Replication-based inference algorithms for hard computational problems

Inference algorithms based on evolving interactions between replicated solutions are introduced and analyzed on a prototypical NP-hard problem: the capacity of the binary Ising perceptron. The efficiency of the algorithm is examined numerically against that of the parallel tempering algorithm, showing improved performance in terms of the results obtained, computing requirements and simplicity of implementation. © 2013 American Physical Society.

Evaluation efficiency of large-scale data set with negative data:an artificial neural network approach

Data envelopment analysis (DEA) is the most widely used methods for measuring the efficiency and productivity of decision-making units (DMUs). The need for huge computer resources in terms of memory and CPU time in DEA is inevitable for a large-scale data set, especially with negative measures. In recent years, wide ranges of studies have been conducted in the area of artificial neural network and DEA combined methods. In this study, a supervised feed-forward neural network is proposed to evaluate the efficiency and productivity of large-scale data sets with negative values in contrast to the corresponding DEA method. Results indicate that the proposed network has some computational advantages over the corresponding DEA models; therefore, it can be considered as a useful tool for measuring the efficiency of DMUs with (large-scale) negative data.

Global efficiency of innovative rotational mold directly heated by thermal fluid

The article is focused on analysis of global efficiency of new mold for rotational molding of plastic parts, being directly heated by thermal fluid. The overall efficiency is based on several items such as reduction of cycle time, better uniformity of heating-cooling and low energy consumption. The new tool takes advantage of additive fabrication and electroforming for making the optimal manifold and cavity shell of the mold. Experimental test of a prototype mold was carried out on an experimental rotational molding machine, developed for this purpose, measuring wall temperature, and internal air temperature, with and without plastic material inside. Results were compared with conventional mold heated into an oven and to theoretical simulations done by Computational Fluid Dynamic software (CFD). The analysis represents considerable improvement of cycle time related to conventional methods (heated by oven) and better thermal uniformity to conventional procedures by direct heating of oil with external channels. In addition to thermal analysis an energetic efficiency study was done. POLYM. ENG. SCI., 52:1998-2005, 2012. © 2012 Society of Plastics Engineers Copyright © 2012 Society of Plastics Engineers.

A generic strategy for dynamic load balancing of distributed memory parallel computational mechanics using unstructured meshes

A large class of computational problems are characterised by frequent synchronisation, and computational requirements which change as a function of time. When such a problem is solved on a message passing multiprocessor machine [5], the combination of these characteristics leads to system performance which deteriorate in time. As the communication performance of parallel hardware steadily improves so load balance becomes a dominant factor in obtaining high parallel efficiency. Performance can be improved with periodic redistribution of computational load; however, redistribution can sometimes be very costly. We study the issue of deciding when to invoke a global load re-balancing mechanism. Such a decision policy must actively weigh the costs of remapping against the performance benefits, and should be general enough to apply automatically to a wide range of computations. This paper discusses a generic strategy for Dynamic Load Balancing (DLB) in unstructured mesh computational mechanics applications. The strategy is intended to handle varying levels of load changes throughout the run. The major issues involved in a generic dynamic load balancing scheme will be investigated together with techniques to automate the implementation of a dynamic load balancing mechanism within the Computer Aided Parallelisation Tools (CAPTools) environment, which is a semi-automatic tool for parallelisation of mesh based FORTRAN codes.

Dynamic load balancing of distributed memory parallel computational mechanics using unstructured meshes for multi-physical modelling

As the complexity of parallel applications increase, the performance limitations resulting from computational load imbalance become dominant. Mapping the problem space to the processors in a parallel machine in a manner that balances the workload of each processors will typically reduce the run-time. In many cases the computation time required for a given calculation cannot be predetermined even at run-time and so static partition of the problem returns poor performance. For problems in which the computational load across the discretisation is dynamic and inhomogeneous, for example multi-physics problems involving fluid and solid mechanics with phase changes, the workload for a static subdomain will change over the course of a computation and cannot be estimated beforehand. For such applications the mapping of loads to process is required to change dynamically, at run-time in order to maintain reasonable efficiency. The issue of dynamic load balancing are examined in the context of PHYSICA, a three dimensional unstructured mesh multi-physics continuum mechanics computational modelling code.

Computational modelling of non-equilibrium condensing steam flows in low-pressure steam turbines

The steam turbines play a significant role in global power generation. Especially, research on low pressure (LP) steam turbine stages is of special importance for steam turbine man- ufactures, vendors, power plant owners and the scientific community due to their lower efficiency than the high pressure steam turbine stages. Because of condensation, the last stages of LP turbine experience irreversible thermodynamic losses, aerodynamic losses and erosion in turbine blades. Additionally, an LP steam turbine requires maintenance due to moisture generation, and therefore, it is also affecting on the turbine reliability. Therefore, the design of energy efficient LP steam turbines requires a comprehensive analysis of condensation phenomena and corresponding losses occurring in the steam tur- bine either by experiments or with numerical simulations. The aim of the present work is to apply computational fluid dynamics (CFD) to enhance the existing knowledge and understanding of condensing steam flows and loss mechanisms that occur due to the irre- versible heat and mass transfer during the condensation process in an LP steam turbine. Throughout this work, two commercial CFD codes were used to model non-equilibrium condensing steam flows. The Eulerian-Eulerian approach was utilised in which the mix- ture of vapour and liquid phases was solved by Reynolds-averaged Navier-Stokes equa- tions. The nucleation process was modelled with the classical nucleation theory, and two different droplet growth models were used to predict the droplet growth rate. The flow turbulence was solved by employing the standard k-ε and the shear stress transport k-ω turbulence models. Further, both models were modified and implemented in the CFD codes. The thermodynamic properties of vapour and liquid phases were evaluated with real gas models. In this thesis, various topics, namely the influence of real gas properties, turbulence mod- elling, unsteadiness and the blade trailing edge shape on wet-steam flows, are studied with different convergent-divergent nozzles, turbine stator cascade and 3D turbine stator-rotor stage. The simulated results of this study were evaluated and discussed together with the available experimental data in the literature. The grid independence study revealed that an adequate grid size is required to capture correct trends of condensation phenomena in LP turbine flows. The study shows that accurate real gas properties are important for the precise modelling of non-equilibrium condensing steam flows. The turbulence modelling revealed that the flow expansion and subsequently the rate of formation of liquid droplet nuclei and its growth process were affected by the turbulence modelling. The losses were rather sensitive to turbulence modelling as well. Based on the presented results, it could be observed that the correct computational prediction of wet-steam flows in the LP turbine requires the turbulence to be modelled accurately. The trailing edge shape of the LP turbine blades influenced the liquid droplet formulation, distribution and sizes, and loss generation. The study shows that the semicircular trailing edge shape predicted the smallest droplet sizes. The square trailing edge shape estimated greater losses. The analysis of steady and unsteady calculations of wet-steam flow exhibited that in unsteady simulations, the interaction of wakes in the rotor blade row affected the flow field. The flow unsteadiness influenced the nucleation and droplet growth processes due to the fluctuation in the Wilson point.

Computational characterization of carbazole-benzonitrile derivatives for applications in Organic Light Emitting Diodes

The technology of Organic Light-Emitting Diodes has reached such a high level of reliability that it can be used in various applications. The required light emission efficiency can be achieved by transforming the triplet excitons into singlet states through Reverse InterSystem Crossing (RISC), which is the main process of a general mechanism called thermally activated delayed fluorescence (TADF). In this thesis, we theoretically analyzed two carbazole-benzonitrile (donor-acceptor) derivatives, 2,5-di(9H-carbazol-9-yl)benzonitrile (p-2CzBN) and 2,3,4,5,6-penta(9H-carbazol-9-yl)benzonitrile (5CzBN), and addressed the problem of how donor-acceptor (D-A) or donor-acceptor-donor (D-A-D) flexible molecular architectures influence the nature of the excited states and the emission intensity. Furthermore, we analyzed the RISC rates as a function of the conformation of the carbazole lateral groups, considering the first electronic states, S0, S1, T1 and T2, involved in TADF process. The two prototype molecules, p-2CzBN and 5CzBN, have a similar energy gap between the first singlet and triplet states (∆EST, a key parameter in the RISC rate), but different TADF performances. Therefore, other parameters must be considered to explain their different behavior. The oscillator strength of p-2CzBN, never tested as emitter in OLEDs, is similar to that of 5CzBN, which is an active TADF molecule. We also note that the presence of a second T2 triplet state, lower in energy than S1 only in 5CzBN, and the reorganization energies, associated with RISC processes involving T1 and T2, are important factors in differentiating the rates in p-2CzBN and 5CzBN. For p-2CzBN, the RISC rate from T2 to S1 is surprisingly higher than that from T1 to S1, in disagreement with El-Sayed rules, due to a large reorganization energy associated to the T1 to S1, process; while the contrary occurs for 5CzBN. These insights are important for designing new TADF emitters based on the benzo-carbazole architecture.

Computational design of a new type of sandwich cross-section for a defined solution of a tree-like column produced by wire-and-arc additive manufacturing

When it comes to designing a structure, architects and engineers want to join forces in order to create and build the most beautiful and efficient building. From finding new shapes and forms to optimizing the stability and the resistance, there is a constant link to be made between both professions. In architecture, there has always been a particular interest in creating new shapes and types of a structure inspired by many different fields, one of them being nature itself. In engineering, the selection of optimum has always dictated the way of thinking and designing structures. This mindset led through studies to the current best practices in construction. However, both disciplines were limited by the traditional manufacturing constraints at a certain point. Over the last decades, much progress was made from a technological point of view, allowing to go beyond today's manufacturing constraints. With the emergence of Wire-and-Arc Additive Manufacturing (WAAM) combined with Algorithmic-Aided Design (AAD), architects and engineers are offered new opportunities to merge architectural beauty and structural efficiency. Both technologies allow for exploring and building unusual and complex structural shapes in addition to a reduction of costs and environmental impacts. Through this study, the author wants to make use of previously mentioned technologies and assess their potential, first to design an aesthetically appreciated tree-like column with the idea of secondly proposing a new type of standardized and optimized sandwich cross-section to the construction industry. Parametric algorithms to model the dendriform column and the new sandwich cross-section are developed and presented in detail. A catalog draft of the latter and methods to establish it are then proposed and discussed. Finally, the buckling behavior of this latter is assessed considering standard steel and WAAM material properties.

Computational Analysis Based on Parametric Models of Historic Masonry Vaulted Structures Strengthened by Fiber-Reinforced Composite Materials

Historic vaulted masonry structures often need strengthening interventions that can effectively improve their structural performance, especially during seismic events, and at the same time respect the existing setting and the modern conservation requirements. In this context, the use of innovative materials such as fiber-reinforced composite materials has been shown as an effective solution that can satisfy both aspects. This work aims to provide insight into the computational modeling of a full-scale masonry vault strengthened by fiber-reinforced composite materials and analyze the influence of the arrangement of the reinforcement on the efficiency of the intervention. At first, a parametric model of a cross vault focusing on a realistic representation of its micro-geometry is proposed. Then numerical modeling, simulating the pushover analyses, of several barrel vaults reinforced with different reinforcement configurations is performed. Finally, the results are collected and discussed in terms of force-displacement curves obtained for each proposed configuration.

Intermittent Fasting Induces Hypothalamic Modifications Resulting In Low Feeding Efficiency, Low Body Mass And Overeating.

Intermittent fasting (IF) is an often-used intervention to decrease body mass. In male Sprague-Dawley rats, 24 hour cycles of IF result in light caloric restriction, reduced body mass gain, and significant decreases in the efficiency of energy conversion. Here, we study the metabolic effects of IF in order to uncover mechanisms involved in this lower energy conversion efficiency. After 3 weeks, IF animals displayed overeating during fed periods and lower body mass, accompanied by alterations in energy-related tissue mass. The lower efficiency of energy use was not due to uncoupling of muscle mitochondria. Enhanced lipid oxidation was observed during fasting days, whereas fed days were accompanied by higher metabolic rates. Furthermore, an increased expression of orexigenic neurotransmitters AGRP and NPY in the hypothalamus of IF animals was found, even on feeding days, which could explain the overeating pattern. Together, these effects provide a mechanistic explanation for the lower efficiency of energy conversion observed. Overall, we find that IF promotes changes in hypothalamic function that explain differences in body mass and caloric intake.

Obesogenic Environment By Excess Of Dietary Fats In Different Phases Of Development Reduces Spermatic Efficiency Of Wistar Rats At Adulthood: Correlations With Metabolic Status.

This study compares the impact of obesogenic environment (OE) in six different periods of development on sperm parameters and the testicular structure of adult rats and their correlations with sex steroid and metabolic scenario. Wistar rats were exposed to OE during gestation (O1), during gestation/lactation (O2), from weaning to adulthood (O3), from lactation to adulthood (O4), from gestation to sexual maturity (O5), and after sexual maturation (O6). OE was induced by a 20% fat diet, and control groups were fed a balanced diet (4% fat). Serum leptin levels and adiposity index indicate that all groups were obese, except for O1. Three progressive levels of impaired metabolic status were observed: O1 presented insulin resistance, O2 were insulin resistant and obese, and groups O3, O4, and O5 were insulin resistant, obese, and diabetic. These three levels of metabolic damage were proportional to the increase of leptin and decreased circulating testosterone. The impairment in the daily sperm production (DSP) paralleled these three levels of metabolic and hormonal damage being marginal in O1, increasing in O2, and being higher in groups O3, O4, O5, and O6. None of the OE periods affected the sperm transit time in the epididymis, and the lower sperm reserves were caused mainly by impaired DSP. In conclusion, OE during sexual maturation markedly reduces the DSP at adulthood in the rat. A severe reduction in the DSP also occurs in OE exposure during gestation/lactation but not in gestation, indicating that breast-feeding is a critical period for spermatogenic impairment under obesogenic conditions.

Semi-determinate Growth Habit Adjusts The Vegetative-to-reproductive Balance And Increases Productivity And Water-use Efficiency In Tomato (solanum Lycopersicum).

Tomato (Solanum lycopersicum) shows three growth habits: determinate, indeterminate and semi-determinate. These are controlled mainly by allelic variation in the SELF-PRUNING (SP) gene family, which also includes the florigen gene SINGLE FLOWER TRUSS (SFT). Determinate cultivars have synchronized flower and fruit production, which allows mechanical harvesting in the tomato processing industry, whereas indeterminate ones have more vegetative growth with continuous flower and fruit formation, being thus preferred for fresh market tomato production. The semi-determinate growth habit is poorly understood, although there are indications that it combines advantages of determinate and indeterminate growth. Here, we used near-isogenic lines (NILs) in the cultivar Micro-Tom (MT) with different growth habit to characterize semi-determinate growth and to determine its impact on developmental and productivity traits. We show that semi-determinate genotypes are equivalent to determinate ones with extended vegetative growth, which in turn impacts shoot height, number of leaves and either stem diameter or internode length. Semi-determinate plants also tend to increase the highly relevant agronomic parameter Brix×ripe yield (BRY). Water-use efficiency (WUE), evaluated either directly as dry mass produced per amount of water transpired or indirectly through C isotope discrimination, was higher in semi-determinate genotypes. We also provide evidence that the increases in BRY in semi-determinate genotypes are a consequence of an improved balance between vegetative and reproductive growth, a mechanism analogous to the conversion of the overly vegetative tall cereal varieties into well-balanced semi-dwarf ones used in the Green Revolution.

G-quadruplex Formation Enhances Splicing Efficiency Of Pax9 Intron 1.

G-quadruplexes are secondary structures present in DNA and RNA molecules, which are formed by stacking of G-quartets (i.e., interaction of four guanines (G-tracts) bounded by Hoogsteen hydrogen bonding). Human PAX9 intron 1 has a putative G-quadruplex-forming region located near exon 1, which is present in all known sequenced placental mammals. Using circular dichroism (CD) analysis and CD melting, we showed that these sequences are able to form highly stable quadruplex structures. Due to the proximity of the quadruplex structure to exon-intron boundary, we used a validated double-reporter splicing assay and qPCR to analyze its role on splicing efficiency. The human quadruplex was shown to have a key role on splicing efficiency of PAX9 intron 1, as a mutation that abolished quadruplex formation decreased dramatically the splicing efficiency of human PAX9 intron 1. The less stable, rat quadruplex had a less efficient splicing when compared to human sequences. Additionally, the treatment with 360A, a strong ligand that stabilizes quadruplex structures, further increased splicing efficiency of human PAX9 intron 1. Altogether, these results provide evidences that G-quadruplex structures are involved in splicing efficiency of PAX9 intron 1.

Leaf Manganese Accumulation And Phosphorus-acquisition Efficiency.

Plants that deploy a phosphorus (P)-mobilising strategy based on the release of carboxylates tend to have high leaf manganese concentrations ([Mn]). This occurs because the carboxylates mobilise not only soil inorganic and organic P, but also a range of micronutrients, including Mn. Concentrations of most other micronutrients increase to a small extent, but Mn accumulates to significant levels, even when plants grow in soil with low concentrations of exchangeable Mn availability. Here, we propose that leaf [Mn] can be used to select for genotypes that are more efficient at acquiring P when soil P availability is low. Likewise, leaf [Mn] can be used to screen for belowground functional traits related to nutrient-acquisition strategies among species in low-P habitats.

A novel polar-based human face recognition computational model

Motivated by a recently proposed biologically inspired face recognition approach, we investigated the relation between human behavior and a computational model based on Fourier-Bessel (FB) spatial patterns. We measured human recognition performance of FB filtered face images using an 8-alternative forced-choice method. Test stimuli were generated by converting the images from the spatial to the FB domain, filtering the resulting coefficients with a band-pass filter, and finally taking the inverse FB transformation of the filtered coefficients. The performance of the computational models was tested using a simulation of the psychophysical experiment. In the FB model, face images were first filtered by simulated V1- type neurons and later analyzed globally for their content of FB components. In general, there was a higher human contrast sensitivity to radially than to angularly filtered images, but both functions peaked at the 11.3-16 frequency interval. The FB-based model presented similar behavior with regard to peak position and relative sensitivity, but had a wider frequency band width and a narrower response range. The response pattern of two alternative models, based on local FB analysis and on raw luminance, strongly diverged from the human behavior patterns. These results suggest that human performance can be constrained by the type of information conveyed by polar patterns, and consequently that humans might use FB-like spatial patterns in face processing.