Numerical simulation of roughness effects on flow and heat transfer in microchannels at slip flow regime

A numerical simulation for studying fluid flow and heat transfer characteristics in microchannels at slip flow regime with consideration of slip and temperature jump is studied. The wall roughness is simulated in two cases with periodically distributed triangular microelements and random shaped micro peaks distributed on the wall surfaces. Various Knudsen numbers have used to investigate the effects of rarefaction. The numerical results have also checked with available theoretical and experimental relations and good agreements has achieved. It has been found that rarefaction has more significant effect on flow field in microchannels with higher relative roughness. The negative influence of roughness on fluid flow and heat transfer found to be the friction factor increment and Nusselt number reduction. In addition high influence of roughness distribution and shape has been shown by a comparison of Poiseuille and Nusselt numbers for tow different cases.     

Action of acrylonitrile on 4-cyano- and 4-carbethoxy pyridazin-3(2H)-ones and their 3-mercapto derivatives. A novel Synthesis of Pyrano and Thiinopyridazines

Reaction of acrylonitrile with 4-cyano-5,6-diphenyl pyridazin-3(2H)-one and 3(2H)-thione derivative ( 1a, b ) at elevated temperature gave 7H-5-amino-6-cyano-3,4-diphenylpyrano and thiino [2,3-c] pyridazines ( 2a, b ), respectively. However, the reaction of 4-carbethoxy pyridazine derivatives ( 1c, d ) with the same reagent, under the same conditions afforded 6H, 7H-6-cyano-3,4-diphenyl-5-oxopyrano ( 3a ) and thiino [2,3-c] pyridazine ( 3b ), respectively. In addition, treatment of ( 1a, c ) and ( 1b, d ) with acrylonitrile ar reflux in alkaline medium give the respective 3-(2′-cyanoethyloxo) ( 7a, c ) and 3-2′-cyanoethylthio ( 7b, d ) pyridazine derivatives. Prolonged alkaline hydrolysis of either ( 1a, c ) or ( 7a, c ) yielded the same product ( 8a ). Also hydrolysis of ( 1b, d ) and ( 7b, d ) afforded one and the same product ( 8b ). The structures of the products were assigned on the basis of satisfactory analytical and spectroscopic data.     

The influence of the depth of substrate dentin surface and thickness of the current restorative samples on bond strength

The effect of sample thickness and dentin depth on bond strength of composite, compomer and resin modified glass ionomer have been investigated. The occlusal surfaces of 84 non carious human third molars were used for bonding. 4 subgroups were tested, superficial dentin with sample thickness 1 and 2 mm and deep dentin with sample thickness 1 and 2 mm respectively SBMP + /Z 100 composite showed 26 +/- 3.2, 22.3 +/- 4.5, 17 +/- 3.2 and 21.8 +/- 4.2 MPa shear bond strength to S. dentin 1 mm, deep dentin 1 and 2 mm and S. dentin 2 mm respectively. Compoglass reported 10.4 +/- 1.57, 9.1 +/- 2.3, 5.0 +/- 0.6 and 9.24 +/- 3.1 MPa while, Vitremer achieved 4.7 +/- 0.49, 3.2 +/- 0.39, 3.0 +/- 0.81 and 3.2 +/- 0.53 MPa. It is concluded that the highest bond strength can be achieved to superficial dentin in thickness or increments not more than 1 mm. And that both dentin depth and sample thickness might influence the quality of the bond to dentin with an effect that varies from one material to another depending upon the mechanism of bond of each material and its chemical composition.     

Optimal pulse shape design for digital communication systems byprojections onto convex sets

Recent developments in DSP hardware has made it possible to use almost any pulse shape for digital data transmission. This resulted in a search for algorithms capable of constructing pulse shapes matching to the properties of a given channel. The projection onto convex sets technique is suitable for the solution of this problem particularly because of its flexibility in modeling a variety of constraints. The use of the technique for the optimal pulse shape design problem is demonstrated through a detailed example from power line communications     

A Comparison of Electric‐Field‐Driven and Pressure‐Driven Fiber Generation Methods for Drug Delivery

Polymeric fibers are prepared by using electric field driven fiber production technology—electrospinning and pressure driven fiber production technology—pressurized gyration. Fibers of four different polymers: polyvinylidene fluoride (PVDF), poly(methyl methacrylate (PMMA), poly(N‐isopropylacrylamide), and polyvinylpyridine (PVP), are spun by both techniques and differences are analyzed for their suitability as drug carriers. The diameters of electrospun fibers are larger in some cases (PVDF and PMMA), producing fibers with lower surface area. Pressurized gyration allows for a higher rate of fiber production. Additionally, drug‐loaded PVP fibers are prepared by using two poorly water‐soluble drugs (Amphotericin B and Itraconazole). In vitro dissolution studies show differences in release rate between the two types of fibers. Drug‐loaded gyrospun fibers release the drugs faster within 15 min compared to the drug‐loaded electrospun fibers. The findings suggest pressurized gyration is a promising and scalable approach to rapid fiber production for drug delivery when compared to electrospinning.     

Implementing regularly structured neural networks on the DREAMmachine

High-throughput implementations of neural network models are required to transfer the technology from small prototype research problems into large-scale "real-world" applications. The flexibility of these implementations in accommodating for modifications to the neural network computation and structure is of paramount importance. The performance of many implementation methods today is greatly dependent on the density and the interconnection structure of the neural network model being implemented. A principal contribution of this paper is to demonstrate an implementation method which exploits maximum amount of parallelism from neural computation, without enforcing stringent conditions on the neural network interconnection structure, to achieve this high implementation efficiency. We propose a new reconfigurable parallel processing architecture, the Dynamically Reconfigurable Extended Array Multiprocessor (DREAM) machine, and an associated mapping method for implementing neural networks with regular interconnection structures. Details of the system execution rate calculation as a function of the neural network structure are presented. Several example neural network structures are used to demonstrate the efficiency of our mapping method and the DREAM machine architecture on implementing diverse interconnection structures. We show that due to the reconfigurable nature of the DREAM machine, most of the available parallelism of neural networks can be efficiently exploited.     

Effect of Co-channel Interference on Two-Way Untrustworthy Relay Selection

Wireless Personal Communications - In wireless sensor networks (WSNs), traffic flow congestion can reduce network performance. We propose a congestion control method for WSNs that use a cache state...     

Simultaneous optimization of repair and control-limit policy in condition-based maintenance

In condition-based maintenance (CBM) planning, collected information from system condition monitoring is the basis of making decision about conducting the maintenance and repair activities. Recently, ample number of studies has been conducted in CBM field especially, in control-limit policy. In control-limit policy, using proportional Hazards model and results of monitoring system condition, one can estimate hazard rate function and its condition’s transition probability matrix. Then, considering replacement costs, optimal control-limit can be determined minimizing the average cost in the long run. The presented model considers repair policy and their implementation cost, and the assumptions of repair during interval inspection is ignored. Then, a model is presented to determine the optimal control-limit and the best repair policy, in which the average total cost per unit time in the long-run, is minimized. At the end, a numerical example is illustrated.