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Ocular microvascular changes in COVID-19: role of hypoxia, D-dimer, IL-6 and systemic treatment
No full textBackgroundThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been associated with endothelial dysfunction, which may also compromise the microcirculation within ocular tissues. This prospective study evaluated associations between radial peripapillary capillary (RPC) vessel density (VD) and systemic treatment, age, hypoxia, D-dimer, and interleukin-6 (IL-6) levels in patients recovering from coronavirus disease 2019 (COVID-19) related pneumonia.MethodsSixty-three individuals who were admitted to the hospital due to COVID-19 bilateral pneumonia underwent ophthalmic examination two months post-discharge. RPC VD was measured using optical coherence tomography angiography. Associations with age, arterial hypertension, and systemic treatment (dexamethasone, remdesivir, and oxygen therapy), oxygen saturation, D-dimer, and IL-6 levels were evaluated. The control group comprised 43 control participants with no history of COVID-19 who attended routine ophthalmic examinations.ResultsNo ophthalmic abnormalities were detected. RPC VD did not differ significantly with hypertension or systemic treatment with dexamethasone and remdesivir. However, patients receiving oxygen therapy had higher RPC VD. A borderline inverse correlation was observed between inferior RPC VD and age. There were no correlations between RPC VD and oxygen saturation. Significant inverse correlations were found between nasal RPC and mean RPC with D-dimer levels and between inferior RPC VD and IL-6 levels. No significant differences in RPC parameters were observed when comparing the COVID-19 group with controls.ConclusionsHypertension or systemic treatment had no significant effect on RCP VD. However, VD in specific RPC areas correlated inversely with D-dimer and IL-6 levels, highlighting the need for monitoring peripapillary microvasculature for potential long-term ocular effects of COVID-19
Determinants of visitors’ flow in Uruguay: A SARIMAX approach
No full textUnderstanding the factors that shape the data-generating process of visitor flows is crucial for evaluating the past, present, and future dynamics of this vital economic activity. This study employs the SARIMAX approach to analyse the determinants of inbound international tourism demand in Uruguay, using quarterly data from 1996 to 2019. The research identifies key factors such as national and relative prices, as well as economic performance, that influence visitors' inflows. The results indicate that stochastic shocks accumulate over time, affecting future outcomes. These findings provide valuable insights for policymakers in promoting international and domestic tourism
Material Synergies and Industrial Symbiosis to Valorize Granite Scraps from Quarries in Sardinia
No full textA Speed-Invariant Template-Based Approach for Estimating Running Temporal Parameters Using Inertial Sensors
No full textSegmentation of running data into gait cycles and stance/swing phases is crucial for evaluating running biomechanics. The benefit of magneto-inertial sensors is their ability to capture data in outdoor conditions. However, state-of-the-art inertial-based methods for estimating running temporal parameters are limited to a restricted range of running speeds and, thus, not able to analyze running at very variable speeds. This limitation prevents their use for real-world analysis for a wide range of runners and for sports disciplines where athletes vary their running speed. This study evaluated the speed-dependance of eight relevant foot-mounted inertial-based methods from previous research and proposed a novel method that could be robust to speed changes. The proposed method applied, for the first time, a template-matching algorithm based on dynamic time warping to running analysis and compared it to existing methods. All the implemented methods were tested on 30 runners at different speeds ranging from jogging to sprinting (8 km/h, 10 km/h, 14 km/h, 19-30 km/h) on both treadmill and overground. The most speed-robust performance was achieved by the proposed template-based method, providing estimation errors below 0.1% in stride, between 7%-19% in stance, and between 3%-6% in swing across running speeds. Conversely, all the tested methods from the literature were proved to be significantly speed-dependent. Thus, this study suggested that template-based approach is a valid solution for the inertial-based estimation of temporal parameters during running from slow jogging to fast sprinting. MATLAB codes and templates have been made available online
Real-time, non-invasive monitoring of IoT 4.0-based indicators for animal management on farms, in relation to different physiological and production stages
No full textThe ongoing digital transformation driven by Industry 4.0 has initiated a paradigm shift in animal husbandry, fostering the integration of cyber-physical systems, sensor technologies, and data analytics within livestock production systems. This dissertation investigates the deployment of Internet of Things (IoT)-enabled tools within the framework of Precision Livestock Farming (PLF), with the objective of developing and validating non-invasive, real-time monitoring systems capable of capturing physiological, morphological, and metabolic indicators in two distinct yet complementary animal models: honeybee colonies (Apis mellifera) and dairy cattle (Bos taurus).
Leveraging automated three-dimensional (3D) modeling and imaging methodologies, this research elucidates the application of contactless technologies for characterizing animal health and nutritional status across varying physiological states. In Apis mellifera, morphometric analyses performed via 3D scanning revealed statistically significant divergences (p < 0.01) in thoracic width and abdominal volume between forager and nurse bees, reflecting task-specific metabolic allocation and resource utilization within the colony. The classification model achieved an accuracy of 92.5% in caste differentiation, with a 95% confidence interval ranging from 89.3% to 95.1%, thereby demonstrating the feasibility of high-resolution, in vivo phenotyping in apicultural settings.
In dairy cattle, 3D body surface reconstruction techniques were integrated with metabolic biomarker profiling to refine body condition score (BCS) estimation. The automated system exhibited >93% concordance with expert visual assessment and yielded a root mean square error (RMSE) of 0.32 on a 5-point BCS scale. Model confidence was estimated at 96% (95% CI: 94.4–97.8%). Furthermore, strong correlations were observed between BCS and serum concentrations of NEFA and BHB (p < 0.001), particularly in multiparous cows during early lactation, highlighting the system’s sensitivity in detecting energy imbalance and metabolic stress.
The empirical findings substantiate the potential of IoT-driven PLF approaches to enhance the precision, efficiency, and ethical sustainability of animal monitoring systems. By enabling continuous, individualized surveillance with minimal disruption, these technologies offer a robust framework for evidence-based decision-making and adaptive management. The research underscores the critical role of digitalization in advancing sustainable livestock production and affirms the necessity of cross-disciplinary integration to address the multifactorial challenges of modern animal agricultureThe ongoing digital transformation driven by Industry 4.0 has initiated a paradigm shift in animal husbandry, fostering the integration of cyber-physical systems, sensor technologies, and data analytics within livestock production systems. This dissertation investigates the deployment of Internet of Things (IoT)-enabled tools within the framework of Precision Livestock Farming (PLF), with the objective of developing and validating non-invasive, real-time monitoring systems capable of capturing physiological, morphological, and metabolic indicators in two distinct yet complementary animal models: honeybee colonies (Apis mellifera) and dairy cattle (Bos taurus).
Leveraging automated three-dimensional (3D) modeling and imaging methodologies, this research elucidates the application of contactless technologies for characterizing animal health and nutritional status across varying physiological states. In Apis mellifera, morphometric analyses performed via 3D scanning revealed statistically significant divergences (p < 0.01) in thoracic width and abdominal volume between forager and nurse bees, reflecting task-specific metabolic allocation and resource utilization within the colony. The classification model achieved an accuracy of 92.5% in caste differentiation, with a 95% confidence interval ranging from 89.3% to 95.1%, thereby demonstrating the feasibility of high-resolution, in vivo phenotyping in apicultural settings.
In dairy cattle, 3D body surface reconstruction techniques were integrated with metabolic biomarker profiling to refine body condition score (BCS) estimation. The automated system exhibited >93% concordance with expert visual assessment and yielded a root mean square error (RMSE) of 0.32 on a 5-point BCS scale. Model confidence was estimated at 96% (95% CI: 94.4–97.8%). Furthermore, strong correlations were observed between BCS and serum concentrations of NEFA and BHB (p < 0.001), particularly in multiparous cows during early lactation, highlighting the system’s sensitivity in detecting energy imbalance and metabolic stress.
The empirical findings substantiate the potential of IoT-driven PLF approaches to enhance the precision, efficiency, and ethical sustainability of animal monitoring systems. By enabling continuous, individualized surveillance with minimal disruption, these technologies offer a robust framework for evidence-based decision-making and adaptive management. The research underscores the critical role of digitalization in advancing sustainable livestock production and affirms the necessity of cross-disciplinary integration to address the multifactorial challenges of modern animal agriculture
Mutuo o pactum de non petendo ad tempus: la parola alle Sezioni Unite
No full textLe Sezioni Unite della Corte di Cassazione sono chiamate a pronunciarsi in tema di mutuo finalizzato al ripianamento di pregresse esposizioni del mutuatario verso lo stesso soggetto finanziatore.
In alcune occasioni, infatti, la stessa Corte ha negato la qualificazione della fattispecie in termini di mutuo, qualificandola, per contro, in termini di pactum de non petendo ad tempus e, sul punto, si registra dunque la presenza di un contrasto giurisprudenziale.
Il saggio analizza le diverse tesi a riguardo, concludendo per la mera residualità della qualificazione in termini di pactum de non petendo ad tempus, stante la non incompatibilità del contratto di mutuo con la funzione solutoria
L'uso del tempo dei direttori generali nella Pubblica Amministrazione italiana. Uno studio esplorativo della Presidenza del Consiglio dei Ministri
No full textDirectors General (DGs) play a key role in Italian public administration, yet little is known about their agenda and daily activities. We use a survey instrument to explore how the DGs in the Presidency of the Council of Ministers organize their average week. We find that they work very long hours, mostly administrative tasks, even if they aspire to a more strategic workflow. At the same time, we also find a focus on relational approaches towards their teams and employees, which appears to indicate some penetration by traditional New Public Management and New Public Governance principles in the organization. However, this remains an «incomplete transition», limiting the organization’s capacity for innovation and strategic developmen
