Generating unconstrained two-dimensional non-guillotine cutting patterns by a Recursive Partitioning Algorithm

In this study, a dynamic programming approach to deal with the unconstrained two-dimensional non-guillotine cutting problem is presented. The method extends the recently introduced recursive partitioning approach for the manufacturer's pallet loading problem. The approach involves two phases and uses bounds based on unconstrained two-staged and non-staged guillotine cutting. The method is able to find the optimal cutting pattern of a large number of pro blem instances of moderate sizes known in the literature and a counterexample for which the approach fails to find known optimal solutions was not found. For the instances that the required computer runtime is excessive, the approach is combined with simple heuristics to reduce its running time. Detailed numerical experiments show the reliability of the method. Journal of the Operational Research Society (2012) 63, 183-200. doi: 10.1057/jors.2011.6 Published online 17 August 2011

Effects of tributyltin exposure in hermit crabs: Clibanarius vittatus as a model

Tributyltin (TBT) contamination affects the reproductive system of many species of invertebrates worldwide. The present study was designed to evaluate the effects of exposure to TBT pollution on the reproduction of the hermit crab Clibanarius vittatus. An orthogonal experiment was designed with two treatments: contamination (with or without TBT in the food) and crab sex (males and females). The animals were reared in the laboratory for nine months, and macroscopic and histological analyses of reproductive organs were carried out after the end of the experiment. Tributyltin was recorded in exposed crabs, but no morphological alterations were detected in the gonads of males, regardless of whether they were exposed to TBT. In contrast, females exposed to TBT displayed disorganization and atrophy of their ovaries, thus directly affecting reproduction in this hermit crab species. This effect observed in female hermit crabs may harm populations located in harbor regions, where TBT concentration is high, even after the worldwide TBT ban.

Considerations for Assessing Maximum Critical Temperatures in Small Ectothermic Animals: Insights from Leaf-Cutting Ants

The thermal limits of individual animals were originally proposed as a link between animal physiology and thermal ecology. Although this link is valid in theory, the evaluation of physiological tolerances involves some problems that are the focus of this study. One rationale was that heating rates shall influence upper critical limits, so that ecological thermal limits need to consider experimental heating rates. In addition, if thermal limits are not surpassed in experiments, subsequent tests of the same individual should yield similar results or produce evidence of hardening. Finally, several non-controlled variables such as time under experimental conditions and procedures may affect results. To analyze these issues we conducted an integrative study of upper critical temperatures in a single species, the ant Atta sexdens rubropiosa, an animal model providing large numbers of individuals of diverse sizes but similar genetic makeup. Our specific aims were to test the 1) influence of heating rates in the experimental evaluation of upper critical temperature, 2) assumptions of absence of physical damage and reproducibility, and 3) sources of variance often overlooked in the thermal-limits literature; and 4) to introduce some experimental approaches that may help researchers to separate physiological and methodological issues. The upper thermal limits were influenced by both heating rates and body mass. In the latter case, the effect was physiological rather than methodological. The critical temperature decreased during subsequent tests performed on the same individual ants, even one week after the initial test. Accordingly, upper thermal limits may have been overestimated by our (and typical) protocols. Heating rates, body mass, procedures independent of temperature and other variables may affect the estimation of upper critical temperatures. Therefore, based on our data, we offer suggestions to enhance the quality of measurements, and offer recommendations to authors aiming to compile and analyze databases from the literature.

Bayesian analysis of random regression models using B-splines to model test-day milk yield of Holstein cattle in Brazil

The objective of this paper is to model variations in test-day milk yields of first lactations of Holstein cows by RR using B-spline functions and Bayesian inference in order to fit adequate and parsimonious models for the estimation of genetic parameters. They used 152,145 test day milk yield records from 7317 first lactations of Holstein cows. The model established in this study was additive, permanent environmental and residual random effects. In addition, contemporary group and linear and quadratic effects of the age of cow at calving were included as fixed effects. Authors modeled the average lactation curve of the population with a fourth-order orthogonal Legendre polynomial. They concluded that a cubic B-spline with seven random regression coefficients for both the additive genetic and permanent environment effects was to be the best according to residual mean square and residual variance estimates. Moreover they urged a lower order model (quadratic B-spline with seven random regression coefficients for both random effects) could be adopted because it yielded practically the same genetic parameter estimates with parsimony. (C) 2012 Elsevier B.V. All rights reserved.

Random regression analyses using B-spline functions to model growth of Nellore cattle

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

The General Curvilinear Environmental Model (GCEM)

[EN] The General Curvilinear Environmental Model is a high-resolution system composed of the General Curvilinear Coastal Ocean Model (GCCOM) and the General Curvilinear Atmospheric Model (GCAM). Both modules are capable of reading a general curvilinear grid, orthogonal as well as non-orthogonal in all three directions. These two modules are weakly coupled using the distributed coupling toolkit (DCT). The model can also be nested within larger models and users are able to interact with the model and run it using a web based computational environment.

Orthogonal gamma-based expansions for volatility option prices under jump-diffusion dynamics

In my work I derive closed-form pricing formulas for volatility based options by suitably approximating the volatility process risk-neutral density function. I exploit and adapt the idea, which stands behind popular techniques already employed in the context of equity options such as Edgeworth and Gram-Charlier expansions, of approximating the underlying process as a sum of some particular polynomials weighted by a kernel, which is typically a Gaussian distribution. I propose instead a Gamma kernel to adapt the methodology to the context of volatility options. VIX vanilla options closed-form pricing formulas are derived and their accuracy is tested for the Heston model (1993) as well as for the jump-diffusion SVJJ model proposed by Duffie et al. (2000).

A triplet spike-timing–dependent plasticity model generalizes the Bienenstock–Cooper–Munro rule to higher-order spatiotemporal correlations

Synaptic strength depresses for low and potentiates for high activation of the postsynaptic neuron. This feature is a key property of the Bienenstock–Cooper–Munro (BCM) synaptic learning rule, which has been shown to maximize the selectivity of the postsynaptic neuron, and thereby offers a possible explanation for experience-dependent cortical plasticity such as orientation selectivity. However, the BCM framework is rate-based and a significant amount of recent work has shown that synaptic plasticity also depends on the precise timing of presynaptic and postsynaptic spikes. Here we consider a triplet model of spike-timing–dependent plasticity (STDP) that depends on the interactions of three precisely timed spikes. Triplet STDP has been shown to describe plasticity experiments that the classical STDP rule, based on pairs of spikes, has failed to capture. In the case of rate-based patterns, we show a tight correspondence between the triplet STDP rule and the BCM rule. We analytically demonstrate the selectivity property of the triplet STDP rule for orthogonal inputs and perform numerical simulations for nonorthogonal inputs. Moreover, in contrast to BCM, we show that triplet STDP can also induce selectivity for input patterns consisting of higher-order spatiotemporal correlations, which exist in natural stimuli and have been measured in the brain. We show that this sensitivity to higher-order correlations can be used to develop direction and speed selectivity.

Animal model for percutaneous creation of traumatic thoracic aortic transection

PURPOSE: This study was conducted to create an animal model for thoracic aortic transection that is suitable for thoracic endograft research. MATERIALS AND METHODS: Percutaneous aortic transection creation was attempted in 12 sheep. A custom collapsible circumferential cutting device was inserted into the proximal descending thoracic aorta via a femoral approach with an 11-F delivery catheter. The device was deployed 2 cm distal to the left subclavian artery origin and rotated 20 times to create aortic transection. Aortic diameters, mean aortic pressures, and heart rates were tested for degrees of difference between measurements before and after the creation of transection. On necropsy, the extent of aortic damage was classified as none, nontransmural, or transmural, and aortic transection was classified as none, partial, or circumferential. RESULTS: On angiography, creation of transmural thoracic aortic transection was successful in 91.7% (11/12) of animals. Aortic transection was circumferential in 54.4% (6/11) of animals and partial in 45.6% (5/11) of animals. Mean aortic diameter was 19.6 +/- 3.4 mm (range 12-24 mm) pre-transection and 25.8 +/- 4.5 mm (range 17.8-33 mm) post-transection (P = .0003). Pre-transection, mean aortic pressure was 79 +/- 13.8 mmHg, and 64.6 +/- 15.8 mmHg 15 min post-transection (P = .041). Pre-transection, mean heart rate was 94.5 +/- 17.2 beats per minute (bpm), and 105.8 +/- 17.2 bpm 15 min post-transection (P = .0057). CONCLUSIONS: Thoracic aortic transection was successfully created percutaneously in most animals. The animals remained in hemodynamically stable condition for as long as 240 minutes after the creation of aortic injury. This percutaneous animal model is straightforward and may be of potential value for future thoracic endograft research.

Experimental model to evaluate in vivo and in vitro cartilage MR imaging by means of histological analyses

OBJECTIVES: Implementation of an experimental model to compare cartilage MR imaging by means of histological analyses. MATERIAL AND METHODS: MRI was obtained from 4 patients expecting total knee replacement at 1.5 and/or 3T prior surgery. The timeframe between pre-op MRI and knee replacement was within two days. Resected cartilage-bone samples were tagged with Ethi((R))-pins to reproduce the histological cutting course. Pre-operative scanning at 1.5T included following parameters for fast low angle shot (FLASH: TR/TE/FA=33ms/6ms/30 degrees , BW=110kHz, 120mmx120mm FOV, 256x256 matrix, 0.65mm slice-thickness) and double echo steady state (DESS: TR/TE/FA=23.7ms/6.9ms/40 degrees , BW=130kHz, 120x120mm FOV, 256x256 matrix, 0.65mm slice-thickness). At 3T, scan parameters were: FLASH (TR/TE/FA=12.2ms/5.1ms/10 degrees , BW=130kHz, 170x170mm FOV, 320x320, 0.5mm slice-thickness) and DESS (TR/TE/FA=15.6ms/4.5ms/25 degrees , BW=200kHz, 135mmx150mm FOV, 288x320matrix, 0.5mm slice-thickness). Imaging of the specimens was done the same day at 1.5T. MRI (Noyes) and histological (Mankin) score scales were correlated using the paired t-test. Sensitivity and specificity for the detection of different grades of cartilage degeneration were assessed. Inter-reader and intra-reader reliability was determined using Kappa analysis. RESULTS: Low correlation (sensitivity, specificity) was found for both sequences in normal to mild Mankin grades. Only moderate to severe changes were diagnosed with higher significance and specificity. The use of higher field-strengths was advantageous for both protocols with sensitivity values ranging from 13.6% to 93.3% (FLASH) and 20.5% to 96.2% (DESS). Kappa values ranged from 0.488 to 0.944. CONCLUSIONS: Correlating MR images with continuous histological slices was feasible by using three-dimensional imaging, multi-planar-reformat and marker pins. The capability of diagnosing early cartilage changes with high accuracy could not be proven for both FLASH and DESS.

ANOVA kernels and RKHS of zero mean functions for model-based sensitivity analysis

Given a reproducing kernel Hilbert space (H,〈.,.〉)(H,〈.,.〉) of real-valued functions and a suitable measure μμ over the source space D⊂RD⊂R, we decompose HH as the sum of a subspace of centered functions for μμ and its orthogonal in HH. This decomposition leads to a special case of ANOVA kernels, for which the functional ANOVA representation of the best predictor can be elegantly derived, either in an interpolation or regularization framework. The proposed kernels appear to be particularly convenient for analyzing the effect of each (group of) variable(s) and computing sensitivity indices without recursivity.

A Model Study of the Seasonal Circulation in the Gulf of Maine

The Princeton Ocean Model is used to study the circulation in the Gulf of Maine and its seasonal transition in response to wind, surface heat flux, river discharge, and the M-2 tide. The model has an orthogonal-curvature linear grid in the horizontal with variable spacing from 3 km nearshore to 7 km offshore and 19 levels in the vertical. It is initialized and forced at the open boundary with model results from the East Coast Forecast System. The first experiment is forced by monthly climatological wind and heat flux from the Comprehensive Ocean Atmosphere Data Set; discharges from the Saint John, Penobscot, Kennebec, and Merrimack Rivers are added in the second experiment; the semidiurnal lunar tide (M-2) is included as part of the open boundary forcing in the third experiment. It is found that the surface heat flux plays an important role in regulating the annual cycle of the circulation in the Gulf of Maine. The spinup of the cyclonic circulation between April and June is likely caused by the differential heating between the interior gulf and the exterior shelf/slope region. From June to December the cyclonic circulation continues to strengthen, but gradually shrinks in size. When winter cooling erodes the stratification, the cyclonic circulation penetrates deeper into the water column. The circulation quickly spins down from December to February as most of the energy is consumed by bottom friction. While inclusion of river discharge changes details of the circulation pattern, the annual evolution of the circulation is largely unaffected. On the other hand, inclusion of the tide results in not only the anticyclonic circulation on Georges Bank but also modifications to the seasonal circulation.

A Model Study of the Circulation in the Pearl River Estuary (PRE) and Its Adjacent Coastal Waters: 1. Simulations and Comparison with Observations

The Princeton Ocean Model is used to study the circulation features in the Pearl River Estuary and their responses to tide, river discharge, wind, and heat flux in the winter dry and summer wet seasons. The model has an orthogonal curvilinear grid in the horizontal plane with variable spacing from 0.5 km in the estuary to 1 km on the shelf and 15 sigma levels in the vertical direction. The initial conditions and the subtidal open boundary forcing are obtained from an associated larger-scale model of the northern South China Sea. Buoyancy forcing uses the climatological monthly heat fluxes and river discharges, and both the climatological monthly wind and the realistic wind are used in the sensitivity experiments. The tidal forcing is represented by sinusoidal functions with the observed amplitudes and phases. In this paper, the simulated tide is first examined. The simulated seasonal distributions of the salinity, as well as the temporal variations of the salinity and velocity over a tidal cycle are described and then compared with the in situ survey data from July 1999 and January 2000. The model successfully reproduces the main hydrodynamic processes, such as the stratification, mixing, frontal dynamics, summer upwelling, two-layer gravitational circulation, etc., and the distributions of hydrodynamic parameters in the Pearl River Estuary and coastal waters for both the winter and the summer season.

Comparative theoretical analysis of continuous wave laser cutting of metals at 1 and 10 um wavelength

We present a derivation and, based on it, an extension of a model originally proposed by V.G. Niziev to describe continuous wave laser cutting of metals. Starting from a local energy balance and by incorporating heat removal through heat conduction to the bulk material, we find a differential equation for the cutting profile. This equation is solved numerically and yields, besides the cutting profiles, the maximum cutting speed, the absorptivity profiles, and other relevant quantities. Our main goal is to demonstrate the model’s capability to explain some of the experimentally observed differences between laser cutting at around 1 and 10 μm wavelengths. To compare our numerical results to experimental observations, we perform simulations for exactly the same material and laser beam parameters as those used in a recent comparative experimental study. Generally, we find good agreement between theoretical and experimental results and show that the main differences between laser cutting with 1- and 10-μm beams arise from the different absorptivity profiles and absorbed intensities. Especially the latter suggests that the energy transfer, and thus the laser cutting process, is more efficient in the case of laser cutting with 1-μm beams.

THE NATURAL AND ORTHOGONAL INTERACTION (NOIA) MODELS FOR QUANTITATIVE TRAITS (QTs) AND COMPLEX DISEASES

My dissertation focuses on developing methods for gene-gene/environment interactions and imprinting effect detections for human complex diseases and quantitative traits. It includes three sections: (1) generalizing the Natural and Orthogonal interaction (NOIA) model for the coding technique originally developed for gene-gene (GxG) interaction and also to reduced models; (2) developing a novel statistical approach that allows for modeling gene-environment (GxE) interactions influencing disease risk, and (3) developing a statistical approach for modeling genetic variants displaying parent-of-origin effects (POEs), such as imprinting. In the past decade, genetic researchers have identified a large number of causal variants for human genetic diseases and traits by single-locus analysis, and interaction has now become a hot topic in the effort to search for the complex network between multiple genes or environmental exposures contributing to the outcome. Epistasis, also known as gene-gene interaction is the departure from additive genetic effects from several genes to a trait, which means that the same alleles of one gene could display different genetic effects under different genetic backgrounds. In this study, we propose to implement the NOIA model for association studies along with interaction for human complex traits and diseases. We compare the performance of the new statistical models we developed and the usual functional model by both simulation study and real data analysis. Both simulation and real data analysis revealed higher power of the NOIA GxG interaction model for detecting both main genetic effects and interaction effects. Through application on a melanoma dataset, we confirmed the previously identified significant regions for melanoma risk at 15q13.1, 16q24.3 and 9p21.3. We also identified potential interactions with these significant regions that contribute to melanoma risk. Based on the NOIA model, we developed a novel statistical approach that allows us to model effects from a genetic factor and binary environmental exposure that are jointly influencing disease risk. Both simulation and real data analyses revealed higher power of the NOIA model for detecting both main genetic effects and interaction effects for both quantitative and binary traits. We also found that estimates of the parameters from logistic regression for binary traits are no longer statistically uncorrelated under the alternative model when there is an association. Applying our novel approach to a lung cancer dataset, we confirmed four SNPs in 5p15 and 15q25 region to be significantly associated with lung cancer risk in Caucasians population: rs2736100, rs402710, rs16969968 and rs8034191. We also validated that rs16969968 and rs8034191 in 15q25 region are significantly interacting with smoking in Caucasian population. Our approach identified the potential interactions of SNP rs2256543 in 6p21 with smoking on contributing to lung cancer risk. Genetic imprinting is the most well-known cause for parent-of-origin effect (POE) whereby a gene is differentially expressed depending on the parental origin of the same alleles. Genetic imprinting affects several human disorders, including diabetes, breast cancer, alcoholism, and obesity. This phenomenon has been shown to be important for normal embryonic development in mammals. Traditional association approaches ignore this important genetic phenomenon. In this study, we propose a NOIA framework for a single locus association study that estimates both main allelic effects and POEs. We develop statistical (Stat-POE) and functional (Func-POE) models, and demonstrate conditions for orthogonality of the Stat-POE model. We conducted simulations for both quantitative and qualitative traits to evaluate the performance of the statistical and functional models with different levels of POEs. Our results showed that the newly proposed Stat-POE model, which ensures orthogonality of variance components if Hardy-Weinberg Equilibrium (HWE) or equal minor and major allele frequencies is satisfied, had greater power for detecting the main allelic additive effect than a Func-POE model, which codes according to allelic substitutions, for both quantitative and qualitative traits. The power for detecting the POE was the same for the Stat-POE and Func-POE models under HWE for quantitative traits.