Array of subarrays using adaptive element patterns

This paper explores the use of subarrays as array elements. Benefits of such a concept include improved gain in any direction without significantly increasing the overall size of the array and enhanced pattern control. The architecture for an array of subarrays will be discussed via a systems approach. Individual system designs are explored in further details and proof of principle is illustrated through a manufactured examples.

The adaptive metabolic response to exercise-induced weight loss influences both energy expenditure and energy intake

BACKGROUND/OBJECTIVEs A decline in resting energy expenditure (REE) beyond that predicted from changes in body composition has been noted following dietary-induced weight loss. However, it is unknown whether a compensatory downregulation in REE also accompanies exercise (EX)-induced weight loss, or whether this adaptive metabolic response influences energy intake (EI). SUBJECTS/METHODS Thirty overweight and obese women (body mass index (BMI)=30.6±3.6 kg/m2) completed 12 weeks of supervised aerobic EX. Body composition, metabolism, EI and metabolic-related hormones were measured at baseline, week 6 and post intervention. The metabolic adaptation (MA), that is, difference between predicted and measured REE was also calculated post intervention (MApost), with REE predicted using a regression equation generated in an independent sample of 66 overweight and obese women (BMI=31.0±3.9 kg/m2). RESULTS Although mean predicted and measured REE did not differ post intervention, 43% of participants experienced a greater-than-expected decline in REE (−102.9±77.5 kcal per day). MApost was associated with the change in leptin (r=0.47; P=0.04), and the change in resting fat (r=0.52; P=0.01) and carbohydrate oxidation (r=−0.44; P=0.02). Furthermore, MApost was also associated with the change in EI following EX (r=−0.44; P=0.01). CONCLUSIONS Marked variability existed in the adaptive metabolic response to EX. Importantly, those who experienced a downregulation in REE also experienced an upregulation in EI, indicating that the adaptive metabolic response to EX influences both physiological and behavioural components of energy balance.

Innate and adaptive immunity at mucosal surfaces of the female reproductive tract : stratification and integration of immune protection against the transmission of sexually transmitted infections

This review examines the multiple levels of pre-existing immunity in the upper and lower female reproductive tract. In addition, we highlight the need for further research of innate and adaptive immune protection of mucosal surfaces in the female reproductive tract. Innate mechanisms include the mucus lining, a tight epithelial barrier and the secretion of antimicrobial peptides and cytokines by epithelial and innate immune cells. Stimulation of the innate immune system also serves to bridge the adaptive arm resulting in the generation of pathogen-specific humoral and cell-mediated immunity. Less understood are the multiple components that act in a coordinated way to provide a network of ongoing protection. Innate and adaptive immunity in the human female reproductive tract are influenced by the stage of menstrual cycle and are directly regulated by the sex steroid hormones, progesterone and estradiol. Furthermore, the effect of hormones on immunity is mediated both directly on immune and epithelial cells and indirectly by stimulating growth factor secretion from stromal cells. The goal of this review is to focus on the diverse aspects of the innate and adaptive immune systems that contribute to a unique network of protection throughout the female reproductive tract.

Do the kinematics of a baulked take-off in springboard diving differ from those of a completed dive

Consistency and invariance in movements are traditionally viewed as essential features of skill acquisition and elite sports performance. This emphasis on the stabilization of action has resulted in important processes of adaptation in movement coordination during performance being overlooked in investigations of elite sport performance. Here we investigate whether differences exist between the movement kinematics displayed by five, elite springboard divers (age 17 ± 2.4 years) in the preparation phases of baulked and completed take-offs. The two-dimensional kinematic characteristics of the reverse somersault take-off phases (approach and hurdle) were recorded during normal training sessions and used for intra-individual analysis. All participants displayed observable differences in movement patterns at key events during the approach phase; however, the presence of similar global topological characteristics suggested that, overall, participants did not perform distinctly different movement patterns during completed and baulked dives. These findings provide a powerful rationale for coaches to consider assessing functional variability or adaptability of motor behaviour as a key criterion of successful performance in sports such as diving.

Real-time image classification for adaptive mission planning using an Autonomous Underwater Vehicle

Real-time image analysis and classification onboard robotic marine vehicles, such as AUVs, is a key step in the realisation of adaptive mission planning for large-scale habitat mapping in previously unexplored environments. This paper describes a novel technique to train, process, and classify images collected onboard an AUV used in relatively shallow waters with poor visibility and non-uniform lighting. The approach utilises Förstner feature detectors and Laws texture energy masks for image characterisation, and a bag of words approach for feature recognition. To improve classification performance we propose a usefulness gain to learn the importance of each histogram component for each class. Experimental results illustrate the performance of the system in characterisation of a variety of marine habitats and its ability to operate onboard an AUV's main processor suitable for real-time mission planning.

A sequential Monte Carlo framework for adaptive Bayesian model discrimination designs using mutual information

In this paper we present a unified sequential Monte Carlo (SMC) framework for performing sequential experimental design for discriminating between a set of models. The model discrimination utility that we advocate is fully Bayesian and based upon the mutual information. SMC provides a convenient way to estimate the mutual information. Our experience suggests that the approach works well on either a set of discrete or continuous models and outperforms other model discrimination approaches.

Multiple-time signature schemes against adaptive chosen message attacks

Multiple-time signatures are digital signature schemes where the signer is able to sign a predetermined number of messages. They are interesting cryptographic primitives because they allow to solve many important cryptographic problems, and at the same time offer substantial efficiency advantage over ordinary digital signature schemes like RSA. Multiple-time signature schemes have found numerous applications, in ordinary, on-line/off-line, forward-secure signatures, and multicast/stream authentication. We propose a multiple-time signature scheme with very efficient signing and verifying. Our construction is based on a combination of one-way functions and cover-free families, and it is secure against the adaptive chosen-message attack.

An approach for adaptive and integrated environmental planning to deal with uncertainty in a Great Barrier Reef Catchment

This paper presents the Mossman Mill District Practices Framework. It was developed in the Wet Tropics region within the Great Barrier Reef in north-eastern Australia to describe the environmental benefits of agricultural management practices for the sugar cane industry. The framework translates complex, unclear and overlapping environmental plans, policy and legal arrangements into a simple framework of management practices that landholders can use to improve their management actions. Practices range from those that are old or outdated through to aspirational practices that have the potential to achieve desired resource condition targets. The framework has been applied by stakeholders at multiple scales to better coordinate and integrate a range of policy arrangements to improve natural resource management. It has been used to structure monitoring and evaluation in order to underpin a more adaptive approach to planning at mill district and property scale. Potentially, the framework and approach can be applied across fields of planning where adaptive management is needed. It has the potential to overcome many of the criticisms of property-scale and regional Natural Resource Management.

Matching image sets via adaptive multi convex hull

Traditional nearest points methods use all the samples in an image set to construct a single convex or affine hull model for classification. However, strong artificial features and noisy data may be generated from combinations of training samples when significant intra-class variations and/or noise occur in the image set. Existing multi-model approaches extract local models by clustering each image set individually only once, with fixed clusters used for matching with various image sets. This may not be optimal for discrimination, as undesirable environmental conditions (eg. illumination and pose variations) may result in the two closest clusters representing different characteristics of an object (eg. frontal face being compared to non-frontal face). To address the above problem, we propose a novel approach to enhance nearest points based methods by integrating affine/convex hull classification with an adapted multi-model approach. We first extract multiple local convex hulls from a query image set via maximum margin clustering to diminish the artificial variations and constrain the noise in local convex hulls. We then propose adaptive reference clustering (ARC) to constrain the clustering of each gallery image set by forcing the clusters to have resemblance to the clusters in the query image set. By applying ARC, noisy clusters in the query set can be discarded. Experiments on Honda, MoBo and ETH-80 datasets show that the proposed method outperforms single model approaches and other recent techniques, such as Sparse Approximated Nearest Points, Mutual Subspace Method and Manifold Discriminant Analysis.

Stabilization of parametric roll resonance with active u-tanks via Lyapunov control design

Parametric ship roll resonance is a phenomenon where a ship can rapidly develop high roll motion while sailing in longitudinal waves. This effect can be described mathematically by periodic changes of the parameters of the equations of motion, which lead to a bifurcation. In this paper, the control design of an active u-tank stabilizer is carried out using Lyapunov theory. A nonlinear backstepping controller is developed to provide global exponential stability of roll. An extension of commonly used u-tank models is presented to account for large roll angles, and the control design is tested via simulation on a high-fidelity model of a vessel under parametric roll resonance.

A variant of the breast cancer type 2 susceptibility protein (BRC) repeat is essential for the RECQL5 Helicase to interact with RAD51 Recombinase for genome stabilization

The BRC repeat is a structural motif in the tumor suppressor BRCA2 (breast cancer type 2 susceptibility protein), which promotes homologous recombination (HR) by regulating RAD51 recombinase activity. To date, the BRC repeat has not been observed in other proteins, so that its role in HR is inferred only in the context of BRCA2. Here, we identified a BRC repeat variant, named BRCv, in the RECQL5 helicase, which possesses anti-recombinase activity in vitro and suppresses HR and promotes cellular resistance to camptothecin-induced replication stress in vivo. RECQL5-BRCv interacted with RAD51 through two conserved motifs similar to those in the BRCA2-BRC repeat. Mutations of either motif compromised functions of RECQL5, including association with RAD51, inhibition of RAD51-mediated D-loop formation, suppression of sister chromatid exchange, and resistance to camptothecin-induced replication stress. Potential BRCvs were also found in other HR regulatory proteins, including Srs2 and Sgs1, which possess anti-recombinase activities similar to that of RECQL5. A point mutation in the predicted Srs2-BRCv disrupted the ability of the protein to bind RAD51 and to inhibit D-loop formation. Thus, BRC is a common RAD51 interaction module that can be utilized by different proteins to either promote HR, as in the case of BRCA2, or to suppress HR, as in RECQL5.

An adaptive appearance-based map for long-term topological localization of mobile robots

"This work considers a mobile service robot which uses an appearance-based representation of its workplace as a map, where the current view and the map are used to estimate the current position in the environment. Due to the nature of real-world environments such as houses and offices, where the appearance keeps changing, the internal representation may become out of date after some time. To solve this problem the robot needs to be able to adapt its internal representation continually to the changes in the environment. This paper presents a method for creating an adaptive map for long-term appearance-based localization of a mobile robot using long-term and short-term memory concepts, with omni-directional vision as the external sensor."--publisher website

An adaptive spherical view representation for navigation in changing environments

Real-world environments such as houses and offices change over time, meaning that a mobile robot’s map will become out of date. In previous work we introduced a method to update the reference views in a topological map so that a mobile robot could continue to localize itself in a changing environment using omni-directional vision. In this work we extend this longterm updating mechanism to incorporate a spherical metric representation of the observed visual features for each node in the topological map. Using multi-view geometry we are then able to estimate the heading of the robot, in order to enable navigation between the nodes of the map, and to simultaneously adapt the spherical view representation in response to environmental changes. The results demonstrate the persistent performance of the proposed system in a long-term experiment.

Long-term experiments with an adaptive spherical view representation for navigation in changing environments

Real-world environments such as houses and offices change over time, meaning that a mobile robot’s map will become out of date. In this work, we introduce a method to update the reference views in a hybrid metrictopological map so that a mobile robot can continue to localize itself in a changing environment. The updating mechanism, based on the multi-store model of human memory, incorporates a spherical metric representation of the observed visual features for each node in the map, which enables the robot to estimate its heading and navigate using multi-view geometry, as well as representing the local 3D geometry of the environment. A series of experiments demonstrate the persistence performance of the proposed system in real changing environments, including analysis of the long-term stability.