Fault Control on a Thermal Anomaly: Conceptual and Numerical Modeling of a Low\u2010Temperature Geothermal System in the Southern Alps Foreland Basin (NE Italy)

The interest on low\u2010temperature geothermal resources is progressively increasing since their renewability and widespread availability. Despite their frequency, these resources and their development have been only partially investigated. This paper unravels the major physical processes driving a low\u2010temperature geothermal resource in NE Italy (Euganean Geothermal System) through conceptual and numerical modeling. Dense fracturing associated to regional fault zones and a relay ramp enhances regional to local flow of thermal waters. Their rapid upwelling in the Euganean Geothermal Field is favored by open extensional fractures deforming the relay ramp. The water (65\u201386 \ub0C) is intensively exploited for balneotherapy, rendering it a profitable resource. Three\u2010dimensional coupled flow and heat transport numerical simulations based on this conceptual model are performed. Despite the presence of a uniform basal heat flow, a thermal anomaly corresponding to field observations develops in the modeling domain reproducing the relay ramp. Intensive fracturing extending across a wide area and a slightly anomalous heat flow favors a local increase in convection that drives the upwelling of deep\u2010seated hot waters. The simulations corroborate and refine the conceptual model, revealing that water of up to 115 \ub0C is likely to be found in the unexplored part of the thermal field. This study furthers knowledge on fault\u2010controlled low\u2010temperature geothermal resources where the geological setting could enhance local convection without anomalous heat flows, creating temperatures favorable for energy production. Conceptual and numerical modeling based on solid geological and hydrogeological reconstructions can offer a support tool for further detailed explorations of these prominent resources

defining the hydrogeological behavior of karst springs through an integrated analysis a case study in the berici mountains area vicenza ne italy

Knowledge of the hydraulic and geological properties of karst systems is particularly valuable to hydrogeologists because these systems represent an important source of potable water in many countries. However, the high heterogeneity that characterizes karst systems complicates the definition of karst hydrogeological properties, and their estimation involves complex and expensive techniques. In this study, a workflow for karst spring characterization was used to analyze two springs, Nanto spring and Mossano spring, located in the Berici Mountains (NE Italy). Based on the data derived from 4 years of continuous hourly monitoring of discharge, water temperature and specific electrical conductivity, a hydrogeological conceptual model for the monitored springs was proposed. Flow rate measurements, which combined recession curve, flow duration curve and autocorrelation function techniques, were used to evaluate the spring discharge variability. Changes in spring discharge can be related both to the degree of karstification/permeability and to the size of the karst aquifer. Moreover, combining monitored parameters and rainfall—analyzed by the cross-correlation function and VESPA (Vulnerability Estimator for Spring Protection Areas) index approach—permitted assessment of the spring response to recharge and the behavior of the drainage system. Although the responses to the recharge events were quite similar, the two springs showed some differences in terms of the degree of karstification. In fact, Mossano spring showed a more developed karst system than Nanto spring. Three systems (two karsts and one matrix/fractured) are outlined for Mossano spring, while two systems (one karst and one matrix/fractured) are outlined for Nanto spring

Chronic constipation diagnosis and treatment evaluation: The "CHRO.CO.DI.T.E." study

Background: According to Rome criteria, chronic constipation (CC) includes functional constipation (FC) and irritable bowel syndrome with constipation (IBS-C). Some patients do not meet these criteria (No Rome Constipation, NRC). The aim of the study was is to evaluate the various clinical presentation and management of FC, IBS-C and NRC in Italy. Methods: During a 2-month period, 52 Italian gastroenterologists recorded clinical data of FC, IBS-C and NRC patients, using Bristol scale, PAC-SYM and PAC-QoL questionnaires. In addition, gastroenterologists were also asked to record whether the patients were clinically assessed for CC for the first time or were in follow up. Diagnostic tests and prescribed therapies were also recorded. Results: Eight hundred seventy-eight consecutive CC patients (706 F) were enrolled (FC 62.5%, IBS-C 31.3%, NRC 6.2%). PAC-SYM and PAC-QoL scores were higher in IBS-C than in FC and NRC. 49.5% were at their first gastroenterological evaluation for CC. In 48.5% CC duration was longer than 10 years. A specialist consultation was requested in 31.6%, more frequently in IBS-C than in NRC. Digital rectal examination was performed in only 56.4%. Diagnostic tests were prescribed to 80.0%. Faecal calprotectin, thyroid tests, celiac serology, breath tests were more frequently suggested in IBS-C and anorectal manometry in FC. More than 90% had at least one treatment suggested on chronic constipation, most frequently dietary changes, macrogol and fibers. Antispasmodics and psychotherapy were more frequently prescribed in IBS-C, prucalopride and pelvic floor rehabilitation in FC. Conclusions: Patients with IBS-C reported more severe symptoms and worse quality of life than FC and NRC. Digital rectal examination was often not performed but at least one diagnostic test was prescribed to most patients. Colonoscopy and blood tests were the "first line" diagnostic tools. Macrogol was the most prescribed laxative, and prucalopride and pelvic floor rehabilitation represented a "second line" approach. Diagnostic tests and prescribed therapies increased by increasing CC severity

Active inference, causal cognition, and structure in the world

In the most general terms, causal cognition could be defined as information processing that involves, more or less explicitly, an appreciation of a notion of causality on the part of an intelligent agent. To a first approximation, appreciating a notion of causality might involve any combination of abilities such as the understanding, exploitation, discovery, and construction of cause-effect relationships (among other things). An agent with that kind of sensitivity could be called a causal agent.Active inference is a theoretical framework developed by Karl Friston and colleagues over many years to account for the computational function(s) of the nervous system and, more fundamentally, self-organization and sentience in complex systems (Friston, 2005, 2019; Friston & Kiebel, 2009; Parr et al., 2020, 2022). Several mathematical formulations of the framework have been used to explain neurocognitive activity in different domains and applied to model neural and behavioural data in computational cognitive neuroscience (Adams et al., 2013; Buckley et al., 2017; Da Costa et al., 2020; Friston, FitzGerald, Rigoli, Schwartenbeck, & Pezzulo, 2017; Friston et al., 2010; Mirza et al., 2016, 2019; Parr & Friston, 2017; Pezzulo et al., 2015, 2018; Seth & Friston, 2016). Also, it has received a lot of philosophical attention and the core ideas have been popularised with the names of predictive processing (PP) and prediction error minimization (PEM) (Clark, 2013, 2016; Hohwy, 2013, 2020; Wiese & Metzinger, 2017).The fundamental and overarching idea of active inference is that information processing in the brain can be seen as a manifestation of some kind of pervasive predictive activity that approximates (hierarchical) Bayesian inference (Friston, 2008; Friston, FitzGerald, Rigoli, Schwartenbeck, & Pezzulo, 2017; Friston, Parr, & de Vries, 2017; Lee & Mumford, 2003). The brain is thought to implement and continuously refine a (hierarchical) generative model of sensory information (Kiefer & Hohwy, 2018). In active inference circles, it is ofthen claimed that an agent equipped with such a generative model is capable of inferring the causes of sensory signal and/or learn about causal structure in the world (see, e.g., Clark, 2016, p. 171; Friston, 2012, p. 2101; Hohwy, 2013, p. 228). Claims like the above may persuasively suggest that active inference agent are causal agent in the sense introduced at the outset; in other words, the overarching theoretical power of active inference would also throw light on causal cognition.The main goal of the dissertation is to look deep into those claims and ascertain whether they stand up to scrutiny. This will be accomplished in two different ways. First, research from the field of causal machine learning will provide important theoretical coordinates against which to clarify notions like causes and causal structure, and give a sense of how (machine) learning methods can be deployed to discover them from observations (Burgess et al., 2018; Higgins, Matthey, et al., 2017; Schölkopf & von Kügelgen, 2022; Schölkopf et al., 2012, 2021). Second, research on causal cognition in non-human and human animals will form a bedrock of behavioural data on which to base experimentally informed distinctions about different levels or dimensions of causal cognition (Penn & Povinelli, 2007; Starzak & Gray, 2021; Visalberghi & Tomasello, 1998; Woodward, 2011). By combining these different (but related) approaches to dissect active inference as far as causal cognition is concerned, the outcome will be a more refined understanding of the extent to which active inference agents can be regarded as causal agents.</p

3D hydrogeological reconstruction of the fault-controlled Euganean Geothermal System (NE Italy)

Data for geothermics paper submissio

Outcome of adrenal vein sampling and computed tomography guided adrenalectomy in primary aldosteronism

none4noneCrimì, Filippo; Torresan, Francesca; Iacobone, Maurizio; Rossi, Gian PaoloCrimì, Filippo; Torresan, Francesca; Iacobone, Maurizio; Rossi, Gian Paol

3D hydrogeological reconstruction of the fault-controlled Euganean Geothermal System (NE Italy)

Assessing the renewability of geothermal and hydrogeological resources is a particular requirement for their future preservation. The sustainable exploitation of a geothermal resource for its long-term utilization is related to both the water demand and the hydrogeological characteristics of the geothermal field, while its renewability is influenced by the geological and hydrogeological processes that enhance the groundwater flow. Numerical modeling can be successfully used to assess both the impacts of processes occurring in the geothermal system and the renewability of associated resources. However, the reliability of a numerical simulation is influenced by the accuracy of the dataset used to reproduce the geological system. A 3D hydrogeological reconstruction model, rather than a simplified conceptualization of the geological setting, can increase the consistency of the modeling results. In the case of the Euganean Geothermal System (NE Italy), a detailed reconstruction was performed to quantitatively reproduce the hydrogeological elements that allow the development of the geothermal system and to estimate the amount of thermal waters stored in the reservoir. The structural setting of the central Veneto region, in particular the high-angle NNW-trending faults of the Schio-Vicenza Fault System, plays a fundamental role in the existence of the Euganean Geothermal System, permitting hydraulic connection between the recharge area and the exploitation field. In addition, regional- and local-scale faults and fractures favor fluid convection, which represents the main process that warms thermal fluids. Reproducing such a complex geological setting in a 3D model allows improving knowledge about the features that characterize the geothermal system and attaining a solid framework for the construction of a 3D regional numerical model that will be used to assess the renewability of the system