Morpho-colorimetric characterization by image analysis to identify diaspores of wild plant species

Digital images of ex situ germplasm stored in the Sardinian Germplasm Bank (BG-SAR) were used for the application of image analysis techniques at the Stazione Sperimentale di Granicoltura per la Sicilia. The analysed accessions refer to 148 taxonomic units belonging to 102 genera and 47 families, typical of the Sardinian flora, and of the Mediterranean basin in general.The images of diaspores were acquired by a flatbed scanner and elaborated with a macro specially developed for the morphometric and colorimetric measurements. This method allowed carrying out a database for the characterization of autochthonous germplasm in entry to the bank and the realization of statistic classifiers for the discrimination of genera and species within the following families: Apiaceae, Boraginaceae, Caryophyllaceae, Cistaceae, Fabaceae and Scrophulariaceae. Such classifiers, based on the linear discriminant analysis (LDA) technique and checked by cross-validation, showed a performance included between 74.3% and 96.4%.In addition, for the genus Astragalus, it was possible to elaborate a classifier able to identify very similar taxa of a species complex, obtaining a performance between 83.7% and 100%. Such analysis proved the validity of the methodology also from the taxonomic point of view.Suggestions for subsequent methodological progress, which could offer applications in other research issues, such as ecological analysis, soil seed bank and archaeological botany are proposed.     

Focus: A Multifaceted Battle Against Cancer: Extracting Knowledge from Chemical Imaging Data Using Computational Algorithms for Digital Cancer Diagnosis

Fourier transform infrared (FTIR) spectroscopic imaging is an emerging microscopy modality for clinical histopathologic diagnoses as well as for biomedical research. Spectral data recorded in this modality are indicative of the underlying, spatially resolved biochemical composition but need computerized algorithms to digitally recognize and transform this information to a diagnostic tool to identify cancer or other physiologic conditions. Statistical pattern recognition forms the backbone of these recognition protocols and can be used for highly accurate results. Aided by biochemical correlations with normal and diseased states and the power of modern computer-aided pattern recognition, this approach is capable of combating many standing questions of traditional histology-based diagnosis models. For example, a simple diagnostic test can be developed to determine cell types in tissue. As a more advanced application, IR spectral data can be integrated with patient information to predict risk of cancer, providing a potential road to precision medicine and personalized care in cancer treatment. The IR imaging approach can be implemented to complement conventional diagnoses, as the samples remain unperturbed and are not destroyed. Despite high potential and utility of this approach, clinical implementation has not yet been achieved due to practical hurdles like speed of data acquisition and lack of optimized computational procedures for extracting clinically actionable information rapidly. The latter problem has been addressed by developing highly efficient ways to process IR imaging data but remains one that has considerable scope for progress. Here, we summarize the major issues and provide practical considerations in implementing a modified Bayesian classification protocol for digital molecular pathology. We hope to familiarize readers with analysis methods in IR imaging data and enable researchers to develop methods that can lead to the use of this promising technique for digital diagnosis of cancer.     

Using Echo Ultrasound from Schooling Fish to Detect and Classify Fish Types

Fish finders have already been widely available in the fishing market for a number of years.However,the sizes of these fishfinders are too big and their prices are expensive to suit for the research of robotic fish or mini-submarine.The goal of thisresearch is to propose a low-cost fish detector and classifier which suits for underwater robot or submarine as a proximity sensor.With some pre-condition in hardware and algorithms,the experimental results show that the proposed design has good per-formance,with a detection rate of 100 % and a classification rate of 94 %.Both the existing type of fish and the group behaviorcan be revealed by statistical interpretations such as hovering passion and sparse swimming mode.     

EMAP-Wetlands: A sampling design with global application

The U.S. Environmental Protection Agency (EPA) initiated the Environmental Monitoring and Assessment Program (EMAP) in 1988. The wetland component (EMAP-Wetlands) is designed to provide quantitative assessments of the current status and long-term trends in the ecological condition of wetland resources. EMAP-Wetlands will develop a wetland monitoring network and will identify and evaluate indicators that describe and quantify wetland condition. The EMAP-Wetlands network will represent a probability sample of the total wetland resource. The EMAP sample is based on a triangular grid of approximately 12,600 sample points in the conterminous U.S. The triangular grid adequately samples wetland resources that are common and uniformly distributed in a region, such as the prairie pothole wetlands of the Midwest. However, the design is flexible and allows the base grid density to be increased to adequately sample wetland resources, such as the coastal wetlands of the Gulf of Mexico, which are distributed linearly along the coast. The Gulf sample network required a 49-fold increase in base grid density. EMAP-Wetlands aggregates the 56 U.S. Fish and Wildlife Service's (FWS) National Wetland Inventory (NWI) categories (Cowardin et al. 1979) into 12 functionally similar groups (Leibowitz et al. 1991). Both the EMAP sample design and aggregated wetland classes are suitable for global inventory and assessment of wetlands.The research described in this report has been funded by the U.S. Environmental Protection Agency. This document has been prepared at the EPA Environmental Research Laboratory in Corvallis, OR, through contract No. 68-C8-0006 to Man Tech Environmental Technology, Inc. This paper has been subjected to the Agency's peer and administrative review and approved for publication. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.     

Biomechanical rationale of coronary artery bypass grafting of multivessel disease

The biomechanical model of human coronary arteries was modified for improving the quality of diagnosis and surgical treatment for coronary heart disease. The problem of hemodynamics in the left coronary artery with multivessel bed disease – 45% stenosis of the anterior descending branch and 75% stenosis of the circumflex branch – was particularly considered. Numerical simulation of the coronary arterial bypass of the main trunk was carried out to estimate the functional condition of the coronary arteries after restoring myocardial blood supply by surgery.     

Integrated palaeoecological and historical data in the service of fine-resolution land use and ecological change assessment during the last 1000 years in Rõuge, southern Estonia

Aims Our aim is to reconstruct decadal scale development of historical landscapes during the last 1000 years by means of fossil pollen analysis of annually laminated lake sediments, and detailed historical maps and documents. Location Lake Rõuge Tõugjärv (Estonia), a small lake with annually laminated lake sediments situated in a dense prehistoric setting. Methods The chronology of the palaeodata is based on the annual laminations supported by AMS ¹⁴C and ²¹⁰Pb dating and ¹³⁷Cs, ²⁴¹Am, and spheroidal carbonaceous particle marker horizons. The time‐scale and resolution allows fine sampling (the pollen samples generally comprise 3.5 years) and vegetation change reconstruction. Relevant source area of pollen (RSAP) of the lake was estimated, and the statistical zonation, rate of change, palynological richness, and DCA and PCA ordinations were generated on the basis of the pollen data. The historical calibration data set (maps, numerical information on population, domestic stock, farmland division, etc.) is based on archival material preserved in the Estonian Historical Archives. Results The topmost part (0–180 cm) of the sediment column of Lake Rõuge Tõugjärv, covering the last 1000 years, is visibly laminated carbonaceous gyttja. The varve chronology extends from ad 2000 to ad 1339, with a cumulative ± 9‐year error estimate. Beyond this the chronology is extrapolated using the ¹⁴C date and varve age–depth estimations. The simulation of the RSAP of Lake Tõugjärv shows that the major portion of the pollen loading originating from local vegetation is derived from plants growing within 2000 m of the sampling site. The pollen record divides into five statistically significant subgroups, which fall on the PCA plot into three clusters reflecting the general openness–closedness of the landscape. During the period between ad 1000 and 1200 (RT 1) the Rõuge area was generally wooded with birch, spruce and pine forests. The advancement of extensive farming gradually opened up the landscape between ad 1200 and 1650 (RT 2 and RT 3). The maximum openness of the landscape was reached between ad 1650 and 1875 (RT 4), with the most open period in the late eighteenth century. Historical maps from 1684 and 1870–99 and available quantitative data on population, domestic stock, farmland division, etc. show the same trend. The pollen data covering the last 125 years, and maps from 1935 and 1995, show the reduction of arable land in RSAP of the lake under investigation and the reduction of open land to an extent comparable with the end of the seventeenth century. Main conclusions The formation and development of the cultural landscape at Rõuge over the last 1000 years is characterized by rapid changes in floristic richness and rates of vegetation change attributed to certain historic processes in the RSAP. Five phases of landscape and social development are clearly distinguished during the last 1000 years. The decadal scale vegetation response to human‐induced forcing agrees with historical maps and documents and could be used for past landscapes prior to the period with solid historical data.     

A unifying theory for methods of systematic analysis

A unifying theory for systematic analysis states that a number of methods should be used jointly to cope with various kinds of data; also that groups should be as consistent as possible, be made with least information loss, and where needed, be polythetic. A test of relationship, homogeneity, can use various kinds of data. It can take account of the internal variation of aggregate items such as genera. It can give due emphasis to smaller clusters that have likely important contexts of external items. It helps in analysing trends, cores and hazes in dendrograms. A proposed detector for formal groups can be based on measures of isolation, identifiability and inclusiveness. Non-mathematical, inter-item reaction tests such as hybridization and serology can also be used in grouping. All relationship data are used polythetically to reveal natural groups. This leads to a unified informational concept for taxa. This is more useful than the biological species concept that is restricted to inter-breeding data. All the methods appear to be analogues of the powerful human grouping instinct. The resulting compatibility is important as precise methods are needed mainly when the data are too complex for the mind to use reliably. Cladograms can be made by self-graded deweighting of homogeneity and agglomerative clustering. Unlike classical cladistics this can reveal any polythetic group. Finding the derived states for making cladograms is often much too hypothetical for a fully cladistic approach to be properly precise. Instead, where the evidence is weak, a milder strength of graded deweighting is used for the cladistic properties, which help to show relationships along with the others. Axiomatic failures of other classes of grouping methods are discussed. Unavoidable remnants of instinctive processing lower the precision of all the methods. The Uniter computer program, based on the theory, is tested with finely graded values of artificially ‘evolved’ items and with coarsely coded cladistic data. The results show that with natural data, the program should act as a fairly sensitive probe of past evolutionary branching. Another test shows how specimens from species complexes can be grouped and how distinctions between groups are analysed.