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Biaryls are ubiquitous core structures in drugs, agrochemicals and organic materials that have profoundly improved many aspects of our society. Although traditional cross-couplings have made practical the synthesis of many biaryls, C–H arylation represents a more attractive and cost-effective strategy for building these structural motifs. Furthermore, the ability to install biaryl units in complex molecules via late-stage C–H arylation would allow access to valuable structural diversity, novel chemical space and intellectual property in only one step. However, known C–H arylation protocols are not suitable for substrates decorated with polar and delicate functionalities, which are commonly found in molecules that possess biological activity. Here we introduce a class of ruthenium catalysts that display a unique efficacy towards late-stage arylation of heavily functionalized substrates. The design and development of this class of catalysts was enabled by a mechanistic breakthrough on the Ru(ii)-catalysed C–H arylation of N–chelating substrates with aryl (pseudo)halides, which has remained poorly understood for nearly two decades.

The telerehabilitation of patients with neurological lesions has recently assumed significant importance due to the COVID-19 pandemic, which has reduced the possibility of access to healthcare facilities by patients. Therefore, the possibility of exercise for these patients safely in their own homes has emerged as an essential need. Our efforts aim to provide an easy-to-implement and open-source methodology that provides doctors with a set of simple, low-cost tools to create and manage patient-adapted virtual reality telerehabilitation batteries of exercises. This is particularly important because many studies show that immediate action and appropriate, specific rehabilitation can guarantee satisfactory results. Appropriate therapy is based on crucial factors, such as the frequency, intensity, and specificity of the exercises. Our work’s most evident result is the definition of a methodology that allows the development of rehabilitation exercises with a limited effect in both economic and implementation terms, using software tools accessible to all.

The COVID-19 pandemic has heightened awareness of airborne disease susceptibility, leading to the development and adoption of various preventive technologies. Among these, microwave sanitization, which inactivates virions through non-thermal mechanical resonance, has gained significant scientific credibility. Laboratory tests have demonstrated its high efficacy, prompting further investigation into its effectiveness in real-world settings. This study employs multi-physical, fluid-dynamic and electromagnetic simulations of office environments to evaluate the reduction of contagion risk. By integrating these simulations with virus inactivation experimental laboratory results, we observed that the introduction of a microwave sanitization device significantly reduces the risk of contamination among individuals in the same environment. These findings suggest potential applications and further studies in other everyday scenarios.

The oxidative cleavage of alkenes is an integral process that converts feedstock materials into high-value synthetic intermediates 1 – 3 . The most viable method to achieve this in one chemical step is with ozone 4 – 7 ; however, this poses technical and safety challenges owing to the explosive nature of ozonolysis products 8 , 9 . Here we report an alternative approach to achieve oxidative cleavage of alkenes using nitroarenes and purple-light irradiation. We demonstrate that photoexcited nitroarenes are effective ozone surrogates that undergo facile radical [3+2] cycloaddition with alkenes. The resulting ‘ N -doped’ ozonides are safe to handle and lead to the corresponding carbonyl products under mild hydrolytic conditions. These features enable the controlled cleavage of all types of alkenes in the presence of a broad array of commonly used organic functionalities. Furthermore, by harnessing electronic, steric and mediated polar effects, the structural and functional diversity of nitroarenes has provided a modular platform to obtain site selectivity in substrates containing more than one alkene. Oxidative cleavage of alkenes is achieved using nitroarenes and light irradiation as an alternative to using ozone to break the carbon–carbon bonds, avoiding the explosive intermediates formed with ozone.

Boron functional groups are often introduced in place of aromatic carbon–hydrogen bonds to expedite small-molecule diversification through coupling of molecular fragments 1 – 3 . Current approaches based on transition-metal-catalysed activation of carbon–hydrogen bonds are effective for the borylation of many (hetero)aromatic derivatives 4 , 5 but show narrow applicability to azines (nitrogen-containing aromatic heterocycles), which are key components of many pharmaceutical and agrochemical products 6 . Here we report an azine borylation strategy using stable and inexpensive amine-borane 7 reagents. Photocatalysis converts these low-molecular-weight materials into highly reactive boryl radicals 8 that undergo efficient addition to azine building blocks. This reactivity provides a mechanistically alternative tactic for sp 2 carbon–boron bond assembly, where the elementary steps of transition-metal-mediated carbon–hydrogen bond activation and reductive elimination from azine-organometallic intermediates are replaced by a direct, Minisci 9 -style, radical addition. The strongly nucleophilic character of the amine-boryl radicals enables predictable and site-selective carbon–boron bond formation by targeting the azine’s most activated position, including the challenging sites adjacent to the basic nitrogen atom. This approach enables access to aromatic sites that elude current strategies based on carbon–hydrogen bond activation, and has led to borylated materials that would otherwise be difficult to prepare. We have applied this process to the introduction of amine-borane functionalities to complex and industrially relevant products. The diversification of the borylated azine products by mainstream cross-coupling technologies establishes aromatic amino-boranes as a powerful class of building blocks for chemical synthesis. Selective borylation of azines—nitrogen-containing aromatic heterocycles used in the synthesis of many pharmaceuticals—is made possible by forming a radical from an aminoborane using a photocatalyst.

This paper provides a methodology for the production of synthetic images for training neural networks to recognise shapes and objects. There are many scenarios in which it is difficult, expensive and even dangerous to produce a set of images that is satisfactory for the training of a neural network. The development of 3D modelling software has nowadays reached such a level of realism and ease of use that it seemed natural to explore this innovative path and to give an answer regarding the reliability of this method that bases the training of the neural network on synthetic images. The results obtained in the two proposed use cases, that of the recognition of a pictorial style and that of the recognition of men at sea, lead us to support the validity of the approach, provided that the work is conducted in a very scrupulous and rigorous manner, exploiting the full potential of the modelling software. The code produced, which automatically generates the transformations necessary for the data augmentation of each image, and the generation of random environmental conditions in the case of Blender and Unity3D software, is available under the GPL licence on GitHub. The results obtained lead us to affirm that through the good practices presented in the article, we have defined a simple, reliable, economic and safe method to feed the training phase of a neural network dedicated to the recognition of objects and features to be applied to various contexts.

Three different methods that use a single ruthenium catalyst to enable the facile formation of meta - and para -substituted alkenylarenes have now been developed. The reactions proceed through a tandem alkenylation/decarboxylation process and provide several advantages over alternative approaches.

The respiratory cloud of an infected person contains droplets of mucosal and salivary fluid carrying germs. As this cloud spreads from the emission point, droplets accumulate, and their concentration increases in the room, unless dilution, adequate ventilation, or filtration is applied. A susceptible person standing nearby can easily be exposed to this infected cloud, potentially inhaling a higher dose of pathogens compared to someone breathing the room’s mixed air. To mitigate this short-distance risk and potential contagion, a local airflow pattern can be employed. Our study presents a numerical investigation of a desktop fan acting as a barrier to airborne pathogen diffusion at a short distance. Positioned strategically between two individuals seated closely in a confined cubic room, the portable fan generates V-shaped air blades to intercept the respiratory cloud path. Employing a validated CFD tool based on the Eulerian-Lagrangian model for particle transmission and Schiller-Naumann for particle drag force coefficient, we explore the influence of fan axial locations, heights, and power levels on particle transmission efficiency. The results highlight the importance of each parameter in impeding airborne particle transmission. Notably, a mere 0.30 m deviation from the center axis can significantly reduce the fan’s efficacy, from 99% to 29%. Similarly, lowering the fan’s height by 0.30 m from the infected individual’s mouth level decreases transmission efficiency from 99% to 31%. Moreover, varying the fan velocity from 3 m/s to 1.5 m/s yields efficiency fluctuations from 99% to 37%.

This study analyses some of the leading technologies for the construction and configuration of IT infrastructures to provide services to users. For modern applications, guaranteeing service continuity even in very high computational load or network problems is essential. Our configuration has among the main objectives of being highly available (HA) and horizontally scalable, that is, able to increase the computational resources that can be delivered when needed and reduce them when they are no longer necessary. Various architectural possibilities are analysed, and the central schemes used to tackle problems of this type are also described in terms of disaster recovery. The benefits offered by virtualisation technologies are highlighted and are bought with modern techniques for managing Docker containers that will be used to build the back-end of a sample infrastructure related to a use-case we have developed. In addition to this, an in-depth analysis is reported on the central autoscaling policies that can help manage high loads of requests from users to the services provided by the infrastructure. The results we have presented show an average response time of 21.7 milliseconds with a standard deviation of 76.3 milliseconds showing excellent responsiveness. Some peaks are associated with high-stress events for the infrastructure, but the response time does not exceed 2 s even in this case. The results of the considered use case studied for nine months are presented and discussed. In the study period, we improved the back-end configuration and defined the main metrics to deploy the web application efficiently.