Bladder compliance in patients with benign prostatic hyperplasia

Factors influencing bladder compliance were examined in 116 patients with benign prostatic hyperplasia (BPH), by evaluating patients' histories, response of isolated bladder strips to acetylcholine, and the effect of prostatic urethral anesthesia. Patients' age, frequency of micturition, and duration of voiding difficulty were not correlated with bladder compliance. Bladder compliance was significantly low in patients within 30 days after urinary retention, as compared with bladder compliance in patients without an episode of retention. More than 30 days after retention, however, there was a tendency toward increased bladder compliance. Restricted to patients without an episode of retention, bladder compliance in the overactive detrusor group was found to be significantly lower than in the normal group. The responses to acetylcholine of bladder strips were compared between patients with low and normal-compliance bladders. The dose-response curve of patients with low-compliance bladders did not differ from that of those with normal compliance bladders, even when patients with an episode of retention were excluded. After prostatic urethral anesthesia, a significant increase of bladder compliance was observed in patients with an overactive detrusor, while the increase was not significant in patients with a normal detrusor. Our results strongly suggest that easy irritability of the anatomically altered prostatic urethra, as well as bladder over-distension caused by urinary retention, are important factors affecting bladder compliance in BPH patients.     

Design of an optimal series compensator based on DARMA model — The MIMO case

Design of an optimal series compensator for MIMO systems is considered in this paper using the DARMA form. The main purpose is to show how to find the smallest number of samples in each output channel to yield an optimal series compensator which is of the smallest possible order.     

Expressions Recognition of North-East Indian (NEI) Faces

Facial expression is one of the major distracting factors for face recognition performance. Pose and illumination variations on face images also influence the performance of face recognition systems. The combination of three variations (facial expression, pose and illumination) seriously degrades the recognition accuracy. In this paper, three experimental protocols are designed in such a way that the successive performance degradation due to the increasing variations (expressions, expressions with illumination effect and expressions with illumination and pose effect) on face images can be examined. The whole experiment is carried out using North-East Indian (NEI) face images with the help of four well-known classification algorithms namely Linear Discriminant Analysis (LDA), K-Nearest Neighbor algorithm (KNN), combination of Principal Component Analysis and Linear Discriminant Analysis (PCA + LDA), combination of Principal Component Analysis and K-Nearest Neighbor algorithm (PCA + KNN). The experimental observations are analyzed through confusion matrices and graphs. This paper also describes the creation of NEI facial expression database, which contains visual static face images of different ethnic groups of the North-East states. The database is useful for future researchers in the area of forensic science, medical applications, affective computing, intelligent environments, lie detection, psychiatry, anthropology, etc.     

Temperature dependence of open-circuit voltage in dye-sensitized solar cells

Temperature, T, dependence of open-circuit voltage, V_oc, was investigated in home-assembled and maker-trial dye-sensitized solar cells, which had wide variety in V_oc, i.e. 600–800 mV. A linear decrease of V_oc was observed with increasing T; all these cells had a slope of about ?2.5 mV/°C, irrespective of the V_ocs in the STC. The mechanism of the T dependence of V_oc was discussed with the electrochemical impedance spectroscopy, EIS. Analyses of EIS data with a newly derived model revealed that this dependence is primarily ascribed to a shift of the TiO₂ conduction band.     

Electric Ejection of Viscous Inks From MEMS Capillary Array Head for Direct Drawing of Fine Patterns

Free-space microink streams are realized by an array of microcapillaries. Ink is ejected from capillaries accelerated by an electric field with low or no back pressure applied. The capillaries are 20 mum in diameter, whereas the microstreams are only a few micrometers thick due to the Taylor cone effect. This method enables one to draw very fine lines down to 1 mum without lithographical techniques. With a pulsed-field application, dotted lines can also be drawn. Direct drawing of both solid and dotted lines has successfully been demonstrated by applying dc and 500-Hz ac fields, respectively.     

Oxidative stability of Echium plantagineum seed oil bodies

Echium plantagineum seed contains a highly polyunsaturated oil (approximately 14% linoleic acid, 10% γ‐linolenic acid, 33% α‐linolenic acid and 14% stearidonic acid); almost half of the fatty acids are omega‐3 fatty acids, so there is an interest in the possible health benefits of this oil, which, once extracted, is prone to oxidation. For the first time in reported literature, oil bodies (OBs), the organelles that store the oil in mature seed, were recovered from E. plantagineum seeds. The oxidative stability of these organelles ex vivo, dispersed in an aqueous continuous phase, was tested against processed E. plantagineum oil emulsions stabilised with either SDS or Tween 20. For both primary and secondary oxidation products the OBs were the most stable form of dispersed oil, and the dispersed systems were all more stable than bulk E. plantagineum oil after incubating at 40°C for 7 days. The possible reasons for the enhanced chemical stability of E. plantagineum OBs are explored in this paper. Practical applications: OBs, the natural store of oil in oilseeds, can be recovered from seeds intact and are relatively stable to oxidation ex vivo. Echium seed OBs, enriched in physiologically active omega‐3 fatty acids, therefore offer an attractive alternative to traditional oil extraction methods and overcome the need to encapsulate the omega‐3 rich oil.     

Low-voltage high-drive CMOS current feedback op-amp

A novel CMOS current feedback op-amp is presented. The solution works using a low supply voltage and provides a wide input/output swing as well as a high current driving capability. Experimental results from a prototype implemented in a 0.35-/spl mu/m technology and powered with 1.5 V are also given. The circuit exhibits a better than 500 kHz closed-loop bandwidth and a /spl plusmn/1 mA current drive capability.     

Tracking Control of Multiple Mobile Robots: A Case Study of Inter‐Robot Collision‐Free Problem

ABSTRACT Tracking control problem of multiple mobile robots is considered. Our system is composed of a reference and two follower robots of unicycle type, which have their own priority numbers. The purpose is to control the two followers so that the reference is tracked with arbitrary desired clearance and also to avoid an inter‐robot collision, which can occur randomly during the control process subjected to communication range limitation. We introduce two switching controllers and appropriately using their convergence properties leading to the collision‐free movement. Simulation results prove efficiency of our control techniques.     

High-speed face recognition using self-adaptive radial basis function neural networks

In this work, we have proposed a self-adaptive radial basis function neural network (RBFNN)-based method for high-speed recognition of human faces. It has been seen that the variations between the images of a person, under varying pose, facial expressions, illumination, etc., are quite high. Therefore, in face recognition problem to achieve high recognition rate, it is necessary to consider the structural information lying within these images in the classification process. In the present study, it has been realized by modeling each of the training images as a hidden layer neuron in the proposed RBFNN. Now, to classify a facial image, a confidence measure has been imposed on the outputs of the hidden layer neurons to reduce the influences of the images belonging to other classes. This process makes the RBFNN as self-adaptive for choosing a subset of the hidden layer neurons, which are in close neighborhood of the input image, to be considered for classifying the input image. The process reduces the computation time at the output layer of the RBFNN by neglecting the ineffective radial basis functions and makes the proposed method to recognize face images in high speed and also in interframe period of video. The performance of the proposed method has been evaluated on the basis of sensitivity and specificity on two popular face recognition databases, the ORL and the UMIST face databases. On the ORL database, the best average sensitivity (recognition) and specificity rates are found to be 97.30 and 99.94%, respectively using five samples per person in the training set. Whereas, on the UMIST database, the above quantities are found to be 96.36 and 99.81%, respectively using eight samples per person in the training set. The experimental results indicate that the proposed method outperforms some of the face recognition approaches.