Integrating subdivision schemes into SVM for improved signal classification

The integration of advanced signal processing techniques into machine learning models has gained increasing attention due to its potential to improve model performance, particularly for classification tasks. Support Vector Machine (SVM) is widely recognized as a powerful tool for signal classification due to its robust mathematical foundation and effectiveness in handling high-dimensional data. Subdivision schemes, originally developed in computer graphics for geometric modeling, offer a novel and parametric approach to feature preprocessing by iteratively refining input data through an efficient computational procedure. This paper studies the impact of subdivision schemes on SVM performance in terms of class separability and provides insights into the relationship between feature transformation and SVM response. Specifically, it investigates the theoretical and empirical implications of applying subdivision schemes to input features in SVM-based classification. The conditions under which these schemes preserve or enhance class separability are analyzed, focusing on the tension parameter which governs both the smoothness properties of the limit curve and the subdivision rule at each iteration. An estimation method for the tension parameter from the training data is also provided. Experimental results, performed in the context of signal classification based on the wavelet scattering transform, demonstrate that the appropriate selection of the tension parameter of the scheme can significantly enhance class separability, highlighting that subdivision schemes are a promising tool for improving classification accuracy in machine learning workflows

Twisted string actuators: Comprehensive review on modeling, design innovations, application advances, and future challenges

Twisted string actuators (TSAs) have emerged as a promising class of soft actuators with diverse applications in fields such as robotics, biomedical engineering, and wearable technology. This review article provides an overview of recent advancements in TSA technology, discusses the challenges associated with their implementation, and explores potential future directions in research and development. Key topics covered include the working principles and mathematical models of TSAs, design solutions, materials selection, fabrication techniques, control, applications, limitations, and avenues for further innovation. By examining the current state of TSA research, this article aims to stimulate discussion and inspire new avenues of exploration in this exciting field

Development and optimisation of influenza C and influenza D pseudotyped viruses

To facilitate the study of influenza C (ICV) and influenza D (IDV) viruses, we generated lentiviral pseudotyped viruses (PVs) expressing the hemagglutinin-esterase fusion (HEF) glycoprotein from ICV (C/Minnesota/33/2015) and IDV (D/Swine/Italy/199724–3/2015, D/Bovine/France/5920/2014, and D/Bovine/Ibaraki/7768/2016). The production of these PVs was optimised using different amount of human airway trypsin-like (HAT) protease to enhance HEF maturation, and the transduction efficiency was evaluated in multiple cell lines. Using these PVs, we established a pseudovirus-based microneutralisation (pMN) assay to measure neutralising antibody responses and adapted an esterase activity assay to evaluate PV. Specific antisera neutralised PVs but failed to inhibit esterase activity. These findings confirm that ICV and IDV PVs provide a scalable, sensitive, and safe tool for antiviral screening, and sero-epidemiological research

Corte internazionale di giustizia

La voce descrive la storia, il funzionamento e l'evoluzione dei poteri della Corte internazionale di giustizia. Si concentra principalmente sul ruolo della Corte come garante della corretta applicazione del diritto internazionale in conformità alle norme della Carta delle Nazioni Unit

The contribution of cryptocurrencies to portfolio diversification

Cryptocurrencies have attracted significant attention due to their high risk, extreme volatility, regulatory controversies, and scandals. Investors and policymakers are drawn to them for their potential to enhance diversification and deliver high returns. This study examines the impact of incorporating cryptocurrencies into investment portfolios, focusing on their ability to improve risk-adjusted returns and diversification. A rolling asset allocation strategy employing the maximum Sharpe Ratio within a Markowitz framework was applied to weekly data from 2018 to April 2024. The analysis compares two unconstrained portfolios and two constrained portfolios, which impose a concentration limit on cryptocurrency investments. Results reveal that in 70% of the rolling periods examined, portfolios with cryptocurrency allocations outperformed non-cryptocurrency portfolios in terms of Sharpe Ratios. However, the heightened volatility of cryptocurrencies significantly increased portfolio risk, with annualized weekly standard deviations ranging from 18% to 25%, compared to 12% to 15% for portfolios without cryptocurrency exposure. These findings illustrate the dual nature of cryptocurrencies: they can act as both a source of instability and an opportunity for diversification. The study underscores the necessity of a cautious and strategic approach to incorporating cryptocurrencies into investment plans, given their inherent risks and unpredictable behavior

Spatial distribution and ecological risk of potentially toxic elements in peri-urban soils of a historically industrialised area

The spatial distribution and ecological risk of potentially toxic elements (PTEs) were investigated in the topsoil of a peri-urban area surrounding a historical industrial complex in the Scarlino Plain in southwestern Tuscany, Italy. Superficial (0-5 cm) soil samples from 44 sites within a 1.5-km radius of the industrial district were analysed for As, Cd, Co, Cr, Cu, Hg, Mn, Ni, Pb, Sb, Sn, Tl, V and Zn concentrations after microwave-assisted acid digestion with HNO3 and H2O2. The results revealed significant contamination exceeding regulatory thresholds, predominantly caused by historical pyrite roasting and natural geochemical anomalies. The enrichment of As, Mn, Cu and Zn compared to European baselines was widespread, with As and Zn levels exceeding the Italian screening values in several samples. Principal component analysis identified distinct contamination patterns linked to land use, with the first component (PC1, 49.2% of the variance) associated with pyrite-derived PTEs (As, Cu, Cd, Pb and Zn), whereas PC2 represented geogenic inputs. Despite their combined contribution to soil contamination, this analysis effectively differentiated industrial signatures from those of natural sources. Ecological risk assessment indicated that As and Cd are major concerns in agricultural soils, where anthropogenic and natural sources overlap. These findings underscore the importance of distinguishing between natural and anthropogenic contributions to inform realistic mitigation targets and protect environmental and human health in historically impacted peri-urban areas

Implications of a consumption-based accounting of greenhouse gas emissions from global dairy cattle systems

Greenhouse gas (GHG) emissions from dairy systems at the national level are typically estimated at the point of production, following guidelines for national reporting. However, exploring the emissions allocated to the point of consumption also provides key insights into reducing emissions across all stages (inputs, production, trade, and consumption). In this study, the GHG emissions associated with global dairy cattle products were estimated using a consumption-based accounting approach. The analysis was based on data from 2015, covering 254 territories and considering 21 dairy cattle commodities. Our findings reveal that international trade in dairy products is dominated by a few countries, with the top 20 net importing/exporting countries accounting for about 70% of global emissions embodied in trade. Although, at the global level, GHG emissions embodied in the international trade of dairy cattle products represented a relatively small share of the total (133 Mt CO2 eq, 9%), they were significant at the country level, particularly for countries heavily involved in trade. In some cases, imports accounted for more than 50% of consumption-related emissions. Trade among European Union countries was relevant representing 32% of the global GHG emission linked with the international trade of dairy products. By adopting a system-wide approach, this study aims to provide novel and critical information to reduce GHG emissions from the global dairy sector, contributing to initiatives such as Pathways to Dairy Net Zero. The results are discussed in the context of the importance of dairy products for global food security. The consumption-based analysis presented represents a different and original perspective in the computation of GHG emissions at the national level for a specific and relevant food item. This approach, guiding policymakers in identifying key impact areas across all stages of the supply chain, can foster the transition to low-carbon dairy products, and support circular economy practices

Analysis and development of the modular elements of a tendon-actuated glove for hand rehabilitation

Robotic rehabilitation requires personalized, versatile, and efficient devices to accommodate the diverse needs of patients recovering from motor impairments. In this paper, we focus on hand rehabilitation and analyse a tendon-driven, modular, and adaptable robotic glove actuated by twisted string actuators (TSAs). The proposed solution exploits flexibility in design, allowing customization based on individual patient needs while ensuring effective assistance in hand movements. Specifically, in this paper we investigate the kinematic relationships between tendon-driven actuators and hand motion. We provide a detailed implementation of multiple functional modules within the glove, designed to accommodate various rehabilitation exercises and adapt to different degrees of motor impairment. In addition, we present experimental tests involving a user to evaluate the system’s performance, usability, and effectiveness in facilitating hand movement. The results provide insights into the potential of TSA-driven robotic gloves for enhancing rehabilitation outcomes through a combination of precise actuation and adaptability to user’s needs