Two-stage power network reconfiguration strategy considering node importance and restored generation capacity

Network reconfiguration after complete blackout of a power system is an essential step for power system restoration. A new node importance evaluation method is presented based on the concept of regret, and maximisation of the average importance of a path is employed as the objective of finding the optimal restoration path. Then, a two-stage method is presented to optimise the network reconfiguration strategy. Specifically, the restoration sequence of generating units is first optimised so as to maximise the restored generation capacity, then the optimal restoration path is selected to restore the generating nodes concerned and the issues of selecting a serial or parallel restoration mode and the reconnecting failure of a transmission line are next considered. Both the restoration path selection and skeleton-network determination are implemented together in the proposed method, which overcomes the shortcoming of separate decision-making in the existing methods. Finally, the New England 10-unit 39-bus power system and the Guangzhou power system in South China are employed to demonstrate the basic features of the proposed method.

Prediction and proactivity in real-time interactive music systems

We advocate for the use of predictive techniques in interactive computer music systems. We suggest that the inclusion of prediction can assist in the design of proactive rather than reactive computational performance partners. We summarize the significant role prediction plays in human musical decisions, and the only modest use of prediction in interactive music systems to date. After describing how we are working toward employing predictive processes in our own metacreation software we reflect on future extensions to these approaches.

A metastatic neuroendocrine anaplastic small cell tumor in a patient with multiple endocrine neoplasia type 1 syndrome : assessment of disease status and response to doxorubicin, cyclophosphamide, etoposide chemotherapy through scintigraphic imaging with 111In-pentetreotide

Extrapulmonary small cell and small cell neuroendocrine tumors of unknown primary site are, in general, aggressive neoplasms with a short median survival. Like small cell lung cancer (SCLC), they often are responsive to chemotherapy and radiotherapy. Small cell lung cancer and well differentiated neuroendocrine carcinomas of the gastrointestinal tract and pancreas tend to express somatostatin receptors. These tumors may be localized in patients by scintigraphic imaging using radiolabeled somatostatin analogues. A patient with an anaplastic neuroendocrine small cell tumor arising on a background of multiple endocrine neoplasia type 1 syndrome is reported. The patient had a known large pancreatic gastrinoma and previously treated parathyroid adenopathy. At presentation, there was small cell cancer throughout the liver and skeleton. Imaging with a radiolabeled somatostatin analogue, 111In- pentetreotide (Mallinckrodt Medical B. V., Petten, Holland), revealed all sites of disease detected by routine biochemical and radiologic methods. After six cycles of chemotherapy with doxorubicin, cyclophosphamide, and etoposide, there was almost complete clearance of the metastatic disease. 111In-pentetreotide scintigraphy revealed uptake consistent with small areas of residual disease in the liver, the abdomen (in mesenteric lymph nodes), and posterior thorax (in a rib). The primary gastrinoma present before the onset of the anaplastic small cell cancer showed no evidence of response to the treatment. The patient remained well for 1 year and then relapsed with brain, lung, liver, and skeletal metastases. Despite an initial response to salvage radiotherapy and chemotherapy with carboplatin and dacarbazine, the patient died 6 months later.

Local stress-strain distribution and load transfer across cartilage matrix at micro-scale using combined microscopy-based finite element method

Articular cartilage is the load-bearing tissue that consists of proteoglycan macromolecules entrapped between collagen fibrils in a three-dimensional architecture. To date, the drudgery of searching for mathematical models to represent the biomechanics of such a system continues without providing a fitting description of its functional response to load at micro-scale level. We believe that the major complication arose when cartilage was first envisaged as a multiphasic model with distinguishable components and that quantifying those and searching for the laws that govern their interaction is inadequate. To the thesis of this paper, cartilage as a bulk is as much continuum as is the response of its components to the external stimuli. For this reason, we framed the fundamental question as to what would be the mechano-structural functionality of such a system in the total absence of one of its key constituents-proteoglycans. To answer this, hydrated normal and proteoglycan depleted samples were tested under confined compression while finite element models were reproduced, for the first time, based on the structural microarchitecture of the cross-sectional profile of the matrices. These micro-porous in silico models served as virtual transducers to produce an internal noninvasive probing mechanism beyond experimental capabilities to render the matrices micromechanics and several others properties like permeability, orientation etc. The results demonstrated that load transfer was closely related to the microarchitecture of the hyperelastic models that represent solid skeleton stress and fluid response based on the state of the collagen network with and without the swollen proteoglycans. In other words, the stress gradient during deformation was a function of the structural pattern of the network and acted in concert with the position-dependent compositional state of the matrix. This reveals that the interaction between indistinguishable components in real cartilage is superimposed by its microarchitectural state which directly influences macromechanical behavior.

Delineating breast cancer cell interactions with engineered bone microenvironments

The mechanisms leading to colonization of metastatic breast cancer cells (BCa) in the skeleton are still not fully understood. Here, we demonstrate that mineralized extracellular matrices secreted by primary human osteoblasts (hOBM) modulate cellular processes associated with BCa colonization of bone. A panel of four BCa cell lines of different bone-metastatic potential (T47D, SUM1315, MDA-MB-231, and the bone-seeking subline MDA-MB-231BO) was cultured on hOBM. After 3 days, the metastatic BCa cells had undergone morphological changes on hOBM and were aligned along the hOBM's collagen type I fibrils that were decorated with bone-specific proteins. In contrast, nonmetastatic BCa cells showed a random orientation on hOBM. Atomic force microscopy-based single-cell force spectroscopy revealed that the metastatic cell lines adhered more strongly to hOBM compared with nonmetastatic cells. Function-blocking experiments indicated that β1-integrins mediated cell adhesion to hOBM. In addition, metastatic BCa cells migrated directionally and invaded hOBM, which was accompanied by enhanced MMP-2 and -9 secretion. Furthermore, we observed gene expression changes associated with osteomimickry in BCa cultured on hOBM. As such, osteopontin mRNA levels were significantly increased in SUM1315 and MDA-MB-231BO cells in a β1-integrin-dependent manner after growing for 3 days on hOBM compared with tissue culture plastic. In conclusion, our results show that extracellular matrices derived from human osteoblasts represent a powerful experimental platform to dissect mechanisms underlying critical steps in the development of bone metastases.

PITX2 and non-canonical Wnt pathway interaction in metastatic prostate cancer

The non-canonical Wnt pathway, a regulator of cellular motility and morphology, is increasingly implicated in cancer metastasis. In a quantitative PCR array analysis of 84 Wnt pathway associated genes, both non-canonical and canonical pathways were activated in primary and metastatic tumors relative to normal prostate. Expression of the Wnt target gene PITX2 in a prostate cancer (PCa) bone metastasis was strikingly elevated over normal prostate (over 2,000-fold) and primary prostate cancer (over 200-fold). The elevation of PITX2 protein was also evident on tissue microarrays, with strong PITX2 immunostaining in PCa skeletal and, to a lesser degree, soft tissue metastases. PITX2 is associated with cell migration during normal tissue morphogenesis. In our studies, overexpression of individual PITX2A/B/C isoforms stimulated PC-3 PCa cell motility, with the PITX2A isoform imparting a specific motility advantage in the presence of non-canonical Wnt5a stimulation. Furthermore, PITX2 specific shRNA inhibited PC-3 cell migration toward bone cell derived chemoattractant. These experimental results support a pivotal role of PITX2A and non-canonical Wnt signaling in enhancement of PCa cell motility, suggest PITX2 involvement in homing of PCa to the skeleton, and are consistent with a role for PITX2 in PCa metastasis to soft and bone tissues. Our findings, which significantly expand previous evidence that PITX2 is associated with risk of PCa biochemical recurrence, indicate that variation in PITX2 expression accompanies and may promote prostate tumor progression and metastasis.

Sampling designs on stream networks using the pseudo-Bayesian approach

Monitoring stream networks through time provides important ecological information. The sampling design problem is to choose locations where measurements are taken so as to maximise information gathered about physicochemical and biological variables on the stream network. This paper uses a pseudo-Bayesian approach, averaging a utility function over a prior distribution, in finding a design which maximizes the average utility. We use models for correlations of observations on the stream network that are based on stream network distances and described by moving average error models. Utility functions used reflect the needs of the experimenter, such as prediction of location values or estimation of parameters. We propose an algorithmic approach to design with the mean utility of a design estimated using Monte Carlo techniques and an exchange algorithm to search for optimal sampling designs. In particular we focus on the problem of finding an optimal design from a set of fixed designs and finding an optimal subset of a given set of sampling locations. As there are many different variables to measure, such as chemical, physical and biological measurements at each location, designs are derived from models based on different types of response variables: continuous, counts and proportions. We apply the methodology to a synthetic example and the Lake Eacham stream network on the Atherton Tablelands in Queensland, Australia. We show that the optimal designs depend very much on the choice of utility function, varying from space filling to clustered designs and mixtures of these, but given the utility function, designs are relatively robust to the type of response variable.

Rapid yet accurate speech indexing using dynamic match lattice spotting

The support for typically out-of-vocabulary query terms such as names, acronyms, and foreign words is an important requirement of many speech indexing applications. However, to date many unrestricted vocabulary indexing systems have struggled to provide a balance between good detection rate and fast query speeds. This paper presents a fast and accurate unrestricted vocabulary speech indexing technique named Dynamic Match Lattice Spotting (DMLS). The proposed method augments the conventional lattice spotting technique with dynamic sequence matching, together with a number of other novel algorithmic enhancements, to obtain a system that is capable of searching hours of speech in seconds while maintaining excellent detection performance

Resilient Navigation through Probabilistic Modality Reconfiguration

This paper proposes an approach to achieve resilient navigation for indoor mobile robots. Resilient navigation seeks to mitigate the impact of control, localisation, or map errors on the safety of the platform while enforcing the robot’s ability to achieve its goal. We show that resilience to unpredictable errors can be achieved by combining the benefits of independent and complementary algorithmic approaches to navigation, or modalities, each tuned to a particular type of environment or situation. In this paper, the modalities comprise a path planning method and a reactive motion strategy. While the robot navigates, a Hidden Markov Model continually estimates the most appropriate modality based on two types of information: context (information known a priori) and monitoring (evaluating unpredictable aspects of the current situation). The robot then uses the recommended modality, switching between one and another dynamically. Experimental validation with a SegwayRMP- based platform in an office environment shows that our approach enables failure mitigation while maintaining the safety of the platform. The robot is shown to reach its goal in the presence of: 1) unpredicted control errors, 2) unexpected map errors and 3) a large injected localisation fault.

Nurse-led chest drain removal in a cardiac high dependency unit

Within the cardiac high dependency unit it is currently a member of the surgical team who makes the decision for a patient's chest drain to be removed after cardiac surgery. This has often resulted in delays in discharging one patient and therefore in admitting the next. A pilot study was carried out using a working standard that had been developed, incorporating an algorithmic model. The results have enabled nursing staff in a cardiac high dependency unit to undertake this responsibility independently.

Multiphase experiments with at least one later laboratory phase. I. orthogonal designs

The paper provides a systematic approach to designing the laboratory phase of a multiphase experiment, taking into account previous phases. General principles are outlined for experiments in which orthogonal designs can be employed. Multiphase experiments occur widely, although their multiphase nature is often not recognized. The need to randomize the material produced from the first phase in the laboratory phase is emphasized. Factor-allocation diagrams are used to depict the randomizations in a design and the use of skeleton analysis-of-variance (ANOVA) tables to evaluate their properties discussed. The methods are illustrated using a scenario and a case study. A basis for categorizing designs is suggested. This article has supplementary material online.

Построение автоматической навигационной системы малогабаритного беспилотного летательного аппарата многократного применения = Development of automatic navigation management system for small unmanned aerial vehicle

Современный этап развития комплексов автоматического управления и навигации малогабаритными БЛА многократного применения предъявляет высокие требования к автономности, точности и миниатюрности данных систем. Противоречивость требований диктует использование функционального и алгоритмического объединения нескольких разнотипных источников навигационной информации в едином вычислительном процессе на основе методов оптимальной фильтрации. Получили широкое развитие бесплатформенные инерциальные навигационные системы (БИНС) на основе комплексирования данных микромеханических датчиков инерциальной информации и датчиков параметров движения в воздушном потоке с данными спутниковых навигационных систем (СНС). Однако в современных условиях такой подход не в полной мере реализует требования к помехозащищённости, автономности и точности получаемой навигационной информации. Одновременно с этим достигли значительного прогресса навигационные системы, использующие принципы корреляционно экстремальной навигации по оптическим ориентирам и цифровым картам местности. Предлагается схема построения автономной автоматической навигационной системы (АНС) для БЛА многоразового применения на основе объединения алгоритмов БИНС, спутниковой навигационной системы и оптической навигационной системы. The modern stage of automatic control and guidance systems development for small unmanned aerial vehicles (UAV) is determined by advanced requirements for autonomy, accuracy and size of the systems. The contradictory of the requirements dictates novel functional and algorithmic tight coupling of several different onboard sensors into one computational process, which is based on methods of optimal filtering. Nowadays, data fusion of micro-electro mechanical sensors of inertial measurement units, barometric pressure sensors, and signals of global navigation satellite systems (GNSS) receivers is widely used in numerous strap down inertial navigation systems (INS). However, the systems do not fully comply with such requirements as jamming immunity, fault tolerance, autonomy, and accuracy of navigation. At the same time, the significant progress has been recently demonstrated by the navigation systems, which use the correlation extremal principle applied for optical data flow and digital maps. This article proposes a new architecture of automatic navigation management system (ANMS) for small UAV, which combines algorithms of strap down INS, satellite navigation and optical navigation system.

Comparison of ovine mesenchymal cell and osteoblast osteogeic capacity in 2D and 3D

This thesis explored the different bone-forming potential of specific bone cells with differing embryological origin, on conventional culture platforms compared to 3D biocompatible scaffolds in vitro. Bone mesenchymal stem cells, mandibular osteoblasts and long bone osteoblasts from adult and juvenile sheep were compared in the study, as the embryological origin of the osteoblasts from the craniofacial and appendicular skeleton differs. The study demonstrated differing characteristics of the various cell types when cultured on the two different platforms compared and this may have an impact on future research into cell seeded tissue scaffolds to aid in vivo tissue regeneration.

Are bone-anchored prostheses about to revolutionise the world of prosthetics?

Individuals with limb amputation fitted with conventional socket-suspended prostheses often experience socket related discomfort leading to a significant decrease in quality of life. Most of these concerns can be overcome by surgical techniques enabling bone-anchored prostheses. In this case, the prosthesis is attached directly to the residual skeleton through a percutaneous implant. The primary aim of this study is to present the current advances in these surgical techniques worldwide with a strong focus on the developments in Australia. The secondary aim is to provide an overview of the possible critical changes that may occurred in the world of prosthetic following these developments in bone-anchored prostheses.

Repeatability of static load bearing exercises during rehabilitation of individuals with transfemoral amputation fitted with osseointegrated implant

Bone-anchored prostheses, relying on implants to attach the prosthesis directly to the residual skeleton, are the ultimate resort for patients with transfemoral amputations (TFA) experiencing severe socket discomfort. The first patient receiving a bone-anchored prosthesis underwent the surgery in 1990 in the Sahlgrenska University Hospital (Sweden). To date, there are two commercially available implants: OPRA (Integrum, Sweden) and ILP (Orthodynamics, Germany). The key to success to this technique is a firm bone-implant bonding, depending on increasing mechanical stress applied daily during load bearing exercises (LBE). The loading data could be analysed through different biomechanical variables. The intra-tester reliability of these exercises will be presented here. Moreover the effect of increase of loading, axes of application of the load and body weight as well as the difference between force and moment variables will be discussed.