A new fuzzy approach for pattern recognition with application to EMG classification

A fuzzy logic system with center average defuzzifier, product-inference rule, nonsingleton fuzzifier and Gauss membership function is discussed. The fuzzy sets are initially defined by the cluster parameters from the Basic ISO-DATA algorithm on input space. The system is then trained via back error propagation algorithm so that the fuzzy sets are fine-tuned. The system is applied to functional EMG classification and compared with its ANN counterpart. It is superior to the latter in at least three points: higher recognition rate; insensitive to over-training; and more consistent outputs thus having higher reliability.published_or_final_versio

Fuzzy EMG classification for prosthesis control

This paper proposes a fuzzy approach to classify single-site electromyograph (EMG) signals for multifunctional prosthesis control. While the classification problem is the focus of this paper, the ultimate goal is to improve myoelectric system control performance, and classification is an essential step in the control. Time segmented features are fed to a fuzzy system for training and classification. In order to obtain acceptable training speed and realistic fuzzy system structure, these features are clustered without supervision using the Basic Isodata algorithm at the beginning of the training phase, and the clustering results are used in initializing the fuzzy system parameters. Afterwards, fuzzy rules in the system are trained with the back-propagation algorithm. The fuzzy approach was compared with an artificial neural network (ANN) method on four subjects, and very similar classification results were obtained. It is superior to the latter in at least three points: slightly higher recognition rate; insensitivity to overtraining; and consistent outputs demonstrating higher reliability. Some potential advantages of the fuzzy approach over the ANN approach are also discussed.published_or_final_versio

CCL2 recruits inflammatory monocytes to facilitate breast-tumour metastasis

Macrophages abundantly found in the tumor microenvironment enhance malignancy(1). At metastatic sites a distinct population of metastasis associated macrophages (MAMs) promote tumor cell extravasation, seeding and persistent growth(2). Our study has defined the origin of these macrophages by showing Gr1+ inflammatory monocytes (IMs) are preferentially recruited to pulmonary metastases but not primary mammary tumors, a process also found for human IMs in pulmonary metastases of human breast cancer cells. The recruitment of these CCR2 (receptor for chemokine CCL2) expressing IMs and subsequently MAMs and their interaction with metastasizing tumor cells is dependent on tumor and stromal synthesized CCL2 (FigS1). Inhibition of CCL2/CCR2 signaling using anti-CCL2 antibodies blocks IM recruitment and inhibits metastasis in vivo and prolongs the survival of tumor-bearing mice. Depletion of tumor cell-derived CCL2 also inhibits metastatic seeding. IMs promote tumor cell extravasation in a process that requires monocyte-derived VEGF. CCL2 expression and macrophage infiltration are correlated with poor prognosis and metastatic disease in human breast cancer (Fig S2)(3-6). Our data provides the mechanistic link between these two clinical associations and indicates new therapeutic targets for treating metastatic breast disease

STM and RHEED study of the Si(001)-c(8x8) surface

The Si(001) surface deoxidized by short annealing at T~925C in the ultrahigh vacuum molecular beam epitaxy chamber has been in situ investigated by high resolution scanning tunnelling microscopy (STM) and reflected high energy electron diffraction (RHEED). RHEED patterns corresponding to (2x1) and (4x4) structures were observed during sample treatment. The (4x4) reconstruction arose at T<600C after annealing. The reconstruction was observed to be reversible: the (4x4) structure turned into the (2x1) one at T>600C, the (4x4) structure appeared again at recurring cooling. The c(8x8) reconstruction was revealed by STM at room temperature on the same samples. A fraction of the surface area covered by the c(8x8) structure decreased as the sample cooling rate was reduced. The (2x1) structure was observed on the surface free of the c(8x8) one. The c(8x8) structure has been evidenced to manifest itself as the (4x4) one in the RHEED patterns. A model of the c(8x8) structure formation has been built on the basis of the STM data. Origin of the high-order structure on the Si(001) surface and its connection with the epinucleation phenomenon are discussed.Comment: 26 pages, 12 figure

From Nonspecific DNA–Protein Encounter Complexes to the Prediction of DNA–Protein Interactions

©2009 Gao, Skolnick. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.doi:10.1371/journal.pcbi.1000341DNA–protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA–protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA–protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA–protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA–protein interaction modes exhibit some similarity to specific DNA–protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Ca deviation from native is up to 5 Å from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA–protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein

Accreting Neutron Stars in Low-Mass X-Ray Binary Systems

Using the Rossi X-ray Timing Explorer (RossiXTE), astronomers have discovered that disk-accreting neutron stars with weak magnetic fields produce three distinct types of high-frequency X-ray oscillations. These oscillations are powered by release of the binding energy of matter falling into the strong gravitational field of the star or by the sudden nuclear burning of matter that has accumulated in the outermost layers of the star. The frequencies of the oscillations reflect the orbital frequencies of gas deep in the gravitational field of the star and/or the spin frequency of the star. These oscillations can therefore be used to explore fundamental physics, such as strong-field gravity and the properties of matter under extreme conditions, and important astrophysical questions, such as the formation and evolution of millisecond pulsars. Observations using RossiXTE have shown that some two dozen neutron stars in low-mass X-ray binary systems have the spin rates and magnetic fields required to become millisecond radio-emitting pulsars when accretion ceases, but that few have spin rates above about 600 Hz. The properties of these stars show that the paucity of spin rates greater than 600 Hz is due in part to the magnetic braking component of the accretion torque and to the limited amount of angular momentum that can be accreted in such systems. Further study will show whether braking by gravitational radiation is also a factor. Analysis of the kilohertz oscillations has provided the first evidence for the existence of the innermost stable circular orbit around dense relativistic stars that is predicted by strong-field general relativity. It has also greatly narrowed the possible descriptions of ultradense matter.Comment: 22 pages, 7 figures, updated list of sources and references, to appear in "Short-period Binary Stars: Observation, Analyses, and Results", eds. E.F. Milone, D.A. Leahy, and D. Hobill (Dordrecht: Springer, http://www.springerlink.com

Kilohertz quasi-periodic oscillations in low-mass X-ray binaries

In early 1996 a series of discoveries begun with NASA's Rossi X-ray Timing Explorer of a new, up to then unknown astrophysical phenomenon. It turned out that accreting low magnetic-field neutron stars show quasi-periodic oscillations in their X-ray flux at rates of up to more than a kilohertz. These kHz QPO, now reported from eleven different systems, are among the fastest phenomena in the sky and can provide us with new information about the fundamental properties of neutron stars and help testing general relativity in the strong-field regime. If, for example, their frequencies can be identified with the Keplerian frequencies of matter in orbit around a 1.4 Solar-mass neutron star, then the radius of the star would have to be less than 15 km, which directly constrains the equation of state of bulk nuclear-density matter, and for an only slightly tighter orbit or slightly more massive neutron star the orbital radius would equal the Schwarzschild-geometry general-relativistic marginally stable orbit (12.5 km for a 1.4 Solar mass object). So far all models that have been put forward for explaining the new phenomenon have encountered problems. In this paper I review the relatively simple and highly suggestive phenomenology as it has emerged from the data up to now, and discuss some of the proposed models.Comment: To be published in the Proceedings of the Wise Observatory 25th Anniversary Symposium "Astronomical Time Series", Tel Aviv, January 199

Monocytes regulate the mechanism of T-cell death by inducing Fas-mediated apoptosis during bacterial infection.

Monocytes and T-cells are critical to the host response to acute bacterial infection but monocytes are primarily viewed as amplifying the inflammatory signal. The mechanisms of cell death regulating T-cell numbers at sites of infection are incompletely characterized. T-cell death in cultures of peripheral blood mononuclear cells (PBMC) showed 'classic' features of apoptosis following exposure to pneumococci. Conversely, purified CD3(+) T-cells cultured with pneumococci demonstrated necrosis with membrane permeabilization. The death of purified CD3(+) T-cells was not inhibited by necrostatin, but required the bacterial toxin pneumolysin. Apoptosis of CD3(+) T-cells in PBMC cultures required 'classical' CD14(+) monocytes, which enhanced T-cell activation. CD3(+) T-cell death was enhanced in HIV-seropositive individuals. Monocyte-mediated CD3(+) T-cell apoptotic death was Fas-dependent both in vitro and in vivo. In the early stages of the T-cell dependent host response to pneumococci reduced Fas ligand mediated T-cell apoptosis was associated with decreased bacterial clearance in the lung and increased bacteremia. In summary monocytes converted pathogen-associated necrosis into Fas-dependent apoptosis and regulated levels of activated T-cells at sites of acute bacterial infection. These changes were associated with enhanced bacterial clearance in the lung and reduced levels of invasive pneumococcal disease

A framework for integrating sustainability estimation with concepts of rules of building measurement

BIM promises improvement in project delivery efficiencies such as reduction in costs and errors and timely completion. Benefits are also expected in sustainable construction aspect with research efforts being extended to sustainable design and assessment. These efforts are still been explored for the purposes of unifying quantification methodologies, the standardisation of system boundaries, terms of references and sustainability measures. Embodied energy and CO2 are two common measures that have been widely used in the construction sector. Although a number calculation system exists, they are not useful to the iterations that occur at the early stages of the project life cycle. At the procurement stage, professionals often rely on schedules and bill of quantities with no reference to sustainability credentials. It is therefore important to integrate sustainability measure with concepts in standard measurement methods. As such, we propose a framework to integrate sustainability credential with the concepts in rule of building measurement. We conclude that this framework can be applicable to any rule of building measurement and it is implementable in a computer programmable environment