Tree-Based Adaptive Spatial Detection for Adaptive Modulated MIMO Systems

Adaptive Multiple-Input Multiple-Output (MIMO) systems achieve a much higher information rate than conventional fixed schemes due to their ability to adapt their configurations according to the wireless communications environment. However, current adaptive MIMO detection schemes exhibit either low performance (and hence low spectral efficiency) or huge computational
complexity. In particular, whilst deterministic Sphere Decoder (SD) detection schemes are well established for static MIMO systems, exhibiting deterministic parallel structure, low computational complexity and quasi-ML detection performance, there are no corresponding adaptive schemes. This paper solves
this problem, describing a hybrid tree based adaptive modulation detection scheme. Fixed Complexity Sphere Decoding (FSD) and Real-Values FSD (RFSD) are modified and combined into a hybrid scheme exploited at low and medium SNR to provide the highest possible information rate with quasi-ML Bit Error
Rate (BER) performance, while Reduced Complexity RFSD, BChase and Decision Feedback (DFE) schemes are exploited in the high SNR regions. This algorithm provides the facility to balance the detection complexity with BER performance with compatible information rate in dynamic, adaptive MIMO communications
environments.

Arsenic behaviour from groundwater and soil to crops:impacts on agriculture and food safety

High levels of As in groundwater commonly found in Bangladesh and other parts of Asia not only pose a risk via drinking water consumption but also a risk in agricultural sustainability and food safety. This review attempts to provide an overview of current knowledge and gaps related to the assessment and management of these risks, including the behaviour of As in the soil-plant system, uptake, phytotoxicity, As speciation in foods, dietary habits, and human health risks. Special emphasis has been given to the situation in Bangladesh, where groundwater via shallow tube wells is the most important source of irrigation water in the dry season. Within the soil-plant system, there is a distinct difference in behaviour of As under flooded conditions, where arsenite (AsIII) predominates, and under nonflooded conditions, where arsenate (AsV) predominates. The former is regarded as most toxic to humans and plants. Limited data indicate that As-contaminated irrigation water can result in a slow buildup of As in the topsoil. In some cases the buildup is reflected by the As levels in crops, in others not. It is not yet possible to predict As uptake and toxicity in plants based on soil parameters. It is unknown under what conditions and in what time frame As is building up in the soil. Representative phytotoxicity data necessary to evaluate current and future soil concentrations are not yet available. Although there are no indications that crop production is currently inhibited by As, long-term risks are clearly present. Therefore, with concurrent assessments of the risks, management options to further prevent As accumulation in the topsoil should already have been explored. With regard to human health, data on As speciation in foods in combination with food consumption data are needed to assess dietary exposure, and these data should include spatial and seasonal variability. It is important to control confounding factors in assessing the risks. In a country where malnutrition is prevalent, levels of inorganic As in foods should be balanced against the nutritional value of the foods. Regarding agriculture, As is only one of the many factors that may pose a risk to the sustainability of crop production. Other risk factors such as nutrient depletion and loss of organic matter also must be taken into account to set priorities in terms of research, management, and overall strategy.

VQ tree search system based on bit level systolic arrays

A bit-level systolic array system for performing a binary tree vector quantization (VQ) codebook search is described. This is based on a highly regular VLSI building block circuit. The system in question exhibits a very high data rate suitable for a range of real-time applications. A technique is described which reduces the storage requirements of such a system by 50%, with a corresponding decrease in hardware complexity.

A bit-level systolic architecture for implementing a VQ tree search

A bit-level systolic array system for performing a binary tree Vector Quantization codebook search is described. This consists of a linear chain of regular VLSI building blocks and exhibits data rates suitable for a wide range of real-time applications. A technique is described which reduces the computation required at each node in the binary tree to that of a single inner product operation. This method applies to all the common distortion measures (including the Euclidean distance, the Weighted Euclidean distance and the Itakura-Saito distortion measure) and significantly reduces the hardware required to implement the tree search system. © 1990 Kluwer Academic Publishers.

Tea tree oil (5%) body wash versus standard care (Johnson's Baby Softwash) to prevent colonization with methicillin-resistant Staphylococcus aureus in critically ill adults::a randomized controlled trial

OBJECTIVES: To determine whether the daily use of 5% tea tree oil (TTO) body wash (Novabac 5% Skin Wash) compared with standard care [Johnson's Baby Softwash (JBS)] had a lower incidence of methicillin-resistant Staphylococcus aureus (MRSA) colonization.

PATIENTS: The study setting was two intensive care units (ICUs; mixed medical, surgical and trauma) in Northern Ireland between October 2007 and July 2009. The study population comprised 391 patients who were randomized to JBS or TTO body wash.

METHODS: This was a Phase 2/3, prospective, open-label, randomized, controlled trial. Trial registration: ISRCTN65190967. The primary outcome was new MRSA colonization during ICU stay. Secondary outcomes included the incidence of MRSA bacteraemia and maximum increase in sequential organ failure assessment score.

RESULTS: A total of 445 patients were randomized to the study. After randomization, 54 patients were withdrawn; 30 because of a positive MRSA screen at study entry, 11 due to lack of consent, 11 were inappropriately randomized and 2 had adverse reactions. Thirty-nine (10%) patients developed new MRSA colonization (JBS n?=?22, 11.2%; TTO body wash n?=?17, 8.7%). The difference in percentage colonized (2.5%, 95% CI -?8.95 to 3.94; P?=?0.50) was not significant. The mean maximum increase in sequential organ failure assessment score was not significant (JBS 1.44, SD 1.92; TTO body wash 1.28, SD 1.79; P?=?0.85) and no study patients developed MRSA bacteraemia.

CONCLUSIONS: Compared with JBS, TTO body wash cannot be recommended as an effective means of reducing MRSA colonization.

Response of farmland biodiversity to the introduction of bioenergy crops: effects of local factors and surrounding landscape context

The recent growth in bioenergy crop cultivation, stimulated by the need to implement measures to reduce net CO emissions, is driving major land-use changes with consequences for biodiversity and ecosystem service provision. Although the type of bioenergy crop and its associated management is likely to affect biodiversity at the local (field) scale, landscape context and its interaction with crop type may also influence biodiversity on farms. In this study, we assessed the impact of replacing conventional agricultural crops with two model bioenergy crops (either oilseed rape Brassica napus or Miscanthus × giganteus) on vascular plant, bumblebee, solitary bee, hoverfly and carabid beetle richness, diversity and abundance in 50 sites in Ireland. We assessed whether within-field biodiversity was also related to surrounding landscape structure. We found that local- and landscape-scale variables correlated with biodiversity in these agricultural landscapes. Overall, the differences between the bioenergy crops and the conventional crops on farmland biodiversity were mostly positive (e.g. higher vascular plant richness in Miscanthus planted on former conventional tillage, higher solitary bee abundance and richness in Miscanthus and oilseed rape compared with conventional crops) or neutral (e.g. no differences between crop types for hoverflies and bumblebees). We showed that these crop type effects were independent of (i.e. no interactions with) the surrounding landscape composition and configuration. However, surrounding landscape context did relate to biodiversity in these farms, negatively for carabid beetles and positively for hoverflies. Although we conclude that the bioenergy crops compared favourably with conventional crops in terms of biodiversity of the taxa studied at the field scale, the effects of large-scale planting in these landscapes could result in very different impacts. Maintaining ecosystem functioning and the delivery of ecosystem services will require a greater understanding of impacts at the landscape scale to ensure the sustainable development of climate change mitigation measures.

The forgiving tree: a self-healing distributed data structure

We consider the problem of self-healing in peer-to-peer networks that are under repeated attack by an omniscient adversary. We assume that the following process continues for up to n rounds where n is the total number of nodes initially in the network: the adversary deletesan arbitrary node from the network, then the network responds by quickly adding a small number of new edges.

We present a distributed data structure that ensures two key properties. First, the diameter of the network is never more than O(log Delta) times its original diameter, where Delta is the maximum degree of the network initially. We note that for many peer-to-peer systems, Delta is polylogarithmic, so the diameter increase would be a O(loglog n) multiplicative factor. Second, the degree of any node never increases by more than 3 over its original degree. Our data structure is fully distributed, has O(1) latency per round and requires each node to send and receive O(1) messages per round. The data structure requires an initial setup phase that has latency equal to the diameter of the original network, and requires, with high probability, each node v to send O(log n) messages along every edge incident to v. Our approach is orthogonal and complementary to traditional topology-based approaches to defending against attack.

Political Posturing or Real Powers: Control of Genetically Modified Crops by the Member States and their Regions

The cultivation of genetically modified (GM) crops in the EU is highly harmonised, involving a central authorisation procedure that aims to ensure a high level of environmental and human health protection. However conflicts over authority persist and the Commission has responded to a combination of internal and external pressures with a more flexible approach to coexistence, a proposed opt-out clause and recently a promise by the head of the Commission to review the existing EU GM legislative regime, providing an opportunity to consider and suggest paths of development. In light of the significance of multilevel governance and subsidiarity for GM cultivation, this paper considers the policy-making powers of the Member States and subnational regions in this regime, focussing upon post-authorisation options in particular. A number of core mechanisms exist, including voluntary measures, safeguard clauses, coexistence measures, a proposed express opt-out and Article 4(2) TEU on ‘national identity. These mechanisms are examined in light of the goals and challenges of multilevel governance, in order to consider whether the relevant powers are located at the appropriate level. Overall, it is apparent that the developments occurring at the EU level are strengthening multilevel governance, but with significant opportunities to improve it further through focussing on the supporting roles and the regional levels in particular.

Extended Tree Augmented Naive Classifier

This work proposes an extended version of the well-known tree-augmented naive Bayes (TAN) classifier where the structure learning step is performed without requiring features to be connected to the class. Based on a modification of Edmonds’ algorithm, our structure learning procedure explores a superset of the structures that are considered by TAN, yet achieves global optimality of the learning score function in a very efficient way (quadratic in the number of features, the same complexity as learning TANs). A range of experiments show that we obtain models with better accuracy than TAN and comparable to the accuracy of the state-of-the-art classifier averaged one-dependence estimator.