Instituto Andaluz de Ciencias de la Tierra

• Trustworthy AI is a prerequisite for deploying FL in high-risk, multi-stakeholder domains. • Privacy-preserving guarantees alone are insufficient to sustain trust in agentic and dynamic FL systems. • We present a requirement-driven taxonomy of challenges aligned with Trustworthy AI principles, explicitly extended to agentic AI and LLM-enabled settings. • We present a coordination blueprint maps Trustworthy AI requirements to FL-native controls and decision-centric, auditable evidence across the lifecycle. • We reframe trust in FL as a continuously maintained operating condition and introduce coordination tools to operationalize it. • We propose Trust Report 2.0 to operationalize trust as evidence, not assumptions, by surfacing what decisions were made, why, and under which constraints, without centralizing raw data. Federated Learning (FL) enables privacy-preserving collaborative learning, yet deployments increasingly show that privacy guarantees alone do not sustain trust in high-risk settings. As FL systems move toward agentic AI, large language model–enabled, and dynamically adaptive architectures, trustworthiness becomes a system-level problem shaped by autonomous decision-making, non-stationary environments, and multi-stakeholder governance. We argue for Trustworthy FL (TFL), treating trust as a continuously maintained operating condition rather than a static model property. Through the lens of Trust Report 2.0, we propose a requirement-driven taxonomy of challenges grounded in TAI and explicitly extended to account for control-plane decisions, agency, and system dynamics across the federated lifecycle. Building on this diagnosis, we introduce a coordination blueprint that structures cross-requirement trade-offs, decision justification, and governance alignment in TFL systems. To operationalize assurance, Trust Report 2.0 is instantiated as a lightweight, privacy-preserving artifact that surfaces decision-centric trust evidence without centralizing raw data. We illustrate applicability via healthcare as a stress-test domain, focusing on oncology FL under regulatory pressure and clinical risk.

Analyzing conflicts between multiple objects within fuzzy information systems (ISs) and providing effective conflict resolution are challenging tasks due to the complexity and uncertainty of the real world. This article proposes a three-way conflict analysis and resolution model for intuitionistic fuzzy ISs (IFISs) based on three-way concept analysis (3WCA). First, the straight and vertical distances between intuitionistic fuzzy values (IFVs) are defined to obtain an intuitionistic fuzzy probability-credibility distribution. Second, intuitionistic fuzzy optimistic and pessimistic formal contexts are proposed based on two novel binary relations of intuitionistic fuzzy information. Afterward, two intuitionistic fuzzy concept lattices are obtained to analyze the marginal conflict degrees among multiple objects via consistency, inconsistency, and uncertainty attribute sets. By introducing three pairs of thresholds, the trisections of object pairs, objects, and attributes are derived through the three-way decision (3WD) process. Specifically, the maximal alliance unit, minimal conflict unit, and feasible strategy set are identified according to the three-way conflict analysis results. Subsequently, the consistency measure extracted from the intuitionistic fuzzy distance matrix is utilized to rank all feasible strategies. Finally, the experimental results are conducted to verify the effectiveness, superiority, and feasibility of the proposed model.

The Cerro de Agrás volcanic cone (Cofrentes, Spain) is a ~2 Ma monogenetic effusive edifice, approximately 1 km wide and ~100 m high. It is dominated by pyroclastic deposits with subordinate meter-sized fragments of alkali basaltic lava, such as spatter flows, suggestive of a Strombolian eruptive style. The alkali basalts are aphanitic and display a porphyritic texture, with prevailing olivine as phenocrysts partially altered to iddingsite. The alkali basalts host small (0.5-4 cm) rounded-to-irregularly shaped ultramafic xenoliths of medium-grained spinel lherzolites with a protogranular texture, characterized by coarse olivine and orthopyroxene crystals (2–3 mm) and finer clinopyroxene and spinel grains (250–300 µm). Olivine shows homogeneously high Mg# [(Mg/Mg+Fe) = 0.90 to 0.94], whereas clinopyroxene diopside display slightly lower Mg# (0.91 to 0.92) and low Al (0.16-0.22 apfu) but noticeable Ca (0.85 to 0.95 apfu). Orthopyroxenes are enstatites with Mg# varying from 0.90 to 0.94. Spinels are Al- and Mg-rich, with Al# (Al/(Al+Cr)) ranging from 0.77 to 0.79 and Mg# ranging from 0.69-0.77. Thermobarometric calculation using the mineral compositions suggests temperatures between 1100 to 1150 °C and pressures ranging 15 to 18 kbar; very likely related with partial melting at ca. 50 km depth. Typically, the rims of the xenoliths, exhibit spongy textures where orthopyroxene is partially replaced by olivine + clinopyroxene. Here, newly-formed olivine grains yield lower Mg# 0.77-0.88 wheras clinopyroxene is augite with lower Ca (0.56 -0.83 apfu) and Mg# (0.95 to 1.00). These features seem to suggest the reaction of preexisting orthopyroxene with a non-equilibrium incoming host alkali basalt during xenolith ascent to surface.

Water vapour is a crucial and highly variable greenhouse gas in the Earth's atmosphere that plays a major role in the radiative balance, energy transport and photochemical processes. It can also affect the radiative budget indirectly through cloud formation and by altering the size, shape, and chemical composition of aerosol particles. Moreover, monitoring water vapour remains challenging due to its high temporal and spatial variability. Consequently, systematic and accurate observations of water vapour are essential to improve our understanding of its role at both local and global scales and for enhancing climate projections.Advances in remote sensing techniques have enabled continuous acquisition of precipitable water vapour (PWV) measurements using sun/star photometry, microwave radiometry and the Global Navigation Satellite System (GNSS). Nevertheless, none of these instruments provides information on the vertical distribution of water vapour, a critical information considering that water vapour concentrations typically vary by up to three orders of magnitude between the surface and the upper troposphere. In this context, Raman lidar has demonstrated its ability to capture the spatial and temporal evolution of water vapour in the troposphere. Accurate retrievals of the water vapour mixing ratio from Raman lidar measurements rely on robust and well-characterised calibration procedures as well as on an accurate estimation of the differential atmospheric transmission term, which accounts for extinction differences between the molecular reference (nitrogen and oxygen) and water vapour wavelengths.In this study, the lidar calibration constant was determined using a hybrid calibration method, which combines correlative PWV measurements for lidar calibration with Numerical Weather Prediction (NWP) data to reconstruct the water vapour profile within the incomplete overlap region of the lidar system. The differential transmission was estimated using an automated method to account for the aerosol contribution, based on sun photometer Aerosol Optical Depth (AOD) measurements and an exponential decay function with attitude to model aerosol extinction (Díaz-Zurita et al., 2025). Subsequently, a long-term database of water vapour profiles over the period 2009-2022 was generated, providing high vertical and temporal resolution measurements of water vapour over the city of Granada, in Southern Spain. A comprehensive statistical analysis was conducted to characterise the vertical distribution of water vapour over a 14-year period, representing the first long-term vertical characterisation of water vapour in this region. Mean interannual and seasonal water vapour profiles were derived for the entire study period, and trend analyses were performed to assess long-term variations in water vapour content in the lower troposphere. Additionally, lidar-derived PWV values were compared with those obtained from microwave radiometer and GNSS observations.This research was funded by Grant PID2021-128008OB-I00 funded by MICIU/AEI/ 10.13039/501100011033 by ERDF/EU European Union, and by the Spanish national projects CNS2023-145435, PID2023-151817OA-I00 and Marie Skłodowska-Curie Staff Exchange Actions with the project GRASP-SYNERGY (grant agreement no. 10113163). Diaz-Zurita et al. (2025). Remote Sens. 2025, 17(20), 3444; https://doi.org/10.3390/rs17203444

Ongoing climate change and increasing anthropogenic pressures are intensifying the challenges associated with the sustainable management of groundwater resources, particularly in Mediterranean regions characterized by pronounced climatic seasonality and recognized as climate change hot spots. Groundwater springs often represent a critical resource for local communities, serving both as a source of high-quality drinking water and as a key component of socio-ecological systems. Understanding the functioning, vulnerability, and resilience of the groundwater systems feeding these springs is therefore essential for effective and sustainable water management.This study presents the first results of an ongoing investigation in the Municipality of Capannori (Lucca, Tuscany, central Italy), where publicly accessible springs are widely used for domestic water supply and have become the focus of increasing conservation efforts by local authorities. The collection of water from local springs represents a shared practice in this region that fosters a strong sense of community and reinforces the concept of water as a common good. Ensuring the sustainable management of these resources, therefore, requires a comprehensive understanding of groundwater systems, achievable through multidisciplinary approaches integrating isotopic fingerprinting with geochemical and hydrogeological tools.A two-year monitoring programme started in April 2024 and involves 19 groundwater springs distributed across three hydrogeological sectors. Groundwater samples were collected for chemical and isotopic analysis (δ18O and δ2H), while temperature, pH, electrical conductivity and redox potential were measured in the field. Tritium and δ34S-δ18O-SO4 were determined on selected samples, and compositional data analysis (CoDA) was applied to the chemical dataset. In addition, a rain sampler was installed in February 2024 to collect monthly precipitation samples for isotopic analysis.The results highlight pronounced chemical and isotopic heterogeneity among springs across the three hydrogeological sectors, reflecting the complexity of the groundwater systems involved. This heterogeneity points to distinct flow paths, water-rock interaction processes, and recharge dynamics, and suggests potentially different sensitivities of individual springs to hydroclimatic variability and anthropogenic pressures. From a management perspective, these differences imply that springs commonly perceived as part of a single resource may in fact exhibit contrasting levels of vulnerability under ongoing and future environmental change.Stable water isotope data, together with deuterium excess, provide robust constraints on the recharge elevations of the aquifers feeding the springs, allowing the identification of recharge areas and the possible extent of recharge catchments. At the same time, part of the observed isotopic variability may reflect a climatic signal related to recharge seasonality rather than elevation alone. However, seasonal isotopic shifts were negligible across all springs, indicating well-mixed recharge systems and relatively slow groundwater circulation that dampens the pronounced isotopic variability of precipitation. Consistently, tritium values show no significant differences among springs (2.5-2.9 TU), indicating young groundwater with residence times not exceeding 5-10 years.Overall, this study demonstrates how integrated isotopic and geochemical approaches can provide process-based insights that are directly relevant for groundwater protection and management under changing hydroclimatic conditions.

The climate action plan has enhanced the demand for critical minerals and metals, such as those found in ore deposits associated with ultramafic-mafic magmas (e.g. platinum group elements, Ni, Cu, Co, V and Ti). A growing demand for these metals is spurring many countries to explore new geological areas, as well as to more fully investigate existing deposits. This special volume contains 11 chapters covering a wide range of topics, organized thematically, which provide new information concerning the genetic links between mineralization and magmatism that will improve our scientific understanding of orthomagmatic ore formation processes.

Computational fluid dynamics (CFD) has been widely used to study cerebrospinal fluid (CSF) flow in Chiari Malformation Type I (CM-I). However, most approaches rely on limited patient-specific detail, and it remains unclear whether such minimal input is sufficient to yield physiologically realistic flow predictions. In this study, we construct a series of MRI-based models of the craniocervical CSF space in a CM-I patient, complemented with representations of microanatomical features derived from ex vivo measurements and patient MRI data, to assess how CFD predictions are influenced by the choice of boundary conditions in the numerical integrations and the inclusion or omission of nerve roots and denticulate ligaments in the anatomical model. Our results reveal that while increasing patient-specific detail in boundary conditions improves agreement with velocity fields measured via phase-contrast MRI, key flow features—most notably anterior–posterior compartmentalization and bidirectional patterns during flow reversal—only emerge when denticulate ligaments are included in the model. In contrast, inclusion of nerve roots has a more localized effect on the velocity field and a modest impact on pressure drops. Our findings not only clarify how more detailed boundary conditions and improved anatomical fidelity affect velocity and pressure predictions, but also provide a mechanistic explanation for flow patterns commonly observed in CM-I that have remained unexplained, highlighting the critical role of denticulate ligaments.