In this paper, we propose a numerical method to construct an approximate solution to Fredholm integral equations of the first kind. These equations are common in image processing, spectroscopy, and other engineering sciences but are often ill-posed. Moreover, the right hand side of such equations could be error-contaminated. To effectively tackle the mentioned challenges, we propose suitable quadrature rules to discretize the continuous problem.The resulting discrete system is solved in a regularized least-squares framework by adopting the Deep-QLP factorization: a novel algorithm that automatically computes an approximate truncated singular value decomposition based on a user-defined tolerance. Additionally, two regularization approaches are introduced. In the first one, given a perturbed right-hand side, a Hankel matrix is constructed and then, the so-called de-Hankelization is performed by adopting the same Deep-QLP algorithm. In the second approach, we rely on locally refined discretization spaces to increase the accuracy of the computed approximate solution, by keeping low the number of the used degrees of freedom. Numerical experiments are conducted on some famous Fredholm integral equations available in the literature.
Large-scale urban afforestation is increasingly promoted as a Nature-Based Solution for reducing urban heat. Yet afforestation does not cool cities uniformly, and the conditions under which it delivers sustained thermal benefits remain poorly understood. This uncertainty limits the ability of planners to design and manage effective afforestation strategies. Using the Beijing Plain Area Afforestation Programme (BPAP) as a large-scale natural experiment, we combined satellite observations, a paired-site framework, and surface-energy-balance analysis to investigate how thermal responses to afforestation evolved between 2015 and 2023. Most afforested sites experienced progressive cooling, but approximately 37% followed warming trajectories. Cooling developed gradually through a maturation process and was consistently associated with increasing latent heat flux, whereas warming sites exhibited limited improvement in evapotranspirative functioning over time. These contrasting trajectories indicate that thermal performance depends not simply on tree establishment, but on the capacity of afforested ecosystems to develop and sustain key biophysical functions. Our findings indicate that cooling from large-scale urban afforestation is conditional rather than universal. They provide a transferable framework for landscape planning by shifting attention from tree-cover targets toward ecosystem performance, long-term monitoring, and site-specific management under increasing climatic and hydrological constraints.
Sea-level reconstructions are critical benchmarks for testing models of ice-sheet stability and climate change. Their interpretation, however, is complicated by sea-level changes driven by different processes, among which include the solid Earth's response to sediment loading. Here we show that incorporating sediment isostastic adjustment reduces long-standing discrepancies among Marine Isotopic Stage (MIS) 5a and 5e records from the Rio de la Plata estuary by up to an order of magnitude, indicating that regional sedimentary histories can shift relative sea-level estimates by several meters compared to traditional glacial isostatic adjustment-based approaches. We further emphasize how sediment loading may play an important role in influencing relative sea level throughout the Holocene and may continue to affect regional modern tide-gauge records. These findings underscore the importance of regionally resolved sedimentation histories, in contrast to approaches based solely on global compilations, and highlight the need for expanded shelf coring and seismic surveys.
Grapevine (Vitis vinifera L.) productivity is highly sensitive to water deficit, a condition of increasing concern in Mediterranean viticulture. The cultivar ‘Italia’, one of the most economically important table grapes in southern Italy, was selected to investigate physiological and molecular responses to drought. Six candidate genes previously identified in transcriptomic analyses (VvPP2C4, VvPP2C8, VvGolS1, VvGolS2, VvHSP18, and VvRD26) were analyzed using quantitative real-time PCR under controlled water stress conditions. The results revealed significant changes in expression, with four genes showing marked differential regulation, particularly those related to ABA signaling and osmoprotection. These findings provide the first targeted validation of candidate drought-responsive genes in ‘Italia’, highlighting their functional role and offering valuable information for breeding strategies aimed at improving grapevine resilience and sustainability under climate change.
Flood events represent a major natural threat, and identifying the key factors contributing to flood occurrence has gained considerable attention in 2010 and 2022 in the Swat River, Pakistan. In this study, Google Earth Engine was utilized to extract flood-related indices for the Mohmand Dam catchment, Pakistan. Different types of datasets were used to calculate fourteen influencing parameters. These indices were processed and normalized in ArcMap 10.8 and Python to enhance their visual and analytical representation. Two multi-criteria analyses with AHP, FAHP, and five machine learning models, including logistic regression, K-nearest neighbors, random forest, support vector machine, and multi-layer perception, were applied to determine the relative importance of each parameter and produce a flood susceptibility map. The results indicate that rainfall, LULC, and soil texture are the most influential factors, each contributing 11.11% to flood susceptibility. The random forest approach demonstrated stronger predictive performance than the AHP and FAHP techniques. The flood susceptibility map reveals that approximately 31.67% (4320.40 km2) of the study area falls under high flood risk. This methodology provides valuable support for planners, policymakers, hydrologists, and disaster management authorities in developing effective flood mitigation, watershed management, and resilience strategies.
