Cluster analysis for multidimensional objects in fuzzy data conditions

This article presents many different areas of practical applications of multivariate cluster analysis under conditions of fuzzy initial data that are described in the literature. New algorithms and formula expressions are proposed for combining various multi-dimensional objects, the parameters of which are given by fuzzy-sets, into clusters along with calculating the coordinates of the centroids of their membership functions. Various types of clustering criteria are formulated in the form of minimizing the weighted average and the sum of distances between the centroids of objects and clusters presented in different metrics, as well as maximizing the distances between the centroids of different clusters. The formulations and mathematical models of three different NP-hard problems of multidimensional clustering in fuzzy-data conditions are proposed; while solving them any of the considered optimality criteria can be used. Heuristic algorithms for the approximate solution of two formulated problems have been developed. The algorithm for solving the 1st problem is illustrated with a numerical example. The obtained results can serve as a direction for further research and have wide practical applications.

Quantifying Threats to Biodiversity and Prioritizing Responses: An Example from Papua New Guinea

Accurately identifying threats to global biodiversity is the first step towards effectively countering or ameliorating them. However, such threats are usually only qualitatively categorized, without any comparative quantitative assessment of threat levels either within or across ecosystems. As part of recent efforts in Papua New Guinea to develop a long-term strategic plan for reducing threats to biodiversity at the national level, we developed a novel and quantitative method for not only assessing relative effects of specific biodiversity threats across multiple ecosystems, but also identifying and prioritizing conservation actions best suited for countering identified threats. To do so, we used an abbreviated quantitative SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis and multivariate cluster analysis to identify the most significant threats to biodiversity in Papua New Guinea. Of 27 specific threats identified, there were nine major threats (each >5% of total) which accounted for approximately 72% of the total quantified biodiversity threat in Papua New Guinea. We then used the information to identify underlying crosscutting threat drivers and specific conservation actions that would have the greatest probability of reducing biodiversity threats across multiple ecosystem realms. We categorized recommended actions within three strategic categories; with actions within each category targeting two different spatial scales. Our integrated quantitative approach to identifying and addressing biodiversity threats is intuitive, comprehensive, repeatable and computationally simple. Analyses of this nature can be invaluable for avoiding not only wasted resources, but also ineffective measures for conserving biodiversity.

Landscape-scale Remote Sensing and Classification of Pond and Lake Habitat Diversity in a Tropical City

Ponds and lakes are common freshwater habitats in urban landscapes, and often have a high biodiversity and conservation value. The importance of landscape-scale conservation of pond networks has recently been recognised, yet the categorisation and classification of pond network spatial structures is missing. Developing spatial methods and tools to characterise and understand pond networks is a critical first step to accurately conserve pond habitats and inhabiting species. This paper presents an inventory of ponds and lakes in Greater Kuala Lumpur, Malaysia, characterising their distribution, abundance and type. Remote sensing was first employed to map and characterise these habitats, followed by multivariate cluster analysis to classify and develop a typology of the ponds identified. Physicochemical data was collected from a sample (n=60) of ponds to compare with the remotely sensed pond classification. Results demonstrated that multi-source remote sensing can be highly accurate and effective in inventorying ponds and lakes of varying sizes. A total of 1013 ponds and lakes were identified within the Greater Kuala Lumpur region and were found to be highly environmentally heterogeneous. Typology clusters were driven by land cover rather than local physicochemical variables demonstrating that specific remotely-sensed variables may be sufficient proxies for certain chemical variables. Landscape-scale conservation and management of pond networks should utilise remote sensing tools, to establish pond network structure, and to maintain wide environmental heterogeneity among pond habitats. Incorporating remote sensing tools into pond conservation will ensure that effective pond conservation can be achieved and biodiversity protection can be maximised.

Intra-body dynamics of d-serine reflects the origin of kidney diseases

Introduction d-Serine, present only in trace amounts in humans, is now recognized as a biomarker of chronic kidney disease (CKD). CKD is heterogeneous in its original kidney diseases, whose diagnoses require kidney biopsy. In this study, we examined whether the intra-body dynamics of d-serine, indexed by its blood and urinary levels, reflects the origin of kidney diseases. Methods Patients with six kinds of kidney disease undergoing kidney biopsy were enrolled in a single center. Levels of d- and l-serine were measured using two-dimensional high-performance liquid chromatography. The associations between the origin of kidney diseases and the intra-body dynamics of d-serine were examined using multivariate cluster analyses. Results Unlike the non-CKD profile, patients with CKD showed broadly-distributed profiles of intra-body dynamics of d-serine. The plasma level of d-serine plays a key role in the detection of kidney diseases, whereas a combination of plasma and urinary levels of d-serine distinguished the origin of CKD, especially lupus nephritis. Conclusion Intra-body dynamics of d-serine have the potential to predict the origin of kidney diseases. Monitoring of d-serine may guide specific treatments for the origin of kidney diseases.

Trajectories of Symptom Severity in Children with Autism: Variability and Turning Points through the Transition to School

This study examined the trajectories of autistic symptom severity in an inception cohort of 187 children with ASD assessed across four time points from diagnosis to age 10. Trajectory groups were derived using multivariate cluster analysis. A two trajectory/cluster solution was selected. Change in trajectory slopes revealed a turning point marked by plateauing in symptom reduction during the period of transition to school (age 6) for one of the two trajectories. Trajectories were labelled: Continuously Improving (27%) and Improving then Plateauing (73% of sample). Children in the two trajectories differed in levels of symptom severity, language, cognitive, and adaptive functioning skills. Study findings can inform the development of more personalized services for children with ASD transitioning into the school system.

Genetic parameters for worm resistance in Santa Inês sheep using the Bayesian animal model

Objective: The objective of this study was to estimate the genetic parameters for worm resistance (WR) and associated characteristics, using the linear-threshold animal model via Bayesian inference in single- and multiple-trait analyses.Methods: Data were collected from a herd of Santa Inês breed sheep. All information was collected with animals submitted to natural contamination conditions. All data (number of eggs per gram of feces [FEC], Famacha score [FS], body condition score [BCS], and hematocrit [HCT]) were collected on the same day. The animals were weighed individually on the day after collection (after 12-h fasting). The WR trait was defined by the multivariate cluster analysis, using the FEC, HCT, BCS, and FS of material collected from naturally infected sheep of the Santa Inês breed. The variance components and genetic parameters for the WR, FEC, HCT, BCS, and FS traits were estimated using the Bayesian inference under the linear and threshold animal model.Results: A low magnitude was obtained for repeatability of worm-related traits. The mean values estimated for heritability were of low-to-high (0.05 to 0.88) magnitude. The FEC, HCT, BCS, FS, and body weight traits showed higher heritability (although low magnitude) in the multiple-trait model due to increased information about traits. All WR characters showed a significant genetic correlation, and heritability estimates ranged from low (0.44; single-trait model) to high (0.88; multiple-trait model).Conclusion: Therefore, we suggest that FS be included as a criterion of ovine genetic selection for endoparasite resistance using the trait defined by multivariate cluster analysis, as it will provide greater genetic gains when compared to any single trait. In addition, its measurement is easy and inexpensive, exhibiting greater heritability and repeatability and a high genetic correlation with the trait of resistance to worms.

Taxonomic updates in Amphitecna (Bignoniaceae): A new Mexican species and the re-establishment of the giant-leaved A. megalophylla

In this study, we analyzed the morphological affinities of the 24 species of Amphitecna based on detailed morphological studies and multivariate cluster analyses. Our results suggest that the genus Amphitecna includes six morphological groups that can be easily distinguished based on floral and fruits characteristics: A. donnell-smithii group, A. macrophylla group, A. megalophylla group, A. molinae group, A. spathicalyx group, and A. steyermarkii group. A new species from Mexico, Amphitecna fonceti, is described. This new species is clearly differentiated by the predominantly ramiflorous inflorescences bearing multiple flowers per shoot, buds rounded at the apex, large flowers with a transverse fold in the corolla throat, calyx surface pubescent and strongly costate, and fruits elliptic, apiculate at the apex. We discuss the characteristics of each morphological group and their geographical distribution, provide a detailed description of the new species including ethnobotany notes, and propose the re-establishment of the giant-leaved species A. megalophylla.