Selection and monitoring of navigation modes for an autonomous rover

Considering the wide spectrum of situations that it may encounter, a robot navigating autonomously in outdoor environments needs to be endowed with several operating modes, for robustness and efficiency reasons. Indeed, the terrain it has to traverse may be composed of flat or rough areas, low cohesive soils such as sand dunes, concrete road etc... Traversing these various kinds of environment calls for different navigation and/or locomotion functionalities, especially if the robot is endowed with different locomotion abilities, such as the robots WorkPartner, Hylos [4], Nomad or the Marsokhod rovers.

Selection and monitoring of navigation modes for an autonomous rover

Considering the wide spectrum of situations that it may encounter, a robot navigating autonomously in outdoor environments needs to be endowed with several operating modes, for robustness and efficiency reasons. Indeed, the terrain it has to traverse may be composed of flat or rough areas, low cohesive soils such as sand dunes, concrete road etc. . .Traversing these various kinds of environment calls for different navigation and/or locomotion functionalities, especially if the robot is endowed with different locomotion abilities, such as the robots WorkPartner, Hylos [4], Nomad or the Marsokhod rovers. Numerous rover navigation techniques have been proposed, each of them being suited to a particular environment context (e.g. path following, obstacle avoidance in more or less cluttered environments, rough terrain traverses...). However, seldom contributions in the literature tackle the problem of selecting autonomously the most suited mode [3]. Most of the existing work is indeed devoted to the passive analysis of a single navigation mode, as in [2]. Fault detection is of course essential: one can imagine that a proper monitoring of the Mars Exploration Rover Opportunity could have avoided the rover to be stuck during several weeks in a dune, by detecting non-nominal behavior of some parameters. But the ability to recover the anticipated problem by switching to a better suited navigation mode would bring higher autonomy abilities, and therefore a better overall efficiency. We propose here a probabilistic framework to achieve this, which fuses environment related and robot related information in order to actively control the rover operations.

The effect of varying diagnostic terminology within patient discharge information on expected mild traumatic brain injury outcome

This study aimed to determine if systematic variation of the diagnostic terminology embedded within written discharge information (i.e., concussion or mild traumatic brain injury, mTBI) would produce different expected symptoms and illness perceptions. We hypothesized that compared to concussion advice, mTBI advice would be associated with worse outcomes. Sixty-two volunteers with no history of brain injury or neurological disease were randomly allocated to one of two conditions in which they read a mTBI vignette followed by information that varied only by use of the embedded terms concussion (n = 28) or mTBI (n = 34). Both groups reported illness perceptions (timeline and consequences subscale of the Illness Perception Questionnaire-Revised) and expected Postconcussion Syndrome (PCS) symptoms 6 months post injury (Neurobehavioral Symptom Inventory, NSI). Statistically significant group differences due to terminology were found on selected NSI scores (i.e., total, cognitive and sensory symptom cluster scores (concussion > mTBI)), but there was no effect of terminology on illness perception. When embedded in discharge advice, diagnostic terminology affects some but not all expected outcomes. Given that such expectations are a known contributor to poor mTBI outcome, clinicians should consider the potential impact of varied terminology on their patients.

Integrin-functionalized artificial membranes as test platforms for monitoring small integrin ligand binding by surface plasmon-enhanced fluorescence spectroscopy

The design and synthesis of molecularly or supramolecularly defined interfacial architectures have seen in recent years a remarkable growth of interest and scientific research activities for various reasons. On the one hand, it is generally believed that the construction of an interactive interface between the living world of cells, tissue, or whole organisms and the (inorganic or organic) materials world of technical devices such as implants or medical parts requires proper construction and structural (and functional) control of this organism–machine interface. It is still the very beginning of generating a better understanding of what is needed to make an organism tolerate implants, to guarantee bidirectional communication between microelectronic devices and living tissue, or to simply construct interactive biocompatibility of surfaces in general. This exhaustive book lucidly describes the design, synthesis, assembly and characterization, and bio-(medical) applications of interfacial layers on solid substrates with molecularly or supramolecularly controlled architectures. Experts in the field share their contributions that have been developed in recent years.

Carbon nanotube composite sensor for structural health monitoring of bridge structures

Bridges are important infrastructures of all nations and are required for transportation of goods as well as human. A catastrophic failure can result in loss of lives and enormous financial hardship to the nation. Although various kinds of sensors are now available to monitor the health of the structures due to corrosion, they do not provide permanent and long term measurements. This paper investigates the fabrication of Carbon Nanotube (CNT) based composite sensors for corrosion detection of structures. Multi-wall CNT (MWCNT)/Nafion composite sensors were fabricated to evaluate their electrical properties for corrosion detection. The test specimens were subjected to real life corrosion experimental tests and the results confirm that the electrical resistance of the sensor electrode was dramatically changed due to corrosion.

Acoustic emission condition monitoring : an application for wind turbine fault detection

Low speed rotating machines which are the most critical components in drive train of wind turbines are often menaced by several technical and environmental defects. These factors contribute to mount the economic requirement for Health Monitoring and Condition Monitoring of the systems. When a defect is happened in such system result in reduced energy loss rates from related process and due to it Condition Monitoring techniques that detecting energy loss are very difficult if not possible to use. However, in the case of Acoustic Emission (AE) technique this issue is partly overcome and is well suited for detecting very small energy release rates. Acoustic Emission (AE) as a technique is more than 50 years old and in this new technology the sounds associated with the failure of materials were detected. Acoustic wave is a non-stationary signal which can discover elastic stress waves in a failure component, capable of online monitoring, and is very sensitive to the fault diagnosis. In this paper the history and background of discovering and developing AE is discussed, different ages of developing AE which include Age of Enlightenment (1950-1967), Golden Age of AE (1967-1980), Period of Transition (1980-Present). In the next section the application of AE condition monitoring in machinery process and various systems that applied AE technique in their health monitoring is discussed. In the end an experimental result is proposed by QUT test rig which an outer race bearing fault was simulated to depict the sensitivity of AE for detecting incipient faults in low speed high frequency machine.

Experimental evaluation of an autonomous surface vehicle for water quality and greenhouse gas emission monitoring

This paper describes the experimental evaluation of a novel Autonomous Surface Vehicle capable of navigating complex inland water reservoirs and measuring a range of water quality properties and greenhouse gas emissions. The 16 ft long solar powered catamaran is capable of collecting water column profiles whilst in motion. It is also directly integrated with a reservoir scale floating sensor network to allow remote mission uploads, data download and adaptive sampling strategies. This paper describes the onboard vehicle navigation and control algorithms as well as obstacle avoidance strategies. Experimental results are shown demonstrating its ability to maintain track and avoid obstacles on a variety of large-scale missions and under differing weather conditions, as well as its ability to continuously collect various water quality parameters complimenting traditional manual monitoring campaigns.

An autonomous surface vehicle for water quality monitoring

This paper describes a novel Autonomous Surface Vehicle capable of navigating throughout complex inland water storages and measuring a range of water quality properties and greenhouse gas emissions. The 16 ft long solar powered catamaran can collect this information throughout the water column whilst the vehicle is moving. A unique feature of this ASV is its integration into a storage scale floating sensor network to allow remote mission uploads, data download and adaptive sampling strategies. This paper provides an overview of the vehicle design and operation including control, laser-based obstacle avoidance, and vision-based inspection capabilities. Experimental results are shown illustrating its ability to continuously collect key water quality parameters and compliment intensive manual monitoring campaigns.

Mixed venous oxygen saturation monitoring revisited : thoughts for critical care nursing practice

Background Less invasive methods of determining cardiac output are now readily available. Using indicator dilution technique, for example has made it easier to continuously measure cardiac output because it uses the existing intra-arterial line. Therefore gone is the need for a pulmonary artery floatation catheter and with it the ability to measure left atrial and left ventricular work indices as well the ability to monitor and measure a mixed venous saturation (SvO2). Purpose The aim of this paper is to put forward the notion that SvO2 provides valuable information about oxygen consumption and venous reserve; important measures in the critically ill to ensure oxygen supply meets cellular demand. In an attempt to portray this, a simplified example of the septic patient is offered to highlight the changing pathophysiological sequelae of the inflammatory process and its importance for monitoring SvO2. Relevance to clinical practice SvO2 monitoring, it could be argued, provides the gold standard for assessing arterial and venous oxygen indices in the critically ill. For the bedside ICU nurse the plethora of information inherent in SvO2 monitoring could provide them with important data that will assist in averting potential problems with oxygen delivery and consumption. However, it has been suggested that central venous saturation (ScvO2) might be an attractive alternative to SvO2 because of its less invasiveness and ease of obtaining a sample for analysis. There are problems with this approach and these are to do with where the catheter tip is sited and the nature of the venous admixture at this site. Studies have shown that ScvO2 is less accurate than SvO2 and should not be used as a sole guiding variable for decision-making. These studies have demonstrated that there is an unacceptably wide range in variance between ScvO2 and SvO2 and this is dependent on the presenting disease, in some cases SvO2 will be significantly lower than ScvO2. Conclusion Whilst newer technologies have been developed to continuously measure cardiac output, SvO2 monitoring is still an important adjunct to clinical decision-making in the ICU. Given the information that it provides, seeking alternatives such as ScvO2 or blood samples obtained from femorally placed central venous lines, can unnecessarily lead to inappropriate treatment being given or withheld. Instead when using ScvO2, trending of this variable should provide clinical determinates that are useable for the bedside ICU nurse, remembering that in most conditions SvO2 will be approximately 16% lower.

Is age a factor in the success or failure of remote monitoring in heart failure? Telemonitoring and structured telephone support in elderly heart failure patients

Background There are few data regarding the effectiveness of remote monitoring for older people with heart failure. We conducted a post-hoc sub-analysis of a previously published large Cochrane systematic review and meta-analysis of relevant randomized controlled trials to determine whether structured telephone support and telemonitoring were effective in this population. Methods A post hoc sub-analysis of a systematic review and meta-analysis that applied the Cochrane methodology was conducted. Meta-analyses of all-cause mortality, all-cause hospitalizations and heart failure-related hospitalizations were performed for studies where the mean or median age of participants was 70 or more years. Results The mean or median age of participants was 70 or more years in eight of the 16 (n=2,659/5,613; 47%) structured telephone support studies and four of the 11 (n=894/2,710; 33%) telemonitoring studies. Structured telephone support (RR 0.80; 95% CI=0.63-1.00) and telemonitoring (RR 0.56; 95% CI=0.41-0.76) interventions reduced mortality. Structured telephone support interventions reduced heart failure-related hospitalizations (RR 0.81; 95% CI=0.67-0.99). Conclusion Despite a systematic bias towards recruitment of individuals younger than the epidemiological average into the randomized controlled trials, older people with heart failure did benefit from structured telephone support and telemonitoring. These post-hoc sub-analysis results were similar to overall effects observed in the main meta-analysis. While further research is required to confirm these observational findings, the evidence at hand indicates that discrimination by age alone may be not be appropriate when inviting participation in a remote monitoring service for heart failure.

Managing and analysing big audio data for environmental monitoring

Environmental monitoring is becoming critical as human activity and climate change place greater pressures on biodiversity, leading to an increasing need for data to make informed decisions. Acoustic sensors can help collect data across large areas for extended periods making them attractive in environmental monitoring. However, managing and analysing large volumes of environmental acoustic data is a great challenge and is consequently hindering the effective utilization of the big dataset collected. This paper presents an overview of our current techniques for collecting, storing and analysing large volumes of acoustic data efficiently, accurately, and cost-effectively.

Investigation of brain derived neurotrophic factor (BDNF) gene variants in migraine

A number of observations have suggested that brain derived neurotrophic factor (BDNF) plays a role in migraine pathophysiology. This study investigates whether variants in the BDNF gene are associated with migraine in an Australian case-control population. Background. Brain derived neurotrophic factor (BDNF) has an important role in neural growth, development and survival in the central nervous system and is an important modulator of central and peripheral pain responses. Variants in BDNF, in particular the functional Val66Met polymorphism (rs6265), have been found to be associated with a number of psychiatric disorders, cognitive function and obesity. As BDNF has been found to be differentially expressed in a number of aspects related to migraine, we tested for association between single nucleotide polymorphisms (SNPs) in BDNF and migraine. Methods. Five SNPs in the BDNF locus (rs1519480, rs6265, rs712507, rs2049046 and rs12273363) were genotyped initially in a cohort of 277 migraine cases, including 172 diagnosed with migraine with aura (MA) and 105 with migraine without aura (MO), and 277 age- and sex-matched controls. Three of these SNPs (rs6265, rs2049046 and rs12273363) were subsequently genotyped in a second cohort of 580 migraineurs, including 473 diagnosed with MA and 105 with O, and 580 matched controls. Results. – BDNF SNPs rs1519480, rs6265, rs712507 and rs12273363 were not significantly associated with migraine. However, rs2049046 showed a significant association with migraine, and in particular, MA in the first cohort. In the second cohort, although an increase in the rs2049046 T-allele frequency was observed in migraine cases, and in both MA and MO subgroups, it was not significantly different from controls. Analysis of data combined from both cohorts for rs2049046 showed significant differences in the genotypic and allelic distributions for this marker in both migraine and the MA sub-group. Conclusion. This study confirmed previous studies that the functional BDNF SNP rs6265 (Val66Met) is not associated with migraine. However, we found that rs2049046, which resides at the 5’ end of 3 one the BDNF transcripts, may be associated with migraine, suggesting that further investigations of this SNP may be warranted.

Mapping, monitoring, and modelling of hazardous waste sites

Management of the industrial nations' hazardous waste is a current and exponentially increasing, global threatening situation. Improved environmental information must be obtained and managed concerning the current status, temporal dynamics and potential future status of these critical sites. To test the application of spatial environmental techniques to the problem of hazardous waste sites, as Superfund (CERCLA) test site was chosen in an industrial/urban valley experiencing severe TCE, PCE, and CTC ground water contamination. A paradigm is presented for investigating spatial/environmental tools available for the mapping, monitoring and modelling of the environment and its toxic contaminated plumes. This model incorporates a range of technical issues concerning the collection of data as augmented by remotely sensed tools, the format and storage of data utilizing geographic information systems, and the analysis and modelling of environment through the use of advance GIS analysis algorithms and geophysic models of hydrologic transport including statistical surface generation. This spatial based approach is evaluated against the current government/industry standards of operations. Advantages and lessons learned of the spatial approach are discussed.

Wetlands : a perspective for mapping, monitoring, and modeling

Experience gained from numerous projects conducted by the U.S. Environmental Protection Agency's (EPA) Environmental Monitoring Systems Laboratory in Las Vegas, Nevada has provided insight to functional issues of mapping, monitoring, and modeling of wetland habitats. Three case studies in poster form describe these issues pertinent to managing wetland resources as mandated under Federal laws. A multiphase project was initiated by the EPA Alaska operations office to provide detailed wetland mapping of arctic plant communities in an area under petroleum development pressure. Existing classification systems did not meet EPA needs. Therefore a Habitat Classification System (HCS) derived from aerial photography was compiled. In conjunction with this photointerpretive keys were developed. These products enable EPA personnel to map large inaccessible areas of the arctic coastal plain and evaluate the sensitivity of various wetland habitats relative to petroleum development needs.

Ghrelin and the brain-gut axis as a pharmacological target for appetite control

Appetite regulation is highly complex and involves a large number of orexigenic and anorexigenic peptide hormones. These are small, processed, secreted peptides derived from larger prepropeptide precursors. These peptides are important targets for the development of therapeutics for obesity, a global health epidemic. As a case study, we consider the ghrelin axis. The ghrelin axis is likely to be a particularly useful drug target, as it also plays a role in energy homeostasis, adipogenesis, insulin regulation and reward associated with food intake. Ghrelin is the only known circulating gut orexigenic peptide hormone. As it appears to play a role in diet-induced obesity, blocking the action of ghrelin is likely to be effective for treating and preventing obesity. The ghrelin peptide has been targeted using a number of approaches, with ghrelin mirror-image oligonucleotides (Spiegelmers) and immunotherapy showing some promise. The ghrelin receptor, the growth hormone secretagogue receptor, may also provide a useful target and a number of antagonists and inverse agonists have been developed. A particularly promising new target is the enzyme which octanoylates ghrelin, ghrelin O-acyltransferase (GOAT), and drugs that inhibit GOAT are likely to circumvent pharmacological issues associated with approaches that directly target ghrelin or its receptor.