Accurate rainfall records producing Intensity-Duration-Frequency (IDF) curves, relating rainfall intensity to its duration and return periods, and derived design storms, are cornerstones of resilient hydraulic and urban drainage design. By translating long-term rainfall statistics into specific storm profiles, engineers can reliably design and size sewers, culverts, basins, and flood defenses, and run hydrological models that predict runoff volumes and peak discharges under future extremes.

We merged two publicly available sources (national meteorological archives and the ECA&D homogenized series) to assemble a continuous 108-year (1916–2024) daily rainfall time‐series for Limassol, Cyprus. A Python‐based gap-filling tool (mean, linear interpolation, moving-average) ensures applicability to other sites. We generated IDF curves from two records lengths (1990–2024, 1970–2024) by fitting Gumbel, GEV, Log-Pearson III, and Weibull distributions, evaluating goodness-of-fit (using two different tests) and selecting the optimal model.

For each one, we produced 24-hour depth tables at multiple return periods and 95% confidence bounds via bootstrap resampling. Finally, we derived hyetographs for multiple return periods, using uniform, triangular, and Chicago methods.

This work provides the first publicly available detailed hydro-meteorological dataset, IDF analysis, and suite of design storms for Limassol, filling a critical gap in local resilience planning.

The process is discussed step by step in a Supplementary Material, guiding modelling, selection, and design decisions that an analyst may face in similar studies.

All steps are incorporated into user-friendly Python scripts, that are readily adaptable to other regions, and will be publicly released to support robust hydrological modelling and infrastructure design.

Iron (Fe) is an essential mineral for human health, but chronic overexposure may induce oxidative stress, particularly in adolescents undergoing physiological and endocrine changes. Scalp hair was collected from 97 adolescents (13–16 years old; 68 girls) living in Alcalá de Henares, an urban–industrial municipality near Madrid, and analysed using ICP-MS (LoD = 1.148 µg/g). Fe was detected in 100% of samples and showed clear sex dependency: significantly higher concentrations were recorded in females than in males [median (range), µg/g: 5.524 (3.167–13.262) vs. 4.464 (2.666–6.173); p = 0.000057]. This effect may reflect hormonal differences, as the endocrine system typically becomes active earlier in females. Nevertheless, potential confounders such as dietary iron intake, supplements, or cosmetic hair treatments could also contribute to variability and warrant further consideration. Hair Fe levels were correlated with matched surface soil samples from the city. Fe was detected in 100% of soils, ranging from 12,588 to 54,169 µg/g (median 26,159 µg/g). A modest but significant correlation was observed between hair and soil concentrations (r = 0.21, p < 0.05), stronger in males (r = 0.43, p < 0.01) and females (r = 0.36, p < 0.01). Fe concentrations did not differ significantly across the four residential areas defined in Alcalá (p = 0.370). These results support the value of hair as a non-invasive biomonitoring matrix for Fe exposure and emphasize the importance of sex-disaggregated and geospatial analyses. Establishing age- and sex-specific reference values could facilitate the inclusion of hair biomonitoring in public health surveillance and preventive strategies.

The COVID-19 pandemic has generated an unprecedented surge in disposable face mask waste, with an estimated 3.4 billion masks discarded daily, exacerbating global plastic pollution while urban agriculture faces water scarcity challenges, particularly in arid regions. This study addresses both issues by developing a circular solution that repurposes surgical masks into hydrogel-enhanced growth substrates for water-efficient urban farming. Sterilized masks were shredded and blended with cross-linked cellulose hydrogels (15% v/v) to create a water-retentive medium, tested in rooftop gardens under arid conditions over 90 days using IoT-monitored irrigation. Results demonstrated a 42% reduction in water use compared to conventional soil, while maintaining 95% crop survival rates (vs. 68% in controls) and increasing tomato yields by 27% due to stable moisture retention. Each square meter of substrate recycled ~35 masks, preventing 1.2 kg CO₂e emission from incineration. The methodology aligns with ecological engineering principles, leveraging mask-derived polypropylene fibers as a structural base for hydrogels, which also reduced microplastic leakage by 89% compared to untreated mask waste. This approach not only diverts PPE from landfills but also enhances urban food security in water-stressed areas. This study concludes that scaling this innovation could mitigate pandemic-era plastic pollution while supporting SDGs 2 (Zero Hunger), 6 (Clean Water), and 12 (Responsible Consumption), with future research needed to optimize hydrogel formulations for diverse crops and climates.

Over the past two decades, studies of the dynamics and efficiency of Nonlinear Energy Sinks (NESs), which were proposed as a development of Tuned Mass Dampers (TMDs), have become widespread. The aim of this work is to compare the efficiency and ability to maintain the tuning of a single-sided vibro-impact NES (SSVI NES), i.e., a vibro-impact damper, and TMD, i.e., a linear damper, under periodic excitation. The research was performed using numerical methods; the impact was simulated by Hertz’s nonlinear contact force. Expressive graphs and tables successfully confirm the findings formulated. Both the SSVI NES and TMD maintain their tuning and demonstrate high efficiency across a fairly wide range of structural parameters; however, in some cases, the TMD maintains its tuning better. At the same time, the zones of bilateral impacts for the SSVI NES with optimized parameters are quite narrow and located near the resonance. These phenomena were verified for lighter dampers with a mass ratio of 2% and for heavier dampers with a mass ratio of 6% when several structure parameters were changed, namely, the damping of the primary structure, its stiffness, and the intensity of the exciting force. The SSVI NESs with lower mass ratios exhibit peculiar behavior; some of their parameters take on non-standard, unusual values. Thus, with periodic excitation, TMDs are not inferior in efficiency to SSVI NESs, which always demonstrate complex dynamics and present difficulties in selecting the optimal design.

Climate change is intensifying the hydrological cycle, leading to more frequent and severe flood events worldwide. In Greece, recent disasters have exposed the vulnerability of aging infrastructure: bridges, drainage networks, flood protection structures, and river buffer zones seem to fail repeatedly because they were designed to outdated rainfall patterns. To build resilience, flood protection design must be updated to reflect current and future climates, and factors that were previously ignored, must be incorporated into the respective regulations.

This study presents examples of disasters that lead us to this suggestion, such as the Storm Girionis (2019), Cyclone Ianos (2020), Storm Daniel (2023). It analyzes causes of failures, and discusses an overlooked factor, the role of Intermittent River and Ephemeral Streams (IRES) in increased flash-flood risks, arguing that they must be properly mapped and integrated into flood protection planning.

Moreover, to enhance the suggested redesign of critical infrastructure, this work presents a novel Python‑based tool that automates the generation of design storm hyetographs from watershed shapefiles using Greece’s official gridded intensity‑duration‑frequency (IDF) parameters (Ministry of Environment, 2023). For a chosen storm duration, return period, and time interval, it computes ready‑to‑use hyetographs. Its application is demonstrated at the national scale (10,773 sub‑catchments).

By rapidly producing site‑specific design storms compatible with national standards, Catchment2Storm empowers engineers and planners to redesign flood protection works, bridges, culverts, drainage systems, and buffer zones, based on up‑to‑date climate data. Integrating holistic mapping and updated storm profiles to routine practice, can transform reactive repair approaches to proactive resilience.

The fourth industrial revolution encompasses not only advanced production technologies, but also fields such as nanotechnology, biotechnology, and new materials. Tissue engineering, which involves using various types of fiber scaffolds to grow tissue, overlaps with three of the four fields when nanofibers are used as tissue. Due to their high surface-to-volume ratio, nanofibers are a promising area of research in this field. Biocompatibility plays a decisive role here, which is why the weakly biocompatible polyacrylonitrile (PAN) nanofibers, commonly found in current research, must be combined with biocompatible polymers such as polyethylene oxide (PEO).
Here, we investigated the influence of different molecular weights of PEO in combination with different PAN-PEO ratios on an adherent 3T3 cell line. In order not to compromise the stability of the spun nanofibers, the ratios 9:1 and 8:2 were chosen, which represent a trade-off between PEO content and fiber stability. The molecular weights investigated were 40 kDa, 300 kDa, and 1000 kDa to cover a broad range of available molecular weights. The percentage of the stained cells that grew over the surface was used as a key parameter for successful cell growth and was examined by using optical analysis. The cell growth was investigated after one, two, and three days.
The combination of a 9:1 ratio and a molecular weight of 300 kDa showed the highest percentage of growth. Further investigations with the atomic force microscope showed that the pores created by the water-soluble PEO were particularly uniform in this sample, which provided the cells with the possibility of stronger adhesion.

As smart homes proliferate globally, smart meter energy consumption data has become vital for data-driven decisions, making data quality crucial for reliable analytics. However, smart meter data often contain anomalies such as outliers, missing values, and redundant entries, caused by communication delays, transmission errors, and device malfunctions. These anomalies can significantly compromise the accuracy of applications, including billing, contingency analysis, and energy forecasting. Among them, outliers are particularly detrimental, as they can distort statistical analysis, mislead machine learning models, and undermine overall system reliability. Thus, to address the challenge of detecting outliers in smart home energy consumption effectively, this paper focuses on hourly usage patterns and explores three methods initially: (i) a clustering-based technique using Density-Based Spatial Clustering of Applications with Noise (DBSCAN), (ii) a statistical forecasting model using Auto-Regressive Integrated Moving Average (ARIMA), and (iii) a time series segmentation method using Change Point Detection (CPD). While each method has its strengths, their standalone use is limited in handling the complexity and variability of real-world data. Therefore, to address this issue, this paper proposes three hybrid models, namely ARIMA+DBSCAN, CPD+DBSCAN, and ARIMA+CPD+DBSCAN. These models are designed to leverage temporal forecasting, structural shifts, and density-based clustering to identify both sudden and subtle deviations in energy consumption behavior. Simulations on a public smart home dataset from Kaggle show that the ARIMA+CPD+DBSCAN model outperforms others, achieving 0.96 precision, 0.89 recall, a 0.90 F1-score, and 0.98 accuracy, demonstrating the advantage of integrating statistical and clustering-based methods for robust outlier detection in smart home energy.

The release of CO₂ gas into the atmosphere is one of the most prolific causes of global climate change. To solve this problem, cost-effective technologies are being sought. Polymer membranes are innovative materials that can be widely used in the process of capturing and separating CO₂ gas. In this work, an amine impregnated and amidated solid sorbent (AISS) containing a copolymer (PMMA-co-AA), which consists of acrylic acid (AA) and methyl methacrylate (MMA), and PEPA (polyethylene polyamine), was synthesized. For the first time, sorbents based on homopolymers and copolymers of acrylic acid and methyl methacrylate were compared for their ability to capture CO₂ gas. Other thanthe synthesis of low swelling AISS, a calculation of its energy consumption, and a comparison of its cyclic capacity with 30% water solutions of monoethanolamine and methyldiethanolamine (MEA and MDEA) were performed. The solid sorbent PMMA-co-AAS showed a higher cyclic capacity than others, corresponding to the order PMMA-co-AAS (23 mg/g) > PAAS (16 mg/g) > MDEA (10 mg/g) > MEA (6 mg/g). The average absorption rate for these sorbents was in the sequence of MEA > PMMA-co-AAS > PAAS > MDEA at 40 °C, and the desorption rates were PMMA-co-AAS > PAAS > MDEA > MEA for these sorbents at 70 °C, correspondingly. When the amount of acrylic acid in the copolymer was varied from 0 to 100%, its water absorption capacity varied from 0.2 to 1359.63%, respectively. Among them, the swelling ability of the chosen sorbent prepared from the 10% AA-containing copolymer and PEPA was 0.64%.

Helicobacter pylori (H. pylori) is a Gram-negative bacterium that colonizes the gastric mucosa and plays a central role in the development of peptic ulcers, chronic gastritis, and gastric cancer. A significant portion of the global population is infected, emphasizing the need for early detection and effective treatment strategies. Natural compounds, especially green tea flavonoids (GTFs), have recently gained attention as promising anti-H. pylori agents. Among them, Epigallocatechin Gallate (EGCG), the major catechin in green tea, shows notable inhibitory effects on H. pylori growth and colonization through mechanisms such as membrane disruption, enzyme inhibition, and oxidative stress modulation. Additionally, the antioxidant and anti-inflammatory properties of GTFs may help mitigate H. pylori-induced gastric inflammation. In this computational study, we employed molecular docking simulations using AutoDock Vina to evaluate the binding potential of key GTFs against H. pylori virulence factors CagA and VacA. EGCG exhibited a docking score of −198.72 kcal/mol against CagA, while Theaflavin-3-gallate scored −177.19 kcal/mol against VacA, indicating strong binding affinities. These in silico results suggest that GTFs, particularly EGCG, may effectively target H. pylori pathogenic proteins and impair their function. Overall, the findings support the therapeutic potential of GTFs and highlight the value of computational approaches in screening natural antibacterial compounds.

This study reports the structural, morphological, and magnetic characterization of two magnetic samples, 8 nm maghemite nanoparticles (MCRES) and MCRES plus zeolite type 5A (MCZ0), the last one developed for Cd²⁺ remediation. Both materials were synthesized via eco-friendly methods using ferruginous precursors and Citrus reticulata peel extract. X-ray diffraction confirmed the presence of maghemite as the dominant magnetic crystalline phase in both samples. The MCRES sample did not exhibit additional diffraction peaks associated with residual precursor phases, whereas MCZ0 displayed improved crystallinity due to the presence of zeolite 5A. Transmission electron microscopy revealed distinct surface morphologies: MCRES featured 2D quasi-spherical nanoparticles, while MCZ0 showed better particle dispersion with more defined contours. Magnetic characterization through vibrating sample magnetometry demonstrated soft ferromagnetic behavior, with MCZ0 exhibiting a lesser saturation magnetization (M_s) of 23 emu g⁻¹ at 300 K than MCRES (M_s ~ 62 emu g⁻¹ at 300 K), suggesting efficient magnetic recovery potential. Fourier transform infrared spectroscopy (FTIR) confirmed the presence of functional groups associated with natural organic residues in MCRES, while MCZ0 showed reduced organic content due to thermal treatment. These findings highlight that the MCZ0 composite, owing to its enhanced crystallinity, reduced organic interference, and superior magnetic response, is a promising candidate for sustainable pollutant removal of Cd²⁺ from aqueous systems. The study provides evidence that the magnetic hybrid significantly uptakes up to 99% for an initial concentration of 50 mg L⁻¹, pH=6, and adsorbent dose of 1.7 g L⁻¹.