On the existence of monodromy groups of fuchsian systems on Riemann's sphere with unipotent genrators

In this paper we consider the following problem: For what choice of the (p+1)-tuple of conjugacy classesC ₁,…,C _p+1 in GL(n,?),p≥2, do there exist irreducible (p+1)-tuples of matricesM _j ∈C _j such that the productM ₁,…,M _p+1 equals identity? We present the necessary and sufficient conditions for the existence of such tuples in the case whereM _j are unipotent.     

Machine learning in control of functional electrical stimulationsystems for locomotion

Two machine learning techniques were evaluated for automatic design of a rule-based control of functional electrical stimulation (FES) for locomotion of spinal cord injured humans. The task was to learn the invariant characteristics of the relationship between sensory information and the FES-control signal by using off-line supervised training. Sensory signals were recorded using pressure sensors installed in the insoles of a subject's shoes and goniometers attached across the joints of the affected leg. The FES-control consisted of pulses corresponding to time intervals when the subject pressed on the manual push-button to deliver the stimulation during FES-assisted ambulation. The machine learning techniques used were the adaptive logic network (ALN) and the inductive learning algorithm (IL). Results to date suggest that, given the same training data, the IL learned faster than the ALN while both performed the test rapidly. The generalization was estimated by measuring the test errors and it was better with an ALN, especially if past points were used to reflect the time dimension. Both techniques were able to predict future stimulation events. An advantage of the ALN over the IL was that ALN's can be retrained with new data without losing previously collected knowledge. The advantages of the IL over the ALN were that the IL produces small, explicit, comprehensible trees and that the relative importance of each sensory contribution can be quantified     

Engineering Analysis and Design with ALE-VMS and Space–Time Methods

Flow problems with moving boundaries and interfaces include fluid–structure interaction (FSI) and a number of other classes of problems, have an important place in engineering analysis and design, and offer some formidable computational challenges. Bringing solution and analysis to them motivated the Deforming-Spatial-Domain/Stabilized Space–Time (DSD/SST) method and also the variational multiscale version of the Arbitrary Lagrangian–Eulerian method (ALE-VMS). Since their inception, these two methods and their improved versions have been applied to a diverse set of challenging problems with a common core computational technology need. The classes of problems solved include free-surface and two-fluid flows, fluid–object and fluid–particle interaction, FSI, and flows with solid surfaces in fast, linear or rotational relative motion. Some of the most challenging FSI problems, including parachute FSI, wind-turbine FSI and arterial FSI, are being solved and analyzed with the DSD/SST and ALE-VMS methods as core technologies. Better accuracy and improved turbulence modeling were brought with the recently-introduced VMS version of the DSD/SST method, which is called DSD/SST-VMST (also ST-VMS). In specific classes of problems, such as parachute FSI, arterial FSI, ship hydrodynamics, fluid–object interaction, aerodynamics of flapping wings, and wind-turbine aerodynamics and FSI, the scope and accuracy of the FSI modeling were increased with the special ALE-VMS and ST FSI techniques targeting each of those classes of problems. This article provides an overview of the core ALE-VMS and ST FSI techniques, their recent versions, and the special ALE-VMS and ST FSI techniques. It also provides examples of challenging problems solved and analyzed in parachute FSI, arterial FSI, ship hydrodynamics, aerodynamics of flapping wings, wind-turbine aerodynamics, and bridge-deck aerodynamics and vortex-induced vibrations.     

Patient-specific computer modeling of blood flow in cerebral arteries with aneurysm and stent

We present the special arterial fluid mechanics techniques we have developed for patient-specific computer modeling of blood flow in cerebral arteries with aneurysm and stent. These techniques are used in conjunction with the core computational technique, which is the space?Ctime version of the variational multiscale (VMS) method and is called ??DST/SST-VMST.?? The special techniques include using NURBS for the spatial representation of the surface over which the stent mesh is built, mesh generation techniques for both the finite- and zero-thickness representations of the stent, techniques for generating refined layers of mesh near the arterial and stent surfaces, and models for representing double stent. We compute the unsteady flow patterns in the aneurysm and investigate how those patterns are influenced by the presence of single and double stents. We also compare the flow patterns obtained with the finite- and zero-thickness representations of the stent.     

Scale and translation invariant minimum average correlation energy filter

A new type, to our knowledge, of scale and translation invariant correlation filter is described. Its form in polar coordinates generalizes the forms of the one-decomposition-term filters. That is combined with the minimum-average-correlation-energy optimization method to suppress the sidelobes and achieve correlation peaks. A theoretical analysis as well as a detailed explanation of the computational procedure is provided. The concept is tested on five interferometric images of 256 gray levels without preprocessing. The computed filter gives correlation peaks for reference image scales in the range of 0.3/4.0 (minimal scale: maximal scale = 1:13). The discrimination ability of the filter is investigated-no false peak occurred. The filter works in the background so that there is no need for input image segmentation. A method for extension is described to calculate a filter for more than one reference image.     

Anaerobic surgical infection

The study covers 125 patients with anaerobic surgical infection, aged 7 to 82 years. Of the total 27 cases are operated for acute cholecystitis, four--diffuse acute peritonitis, seventeen--acute appendicitis, and three--acute hematogenous osteomyelitis. In acute cholecystitis and acute appendicitis microbiological study is carried out of the content, organic wall and periorganic space. In acute cholecystitis patients anaerobic flora is found in 39.01 per cent, and gram-negative--in 44.9 per cent, and in those presenting acute appendicitis--in 28.3 per cent and 58 per cent, respectively. The clinical analysis results point to a severer clinical course in the patients presenting anaerobic flora. The letter becomes manifest as mono infection in 37.2 per cent. It is pointed out that in the presence of two or more signs, characteristic of anaerobic infection, namely: destructive early process, offensive odor and intoxication, anaerobic bacterial flora should be invariably considered. At each microbiological examination the results of staining according to Gram should be also demanded from the laboratory.     

Sensory nerve recording for closed-loop control to restore motorfunctions

A method is developed for using neural recordings to control functional electrical stimulation (FES) to nerves and muscles. Experiments were done in chronic cats with a goal of designing a rule-based controller to generate rhythmic movements of the ankle joint during treadmill locomotion. Neural signals from the tibial and superficial peroneal nerves were recorded with cuff electrodes and processed simultaneously with muscular signals from ankle flexors and extensors in the cat's hind limb. Cuff electrodes are an effective method for long-term chronic recording in peripheral nerves without causing discomfort or damage to the nerve. For real-time operation the authors designed a low-noise amplifier with a blanking circuit to minimize stimulation artifacts. They used threshold detection to design a simple rule-based control and compared its output to the pattern determined using adaptive neural networks. Both the threshold detection and adaptive networks are robust enough to accommodate the variability in neural recordings. The adaptive logic network used for this study is effective in mapping transfer functions and therefore applicable for determination of gait invariants to be used for closed loop control in an FES system. Simple rule-bases will probably be chosen for initial applications to human patients. However, more complex FES applications require more complex rule-bases and better mapping of continuous neural recordings and muscular activity. Adaptive neural networks have promise for these more complex applications     

Ion-exchange copolymers based on tetrafluoroethylene,hexafluoropropylene, and acrylic acid

Peroxide-induced copolymerization of tetrafluoroethylene (TFE) with hexafluoropropylene (HFP) and acrylic acid (AA) at different molar ratios of monomers, reaction time, pressure, and initiator concentration was studied. By means of IR spectroscopy and temperature and phase characteristics of the copolymers obtained it was proved that a ternary copolymer of TFE, HFP, and AA was synthesized. Fluoro-containing polymers with ion-exchange capacities up to 0.8 meq/g were obtained. The composition of binary TFE-HFP and ternary TFE-HFP-AA copolymers and some of their characteristics were determined. Copolymerization takes place mainly in the stationary state with an induction period. Polymerization rate R ～ [In]^0.7, which is presumably connected with chain transfer reaction to AA.     

Carbon nanotubes based optical immunodetection of Staphylococcal Enterotoxin B (SEB) in food

Staphylococcal enterotoxins (SEs) are a major cause of food-borne diseases, traditionally SEs assayed immunologically with ELISA. Carbon nanotubes' (CNT) unique mechanical and electronic properties combined with a large specific surface area make them attractive for biosensing. To investigate whether CNT could improve the sensitivity of ELISA assays, we developed an optical CNT immunosensor for the detection of Staphylococcal Enterotoxin B (SEB) in food. Anti-SEB antibodies were immobilized onto a CNT surface through electrostatic adsorption and then the antibody-nanotube mixture was bound onto a polycarbonate film. SEB was then detected by a "sandwich-type" ELISA assay on the polycarbonate film. The use of CNT increased the sensitivity of the immunosensor by at least 6-fold, lowering the detection limit of SEB. The CNT immunosensor was also able to detect SEB various foods, suggesting the utility of CNT for this and other optical-based immunological detection methods.