Segmentation of transitional cell carcinoma nuclei by nonsupervised thresholding in different color spaces

OBJECTIVE: To develop a method for nonsupervised thresholding of transitional cell carcinoma nuclei of hematoxylin-eosin-stained histologic sections. STUDY DESIGN: For grayscale, RGB, HSL and L*a*b* thresholding we used an extension of a clustering method, based on a between-class/within-class criterion, applying optimal gray-level thresholding to distributions of R, G, B, or H and S or L* color domains. Algorithms were tested on 20 hematoxylin-eosin-stained sections of bladder carcinomas. RESULTS: Results were compared with corresponding results of manually selected nuclear areas. Images were compared pixel to pixel with matching reference images. Grayscale automatic thresholding presented unacceptably low pixel specificity, which complicated further nuclear segmentation. Nonsupervised thresholding in RGB or HSL, as well as semimanual thresholding in L*a*b* color space demonstrated significantly better accuracy and high values of pixel specificity and sensitivity, which permitted errors of only 4.27-5.83% in the subsequent mean area estimation of the transitional cell carcinoma nuclei. CONCLUSION: Nonsupervised multispectral thresholding in RGB or HSL color space extends single graylevel thresholding techniques to multilevel thresholding. This seems to be an effective, relatively simple and fast alternative to the widely used automatic grayscale or manual color thresholding for segmentation of nuclei in routine histologic sections.     

Colorimetry for the stain technologist. IV. Analysis of the components of color difference

Total color differences have been calculated for various pairs of stained microscopic substrates. The latter include azure B/eosin stained blood cells and Papanicolaou stained cells from the uterine cervix. Both the CIE L*u*v* and L*a*b* color spaces have been used. Total color differences have been analyzed in terms of lightness, hue and chroma components. Various discrepancies have been noted among these components, especially the chroma difference, for the two spaces. It is concluded that current color-difference formulae are less than perfect, although they can provide much useful information.     

Technical note: quantitative measures of iris color using high resolution photographs

Our understanding of the genetic architecture of iris color is still limited. This is partly related to difficulties associated with obtaining quantitative measurements of eye color. Here we introduce a new automated method for measuring iris color using high resolution photographs. This method extracts color measurements in the CIE 1976 L*a*b* (CIELAB) color space from a 256 by 256 pixel square sampled from the 9:00 meridian of the iris. Color is defined across three dimensions: L* (the lightness coordinate), a* (the red-green coordinate), and b* (the blue-yellow coordinate). We applied this method to a sample of individuals of diverse ancestry (East Asian, European and South Asian) that was genotyped for the HERC2 rs12913832 polymorphism, which is strongly associated with blue eye color. We identified substantial variation in the CIELAB color space, not only in the European sample, but also in the East Asian and South Asian samples. As expected, rs12913832 was significantly associated with quantitative iris color measurements in subjects of European ancestry. However, this SNP was also strongly associated with iris color in the South Asian sample, although there were no participants with blue irides in this sample. The usefulness of this method is not restricted only to the study of iris pigmentation. High-resolution pictures of the iris will also make it possible to study the genetic variation involved in iris textural patterns, which show substantial heritability in human populations.     

Hair color measurement and variation

Pigmentation of hair in humans has been investigated by medical scientists, anthropologists and, more recently, by forensic scientists. In every investigation, hair color must first be defined by the researchers. Subjective color assessment inhibits the reproducibility of experiments and the direct comparison of results. The aim of this study was to objectively measure human hair color and examine the variation found in a population with European ancestry, using the CIE L*a*b* color space. Observer-perceived hair colors were compared with self-reported hair colors and the color as measured by reflective spectrophotometry of 132 subjects of European ancestry. The presented data show that self-reported hair colors and observer-reported colors are similar; however, these categories are not necessarily the best way to categorize hair color for quantitative research. Using a two-step cluster analysis, hair color can be divided into categories or clusters based on spectrophotometric measurements in the CIE L*a*b* color space and these clusters can be well discriminated from each other. This separation is primarily based on the b* (yellow) color component and the clusters show agreement to observer-reported colors. This study illustrates the possibilities for and necessity of objectively defining the hair color phenotype for various downstream applications.     

Categorization and discrimination of "chick-a-dee" calls by wild-caught and hand-reared chickadees

Bloomfield and Sturdy [Bloomfield, L.L., Sturdy, C.B. All chick-a-dee calls are not created equally. Part I. Open-ended categorization by sympatric and allopatric chickadees. Behav. Proc., in press] previously reported that black-capped chickadees (Poecile atricapillus) discriminate conspecific from heterospecific (mountain chickadee, P. gambeli) 'chick-a-dee' calls, and their ability to accurately discriminate and classify the calls as belonging to separate species' defined categories was largely unaffected by their prior experience with mountain chickadees and their calls. To further examine the potential influence of experience on discrimination and categorization, we compare wild-caught black-capped chickadees, wild-caught mountain chickadees, and black-capped chickadees hand-reared among either adult laboratory-housed black-capped chickadees or adult laboratory-housed mountain chickadees on a true category/pseudo category chick-a-dee call discrimination task. Irrespective of group assignment, hand-reared birds performed as well as wild-caught birds and did not show a conspecific- or rearing-specific advantage in discrimination, categorization or memorization of chick-a-dee calls. While vocal learning is under the influence of ontogenetic experience, the results derived from the current methods suggest that experience (or a lack thereof) does not affect categorization and memorization abilities.     

养殖条件下山女鳟银化体色个体生产性状

以山女鳟(Oncorhynchus masou masou)群体中出现的银化体色个体为研究对象,系统研究了在人工养殖条件下银化体色个体在群体中所占比率、银化体色个体与正常体色个体的体色差异,以及银化体色个体生长性状等.结果表明:①群体中不同家系间银化体色个体所占比率在O～0.21范围内,采用3×2列联表法进行卡方检验,...     

金叶银杏半同胞子代无性系的叶色和色素含量变化及呈色机制分析

对4月份至11月份金叶银杏‘万年金'( Ginkgo biloba ‘Wannianjin')32个半同胞子代无性系与亲本的叶色差异进行比较;比较了不同色系叶片的色素含量和比值及叶色参数(L*、a*和b*)的变化,分析了叶色参数与叶片色素含量的相关性;并观察了不同色系的叶绿体超微结构。结果表明：32个半同胞子代无性系可被分为金黄、浅黄、草绿和蓝绿4个色系。随时间推移,草绿和蓝绿色系叶片的总叶绿素( Chl)、叶绿素a( Chla)、叶绿素b( Chlb)和类胡萝卜素( Car)含量均呈“双峰型”变化趋势,Car/Chl和Car/Chla比值的变幅均较小;而金黄和浅黄色系叶片的上述色素含量呈“升高—降低—升高”变化趋势,Car/Chl和Car/Chla比值总体呈“迅速下降—相对稳定—缓慢升高”的变化趋势。各色系叶片的上述色素含量在夏季均不同程度下降,Car/Chlb比值变化差异较大,且金黄和浅黄色系的各色素含量均低于草绿和蓝绿色系。随时间推移,金黄和浅黄色系叶片的L*、a*和b*值以及草绿和蓝绿色系叶片的L*和b*值均先降低后升高,后2个色系的a*值则先升高后下降;并且,前2个色系的L*和b*值总体上显著高于后2个色系,而a*值则总体上低于后2个色系。金黄色系的Chla和Chl含量与L*和a*值显著负相关,而其Car/Chl和Car/Chla比值则与L*、a*和b*值显著或极显著正相关;浅黄色系的Chlb含量与a*值显著负相关,其Car/Chla比值与L*和b*值以及Car/Chlb比值与a*值均显著正相关;草绿色系的Chla含量与L*值显著负相关,其Car/Chla比值与L*和b*值以及Car/Chlb比值与a*值均显著正相关;这3个色系叶片的其余指标间以及蓝绿色系叶片的各指标间均无显著相关性。观察结果显示：金黄和浅黄色系的叶绿体基粒片层发育不健全,基粒片层可见但排列较疏松,且无明显垛叠,分布范围小而稀疏;蓝绿和草绿色系叶绿体的基粒类囊体垛叠层数均较多,基粒片层发达且排列紧致、整齐,分布范围大而稠密。综合分析结果表明：‘万年金'4个色系半同胞子代无性系叶片的呈色差异和叶色变化由多种因素控制,其中,Car/Chl和Car/Chla比值高且叶绿体基粒片层发育不健全是叶片呈黄色的主要原因。     

Protein arrangement factor: a new photosynthetic parameter characterizing the organization of thylakoid membrane proteins

A proper spatial distribution of photosynthetic pigment‐protein complexes – PPCs (photosystems, light‐harvesting antennas) is crucial for photosynthesis. In plants, photosystems I and II (PSI and PSII) are heterogeneously distributed between granal and stromal thylakoids. Here we have described similar heterogeneity in the PSI, PSII and phycobilisomes (PBSs) distribution in cyanobacteria thylakoids into microdomains by applying a new image processing method suitable for the Synechocystis sp. PCC6803 strain with yellow fluorescent protein‐tagged PSI. The new image processing method is able to analyze the fluorescence ratios of PPCs on a single‐cell level, pixel per pixel. Each cell pixel is plotted in CIE1931 color space by forming a pixel‐color distribution of the cell. The most common position in CIE1931 is then defined as protein arrangement (PA) factor with xy coordinates. The PA‐factor represents the most abundant fluorescence ratio of PSI/PSII/PBS, the ‘mode color’ of studied cell. We proved that a shift of the PA‐factor from the center of the cell‐pixel distribution (the ‘median’ cell color) is an indicator of the presence of special subcellular microdomain(s) with a unique PSI/PSII/PBS fluorescence ratio in comparison to other parts of the cell. Furthermore, during a 6‐h high‐light (HL) treatment, ‘median’ and ‘mode’ color (PA‐factor) of the cell changed similarly on the population level, indicating that such microdomains with unique PSI/PSII/PBS fluorescence were not formed during HL (i.e. fluorescence changed equally in the whole cell). However, the PA‐factor was very sensitive in characterizing the fluorescence ratios of PSI/PSII/PBS in cyanobacterial cells during HL by depicting a 4‐phase acclimation to HL, and their physiological interpretation has been discussed.     

Thresholds of color attribute differences in detecting camouflaged textures

We examined the threshold at which a camouflaged color texture pattern (target) embedded in a surrounding colored texture pattern (background) was discriminated by making the difference between their color distributions serve as a cue. The texture consisted of 900 colored disks. The color applied to the disk was chosen from a normal distribution with the mean and the standard deviation set beforehand. The mean of the background's distribution was a standard achromatic color set at L*=40, u*=0, and v*=0 of CIELUV. In experiment 1, the mean of the target's color distribution was shifted from the background's one. The threshold for the mean of the target's color distribution depended on the standard deviation and increased as the standard deviation became bigger. In experiment 2, the standard deviation of the target's color distribution was shifted. There was the slight dependence of threshold of the standard deviation of the target's distribution on that of the background's distribution. In experiment 3, both of the mean and the standard deviation of the target's color distribution were shifted at the same time. The threshold was not determined by each of the mean and the standard deviation independently. There seemed to be some compensating contribution between them to each other. The threshold could be characterized by Doyle metric or modified Doyle metric.     

Normalization of multicolor fluorescence in situ hybridization (M-FISH) images for improving color karyotyping.

BACKGROUND: Multiplex or multicolor fluorescence in situ hybridization (M-FISH) is a recently developed cytogenetic technique for cancer diagnosis and research on genetic disorders. By simultaneously viewing the multiply labeled specimens in different color channels, M-FISH facilitates the detection of subtle chromosomal aberrations. The success of this technique largely depends on the accuracy of pixel classification (color karyotyping). Improvements in classifier performance would allow the elucidation of more complex and more subtle chromosomal rearrangements. Normalization of M-FISH images has a significant effect on the accuracy of classification. In particular, misalignment or misregistration across multiple channels seriously affects classification accuracy. Image normalization, including automated registration, must be done before pixel classification. METHODS AND RESULTS: We studied several image normalization approaches that affect image classification. In particular, we developed an automated registration technique to correct misalignment across the different fluor images (caused by chromatic aberration and other factors). This new registration algorithm is based on wavelets and spline approximations that have computational advantages and improved accuracy. To evaluate the performance improvement brought about by these data normalization approaches, we used the downstream pixel classification accuracy as a measurement. A Bayesian classifier assumed that each of 24 chromosome classes had a normal probability distribution. The effects that this registration and other normalization steps have on subsequent classification accuracy were evaluated on a comprehensive M-FISH database established by Advanced Digital Imaging Research (http://www.adires.com/05/Project/MFISH_DB/MFISH_DB.shtml). CONCLUSIONS: Pixel misclassification errors result from different factors. These include uneven hybridization, spectral overlap among fluors, and image misregistration. Effective preprocessing of M-FISH images can decrease the effects of those factors and thereby increase pixel classification accuracy. The data normalization steps described in this report, such as image registration and background flattening, can significantly improve subsequent classification accuracy. An improved classifier in turn would allow subtle DNA rearrangements to be identified in genetic diagnosis and cancer research.     

Long-term exposure to enhanced ultraviolet-B radiation in the sub-arctic does not cause oxidative stress in Vaccinium myrtillus

The aim of this work was to assess whether or not oxidative stress had developed in a dwarf shrub bilberry ( Vaccinium myrtillus L.) under long-term exposure to enhanced levels of ultraviolet-B (u.v.-B) radiation. The bilberry plants were exposed to increased u.v.-B representing a 15% stratospheric ozone depletion for seven full growing seasons (1991–1997) at Abisko, Swedish Lapland (68°N). The oxidative stress was assessed on leaves and stems by analysing ascorbate and glutathione concentrations, and activities of the closely related enzymes ascorbate peroxidase (EC 1.11.1.11) and glutathione reductase (EC 1.6.4.2). The affects of autumnal leaf senescence and stem cold hardening on these variables were also considered. The results showed that the treatment caused scarcely any response in the studied variables, indicating that u.v.-B flux representing a 15% ozone depletion under clear sky conditions is not sufficient to cause oxidative stress in the bilberry. It is suggested that no strain was evoked since adaptation was possible under such u.v.-B increases. The studied variables did, however, respond significantly to leaf senescence and especially to stem cold hardening.     

5种野牡丹属植物花色素成分及影响花色呈色因子分析

为明确野牡丹属(Melastoma L.)植物花瓣的色素成分和呈色机理,为花色育种提供参考。以野牡丹(M.candidum)、白花野牡丹(M.candidum f.albiflorum)、印度野牡丹(M.malabathiricum)、白花印度野牡丹(M. malabathricumvar.alba)、毛稔(M.sanguinrum)5种野牡丹属植物材料,采用目测法、RHSCC比色法和色差仪测定花瓣表型,应用化学显色法、紫外分光光度法对花色素成分及含量进行初步分析与测定,通过徒手切片组织切片法观察花瓣表皮细胞的显微结构和分布特点,测定花瓣pH值、可溶性糖及可溶性蛋白含量等生理指标分析对花色的影响。结果显示,野牡丹属植物花瓣不含叶绿素和类胡萝卜素,紫罗兰色系主要含花青素苷和黄酮类化合物,白色系主要含黄酮类化合物。野牡丹和毛稔花色素分布于上、下表皮,印度野牡丹花色素分布于上、下表皮和栅栏组织,白花野牡丹和白花印度野牡丹花瓣没有发现色素积累;紫罗兰色系野牡丹上表皮细胞呈圆锥形突起,白色系野牡丹上表皮细胞呈不规则的扁平状,它们下表皮细胞全呈不规则的扁平状。野牡丹属植物花色明度L*随花瓣颜色变深而降低,明度L*与红度a*呈极显著负相关、与蓝度b*呈极显著的正相关。花瓣中花青素苷含量与其明度L*和蓝度b*呈显著负相关,pH值与花瓣红度a*呈现显著的负相关。研究表明,野牡丹属植物花色主要由花青素苷决定,花青素苷含量、色素分布、上表皮细胞形状等是引起花色呈现多样的主要因子。     

No female mate choice in Mallee dragon lizards, Ctenophorus fordi

Aspects of sexual selection were studied in a sexually monomorphic Australian agamid lizard (Ctenophorus fordi), in particular with respect to the sensory exploitation hypothesis. In enclosure trials, females were offered the choice between large vs. small males and, in a different experiment, males with blue vs. normal head color. The rationale for these experiments was: firstly, to establish if females actively solicit copulations; secondly, if so, do females solicit copulations non-randomly with respect to male size (because large males may have access to food resources); thirdly, if male coloration is manipulated to match traits of congeneric, conspicuous and sexually dimorphic species, do females show preference for this novel trait (in accordance with the sensory exploitation hypothesis). The corresponding manipulations were also made in a free-living population where the distribution of females on the home ranges of color-manipulated males were monitored. Blue-headed males were accepted as mating partners both in the staged mating trials and in the natural population. Females appeared not to express any kind of active or passive mate choice (rejection); in only one out of 62 trials did a female approach a male herself rather than being approached by the male(s). There was no discrimination against any male category regardless of size or color within a female's receptive period and the manipulation of male head color in the natural population did not result in spatial re-distribution of females. Thus, a female appears to mate unselectively within her receptive period. Rejection behaviors were used only outside of the receptive period to communicate, to all males, that the female is not receptive.     

ON THE PHYLOGENY AND HIGHER CLASSIFICATION OF THE OLIGOCHAETA

Abstract— The 50 oligochaete taxa representing all families of “opisthoporous” oligochaetes (Aliuroididae, earthworms and aquatic “megadriles”) together with two representatives of the Haplotaxidac and three examples of “microdiles” were subjected to cladistic analysis using the PAUP program. Sixty-eight characters used in the analyses were derived from a comprehensive range of somatic and genital systems. The optimal result, in terms of maximal number of characters and taxa and of parsimony, produced two trees (consistency index 0.362) differing only in the placement of the monotypic clade for the family Lumbriculidae. From a line originating from the presumed octogonadial ancestor, the following branches were derived, in sequence from the basal to most derived (new taxa asterisked): subclass Randiellata* (order Randiellida*, Randiellidae); subclass Tubificata* (order Tubificida, Tubincidae, Naididae computed and others not computed); subclass Lumbriculata* (order Lumbriculida, Lumbriculidae); superorder Haplotaxidea* (order Haplotaxida, Haplotaxidae); order Moniligastrida (Moniligastridae); suborder Alluroidina (Aliuroididae and Syngenodrilidae); cohort Aquamegadrili* (with, in succession, superfamilice Sparganophiloidea, Sparganophilidae; Biwadriloidea, Biwadrilidac, and Almoidca—Lutodrilidac and Almidae, including Criodrilus); superfamily Eudriloidea*, superfamily Lumbricoidea and, as the adelphotaxon of the latter, the superfamily Megascolecoidea. Intermediate nodes were given the following names, with the adelpholaxon through to the Megascolecoidea, M, in parentheses: subclass Diplotesticulata (Haplotaxidea—M); superorder Metagynopohora* (Moniligastrida—M); order Opisthopora (Alluroidina M); suborder Crassiclitellata* (Aquamegadrili — M); cohort Terrimegadrili* (Ocnerodriloidea M); unnamed (Eudriloidea M); unnamed (Lumbricoidea and Megascolecoidea). Recognition of the Randiellata, which alone were added intuitively and not computed, and the position of the Lumbriculata, are tentative. Location of the Lumbricoidea as the adelphotaxon of a restricted Megascoecloidea is heuristic, but the alternative depiction of lumbricoids in some analyses, as the adelphotaxon of an ocnerodrilid-eudrilid-megascolecoid clade (the conventional Megascolecoidea s. lat.), is not conclusively dismissed.     

Spatially Pooled Contrast Responses Predict Neural and Perceptual Similarity of Naturalistic Image Categories

The visual world is complex and continuously changing. Yet, our brain transforms patterns of light falling on our retina into a coherent percept within a few hundred milliseconds. Possibly, low-level neural responses already carry substantial information to facilitate rapid characterization of the visual input. Here, we computationally estimated low-level contrast responses to computer-generated naturalistic images, and tested whether spatial pooling of these responses could predict image similarity at the neural and behavioral level. Using EEG, we show that statistics derived from pooled responses explain a large amount of variance between single-image evoked potentials (ERPs) in individual subjects. Dissimilarity analysis on multi-electrode ERPs demonstrated that large differences between images in pooled response statistics are predictive of more dissimilar patterns of evoked activity, whereas images with little difference in statistics give rise to highly similar evoked activity patterns. In a separate behavioral experiment, images with large differences in statistics were judged as different categories, whereas images with little differences were confused. These findings suggest that statistics derived from low-level contrast responses can be extracted in early visual processing and can be relevant for rapid judgment of visual similarity. We compared our results with two other, well- known contrast statistics: Fourier power spectra and higher-order properties of contrast distributions (skewness and kurtosis). Interestingly, whereas these statistics allow for accurate image categorization, they do not predict ERP response patterns or behavioral categorization confusions. These converging computational, neural and behavioral results suggest that statistics of pooled contrast responses contain information that corresponds with perceived visual similarity in a rapid, low-level categorization task.     

CMEIAS Color Segmentation: An Improved Computing Technology to Process Color Images for Quantitative Microbial Ecology Studies at Single-Cell Resolution

Quantitative microscopy and digital image analysis are underutilized in microbial ecology largely because of the laborious task to segment foreground object pixels from background, especially in complex color micrographs of environmental samples. In this paper, we describe an improved computing technology developed to alleviate this limitation. The system’s uniqueness is its ability to edit digital images accurately when presented with the difficult yet commonplace challenge of removing background pixels whose three-dimensional color space overlaps the range that defines foreground objects. Image segmentation is accomplished by utilizing algorithms that address color and spatial relationships of user-selected foreground object pixels. Performance of the color segmentation algorithm evaluated on 26 complex micrographs at single pixel resolution had an overall pixel classification accuracy of 99+%. Several applications illustrate how this improved computing technology can successfully resolve numerous challenges of complex color segmentation in order to produce images from which quantitative information can be accurately extracted, thereby gain new perspectives on the in situ ecology of microorganisms. Examples include improvements in the quantitative analysis of (1) microbial abundance and phylotype diversity of single cells classified by their discriminating color within heterogeneous communities, (2) cell viability, (3) spatial relationships and intensity of bacterial gene expression involved in cellular communication between individual cells within rhizoplane biofilms, and (4) biofilm ecophysiology based on ribotype-differentiated radioactive substrate utilization. The stand-alone executable file plus user manual and tutorial images for this color segmentation computing application are freely available at . This improved computing technology opens new opportunities of imaging applications where discriminating colors really matter most, thereby strengthening quantitative microscopy-based approaches to advance microbial ecology in situ at individual single-cell resolution.     

Biodiversity of Salix spp. honeydew and nectar honeys determined by RP-HPLC and evaluation of their antioxidant capacity

Rare unifloral willow (Salix spp.) honeys obtained from nectar or honeydew were investigated by direct RP‐HPLC‐DAD method in order to identify and quantify compounds that can be used as possible markers of their origin. Antioxidant and antiradical activities of willow honeys were evaluated using FRAP (=ferric reducing antioxidant assay) and DPPH (=1,1‐diphenyl‐2‐picrylhydrazyl radical) tests, respectively. Also HMF (=5‐(hydroxymethyl)furfural), diastase activity, and CIE L*a*b*C*h* chromatic coordinates were evaluated. Abscisic acids (ABA) are typical of willow nectar honey, with a predominance of (Z,E)‐ABA on (E,E)‐ABA (98.2 and 31.7 mg/kg, resp.). Kinurenic acid and salicylic acid are useful to mark willow honeydew honey. The proposed HPLC‐DAD method proved to be easy and reliable to identify the two different Salix spp. honeys, being not affected from any sample preparation artifact. Total antioxidant activity measured with the FRAP assay ranged from 3.2 to 12.6 mmol Fe²⁺/kg, and the antiradical activity measured with the DPPH assay ranged from 0.6 to 3.0 mmol TEAC (=Trolox equivalent antioxidant capacity)/kg in nectar and honeydew honeys, respectively. Salix spp. nectar and honeydew honeys proved to be two completely different honeys, because, besides color attributes, they show different antioxidant properties and specific compounds.     

Atomic force microscopic study on topological structures of pBR322 DNA

Plasmid pBR322 DNA (0.5mg/mL) isolated from Escherichia coli HB101 was suspended in Tris-HCl-EDTA (1 mol/L - 0.1 mol/L, pH8.5); then a drop of the above solution was deposited on freshly cleaved mica substrate. After adsorption for about 1 min, the sample was stained with phosphotungstic acid. The residua] solution was removed with a piece of filter paper. Afterwards the sample was imaged with a home-made atomic force microscope (AFM) in air. The AFM images of pBR322 DNA with a molecular resolution have been obtained. These images show that pBR322 DNA exists in several different topological structures: (i) relaxed circular DNA with a different diameter; (ii) supercondensed DNA with different particle sizes; (iii) dimeric catenane connected by one relaxed circular molecule and another dose-compacted molecule which might be either supercoiled or intramolecular knotted form; (iv) oligomeric catenane with multiple irregular molecules in which DNA is interlocked into a complex oligomer; (v) possibly-existing     

Estimating the spatial position of marine mammals based on digital camera recordings

Estimating the spatial position of organisms is essential to quantify interactions between the organism and the characteristics of its surroundings, for example, predator–prey interactions, habitat selection, and social associations. Because marine mammals spend most of their time under water and may appear at the surface only briefly, determining their exact geographic location can be challenging. Here, we developed a photogrammetric method to accurately estimate the spatial position of marine mammals or birds at the sea surface. Digital recordings containing landscape features with known geographic coordinates can be used to estimate the distance and bearing of each sighting relative to the observation point. The method can correct for frame rotation, estimates pixel size based on the reference points, and can be applied to scenarios with and without a visible horizon. A set of R functions was written to process the images and obtain accurate geographic coordinates for each sighting. The method is applied to estimate the spatiotemporal fine‐scale distribution of harbour porpoises in a tidal inlet. Video recordings of harbour porpoises were made from land, using a standard digital single‐lens reflex (DSLR) camera, positioned at a height of 9.59 m above mean sea level. Porpoises were detected up to a distance of ~3136 m (mean 596 m), with a mean location error of 12 m. The method presented here allows for multiple detections of different individuals within a single video frame and for tracking movements of individuals based on repeated sightings. In comparison with traditional methods, this method only requires a digital camera to provide accurate location estimates. It especially has great potential in regions with ample data on local (a)biotic conditions, to help resolve functional mechanisms underlying habitat selection and other behaviors in marine mammals in coastal areas.     

Scene-segmentation algorithm development using error measures

Development of scene-segmentation algorithms has generally been an ad hoc process. This paper presents a systematic technique for developing these algorithms using error-measure minimization. If scene segmentation is regarded as a problem of pixel classification whereby each pixel of a scene is assigned to a particular object class, development of a scene-segmentation algorithm becomes primarily a process of feature selection. In this study, four methods of feature selection were used to develop segmentation techniques for cervical cytology images: (1) random selection, (2) manual selection (best features in the subjective judgment of the investigator), (3) eigenvector selection (ranking features according to the largest contribution to each eigenvector of the feature covariance matrix) and (4) selection using the scene-segmentation error measure A2. Four features were selected by each method from a universe of 35 features consisting of gray level, color, texture and special pixel neighborhood features in 40 cervical cytology images . Evaluation of the results was done with a composite of the scene-segmentation error measure A2, which depends on the percentage of scenes with measurable error, the agreement of pixel class proportions, the agreement of number of objects for each pixel class and the distance of each misclassified pixel to the nearest pixel of the misclassified class. Results indicate that random and eigenvector feature selection were the poorest methods, manual feature selection somewhat better and error-measure feature selection best. The error-measure feature selection method provides a useful, systematic method of developing and evaluating scene-segmentation algorithms.