Abnormal sensory nerve conduction in multifocal demyelinating neuropathy with persistent conduction block

Two patients exhibited chronic, slightly asymmetric weakness and wasting with fasciculations of the upper limb and hand muscles. Motor nerve conduction studies showed features of multifocal conduction block in nerve segments other than those usually involved in entrapment syndromes. The F wave was markedly delayed in the median and ulnar nerves. Transcranial cortical and cervical root magnetic stimulation showed bilaterally delayed thenar responses with normal central conduction time. Needle electromyography demonstrated a chronic denervation pattern with large polyphasic motor units in several muscles of the upper limbs. Sensory symptoms were mild and limited to paresthesias in the fingertips. Sensory nerve conduction velocity and sensory nerve action potential amplitudes were normal in elbow-to-wrist and wrist-to-finger segments of the median and ulnar nerves, but there was a delayed cortical response and unrecognizable Erb's point and cervical responses in the somatosensory evoked potentials to median nerve electrical stimulation. Electrophysiologic examination was normal in most nerves of the lower limbs. These two patients, meeting clinical and electrophysiologic criteria of multifocal neuropathy with conduction block, demonstrate that sensory fibers may also be involved in this syndrome.     

Fundamental properties of reset control systems

Reset controllers are linear controllers that reset some of their states to zero when their input is zero. We are interested in their feedback connection with linear plants, and in this paper we establish fundamental closed-loop properties including stability and asymptotic tracking. This paper considers more general reset structures than previously considered, allowing for higher-order controllers and partial-state resetting. It gives a testable necessary and sufficient condition for quadratic stability and links it to both uniform bounded-input bounded-state stability and steady-state performance. Unlike previous related research, which includes the study of impulsive differential equations, our stability results require no assumptions on the evolution of reset times.     

Fast Decodable Turbo Codes

Decoding delay is an important consideration for the use of turbo codes in practical applications. We propose a new structure for turbo codes which is very suitable for parallel decoding. It is shown by union bound analysis and simulation results that the proposed system performance is comparable to that of the classical turbo codes     

Zirconium tetra-n-butylate modified with different organic acids: Hydrolysis and polymerization of the products

In this work, (a) complexation reaction of zirconium tetra-n-butylate, Zr(OBu ⁿ )₄, with MAc and different organic acids, (b) the hydrolysis reaction of modified Zr species, and (c) the polymerization reaction of complex products are studied. Zr(OBu ⁿ )₄ was reacted with different mole ratios of methacrylic acid (MAc) at room temperature and the maximum combination ratio was found to be 1:2 [Zr(OBu ⁿ )₄:MAc] by FT-IR. The modification of zirconium tetra-n-butylate with the acid mixtures [methacrylic acid-acetic acid (MeCOOH), methacrylic acid-propionic acid (EtCOOH), methacrylic acid-butyric acid (PrCOOH)] was made for a combination ratio of 1:1:1 [MAc:RCOOH:Zr(OBu ⁿ )₄; R: Me, Et, Pr] and the products were characterized by¹H-NMR, FT-IR, and UV spectroscopies. Following their synthesis, hydrolysis of the complexes with various amounts of water and polymerization with benzoyl peroxide were realized. The hydrolysis and polymerization products of the complexes were studied by Karl-Fischer coulometric titration and thermal analysis, respectively. Methyl ethyl ketone(MEK) and chloroform were chosen as solvents.     

Using genetic algorithm for the optimization of seismic behavior of steel planar frames with semi-rigid connections

Beam-column connections have a significant role in the results of the analysis and the design of steel frames. In this paper, a genetic algorithm has been used for the non-linear analysis and design of steel frames. For minimizing the weight of frames, while satisfying the applied constraints and restraints such as the limits of normal and combined stresses, criteria such as target displacement(s) and the number and locations of plastic hinges were used. To analyze and design the frame elements, I and box-shaped standard sections were used for beams and columns, respectively. Finally, some clues for finding optimizing semi-rigid connection stiffness values for beam-to-column connections have been obtained. The degrees of these rigidities are obtained by a genetic algorithm during the procedure of optimization in order to reach a frame with the minimum weight. SAP2000 structural analysis program was used to perform modal analysis and linear and non-linear static solutions as well as the design of the elements. A MATLAB program was written for the process of optimization. The procedure of optimization was based on a weight minimization carried out for 9 steel frames. Thus, the optimum connection stiffness could be obtained for minimizing the weight of the structure. The results show that the non-linear analysis gives less weight for short period frames with semi-rigid connections compared to those of linear ones. However, by increasing the periods of frames, much less weights are obtained in the case of non-linear analysis with semi-rigid connections.     

Release of salicylic acid through poly(vinyl alcohol)/poly(vinyl pyrrolidone) and poly(vinyl alcohol‐g‐N‐vinyl‐2‐pyrrolidone) membranes

A controlled release profile of salicylic acid (SA) for transdermal administration has been developed. Poly (vinyl alcohol) (PVA) and Poly(vinyl alcohol)/Poly(vinyl pyrrolidone) (PVP) blended preparations were used to prepare the membranes by solvent‐casting technique. The release of the drug from the membranes was evaluated at in vitro conditions. The effects of PVA/PVP (v/v) ratio, pH, SA concentration and temperature were investigated. 60/40 (v/v) PVA/PVP ratio was found to be the best ratio for the SA release. Increase in pH and temperature was observed to increase the transport of SA. Instead of blending PVA with PVP, N‐Vinyl‐2‐pyrrolidone (VP) was grafted onto the PVA and the delivery performance for SA was compared with that of the blended PVA/PVP membranes. Grafted membranes gave higher transport percentages than the blended membranes. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 102:1244–1253, 2006     

An investigation of chloride-substituted Schiff bases as corrosion inhibitors for steel

Polarization and impedance measurements were performed on steel in deaerated 5% HCl solution with and without Schiff base additives within the concentration range 1 × 10⁻⁴–5 × 10⁻³ mol/dm³. The Schiff base compounds used were salicylaldimine, R, N-(2-chlorophenyl)salicyaldimine, 2Cl-R, N-(3-chlorophenyl)salicyaldimine, 3Cl-R, and N-(4-chlorophenyl)salicyaldimine, 4Cl-R. It was found that when the concentration of the inhibitors were increased the inhibitor efficiencies, η, also increased with increasing surface coverage. The results indicated that the ortho-substituted (2Cl-R) compound had the highest inhibition efficiency. All the Schiff base additives studied obeyed the Langmuir isotherm.     

Classification of brain hemorrhage computed tomography images using OzNet hybrid algorithm

Classification of brain hemorrhage computed tomography (CT) images provides a better diagnostic implementation for emergency patients. Attentively, each brain CT image must be examined by doctors. This situation is time-consuming, exhausting, and sometimes leads to making errors. Hence, we aim to find the best algorithm owing to a requirement for automatic classification of CT images to detect brain hemorrhage. In this study, we developed OzNet hybrid algorithm, which is a novel convolution neural networks (CNN) algorithm. Although OzNet achieves high classification performance, we combine it with Neighborhood Component Analysis (NCA) and many classifiers: Artificial neural networks (ANN), Adaboost, Bagging, Decision Tree, K-Nearest Neighbor (K-NN), Linear Discriminant Analysis (LDA), Naïve Bayes and Support Vector Machines (SVM). In addition, Oznet is utilized for feature extraction, where 4096 features are extracted from the fully connected layer. These features are reduced to have significant and informative features with minimum loss by NCA. Eventually, we use these classifiers to classify these significant features. Finally, experimental results display that OzNet-NCA-ANN excellent classifier model and achieves 100% accuracy with created Dataset 2 from Brain Hemorrhage CT images.