Design of stable fuzzy controllers for an AGV

Fuzzy logic control is a relatively new technology and hence it needs rigorous comparative analyses with other well-established conventional control schemes. Further, fuzzy controller stability analysis is a major hindrance for its popularity among control engineers. This paper shows how stable fuzzy controllers may be synthesized for a typical AGV from the perspective of variable structure systems (VSS) theory. VSS or sliding model control (SMC) is an established robust non-linear control methodology. The AGV is characterized by highly non-linear, coupled and configuration dependent dynamics, with uncertainty in model parameters. Similarity in performance of the fuzzy controllers to the SMC controller is demonstrated through experimental results obtained for steer control of the AGV

Road curb and intersection detection using A 2D LMS

In most urban roads, and similar environments such as in theme parks, campus sites, industrial estates, science parks and the like, the painted lane markings that exist may not be easily discernible by CCD cameras due to poor lighting, bad weather conditions, and inadequate maintenance. An important feature of roads in such environments is the existence of pavements or curbs on either side defining the road boundaries. These curbs, which are mostly parallel to the road, can be hardnessed to extract useful features of the road for implementing autonomous navigation or driver assistance systems. However, extraction of the curb or road edge feature using vision image data is a very formidable task as the curb is not conspicuous in the vision image. To extract the curb using vision data requires extensive image processing, heuristics and very favorable ambient lighting. In our approach, road curbs are extracted speedily using range data provided by a 2D Laser range Measurement System (LMS). Experimental results are presented to demonstrate the viability, and effectiveness, of the proposed methodology and its robustness to different road configurations including road intersections

Road edge and lane boundary detection using laser and vision

This paper presents a methodology for extracting road edge and lane information for smart and intelligent navigation of vehicles. The range information provided by a fast laser range-measuring device is processed by an extended Kalman filter to extract the road edge or curb information. The resultant road edge information is used to aid in the extraction of the lane boundary from a CCD camera image. Hough Transform (HT) is used to extract the candidate lane boundary edges, and the most probable lane boundary is determined using an Active Line Model based on minimizing an appropriate Energy function. Experimental results are presented to demonstrate the effectiveness of the combined Laser and Vision strategy for road-edge and lane boundary detection

Green revolution vaccines, edible vaccines

Edible vaccines are sub-unit vaccines where the selected genes are introduced into the plants and the transgenic plant is then induced to manufacture the encoded protein. Edible vaccines are mucosal-targeted vaccines where stimulation of both systematic and mucosal immune network takes place. Foods under study include potatoes, bananas, lettuce, rice, wheat, soybean, corn and legumes. Edible vaccines for various diseases such as measles, cholera, hepatitis-B, and many more are in the process of development. Food vaccines may also help to suppress autoimmunity disorders such as Type-1 Diabetes. Key words: Edible vaccines, oral vaccines, antigen expression, food vaccines. African Journal of Biotechnology Vol. 2 (12), pp. 679-683, December 200

Road curb tracking in an urban environment

Road detection and tracking is very useful in the synthesis of driver assistance and intelligent transportation systems. In this paper a methodology is proposed based on the extended Kalman filer for robust road curb detection and tracking using a combination of onboard active and passive sensors. The problem is formulated as detecting and tracking a maneuvering target in clutter using onboard sensors on a moving platform. The primary sensors utilized are a 2 dimensional SICK laser scanner, five encoders and a gyroscope, together with an image sensor (CCD camera). Compared to the active 20 laser scanner the CCD camera is capable of providing observations over an extended horizon, thus making available much useful information about the curb trend, which is exploited in mainly the laser based tracking algorithm. The advantage of the proposed image enhanced laser detection/tracking method, over laser alone detection/tracking, is illustrated using simulations and its robustness to varied road curvatures, branching, turns and scenarios, is demonstrated through experimental results. © 2003 ISlF

DEVELOPMENT AND VALIDATION OF STABILITY INDICATING REVERSED PHASE HIGHPRESSURE LIQUID CHROMATOGRAPHY METHOD FOR SIMULTANEOUS ESTIMATION OF METFORMIN AND EMPAGLIFLOZIN IN BULK AND TABLET DOSAGE FORM

ABSTRACT Objective: To develop accurate, fast, simple, and precise reversed-phase high-pressure liquid chromatography method for simultaneous determination of the binary mixture of metformin (MET) and empagliflozin (EMPA) in dosage forms. Methods: The method uses a mobile phase consisting of phosphate buffer, acetonitrile, methanol (15:80:5 v/v/v), an octadecyl silica C-18 column (4.6 mm × 250 mm, 5 μ particle size) in isocratic mode, detection wavelength of 227 nm, and a flow rate of 1 mL/minutes. Results:  The  measured  retention  times  for  MET  and  EMPA  and  were  2.528  and  4.140 minutes,  respectively.  The  percentage  recoveries  of  MET  and  EMPA  were 101.12% and 100.55%, respectively. The relative standard deviation for assay of tablets was found to beÂ

The unfolded protein response and its potential role in Huntington's disease elucidated by a systems biology approach.

Huntington ´s disease (HD) is a progressive, neurodegenerative disease with a fatal outcome. Although the disease-causing gene (huntingtin) has been known for over 20 years, the exact mechanisms leading to neuronal cell death are still controversial. One potential mechanism contributing to the massive loss of neurons observed in the brain of HD patients could be the unfolded protein response (UPR) activated by accumulation of misfolded proteins in the endoplasmic reticulum (ER). As an adaptive response to counter-balance accumulation of un- or misfolded proteins, the UPR upregulates transcription of chaperones, temporarily attenuates new translation, and activates protein degradation via the proteasome. However, persistent ER stress and an activated UPR can also cause apoptotic cell death. Although different studies have indicated a role for the UPR in HD, the evidence remains inconclusive. Here, we present extensive bioinformatic analyses that revealed UPR activation in different experimental HD models based on transcriptomic data. Accordingly, we have identified 53 genes, including RAB5A, HMGB1, CTNNB1, DNM1, TUBB, TSG101, EEF2, DYNC1H1, SLC12A5, ATG5, AKT1, CASP7 and SYVN1 that provide a potential link between UPR and HD. To further elucidate the potential role of UPR as a disease-relevant process, we examined its connection to apoptosis based on molecular interaction data, and identified a set of 40 genes including ADD1, HSP90B1, IKBKB, IKBKG, RPS3A and LMNB1, which seem to be at the crossroads between these two important cellular processes. Remarkably, we also found strong correlation of UPR gene expression with the length of the polyglutamine tract of Huntingtin, which is a critical determinant of age of disease onset in human HD patients pointing to the UPR as a promising target for therapeutic intervention. The study is complemented by a newly developed web-portal called UPR-HD (http://uprhd.sysbiolab.eu) that enables visualization and interactive analysis of UPR-associated gene expression across various HD models