Abstract: Digital twins offer significant potential for operationalizing a circular economy at the municipal level. This study aims to propose a business model framework that optimizes the circular management of municipal solid waste (MSW) by leveraging the concept of "Co-creative Digital Process Twins." The methodology was structured around two primary axes: first, a critical literature review conducted via the PRISMA-ScR protocol to identify process architectures and existing research gaps in digital process twin development; and second, a theoretical-practical integration using the Business Model Canvas tool, grounded in the paradigms of the circular economy and participatory design, applied to a case study in the municipality of Progreso, Hidalgo, Mexico. Our findings reveal a significant bias in the current state of the art: existing digital twin applications are predominantly industrial and notably lack social inclusion mechanisms. In response, this paper presents a multidimensional business model that integrates key social actors into the digital ecosystem, establishing an architecture explicitly designed to maximize material recovery rates. Conclusively, the adoption of co-creative digital process twins provides a robust socio-technical infrastructure that not only simulates and optimizes the waste value chain but also fosters social inclusion, thereby catalyzing the transition toward a genuinely circular municipal economy.

Abstract: To improve the antifouling and self-cleaning performance of 3003 aluminum alloy, a green fluorine-free superhydrophobic surface was fabricated by combining nanosecond laser processing with subsequent heat treatment. The effects of laser processing parameters, including scanning speed, laser power, pulse frequency, and scanning interval, on surface wettability were systematically investigated. The results showed that optimized processing conditions (2700 mm/s, 6 W, 35 kHz, and 20 μm) enabled the formation of hierarchical micro-/nano-structures, resulting in a maximum water contact angle of 154.32°. SEM and EDS analyses suggested that the enhanced wettability originated from the synergistic effect of hierarchical rough structures and heat-treatment-induced surface chemical modification, which promoted the formation of a stable Cassie–Baxter state. The fabricated surface exhibited excellent self-cleaning performance, as water droplets effectively removed SiO₂ contaminants by rolling behavior. In addition, the surface maintained high hydrophobicity after repeated water jet impact and tape-peeling tests, indicating good resistance to dynamic flow and mechanical damage. This study provides a simple, environmentally friendly, and effective strategy for fabricating durable superhydrophobic aluminum alloy surfaces for antifouling and protective applications.

Abstract: Background/Objectives: Antineoplastic therapies have improved cancer survival but remain a major source of treatment-related cardiotoxicity. Comparative global pharmacovigilance evidence across anthracyclines, anti-HER2, and anti-VEGF therapies remains limited. Methods: A retrospective disproportionality study was conducted using Individual Case Safety Reports (ICSR) from the World Health Organization (WHO) VigiBase accessed via VigiAccess (March 23, 2026). Eight antineoplastic agents were grouped into three therapeutic classes. Descriptive analyses of demographic characteristics, System Organ Class (SOC) distributions, and cardiac Preferred Terms (PT) were performed. Reporting Odds Ratios (ROR) with 95% confidence intervals were calculated using a restricted antineoplastic comparator cohort. Signals were defined as ROR lower 95% CI >1 with ≥5 cases. Results: A total of 388,068 ICSR were analyzed. Anti-HER2 agents showed the highest relative cardiotoxic burden (10.43%) and the strongest disproportionality signal (ROR 1.91; trastuzumab ROR 2.11). Anthracyclines accounted for the largest number of cardiac reports (n = 11,273), with a predominantly structural-myocardial phenotype led by cardiomyopathy and heart failure. Anti-VEGF agents displayed a distinct vascular–ischemic profile, with redistribution toward vascular (10.86%) and renal (6.08%) SOCs and myocardial infarction as a dominant cardiac PT. Conclusions: Cardiotoxicity associated with antineoplastic therapy follows class-specific phenotypic patterns rather than a uniform profile. Anti-HER2 agents concentrate the highest relative burden, anthracyclines the greatest absolute volume, and anti-VEGF therapies exhibit a distinct vascular–ischemic phenotype. These findings support mechanism informed, class-specific cardiovascular surveillance strategies and highlight the value of global pharmacovigilance data.

Abstract: Claim reserving is one of the most important tasks in non-life insurance, as it directly affects solvency assessment, financial reporting, and risk management. Traditional reserving methods often assume a relatively homogeneous claim-development process and may fail to capture hidden structures within complex insurance portfolios. This paper introduces a novel reserving framework that integrates Topological Data Analysis (TDA) with both aggregate and micro-level reserving methodologies. Using a portfolio of motor insurance claim payments, we employ topological techniques to identify latent claim-development regimes and portfolio heterogeneity. The extracted topological information is subsequently incorporated into an Inverse Probability Weighting (IPW) reserving framework and a TDA-enhanced Chain-Ladder (CL) methodology. The empirical results suggest that the proposed TDA-based approaches may improve reserve estimation accuracy relative to their traditional counterparts. Both TDA-IPW and TDA-CL produce reserve estimates that are remarkably close to realized future claim payments. The findings suggest that topological structures contain valuable information for actuarial reserving and that Topological Data Analysis may provide a promising new direction for the development of reserving methodologies.

Abstract: Forced periodic operation (FPO) has emerged as a promising process intensification strategy for nonlinear catalytic reactors. In this study, the nonlinear frequency response (NFR) methodology was applied to investigate square-wave FPO of an isothermal CSTR for methanol synthesis. The analysis focused on periodic modulation of the inlet CO and flow rate, considering both single-input and simultaneous-input forcing. The reactor response was evaluated using higher-order frequency response functions (FRFs) to quantify the non-periodic component responsible for time-averaged process enhancement. The results showed that individual modulation of either inlet CO or flow rate doesn't provide significant improvement in reactor performance and may even reduce methanol productivity. In contrast, simultaneous modulation of both inputs generates a strong positive nonlinear interaction that substantially enhances reactor performance. Under optimal forcing conditions, methanol productivity increased from 336.9 mmol min⁻¹kgcat-1 at steady-state to 553.6 mmol min⁻¹kgcat-1, corresponding to a 64.3% improvement. Compared with previously reported cosine forcing, square-wave modulation nearly doubled the attainable productivity enhancement while also improving hydrogen utilisation efficiency. The results demonstrate that square-wave FPO represents a highly effective strategy for methanol synthesis intensification and confirm the capability of the NFR methodology for a priori evaluation and optimisation of periodically operated catalytic reactor systems.

Abstract: This study is anchored in the quest to systematically chart the academic territory of digital twin technology applications in smart city development. It aims to elucidate the extent and focus of scholarly discourse, pinpointing key thematic developments and assessing their evolution over time. This study conducts a bibliometric analysis using literature focusing on the period 2018–2024 of research on digital twins and smart cities. The most frequently used Scopus database was used to extract bibliometric data. 422 ar-ticles were considered for analysis. This study utilizes co-authorship, co-occurrence, citation analysis, and bibliographic coupling of author keywords while graphically mapping the bibliographic material using BiblioMagika software. This study identified the authors, institutions and countries that publish the most globally on the topic of Digital Twins and Smart Cities. The results revealed that most of the published articles come from China. The other highly ranked countries by origins of studies on Digital Twins and Smart Cities were found to be the USA and Italy all of which are developed nations or economies. The study makes significant and emergent contributions by building on the research area as well as providing a reference point for the interpretation of findings, as well as directions for future research.

Abstract: Estimating PM₂.₅ exposure in high-altitude Andean cities is challenging due to limited monitoring coverage and the complex interactions among topography, meteorology, and atmospheric chemistry. This study presents a comparative assessment of Random Forest and Extreme Gradient Boosting (XGBoost) for urban-scale PM₂.₅ estimation in Quito, Ecuador. Ground-based observations from the Metropolitan Atmospheric Mon-itoring Network of Quito (REMMAQ) were integrated with Sentinel-5P TROPOMI products, meteorological variables, and topographic predictors processed in Google Earth Engine. Models were developed separately for wet and dry seasons to account for seasonal variability. XGBoost achieved the highest predictive accuracy during the wet season (R² = 0.73), when topographic controls dominated PM₂.₅ variability and the DEM emerged as the most influential predictor. In contrast, RF demonstrated greater robustness during the dry season (R² = 0.63), when photochemical interactions became increasingly important and the CO–SO₂ combustion index was the dominant predictor. Spatial predictions identified a persistent north–south pollution corridor within the urban core of Quito. These findings indicate that PM₂.₅ dynamics in inter-Andean val-leys are governed by seasonally shifting physical and chemical controls. The proposed framework provides a scalable approach for generating spatially continuous air-quality estimates in mountainous urban environments with limited monitoring in-frastructure.

Abstract: Adipose tissue has emerged as a pivotal endocrine organ, secreting bioactive proteins termed adipokines that regulate metabolic and immune processes across multiple organ systems. In the context of sepsis and critical illness, conditions defined by a dysregulated host response to infection with life-threatening organ dysfunction, the role of novel adipokines has attracted considerable research interest. This review focuses on three novel adipokines, chemerin, vaspin (SERPINA12), and omentin-1 (intelectin-1). We will discuss current in vitro, in vivo experimental animal models, and clinical evidence, emphasizing their biology, mechanisms of action, and potential as diagnostic and prognostic biomarkers in critically ill patients. All three adipokines are elevated in sepsis compared with healthy controls and correlate with established severity scores, including APACHE II and SOFA. Chemerin and omentin-1 have both been independently associated with 28-day mortality in prospective cohort studies. Vaspin exhibits robust cardioprotective effects in murine sepsis models via inhibition of kallikrein 7 (KLK7) and attenuates lipopolysaccharide (LPS)-induced acute lung injury (ALI) both in vitro and in vivo. Omentin-1 suppresses LPS-induced macrophage activation through TLR4/MyD88/NF-κB inhibition in vitro and protects against LPS-induced ALI in murine models. Despite these promising findings, substantial methodological heterogeneity and limited large-scale clinical data currently preclude clinical implementation. Future research that standardizes assays, expands to multicenter cohorts, and investigates therapeutic modulation of these pathways is urgently needed.

Abstract: This work presents a comparative handling and stability analysis between conventional pneumatic tires and self-supporting run-flat tires (SSRFT) subject to severe inflation pressure loss. A comprehensive seven-degree-of-freedom (7-DOF) full-scale vehicle dynamics plant model was developed to evaluate vehicle performance across four distinct operational scenarios under the standardized closed-loop tracking constraints of the ISO 3888-2 double lane change maneuver. Dynamic vehicle behavior was quantified using a broad suite of handling metrics, including: individual tire lateral forces, transient lateral acceleration, yaw rate, body roll angle, exit speed, body sideslip angle, and Kamm friction circle envelopes. The simulation results demonstrate a severe degradation in trajectory tracking for deflated conventional configurations yielding critical understeer saturation. Conversely, the SSRFT configurations preserve sufficient cornering stiffness to remain within stable path boundaries. These findings provide high-value empirical insights essential for optimizing future active chassis management architectures and electronic stability control systems logic.

Abstract: Power control of photovoltaic generation, flexible loads, e.g. electric vehicles and heat pumps, and battery energy storage systems (BESS)havebecomeimportantforenergyarbitrage. Thisworkdevelops a two-level power control model for day-ahead and real-time scheduling, where the contribution of flexible loads (e.g. vehicle-to-grid (V2G) use) and BESS is compared, considering different grid types, grid sizes, seasons, and battery degradation. An empirical degradation model has been linearized and incorporated, including cyclic and calendar aging. The results showed that the seasonal effect significantly influences the grid power exchange and the V2G use. Moreover, the grid type has a notable impact on the flexibility of the node since commercial grids import less grid power and use less V2G due to lower flexibility. Furthermore, a larger grid size decreases the need for BESS use and increases the likelihood of V2G use. While degradation has a small effect on the total cost of small grids, the effect increases notably as the size of the grid increases, while it also greatly reduces V2G and BESS use. Finally, the model has been validated against benchmark and control models, showing cost reductions of up to 5.81% and 30.6%, without and with BESS use, respectively.

Abstract: The increasing complexity of automotive software driven by ADAS and autonomous driving has intensified the need for time-deterministic network validation beyond CAN/LIN, while HIL integration remains constrained by limited ECU prototypes and labor-intensive manual configuration. This paper presents a network-oriented virtual verification environment that couples Renode-based virtual ECUs (vECUs) with FMU-based Interaction Layer (FIL) Nodes automatically generated from DBC specifications. The vECUs provide instruction-accurate execution of unmodified target binaries without physical hardware, while the generated FIL Nodes encapsulate communication behavior as model-based FMUs to maintain continuity from MIL to SIL without manual signal mapping. The proposed framework constructs virtual CAN networks from communication-definition files, reproduces periodic and event-triggered traffic patterns, and supports synchronized multi-ECU co-simulation under master-controlled time stepping. Experimental results show that the vHIL environment reproduces physical ECU timing behavior with a maximum relative error of 0.086%–0.171% across all evaluated step sizes (10 μs to 1000 μs), confirming binary-level timing fidelity. Replacing vECUs with FIL Nodes for network communication processing significantly reduces wall-clock execution time in multi-node configurations, demonstrating improved scalability without sacrificing determinism. These results demonstrate that the proposed methodology effectively reduces early-stage integration bottlenecks while preserving timing fidelity for automotive networked ECU validation.

Abstract: In oil production, the formation of oil emulsions due to reservoir water breakthrough is widely observed. Since the viscosity of these emulsions, which are considered polydisperse systems, can increase sharply depending on the degree of water cut, they create considerable difficulties in well-gathering systems and also increase hydraulic losses. The rheological properties of oil emulsions depend on the phase ratio, flow velocity, degree of dispersion, and numerous other parameters. There is no generalized model for the rheological description and determination of the properties of oil emulsions, which belong to anomalous and rheologically complex systems. Therefore, a diagnostic method for determining the viscosity of stable emulsions, taking into account the effect of increasing water content, is of great importance. In this article, the existing empirical expressions currently used for diagnosing the rheological properties of oil emulsions are examined. It has been determined that their application in oilfield practice is associated with certain difficulties and, in most cases, they are not considered suitable for solving engineering problems. In the article, a mathematical model has been developed, tested, and shown to provide good results for determining and predicting the viscosity of structurally stable oil emulsions depending on the degree of water cut.

Abstract: Among the micropollutants of medium-depth waters in isolated inhabited areas, the inorganic ones deserve special attention: nitrate anion (NO₃⁻) and phosphate anions (HxPO4^⁻(3⁻x)). The individual removal of these anions from water is widely studied, with different methods being found: chemical, ion exchange or biological. This paper presents a membrane method for the simultaneous removal of nitrate anion and phosphate anions from dilute synthetic aqueous solutions. The developed method is nanofiltration using composite membranes made of cellulose acetate (CA) and silver nanoparticles (Agnp). The composite membranes were made by phase inversion of the dimethylformamide (DMF) solution containing the two components (CA–Agnp) on a polypropylene (PP) capillary fiber using deionized waster as a coagulant. The DMF solution of CA containing Agnp was obtained by dissolving black-and-white cinematographic films (exposed and unexposed to light). CA–Agnp–PP composite membranes were tested for the simultaneous removal of nitrate anion and phosphate anions from aqueous solution by nanofiltration at pressures ranging from 5 to 25 bars. A removal of over 98% of phosphate anions and more than 95% of nitrate anion was achieved. Fluxes of 10 L·m^⁻2·h^⁻1 were obtained for the working pressure of 15 atm, depending on the pH, flow rate and concentration of the feed water (feed solution). Variable parameters studied were also the concentration of CA and Agnp.

Abstract: Islanded and weakly interconnected power systems face increasing operational challenges as the penetration of renewable energy grows, particularly in environments with limited flexibility and reserve support. This study investigates a residential energy community in Cyprus using real time prosumer data and proposes a hierarchical decentralized Energy Management System (EMS). The EMS was initially implemented as a rule-based Minimum Viable Prototype (MVP), enabling practical validation of system operation and data integrity under realistic conditions. Building on this foundation, the final EMS adopts a three-layer control architecture in which rule-based household storage operation and peer-to-peer energy trading are complemented by a community-level Model Predictive Control (MPC) strategy for shared battery management. The MPC leverages short-term net-energy forecasts to proactively schedule charging and discharging of the community battery with the objective of reducing grid energy imports and improving local renewable energy utilization, while respecting battery operational limits and regulatory constraints. Simulation results based on measured data demonstrate consistent improvements over the rule-based baseline, achieving up to 23.4% reduction in electricity cost, approximately 6–7% reduction in grid energy imports, and a 1–2% increase in community self-sufficiency. Although the reduction in imported energy is moderate, its cumulative impact over long-term operation leads to significant economic benefits under time-varying tariffs. These results demonstrate that even when MPC is applied exclusively at the community battery layer, coordinated system-level energy management can deliver stable and economically meaningful improvements under realistic operating conditions.

Abstract: As enterprises continuously rely on data to effectively drive and power business processes in a digital economy, privacy concerns have emerged as a major source of deep concern among consumers and privacy advocates in a digital society. Several scholars have shared their opinions and perspectives in related articles on this issue since privacy is a fundamental and constitutional right in many countries that must be protected at all times. While several practitioners and industry experts have proffered various privacy-preserving measures to help empower users to make informed decisions that relate to the use of their personal information, others have proposed various privacy preserving measures and mechanisms to help protect the use of personal information in a digital society to create the necessary confidence and trust amongst members of the public. With the current advances in artificial intelligence, social media platforms, and automation, the issue has emerged as a major source of concern among policymakers, privacy advocates, and industry experts. The purpose of the e-Delphi study was to gain consensus from the opinions of industry experts on best practice measures and various effective privacy-preserving measures to help enhance users’ privacy and allay privacy concerns in a digital society. The study adopted the Restricted Access/Limited Control (RALC) theory of privacy to provide a theoretical framework for the research study. The study included three rounds of questioning using the Delphi method. The findings from the study revealed that effective privacy-preserving measures, such as Data minimization, Privacy-By-Design, Privacy Labels and icons, Data Ownership and control, Third-party App Permission, Mandatory Data/Privacy Breach Notice, Frequent Policy Updates, End-to-End Encryption, User-Friendly Privacy Control features, and Informed Consent, provided an effective way to allay the fears of consumers in a digital age.

Abstract: Rising global temperatures pose a serious threat to wild small mammal’s population persistence. In this study, we investigated the molecular mechanisms underlying heat-induced testicular impairment in Brandt’s vole (Lasiopodomys brandtii), a dominant small mammal species of the Eurasian temperate steppe. Adult males were subjected to short term heat exposure at 37°C, 39°C, and 41°C. Heat stress at temperatures ≥39°C significantly reduced the testicular index and caused histopathological damage. Integrated transcriptomic and data-independent acquisition proteomic analyses revealed significant enrichment of pathways related to endoplasmic reticulum protein processing and barrier function. Further molecular validation demonstrated robust activation of the unfolded protein response, indicated by increased expression of ATF4, ATF6B, phosphorylated eIF2α, and XBP1. Together, these results identify endoplasmic reticulum stress as a key mediator of heat-induced testicular injury and highlight that 39°C represents a critical reproductive threshold for Brandt’s voles, even following short-term exposure.

Abstract: This article presents the design and deployment of ClimaBogotá v1.2, a climate prediction system tailored for high-altitude urban micro-zones in Bogotá, Colombia. The system combines low-cost IoT sensing, machine learning modeling, and cloud-based orchestration to enable scalable and affordable meteorological forecasting. Its architecture comprises Raspberry Pi-based weather stations, a Random Forest model trained on engineered temporal features, and an n8n-driven automation pipeline for real-time inference and dissemination via Telegram, PostgreSQL, and Grafana. With a Mean Absolute Error of 2.59°C and an R² of 0.6286 on a 30-minute forecast horizon, the system demonstrates both predictive reliability and operational feasibility using free-tier cloud resources. Unlike traditional weather systems, ClimaBogotá emphasizes modularity, adaptability, and cost-efficiency, offering a replicable framework for decentralized climate monitoring in data-scarce urban environments. Temporal misalignment between sensor nodes was identified as the primary constraint, informing future enhancements toward distributed learning strategies.

Abstract: Background/Objectives: Advanced-stage hepatocellular carcinoma is characterized by a very poor prognosis; thus, highly effective medication is still needed. Often overexpressed heat shock protein 90 is a promising target due to its pivotal role in carcinogenesis. Methods: Antiproliferative effects of novel synthesized inhibitor 246TMP-3SF5 on HepG2 and HuH-7 were analyzed through crystal violet staining. Apoptosis was assessed by measurement of subG1 peak, caspase-3 activity and cleavage of PARP. Ferroptosis was evaluated through reactive oxygen species, glutathione and malondialdehyde levels. Scratch assays were used to assess cancer cell migration and in-ovo models to analyze effects of 246TMP-3SF5 on angiogenesis and microtumors. Molecular docking and molecular dynamics simulation into heat shock protein 90 were carried out using Autodock Vina and Gromacs respectively. Results: Profound dose- and time-dependent antiproliferative effects of 246TMP-3SF5 against HCC cell lines were observed, revealing low micromolecular IC50 values. A significant increase in subG1 peak, key effector caspase-3 activity as well as cleavage of PARP strongly suggested apoptosis playing a crucial role in the antiproliferative effects. Additionally, HuH-7 cells revealed an elevation of reactive oxygen species and both cell lines showed significant glutathione depletion concomitant with malondialdehyde concentration increased upon treatment. The observed effect could be partially reversed applying ferrostatin-1, suggesting ferroptosis as an additionally relevant mode of action. Changes in the cell cycle as well as impaired tumor cell migration were observed. Upon treatment angiogenesis was impaired and mass of microtumors was significantly reduced. Molecular docking revealed interaction with catalytic site of heat shock protein 90. Conclusions: 246TMP-3SF5 is a promising novel inhibitor meriting further research as potential treatment against hepatocellular carcinoma.

Abstract: Across the post-Soviet space, the disappearance and commercialisation of traditional public realms have shifted everyday social life toward privately owned, publicly used environments. This study examines whether and how contemporary shopping malls function as quasi-public spaces and “third places” in Almaty, Kazakhstan’s largest city. Drawing on Oldenburg’s third-place theory and debates on the privatisation of the public realm, a mixed-methods design combined a visitor questionnaire (n = 412) across five malls, 40 hours of behavioural mapping, and 30 semi-structured interviews with visitors and mall managers. Results indicate that, beyond consumption, malls host substantial non-commercial sociability: 56.4% of respondents reported visiting primarily for dining, leisure, or meeting others rather than shopping, and the majority agreed that malls feel comfortable and broadly accessible. At the same time, only a minority unambiguously regarded the mall as a “public space”, and perceptions of inclusiveness varied significantly with age, income, and mode of arrival. Malls thus operate as conditional and negotiated third places whose publicness is real but managed. The paper argues that recognising malls as de facto social infrastructure has direct implications for socially sustainable urban planning in rapidly transforming Central Asian cities, and outlines design and policy measures to strengthen genuine inclusiveness.

Abstract:

Forest ecosystems in Northern Ghana's Guinea Savannah landscape face mounting pressures from illegal logging, charcoal production, agricultural expansion, bushfires, and climate variability, threatening biodiversity, carbon stocks, and the parkland mosaic of shea, dawadawa, neem, and baobab that sustains local livelihoods. The Risk Management Framework (RMF) offers a structured approach to anticipate, assess, and mitigate such environmental risks, yet its operational integration into forest governance in Sub-Saharan Africa remains weak. This study examined the awareness, understanding, and applied knowledge of the RMF among forestry stakeholders in Northern Ghana and analysed the socio-demographic and institutional factors shaping engagement with risk-based environmental governance. Using an explanatory sequential mixed-methods design, a structured survey was administered to 160 stakeholders across five districts (West Mamprusi, Mamprugu Moagduri, North Gonja, Sagnarigu, and Tamale Metropolitan), complemented by five focus group discussions with Community Resource Management Area (CREMA) groups and seven key informant interviews with officers from the Forestry Commission, Environmental Protection Agency, and Ministry of Food and Agriculture. Data were analysed using descriptive statistics, multiple linear regression, a validated three-item Knowledge Scoring Index (Cronbach's α = 0.78), and thematic analysis. Results show that while overall awareness of RMF was high (94%), applied knowledge was substantially weaker, particularly regarding the institution responsible for RMF implementation (mean = 0.32). Education, occupation, and composite knowledge score significantly predicted RMF knowledge, while gender and community-leader status did not. Qualitative findings revealed three structural patterns: symbolic risk governance, a community-leader bottleneck in information transmission, and an awareness–understanding divergence in which stakeholders interpret formal RMF terminology through indigenous and CREMA-based practices. The findings demonstrate that human knowledge systems mediate forest ecosystem outcomes and underscore the need for institutional clarification, targeted capacity-building, and a phased digital tools roadmap, including mobile-based reporting platforms, satellite-derived monitoring dashboards, and integration of indigenous early warning indicators, to strengthen forest sustainability, biodiversity conservation, and climate resilience in dryland Sub-Saharan Africa.