Selective combination of visual and thermal imaging for resilient localization in adverse conditions : day and night, smoke and fire

Long-term autonomy in robotics requires perception systems that are resilient to unusual but realistic conditions that will eventually occur during extended missions. For example, unmanned ground vehicles (UGVs) need to be capable of operating safely in adverse and low-visibility conditions, such as at night or in the presence of smoke. The key to a resilient UGV perception system lies in the use of multiple sensor modalities, e.g., operating at different frequencies of the electromagnetic spectrum, to compensate for the limitations of a single sensor type. In this paper, visual and infrared imaging are combined in a Visual-SLAM algorithm to achieve localization. We propose to evaluate the quality of data provided by each sensor modality prior to data combination. This evaluation is used to discard low-quality data, i.e., data most likely to induce large localization errors. In this way, perceptual failures are anticipated and mitigated. An extensive experimental evaluation is conducted on data sets collected with a UGV in a range of environments and adverse conditions, including the presence of smoke (obstructing the visual camera), fire, extreme heat (saturating the infrared camera), low-light conditions (dusk), and at night with sudden variations of artificial light. A total of 240 trajectory estimates are obtained using five different variations of data sources and data combination strategies in the localization method. In particular, the proposed approach for selective data combination is compared to methods using a single sensor type or combining both modalities without preselection. We show that the proposed framework allows for camera-based localization resilient to a large range of low-visibility conditions.

Error modeling and calibration of exteroceptive sensors for accurate mapping applications

Reliable robotic perception and planning are critical to performing autonomous actions in uncertain, unstructured environments. In field robotic systems, automation is achieved by interpreting exteroceptive sensor information to infer something about the world. This is then mapped to provide a consistent spatial context, so that actions can be planned around the predicted future interaction of the robot and the world. The whole system is as reliable as the weakest link in this chain. In this paper, the term mapping is used broadly to describe the transformation of range-based exteroceptive sensor data (such as LIDAR or stereo vision) to a fixed navigation frame, so that it can be used to form an internal representation of the environment. The coordinate transformation from the sensor frame to the navigation frame is analyzed to produce a spatial error model that captures the dominant geometric and temporal sources of mapping error. This allows the mapping accuracy to be calculated at run time. A generic extrinsic calibration method for exteroceptive range-based sensors is then presented to determine the sensor location and orientation. This allows systematic errors in individual sensors to be minimized, and when multiple sensors are used, it minimizes the systematic contradiction between them to enable reliable multisensor data fusion. The mathematical derivations at the core of this model are not particularly novel or complicated, but the rigorous analysis and application to field robotics seems to be largely absent from the literature to date. The techniques in this paper are simple to implement, and they offer a significant improvement to the accuracy, precision, and integrity of mapped information. Consequently, they should be employed whenever maps are formed from range-based exteroceptive sensor data. © 2009 Wiley Periodicals, Inc.

Bonding and bridging : transition to school and social capital formation among a community of Indigenous Australian children

This study reports on an intervention program designed to facilitate transition to school of a whole community of Indigenous Australian children who had previously not been attending. The children were from families displaced from their traditional lands and experienced on-going social marginalisation and transience. A social capital framework was employed to track change in the children’s social inclusion and family-school engagement for two years, from school entry. Sociometric measurement and interview techniques were applied to assess the children’s social connectedness and peer relationship quality. Using these data, analyses examined whether bonding within the group supported or inhibited formation of new social relationships. Although transience disrupted attendance, there was a group trend towards increased social inclusion with some evidence that group bonds supported bridging to new social relationships. Change in family-school engagement was tracked using multi-informant interviews. Limited engagement between school and families presented an on-going challenge to sustained educational engagement.

Autonomous multisensor calibration and closed-loop fusion for SLAM

The vast majority of current robot mapping and navigation systems require specific well-characterized sensors that may require human-supervised calibration and are applicable only in one type of environment. Furthermore, if a sensor degrades in performance, either through damage to itself or changes in environmental conditions, the effect on the mapping system is usually catastrophic. In contrast, the natural world presents robust, reasonably well-characterized solutions to these problems. Using simple movement behaviors and neural learning mechanisms, rats calibrate their sensors for mapping and navigation in an incredibly diverse range of environments and then go on to adapt to sensor damage and changes in the environment over the course of their lifetimes. In this paper, we introduce similar movement-based autonomous calibration techniques that calibrate place recognition and self-motion processes as well as methods for online multisensor weighting and fusion. We present calibration and mapping results from multiple robot platforms and multisensory configurations in an office building, university campus, and forest. With moderate assumptions and almost no prior knowledge of the robot, sensor suite, or environment, the methods enable the bio-inspired RatSLAM system to generate topologically correct maps in the majority of experiments.

Crucial roles for olfactory ensheathing cells and olfactory mucosal cells in the repair of damaged neural tracts

Olfactory ensheathing cells, the glial cells of the olfactory nervous system, exhibit unique growth-promoting and migratory properties that make them interesting candidates for cell therapies targeting neuronal injuries such as spinal cord injury. Transplantation of olfactory cells is feasible and safe in humans; however, functional outcomes are highly variable with some studies showing dramatic improvements and some no improvements at all. We propose that the reason for this is that the identity and purity of the cells is different in each individual study. We have shown that olfactory ensheathing cells are not a uniform cell population and that individual subpopulations of OECs are present in different regions of the olfactory nervous system, with strikingly different behaviors. Furthermore, the presence of fibroblasts and other cell types in the transplant can dramatically alter the behavior of the transplanted glial cells. Thus, a thorough characterization of the differences between olfactory ensheathing cell subpopulations and how the behavior of these cells is affected by the presence of other cell types is highly warranted.

Heparan sulfate proteoglycans and human breast cancer epithelial cell tumorigenicity

Heparan sulfate proteoglycans (HSPGs) are key components of the extracellular matrix that mediate cell proliferation, invasion, and cellular signaling. The biological functions of HSPGs are linked to their co-stimulatory effects on extracellular ligands (e.g., WNTs) and the resulting activation of transcription factors that control mammalian development but also associated with tumorigenesis. We examined the expression profile of HSPG core protein syndecans (SDC1–4) and glypicans (GPC1–6) along with the enzymes that initiate or modify their glycosaminoglycan chains in human breast cancer (HBC) epithelial cells. Gene expression in relation to cell proliferation was examined in the HBC cell lines MCF-7 and MDA-MB-231 following treatment with the HS agonist heparin. Heparin increased gene expression of chain initiation and modification enzymes including EXT1 and NDST1, as well as core proteins SDC2 and GPC6. With HS/Wnt interactions established, we next investigated WNT pathway components and observed that increased proliferation of the more invasive MDA-MB-231 cells is associated with activation of the Wnt signaling pathway. Specifically, there was substantial upregulation (>5-fold) of AXIN1, WNT4A, and MYC in MDA-MB-231 but not in MCF-7 cells. The changes in gene expression observed for HSPG core proteins and related enzymes along with the associated Wnt signaling components suggest coordinated interactions. The influence of HSPGs on cellular proliferation and invasive potential of breast cancer epithelial cells are cell and niche specific. Further studies on the interactions between HSPGs and WNT ligands may yield clinically relevant molecular targets, as well as new biomarkers for characterization of breast cancer progression.

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.

Mechanism‐based selection of a potent kallikrein‐related peptidase 7 inhibitor from a versatile library based on the sunflower trypsin inhibitor SFTI‐1

Potent and specific enzyme inhibition is a key goal in the development of therapeutic inhibitors targeting proteolytic activity. The backbone-cyclized peptide, Sunflower Trypsin Inhibitor (SFTI-1) affords a scaffold that can be engineered to achieve both these aims. SFTI-1's mechanism of inhibition is unusual in that it shows fast-on/slow-off kinetics driven by cleavage and religation of a scissile bond. This phenomenon was used to select a nanomolar inhibitor of kallikrein-related peptidase 7 (KLK7) from a versatile library of SFTI variants with diversity tailored to exploit distinctive surfaces present in the active site of serine proteases. Inhibitor selection was achieved through the use of size exclusion chromatography to separate protease/inhibitor complexes from unbound inhibitors followed by inhibitor identification according to molecular mass ascertained by mass spectrometry. This approach identified a single dominant inhibitor species with molecular weight of 1562.4 Da, which is consistent with the SFTI variant SFTI-WCTF. Once synthesized individually this inhibitor showed an IC50 of 173.9 ± 7.6 nM against chromogenic substrates and could block protein proteolysis. Molecular modeling analysis suggested that selection of SFTI-WCTF was driven by specific aromatic interactions and stabilized by an enhanced internal hydrogen bonding network. This approach provides a robust and rapid route to inhibitor selection and design.

Evaluation of BMP-2 gene-activated muscle grafts for cranial defect repair

Large, osseous, segmental defects heal poorly. Muscle has a propensity to form bone when exposed to an osteogenic stimulus such as that provided by transfer and expression of cDNA encoding bone morphogenetic protein-2 (BMP-2). The present study evaluated the ability of genetically modified, autologous muscle to heal large cranial defects in rats. Autologous grafts (8 mm � 2 mm) were punched from the biceps femoris muscle and transduced intraoperatively with recombinant adenovirus vector containing human BMP-2 or green fluorescent protein cDNA. While the muscle biopsies were incubating with the vector, a central parietal 8 mm defect was surgically created in the calvarium of the same animal. The gene-activated muscle graft was then implanted into the cranial defect. After 8 weeks, crania were examined radiographically, histologically, and by micro-computed tomography and dual energy X-ray absorptiometry. Although none of the defects were completely healed in this time, muscle grafts expressing BMP-2 deposited more than twice as much new bone as controls. Histology confirmed the anatomical integrity of the newly formed bone, which was comparable in thickness and mineral density to the original cranial bone. This study confirms the in vivo osteogenic properties of genetically modified muscle and suggests novel strategies for healing bone. � 2011 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 30:1095–1102, 2012

Management based on exhaled nitric oxidelevels adjusted for atopy reduces asthma exacerbations in children : A dual centre randomised controlled trial

While several randomised control trials (RCTs) have evaluated the use of fractional exhaled nitric oxide (FeNO) to improve asthma outcomes, none used FeNO cut-offs adjusted for atopy, a determinant of FeNO levels. In a dual centre RCT, we assessed whether a treatment strategy based on FeNO levels, adjusted for atopy, reduces asthma exacerbations compared with the symptoms-based management (controls). Children with asthma from hospital clinics of two hospitals were randomly allocated to receive an a-priori determined treatment hierarchy based on symptoms or FeNO levels. There was a 2-week run-in period and they were then reviewed ten times over 12-months. The primary outcome was the number of children with exacerbations over 12-months. Sixty-three children were randomised (FeNO=31, controls=32); 55 (86%) completed the study. Although we did achieve our planned sample size, significantly fewer children in the FeNO group (6 of 27) had an asthma exacerbation compared to controls (15 of 28), p=0.021; number to treat for benefit=4 (95%CI 3-24). There was no difference between groups for any secondary outcomes (quality of life, symptoms, FEV1). The final daily inhaled corticosteroids (ICS) dose was significantly (p=0.037) higher in the FeNO group (median 400µg, IQR 250-600) compared to the controls (200, IQR100-400). Taking atopy into account when using FeNO to tailor asthma medications is likely beneficial in reducing the number of children with severe exacerbations at the expense of increased ICS use. However, the strategy is unlikely beneficial for improving asthma control. A larger study is required to confirm or refute our findings.

Task-relationship-self : a framework for understanding service encounter behaviors

Research conducted over past decades has investigated selected service encounter behaviors from either a customer or service provider perspective. However, a comprehensive, dual-perspective framework is lacking. Such a framework is needed to organize knowledge of these behaviors, and thereby provide structure, clarity, and parsimony to the field. This paper describes a three-tier framework of service encounter behavior that was developed by applying grounded theory principles to interviews with customers, service employees, and other stakeholders. These informants described many ways in which they behave when executing service exchanges, dealing with service difficulties, and managing themselves in the process. Using an iterative inductive approach, a conceptual framework was developed in which specific (Tier 1) behaviors were placed within broader (Tier 2) categories, and these lower classification levels were, in turn, interpreted within a conceptual space defined by the (Tier 3) dimensions of task, relationship, and self. This framework was then elaborated and refined by reference to the psychology and marketing literature, a set of 157 audio-recorded service interactions, and an expert panel study. The paper includes comparisons between the framework and those previously proposed, propositions regarding service encounter processes and outcomes, and implications for future research and practice.

Vulnerability to loneliness in people with intellectual disability: an explanatory model

Research with typically developing groups has identified loneliness as a significant predictor of a range of physical and mental health problems. This paper reviews research about loneliness in children and adults with intellectual disability. Although a considerable body of evidence has highlighted the difficulties individuals with intellectual disability have with friendships, there is a relative scarcity of research focused explicitly on loneliness. The available evidence suggests that up to half of those with intellectual disability are chronically lonely, compared with around 15-30% of people in the general population. The cognitive, physical and mental health problems already associated with intellectual disability are likely to be compounded by experiences of chronic loneliness. We argue that people with intellectual disability are highly vulnerable to loneliness and present a theoretical model of vulnerability that comprises three reciprocally influencing domains: social attitudes and expectations; opportunities and experiences; and skill deficits associated with intellectual disability. We propose that societal views which have traditionally devalued and stigmatised those with intellectual disability limit their opportunities for experiencing social and emotional connectedness with others. Individual skill deficits in areas such as communication, self-regulation and social understanding, as well as functional difficulties associated with intellectual disability, also potentially influence the opportunities and experiences of people with intellectual disability, both directly and via multiple layers of the social context. In turn, limited opportunities will entrench particular skill deficits and reinforce negative attitudes towards intellectual disability. Future research about loneliness and intellectual disability needs to address the difficulties of measuring emotional isolation in this population, as well as the possibility that people with intellectual disability may understand, experience and interpret loneliness somewhat differently from others. The model proposed in this paper provides a starting point for developing a more sophisticated understanding of the experience of loneliness for individuals with intellectual disability.

Advanced mass spectrometry-based multi-omics technologies for exploring the pathogenesis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the primary hepatic malignancies and is the third most common cause of cancer related death worldwide. Although a wealth of knowledge has been gained concerning the initiation and progression of HCC over the last half century, efforts to improve our understanding of its pathogenesis at a molecular level are still greatly needed, to enable clinicians to enhance the standards of the current diagnosis and treatment of HCC. In the post-genome era, advanced mass spectrometry driven multi-omics technologies (e.g., profiling of DNA damage adducts, RNA modification profiling, proteomics, and metabolomics) stand at the interface between chemistry and biology, and have yielded valuable outcomes from the study of a diversity of complicated diseases. Particularly, these technologies are being broadly used to dissect various biological aspects of HCC with the purpose of biomarker discovery, interrogating pathogenesis as well as for therapeutic discovery. This proof of knowledge-based critical review aims at exploring the selected applications of those defined omics technologies in the HCC niche with an emphasis on translational applications driven by advanced mass spectrometry, toward the specific clinical use for HCC patients. This approach will enable the biomedical community, through both basic research and the clinical sciences, to enhance the applicability of mass spectrometry-based omics technologies in dissecting the pathogenesis of HCC and could lead to novel therapeutic discoveries for HCC.

Emotional climate and high quality learning experiences in science teacher education

The role of emotion during learning encounters in science teacher education is under-researched and under-theorized. In this case study we explore the emotional climates, that is, the collective states of emotional arousal, of a preservice secondary science education class to illuminate practice for producing and reproducing high quality learning experiences for preservice science teachers. Theories related to the sociology of emotions informed our analyses from data sources such as preservice teachers’ perceptions of the emotional climate of their class, emotional facial expressions, classroom conversations, and cogenerative dialogue. The major outcome from our analyses was that even though preservice teachers reported high positive emotional climate during the professor’s science demonstrations, they also valued the professor’s in the moment reflections on her teaching that were associated with low emotional climate ratings. We co-relate emotional climate data and preservice teachers’ comments during cogenerative dialogue to expand our understanding of high quality experiences and emotional climate in science teacher education. Our study also contributes refinements to research perspectives on emotional climate.

Plasma-controlled nanocrystallinity and phase composition of TiO2 : a smart way to enhance biomimetic response

This contribution sheds light on the role of crystal size and phase composition in inducing biomimetic apatite growth on the surface of nanostructured titania films synthesized by reactive magnetron sputtering of Ti targets in Ar+O2 plasmas. Unlike most existing techniques, this method enables one to deposit highly crystalline titania films with a wide range of phase composition and nanocrystal size, without any substrate heating or postannealing. Moreover, by using this dry plasma-based method one can avoid surface hydroxylation at the deposition stage, almost inevitable in wet chemical processes. Results of this work show that high phase purity and optimum crystal size appear to be the essential requirement for efficient apatite formation on magnetron plasma-fabricated bioactive titania coatings. © 2006 Wiley Periodicals, Inc.