Optimization of Potential Field Method Parameters through networks for Swarm Cooperative Manipulation Tasks

An interesting current research field related to autonomous robots is mobile manipulation performed by cooperating robots (in terrestrial, aerial and underwater environments). Focusing on the underwater scenario, cooperative manipulation of Intervention-Autonomous Underwater Vehicles (I-AUVs) is a complex and difficult application compared with the terrestrial or aerial ones because of many technical issues, such as underwater localization and limited communication. A decentralized approach for cooperative mobile manipulation of I-AUVs based on Artificial Neural Networks (ANNs) is proposed in this article. This strategy exploits the potential field method; a multi-layer control structure is developed to manage the coordination of the swarm, the guidance and navigation of I-AUVs and the manipulation task. In the article, this new strategy has been implemented in the simulation environment, simulating the transportation of an object. This object is moved along a desired trajectory in an unknown environment and it is transported by four underwater mobile robots, each one provided with a seven-degrees-of-freedom robotic arm. The simulation results are optimized thanks to the ANNs used for the potentials tuning

Oxygen DX center in In0.17Al0.83N: Nonradiative recombination and persistent photoconductivity

Using a hybrid density-functional scheme, we address the O impurity substitutional to N (O-N) in In0.17Al0.83N. Our modelling supports In clustering to account for the strong band-gap bowing observed in InxAl1-xN alloys. To study the ON defect in In0.17Al0.83N alloys, we therefore consider a model containing an In cluster and find that the most stable configuration shows four In nearest neighbors. We show that such a ON defect forms a DX center and gives rise to two defect levels at 0.70 and 0.41 eV below the conduction band edge, in good agreement with experiment. The calculated defect energetics entail a fast nonradiative recombination upon photoexcitation at room temperature and account for the observation of persistent photoconductivity at low temperature. Published by AIP Publishing

entos: A Quantum Molecular Simulation Package

entos is designed for ab initio MD simulations of molecular and condensed-phase chemical reactions and other processes, with particular focus on mean-field and quantum embedding methods for electronic structure. The entos software package is developed in the C++14 programming language with a structure that enables flexibility (by providing a long-term sustainable platform for development of methods in this area), efficiency (via task-based multi-threaded parallelism), and rigorous software engineering standards

entos: A Quantum Molecular Simulation Package

entos is designed for ab initio MD simulations of molecular and condensed-phase chemical reactions and other processes, with particular focus on mean-field and quantum embedding methods for electronic structure. The entos software package is developed in the C++14 programming language with a structure that enables flexibility (by providing a long-term sustainable platform for development of methods in this area), efficiency (via task-based multi-threaded parallelism), and rigorous software engineering standards

All in the Game. The Wire: un campo di ricerca sociologica

Analyzing with an ethnographic approach The Wire, one of the most important TV series on American ghettos, to understand and question the sociological perspective that emerges from the series, positioning it into the broader scientific debate. This is, in a nutshell, the work presented in the book It's all in the Game, the outcome of a laboratorial research activity carried out in 2020 by students and teachers of the Sociology of Communities and Urban Neighborhoods class, at the University of Bologna. The text is structured into four chapters, resulting from the four topics used to analysis the TV series: forms of social capital, the relationship between structural forces- culture of poverty and individual agency, neighborhood effects mechanism and the relationship between statistics and political action. Four subjects that are the core of many neighborhood- studies related researches and on which the TV series makes a clear stand. We analyzed those topics through a critical perspective, not considering them as a truth about ghettos, but as a very precise way of thinking about life in the American suburbs

Acute Delta Hepatitis in Italy spanning three decades (1991–2019): Evidence for the effectiveness of the hepatitis B vaccination campaign

Updated incidence data of acute Delta virus hepatitis (HDV) are lacking worldwide. Our aim was to evaluate incidence of and risk factors for acute HDV in Italy after the introduction of the compulsory vaccination against hepatitis B virus (HBV) in 1991. Data were obtained from the National Surveillance System of acute viral hepatitis (SEIEVA). Independent predictors of HDV were assessed by logistic-regression analysis. The incidence of acute HDV per 1-million population declined from 3.2 cases in 1987 to 0.04 in 2019, parallel to that of acute HBV per 100,000 from 10.0 to 0.39 cases during the same period. The median age of cases increased from 27 years in the decade 1991-1999 to 44 years in the decade 2010-2019 (p < .001). Over the same period, the male/female ratio decreased from 3.8 to 2.1, the proportion of coinfections increased from 55% to 75% (p = .003) and that of HBsAg positive acute hepatitis tested for by IgM anti-HDV linearly decreased from 50.1% to 34.1% (p < .001). People born abroad accounted for 24.6% of cases in 2004-2010 and 32.1% in 2011-2019. In the period 2010-2019, risky sexual behaviour (O.R. 4.2; 95%CI: 1.4-12.8) was the sole independent predictor of acute HDV; conversely intravenous drug use was no longer associated (O.R. 1.25; 95%CI: 0.15-10.22) with this. In conclusion, HBV vaccination was an effective measure to control acute HDV. Intravenous drug use is no longer an efficient mode of HDV spread. Testing for IgM-anti HDV is a grey area requiring alert. Acute HDV in foreigners should be monitored in the years to come

Deep learning applications in structure-based drug discovery

In recent years, machine learning and deep learning applications have permeated all fields of science thanks to rapid algorithmic advances and computer hardware developments. A very active area of research is the use of deep learning in structure-based drug design, where the goal is to design effective drugs against a pharmacological target of interest. In this work, we explored the use of deep learning in the early stages of drug discovery. In particular, we focussed on structure-based virtual screening, binding affinity prediction, and de novo drug design. First, we enabled docking with flexible residues within Gnina, a state-of-the- art docking software based on convolutional neural networks, and we performed a large-scale cross-docking study of such methodology, outlining its strengths and weaknesses. Second, we extracted the convolutional neural network scoring function from the docking software into a standalone package for fast prototyping. With the new software at hand, we explored different annotations for supervised learning to improve the convolutional neural network scoring function for docking with flexible residues. Third, we developed a novel scoring function for binding affinity prediction based on a successful deep learning architecture used to develop machine learning force fields. Finally, we carefully evaluate a generative model for de novo design for the application in industrial drug discovery pipelines. We outline the weaknesses of the method and the problems with current evaluations of generative models

Replication of "Cognitive Performance in Remote Work: Evidence from Professional Chess"

Replication Package of: Steffen Künn, Christian Seel, Dainis Zegners, Cognitive Performance in Remote Work: Evidence from Professional Chess, The Economic Journal, Volume 132, Issue 643, April 2022, Pages 1218–1232, https://doi.org/10.1093/ej/ueab09