Archivio Istituzionale della Ricerca- Università del Salento
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The economic thought on women in post-unified Italy and the liberal conception of emancipation of women journalists (1861–1902)
No full textThe representation of women in post-unified Italy, in society in general and in the economic sphere in particular, is the main topic of this contribution. Women liberal journalists, such as Beccari, Mozzoni and Maslova, proposed a “new” way of interpreting the theme of women’s economic role. They linked the issue of work participation to the request for equal political rights between men and women and discussed the economic categories used by economists to limit the presence of women in the labour market. Their contributions were aimed at questioning the model that assigned women to a predominantly domestic economic role
A Real-Time IoT-Based System for Solar Energy Forecasting and Automated Anomaly Notifications
No full textEnergy efficiency is crucial in modern society, particularly in residential settings where photovoltaic (PV) systems enable users to generate electricity and reduce costs. However, without accurate solar energy forecasting, PV systems often operate below optimal efficiency, impacting energy management in smart grids and residential systems. In recent years, IoT and Machine Learning techniques have significantly improved energy monitoring by providing tools to track production. Despite the demonstrated efficacy of existing solutions, there is a lack of real-time systems that combine dashboard visualization with automated notifications for notifying overproduction, underproduction, or inadequate power generation due to weather conditions. This paper presents an IoT-based platform for solar energy production forecasting that integrates a) a data acquisition module to acquire real-time meteorological and production data, b) a Machine Learning module to forecast production, c) a dashboard to show the collected information, and d) a notification system to notify production anomalies (overproduction, underproduction, or potential malfunctions). Forecasting is performed using an ensemble of Support Vector Regression (SVR), Random Forest, Ridge Regression, and Kernel Ridge Regression, improving robustness against data variability and demonstrating the enhancements that ensemble Learning can bring compared to individual models. The proposed solution is validated on a real-world photovoltaic system, contributing to the overall enhancement of the research in smart energy management, and offering a scalable IoT framework for optimizing renewable energy production
Ageing of Red Wine (cv. Negroamaro) in Mediterranean Areas: Impact of Different Barrels and Apulian Traditional Amphorae on Phenolic Indices, Volatile Composition and Sensory Analysis
Get PDFThis study investigated the impact of different ageing containers on the volatile composition and quality of Negroamaro wine, a key variety from Apulia, Italy. Seven vessel types were evaluated: traditional Apulian amphorae (ozza), five types of oak barrels (American oak, French oak, European oak, a French + European oak and a multi-wood mix) and glass bottles as the control. The impact of the vessels was evaluated after 6 months of ageing through the characterization of phenolic, volatile and sensory profiles. Amphorae allowed a specific evolution of the wine’s primary aromas, such as fruity and floral notes, while enhancing volatile compounds like furaneol, which contributed to caramel and red fruit nuances, and also 3-methyl-2,4-nonanedione, a key compound related to anise, plum and premature ageing, depending on its concentration. This container also demonstrated effectiveness in stabilizing anthocyanin–tannin complexes, supporting color stabilization. Oak barrels allowed different outcomes to be obtained in terms of color stabilization, volatile profile, aroma and astringency. French oak exhibited the highest phenolic and tannin levels, enhancing anthocyanin stabilization and color intensity. European oak followed closely, while American oak excelled in color stabilization, with tannins less reactive to polymers. Mixed wood barrels showed lower phenolic extraction and the best astringency evolution
Maradona, secular god of the Mediterranean: sporting legend and identity cohesion in post-championship Naples
Get PDFA deep-learning approach to parameter fitting for a lithium metal battery cycling model, validated with experimental cell cycling time series
Get PDFSymmetric coin cell cycling is an important tool for the analysis of battery materials, enabling the study of electrode/electrolyte systems under realistic operating conditions. In the case of metal lithium SEI growth and shape changes, cycling studies are especially important to assess the impact of the alternation of anodic–cathodic polarization with the relevant electrolyte geometry and mass-transport conditions. Notwithstanding notable progress in analysis of lithium/lithium symmetric coin cell cycling data, on the one hand, some aspects of the cell electrochemical response still warrant investigation, and, on the other hand, very limited quantitative use is made of large corpora of experimental data generated in electrochemical experiments. This study contributes to shedding light on this highly technologically relevant problem, thanks to the combination of quantitative data exploitation and Partial Differential Equation (PDE) modelling for metal anode cycling. Toward this goal, we propose the use of a Convolutional Neural Network-Long-Short Term Memory (CNN-LSTM) to identify relevant physico-chemical parameters in the PDE model and to describe the behaviour of simulated and experimental charge–discharge profiles. Specifically, we have carried out parameter identification tasks for experimental data regarding the cycling of symmetric coin cells with Li chips as electrodes and LP30 electrolyte. Representative selection of numerical results highlights the advantages of this new approach with respect to traditional Least Squares fitting
Integrability properties and multi-kink solutions of a generalised Fokker–Planck equation
Get PDFWe analyse a generalised Fokker-Planck equation in which both the nonlinear terms and the diffusivity are non-trivially dependent on the density and its derivatives. The key feature of the equation is its integrability, for it is linearisable through a Cole-Hopf transformation. We determine solutions of travelling wave and multi-kink type by resorting to a geometric construction in the regime of small viscosity. The resulting asymptotic solutions are time-dependent Heaviside step functions representing classical (viscous) shock waves. As a result, line segments in the space of independent variables arise as resonance conditions of exponentials and represent shock trajectories. We then discuss fusion and fission dynamics exhibited by the multi-kinks by drawing parallels in terms of shock collisions and scattering processes between particles, which preserve total mass and momentum. Finally, we propose Bäcklund transformations and examine their action on the solutions to the equation under study
Virtual Fencing for Safety-Critical Cyber-Physical Systems: Computer-Vision Enabled Digital Twins
Get PDFEarly warning zones (EWZs) are pivotal for future crowd management in smart cities, leveraging computer vision to transform dynamic environments into controllable cyber-physical systems. This approach aims to restrict unsafe or threatening movements by creating EWZs that enhance the resilience of critical infrastructures and ensure citizen safety. While conventional virtual fencing uses GPS-based solutions for outdoor zone-monitoring or surveillance of densely populated areas, as well as fixed cameras for indoor environments (e.g., museums), this article explores the use of computer vision and Uncrewed Aerial Vehicles (UAVs) to create risk-ranked EWZs. These zones can safeguard critical infrastructure and densely populated areas by using UAVs (where fixed cameras are not installed), thus promising to enhance crowd management and safety in smart cities. In this study, the EWZs are categorized by risk levels, with the proximity to hazardous areas determining the severity from low to high. This tiered structure allows for appropriate and timely responses to potential threats, thereby ensuring a robust early warning mechanism. A physical testbed was constructed to monitor human movement as a reflection of behavior within this cyber-physical-social environment. Experiments simulating virtual fence (V-fence) crossings demonstrated the system’s effectiveness in providing early warnings. The results also showed that the system successfully tracked multiple persons through a lightweight framework that can be deployed at the edge, ensuring real-time surveillance and response
Emergency politics and de-democratization in the age of authoritarian neoliberalism
No full textThis book enquires into the state of health of contemporary democracies, offering a sociological reading of democracy to identify the causes of the current transformation of democracy from a social and cultural perspective. With attention to the social dynamics present in modern Western societies, it analyses phenomena
such as populism, new conspiracy theories and denialism, and processes including de-politicisation and de-democratisation. Identifying the centrality of questions concerning social identity and the political imaginary to our understanding of such phenomena, Democracies on the Move explores the mechanisms that link
the transformations of today’s societies to the current phase of crisis in Western democracies. It will therefore appeal to scholars of social and political theory and political sociology
Optimized Scheduling of IoT Devices in Healthcare Facilities: Balancing Cost and Quality of Care
Get PDFFeatured Application: This study optimizes the allocation and scheduling of IoT devices for patient monitoring in healthcare. Utilizing NSGA-II, it minimizes costs while maximizing quality of care, ensuring efficient resource use. The findings assist healthcare facility administrators in improving patient tracking and operational efficiency in dynamic healthcare settings. This paper addresses the critical challenge of optimal allocation and scheduling of Internet of Things (IoT) tracking devices for patient monitoring in healthcare facilities, where limited resources must be efficiently distributed to minimize cost and maximize care quality. We formulate this healthcare management problem as a specialized variant of the Resource-Constrained Scheduling Problem that incorporates patient-specific factors such as duration of stay and priority. After establishing the computational complexity of the problem, we propose a Non-dominated Sorting Genetic Algorithm II (NSGA-II) to address the complex problem of balancing multiple objectives: cost minimization and quality of care maximization. Our approach offers a set of optimal trade-offs, enabling informed decision-making to select the best final solution. Computational experiments conducted on both simulated scenarios and real-world healthcare facility datasets demonstrate that our approach outperforms existing methods, achieving between 1.2 and 3.0 times more solutions than the state of the art. Moreover, in comparison to manual scheduling by medical center managers, our method achieves cost savings of up to 12% (with an average of 6.3%) and quality improvements of up to 20% (with an average of 10%) across the tested experiments. The proposed method scales effectively to realistic healthcare settings with varying numbers of patients and tracking devices, maintaining solution quality while keeping computational time within practical limits for daily operational use. Our findings contribute to both healthcare operations research and clinical practice by providing an efficient methodology for optimizing the use of limited monitoring resources while prioritizing patient safety
La consulenza tecnica preventiva. Modelli processuali
No full textL'a. affronta le problematiche derivanti dall’intro-
duzione, nel rito civile, dell’istituto della consulenza tecnica preventiva
e delle successive declinazioni, tese a risolvere l’esponenziale aumento
di ricorsi nel contenzioso previdenziale e medico-sanitario. L’apparente
cornice cautelare che, in forza dell’assonanza con l’accertamento tecnico,
sembrava caratterizzare il modello dell’art. 696-bis c.p.c., è stemperata e
annullata dalle ricostruzioni della giurisprudenza costituzionale che ne
individua il carattere prettamente contenzioso e dalla scelta, compiuta ex
ante dal legislatore, di privilegiare l’inedita funzionalità conciliativa affi-
data al consulente tecnico d’ufficio, anche nella forma della condizione
di procedibilità, al fine di giungere alla soluzione concordata della lite,
sostitutiva della sentenza