Integrating simulated annealing and delta technique for constructing optimal prediction intervals

This paper aims at developing a new criterion for quantitative assessment of prediction intervals. The proposed criterion is developed based on both key measures related to quality of prediction intervals: length and coverage probability. This criterion is applied as a cost function for optimizing prediction intervals constructed using delta technique for neural network model. Optimization seeks out to minimize length of prediction intervals without compromising their coverage probability. Simulated Annealing method is employed for readjusting neural network parameters for minimization of the new cost function. To further ameliorate search efficiency of the optimization method, parameters of the network trained using weight decay method are considered as the initial set in Simulated Annealing algorithm. Implementation of the proposed method for a real world case study shows length and coverage probability of constructed prediction intervals are better than those constructed using traditional techniques.

Partial least squares and principal components analysis of wine vintage by high performance liquid chromatography with chemiluminescence detection

HPLC with acidic potassium permanganate chemiluminescence detection was employed to analyse 17 Cabernet Sauvignon wines across a range of vintages (1971–2003). Partial least squares regression analysis and principal components analysis was used in order to investigate the relationship between wine composition and vintage. Tartaric acid, vanillic acid, catechin, sinapic acid, ethyl gallate, myricetin, procyanadin B and resveratrol were found to be important components in terms of differences between the vintages.

Partial exfoliation of layered double hydroxides in DMSO : a route to transparent polymer nanocomposites

Layered double hydroxides (LDHs), either having nitrate counter anions or intercalated with organic molecules, have been for the first time partially exfoliated in dimethyl sulfoxide (DMSO) to form a transparent suspension. Atomic force microscopy (AFM) images showed that both the lateral size and the thickness of the LDH nanoplatelets were decreased after the exfoliation. The organic-LDHs maintained their intercalation characteristics, i.e. the thermal stability improvement of the incorporated organic anions, after the exfoliation in DMSO. Transparent ethylene-vinyl alcohol copolymer (EVOH) nanocomposite films containing partially exfoliated LDHs intercalated with UV absorbers were prepared using DMSO as the processing solvent. As the first reported example of a highly transparent LDH/polymer composite, the obtained composite film had a visible light transmittance of 90% (comparable to that of the pure matrix), was flexible and exhibited an excellent UV-shielding capability and thermal stability.

Synthesis of boron nitride nanotubes by boron ink annealing

Ball-milling and annealing is one effective method for the mass production of boron nitride nanotubes (BNNTs). We report that the method has been modified to a boron (B) ink annealing method. In this new process, the nanosize ball-milled B particles are mixed with metal nitrate in ethanol to form an ink-like solution, and then the ink is annealed in nitrogen-containing gas to form nanotubes. The new method greatly enhances the yield of BNNTs, giving a higher density of nanotubes. These improvements are caused by the addition of metal nitrate and ethanol, both of which can strongly boost the nitriding reaction, as revealed by thermogravimetric analysis. The size and structure of BNNTs can be controlled by varying the annealing conditions. This high-yield production of BNNTs in large quantities enables the large-scale application of BNNTs.

Pareto archived simulated annealing for single machine job shop scheduling with multiple objectives

In this paper, the single machine job shop scheduling problem is studied with the objectives of minimizing the tardiness and the material cost of jobs. The simultaneous consideration of these objectives is the multi-criteria optimization problem under study. A metaheuristic procedure based on simulated annealing is proposed to find the approximate Pareto optimal (non-dominated) solutions. The two objectives are combined in one composite utility function based on the decision maker’s interest in having a schedule with weighted combination. In view of the unknown nature of the weights for the defined objectives, a priori approach is applied to search for the non-dominated set of solutions based on the Pareto dominance. The obtained solutions set is presented to the decision maker to choose the best solution according to his preferences. The performance of the algorithm is evaluated in terms of the number of non-dominated schedules generated and the proximity of the obtained non-dominated front to the true Pareto front. Results show that the produced solutions do not differ significantly from the optimal solutions.

Microstructure evolution and softening processes occurring during annealing of hot deformed Ni-30Fe austenite

The current work investigates the microstructure evolution and softening processes that take place during annealing of an austenitic Ni-30Fe model alloy subjected to hot deformation in the dynamic recrystallization (DRX) regime. The substructure of the deformed matrix grains largely comprised organized microband arrays, though that of the DRX grains consisted of more random, complex subgrain/cell arrangements. This substructure disparity was also reflected by the distinct difference in the mechanism of post-deformation softening taking place during annealing of the deformed matrix and DRX grains. In the former, the recrystallization process took place through nucleation and growth of new grains fully replacing the deformed structure, as expected for the classical static recrystallization (SRX). The corresponding texture was essentially random, in contrast to that of the DRX grains dominated by low Taylor factor components. The microbands originally present within the deformed matrix grains displayed some tendency to disintegrate during annealing, nonetheless, they remained largely preserved even at prolonged holding times. During annealing of the fully DRX microstructure, a novel softening mechanism was revealed. The initial post-dynamic softening stage involved rapid growth of the dynamically formed nuclei and migration of the mobile boundaries in correspondence with the well-established metadynamic recrystallization (MDRX) mechanism. However, in contrast to the deformed matrix, SRX was not observed and the sub-boundaries within DRX grains rapidly disintegrated through dislocation climb and dislocation annihilation, which led to the formation of dislocation-free grains already at short holding times. Consequently, the DRX texture initially became slightly weakened and then remained largely preserved throughout the annealing process.

Morphology evolution during annealing and electrical conductivity of titania nanotube films

Titania nanotube films were produced by anodization of titanium foil. The titania nanotube films were annealed at different temperatures. Morphology evolution, phase transformation and electrical conductivity of the titania nanotubes were studied. Results showed that the nanotube walls became rough, porous and even collapsed after annealed at 400, 500 and 600°C respectively. Titania anatase phase formed after annealed at 400°C; the amount of anatase phase increased as the annealing temperature increased. The conductivity of the nanotube film annealed at 400°C was improved greatly compared with the conductivity of the as-anodized nanotube film. However, the conductivity of the nanotube films annealed at higher temperatures decreased. The effect of the morphology on the electronic conductivity of the titania nanotube films was discussed.

Texture evolution and softening processes in an austenitic Ni-30Fe alloy subjected to hot deformation and subsequent annealing

The current work has investigated the texture development in an austenitic Ni-30Fe model alloy during deformation within the dynamic recrystallization (DRX) regime and after post-deformation annealing. Both the deformed matrix and DRX texture displayed the expected FCC shear components, the latter being dominated by the low Taylor factor grains, which was presumably caused by their lower consumption rate during DRX. The deformed matrix grains were largely characterized by organized, microband structures, while the DRX grains showed more random, complex subgrains/cell arrangements. The latter substructure type proved to be significantly less stable during post-deformation annealing. The recrystallization of the deformed matrix occurred through nucleation and growth of new grains fully replacing the deformed structure, as expected for the classical static recrystallization (SRX). Unlike the DRX grains, the SRX texture was essentially random. By contrast, a novel softening mechanism was revealed during annealing of the fully DRX microstructure. The initial post-dynamic softening stage involved rapid growth of the dynamically formed nuclei and migration of the mobile boundaries in line with the well-established metadynamic recrystallization (MDRX) mechanism, which weakened the starting DRX texture. However, in parallel, the sub-boundaries within the deformed DRX grains progressively disintegrated through dislocation climb and dislocation annihilation, which ultimately led to the formation of dislocation-free grains. Consequently, the weakened DRX texture largely remained preserved throughout the annealing process.

Observation-switching linear dynamic systems for tracking humans through unexpected partial occlusions by scene objects

This paper focuses on the problem of tracking people through occlusions by scene objects. Rather than relying on models of the scene to predict when occlusions will occur as other researchers have done, this paper proposes a linear dynamic system that switches between two alternatives of the position measurement in order to handle occlusions as they occur. The filter automatically switches between a foot-based measure of position (assuming z = Q) to a head-based position measure (given the person's height) when an occlusion of the person's lower body occurs. No knowledge of the scene or its occluding objects is used. Unlike similar research [2, 14], the approach does not assume a fixed height for people and so is able to track humans through occlusions even when they change height during the occlusion. The approach is evaluated on three furnished scenes containing tables, chairs, desks and partitions. Occlusions range from occlusions of legs, occlusions whilst being seated and near-total occlusions where only the person's head is visible. Results show that the approach provides a significant reduction in false-positive tracks in a multi-camera environment, and more than halves the number of lost tracks in single monocular camera views.

Partial state and unknown input estimation for time-delay systems

This article considers the problem of estimating a partial set of the state vector and/or unknown input vector of linear systems driven by unknown inputs and time-varying delay in the state variables. Three types of reduced-order observers, namely, observers with delays, observers without internal delays and delay-free observers are proposed in this article. Existence conditions and design procedures are presented for the determination of parameters for each case of observers. Numerical examples are presented to illustrate the design procedures.

Hedgehog partial agonism drives warburg-lie metabolism in muscle and brown fat

Diabetes, obesity, and cancer affect upward of 15% of the world’s population. Interestingly, all three diseases juxtapose dysregulated intracellular signaling with altered metabolic state. Exactly which genetic factors define stable metabolic set points in vivo remains poorly understood. Here, we show that hedgehog signaling rewires cellular metabolism. We identify a cilium-dependent Smo-Ca2+-Ampk axis that triggers rapid Warburg-like metabolic reprogramming within minutes of activation and is required for proper metabolic selectivity and flexibility. We show that Smo modulators can uncouple the Smo-Ampk axis from canonical signaling and identify cyclopamine as one of a new class of “selective partial agonists,” capable of concomitant inhibition of canonical and activation of noncanonical hedgehog signaling. Intriguingly, activation of the Smo-Ampk axis in vivo drives robust insulin-independent glucose uptake in muscle and brown adipose tissue. These data identify multiple noncanonical endpoints that are pivotal for rational design of hedgehog modulators and provide a new therapeutic avenue for obesity and diabetes.