Carbon Nanodots from an In Silico Perspective

Carbon nanodots (CNDs) are the latest and most shining rising stars among photoluminescent (PL) nanomaterials. These carbon-based surface-passivated nanostructures compete with other related PL materials, including traditional semiconductor quantum dots and organic dyes, with a long list of benefits and emerging applications. Advantages of CNDs include tunable inherent optical properties and high photostability, rich possibilities for surface functionalization and doping, dispersibility, low toxicity, and viable synthesis (top-down and bottom-up) from organic materials. CNDs can be applied to biomedicine including imaging and sensing, drug-delivery, photodynamic therapy, photocatalysis but also to energy harvesting in solar cells and as LEDs. More applications are reported continuously, making this already a research field of its own. Understanding of the properties of CNDs requires one to go to the levels of electrons, atoms, molecules, and nanostructures at different scales using modern molecular modeling and to correlate it tightly with experiments. This review highlights different in silico techniques and studies, from quantum chemistry to the mesoscale, with particular reference to carbon nanodots, carbonaceous nanoparticles whose structural and photophysical properties are not fully elucidated. The role of experimental investigation is also presented. Hereby, we hope to encourage the reader to investigate CNDs and to apply virtual chemistry to obtain further insights needed to customize these amazing systems for novel prospective applications

Genome-wide meta-analysis identifies five new susceptibility loci for pancreatic cancer.

In 2020, 146,063 deaths due to pancreatic cancer are estimated to occur in Europe and the United States combined. To identify common susceptibility alleles, we performed the largest pancreatic cancer GWAS to date, including 9040 patients and 12,496 controls of European ancestry from the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4). Here, we find significant evidence of a novel association at rs78417682 (7p12/TNS3, P = 4.35 × 10-8). Replication of 10 promising signals in up to 2737 patients and 4752 controls from the PANcreatic Disease ReseArch (PANDoRA) consortium yields new genome-wide significant loci: rs13303010 at 1p36.33 (NOC2L, P = 8.36 × 10-14), rs2941471 at 8q21.11 (HNF4G, P = 6.60 × 10-10), rs4795218 at 17q12 (HNF1B, P = 1.32 × 10-8), and rs1517037 at 18q21.32 (GRP, P = 3.28 × 10-8). rs78417682 is not statistically significantly associated with pancreatic cancer in PANDoRA. Expression quantitative trait locus analysis in three independent pancreatic data sets provides molecular support of NOC2L as a pancreatic cancer susceptibility gene

Design of hierarchical ring networks

Consiglio Nazionale delle Ricerche (CNR). Biblioteca Centrale / CNR - Consiglio Nazionale delle RichercheSIGLEITItal

Optimization of ring network design: an overview

Lavoro eseguito nell'ambito della Convenzione in atto tra l'Amministrazione delle Poste e Telecomunicazioni e la Fondazione Ugo Bordoni. Relazione FUB: 4B00491SIGLEITItal

An Event-Driven Agent-Based Simulation Model for Industrial Processes

Process manufacturing industries are complex and dynamic systems composed of several processes, subject to many operations and unexpected events that can compromise overall system performance. Therefore, the use of technologies and methods that can transform traditional process industries into smart factories is necessary. In this paper, a smart industrial process based on intelligent software agents is presented with the aim of providing a technological solution to the specific needs of the process industry. An event-driven agent-based simulation model composed of eight reactive agents was designed to simulate and control the operations of a generic industrial process. The agents were modeled using the actor approach and the communication mechanism was based on the publish–subscribe paradigm. The overall system was tested in different scenarios, such as faults, changing operating conditions and off-spec productions. The proposed agent-based simulation model proved to be very efficient in promptly reacting to different dynamic scenarios and in suitably handling different situations. Furthermore, the usability and the practicality of the proposed software tool facilitate its deployment and customization to different production chains, and provide a practical example of the use of multi-agent systems and artificial intelligence in the context of industry 4.0

Le dépotoir B1 de la villa de Richeaume (Puyloubier, 13). Nouvelle approche archéométrique pour la caractérisation des céramiques provençales

International audienceA petrographic and mineralogical study has been performed on potteries from a late IVth century AD dump, of a Roman villa near Aix-en-Provence. Among well known imported wares, this dump provided a series of regionally or locally produced red slip wares and coarse wares. Several fabric groups have been identified, based on petrographic thin section analyses and magnetic mineralogical analyses. This latter method combines magnetic susceptibility measurement, hysteresis loops acquisition with associated parameters and Natural remanent magnetization (NRM), Anhysteretic remanent magnetization (ARN), and Isothermal remanent magnetization (IRM) measurements and stepwise alternating field demagnetization. Through the determination of grain size and magnetochemistry of iron oxides, these approaches enabled us to create new regional/local pottery groups and to identify different sub-fabrics in already known ceramic groups. This integrated archaeological and archaeometrical survey enriches our knowledge of the Aix-en-Provence ceramic production during the late 4th century AD. Such results show the relevance of a multidisciplinary approach in ceramic identification.Une étude pétrographique et minéralogique a été réalisée sur de la vaisselle céramique d'un dépotoir de la fin du IVe siècle après J.-C. dans une villa romaine près d'Aix-en-Provence. L'étude des productions céramiques de ce dépotoir a révélé, parmi des productions importées et régionales connues, de nouvelles productions de céramiques sigillées et communes d'origine probablement locale ou régionale. Plusieurs groupes de pâte ont pu être élaborés sur la base de descriptions pétrographiques en lame mince au microscope optique et par la détermination de la minéralogie magnétique. Cette dernière approche combine mesures de susceptibilité magnétique, acquisition de courbes d'hystérésis avec calcul de paramètres caractéristiques et des mesures de l'Aimantation Rémanente Naturelle (ARN), Anhystérétique (ARA) et Isotherme (ARI) ainsi que leur désaimantation pas à pas par champ alternatif croissant. On déduit ainsi des caractéristiques concernant la granulométrie et la magnétochimie des oxydes de fer permettant aussi bien d'identifier de nouvelles productions au sein du dépotoir que de distinguer différents sous-types de pâtes au sein d'un groupe donné, enrichissant notre connaissance des productions de céramiques de cette région à la fin du IVe siècle apr. J.-C. Les résultats obtenus montrent la pertinence d'une approche pluridisciplinaire dans l'identification des céramiques

Application du magnétisme des roches à l’étude archéométrique des céramiques provençales

International audienc

Multi-agent systems to improve efficiency in steelworks

A multi-agent system consists of several computational entities capable of autonomous actions, called agents, which communicate with each other, and have the ability to coordinate their actions and to cooperate. Multi-agent systems received a great interest and attention over time, as they can be seen as a key enabling technology for complex applications, where distributed and processing of data, autonomy, and high degree of interactions in dynamic environments are required at the same time. Therefore, in view of current and future developments of the digitalization of industrial production cycles promoted by Industry 4.0, multi-agent systems are foreseen to play an increasing role for industrial production management and optimization. Because of barriers represented by large presence of legacy systems, in the steel sector agent-based technology is not widely applied yet, and multi-agent systems applications are very few. On the other hand, steel manufacturing industries are complex and dynamic systems whose production processes held a strategic role in the global economy. During last decades, the steel sector has undergone relevant transformations, especially through the massive digitalization and the innovation introduced by Industry 4.0. A further evolution is foreseen in the incoming years to improve the sustainability of the production cycle by improving energy and resource efficiency. Therefore, steel industries must face several challenges on the path toward the factory of the future. In such context multi-agent systems, through their intrinsic properties, such as autonomy, social abilities, reactivity, proactivity, and mobility, can overcome existing drawbacks and barriers, by increasing flexibility, improving resources efficiency, handling production operations, reacting to unpredicted events, optimizing production processes, and supporting legacy systems. In this paper, some applications of multi-agent systems in steel sector are presented to show the advantages and opportunities of agent-based technology