Maximizing Convergence Speed for Second Order Consensus in Leaderless Multi-Agent Systems

The paper deals with the consensus problem in a leaderless network of agents that have to reach a common velocity while forming a uniformly spaced string. Moreover, the final common velocity (reference velocity) is determined by the agents in a distributed and leaderless way. Then, the consensus protocol parameters are optimized for networks characterized by a communication topology described by a class of directed graphs having a directed spanning tree, in order to maximize the convergence rate and avoid oscillations. The advantages of the optimized consensus protocol are enlightened by some simulation results and comparison with a protocol proposed in the related literature. The presented protocol can be applied to coordinate agents such as mobile robots, automated guided vehicles (AGVs) and autonomous vehicles that have to move with the same velocity and a common inter-space gap.      

PRILJ: an efficient two-step method based on embedding and clustering for the identification of regularities in legal case judgments

In an era characterized by fast technological progress that introduces new unpredictable scenarios every day, working in the law field may appear very difficult, if not supported by the right tools. In this respect, some systems based on Artificial Intelligence methods have been proposed in the literature, to support several tasks in the legal sector. Following this line of research, in this paper we propose a novel method, called PRILJ, that identifies paragraph regularities in legal case judgments, to support legal experts during the redaction of legal documents. Methodologically, PRILJ adopts a two-step approach that first groups documents into clusters, according to their semantic content, and then identifies regularities in the paragraphs for each cluster. Embedding-based methods are adopted to properly represent documents and paragraphs into a semantic numerical feature space, and an Approximated Nearest Neighbor Search method is adopted to efficiently retrieve the most similar paragraphs with respect to the paragraphs of a document under preparation. Our extensive experimental evaluation, performed on a real-world dataset provided by EUR-Lex, proves the effectiveness and the efficiency of the proposed method. In particular, its ability of modeling different topics of legal documents, as well as of capturing the semantics of the textual content, appear very beneficial for the considered task, and make PRILJ very robust to the possible presence of noise in the data.

     

Hierarchical Y and USY Zeolites Designed by Post‐Synthetic Strategies

Strategic combinations of affordable and scalable post‐synthetic modifications enabled to design a broad family of hierarchical Y and USY zeolites (FAU topology) independent on the Si/Al ratio. Pristine (Y, Si/Al = 2.4), steamed (USY, Si/Al = 2.6), and steamed and dealuminated (USY, Si/Al = 15 and 30) zeolites were exposed to a variety of acid (H₄EDTA and Na₂H₂EDTA) and base (NaOH) treatments, which led to the introduction of mesopore surfaces up to 500 m² g^?1, while preserving the intrinsic zeolite properties. Pristine Y and USY zeolites (Si/Al ～ 2.5) required mild dealumination (to Si/Al > 4 in the case of Y) to facilitate subsequent efficient desilication. Alkaline treatment of Y and USY zeolites with low Si/Al ratios (～4–6) led to an abundance of Al‐rich debris, which could be removed by a subsequent mild acid wash. On the other hand, severely steamed and dealuminated, hence Si‐rich, USY zeolites (Si/Al = 15 and 30) proved extremely sensitive to the alkaline solution, displaying facile dissolution and substantial amorphization. For the latter group of ultra‐stable Y zeolites, the presence of TPA⁺ in the alkaline solution enables to protect the zeolite structures upon the introduction of mesoporosity by desilication, preserving crystallinity and micropore volume. The sorption and catalytic properties of the hierarchical Y and USY zeolites were superior compared to the conventional counterparts.     

Neutron wave propagation in multiplying assemblies with and without control rods

In this work the dispersion law is expanded in a power series of the frequency up to the third order; for this, two-group diffusion theory is used. In this manner the nuclear parameters of this approximation can be related with the experimental observables in a closed and definite form. Also a model is developed that predicts the existance of an asymptotic progagation mode even in the presence of control rods; this model permits one to calculate the wave front and the dispersion law. The models are compared with experiments done in a highly compact system with 90% ²³⁵U enriched uranium fuel and H₂O moderator.     

BROCCOLI: overlapping and outlier-robust biclustering through proximal stochastic gradient descent

Data Mining and Knowledge Discovery - Matrix tri-factorization subject to binary constraints is a versatile and powerful framework for the simultaneous clustering of observations and features, also...     

ST推出Teseo Ⅲ芯片,支持北斗车辆定位

正今年初,意法半导体(ST)推出Teseo III独立式定位单芯片,能够接收五大卫星导航系统发射的信号,包括中国北斗、美国GPS、欧洲Galileo、俄罗斯GLONASS和日本的QZSS。Teseo III产品系列传承了Teseo II单芯片卫星导航IC领先的产品性能,将定位准确度提升至一个新的水平。据悉,我国北斗卫星导航系统自2012年12月27日正式对外开放以来,先后吸引高通、博通、联发科和ST等国     

Multivalent interacting glycodendrimer to prevent amyloid-peptide fibril formation induced by Cu(II): A multidisciplinary approach

Amyloid peptide fibrillogenesis induced by Cu(II) ions is a key event in the pathogenesis of Alzheimer’s disease. Dendrimers have been found to be active in preventing fibril formation. Therefore, they hold promise for the treatment of Alzheimer’s disease. In this study, the fibrillation mechanism of amyloid peptide Aβ 1-40 was studied by adding Cu(II) in the absence and presence of 4^th generation poly(propyleneimine) glycodendrimer functionalized with sulfate groups, using dynamic light scattering (DLS), circular dichroism (CD), fluorescence, electron paramagnetic resonance (EPR) and molecular modeling (MD). The glycodendrimer was non-toxic to mHippoE-18 embryonic mouse hippocampal cells, selected as a nerve cell model, and decreased the toxicity of peptide aggregates formed after the addition of Cu(II). The binary systems of Cu(II)–glycodendrimer, Cu(II)–peptide, and glycodendrimer–peptide were first characterized. At the lowest Cu(II)/glycodendrimer molar ratios, Cu(II) was complexed by the internal-dendrimer nitrogen sites. After saturation of these sites, Cu(II) binding with sulfate groups occurred. Stable Cu(II)–peptide complexes formed within 5 min and were responsible for a transition from an α helix to a β-sheet conformation of Aβ 1-40. Glycodendrimer–peptide interactions provoked the stabilization of the α-helix, as demonstrated in the absence of Cu(II) by the Thioflavin T assay, and in the presence of Cu(II) by CD, EPR, and MD. Formation of fibrils is differentially modulated by glycodendrimer and Cu(II) concentrations for a fixed amount of Aβ 1-40. Therefore, this multidisciplinary study facilitated the recognition of optimal experimental conditions that allow the glycodendrimer to avoid the fibril formation induced by Cu(II).

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Application of the theory of random matrices to a reactor-noise problem

The stochastic equation corresponding to a nuclear reactor with random distribution of materials is written in a matrix form, in this way the probability distribution of reactivities is derived as the probability distribution of the higher eigenvalues of random matrices. The theoretical results are illustrated and validated with Monte Carlo simulations based on the diffusion equations and the matrix approach.