Networking protocols for long life wireless sensor networks

My original contribution to knowledge is the creation of a WSN system that further improves the functionality of existing technology, whilst achieving improved power consumption and reliability. This thesis concerns the development of industrially applicable wireless sensor networks that are low-power, reliable and latency aware. This work aims to improve upon the state of the art in networking protocols for low-rate multi-hop wireless sensor networks. Presented is an application-driven co-design approach to the development of such a system. Starting with the physical layer, hardware was designed to meet industry specified requirements. The end system required further investigation of communications protocols that could achieve the derived application-level system performance specifications. A CSMA/TDMA hybrid MAC protocol was developed, leveraging numerous techniques from the literature and novel optimisations. It extends the current art with respect to power consumption for radio duty-cycled applications, and reliability, in dense wireless sensor networks, whilst respecting latency bounds. Specifically, it provides 100% packet delivery for 11 concurrent senders transmitting towards a single radio duty cycled sink-node. This is representative of an order of magnitude improvement over the comparable art, considering MAC-only mechanisms. A novel latency-aware routing protocol was developed to exploit the developed hardware and MAC protocol. It is based on a new weighted objective function with multiple fail safe mechanisms to ensure extremely high reliability and robustness. The system was empirically evaluated on two hardware platforms. These are the application-specific custom 868 MHz node and the de facto community-standard TelosB. Extensive empirical comparative performance analyses were conducted against the relevant art to demonstrate the advances made. The resultant system is capable of exceeding 10-year battery life, and exhibits reliability performance in excess of 99.9%.

Anti-CTLA-4 treatment induces IL-10-producing ICOS+ regulatory T cells displaying IDO-dependent anti-inflammatory properties in a mouse model of colitis.

BACKGROUND AND AIMS: Cytotoxic T lymphocyte-associated antigen 4 (CTLA-4) has been shown to act as a negative regulator of T cell function and has been implicated in the regulation of T helper 1 (Th1)/Th2 development and the function of regulatory T cells. Tests were carried out to determine whether anti-CTLA-4 treatment would alter the polarisation of naive T cells in vivo. METHODS: Mice were treated with anti-CTLA-4 monoclonal antibody (mAb) (UC10-4F10) at the time of immunisation or colonic instillation of trinitrobenzene sulfonic acid (TNBS). The cytokines produced by lymph node cells after in vitro antigenic stimulation and the role of indoleamine 2,3 dioxygenase (IDO) and of interleukin-10 (IL-10) were tested, and the survival of mice was monitored. RESULTS: Injection of anti-CTLA-4 mAb in mice during priming induced the development of adaptive CD4(+) regulatory T cells which expressed high levels of ICOS (inducible co-stimulator), secreted IL-4 and IL-10. This treatment inhibited Th1 memory responses in vivo and repressed experimental intestinal inflammation. The anti-CTLA-4-induced amelioration of disease correlated with IDO expression and infiltration of ICOS(high) Foxp3(+) T cells in the intestine, suggesting that anti-CTLA-4 acted indirectly through the development of regulatory T cells producing IL-10 and inducing IDO. CONCLUSIONS: These observations emphasise the synergy between IL-10 and IDO as anti-inflammatory agents and highlight anti-CTLA-4 treatment as a potential novel immunotherapeutic approach for inducing adaptive regulatory T cells.

Estimating the magnitude of trastuzumab effects within patient subgroups in the HERA trial.

BACKGROUND: Trastuzumab (Herceptin(R)) improves disease-free survival (DFS) and overall survival for patients with human epidermal growth factor receptor 2 (HER2)-positive early breast cancer. We aimed to assess the magnitude of its clinical benefit for subpopulations defined by nodal and steroid hormone receptor status using data from the Herceptin Adjuvant (HERA) study. PATIENTS AND METHODS: HERA is an international multicenter randomized trial comparing 1 or 2 years of trastuzumab treatment with observation after standard chemotherapy in women with HER2-positive breast cancer. In total, 1703 women randomized to 1-year trastuzumab and 1698 women randomized to observation were included in these analyses. Median follow-up was 23.5 months. The primary endpoint was DFS. RESULTS: The overall hazard ratio (HR) for trastuzumab versus observation was 0.64 [95% confidence interval (CI) 0.54-0.76; P < 0.0001], ranging from 0.46 to 0.82 for subgroups. Estimated improvement in 3-year DFS in subgroups ranged from +11.3% to +0.6%. Patients with the best prognosis (those with node-negative disease and tumors 1.1-2.0 cm) had benefit similar to the overall cohort (HR 0.53, 95% CI 0.26-1.07; 3-year DFS improvement +4.6%, 95% CI -4.0% to 13.2%). CONCLUSIONS: Adjuvant trastuzumab therapy reduces the risk of relapse similarly across subgroups defined by nodal status and steroid hormone receptor status, even those at relatively low risk for relapse.

Nested dictionary learning for hierarchical organization of imagery and text

A tree-based dictionary learning model is developed for joint analysis of imagery and associated text. The dictionary learning may be applied directly to the imagery from patches, or to general feature vectors extracted from patches or superpixels (using any existing method for image feature extraction). Each image is associated with a path through the tree (from root to a leaf), and each of the multiple patches in a given image is associated with one node in that path. Nodes near the tree root are shared between multiple paths, representing image characteristics that are common among different types of images. Moving toward the leaves, nodes become specialized, representing details in image classes. If available, words (text) are also jointly modeled, with a path-dependent probability over words. The tree structure is inferred via a nested Dirichlet process, and a retrospective stick-breaking sampler is used to infer the tree depth and width.

Gene selection using iterative feature elimination random forests for survival outcomes.

Although many feature selection methods for classification have been developed, there is a need to identify genes in high-dimensional data with censored survival outcomes. Traditional methods for gene selection in classification problems have several drawbacks. First, the majority of the gene selection approaches for classification are single-gene based. Second, many of the gene selection procedures are not embedded within the algorithm itself. The technique of random forests has been found to perform well in high-dimensional data settings with survival outcomes. It also has an embedded feature to identify variables of importance. Therefore, it is an ideal candidate for gene selection in high-dimensional data with survival outcomes. In this paper, we develop a novel method based on the random forests to identify a set of prognostic genes. We compare our method with several machine learning methods and various node split criteria using several real data sets. Our method performed well in both simulations and real data analysis.Additionally, we have shown the advantages of our approach over single-gene-based approaches. Our method incorporates multivariate correlations in microarray data for survival outcomes. The described method allows us to better utilize the information available from microarray data with survival outcomes.

Primary vascularization of the graft determines the immunodominance of murine minor H antigens during organ transplantation.

Grafts can be rejected even when matched for MHC because of differences in the minor histocompatibility Ags (mH-Ags). H4- and H60-derived epitopes are known as immunodominant mH-Ags in H2(b)-compatible BALB.B to C57BL/6 transplantation settings. Although multiple explanations have been provided to explain immunodominance of Ags, the role of vascularization of the graft is yet to be determined. In this study, we used heart (vascularized) and skin (nonvascularized) transplantations to determine the role of primary vascularization of the graft. A higher IFN-γ response toward H60 peptide occurs in heart recipients. In contrast, a higher IFN-γ response was generated against H4 peptide in skin transplant recipients. Peptide-loaded tetramer staining revealed a distinct antigenic hierarchy between heart and skin transplantation: H60-specific CD8(+) T cells were the most abundant after heart transplantation, whereas H4-specific CD8(+) T cells were more abundant after skin graft. Neither the tissue-specific distribution of mH-Ags nor the draining lymph node-derived dendritic cells correlated with the observed immunodominance. Interestingly, non-primarily vascularized cardiac allografts mimicked skin grafts in the observed immunodominance, and H60 immunodominance was observed in primarily vascularized skin grafts. However, T cell depletion from the BALB.B donor prior to cardiac allograft induces H4 immunodominance in vascularized cardiac allograft. Collectively, our data suggest that immediate transmigration of donor T cells via primary vascularization is responsible for the immunodominance of H60 mH-Ag in organ and tissue transplantation.

B cells in rheumatoid synovitis.

In rheumatoid arthritis, T cells, B cells, macrophages, and dendritic cells invade the synovial membranes, establishing complex microstructures that promote inflammatory/tissue destructive lesions. B cell involvement has been considered to be limited to autoantibody production. However, recent studies suggest that B cells support rheumatoid disease through other mechanisms. A critical element of rheumatoid synovitis is the process of ectopic lymphoid neogenesis, with highly efficient lymphoid architectures established in a nonlymphoid tissue site. Rheumatoid synovitis recapitulates the pathways of lymph node formation, and B cells play a key role in this process. Furthermore, studies of rheumatoid lesions implanted in immunodeficient mice suggest that T cell activation in synovitis is B cell dependent, indicating the role played by B cells in presenting antigens and providing survival signals.

What the brain stem tells the frontal cortex. II. Role of the SC-MD-FEF pathway in corollary discharge.

One way we keep track of our movements is by monitoring corollary discharges or internal copies of movement commands. This study tested a hypothesis that the pathway from superior colliculus (SC) to mediodorsal thalamus (MD) to frontal eye field (FEF) carries a corollary discharge about saccades made into the contralateral visual field. We inactivated the MD relay node with muscimol in monkeys and measured corollary discharge deficits using a double-step task: two sequential saccades were made to the locations of briefly flashed targets. To make second saccades correctly, monkeys had to internally monitor their first saccades; therefore deficits in the corollary discharge representation of first saccades should disrupt second saccades. We found, first, that monkeys seemed to misjudge the amplitudes of their first saccades; this was revealed by systematic shifts in second saccade end points. Thus corollary discharge accuracy was impaired. Second, monkeys were less able to detect trial-by-trial variations in their first saccades; this was revealed by reduced compensatory changes in second saccade angles. Thus corollary discharge precision also was impaired. Both deficits occurred only when first saccades went into the contralateral visual field. Single-saccade generation was unaffected. Additional deficits occurred in reaction time and overall performance, but these were bilateral. We conclude that the SC-MD-FEF pathway conveys a corollary discharge used for coordinating sequential saccades and possibly for stabilizing vision across saccades. This pathway is the first elucidated in what may be a multilevel chain of corollary discharge circuits extending from the extraocular motoneurons up into cerebral cortex.

Diminishment of respiratory sinus arrhythmia foreshadows doxorubicin-induced cardiomyopathy.

BACKGROUND: The development of a microcomputer-based device permits quick, simple, and noninvasive quantification of the respiratory sinus arrhythmia (RSA) during quiet breathing. METHODS AND RESULTS: We prospectively and serially measured the radionuclide left ventricular ejection fraction and the RSA amplitude in 34 cancer patients receiving up to nine monthly bolus treatments with doxorubicin hydrochloride (60 mg/m2). Of the eight patients who ultimately developed symptomatic doxorubicin-induced congestive heart failure, seven (87.5%) demonstrated a significant decline in RSA amplitude; five of 26 subjects without clinical symptoms of cardiotoxicity (19.2%) showed a similar RSA amplitude decline. On average, significant RSA amplitude decline occurred 3 months before the last planned doxorubicin dose in patients destined to develop clinical congestive heart failure. CONCLUSION: Overall, RSA amplitude abnormality proved to be a more specific predictor of clinically significant congestive heart failure than did serial resting radionuclide ejection fractions.

Synthesis of antibodies and immunoglobulins bearing recipient allotypic markers and donor idiotypic specificities in irradiated rabbits grafted with allogeneic cells from hyperimmune donors

Irradiated rabbits were grafted with a mixture of bone marrow, lymph node and spleen cells from donors hyperimmunized against tobacco mosaic virus (TMV). Recipient and donors were characterized by different allotypic specificities. Antibodies synthesized in the recipients display allotypic markers from the recipients but idiotypic specificities cross-reactive with those of donor antibodies. The results show that the differentiation of new host B cells is influenced by the presence of donor memory cells and are interpreted in the light of network concepts.

Synthesis of high affinity antibodies in irradiated rabbits grafted with allogeneic cells from hyperimmune donors

Irradiated rabbits grafted with allogeneic lymph node, spleen and bone marrow cells from a donor rabbit hyperimmunized against tobacco mosaic virus synthesize high affinity antibodies, displaying mainly recipient allotypic specificities, after antigen boosting. By contrast, recipient rabbits from non-immune donors synthesize antibodies of lower affinity. It is suggested that the differentiation of new emerging host B cells is specifically influenced by the presence of donor-memory cells.

Performance evaluation of the register insertion protocol for voice-data integration

The performance of the register insertion protocol for mixed voice-data traffic is investigated by simulation. The simulation model incorporates a common insertion buffer for station and ring packets. Bandwidth allocation is achieved by imposing a queue limit at each node. A simple priority scheme is introduced by allowing the queue limit to vary from node to node. This enables voice traffic to be given priority over data. The effect on performance of various operational and design parameters such as ratio of voice to data traffic, queue limit and voice packet size is investigated. Comparisons are made where possible with related work on other protocols proposed for voice-data integration. The main conclusions are: (a) there is a general degradation of performance as the ratio of voice traffic to data traffic increases, (b) substantial improvement in performance can be achieved by restricting the queue length at data nodes and (c) for a given ring utilisation, smaller voice packets result in lower delays for both voice and data traffic.

Evaluation of loadsharing algorithms for heterogeneous distributed systems

The performance of loadsharing algorithms for heterogeneous distributed systems is investigated by simulation. The systems considered are networks of workstations (nodes) which differ in processing power. Two parameters are proposed for characterising system heterogeneity, namely the variance and skew of the distribution of processing power among the network nodes. A variety of networks are investigated, with the same number of nodes and total processing power, but with the processing power distributed differently among the nodes. Two loadsharing algorithms are evaluated, at overall system loadings of 50% and 90%, using job response time as the performance metric. Comparison is made with the ideal situation of ‘perfect sharing’, where it is assumed that the communication delays are zero and that complete knowledge is available about job lengths and the loading at the different nodes, so that an arriving job can be sent to the node where it will be completed in the shortest time. The algorithms studied are based on those already in use for homogeneous networks, but were adapted to take account of system heterogeneity. Both algorithms take into account the differences in the processing powers of the nodes in their location policies, but differ in the extent to which they ‘discriminate’ against the slower nodes. It is seen that the relative performance of the two is strongly influenced by the system utilisation and the distribution of processing power among the nodes.

Virtual manufacturing and design in the real world - implementation and scalability on HPPC systems

Virtual manufacturing and design assessment increasingly involve the simulation of interacting phenomena, sic. multi-physics, an activity which is very computationally intensive. This chapter describes an attempt to address the parallel issues associated with a multi-physics simulation approach based upon a range of compatible procedures operating on one mesh using a single database - the distinct physics solvers can operate separately or coupled on sub-domains of the whole geometric space. Moreover, the finite volume unstructured mesh solvers use different discretization schemes (and, particularly, different ‘nodal’ locations and control volumes). A two-level approach to the parallelization of this simulation software is described: the code is restructured into parallel form on the basis of the mesh partitioning alone, that is, without regard to the physics. However, at run time, the mesh is partitioned to achieve a load balance, by considering the load per node/element across the whole domain. The latter of course is determined by the problem specific physics at a particular location.

Multilevel mesh partitioning for heterogeneous communication networks

Multilevel algorithms are a successful class of optimisation techniques which address the mesh partitioning problem for distributing unstructured meshes onto parallel computers. They usually combine a graph contraction algorithm together with a local optimisation method which refines the partition at each graph level. To date these algorithms have been used almost exclusively to minimise the cut edge weight in the graph with the aim of minimising the parallel communication overhead, but recently there has been a perceived need to take into account the communications network of the parallel machine. For example the increasing use of SMP clusters (systems of multiprocessor compute nodes with very fast intra-node communications but relatively slow inter-node networks) suggest the use of hierarchical network models. Indeed this requirement is exacerbated in the early experiments with meta-computers (multiple supercomputers combined together, in extreme cases over inter-continental networks). In this paper therefore, we modify a multilevel algorithm in order to minimise a cost function based on a model of the communications network. Several network models and variants of the algorithm are tested and we establish that it is possible to successfully guide the optimisation to reflect the chosen architecture.