Semantic social routing in Gnutella

The objective of this project is to improve the performance of the Gnutella peer-to-peer protocol (version 0.4) by introducing a semantic-social routing model and several categories of interest. The Gnutella protocol requires peers to broadcast messages to their neighbours when they search files. The message passing generates a lot of traffic in the network, which degrades the quality of service. We propose using social networks to optimize the speed of search and to improve the quality of service in a Gnutella based peer-to-peer environment. Each peer creates and updates a “friends list” from its past experience, for each category of interest. Once peers generate their friends lists, they use these lists to semantically route queries in the network. Search messages in a given category are mainly sent to “friends” who have been useful in the past in finding files in the same category. This helps to reduce the search time and to decrease the network traffic by minimizing the number of messages circulating in the system as compared to standard Gnutella. This project will demonstrate by simulating a peer-to-peer type of environment with the JADE multi-agent system platform that by learning other peers’ interests, building and exploiting their social networks (friends lists) to route queries semantically, peers can get more relevant resources faster and with less traffic generated, i.e. that the performance of the Gnutella system can be improved

A Convenient Synthesis of 14C-Anthralin

Anthralin [1,8-dihydroxy-9(10H)-anthracenone] is among the most widely used drugs in the topical treatment of psoriasis1). However, not much is known concerning its mode of action at the molecular level, although a variety of cellular targets have been implicated both in the main and side effects of anthralin2 ). In particular, the interaction of anthralin with proteins has long been recognized to occur3 , 4 ) and there has been renewed interest in this topic, mostly directed toward the investigation whether enzyme inhibition by anthralin is related to oxygen radicalmediated damage of proteins5 ) . In order to gain a more profound understanding of the interaction between this drug and cellular targets, anthralin labelled with a non-exchangeable radioisotope in a suitable position was highly desirable. Furthermore, this labelled compound might serve as a useful starting material for the synthesis of analogues labelled in the anthrone nucleus. Since structural modification of anthralin has provided compounds with improved biological activity6 '7), labelled compounds are required for studies on skin penetration and metabolism of these future drugs. Although routes to 14C-anthralin have already been described8,9), each of these methods suffers from too many synthetic steps, or the use of hazardous 14C-sources1 ) . In this paper, we describe a short and efficient synthesis of l,8-dihydroxy-[10-14C]-9(10H)-anthracenone

Teaching Robots Novel Objects by Pointing at Them

Robots that must operate in novel environments and collaborate with humans must be capable of acquiring new knowledge from human experts during operation. We propose teaching a robot novel objects it has not encountered before by pointing a hand at the new object of interest. An end-to-end neural network is used to attend to the novel object of interest indicated by the pointing hand and then to localize the object in new scenes. In order to attend to the novel object indicated by the pointing hand, we propose a spatial attention modulation mechanism that learns to focus on the highlighted object while ignoring the other objects in the scene. We show that a robot arm can manipulate novel objects that are highlighted by pointing a hand at them. We also evaluate the performance of the proposed architecture on a synthetic dataset constructed using emojis and on a real-world dataset of common objects

Open Arms: Open-Source Arms, Hands & Control

Open Arms is a novel open-source platform of realistic human-like robotic hands and arms hardware with 28 Degree-of-Freedom (DoF), designed to extend the capabilities and accessibility of humanoid robotic grasping and manipulation. The Open Arms framework includes an open SDK and development environment, simulation tools, and application development tools to build and operate Open Arms. This paper describes these hands controls, sensing, mechanisms, aesthetic design, and manufacturing and their real-world applications with a teleoperated nursing robot. From 2015 to 2022, the authors have designed and established the manufacturing of Open Arms as a low-cost, high functionality robotic arms hardware and software framework to serve both humanoid robot applications and the urgent demand for low-cost prosthetics, as part of the Hanson Robotics Sophia Robot platform. Using the techniques of consumer product manufacturing, we set out to define modular, low-cost techniques for approximating the dexterity and sensitivity of human hands. To demonstrate the dexterity and control of our hands, we present a Generative Grasping Residual CNN (GGR-CNN) model that can generate robust antipodal grasps from input images of various objects in real-time speeds (22ms). We achieved state-of-the-art accuracy of 92.4% using our model architecture on a standard Cornell Grasping Dataset, which contains a diverse set of household objects.Comment: Submitted to 36th Conference on Neural Information Processing Systems (NeurIPS 2022

The use of the SeDeM diagram expert system for the formulation of Captopril SR matrix tablets by direct compression

The SeDeM Diagram Expert System has been used to study excipients, Captopril and designed formulations for their galenic characterization and to ascertain the critical points of the formula affecting product quality to obtain suitable formulations of Captopril Direct Compression SR Matrix Tablets. The application of the Sedem Diagram Expert System enables selecting excipients with in order to optimize the formula in the preformulation and formulation studies. The methodology is based on the implementation of ICH Q8, establishing the design space of the formula with the use of experiment design, using the parameters of the SeDeM Diagram Expert System as system responses