Atlantic Coastal Plain east of Dover, Delaware, in late 2017. We analyze data from a temporary 14-station network and use template matching to search for aftershocks, which we locate using a custom 1D velocity model. We find aftershock locations favoring slip on a northwest–southeast-striking fault oblique to the presumed fault where the mainshock was located. We document an unusually low a value and large magnitude difference between the mainshock and the largest aftershock, as well as an average aftershock decay p value. Factors proposed to explain variations in aftershock productivity include fault alignment relative to the prevailing stress field (Hardebeck, 2010) and low productivity after a high stress drop (Wetzler et al., 2018). We test these hypotheses in relation to the 2017 Delaware earthquake aftershocks, showing the Delaware earthquake had a stress drop of 35 MPa, normal for an intraplate region (Boyd et al., 2017), and had favorable alignment for aftershock thrust faulting. We therefore propose a small fault of possible pre-Mesozoic origin, limiting the productivity observed.

Rapid detection of antibiotic-resistant bacteria is a crucial tool in the global fight against antimicrobial resistance, helping to limit the spread of resistance and guide treatment decisions. Here, we report the design, synthesis, and electrochemical evaluation of β-lactam-based redox-activatable probes for detecting β-lactamase activity. The probes incorporate a β-lactam core linked to redox reporters through cleavable linkages, enabling signal generation upon enzymatic hydrolysis. High-performance liquid chromatography and differential pulse voltammetry analyses were used to assess time-dependent activation and concentration-dependent responses against commercial β-lactamase blends and metallo-β-lactamases. Selected probes, bearing cephalosporin recognition motifs and maltol redox reporters, were further evaluated against clinical isolates, demonstrating selective activation in carbapenemase-producing strains. To extend the platform toward solid-state biosensing, an azide-functionalized analog was clicked on alkyne-modified glassy carbon electrodes. Stepwise surface functionalization and immobilization were validated electrochemically using model redox reporters, confirming their activity. The immobilized probe retained responsiveness, demonstrating the feasibility of integrating this sensing strategy into solid-state diagnostic devices. By integrating stable cephalosporin scaffolds with redox-reporter signaling, this work introduces a novel probe system that unites chemical probe design with surface-based electrochemical sensing, providing a strong foundation for the development of portable, point-of-care diagnostics for β-lactamase-mediated antibiotic resistance.