The femoral sulcus angle in neonatal cadavers: a macroscopical and ultrasonographical study

A modification in the design of the pedicled latissimus dorsi musculocutaneous flap is described that aims to minimize the cosmetic morbidity of its donor site. The implications of this variation are discussed with particular reference to use of the flap in postmastectomy reconstruction.     

The effects of maturation on early and late phases of phrenic neurogram during eupnea

In this paper, we investigate the effects of maturation on the early and late phases of the phrenic neurogram. We have used the matching pursuit (MP) method to examine the effects of maturation on breathing patterns in both time and frequency domains. The MP was chosen since the wavelet transform method may not represent signals whose Fourier transforms have a narrow high-frequency support. The phrenic neurogram was recorded from 25 piglets (3-35 days) during eupnea (normal breathing) at three postnatal age groups: young (3-7 days (n = 9)), (middle) 10-21 days (n = 6), and old (29-35 days (n = 10)). The energy percentage of atoms representing the nonperiodic neural activities (NPNAs) significantly decreased from young age to middle age groups (p<0.01) and from young age to old age groups (p<0.01), and from middle age to old age groups (p<0.055) in the early phase (the first half) of the phrenic neurogram, but these changes were not statistically significant in the late phase (the second half) of the phrenic neurogram as maturation proceeded. However, the energy percentage of atoms representing the periodic neural activities (PNAs) decreased with maturation, but these changes were not statistically significant in the early phase of the phrenic neurogram. The energy percentage of (PNAs) increased in the late phase of the phrenic neurogram as maturation proceeded although these changes were only significant between young and old age groups (p<0.01). These results suggest that the significant decrease of the NPNAs in the early phase and the increase in the late phase of the phrenic neurogram could be a sign of maturation in piglets.     

Investigation of microstructure and wear behaviors of al matrix composites reinforced by carbon nanotube

In this study, the effect of CNT amount in Al-CNT composites produced by adding carbon nanotube (CNT) to 7075 Al alloy in various amounts on microstructure and wear behaviors of aluminum matrix composites was investigated. CNT was added to 7075 Al alloy powder at five different amounts. The powders were mechanically milled for 2 hours. Mechanical milled powders were cold pressed and then pre-shaped by hot pressing. Pre-shaped samples were sintered for 1 hour under 10^?6 millibar in 580°C. Microstructure examinations, hardness measurements, and wear tests were carried out. The results show that CNT's in the microstructure were agglomerated as nanotube amount increases and there was no uniform distribution. The highest hardness value was obtained in AMC reinforced with 1% CNT while it is seen that hardness of the composite decreases and weight loss increases as CNT amount increases.     

Dexterous workspace optimization of an asymmetric six-degree of freedom Stewart–Gough platform type manipulator

In this paper, an asymmetric Generalized Stewart–Gough Platform (GSP) type parallel manipulator is designed by considering the type synthesis approach. The asymmetric six-Degree Of Freedom (DOF) manipulator optimized in this paper is selected among the GSPs classified under the name of 6D. The dexterous workspace optimization of Asymmetric parallel Manipulator with tEn Different Linear Actuator Lengths (AMEDLAL) subject to kinematics and geometric constraints is performed by using the Particle Swarm Optimization (PSO). The condition number and Minimum Singular Value (MSV) of homogenized Jacobian matrix are employed to obtain the dexterous workspace of AMEDLAL. Finally, the six-DOF AMEDLAL is also compared with the optimized Traditional Stewart–Gough Platform Manipulator (TSPM) considering the volume of the dexterous workspace in order to demonstrate its kinematic performance. Comparisons show that the manipulator proposed in this study illustrates better kinematic performance than TSPM.     

Optimizing decomposition of software architecture for local recovery

The increasing size and complexity of software systems has led to an amplified number of potential failures and as such makes it harder to ensure software reliability. Since it is usually hard to prevent all the failures, fault tolerance techniques have become more important. An essential element of fault tolerance is the recovery from failures. Local recovery is an effective approach whereby only the erroneous parts of the system are recovered while the other parts remain available. For achieving local recovery, the architecture needs to be decomposed into separate units that can be recovered in isolation. Usually, there are many different alternative ways to decompose the system into recoverable units. It appears that each of these decomposition alternatives performs differently with respect to availability and performance metrics. We propose a systematic approach dedicated to optimizing the decomposition of software architecture for local recovery. The approach provides systematic guidelines to depict the design space of the possible decomposition alternatives, to reduce the design space with respect to domain and stakeholder constraints and to balance the feasible alternatives with respect to availability and performance. The approach is supported by an integrated set of tools and illustrated for the open-source MPlayer software.     

Hermite matrix in Lagrange basis for scaling static output feedback polynomial matrix inequalities

Using Hermite's formulation of polynomial stability conditions, static output feedback (SOF) controller design can be formulated as a polynomial matrix inequality (PMI), a (generally nonconvex) nonlinear semidefinite programming problem that can be solved (locally) with PENNON, an implementation of a penalty and augmented Lagrangian method. Typically, Hermite SOF PMI problems are badly scaled and experiments reveal that this has a negative impact on the overall performance of the solver. In this note we recall the algebraic interpretation of Hermite's quadratic form as a particular Bézoutian and we use results on polynomial interpolation to express the Hermite PMI in a Lagrange polynomial basis, as an alternative to the conventional power basis. Numerical experiments on benchmark problem instances show the improvement brought by the approach, in terms of problem scaling, number of iterations and convergence behaviour of PENNON.     

Computation of approximate optimal policies in a partially observed inventory model with rain checks

This paper proposes a new methodology to solve partially observed inventory problems. Generally, these problems have infinite-dimensional states that are conditional distributions of the inventory level. Our methodology involves linearizing the state transitions via unnormalized probabilities. It then uses an appropriate functional basis to represent the state. Considering the speed and stability of computations, we choose truncated Chebyshev polynomials as the basis. We use Fast Fourier Transforms along with an appropriate discretization of inventory levels to speed up the computations. These main ideas are blended to obtain an iterative algorithm to solve a partially observed inventory model with rain checks. In this model, the inventory manager (IM) does not know the inventory level when it is positive. Otherwise, the IM fully observes it. This model provides a context to illustrate our methodology, which applies to other such models. Although this model has been studied mathematically in the literature, the use of our algorithm provides a numerical approximation of the optimal order quantities. These are compared to the orders released under a base mean-stock policy, where the IM replaces the unobserved inventory level with its mean and applies the well-known base stock policy. We show numerically that the optimal order quantity is very close to the base mean-stock order quantity, when the variance of the inventory distribution is small. When the mean of the inventory distribution is large, the optimal order quantity is more than the base mean-stock quantity, and it is the other way around when the mean is small or negative. These insights are explained via uncertainty and information effects and their interplay. We expect this interplay to show up in other partially observed inventory models.     

Synthesis and characterization of poly(N-(2-(thiophen-3-yl)methylcarbonyloxyethyl)maleimide) and its spectroelectrochemical properties

A new monomer; N-(2-(thiophen-3-yl)methylcarbonyloxyethyl) maleimide (NMT) was synthesized. The chemical structure of the monomer was characterized by Nuclear Magnetic Resonance (¹H-NMR) and Fourier Transform Infrared (FTIR) Spectroscopy. Electrochemical polymerization of NMT was performed in acetonitrile (AN)/borontrifloride ethylether (BFEE) solvent mixture (1:1, v/v) where tetrabutylammonium tetrafluoroborate (TBAFB) was utilized as the supporting electrolyte. The resulting conducting polymer was characterized by Fourier Transform Infrared (FTIR) Spectroscopy, thermal analyses and Scanning Electron Microscopy (SEM). Electrical conductivity was measured by the four-probe technique. The spectroelectrochemical behavior and switching ability of P(NMT) film were investigated by UV–Vis spectrophotometry. P(NMT) revealed color changes between yellow and blue in the reduced and oxidized states respectively.     

Optimization of Multireservoir Systems by Genetic Algorithm

Application of optimization techniques for determining the optimal operating policy of reservoirs is a major issue in water resources planning and management. As an optimization Genetic Algorithm, ruled by evolution techniques, have become popular in diversified fields of science. The main aim of this study is to explore the efficiency and effectiveness of genetic algorithm in optimization of multi-reservoirs. A computer code has been constructed for this purpose and verified by means of a reference problem with a known global optimum. Three reservoirs in the Colorado River Storage Project were optimized for maximization of energy production. Besides, a real-time approach utilizing a blend of online and a posteriori data was proposed. The results obtained were compared to the real operational data and genetic algorithm was found to be effective and can be utilized as an alternative technique to other traditional optimization techniques.     

Effect of injection timing on the exhaust emissions of a diesel engine using diesel–methanol blends

Environmental concerns and limited resource of petroleum fuels have caused interests in the development of alternative fuels for internal combustion (IC) engines. For diesel engines, alcohols are receiving increasing attention because they are oxygenated and renewable fuels. Therefore, in this study, the effect of injection timing on the exhaust emissions of a single cylinder, naturally aspirated, four-stroke, direct injection diesel engine has been experimentally investigated by using methanol-blended diesel fuel from 0% to 15% with an increment of 5%. The tests were conducted for three different injection timings (15°, 20° and 25 °CA BTDC) at four different engine loads (5 Nm, 10 Nm, 15 Nm, 20 Nm) at 2200 rpm. The experimental test results showed that Bsfc, NO_x and CO₂ emissions increased as BTE, smoke opacity, CO and UHC emissions decreased with increasing amount of methanol in the fuel mixture. When compared the results to those of original injection timing, NO_x and CO₂ emissions decreased, smoke opacity, UHC and CO emissions increased for the retarded injection timing (15 °CA BTDC). On the other hand, with the advanced injection timing (25 °CA BTDC), decreasing smoke opacity, UHC and CO emissions diminished, and NO_x and CO₂ emissions boosted at all test conditions. In terms of Bsfc and BTE, retarded and advanced injection timings gave negative results for all fuel blends in all engine loads.