Trajectory control of a quadrotor using a control allocation approach

A quadrotor is an underactuated unmanned aerial vehicle with four inputs to control the dynamics. Trajectory control of a quadrotor is a challenging task and usually tackled in a hierarchical framework where desired/reference attitude angles are analytically determined from the desired command signals, i.e. virtual controls, that control the positional dynamics of the quadrotor and the desired yaw angle is set to some constant value. Although this method is relatively straightforward, it may produce large and nonsmooth reference angles which must be saturated and low-pass filtered. In this work, we show that the determination of desired attitude angles from virtual controls can be viewed as a control allocation problem and it can be solved numerically using nonlinear optimization where certain magnitude and rate constraints can be imposed on the desired attitude angles and the yaw angle need not be constant. Simulation results for both analytical and numerical methods have been presented and compared. Results for constrained optimization show that the flight performance is quite satisfactory. © 2017 IEEE

Reward shaping using directed graph convolution neural networks for reinforcement learning and games

Game theory can employ reinforcement learning algorithms to identify the optimal policy or equilibrium solution. Potential-based reward shaping (PBRS) methods are prevalently used for accelerating reinforcement learning, ensuring the optimal policy remains consistent. Existing PBRS research performs message passing based on graph convolution neural networks (GCNs) to propagate information from rewarding states. However, in an irreversible time-series reinforcement learning problem, undirected graphs will not only mislead message-passing schemes but also lose a distinctive direction structure. In this paper, a novel approach called directed graph convolution neural networks for reward shaping φDCN has been proposed to tackle this problem. The key innovation of φDCN is the extension of spectral-based undirected graph convolution to directed graphs. Messages can be efficiently propagated by leveraging a directed graph Laplacian as a substitute for the state transition matrix. As a consequence, potential-based reward shaping can then be implemented by the propagated messages. The incorporation of temporal dependencies between states makes φDCN more suitable for real-world scenarios than existing potential-based reward shaping methods based on undirected graph convolutional networks. Preliminary experiments demonstrate that the proposed φDCN exhibits a substantial improvement compared to other competing algorithms on both Atari and MuJoCo benchmarks

Méthodologie générale d’une étude ACP : Généralités, concepts et exemples

Le développement des modèles statistiques des relations quantitatives structure-activité/propriété joue un rôle important dans la conception de nouveaux produits chimiques spécialement pharmaceutiques. La prédiction des propriétés biologiques des produits non testées passe d’abord par une analyse ACP. Il s’agit de l’analyse en composante principale : c’est une méthode basée sur des statistiques descriptives multidimensionnelles permettant de traiter simultanément un nombre quelconque de variables quantitatives. L’objectif est de visualiser et résumer l’information contenue dans les différentes données afin d’avoir une représentation permettant plus facilement l’interprétation. Dans ce papier, nous décrivons des généralités et les principaux concepts et techniques les plus pertinents pour la réalisation d’une étude ACP

Observation of diurnal variation of urban microclimate in Kuala Lumpur, Malaysia

To realise sustainable urban architecture and design in tropical climate conditions, a quantitative understanding of the urban microclimate of a real tropical city through long-Term measurements is crucial. The target city of this work, which is Kuala Lumpur, Malaysia, is classified to be within the tropical rainforest climate zone. Data were collected for a full-year study (March 2014 - February 2015) using a weather station installed in a university campus located in Kuala Lumpur. Parameters such as air temperature, relative humidity, solar radiation, wind speed and direction, and rainfall were recorded and analysed at hourly, daily, and monthly time scales. The results showed that the ranges of the urban microclimate parameters were large: The average wind speed ranged between 0 - 2 m/s, solar radiation was 100 - 200 W/m2 and relative humidity 60 - 90 %. The results suggest that the urban microclimatic parameters were influenced by both monsoon seasons and the urban surface

Computational investigation of mechanistic insights of Aβ42 interactions against extracellular domain of nAChRα7 in Alzheimer's disease

Aim: Amyloid beta (Aβ) 1-42, which is a basic constituent of amyloid plaques, binds with extracellular transmembrane receptor nicotine acetylcholine receptor α7 (nAChRα7) in Alzheimer’s disease. Materials and Methods: In the current study, a computational approach was employed to explore the active binding sites of nAChRα7 through Aβ 1–42 interactions and their involvement in the activation of downstream signalling pathways. Sequential and structural analyses were performed on the extracellular part of nAChRα7 to identify its core active binding site. Results: Results showed that a conserved residual pattern and well superimposed structures were observed in all nAChRs proteins. Molecular docking servers were used to predict the common interactive residues in nAChRα7 and Aβ1–42 proteins. The docking profile results showed some common interactive residues such as Glu22, Ala42 and Trp171 may consider as the active key player in the activation of downstream signalling pathways. Moreover, the signal communication and receiving efficacy of best-docked complexes was checked through DynOmic online server. Furthermore, the results from molecular dynamic simulation experiment showed the stability of nAChRα7. The generated root mean square deviations and fluctuations (RMSD/F), solvent accessible surface area (SASA) and radius of gyration (Rg) graphs of nAChRα7 also showed its backbone stability and compactness, respectively. Conclusion: Taken together, our predicted results intimated the structural insight on the molecular interactions of beta amyloid protein involved in the activation of nAChRα7 receptor. In future, a better understanding of nAChRα7 and their interconnected proteins signalling cascade may be consider as target to cure Alzheimer’s disease.This was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2017R1D1A1B03034948).Scopu

Short Co-occurring Polypeptide Regions Can Predict Global Protein Interaction Maps

A goal of the post-genomics era has been to elucidate a detailed global map of protein-protein interactions (PPIs) within a cell. Here, we show that the presence of co-occurring short polypeptide sequences between interacting protein partners appears to be conserved across different organisms. We present an algorithm to automatically generate PPI prediction method parameters for various organisms and illustrate that global PPIs can be predicted from previously reported PPIs within the same or a different organism using protein primary sequences. The PPI prediction code is further accelerated through the use of parallel multi-core programming, which improves its usability for large scale or proteome-wide PPI prediction. We predict and analyze hundreds of novel human PPIs, experimentally confirm protein functions and importantly predict the first genome-wide PPI maps for S. pombe (∼9,000 PPIs) and C. elegans (∼37,500 PPIs)

Wireless Network Virtualization: Opportunities for Sharing in the 3.5 GHz Band

In this paper, we evaluate the opportunities that Wireless Network Virtualization (WNV) can bring for spectrum sharing by focusing on the regulatory framework that has been deployed by the Federal Communications Commission (FCC) for the 3.5GHz band. Pairing this regulatory approach with WNV permits us to present a sharing proposal where emphasis is made on increasing resource availability and providing flexible methods for negotiating for resource access. We include an economics framework that aims at presenting an additional perspective on the attainable outcomes of our sharing proposal. We find that by pairing regulatory flexibility with an enabling technology, within an appropriate economics context, we can increase resource access opportunities and enhance current sharing arrangements

Molecular identification of adenoviruses associated with respiratory infection in Egypt from 2003 to 2010.

BACKGROUND: Human adenoviruses of species B, C, and E (HAdV-B, -C, -E) are frequent causative agents of acute respiratory infections worldwide. As part of a surveillance program aimed at identifying the etiology of influenza-like illness (ILI) in Egypt, we characterized 105 adenovirus isolates from clinical samples collected between 2003 and 2010. METHODS: Identification of the isolates as HAdV was accomplished by an immunofluorescence assay (IFA) and confirmed by a set of species and type specific polymerase chain reactions (PCR). RESULTS: Of the 105 isolates, 42% were identified as belonging to HAdV-B, 60% as HAdV-C, and 1% as HAdV-E. We identified a total of six co-infections by PCR, of which five were HAdV-B/HAdV-C co-infections, and one was a co-infection of two HAdV-C types: HAdV-5/HAdV-6. Molecular typing by PCR enabled the identification of eight genotypes of human adenoviruses; HAdV-3 (n = 22), HAdV-7 (n = 14), HAdV-11 (n = 8), HAdV-1 (n = 22), HAdV-2 (20), HAdV-5 (n = 15), HAdV-6 (n = 3) and HAdV-4 (n = 1). The most abundant species in the characterized collection of isolates was HAdV-C, which is concordant with existing data for worldwide epidemiology of HAdV respiratory infections. CONCLUSIONS: We identified three species, HAdV-B, -C and -E, among patients with ILI over the course of 7 years in Egypt, with at least eight diverse types circulating

Canine respiratory coronavirus employs caveolin-1-mediated pathway for internalization to HRT-18G cells

Canine respiratory coronavirus (CRCoV), identified in 2003, is a member of the Coronaviridae family. The virus is a betacoronavirus and a close relative of human coronavirus OC43 and bovine coronavirus. Here, we examined entry of CRCoV into human rectal tumor cells (HRT-18G cell line) by analyzing co-localization of single virus particles with cellular markers in the presence or absence of chemical inhibitors of pathways potentially involved in virus entry. We also targeted these pathways using siRNA. The results show that the virus hijacks caveolin-dependent endocytosis to enter cells via endocytic internalization