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European black pine (Pinus nigra Arn. subsp. nigra) persists in scattered montane stands across Greece, where isolated populations harbour genetic variation shaped by local environments and demographic history. In this study, we assessed the genetic diversity and population structure of P. nigra using nuclear microsatellite markers (nSSRs) across four populations: Mt. Athos, Sithonia, Thassos, and Perama. A total of 67 individuals were genotyped, and seven high-quality polymorphic loci were retained after rigorous filtering. The Mt. Athos population exhibited the highest allelic richness and heterozygosity, with all loci being polymorphic and a low inbreeding coefficient after null allele correction. In contrast, the Perama population displayed reduced diversity, fewer polymorphic loci, and persistent heterozygote deficits. Principal Component Analysis (PCA) and Discriminant Analysis of Principal Components (DAPC) revealed weak overall population structure, with Perama genetically distinct from the other sites. Spatial Principal Component Analysis (sPCA) further uncovered an east–west cline within Athos and localized structure potentially shaped by both natural isolation and human influence. These findings highlight regional variation in genetic diversity within P. nigra and identify Athos as a genetically rich population of particular interest. The results provide a foundation for long-term monitoring and support informed strategies for the management and conservation of P. nigra in Greece.

South European and Mediterranean countries traditionally suffer from water scarcity, especially the regions around the Mediterranean. In Cyclades, the effects of drought have historically been observed and tackled with small-scale applications, with the most efficient method being rainwater harvesting (RWH). RWH is an inherent aspect of the local population’s culture and architecture, since most houses have built-in water tanks and flat roofs to harvest as much rainwater as possible. In recent decades, the increase in local population and tourism have added additional stress to the limited water resources of the Cycladic islands. To overcome water shortages, most of the islands are equipped with desalination plants. Despite the use of these plants, RWH is still a vital source of water that is free and has zero carbon footprint. Thus, it is important to compare, assess and quantify the performance of this traditional water conserving method as a key water source for the islands’ water resources management, today and for the coming decades. In this research, we investigate and quantify the future performance of rainwater harvesting applications and their contribution to continuous, sustainable, and climate-resilient water supply. The results show a decrease in rainwater harvesting potential in most of the islands, as well as the negative effect of touristic activity on per capita water availability on the islands.

This paper introduces a climatic multi-hazard risk assessment for Greece, as the first-ever attempt to enhance scientific knowledge for the identification and definition of hazards, a critical element of risk-informed decision making. Building on an extensively validated climate database with a very high spatial resolution (5 × 5 km2), a detailed assessment of key climatic hazards is performed that allows for: (a) the analysis of hazard dynamics and their evolution due to climate change and (b) direct comparisons and spatial prioritization across Greece. The high geographical complexity of Greece requires that a large number of diverse hazards (heatwaves—TX, cold spells—TN, torrential rainfall—RR, snowstorms, and windstorms), need to be considered in order to correctly capture the country’s susceptibility to climate extremes. The current key findings include the dominance of cold-temperature extremes in mountainous regions and warm extremes over the coasts and plains. Extreme rainfall has been observed in the eastern mainland coasts and windstorms over Crete and the Aegean and Ionian Seas. Projections of the near future reveal more warm extremes in northern areas becoming more dominant all over the country by the end of the century.

Future fire weather conditions under climate change were investigated based on the Fire Weather Index (FWI), Initial Spread Index (ISI) and threshold-specific indicators in Greece. The indices were calculated from climate datasets derived from high-resolution validated simulations of 5 km. The dynamical downscaled simulations with the WRF model were driven by EC-Earth output for historical (1980–2004) and future periods, under two Representative Concentration Pathways (RCPs), RCP4.5 and 8.5. The analysis showed that the FWI is expected to increase substantially, particularly in the southern parts with extreme values found above 100. In addition, the number of days with an FWI above the 90th percentile is projected to increase considerably (above 30 days), under both scenarios. Over the eastern and northern mainland, the increase is estimated with more than 70 days under RCP4.5, in the near future (2025–2049). Moreover, central and north-eastern parts of the country will be affected with 30 or more extreme consecutive days of prolonged fire weather, under RCP4.5, in the near future and under RCP8.5 in the far future (2075–2099). Finally, the expected rate of fire spread is more spatially extended all over the country and particularly from southern to northern parts compared to the historical state.

An ever-growing amount of accumulated data has materialized in several scientific fields, due to recent technological progress. New challenges emerge in exploiting these data and utilizing the valuable available information. Causal models are a powerful tool that can be employed towards this aim, by unveiling the structure of causal relationships between different variables. The causal structure may avail experts to better understand relationships, or even uncover new knowledge. Based on 963 patients with coronary artery disease, the robustness of the causal structure of single nucleotide polymorphisms was assessed, taking into account the value of the Syntax Score, an index that evaluates the complexity of the disease. The causal structure was investigated, both locally and globally, under different levels of intervention, reflected in the number of patients that were randomly excluded from the original datasets corresponding to two categories of the Syntax Score, zero and positive. It is shown that the causal structure of single nucleotide polymorphisms was more robust under milder interventions, whereas in the case of stronger interventions, the impact increased. The local causal structure around the Syntax Score was studied in the case of a positive Syntax Score, and it was found to be resilient, even when the intervention was strong. Consequently, employing causal models in this context may increase the understanding of the biological aspects of coronary artery disease.

Background: Common clinical practice for the provision of parenteral nutrition of neonates is to administer the nutrients in separate solutions. The aim of this study was to introduce and examine an alternative way of parenteral feeding for neonates, providing all-in-one parenteral regimes. Methods: Stability studies were carried out on 2 all-in-one admixtures. Stability assays consisted of the assessment of the admixture's (1) macroscopic aspect, (2) drop size measurement, (3) pH measurement, (4) peroxide value, and (5) α-tocopherol concentration. For the measurements, the admixtures were stored at 2 different temperatures, 4°C (storage) and 25°C (compounding), and then analyzed at a starting time, 24 hours, 48 hours, and 7 days after compounding. Results: The 2 all-in-one parenteral admixtures for neonates were shown to be physically stable under analysis conditions, and there were no particles larger than 1μ m. The maximum loss of α-tocopherol was approximately 24%. In all-in-one admixtures, lipid peroxide occurred within 24 hours after the addition of the lipid emulsion. Conclusions: The addition of fat emulsion and fat-soluble vitamins did not alter the physical stability of parenteral admixtures for neonates. Moreover, the admixtures examined were relatively chemically stable for 24 hours, as far as vitamin E is concerned. Lipid peroxidation was the limiting factor for application stability of an all-in-one neonatal parenteral regimen. All-in-one parenteral admixtures have been shown to be advantageous clinically and economically. This study intended to introduce all-in-one parenteral regimes for neonates.

Recent advances in the efficiency and robustness of algorithms solving convex quadratically constrained quadratic programming (QCQP) problems motivate developing techniques for creating convex quadratic relaxations that, although more expensive to compute, provide tighter bounds than their classical linear counterparts. In the first part of this two-paper series [Strahl et al., 2024], we developed a cutting plane algorithm to construct convex quadratic underestimators for twice-differentiable convex functions, which we extend here to address the case of non-convex difference-of-convex (d.c.) functions as well. Furthermore, we generalize our approach to consider a hierarchy of quadratic forms, thereby allowing the construction of even tighter underestimators. On a set of d.c. functions extracted from benchmark libraries, we demonstrate noteworthy reduction in the hypervolume between our quadratic underestimators and linear ones constructed at the same points. Additionally, we construct convex QCQP relaxations at the root node of a spatial branch-and-bound tree for a set of systematically created d.c. optimization problems in up to four dimensions, and we show that our relaxations reduce the gap between the lower bound computed by the state-of-the-art global optimization solver BARON and the optimal solution by an excess of 90%, on average.

When computing bounds, spatial branch-and-bound algorithms often linearly outer approximate convex relaxations for non-convex expressions in order to capitalize on the efficiency and robustness of linear programming solvers. Considering that linear outer approximations sacrifice accuracy when approximating highly nonlinear functions and recognizing the recent advancements in the efficiency and robustness of available methods to solve optimization problems with quadratic objectives and constraints, we contemplate here the construction of quadratic outer approximations of twice-differentiable convex functions for use in deterministic global optimization. To this end, we present a novel cutting-plane algorithm that determines the tightest scaling parameter, \\(\\alpha\\), in the second-order Taylor series approximation quadratic underestimator proposed by Su et al. We use a representative set of convex functions extracted from optimization benchmark libraries to showcase--qualitatively and quantitatively--the tightness of the constructed quadratic underestimators and to demonstrate the overall computational efficiency of our algorithm. Furthermore, we extend our construction procedure to generate even tighter quadratic underestimators by allowing overestimation in infeasible polyhedral regions of optimization problems, as informed by the latter's linear constraints.