Second-order Relationships Research Articles

Genome-wide SNP data show little differentiation between the Appaloosa and other American stock horse breeds.

The Appaloosa, American Quarter Horse (QH) and American Paint Horse (Paint) breeds are commonly referred to as stock horses, as each is used, to some extent, when managing livestock. QHs and Paint horses are genetically similar, which is predicted based on phenotype, ancestry and admixture allowed between the registries and with the Thoroughbred. In the Appaloosa, admixture is also allowed with the Thoroughbred, QH and Arabian. The Appaloosa is similar in conformation to the other stock breeds but has a unique leopard-spotting coat color pattern as well as mottled skin, white sclera of the eye and striped hooves. The goal of this study was to examine the relationship of the Appaloosa to the other stock breeds and determine whether genomic regions unique to the breed could be identified. This work will inform future clinical and genetic work of inherited phenotypes. The horses studied were sampled for other purposes and, as much as possible, represented a random sample of each breed. Second-order relationships (shared grandsire/dam) within each breed were excluded based on pedigree. The Appaloosas (n = 24) included 20 in the regular registry (had Appaloosa characteristics), two non-characteristic and two non-characteristic but with a completed certified pedigree option. Six Appaloosas had a QH parent, whereas 11 others had a QH or Thoroughbred grandsire/dam. Twenty-five QHs and 18 Paint horses were included. Diversity and F-statistics were calculated from 12 013 autosomal SNPs genotyped on the Illumina SNP50 or SNP70 BeadArray; these SNPs were selected after eliminating loci with minor allele frequency 0.2) in PLINK. The Appaloosas studied had higher diversity (expected heterozygosity) than did the QH and Paint as anticipated by pedigree. This greater degree of diversity was also noted in the number of fixed loci (of 40 281 total) within each breed (QH = 728, Paint = 1347, Appaloosa = 567). FIS did not indicate inbreeding (Table S1). Across breeds, cluster analysis (STRUCTURE) was unable to support clustering beyond K = 1 (Fig. S1). Principal component (PC) analysis in SNPRELATE revealed that PCs 1 and 2 accounted for 4.15% of the total variation. PCs 1 and 3 failed to separate the breeds, whereas PC 2 showed a trend of clustering the Appaloosas apart from the intermingled Paint and QHs (Fig. 1). Pairwise FST values were low [0.001 (Paint-QH) to 0.005 (QH-Appaloosa)] (Table S1) but significantly different from zero as determined by 15 000 permutations in ARLEQUIN; however, an exact test of population differentiation, assuming the null hypothesis that all alleles are drawn from the same pool/population, was not significant. The highest single-locus FST across populations was on ECA1 at 108.9 Mb, which also was the highest pairwise value between the Appaloosa and Paint and ranked second when comparing Appaloosa to the QH (Table S1); this SNP is 574.5 kb from the 5’ end of TRPM1, the gene implicated in Appaloosa coat color. Another SNP on ECA1, 62.5 kb from TRPM1, also had a high FST in pairwise comparisons including the Appaloosa. Therefore, although the divergence between breeds is low, these results are evidence that genomic signatures of selection for major, breed-defining phenotypes in the Appaloosa can be detected.

Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and the probabilities of trends of fuzzy logical relationships.

In this paper, we present a new method for fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and the probabilities of trends of fuzzy-trend logical relationships. Firstly, the proposed method fuzzifies the historical training data of the main factor and the secondary factor into fuzzy sets, respectively, to form two-factors second-order fuzzy logical relationships. Then, it groups the obtained two-factors second-order fuzzy logical relationships into two-factors second-order fuzzy-trend logical relationship groups. Then, it calculates the probability of the "down-trend," the probability of the "equal-trend" and the probability of the "up-trend" of the two-factors second-order fuzzy-trend logical relationships in each two-factors second-order fuzzy-trend logical relationship group, respectively. Finally, it performs the forecasting based on the probabilities of the down-trend, the equal-trend, and the up-trend of the two-factors second-order fuzzy-trend logical relationships in each two-factors second-order fuzzy-trend logical relationship group. We also apply the proposed method to forecast the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) and the NTD/USD exchange rates. The experimental results show that the proposed method outperforms the existing methods.

Response Surface Modeling for Optimization of Textural and Color Characteristics of Dried Grapes

Abstract This study presents the optimization of pre-drying treatment and storage conditions on textural and color properties of dried grapes using a response surface methodology – central composite rotatable design. Effects of three variables, potassium carbonate concentration (K2CO3, 5.98–11.02%), storage temperature (3.18–36.82°C), and relative humidity (RH, 6.96–91.04%), were evaluated. The response variables were defined as the rupture force, deformation, and Hunter L, a, and b values of dried grapes. Second-order empirical relationships with high R 2 (>0.96) values between the responses and independent variables were derived. Results also showed that the K2CO3 concentration and temperature were the most significant factors influencing the studied textural and color characteristics, respectively. The overall optimum region resulted in the desirable characteristics was predicted at a combined level of 9.27% K2CO3 concentration, 4°C storage temperature, and 67.34% RH. Under these conditions, the corresponding predicted response values for the rupture force, deformation, and Hunter L, a, and b values of dried grapes were 2.15 N, 2.53 mm, 28.54, 3.25, and 9.74, respectively. The predicted values thus obtained were close to the actual values indicating suitability of the models.

Identifying genetic relatives without compromising privacy

The development of high-throughput genomic technologies has impacted many areas of genetic research. While many applications of these technologies focus on the discovery of genes involved in disease from population samples, applications of genomic technologies to an individual’s genome or personal genomics have recently gained much interest. One such application is the identification of relatives from genetic data. In this application, genetic information from a set of individuals is collected in a database, and each pair of individuals is compared in order to identify genetic relatives. An inherent issue that arises in the identification of relatives is privacy. In this article, we propose a method for identifying genetic relatives without compromising privacy by taking advantage of novel cryptographic techniques customized for secure and private comparison of genetic information. We demonstrate the utility of these techniques by allowing a pair of individuals to discover whether or not they are related without compromising their genetic information or revealing it to a third party. The idea is that individuals only share enough special-purpose cryptographically protected information with each other to identify whether or not they are relatives, but not enough to expose any information about their genomes. We show in HapMap and 1000 Genomes data that our method can recover first- and second-order genetic relationships and, through simulations, show that our method can identify relationships as distant as third cousins while preserving privacy.

Fuzzy Forecasting Based on Two-Factors Second-Order Fuzzy-Trend Logical Relationship Groups and Particle Swarm Optimization Techniques

In this paper, we present a new method for fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and particle swarm optimization (PSO) techniques. First, we fuzzify the historical training data of the main factor and the secondary factor, respectively, to form two-factors second-order fuzzy logical relationships. Then, we group the two-factors second-order fuzzy logical relationships into two-factors second-order fuzzy-trend logical relationship groups. Then, we obtain the optimal weighting vector for each fuzzy-trend logical relationship group by using PSO techniques to perform the forecasting. We also apply the proposed method to forecast the Taiwan Stock Exchange Capitalization Weighted Stock Index and the NTD/USD exchange rates. The experimental results show that the proposed method gets better forecasting performance than the existing methods.

Seeing Deep Structure From the Interactions of Surface Features

Transfer is typically thought of as requiring individuals to “see” what is the same in the deep structure between a new target problem and a previously encountered source problem, even though the surface features may be dissimilar. We propose that experts can “see” the deep structure by considering the first-order interactions of the explicit surface features and the second-order relationships between the first-order cues. Based on this speculative hypothesis, we propose a domain-specific bottom-up instructional approach that teaches students explicitly to focus on deriving the first-order interactions cues and noticing the second-order relationships among the first-order interaction cues. To do so, researchers and instructional designers need to first extract from experienced solvers or experts how they derive such first-order cues. Transfer is assumed to be based on the similarities in the second-order relationships, which are familiar everyday relationships such as equal to, greater than, and so forth.

Predicting requirement change propagation, using higher order design structure matrices: an industry case study

This research examines higher order design structure matrices as requirements change modelling tools to predict requirement change propagation through two large-scale industry design projects. Due to the iterative nature of design, requirements will evolve and change. Changes in requirements can propagate to other requirements on different subsystems leading to possible increases in the project cost and lead-time. Predicting these requirement changes enables the designers to foresee unanticipated changes and maximises the probability for the project's success. These studies reveal that second-order relationships are influential in predicting requirement change propagation. Unforeseen propagation occurring in first-order form was rare, rather it was occurring in second order. Modelling requirements change exposes these secondary relationships early in the engineering change (EC) definition process, thereby enhancing the decision-making process and augmenting cost estimation. A modelling tool, such as that proposed in this paper, can provide the designer insight into the requirements which may be affected before approving an EC.

Reynolds number effects on scale energy balance in wall turbulence

The scale energy budget utilizes a modified version of the classical Kolmogorov equation of wall turbulence to develop an evolution equation for the second order structure function [R. J. Hill, “Exact second-order structure-function relationships,” J. Fluid Mech. 468, 317 (2002)]. This methodology allows for the simultaneous characterization of the energy cascade and spatial fluxes in turbulent shear flows across the entire physical domain as well as the range of scales. The present study utilizes this methodology to characterize the effects of Reynolds number on the balance of energy fluxes in turbulent channel flows. Direct numerical simulation data in the range Reτ = 300–934 are compared to previously published results at Reτ = 180 [N. Marati, C. M. Casciola, and R. Piva, “Energy cascade and spatial fluxes in wall turbulence,” J. Fluid Mech. 521, 191 (2004)]. The present results show no Reynolds number effects in the terms of the scale energy budget in either the viscous sublayer or buffer regions of the channel. In the logarithmic layer, the transfer of energy across scales clearly varies with Reynolds number, while the production of turbulent kinetic energy is not dependent on Reynolds number. An envelope of inverse energy cascade is quantified in the buffer region within which energy is transferred from small to larger scales. This envelope is observed in the range 6 < y+ < 37, where all scales except the smallest scales display characteristics of an inverse energy cascade. The cross-over scale lc+, which indicates the transition between production dominated and scale transfer dominated regimes, increases with Reynolds number, implying a larger range of transfer dominated scales, before the dominant mechanism switches to production. At higher Reynolds numbers, two distinct regimes of lc+ as a function of wall-normal location are observed, which was not captured at Reτ = 180. The variations of lc+ match the trends of the shear scale, which is a representation of the mean shear in the flow. Thus, this study demonstrates the utility and importance of the use of higher Reynolds number data in order to accurately characterize and understand the energy dynamics of various scales across the entire boundary layer.

Lineage Identification and Genealogical Relationships Among Captive Galápagos Tortoises

Genetic tools have become a critical complement to traditional approaches for meeting short- and long-term goals of ex situ conservation programs. The San Diego Zoo (SDZ) harbors a collection of wild-born and captive-born Galápagos giant tortoises (n = 22) of uncertain species designation and unknown genealogical relationships. Here, we used mitochondrial DNA haplotypic data and nuclear microsatellite genotypic data to identify the evolutionary lineage of wild-born and captive-born tortoises of unknown ancestry, to infer levels of relatedness among founders and captive-born tortoises, and assess putative pedigree relationships assigned by the SDZ studbook. Assignment tests revealed that 12 wild-born and five captive-born tortoises represent five different species from Isabela Island and one species from Santa Cruz Island, only five of which were consistent with current studbook designations. Three wild-born and one captive-born tortoise were of mixed ancestry. In addition, kinship analyses revealed two significant first-order relationship pairs between wild-born and captive-born tortoises, four second-order relationships (half-sibling) between wild-born and captive tortoises (full-sibs or parent-offspring), and one second-order relationship between two captive-born tortoises. Of particular note, we also reconstructed a first-order relationship between two wild-born individuals, violating the founder assumption. Overall, our results contribute to a worldwide effort in identifying genetically important Galápagos tortoises currently in captivity while revealing closely related founders, reconstructing genealogical relationships, and providing detailed management recommendations for the SDZ tortoises.

The privileged status of locality in consonant harmony

While the vast majority of linguistic processes apply locally, consonant harmony appears to be an exception. In this phonological process, consonants share the same value of a phonological feature, such as secondary place of articulation. In sibilant harmony, [s] and [∫] (‘sh’) alternate such that if a word contains the sound [∫], all [s] sounds become [∫]. This can apply locally as a first-order or non-locally as a second-order pattern. In the first-order case, no consonants intervene between the two sibilants (e.g., [pisasu], [pi∫a∫u]). In second-order case, a consonant may intervene (e.g., [sipasu], [∫ipa∫u]). The fact that there are languages that allow second-order non-local agreement of consonant features has led some to question whether locality constraints apply to consonant harmony. This paper presents the results from two artificial grammar learning experiments that demonstrate the privileged role of locality constraints, even in patterns that allow second-order non-local interactions. In Experiment 1, we show that learners do not extend first-order non-local relationships in consonant harmony to second-order non-local relationships. In Experiment 2, we show that learners will extend a consonant harmony pattern with second-order long distance relationships to a consonant harmony with first-order long distance relationships. Because second-order non-local application implies first-order non-local application, but first-order non-local application does not imply second-order non-local application, we establish that local constraints are privileged even in consonant harmony.

A Measurement and Conceptual Investigation of Exercise Imagery Establishing Construct Validity

We assessed the factor structure of a revised version of the Exercise Imagery Inventory (EII; Giacobbi, Hausenblas, & Penfield, 2005), second-order interrelationships for cognitive and motivational forms of mental imagery, and associations with exercise behavior and barriers self-efficacy. A convenience sample of 358 (M age = 20.55 years, SD = 3.88) college students completed the EII-revised (EII-R), a measure of barriers self-efficacy and the Leisure-Time Exercise Questionnaire. The EII-R demonstrated reliability and factorial validity with good model fit statistics. We observed second-order relationships among scale scores and discriminant validity evidence that distinguished cognitive (e.g., exercise technique, exercise routines) and motivational (e.g., appearance/health, exercise self-efficacy, exercise feelings) factors. The second-order imagery factors were significantly and moderately associated with barriers self-efficacy and exercise behavior.

Analytical methods for quantifying environmental connectivity for the control and surveillance of infectious disease spread

The sustained transmission and spread of environmentally mediated infectious diseases is governed in part by the dispersal of parasites, disease vectors and intermediate hosts between sites of transmission. Functional geospatial models can be used to quantify and predict the degree to which environmental features facilitate or limit connectivity between target populations, yet typical models are limited in their geographical and analytical approach, providing simplistic, global measures of connectivity and lacking methods to assess the epidemiological implications of fine-scale heterogeneous landscapes. Here, functional spatial models are applied to problems of surveillance and control of the parasitic blood fluke Schistosoma japonicum and its intermediate snail host Oncomelania haupensis in western China. We advance functional connectivity methods by providing an analytical framework to (i) identify nodes of transmission where the degree of connectedness to other villages, and thus the potential for disease spread, is higher than is estimated using Euclidean distance alone and (ii) (re)organize transmission sites into disease surveillance units based on second-order relationships among nodes using non-Euclidean distance measures, termed effective geographical distance (EGD). Functional environmental models are parametrized using ecological information on the target organisms, and pair-wise distributions of inter-node EGD are estimated. A Monte Carlo rank product analysis is presented to identify nearby nodes under alternative distance models. Nodes are then iteratively embedded into EGD space and clustered using a k-means algorithm to group villages into ecologically meaningful surveillance groups. A consensus clustering approach is taken to derive the most stable cluster structure. The results indicate that novel relationships between nodes are revealed when non-Euclidean, ecologically determined distance measures are used to quantify connectivity in heterogeneous landscapes. These connections are not evident when analysing nodes in Euclidean space, and thus surveillance and control activities planned using Euclidean distance measures may be suboptimal. The methods developed here provide a quantitative framework for assessing the effectiveness of ecologically grounded surveillance systems and of control and prevention strategies for environmentally mediated diseases.

An index directly indicates land-based pollutant load contributions of domestic wastewater to the water pollution and its application

As indices directly indicate land-based pollutant load contributions to public water pollution, pollutant load per capita flowing into the water body (PLCwb) for the drainage areas of inner city rivers in Chiba City, Chiba Prefecture, Japan, was analyzed. It was reaffirmed that PLCwb was different by the drainage area. For example, the biochemical oxygen demand (BOD) load per capita flowing into the water body (PLCwb-BOD) was calculated as 0.83 g BOD person−1 day−1 for population served with wastewater treatment plant (WWTP). In regards to the three types of on-site domestic wastewater treatment methods in Japan: 0.4–2.1 g BOD person−1 day−1 for combined jokaso (CJ), 4.5–21 g BOD person−1 day−1 for simple jokaso (SJ) and 4.3–19 g BOD person−1 day−1 for night soil treatment (NST). In regards to nutrient parameters of the three on-site treatment methods, population weighted average of PLCwb were almost the same, however, relatively small PLCwb were observed for CJ and SJ through the analysis. Environmental accounting housekeeping (EAH) books for domestic wastewater were prepared based on the analysis results as the application of the indices. EAH books are effective tools for water pollution mitigation in public water bodies. The results of the preliminary correlation analysis of the indices showed that high-efficiency treatment methods including WWTP, agriculture village wastewater treatment facility (AVETF) and CJ are effective in reducing pollutant load flowing into the water body, and that PLCwb have second-order equation relationships with population density of the drainage area. Judging from these characteristics and the analytical results of this study, PLCwb may be useful as an index for demonstrating the benefit of wastewater treatment in reduction of water pollution in the water body.

Receptive fields for flexible face categorizations.

Abstract-Examining the receptive fields of brain signals can elucidate how information impinging on the former modulates the latter. We applied this time-honored approach in early vision to the higher-level brain processes underlying face categorizations. Electroencephalograms in response to face-information samples were recorded while observers resolved two different categorizations (gender, expressive or not). Using a method with low bias and low variance, we compared, in a common space of information states, the information determining behavior (accuracy and reaction time) with the information that modulates emergent brain signals associated with early face encoding and later category decision. Our results provide a time line for face processing in which selective attention to diagnostic information for categorizing stimuli (the eyes and their second-order relationships in gender categorization; the mouth in expressive-or-not categorization) correlates with late electrophysiological (P300) activity, whereas early face-sensitive occipito-temporal (N170) activity is mainly driven by the contralateral eye, irrespective of the categorization task.

Constraint Based Region Matching for Image Retrieval

Objects and their spatial relationships are important features for human visual perception. In most existing content-based image retrieval systems, however, only global features extracted from the whole image are used. While they are easy to implement, they have limited power to model semantic-level objects and spatial relationship. To overcome this difficulty, this paper proposes a constraint-based region matching approach to image retrieval. Unlike existing region-based approaches where either individual regions are used or only first-order constraints are modeled, the proposed approach formulates the problem in a probabilistic framework and simultaneously models both first-order region properties and second-order spatial relationships for all the regions in the image. Specifically, in this paper we present a complete system that includes image segmentation, local feature extraction, first- and second-order constraints, and probabilistic region weight estimation. Extensive experiments have been carried out on a large heterogeneous image collection with 17,000 images. The proposed approach achieves significantly better performance than the state-of-the-art approaches.

Second-order functions are the simplest correlations between flow cytometric light scatter and bacterial diameter

Second-order mathematical relationships between bacterial cell diameter determined by electric particle analyser and flow cytometric forward light scatter in axenic cultures are obtained and discussed. Since it is technically impossible today to obtain both measurements for each individual cell, standard regression techniques cannot be applied. To overcome this limitation, we assume that these two parameters are related by a monotone increasing function that enables their mathematical relationships to be studied. Our conclusion is that forward light scatter data cannot be linearly transformed into bacterial size values by an accurate and universal function. However, second-order relationships seem to be the simplest satisfactory relationships between cell diameter and forward light scatter in eubacteria.

Recursive Modeling of Serial Flexible Manipulators

This paper discusses the modeling of serial manipulators with flexible links and joints. The model of a flexible link includes bending in two perpendicular directions and torsion around the longitudinal axis. Second-order strain-displacement relationships, coupled with curvatures as generalized coordinates, are used to represent the foreshortening effect. Then, the dynamic equations are exact to first order in terms of the generalized coordinates associated with the flexible links. These generalized coordinates and their first time-derivatives are assumed to be small (of first order). The model developed captures all the important phenomena, such as stiffening due to the angular speed or buckling due to large payloads. The dynamic equations are developed recursively using Jourdain’s principle to allow an efficient symbolic implementation. The equations associated with the flexible links are reformulated to enable off-line symbolic integration. The gyroscopic effects of motors with reducers are included.

Scanning transmission ion microscopy (STIM) with a 3 MeV proton cyclotron beam

A method is developed to optimize the lateral resolution of a scanning proton microprobe using a 3 MeV cyclotron beam. The most important part of the method is the optimization of an asymmetrical quadrupole quadruplet, based on second-order relationships between diaphragm widths and the full width of the spot. A STIM example is presented of cellular structures of rat-heart tissue.

Genetic and environmental effects on blood pressure in a Norwegian sample.

Systolic (SBP) and diastolic (DBP) blood pressures were measured in a health screening of the adult population in Nord-Trøndelag, Norway. Correlations were computed for 23,936 pairs of spouses, 43,586 pairs of parent and offspring, 19,151 pairs of siblings, 1,251 pairs of grandparents-grandchildren, 1,146 pairs of biological uncles/aunts-nephews/nieces (avuncular), 801 non-biological avuncular pairs, 169 pairs of same-sex twins, and smaller groups of other types of relationships. Spouse correlations of 0.08 and 0.09 were approximately constant or slightly decreasing with marital duration. The correlation values for SBP and DBP were approximately 0.16 for parents-offspring, 0.19 to 0.23 for same-sex siblings with similar values for DZ twins, 0.19 and 0.16 for opposite-sex siblings, 0.52 and 0.43 for MZ twins, and close to zero for most of the second-order relationships. Genetic additive variance was estimated at 0.29 and genetic dominance variance at 0.18 with the best model for SBP. The corresponding estimates from the best models for DBP were 0.29 or lower and 0.22 or lower, the sum not exceeding 0.35. There was evidence of a moderate effect of environmental factors shared by same-sex siblings and twins (for DBP), but no cultural transmission, and whether or not adult relatives live together does not affect familial resemblance for BP. The data did not permit a very precise resolution of the relative magnitude of genetic dominance and sibling effects. The correlation structure did not show sex-specific genetic effects.

Analytic expression of the second derivatives of electronic energy for full configuration interaction wave functions

A new analytic second derivative expression of the electronic energy is derived for full configuration interaction (CI) wave functions. This formula is shown to be free from the derivative terms of both CI and MO coefficients. The second-order relationships between CI and MO coefficients for full CI wave functions are also presented.