Security for Two-Way Untrusted Relay against Constant and Reactive Jamming with Fixed Signals

Active attacking in physical-layer security has not been significantly studied while potentially causing serious consequences for the legitimate networks. In this paper, we propose a novel method to estimate and remove the jamming signals from multiple multi-antenna jammers in a two-way relay network with multi-antenna legitimate and relay nodes. We carefully consider the signals in the time slots in order to exploit the repetition of the signals and design the transmitted signals which can work in different cases. The numerical results show that the secrecy maximum achievable sum-rate (MASR) at the legitimate nodes is higher than that of the conventional method when considering the affect of transmit SNR; the number antennas at the legitimate and relay nodes; normalized distance between one legitimate node and the relay; and the vertical coordinate of the relay

Combining tree-based and dynamical systems for the inference of gene regulatory networks

Motivation: Reconstructing the topology of gene regulatory networks (GRNs) from time series of gene expression data remains an important open problem in computational systems biology. Existing GRN inference algorithms face one of two limitations: model-free methods are scalable but suffer from a lack of interpretability and cannot in general be used for out of sample predictions. On the other hand, model-based methods focus on identifying a dynamical model of the system. These are clearly interpretable and can be used for predictions; however, they rely on strong assumptions and are typically very demanding computationally. Results: Here, we propose a new hybrid approach for GRN inference, called Jump3, exploiting time series of expression data. Jump3 is based on a formal on/off model of gene expression but uses a non-parametric procedure based on decision trees (called "jump trees") to reconstruct the GRN topology, allowing the inference of networks of hundreds of genes. We show the good performance of Jump3 on in silico and synthetic networks and applied the approach to identify regulatory interactions activated in the presence of interferon gamma. Availability and implementation: Our MATLAB implementation of Jump3 is available at http:// homepages.inf.ed.ac.uk/vhuynht/software.html

Creating an appropriate tenure foundation for REDD+: The record to date and prospects for the future

Attention to tenure is a fundamental step in preparation for REDD+ implementation. Unclear and conflicting tenure has been the main challenge faced by the proponents of subnational REDD+ initiatives, and accordingly, they have expended much effort to remedy the problem. This article assesses how well REDD+ has performed in laying an appropriate tenure foundation. Field research was carried out in two phases (2010-2012 and 2013-2014) in five countries (Brazil, Peru, Cameroon, Tanzania, Indonesia) at 21 subnational initiatives, 141 villages (half targeted for REDD+ interventions), and 3,754 households. Three questions are posed: 1) What was the effect of REDD+ on perceived tenure insecurity of village residents?; 2) What are the main reasons for change in the level of tenure insecurity and security from Phase 1 to Phase 2 perceived by village residents in control and intervention villages?; and 3) How do intervention village residents evaluate the impact of tenure-related interventions on community well-being? Among the notable findings are that: 1) tenure insecurity decreases slightly across the whole sample of villages, but we only find that REDD+ significantly reduces tenure insecurity in Cameroon, while actually increasing insecurity of smallholder agricultural land tenure in Brazil at the household level; 2) among the main reported reasons for increasing tenure insecurity (where it occurs) are problems with outside companies, lack of title, and competition from neighboring villagers; and 3) views on the effect of REDD+ tenure-related interventions on community well-being lean towards the positive, including for interventions that restrain access to forest. Thus, while there is little evidence that REDD+ interventions have worsened smallholder tenure insecurity (as feared by critics), there is also little evidence that the proponents' efforts to address tenure insecurity have produced results. Work on tenure remains an urgent priority for safeguarding local livelihoods as well as for reducing deforestation. This will require increased attention to participatory engagement, improved reward systems, tenure policy reform, integration of national and local efforts, and "business-as-usual" interestsThis research is part of CIFOR’s Global Comparative Study on REDD+ (www.cifor.org/gcs). The funding partners that have supported this research include the Norwegian Agency for Development Cooperation (Norad) [grant numbers QZA-10/0468, QZA-12/0882, QZA-16/0110], the Australian Department of Foreign Affairs and Trade (DFAT) [grant numbers 46167, 63560], the European Commission (EC) [grant number DCI-ENV/2011/269-520], the International Climate Initiative (IKI) of the German Federal Ministry for the Environment, Nature Conservation, Building and Nuclear Safety (BMUB) [grant number KI II 7 - 42206-6/75], the United Kingdom Department for International Development (UKAID) [grant number TF069018], and the CGIAR Research Program on Forests, Trees and Agroforestry (CRP-FTA) [grant number TF No. 069018], with financial support from the donors contributing to the CGIAR Fund. David Solis provided a valuable service in reviewing our methods for taking into account attrition of households over time

Sand Spit Morphology at an Inlet on Phu Quoc Island, Vietnam

Tidal inlets with attached sand spits are a very common coastal landform. Since the evolution of sand spits along coastlines influence the social-economic development of local coastal areas, sand spits have become the objects of numerous studies. However, previous studies have mainly focused on sand spits that are usually in the scale of hundreds of meters in width, whilst knowledge about the evolution of smaller-scale sand spits still remains limited. Therefore, in this study, the morphological change of a small and unexplored sand spit in front of Song Tranh Inlet on the west coast of Phu Quoc Island, Vietnam is investigated. Satellite images are first used to observe the morphological change of the sand spit and calculate the longshore sediment transport rates (LSTR) along the sand spit. Waves and beach sediments are collected at the study site to calculate the longshore sediment transport rate using the CERC formula. It is found that there is a seasonal variation in the evolution of the sand spit at Song Tranh Inlet. The longshore sediment transport rates along the spit calculated by image analysis are 39,000 m$^3$/year, 66,000 m$^3$/year, and 40,000 m$^3$/year, whilst the longshore sediment transport rate calculated by the CERC formula is 72,000 m$^3$/year. This study aims to contribute to the methodology for investigating the evolutions of small sand spits and, specifically, sustainable coastal management for Phu Quoc Island, which is well-known as the Pearl Island of Vietnam

Reverse Engineering Gene Networks with ANN: Variability in Network Inference Algorithms

Motivation :Reconstructing the topology of a gene regulatory network is one of the key tasks in systems biology. Despite of the wide variety of proposed methods, very little work has been dedicated to the assessment of their stability properties. Here we present a methodical comparison of the performance of a novel method (RegnANN) for gene network inference based on multilayer perceptrons with three reference algorithms (ARACNE, CLR, KELLER), focussing our analysis on the prediction variability induced by both the network intrinsic structure and the available data. Results: The extensive evaluation on both synthetic data and a selection of gene modules of "Escherichia coli" indicates that all the algorithms suffer of instability and variability issues with regards to the reconstruction of the topology of the network. This instability makes objectively very hard the task of establishing which method performs best. Nevertheless, RegnANN shows MCC scores that compare very favorably with all the other inference methods tested. Availability: The software for the RegnANN inference algorithm is distributed under GPL3 and it is available at the corresponding author home page (http://mpba.fbk.eu/grimaldi/regnann-supmat

Attenuation of stripe artifacts in optical coherence tomography images through wavelet-FFT filtering

The use of polarization-maintaining (PM) fibers for polarization-sensitive optical coherence tomography (PS-OCT) can result in numerous image artifacts which degrade the reliability of birefringence measurements. Similar artifacts can also arise in conventional OCT, due to stray reflections from optical surfaces, a problem which is increasing in tandem with the steady rise in source coherence lengths. Here, a recently presented wavelet-FFT filter[Opt. Express 17(10), 8567 (2009). [PubMed] ] is combined with surface flattening displacement fields in order to suppress ghost artifacts following either a duplicate or inverse profile to that of the sample surface. In addition, horizontal coherence stripes originating from Fresnel reflections of optical components are suppressed in order to facilitate accurate surface detection. The result is an improved visualization of the phase-retardance profile within tissue, which may improve the reliability of curve-fitting methods for localized birefringence estimation. While the results are presented with a focus towards PS-OCT, the filtering method can also be applied to the removal of stray reflection artifacts in conventional OCT images

Data-driven reverse engineering of signaling pathways using ensembles of dynamic models

Signaling pathways play a key role in complex diseases such as cancer, for which the development of novel therapies is a difficult, expensive and laborious task. Computational models that can predict the effect of a new combination of drugs without having to test it experimentally can help in accelerating this process. In particular, network-based dynamic models of these pathways hold promise to both understand and predict the effect of therapeutics. However, their use is currently hampered by limitations in our knowledge of the underlying biochemistry, as well as in the experimental and computational technologies used for calibrating the models. Thus, the results from such models need to be carefully interpreted and used in order to avoid biased predictions. Here we present a procedure that deals with this uncertainty by using experimental data to build an ensemble of dynamic models. The method incorporates steps to reduce overfitting and maximize predictive capability. We find that by combining the outputs of individual models in an ensemble it is possible to obtain a more robust prediction. We report results obtained with this method, which we call SELDOM (enSEmbLe of Dynamic lOgic-based Models), showing that it improves the predictions previously reported for several challenging problems.JRB and DH acknowledge funding from the EU FP7 project NICHE (ITN Grant number 289384). JRB acknowledges funding from the Spanish MINECO project SYNBIOFACTORY (grant number DPI2014-55276-C5-2-R). AFV acknowledges funding from the Galician government (Xunta de Galiza) through the I2C postdoctoral fellowship ED481B2014/133-0. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.info:eu-repo/semantics/publishedVersio

Molecular Characterization of HIV-1 CRF01_AE in Mekong Delta, Vietnam, and Impact of T-Cell Epitope Mutations on HLA Recognition (ANRS 12159)

To date, 11 HIV-1 subtypes and 48 circulating recombinant forms have been described worldwide. The underlying reason why their distribution is so heterogeneous is not clear. Host genetic factors could partly explain this distribution. The aim of this study was to describe HIV-1 strains circulating in an unexplored area of Mekong Delta, Vietnam, and to assess the impact of optimal epitope mutations on HLA binding.We recruited 125 chronically antiretroviral-naive HIV-1-infected subjects from five cities in the Mekong Delta. We performed high-resolution DNA typing of HLA class I alleles, sequencing of Gag and RT-Prot genes and phylogenetic analysis of the strains. Epitope mutations were analyzed in patients bearing the HLA allele restricting the studied epitope. Optimal wild-type epitopes from the Los Alamos database were used as reference. T-cell epitope recognition was predicted using the immune epitope database tool according to three different scores involved in antigen processing (TAP and proteasome scores) and HLA binding (MHC score). with a Vietnamese specificity held by two different haplotypes. The percentage of homology between Mekong and B consensus HIV-1 sequences was above 85%. Divergent epitopes had TAP and proteasome scores comparable with wild-type epitopes. MHC scores were significantly lower in divergent epitopes with a mean of 2.4 (±0.9) versus 2 (±0.7) in non-divergent ones (p<0.0001).Our study confirms the wide predominance of CRF01_AE in the Mekong Delta where patients harbor a specific HLA pattern. Moreover, it demonstrates the lower MHC binding affinity among divergent epitopes. This weak immune pressure combined with a narrow genetic diversity favors immune escape and could explain why CRF01_AE is still predominant in Vietnam, particularly in the Mekong area

Partial food systems baseline assessment at the Vietnam benchmark sites

Using data collected from a cross-sectional study in Moc Chau, Dong Anh and Cau Giay districts in Vietnam, this report aims to elucidate specific components of local Vietnamese food systems along a rural to urban transect focusing specifically on (i) diets, (ii) nutrition status (anthropometry), (iii) consumer behavior, (iv) food environment, and (v) food flows

Network deconvolution as a general method to distinguish direct dependencies in networks

Recognizing direct relationships between variables connected in a network is a pervasive problem in biological, social and information sciences as correlation-based networks contain numerous indirect relationships. Here we present a general method for inferring direct effects from an observed correlation matrix containing both direct and indirect effects. We formulate the problem as the inverse of network convolution, and introduce an algorithm that removes the combined effect of all indirect paths of arbitrary length in a closed-form solution by exploiting eigen-decomposition and infinite-series sums. We demonstrate the effectiveness of our approach in several network applications: distinguishing direct targets in gene expression regulatory networks; recognizing directly interacting amino-acid residues for protein structure prediction from sequence alignments; and distinguishing strong collaborations in co-authorship social networks using connectivity information alone. In addition to its theoretical impact as a foundational graph theoretic tool, our results suggest network deconvolution is widely applicable for computing direct dependencies in network science across diverse disciplines.National Institutes of Health (U.S.) (grant R01 HG004037)National Institutes of Health (U.S.) (grant HG005639)Swiss National Science Foundation (Fellowship)National Science Foundation (U.S.) (NSF CAREER Award 0644282