Relative Dissimilarity Research Articles

An ordinal-cardinal consensus adjustment allocation mechanism for large-scale group decision making based on the consistency of distributed preference relations under fuzzy uncertainty

Large-scale group decision making (LSGDM) problem is common in real life. With the increase in the number of alternatives and the limited rationality of human beings, consistency problem is inevitable when pairwise comparison method is used. We propose an improved consistency calculation approach to generate consistent distributed preference relations (DPRs), which adopts adjacent score intervals to calculate the score intervals of non-adjacent alternative pairs. By using optimization model, the initial DPR is preserved as much as possible on the premise of order consistency. As for the consensus analysis, the concept of relationship-possibility degree is defined to capture the ignorance and fuzzy uncertainty in assessments. An ordinal consensus measure method considering absolute position difference and relative position dissimilarity with relationship-possibility degree is proposed. Ordinal-cardinal consensus adjustment model based on DPR is then constructed to obtain the minimum consensus adjustment of decision makers or subgroups coalition which are considered as coalition payoff. In addition, to distribute the ordinal-cardinal minimum consensus adjustment reasonably, we construct a two-stage consensus adjustment allocation mechanism adopting the improved multi-weighted Shapley function in the cooperative game. Several optimization models are constructed to obtain the adjusted DPRs of decision makers or subgroups. Finally, an illustrative example is presented to demonstrate the validity of the proposed method in dealing with the decision problems of product development engineering. It is expected to make the LSGDM procedure in a more intelligent way.

I love you but I hate your politics: The role of political dissimilarity in romantic relationships.

Amid heightened political polarization in the United States, have politics worked their way into the bedroom? An increase in political similarity between romantic partners has consequences not just for romantic relationships but for society as a whole; political homophily increases our political echo chambers and affects future generations. We drew upon 11 data sets with over 4,000 individuals (including more than 500 couples) to test four preregistered research questions about the prevalence, correlates, consequences, and potential buffers of political dissimilarity in modern-day relationships. Across measures of similarity (overall perceptions, partisanship matching, shared political ideology), couples in our sample showed high levels of political similarity (e.g., 23% were cross-partisan, with fewer than 8% composed of one Democrat and one Republican). Examining 18 potential correlates of political dissimilarity, we found little evidence that certain factors predispose people to end up in a politically dissimilar relationship. When considering the potential consequences of political dissimilarity, we found a small association between political dissimilarity and relationship quality in general and in daily life. The effect was evident when examining perceived political dissimilarity (over and above perceptions of overall similarity) and, to a lesser extent, dissimilarity in terms of partisanship and political ideology. Prosocial processes such as appreciation and perspective-taking may moderate these effects. Taken together, these findings speak to the need to further consider the ways in which the sociopolitical context is shaping the formation and maintenance of close relationships. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Representational Dissimilarity of Faces and Places during a Working Memory Task is Associated with Subsequent Recognition Memory during Development.

Nearly 50 years of research has focused on faces as a special visual category, especially during development. Yet it remains unclear how spatial patterns of neural similarity of faces and places relate to how information processing supports subsequent recognition of items from these categories. The current study uses representational similarity analysis and functional imaging data from 9- and 10-year-old youth during an emotional n-back task from the Adolescent Brain and Cognitive Development Study 3.0 data release to relate spatial patterns of neural similarity during working memory to subsequent out-of-scanner performance on a recognition memory task. Specifically, we examine how similarities in representations within face categories (neutral, happy, and fearful faces) and representations between visual categories (faces and places) relate to subsequent recognition memory of these visual categories. Although working memory performance was higher for faces than places, subsequent recognition memory was greater for places than faces. Representational similarity analysis revealed category-specific patterns in face-and place-sensitive brain regions (fusiform gyrus, parahippocampal gyrus) compared with a nonsensitive visual region (pericalcarine cortex). Similarity within face categories and dissimilarity between face and place categories in the parahippocampus was related to better recognition of places from the n-back task. Conversely, in the fusiform, similarity within face categories and their relative dissimilarity from places was associated with better recognition of new faces, but not old faces. These findings highlight how the representational distinctiveness of visual categories influence what information is subsequently prioritized in recognition memory during development.

Similarity and dissimilarity relationships based graphs for multimodal change detection

Multimodal change detection (CD) is an increasingly interesting yet highly challenging subject in remote sensing. To facilitate the comparison of multimodal images, some image regression methods transform one image to the domain of the other image, allowing for images comparison in the same domain as in unimodal CD. In this paper, we begin by analyzing the limitations of previous image structure based regression models that only rely on similarity relationships. Then, we highlight the significance of incorporating dissimilarity relationships as a complementary approach to more comprehensively characterize and utilize the image structure. In light of this, we propose a novel method for multimodal CD called Similarity and Dissimilarity induced Image Regression (SDIR). Specifically, SDIR construct a similarity based k-nearest neighbors (KNN) graph and a dissimilarity based k-farthest neighbors (KFN) graph, where the former mainly characterizes the low-frequency information and the latter captures the high-frequency information in spectral domain. Therefore, the proposed SDIR that incorporates similarity (low-frequency) and dissimilarity (high-frequency) relationships enables to achieve better regression performance. After completing the image regression, we utilize a Markovian based fusion segmentation model to combine the change fusion and change extraction processes for improving the final CD accuracy. The proposed method’s effectiveness is demonstrated through experiments on six real datasets and compared with eleven advanced and widely used methods, achieving 5.6% improvements in the average Kappa coefficient. The source code is accessible at https://github.com/yulisun/SDIR.

Enhancing temperate grassland diversity and functionality: Crafting seed mixtures to align stakeholder interests and to increase establishment success

Grassland biodiversity is positively correlated to ecosystem productivity and resilience that secure net gains and functionality of such systems. Land-use change of grasslands is associated with local extinction of species and declining ecosystem services. Hence, the design of more diverse seed mixtures is crucial for successful species reintroduction and grassland functionality. Thus, we conducted a systematic review of the scientific literature on temperate grassland reseeding during the past 30 years. This generated a knowledge base of reseeding methods and success, and revealed knowledge gaps and mismatches in the design of seed mixtures created by different stakeholders. From 201 published studies, we extracted information on stakeholder groups and focus, starting conditions, species selection for the mixtures, and monitoring of reseeded grasslands. Our review showed: (i) There were five stakeholder groups with varying focus along a gradient of biodiversity control; in turn, the starting conditions of reseeded sites changed along a gradient of dissimilarity in relation to reference grasslands. (ii) The design of the grassland mixtures varied in species composition, seed origin, and seed quality. (iii) While mixtures aiming at a certain vegetation structure and biomass showed high establishment success, grassland reseeding with a biodiversity focus was less successful. (iv) The design of seed mixtures changed significantly during the past decades, since species numbers in mixtures, i.e., the biodiversity focus, and the proportion of forbs, which indicates lower productivity, decreased in most stakeholder groups. (v) The number of ecosystem services monitored, i.e., the proportion of multiple-to-single ecosystem services, also declined for most stakeholders. Such findings indicate a narrowing focus on specific grassland composition and functions by stakeholders, in contrast to current trends toward multiple ecosystem services. The different establishment success of stakeholders conducting temperate grassland reseeding call for knowledge transfer among groups to achieve higher establishment success in restoration and conservation professionals as seen among turf managers and farmers. Overall, the design of grassland mixtures needs to be revisited in the face of the current biodiversity losses and climate change.

Nutrient cycling aspects as possible ecosystem functional indicators of successional stage in Semideciduous seasonal forest, Rio de Janeiro state, Brazil

Semideciduous Seasonal Forest is a phytophysiognomy of Atlantic Forest with high plant richness but low representativeness in few remnants areas in different successional stages. The assessment of the degree of conservation of those areas helps to indicate whether there is a need for taking strategies to favor forest succession. Thus, the aim of this study was to identify litterfall and its nutrient content, accumulated litter biomass on topsoil, leaf litter decomposition, and topsoil (0–10 cm) chemical attributes as possible indicators of successional stages in areas of Seasonally Semideciduous Forest. We collected available information in literature on CAPES Portal and Google Scholar (May/2021 to February/2022) for Pinheiral municipality, State of Rio de Janeiro, Brazil, which were evaluated by multivariate analysis. Accumulated litter biomass, nutrient content (N, P, K) in total litterfall, pH and P availability in topsoil, leaf litter decomposition constant, and half-life time of leaf litter were the most sensitive attributes to indicate the successional stage in the study area, according to Principal Component Analysis. This multivariate analysis indicated that areas in early successional stage were associated with higher values of leaves contribution, half-life of leaf litterfall, contents of Ca and K in total litterfall, whereas areas in middle successional stage were associated with higher values of pH, total organic carbon, exchangeable Ca2+, K+, and Mg+, sum of bases and cation exchange capacity, and lower values of extractable acidity and exchangeable Al3+ in the topsoil. Areas in advanced stages of succession were associated to higher values of total litterfall and its nutrient content (N, K, Mg), accumulated litter biomass, available P in topsoil, and leaf litter decomposition constant. The Cluster multivariate analysis revealed that the areas in advanced successional stage presented high dissimilarity in relation to the areas in early and middle successional stage.

Does the brain sleep differently depending on intellectual abilities?

To compare the children's sleep electroencephalogram according to their intellectual profile. Children were grouped according to their Wechsler Intelligence Scale for Children (WISC) scores (17 with normal intelligence quotient [IQ, NIQ] and 24 with high IQ [HIQ]). Comparisons of spectral power between groups and its relationship with WISC scores were assessed using analyses of variance and linear regression models, adjusted for age and sex. Children with HIQ had more rapid eye movement (REM) sleep, especially late at night, and more power in slow-frequency bands during REM sleep than those with NIQ. There were also positive associations between the processing speed index and the spectral power in β bands in NREM sleep, and with the spectral power in α, σ, β, and γ bands in REM sleep, with different associations between groups. The enhanced power in slow bands during REM sleep in children with HIQ overlaps with that of typical REM sleep oscillations thought to be involved in emotional memory consolidation. The dissimilar relationships between spectral power and WISC scores in NIQ and HIQ groups may underlie functional differences in brain activity related to cognitive efficiency, questioning the direction of the relationship between sleep and cognitive functioning.

How do people communicate about sensory descriptors in social media? An investigation comprising floral descriptors, four beverages, and thirteen English‐speaking countries

AbstractThe internet has become a mainstay of modern‐day life, with people worldwide using social media platforms to discuss ideas and exchange opinions. In recent years, social media platforms have become a data source for research focusing on consumers' natural and spontaneous lexicons. The increased use of social media and virtual meetings means people can exchange ideas, and cultural boundaries have blurred. Thus, this study aims to investigate how culture influences the use of the beverage descriptor “floral” on social media for four different beverages when people share the same language. A social media study was performed, collecting data over 1 year in 13 English‐speaking countries: Australia, Canada, South Africa, the United Kingdom, Singapore, New Zealand, and seven Caribbean Islands. Words associated with four beverages (beer, cocktails, tea, and wine) and floral were filtered on social media mentions. A total of 258,221 mentions were obtained from different types of social media such as Twitter, Instagram, Facebook, and so forth. The mentions were filtered to obtain the frequency of words by country. Each beverage was analyzed separately, and contingency tables were arranged by country and descriptor. A correspondence analysis was performed on each contingency table to identify relative similarities and dissimilarities between the countries in the study. Overall, rose was the most cited floral descriptor, and there was a link between beer and wine descriptions. However, for cocktails and tea, the floral descriptors varied per country. Thus, it suggests that the impact of culture on the use of floral descriptors depends on the beverage being discussed.Practical ApplicationsThe results obtained in this study have relevance for people interested in sensory and specifically in beverage descriptions, as well as those involved in the alcohol industry, particularly those involved in beer and wine, and the non‐alcohol industry (tea). These results can drive the construction of applied and effective marketing strategic plans for the beverage and flavor industry in the areas covered by the study.

The Initiation and Growth of Transpressional Shear Zones Through Continental Arc Lithosphere, Southwest New Zealand

AbstractStructural analyses combined with new U‐Pb zircon and titanite geochronology show how two Early Cretaceous transpressional shear zones initiated and grew through a nearly complete section of continental arc crust during oblique convergence. Both shear zones reactivated Carboniferous faults that penetrated the upper mantle below Zealandia's Median Batholith but show opposite growth patterns and dissimilar relationships with respect to arc magmatism. The Grebe‐Indecision Creek shear zone was magma‐starved and first reactivated at ∼136 Ma as an oblique‐reverse fault, along which an outboard batholith partially subducted beneath Gondwana. This system nucleated at or above ∼20 km depth and propagated downward at 2–3 mm yr−1, accumulating at least 35–45 km of horizontal (arc‐normal) shortening by ∼124 Ma. In contrast, the magma‐rich George Sound shear zone first reactivated in the lower crust (∼55 km depth) at ∼124 Ma and grew upward at ∼3 mm yr−1, reaching the upper crust by ∼110 Ma. In this latter system, magmatism influenced shear zone architecture and drove its growth while subduction and oblique convergence ended. As magma entered the roots of the system and began to solidify, deformation was driven out of the lower crust and into the middle crust where the system widened by a factor of three when fold‐thrust belts formed on either side of a steep, central transpressional shear zone. This study illustrates how the reactivation of structural weaknesses localizes deformation at all depths in the lithosphere and shows how magma‐deformation feedbacks influence shear zone connectivity and built a batholith from the bottom up.

Unsupervised double weighted graphs via good neighbours for dimension reduction of hyperspectral image

ABSTRACT As the major research in pattern recognition, unsupervised dimension reduction is a challenging problem because of no label information. Most unsupervised dimension reduction methods usually construct similarity graph by k-nearest neighbour to preserve local structure in the low-dimensional subspace. However, k-nearest neighbour is calculated by Euclidean distance, which is sensitive to noise and outliers. And only considering local structure will reduce the classification accuracy. In this paper, a new unsupervised dimension reduction method called unsupervised double-weighted graphs via good neighbours (uDWG-GN) is proposed. First, uDWG-GN proposes a local structure Low-Rank Representation to learn similarity matrix and then uses the similarity matrix to find good neighbours of each sample. Second, according to good neighbours of the sample, uDWG-GN considers similar and dissimilar relationship between samples and constructs double-weighted graphs. Finally, based on norm, uDWG-GN finds the optimal projection matrix by maximizing the distance of dissimilar samples and minimizing the distance of similar samples. Experimental results on three hyperspectral images demonstrate the superiority and effectiveness of our method compared with other dimension reduction methods.

The Need for Speed: The Role of Employers in Immigrant Work Visa Acceleration and Approval

Why are some immigrant work visa applications processed and approved in a matter of days, while others languish for months before receiving a decision? We contend that the relative dissimilarity between a focal visa application and an employer’s past work visa filings is a key, yet unstudied, strategic value consideration affecting the sponsoring firm’s engagement with the regulatory bureaucracy. Using U.S. CIS administrative records obtained through the Freedom of Information Act detailing all H-1B visa applications from 2006 to 2015, we analyze employers’ acceleration of select applications through the “premium processing” program, which guarantees an initial visa decision in 15 days in exchange for a $1,225 per-application payment. We find that employers are more likely to use premium processing for immigrants whose countries of birth, prospective jobs, and educational experiences are dissimilar relative to the applications previously filed by that employer. Further, employers less frequently withdraw or abandon dissimilar applications, and request longer employment durations in these dissimilar applications. In contrast to prior arguments regarding immigrants’ regulatory and employment success, we argue that immigrants identical on observables and migration inclination may fare differently in the U.S. immigration system depending on their dissimilarity within the context of their sponsoring employer.

Love and politics: The influence of politically (dis)similar romantic relationships on political participation and relationship satisfaction

Abstract People are more likely to seek out romantic partners who are politically similar to themselves. Nonetheless, romantic partners who disagree politically do exist. This study examines the influence of political (dis)similarity in romantic relationships on both political participation and relationship satisfaction. We found that (1) people in politically similar romantic relationships are more satisfied in their relationships and more politically participative than those who are in dissimilar relationships, (2) discussion expressiveness mediates the relationships between political similarity and satisfaction, (3) discussion frequency and expressiveness mediate the relationship between political similarity and participation, and (4) whereas political conflict intensity mediates the relationship between political similarity and satisfaction, it does not affect participation. Findings indicate that the quality of discussion and conflict, not merely their occurrence, help explain the political and relational results of political (dis)similarity within romantic relationships.

Is there a continuum between speech and other oromotor tasks? evidence from motor speech disorders

ABSTRACT Background Oral diadochokinetic (DDK) tasks are widely used in the assessment of patients with motor speech disorders (MSD). They require the repetition of homogeneous and of heterogeneous syllables at a maximum rate. The nature of DDK tasks is a matter of debate: although they are usually considered as “non-speech”, given the involvement of real speech syllables, they have also been recognized to share more properties and requirements with speech as compared to other oromotor behaviours (i.e., non-speech gestures). Additionally, the production of heterogeneous syllables has been suggested to exhibit closer correspondence with speech given the production of a cluster of different syllables, as compared to the repetition of a monosyllable. Each DDK task being differently related to speech supports the assumption of a continuum between speech and other oromotor processes, in which tasks with increasingly speech-like properties may overlap to a larger extent with speech. Aim To test the potentially differential relationship between speech and DDK tasks in patients with MSD. Traditional views of MSD claim that speech and other oromotor behaviours are impaired in patients with dysarthria, while patients with AoS present with speech being exclusively compromised. This suggests that DDK tasks should be differently affected in these two MSD populations. Moreover, in the framework of a continuum, oromotor tasks sharing some characteristics with speech (i.e., heterogeneous DDK task) should also be impaired in patients with AoS. Method Syllabic rates of a sentence production (SP) task are contrasted with those of homogeneous and heterogeneous DDK tasks in three pathological populations: patients with dysarthria due to Parkinson’s Disease (PD, n = 10) or due to amyotrophic lateral sclerosis (ALS, n = 10) and patients with apraxia of speech (AoS, n = 10); and 30 matched neurotypical controls. Results While patients with PD show similar rates across the SP and the DDK tasks relative to control speakers, patients with ALS display significantly slower rates across all tasks as compared to matched controls. Patients with AoS show reduced performances in the SP and in the heterogeneous DDK task, but not on the repetition of homogeneous syllables. Conclusions The findings of this study confirm that the repetition of heterogeneous syllables shares more principles and properties with speech than the homogeneous DDK task. This dissimilar relationship between speech and the two types of DDK tasks points to the existence of a continuum among oromotor tasks.

A strategy to define applicability domains for read-across

The definition, characterisation and assessment of the similarity between target and source molecules are cornerstones of the acceptance of a read-across prediction to fill a data gap for a toxicological endpoint. There is much guidance and many frameworks which are applicable in a regulatory context, but as yet no formalised process exists by which to determine whether or not the properties of an analogue (or chemicals within a category) fall within an appropriate domain from which a reliable read-across prediction can be made. This investigation has synthesised much of the existing knowledge in this area into a practical strategy to enable the domain of a read-across prediction to be defined, in terms of chemistry (structure and properties), toxicodynamics and toxicokinetics. The strategy is robust, comprehensive, flexible, and can be implemented readily. It enables the relative similarity and dissimilarity, between target and source molecules, for both the analogue and category approaches, to be analysed and provides a basis for alternative scenarios such as read-across based on formation of a common metabolite or biological profile to be defiend. Herein, the read-across domains for the repeated dose toxicity of a group of triazoles and imidazoles have been evaluated. The most challenging aspect to this approach will continue to be determining what is an “acceptable” degree of similarity when performing read-across for a specific purpose.

Ethnic Differences in Context: Does Emotional Conflict Mediate the Effects of Both Team- and Individual-Level Ethnic Diversity on Emotional Strain?

Work teams are becoming increasingly heterogeneous with respect to their team members’ ethnic backgrounds. Two lines of research examine ethnic diversity in work teams: The compositional approach views team-level ethnic heterogeneity as a team characteristic, and relational demography views individual-level ethnic dissimilarity as an individual member’s relation to their team. This study compares and contrasts team-level ethnic heterogeneity and individual-level ethnic dissimilarity regarding their effects on impaired well-being (i.e., emotional strain) via team- and individual-level emotional conflict. Fifty teams of retail chain salespeople (n = 602) participated in our survey at two points of measurement. Based on the ethnic background of team members, we calculated team-level ethnic heterogeneity that applied to all members, and individual-level ethnic dissimilarity within the team that varied according to each member’s ethnic background. Multilevel path modeling showed that high levels of team-level ethnic heterogeneity were related to high levels of emotional strain via team-level emotional conflict. However, the opposite was found for individual-level ethnic dissimilarity. We discussed this difference by contextualizing individual-level ethnic dissimilarity in the team-level heterogeneity and social status of ethnic groups in society at large. Our findings suggest that the social status of the ethnic group to which team members belong may impact how ethnic diversity relates to team processes and well-being.

Influence of Forest Fragment Composition and Structure on Ground-Dwelling Arthropod Communities

Habitat fragmentation is the process of reducing habitat area while increasing the number and isolation of habitat patches. Although much of Indiana's land area was historically covered with contiguous forests, remaining forests are now heavily fragmented. This is especially true in northeastern Indiana where agriculture is the dominant land use cover type. Loss of functional forests in northeast Indiana could lead to a loss of biodiversity at a regional scale. Ground-dwelling arthropods have been used frequently as biological indicator taxa of forest health. We characterized 10 typical northeast Indiana forest plant communities and inventoried ground-dwelling arthropod communities within those forests. Plant community and environmental heterogeneity within forests were used to assess forest complexity, and ground-dwelling arthropod communities were compared to forest environmental characteristics. Our forest comparisons revealed plant community and structural heterogeneity differences. While overstory and understory diversity, compositional heterogeneity, and litter depth did have influence on arthropod communities' relative dissimilarities in nonmetric multidimensional scaling ordination plots, those communities were similar across all forest patches. However, those same environmental variables did not have direct influence on overall arthropod abundance, richness, or diversity. Even though differences did occur in forest structure and composition, arthropod communities had high similarity values, especially in August. As the forests in the region are similar in type and structure, between-forest comparisons of arthropod communities showed corresponding similarities in composition, abundance, richness, and diversity.

Using morphofunctional characteristics as a model of phytoplankton dynamics in a tropical reservoir

The study of phytoplankton morphological characteristics, using the morphology-based functional classification (MBFG), reflects the different abilities for absorption of light and nutrients, growth, mechanisms for preventing sedimentation and predation in the aquatic ecosystem and can be a model in simplification of the phytoplankton community dynamics in the reservoirs. This study that was developed in a tropical reservoir aimed to evaluate which phytoplankton morphofunctional characteristics are selected by the spatial and temporal heterogeneity in the reservoir, and how these characteristics are related to the environmental conditions. For this, phytoplankton and environmental variables were sampled in different sites along the spatial extent of the reservoir during dry and rainy periods. The lotic region showed the greatest environmental dissimilarity in relation to the other regions, both in the dry and rainy periods. Differences in density of all MBFG were verified along the spatial extent of the reservoir, with higher values in the lentic region, while differences between hydrological periods were verified for MBFG I (small organisms with a high surface/volume ratio), MBFG IV (medium-sized organisms without specialized traits) and MBFG VII (large mucilaginous colonies). The conditions of pH, temperature and turbidity were important in the selection of the morphofunctional characteristics and in MBFG dynamics. Therefore, the use of MBFG can be a form of simplification of the relationship between phytoplankton and environmental heterogeneity, reflecting the reservoir functioning.

COMBINING ABILITY AND GENETIC DIVERGENCE IN COTTON ( G. barbadense L.)

This experiment was conducted in order to estimate general and specific combining abilities effects and genetic divergence for yield and quality characters using the line x tester mating design. Seven lines and four testers along with their 28 crosses of (Gosssypium barbadense L.) were evaluated for yield and fiber characters at Sakha Agric. Res. Stat. during 2018 growing season. Analysis of variance revealed significant differences among the genotypes, parents and crosses for all studied characters, indicating the presence of considerable amount of genetic variability among the evaluated genotypes. The variance due to parents versus crosses was also significant for most studied characters indicating that significant heterosis could be expected incrosses for these characters and comparison will be much relevant. The variance due to males and females were also significant for most studied characters and majority than the variance due to parents (lines and testers), these results indicated that the experimental materials possessed considerable variability and the two types of combining ability were involved in the genetic expression of these characters. However line vs. tester showed highly significant differences for most studied traits, showing theimportance of both additive and non additive variance gene effects. Among the female parents (testers) Karshenky2 was the best combines for earliness index and micronaire reading. Giza 94 was the best general combines for earliness index , most yield and fiber characters. Giza45 and Giza 86 were predicted to be best general combines for fiber characters.While, Giza 93 has positive and significant general combining ability (GCA) for all the studied yield traits and fiber strength. The cross combinations Giza 86 x Giza 94 and Giza 93 x Giza 94 showed significant positive SCA values for boll weight, seed index and lint index. The dissimilarity coefficients among eleven cotton genotype corresponding to 55 possible comparisons showed that about 95% of the values were significant as Chi squares values. The eleven cotton parental genotypes evaluated in this study were grouped into five major clusters by using hierarchical clustering method on the basis of dissimilarity among parents and contribution of evaluated characters. The inter cluster distance was higher than the intra cluster indicating wide genetic divergent among the genotypes. The female parents Kar2, Suvin, Giza89*p s6 and Giza94 grouped at three wide clusters and divergent distance from each others. The extra-long varieties Giza 96, Giza 93and Giza 92 grouped at the same cluster and closely related with Giza 45 (cluster5) and divergent distance with the other groups. The male parents Giza 85, Giza90 and the female Kar2 grouped at the same cluster (1) and characterized as a good combiner for earliness index. The Egyptian variety Giza94 and the Indian genotype Suvin formed unique two groups (clusters 2 and 4) and pose most genes which controlling general combining ability for yield traits. The 36 genotypes were grouped into 12 major clusters based on relative dissimilarity among genotypes. The distribution of parental genotypes and their F1 heterozygous in dendrogram reflects a broad parallelism between divergence distance, general and specific combining ability. Parents for hybridization could be selected based on large inter cluster distance to isolate useful recombinants through segregates

Selection of BC1F3 populations of Santa Cruz type dwarf tomato plant by computational intelligence techniques

ABSTRACT The aim of this study was to estimate genetic divergence and select BC1F3 populations of dwarf tomato plant within the Santa Cruz segment by computational intelligence techniques. The experiment was conducted in a greenhouse in the Vegetable Crop Experimental Station of the Universidade Federal de Uberlândia (UFU), Monte Carmelo, MG, Brazil. A randomized block experimental design was used with 17 treatments and four replications. The genetic material evaluated comprised thirteen dwarf tomato plant populations obtained by a backcross and two self-fertilizations, plus both parents (recurrent and donor), and two commercial check varieties. The traits evaluated were mean fruit weight (MFW), soluble solids content (SSC), fruit diameter (FD), fruit length (FL), fruit shape (FS), pulp thickness (PT), number of locules (NL), distance between internodes, and acylsugar, β-carotene, and lycopene content. The data were analyzed by means testing, and genetic divergence was measured using Mahalanobis generalized distance by the unweighted pair group method with arithmetic mean (UPGMA) and through computational intelligence using Kohonen self-organizing maps (SOM). Genetic dissimilarity in relation to the donor parent could be confirmed through both methodologies. However, the SOM was able to detect differences and organize the similarities among the populations in a more consistent manner, resulting in a larger number of groups. In addition, the computational intelligence techniques allow the weight of each variable in formation of the groups to be ascertained. Among the BC1F3 populations, UFU-SC#3 and UFU-SC#5 stood out for agronomic traits, and UFU-SC#10 and UFU-SC#11 stood out for quality parameters.

Local bit-plane neighbour dissimilarity pattern in non-subsampled shearlet transform domain for bio-medical image retrieval.

This paper introduces a novel descriptor non-subsampled shearlet transform (NSST) local bit-plane neighbour dissimilarity pattern (NSST-LBNDP) for biomedical image retrieval based on NSST, bit-plane slicing and local pattern based features. In NSST-LBNDP, the input image is first decomposed by NSST, followed by introduction of non-linearity on the NSST coefficients by computing local energy features. The local energy features are next normalized into 8-bit values. The multiscale NSST is used to provide translational invariance and has flexible directional sensitivity to catch more anisotropic information of an image. The normalised NSST subband features are next decomposed into bit-plane slices in order to capture very fine to coarse subband details. Then each bit-plane slices of all the subbands are encoded by exploiting the dissimilarity relationship between each neighbouring pixel and its adjacent neighbours. Experiments on two computed tomography (CT) and one magnetic resonance imaging (MRI) image datasets confirms the superior results of NSST-LBNDP when compared to many recent well known relevant descriptors both in terms of average retrieval precision (ARP) and average retrieval recall (ARR).