Extracting a largest redundancy-free XML storage structure from an acyclic hypergraph in polynomial time

Given a hypergraph and a set of embedded functional dependencies, we investigate the problem of determining the conditions under which we can efficiently generate redundancy-free XML storage structures with as few scheme trees as possible. Redundancy-free XML structures guarantee both economy in storage space and the absence of update anomalies, and having the least number of scheme trees requires the fewest number of joins to navigate among the data elements. We know that the general problem is intractable. The problem may still be intractable even when the hypergraph is acyclic and each hyperedge is in Boyce–Codd normal form (BCNF). As we show here, however, given an acyclic hypergraph with each hyperedge in BCNF, a polynomial-time algorithm exists that generates a largest possible redundancy-free XML storage structure. Successively generating largest possible scheme trees from among hyperedges not already included in generated scheme trees constitutes a reasonable heuristic for finding the fewest possible scheme trees. For many practical cases, this heuristic finds the set of redundancy-free XML storage structures with the fewest number of scheme trees. In addition to a correctness proof and a complexity analysis showing that the algorithm is polynomial, we also give experimental results over randomly generated but appropriately constrained hypergraphs showing empirically that the algorithm is indeed polynomial.     

A localized approach for the method of approximate particular solutions

The method of approximate particular solutions (MAPS) has been recently developed to solve various types of partial differential equations. In the MAPS, radial basis functions play an important role in approximating the forcing term. Coupled with the concept of particular solutions and radial basis functions, a simple and effective numerical method for solving a large class of partial differential equations can be achieved. One of the difficulties of globally applying MAPS is that this method results in a large dense matrix which in turn severely restricts the number of interpolation points, thereby affecting our ability to solve large-scale science and engineering problems.In this paper we develop a localized scheme for the method of approximate particular solutions (LMAPS). The new localized approach allows the use of a small neighborhood of points to find the approximate solution of the given partial differential equation. In this paper, this local numerical scheme is used for solving large-scale problems, up to one million interpolation points. Three numerical examples in two-dimensions are used to validate the proposed numerical scheme.     

Adaptive decoding for brain-machine interfaces through Bayesian parameter updates

Brain-machine interfaces (BMIs) transform the activity of neurons recorded in motor areas of the brain into movements of external actuators. Representation of movements by neuronal populations varies over time, during both voluntary limb movements and movements controlled through BMIs, due to motor learning, neuronal plasticity, and instability in recordings. To ensure accurate BMI performance over long time spans, BMI decoders must adapt to these changes. We propose the Bayesian regression self-training method for updating the parameters of an unscented Kalman filter decoder. This novel paradigm uses the decoder's output to periodically update its neuronal tuning model in a Bayesian linear regression. We use two previously known statistical formulations of Bayesian linear regression: a joint formulation, which allows fast and exact inference, and a factorized formulation, which allows the addition and temporary omission of neurons from updates but requires approximate variational inference. To evaluate these methods, we performed offline reconstructions and closed-loop experiments with rhesus monkeys implanted cortically with microwire electrodes. Offline reconstructions used data recorded in areas M1, S1, PMd, SMA, and PP of three monkeys while they controlled a cursor using a handheld joystick. The Bayesian regression self-training updates significantly improved the accuracy of offline reconstructions compared to the same decoder without updates. We performed 11 sessions of real-time, closed-loop experiments with a monkey implanted in areas M1 and S1. These sessions spanned 29 days. The monkey controlled the cursor using the decoder with and without updates. The updates maintained control accuracy and did not require information about monkey hand movements, assumptions about desired movements, or knowledge of the intended movement goals as training signals. These results indicate that Bayesian regression self-training can maintain BMI control accuracy over long periods, making clinical neuroprosthetics more viable.     

Label-free Growth Receptor-2 Detection and Dissociation Constant Assessment in Diluted Human Serum Using a Longitudinal Extension Mode of a Piezoelectric Microcantilever Sensor

We have investigated real-time, label-free, in-situ detection of human epidermal growth factor receptor 2 (Her2) in diluted serum using the first longitudinal extension mode of a lead zirconate-lead titanate (PZT)/glass piezoelectric microcantilever sensor (PEMS) with H3 single-chain variable fragment (scFv) immobilized on the 3-mercaptopropyltrimethoxysilane (MPS) insulation layer of the PEMS surface. We showed that with the longitudinal extension mode, the PZT/glass PEMS consisting of a 1 mm long and 127 μm thick PZT layer bonded with a 75 μm thick glass layer with a 1.8 mm long glass tip could detect Her2 at a concentration of 6-60 ng/ml (or 0.06-0.6 nM) in diluted human serum, about 100 times lower than the concentration limit obtained using the lower-frequency flexural mode of a similar PZT/glass PEMS. We further showed that with the longitudinal mode, the PZT/glass PEMS determined the equilibrium H3-Her2 dissociation constant K(d) to be 3.3±0.3 × 10(-8) M consistent with the value, 3.2±0.28 ×10(-8) M deduced by the surface plasmon resonance method (BIAcore).     

Effects of gender differences on the subjective perceived intensity of steering wheel rotational vibration based on a multivariate regression model

The aims of this study were to determine equal sensation curves for hand–arm steering wheel rotational vibration and to investigate the effect of gender on the subjective perceived intensity of steering wheel hand–arm vibration. Psychophysical response tests of 40 participants (20 males and 20 females) were performed using a steering wheel rotational vibration simulator using the category-ratio Borg CR10 scale procedure for direct estimation of perceived intensity. The test stimuli were sinusoidal vibrations at 22 third octave band centre frequencies in the range from 3 to 400 Hz, with acceleration amplitudes in the range from 0.04 to 27 m/s² r.m.s. Multivariate regression procedures were applied to the experimentally acquired data in order to establish a regression model expressing the Borg CR10 perceived intensity values as a function of the two independent parameters of the frequency and amplitude of vibration. The equal sensation curves suggested a non-linear dependency of the subjective perceived intensity on both frequency and amplitude. Females were found to provide higher Borg CR10 perceived intensity values than males (p < 0.05), particularly at the higher intensity levels above approximately 1.0 m/s² r.m.s and at the higher frequencies above approximately 20 Hz.

Relevance to industry

For the manufacturers of steering systems and of other automobile components this study provides vibration perception curves and identifies the possible importance of gender towards the perception of vibration which arrives at the steering wheel.     

Ultrafast imaging of polyatomic molecules with simplex algorithm

A simplex algorithm used to solve molecular structure from asymptotic momentum values is reported. The geometry of ${\text{CO}}_2^{3+}$ molecular ions in linear and bent configurations is reconstructed. A polyatomic molecular ion with trigonal planar symmetry is used to demonstrate the scalability of the algorithm.     

Implementation of wide-field integration of optic flow for autonomous quadrotor navigation

Insects are capable of robust visual navigation in complex environments using efficient information extraction and processing approaches. This paper presents an implementation of insect inspired visual navigation that uses spatial decompositions of the instantaneous optic flow to extract local proximity information. The approach is demonstrated in a corridor environment on an autonomous quadrotor micro-air-vehicle (MAV) where all the sensing and processing, including altitude, attitude, and outer loop control is performed on-board. The resulting methodology has the advantages of computation speed and simplicity, hence are consistent with the stringent size, weight, and power requirements of MAVs.     

Brain–computer interfaces and dualism: a problem of brain,mind, and body

The brain–computer interface (BCI) has made remarkable progress in the bridging the divide between the brain and the external environment to assist persons with severe disabilities caused by brain impairments. There is also continuing philosophical interest in BCIs which emerges from thoughtful reflection on computers, machines, and artificial intelligence. This article seeks to apply BCI perspectives to examine, challenge, and work towards a possible resolution to a persistent problem in the mind–body relationship, namely dualism. The original humanitarian goals of BCIs and the technological inventiveness result in BCIs being surprisingly useful. We begin from the neurologically impaired person, the problems encountered, and some pioneering responses from computers and machines. Secondly, the interface of mind and brain is explored via two points of clarification: direct and indirect BCIs, and the nature of thoughts. Thirdly, dualism is beset by mind–body interaction difficulties and is further questioned by the phenomena of intentions, interactions, and technology. Fourthly, animal minds and robots are explored in BCI settings again with relevance for dualism. After a brief look at other BCIs, we conclude by outlining a future BCI philosophy of brain and mind, which might appear ominous and could be possible.     

Dealing with logical omniscience: Expressiveness and pragmatics

We examine four approaches for dealing with the logical omniscience problem and their potential applicability: the syntactic approach, awareness, algorithmic knowledge, and impossible possible worlds. Although in some settings these approaches are equi-expressive and can capture all epistemic states, in other settings of interest (especially with probability in the picture), we show that they are not equi-expressive. We then consider the pragmatics of dealing with logical omniscience—how to choose an approach and construct an appropriate model.     

Fruit Senescence and Decay Simulation

Aging and imperfections provide important visual cues for realism. We present a novel physically‐based approach for simulating the biological aging and decay process in fruits. This method simulates interactions between multiple processes. Our biologically‐derived, reaction‐diffusion model generates growth patterns for areas of fungal and bacterial infection. Fungal colony spread and propagation is affected by both bacterial growth and nutrient depletion. This process changes the physical properties of the surface of the fruit as well as its internal volume substrate. The fruit is physically simulated with parameters such as skin thickness and porosity, water content, flesh rigidity, ambient temperature, humidity, and proximity to other surfaces. Our model produces a simulation that closely mirrors the progression of decay in real fruits under similar parameterized conditions. Additionally, we provide a tool that allows artists to customize the input of the program to produce generalized fruit simulations.