Adaptive subcarrier allocation in multiuser OFDM system using forced cost based decisions

Subcarrier allocation scheme for Orthogonal Frequency Division Multiplexing(OFDM) based multiuser system is proposed. Most previous algorithms use greedy approach as a subcarrier allocation scheme until a conflict occurs or as an initial first round allocation with improvement steps carried out in next rounds. Our algorithm uses information obtained by the forced costs of a system that incur by a current allocation to make assignment decisions. This algorithm does not rely on greedy approach and therefore can also be considered as a substitute for first layer Greedy algorithms. Simulation results show that for two user case this algorithm gives better or equal allocation 80-90 percent of the time when compared with the greedy allocation.

Resource allocation in multiuser cooperative OFDM system using forced cost based decisions

A sub optimal resource allocation algorithm for Orthogonal Frequency Division Multiplexing (OFDM) based cooperative scheme is proposed. The system consists of multiple relays. Subcarrier space is divided into blocks and relays participating in cooperation are allocated specific blocks to be used with a user. To ensure unique subcarrier assignment system is constrained such that same block cannot be used by more than one user. Users are given fair block assignments while no restriction for maximum number of blocks a relay can employ is given. Forced cost based decisions [1] are used for block allocation. Simulation results show that this scheme outperforms a non cooperating scheme with sequential allocation with respect to power usage.

Linear adaptive channel equalization for multiuser MIMO-OFDM systems

Linear adaptive channel equalization using the least mean square (LMS) algorithm and the recursive least-squares(RLS) algorithm for an innovative multi-user (MU) MIMOOFDM wireless broadband communications system is proposed. The proposed equalization method adaptively compensates the channel impairments caused by frequency selectivity in the propagation environment. Simulations for the proposed adaptive equalizer are conducted using a training sequence method to determine optimal performance through a comparative analysis. Results show an improvement of 0.15 in BER (at a SNR of 16 dB) when using Adaptive Equalization and RLS algorithm compared to the case in which no equalization is employed. In general, adaptive equalization using LMS and RLS algorithms showed to be significantly beneficial for MU-MIMO-OFDM systems.

Multidisciplinary design and flight testing of a remote gas/particle airborne sensor system

The main objective of this paper is to describe the development of a remote sensing airborne air sampling system for Unmanned Aerial Systems (UAS) and provide the capability for the detection of particle and gas concentrations in real time over remote locations. The design of the air sampling methodology started by defining system architecture, and then by selecting and integrating each subsystem. A multifunctional air sampling instrument, with capability for simultaneous measurement of particle and gas concentrations was modified and integrated with ARCAA’s Flamingo UAS platform and communications protocols. As result of the integration process, a system capable of both real time geo-location monitoring and indexed-link sampling was obtained. Wind tunnel tests were conducted in order to evaluate the performance of the air sampling instrument in controlled nonstationary conditions at the typical operational velocities of the UAS platform. Once the remote fully operative air sampling system was obtained, the problem of mission design was analyzed through the simulation of different scenarios. Furthermore, flight tests of the complete air sampling system were then conducted to check the dynamic characteristics of the UAS with the air sampling system and to prove its capability to perform an air sampling mission following a specific flight path.

Mutations in cardiac T-Box Factor gene TBX20 are associated with diverse cardiac pathologies, including defects of septation and valvulogenesis and cardiomyopathy

The T-box family transcription factor gene TBX20 acts in a conserved regulatory network, guiding heart formation and patterning in diverse species. Mouse Tbx20 is expressed in cardiac progenitor cells, differentiating cardiomyocytes, and developing valvular tissue, and its deletion or RNA interference-mediated knockdown is catastrophic for heart development. TBX20 interacts physically, functionally, and genetically with other cardiac transcription factors, including NKX2-5, GATA4, and TBX5, mutations of which cause congenital heart disease (CHD). Here, we report nonsense (Q195X) and missense (I152M) germline mutations within the T-box DNA-binding domain of human TBX20 that were associated with a family history of CHD and a complex spectrum of developmental anomalies, including defects in septation, chamber growth, and valvulogenesis. Biophysical characterization of wild-type and mutant proteins indicated how the missense mutation disrupts the structure and function of the TBX20 T-box. Dilated cardiomyopathy was a feature of the TBX20 mutant phenotype in humans and mice, suggesting that mutations in developmental transcription factors can provide a sensitized template for adult-onset heart disease. Our findings are the first to link TBX20 mutations to human pathology. They provide insights into how mutation of different genes in an interactive regulatory circuit lead to diverse clinical phenotypes, with implications for diagnosis, genetic screening, and patient follow-up.

Behavioral evaluation of eight rat lines selected for high and low anxiety-related responses

Anxiety traits can be stable and permanent characteristics of an individual across time that is less susceptible of influences by a particular situation. One way to study trait anxiety in an experimental context is through the use of rat lines, selected according to contrasting phenotypes of fear and anxiety. It is not clear whether the behavioral differences between two contrasting rat lines in one given anxiety test are also present in others paradigms of state anxiety. Here, we examine the extent to which multiple anxiety traits generalize across selected animal lines originally selected for a single anxiety trait. We review the behavioral results available in the literature of eight rat genetic models of trait anxiety - namely Maudsley Reactive and Non-reactive rats, Floripa H and L rats, Tsukuba High and Low Emotional rats, High and Low Anxiety-related rats, High and Low Ultrasonic Vocalization rats, Roman High and Low Avoidance rats, Syracuse High and Low Avoidance rats, and Carioca High and Low Conditioned Freezing rats - across 11 behavioral paradigms of innate anxiety or aversive learning frequently used in the experimental setting. We observed both convergence and divergence of behavioral responses in these selected lines across the 11 paradigms. We find that predisposition for specific anxiety traits will usually be generalized to other anxiety provoking stimuli. However this generalization is not observed across all genetic models indicating some unique trait and state interactions. Genetic models of enhanced-anxiety related responses are beginning to help define how anxiety can manifest differently depending on the underlying traits and the current environmentally induced state.

Effective punishment experiences : the need for a more comprehensive approach to conceptualising behavioural punishers and reinforcers in a road safety context

Determining what consequences are likely to serve as effective punishment for any given behaviour is a complex task. This chapter focuses specifically on illegal road user behaviours and the mechanisms used to punish and deter them. Traffic law enforcement has traditionally used the threat and/or receipt of legal sanctions and penalties to deter illegal and risky behaviours. This process represents the use of positive punishment, one of the key behaviour modification mechanisms. Behaviour modification principles describe four types of reinforcers: positive and negative punishments and positive and negative reinforcements. The terms ‘positive’ and ‘negative’ are not used in an evaluative sense here. Rather, they represent the presence (positive) or absence (negative) of stimuli to promote behaviour change. Punishments aim to inhibit behaviour and reinforcements aim to encourage it. This chapter describes a variety of punishments and reinforcements that have been and could be used to modify illegal road user behaviours. In doing so, it draws on several theoretical perspectives that have defined behavioural reinforcement and punishment in different ways. Historically, the main theoretical approach used to deter risky road use has been classical deterrence theory which has focussed on the perceived certainty, severity and swiftness of penalties. Stafford and Warr (1993) extended the traditional deterrence principles to include the positive reinforcement concept of punishment avoidance. Evidence of the association between punishment avoidance experiences and behaviour has been established for a number of risky road user behaviours including drink driving, unlicensed driving, and speeding. We chose a novel way of assessing punishment avoidance by specifying two sub-constructs (detection evasion and punishment evasion). Another theorist, Akers, described the idea of competing reinforcers, termed differential reinforcement, within social learning theory (1977). Differential reinforcement describes a balance of reinforcements and punishments as influential on behaviour. This chapter describes comprehensive way of conceptualising a broad range of reinforcement and punishment concepts, consistent with Akers’ differential reinforcement concept, within a behaviour modification framework that incorporates deterrence principles. The efficacy of three theoretical perspectives to explain self-reported speeding among a sample of 833 Australian car drivers was examined. Results demonstrated that a broad range of variables predicted speeding including personal experiences of evading detection and punishment for speeding, intrinsic sensations, practical benefits expected from speeding, and an absence of punishing effects from being caught. Not surprisingly, being younger was also significantly related to more frequent speeding, although in a regression analysis, gender did not retain a significant influence once all punishment and reinforcement variables were entered. The implications for speed management, as well as road user behaviour modification more generally, are discussed in light of these findings. Overall, the findings reported in this chapter suggest that a more comprehensive approach is required to manage the behaviour of road users which does not rely solely on traditional legal penalties and sanctions.

Punishment Avoidance and Intentional Risky Driving Behaviour : What are the Implications for ‘Getting Away with it’?

Every motorised jurisdiction mandates legal driving behaviour which facilitates driver mobility and road user safety through explicit road rules that are enforced by regulatory authorities such as the Police. In road safety, traffic law enforcement has been very successfully applied to modify road user behaviour, and increasingly technology is fundamental in detecting illegal road user behaviour. Furthermore, there is also sound evidence that highly visible and/or intensive enforcement programs achieve long-term deterrent effects. To illustrate, in Australia random breath testing has considerably reduced the incidence and prevalence of driving whilst under the influence of alcohol. There is, however, evidence that many road rules continue to be broken, including speeding and using a mobile phone whilst driving, and there are many instances where drivers are not detected or sufficiently sanctioned for these transgressions. Furthermore, there is a growing body of evidence suggesting that experiences of punishment avoidance – that is, successful attempts at avoiding punishment such as drivers talking themselves out of a ticket, or changing driving routes to evade detection –are associated with and predictive of the extent of illegal driving behaviour and future illegal driving intentions. Therefore there is a need to better understand the phenomenon of punishment avoidance to enhance our traffic law enforcement procedures and therefore safety of all road users. This chapter begins with a review of the young driver road safety problem, followed by an examination of contemporary deterrence theory to enhance our understanding of both the experiences and implications of punishment avoidance in the road environment. It is noteworthy that in situations where detection and punishment remain relatively rare, such as on extensive road networks, the research evidence suggests that experiences of punishment avoidance may have a stronger influence upon risky driving behaviour than experiences of punishment. Finally, data from a case study examining the risky behaviour of young drivers will be presented, and the implications for ‘getting away with it’ will be discussed.

Applying the ecological model of behavior change to a physical activity trial in retirement communities : description of the study protocol

Objectives To describe the intervention protocol for the first multilevel ecological intervention for physical activity in retirement communities that addresses individual, interpersonal and community influences on behavior change. Design A cluster randomized controlled trial design was employed with two study arms: a physical activity intervention and an attention control successful aging condition. Setting Sixteen continuing care retirement communities in San Diego County. Participants Three hundred twenty older adults, aged 65 years and older, are being recruited to participate in the trial. In addition, peer leaders are being recruited to lead some study activities, especially to sustain the intervention after study activities ceased. Intervention Participants in the physical activity trial receive individual, interpersonal and community intervention components. The individual level components include pedometers, goal setting and individual phone counseling. The interpersonal level components include group education sessions and peer-led activities. The community level components include resource audits and enumeration, tailored walking maps, and community improvement projects. The successful aging group receives individual and group attention about successful aging topics. Measurements The main outcome is light to moderate physical activity, measured objectively by accelerometry. Other objective outcomes included physical functioning, blood pressure, physical fitness, and cognitive functioning. Self report measures include depressive symptoms and health related quality of life. Results The intervention is being delivered successfully in the communities and compliance rates are high. Conclusion Ecological Models call for interventions that address multiple levels of the model. Previous studies have not included components at each level and retirement communities provide a model environment to demonstrate how to implement such an intervention.

Laser-radar data fusion with Gaussian Process Implicit Surfaces

This work considers the problem of building high-fidelity 3D representations of the environment from sensor data acquired by mobile robots. Multi-sensor data fusion allows for more complete and accurate representations, and for more reliable perception, especially when different sensing modalities are used. In this paper, we propose a thorough experimental analysis of the performance of 3D surface reconstruction from laser and mm-wave radar data using Gaussian Process Implicit Surfaces (GPIS), in a realistic field robotics scenario. We first analyse the performance of GPIS using raw laser data alone and raw radar data alone, respectively, with different choices of covariance matrices and different resolutions of the input data. We then evaluate and compare the performance of two different GPIS fusion approaches. The first, state-of-the-art approach directly fuses raw data from laser and radar. The alternative approach proposed in this paper first computes an initial estimate of the surface from each single source of data, and then fuses these two estimates. We show that this method outperforms the state of the art, especially in situations where the sensors react differently to the targets they perceive.

Laser-to-radar sensing redundancy for resilient perception in adverse environmental conditions

This paper presents an approach to promote the integrity of perception systems for outdoor unmanned ground vehicles (UGV) operating in challenging environmental conditions (presence of dust or smoke). The proposed technique automatically evaluates the consistency of the data provided by two sensing modalities: a 2D laser range finder and a millimetre-wave radar, allowing for perceptual failure mitigation. Experimental results, obtained with a UGV operating in rural environments, and an error analysis validate the approach.

Disclose

Table of Contents “your darkness also/rich and beyond fear”: Community Performance, Somatic Poetics and the Vessels of Self and Other - Petra Kuppers. "So what will you do on the plinth?”: A Personal Experience of Disclosure during Antony Gormley’s "One & Other" Project - Jill Francesca Dowse. Food Confessions: Disclosing the Self through the Performance of Food - Jenny Lawson Participation Cartography: The Presentation of Self in Spatio-Temporal Terms - Luis Carlos Sotelo-Castro Disclosure in Biographically-Based Fiction: The Challenges of Writing Narratives Based on True Life Stories - Donna Lee Brien. Closure through Mock-Disclosure in Bret Easton Ellis’s Lunar Park - Jennifer Anne Phillips. Disclosing the Ethnographic Self - Christine Lohmeier Celebrity Twitter: Strategies of Intrusion and Disclosure in the Age of Technoculture - Nick Muntean, Anne Helen Petersen. “Just Emotional People”? Emo Culture and the Anxieties of Disclosure - Michelle Phillipov.

Examining the effects of early cost drivers on contingencies

The accuracy of early cost estimates is critical to the success of construction projects. The selected tender price (clients' building cost) is usually seen in previous research as a holistic dependent variable when examining early stage estimates. Unlike other components of construction cost, the amount of contingencies is decided by clients/consultants with consideration of early project information. Cost drivers of contingencies estimates are associated with uncertainty and complexity, and include project size, schedule, ground condition, construction site access, market condition and so on. A path analysis of 133 UK school building contracts was conducted to identify impacts of nine major cost drivers on the determination of contingencies by different clients/cost estimators. This research finds that gross floor area (GFA), schedule and requirement of air conditioning have statistically significant impacts on the contingency determination. The mediating role of schedule between gross floor area and contingencies (GFA→Schedule→Contingencies) was confirmed with the Soble test. The total effects of the three variables on contingencies estimates were obtained with the consideration of this indirect effect. The squared multiple correlation (SMC) of contingencies (=0.624) indicates the identified three variables can explain 62.4% variance of contingencies, and it is comparatively satisfactory considering the heterogeneity among different estimators, unknown estimating techniques and different projects

Anti-proliferative and cytotoxic activity of pentadactylin isolated from Leptodactylus labyrinthicus on melanoma cells

Nowadays, the emergence of resistance to the current available chemotherapeutic drugs by cancer cells makes the development of new agents imperative. The skin secretion of amphibians is a natural rich source of antimicrobial peptides (AMP), and researchers have shown that some of these wide spectrum molecules are also toxic to cancer cells. The aim of this study was to verify a putative anticancer activity of the AMP pentadactylin isolated for the first time from the skin secretion of the frog Leptodactylus labyrinthicus and also to study its cytotoxic mechanism to the murine melanoma cell line B16F10. The results have shown that pentadactylin reduces the cell viability of B16F10 cells in a dose-dependent manner. It was also cytotoxic to normal human fibroblast cells; nevertheless, pentadactylin was more potent in the first case. The studies of action mechanism revealed that pentadactylin causes cell morphology alterations (e.g., round shape and shrinkage morphology), membrane disruption, DNA fragmentation, cell cycle arrest at the S phase, and alteration of mitochondrial membrane potential, suggesting that B16F10 cells die by apoptosis. The exact mechanism that causes reduction of cell viability and cytotoxicity after treatment with pentadactylin is still unknown. In conclusion, as cancer cells become resilient to death, it is worthwhile the discovery of new drugs such as pentadactylin that induces apoptosis.

Robust multiple-sensing-modality data fusion using Gaussian Process Implicit Surfaces

The ability to build high-fidelity 3D representations of the environment from sensor data is critical for autonomous robots. Multi-sensor data fusion allows for more complete and accurate representations. Furthermore, using distinct sensing modalities (i.e. sensors using a different physical process and/or operating at different electromagnetic frequencies) usually leads to more reliable perception, especially in challenging environments, as modalities may complement each other. However, they may react differently to certain materials or environmental conditions, leading to catastrophic fusion. In this paper, we propose a new method to reliably fuse data from multiple sensing modalities, including in situations where they detect different targets. We first compute distinct continuous surface representations for each sensing modality, with uncertainty, using Gaussian Process Implicit Surfaces (GPIS). Second, we perform a local consistency test between these representations, to separate consistent data (i.e. data corresponding to the detection of the same target by the sensors) from inconsistent data. The consistent data can then be fused together, using another GPIS process, and the rest of the data can be combined as appropriate. The approach is first validated using synthetic data. We then demonstrate its benefit using a mobile robot, equipped with a laser scanner and a radar, which operates in an outdoor environment in the presence of large clouds of airborne dust and smoke.