A Traffic-Aware Federated Imitation Learning Framework for Motion Control at Unsignalized Intersections with Internet of Vehicles

The wealth of data and the enhanced computation capabilities of Internet of Vehicles (IoV) enable the optimized motion control of vehicles passing through an intersection without traffic lights. However, more intersections and demands for privacy protection pose new challenges to motion control optimization. Federated Learning (FL) can protect privacy via model interaction in IoV, but traditional FL methods hardly deal with the transportation issue. To address the aforementioned issue, this study proposes a Traffic-Aware Federated Imitation learning framework for Motion Control (TAFI-MC), consisting of Vehicle Interactors (VIs), Edge Trainers (ETs), and a Cloud Aggregator (CA). An Imitation Learning (IL) algorithm is integrated into TAFI-MC to improve motion control. Furthermore, a loss-aware experience selection strategy is explored to reduce communication overhead between ETs and VIs. The experimental results show that the proposed TAFI-MC outperforms imitated rules in the respect of collision avoidance and driving comfort, and the experience selection strategy can reduce communication overheads while ensuring convergence.

Numerical simulation of domain wall motion in a surface discharge over a ferroelectric

The article presents a simplified numerical simulation of a vacuum ferroelectric cathode operating in a low-current mode (without surface plasma formation). The field emission from the cathode was simulated for the range of applied electric field magnitudes. The polarization domain growth process during the charging of ferroelectric surface was simulated using Landau-Ginzburg-Devonshire model. Interaction of the electrons with a depolarization field of a domain wall led to an attraction of the electrons to the polarization domain boundaries. A close to the linear dependence of the equilibrium domain wall position from the applied electric field was found with the total emitted charge proportional to the domain size.

Evaluating Effectiveness of Outpatient Monitoring in Type 2 Diabetes: The One-Year Experience in an Italian Group of Primary Care

Nowadays, chronic disease management is the primary challenge of the healthcare system. From 2015, in the Veneto region (Italy), patients with a diagnosis of type 2 diabetes mellitus (T2DM) have been included in the diagnostic-therapeutic pathway (PDTA) program, and their clinical condition has been continuously monitored. The aim of this retrospective study is to determine the effectiveness of PDTA intervention, alone or in combination with a specialized one, in subjects with diagnosis of T2DM. Clinical and behavioral characteristics were collected at baseline and after 1 year of follow-up. Two subgroups were considered: subjects enrolled in PDTA only and subjects enrolled in both the PDTA program and in the care plan proposed by the specialized medical center (CAD group). Longitudinal analysis showed a relevant positive effect of time on diastolic blood pressure, while CAD enrollment appears to be related to higher levels of glycated hemoglobin. When included together in the same model, interaction between time and CAD covariates results in completely nonsignificant effects. As long-term management of chronic disorders, such as T2DM, is often difficult due to disease characteristics and problems in healthcare organization, monitoring programs, such as PDTA, and specialized care programs, such as CAD, do not show a clinically relevant effect in the first year of follow-up. Therefore, they should be analyzed over a longer period. However, they should also carefully consider the need for adequate tools for data collection and sharing, in addition to the context of application, patient expectations and the need for a long-term educational program.

Compatible organic and natural solvent mixture of synthesising biodegradable polymeric nanoparticles

The Flory-Huggins model interaction explained the compatibility and extent of polymer dissolution in selected solvent mixtures via Hansen Solubility Parameters (HSP). Metastable zone where nucleation of NPs would start was determined by the solvent mixture – polymer – water interaction. Simulation results explained that the combination of acetone-chloroform (0.20:0.80) was better than acetone-ethyl lactate (0.40:0.60) for PCL solvation while ethyl lactate-dimethyl sulfoxide (0.60:0.40) was better for PLA solvation as compared to ethyl lactate-acetone (0.80:0.20). Nanoprecipitation with aqueous to organic volume ratio of 10 was used to prepare the biodegradable PCL nanoparticles for experimental validation. The organic phase was 1 g L−1 PCL in solvents or solvent mixtures and the antisolvent was deionized (DI) water. Scanning Electron Microscope (SEM) and Atomic Force Microscope (AFM) were used to examine the morphology and size of nanoparticles formed. Results showed that the acetone-chloroform with volume fraction of 0.20 to 0.80 was the best solvent mixture for PCL in producing NPs with the mean size less than 100 nm. Solvent mixture proved by numerical simulation and experimental validation, able to enhance the affinity of polymer (PCL or PLA) for water to produce nanoparticles with much smaller size.

The impact of intermediaries on a negotiation: an approach from game theory

Standard approaches to model interaction networks are limited in their capacity to describe the nuances of real communication. We present a game theoretical framework to quantify the effect of intermediaries on the interaction between agents. Inspired by the seminal work Myerson (1977). on cooperative structures in cooperative games, we set the basis for multidimensional network analysis within game theory. More specifically, an extension of the point-arc game Feltkamp and van den Nouwe51 land (1992). is introduced, generalizing the analysis of cooperative games to multigraphs. An efficient algorithm is proposed for the computation of Shapley value of this game. We prove the validity of our approach by applying it to a intermediaries network model. We are able to recover meaningful results on the dependence of the game outcome on the intermediaries network. This work contributes to the optimal design of networks in economic environments and allows the ranking of players in complex networks.

Interactions of a small molecule configuration mimetic the interactions found in α-synuclein aggregation

Parkinson’s disease (PD) is an increasingly prevalent and currently incurable neurodegenerative disorder. The aggregation of the amyloid disordered protein α-synuclein (Syn) has been implicated in the development of PD. Syn aggregation has been widely investigated but information concerning the conformational alterations in the diverse protein aggregated species at the molecular level is still scarce. To address this issue, it was here developed a comparative study involving the known parent N-acetyl-L-tyrosinamide (NAYA) compound and the Syn protein by using spectroscopic techniques. At least two different configurations of the NAYA compound were found to exist in solution. One configuration, known as the NAYA closed shape configuration, involves an amide intramolecular hydrogen-bonded interaction and was found to be a model interaction for the hydrophilic core of β-sheets, which are the most common conformational alteration found in Syn aggregated species. Since the spectroscopic techniques used herein also differentiate between tyrosyl and peptide bond groups and both NAYA and Syn possess such groups it was possible to assign these groups interactions in the β-sheets formed. This study retrieves the importance of using model compounds with spectroscopic characteristics similar to those found in proteins to access the complex interactions network existing in the amyloid aggregated species.