Ferromagnetic nano model study for the peristaltic flow in a plumb duct with permeable walls

Microsystem Technologies - The purpose of the present enquiry is to analyse the mechanics of an incompressible fluid, with water as base fluid, through a radially symmetric plumb duct with...     

A fog-based security framework for intelligent traffic light control system

Multimedia Tools and Applications - The world is facing many problems including that of traffic congestion. To highlight the issue of traffic congestion worldwide specially in urban areas and to...     

Comparative immunoreactivity of CD-68 and HMB-45 in malignant melanoma, neural tumors and nevi

The monoclonal antibody CD 68 (KP 1) reacts with fibrohistiocytic and some epithelial neoplasms; its reactivity compared with that of HMB 45 in malignant melanoma (MM) and neural tumors needs further elucidation. Using a streptavidin-biotin-immunoperoxidase procedure, we examined the reactivity of 65 MM (46 conventional, 1 polypoid, 6 desmoplastic [DMM], and 12 metastatic), 21 neurofibromas, 1 neurofibrosarcoma, 10 schwannomas, 1 perineurioma, 2 neurothekeomas, and 14 blue and 26 other nevi for CD-68, HMB-45-defined antigen, S 100 and neurofilament protein. A positive staining for CD 68 was observed in 38 of 42 primary, 5 of 6 DMM, and 11 of 12 metastatic melanomas; 6 of 10 schwannomas; 5 of 10 nevi with junctional component and all 14 blue nevi. All 21 neurofibromas, 1 each neurofibrosarcoma and perineurioma, both neurothekeomas, and all 12 nevi with dermal component were CD 68-negative. HBM 45 was expressed by all 44 primary, none of 6 DMM, and 7 of 12 metastatic melanomas; by none of 10 schwannomas, 6 neurofibromas, 1 neurofibrosarcoma, 1 perineurioma and 2 neurothekeomas. Both junctional nevi, 8 of 10 nevi with junctional components, 1 of 10 dermal components of junctional nevi, and 11 of 13 blue nevi were also HMB 45 positive. Except for 1 perineurioma, S 100 decorated all tumors examined. NF was immunoreactive in 1 of 45 conventional melanomas, 2 of 21 neurofibromas, 2 of 10 schwannomas, and 3 of 10 blue nevi; it was non-reactive in all polypoid, desmoplastic and metastatic melanomas; neurofibrosarcoma, perineurioma, neurothekeoma and other nevi. We conclude that the CD-68-reactivity in primary melanomas, neurofibromas, neurofibrosarcomas, perineuriomas, and nevi was similar to that of HMB 45. The significantly higher CD 68-positivity than of HMB 45 in metastatic and desmoplastic melanomas and schwannomas may be of diagnostic value.     

A Novel DUF569 Gene Is a Positive Regulator of the Drought Stress Response in Arabidopsis

In the last two decades, global environmental change has increased abiotic stress on plants and severely affected crops. For example, drought stress is a serious abiotic stress that rapidly and substantially alters the morphological, physiological, and molecular responses of plants. In Arabidopsis, several drought-responsive genes have been identified; however, the underlying molecular mechanism of drought tolerance in plants remains largely unclear. Here, we report that the “domain of unknown function” novel gene DUF569 (AT1G69890) positively regulates drought stress in Arabidopsis. The Arabidopsis loss-of-function mutant atduf569 showed significant sensitivity to drought stress, i.e., severe wilting at the rosette-leaf stage after water was withheld for 3 days. Importantly, the mutant plant did not recover after rewatering, unlike wild-type (WT) plants. In addition, atduf569 plants showed significantly lower abscisic acid accumulation under optimal and drought-stress conditions, as well as significantly higher electrolyte leakage when compared with WT Col-0 plants. Spectrophotometric analyses also indicated a significantly lower accumulation of polyphenols, flavonoids, carotenoids, and chlorophylls in atduf569 mutant plants. Overall, our results suggest that novel DUF569 is a positive regulator of the response to drought in Arabidopsis.     

Modeling and solving mixed-model assembly line balancing problem with setups. Part I: A mixed integer linear programming model

This paper is the first one of the two papers entitled “modeling and solving mixed-model assembly line balancing problem with setups”, which has the aim of developing the mathematical programming formulation of the problem and solving it with a hybrid meta-heuristic approach. In this current part, a mixed-integer linear mathematical programming (MILP) model for mixed-model assembly line balancing problem with setups is developed. The proposed MILP model considers some particular features of the real world problems such as parallel workstations, zoning constraints, and sequence dependent setup times between tasks, which is an actual framework in assembly line balancing problems. The main endeavor of Part-I is to formulate the sequence dependent setup times between tasks in type-I mixed-model assembly line balancing problem. The proposed model considers the setups between the tasks of the same model and the setups because of the model switches in any workstation. The capability of our MILP is tested through a set of computational experiments. Part-II tackles the problem with a multiple colony hybrid bees algorithm. A set of computational experiments is also carried out for the proposed approach in Part-II.     

Studies of distributed parameter systems: Decoupling the state-parameter estimation problem

The problem of state-parameter estimation is considered in terms of decoupling the estimation procedure. First, the theoretical preliminaries necessary for the mathematical statement of the problem are defined. Then using the extended Kalman filter (EKF) approach, the state and parameter are estimated by applying the solution techniques to a distributed parameter system. Next, the state estimation problem is decoupled from the parameter estimation problem and by using a numerical example, the advantage of this decoupling procedure is demonstrated. The numerical results show that convergence can be improved when this decoupling procedure is employed. The effect of the location of the measurements on the estimation problem is also analysed in this work. The results show that the convergence of the problem depends on the location as well as the number of measurements.     

Antibody purification by concanavalin A affinity chromatography

Concanavalin A (Con A) immobilized poly(2‐hydroxyethyl methacrylate) (PHEMA) beads in a spherical form (100–150 μm in diameter) were used for the affinity chromatography purification of human immunoglobulin G (IgG) from aqueous solutions and human plasma. PHEMA adsorbents were prepared by suspension polymerization. Bioligand Con A was then immobilized by covalent binding onto PHEMA beads. The maximum IgG adsorption on the PHEMA/Con A beads was observed at pH 6.0. The nonspecific IgG adsorption onto the plain PHEMA adsorbents was very low (ca. 0.17 mg/g). Higher adsorption values (up to 54.3 mg/g) were obtained when the PHEMA/Con A beads were used from aqueous solutions. A higher adsorption capacity was observed for human plasma (up to 69.4 mg/g) with a purity of 82.5%. The adsorption capacities of other blood proteins were 2.0 mg/g for fibrinogen and 4.2 mg/g for albumin. The total protein adsorption was determined to be 76.0 mg/g. IgG molecules could be repeatedly adsorbed and desorbed with the PHEMA/Con A beads without noticeable loss in the IgG adsorption capacity. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 97: 1202–1208, 2005     

Copy move forgery detection using DCT,PatchMatch and cellular automata

Multimedia Tools and Applications - Copy-move image forgery is a type of digital image forgery where content is copied and pasted within the same image, either by hiding foreground objects within...     

Toward an efficient and scalable feature selection approach for internet traffic classification

There is significant interest in the network management and industrial security community about the need to identify the “best” and most relevant features for network traffic in order to properly characterize user behaviour and predict future traffic. The ability to eliminate redundant features is an important Machine Learning (ML) task because it helps to identify the best features in order to improve the classification accuracy as well as to reduce the computational complexity related to the construction of the classifier. In practice, feature selection (FS) techniques can be used as a preprocessing step to eliminate irrelevant features and as a knowledge discovery tool to reveal the “best” features in many soft computing applications. In this paper, we investigate the advantages and disadvantages of such FS techniques with new proposed metrics (namely goodness, stability and similarity). We continue our efforts toward developing an integrated FS technique that is built on the key strengths of existing FS techniques. A novel way is proposed to identify efficiently and accurately the “best” features by first combining the results of some well-known FS techniques to find consistent features, and then use the proposed concept of support to select a smallest set of features and cover data optimality. The empirical study over ten high-dimensional network traffic data sets demonstrates significant gain in accuracy and improved run-time performance of a classifier compared to individual results produced by some well-known FS techniques.