Evidence for Permo-Triassic collision in Far East Asia: The Korean collisional orogen

Eclogites from paragneiss in the Korean Peninsula are characterized by a peak pressure assemblage of garnet + omphacite + quartz + rutile, that is overprinted by multiphase symplectites involving augite, amphibole, orthopyroxene, ilmenite and plagioclase and by a similar high-pressure assemblage with a pronounced absence of the omphacite component in clinopyroxene formed during the peak and orthopyroxene in the retrograde stage. Eclogites were metamorphosed at a minimum pressures of not, vert, similar 20–23 kbar at temperatures of not, vert, similar 840–1000 °C, equivalent to a crustal depth of not, vert, similar 70–75 km, whereas high-pressure granulite in Late Paleozoic rocks underwent metamorphic conditions of not, vert, similar 18–19 kbar at not, vert, similar 950 °C with a minimum crustal depth of not, vert, similar 60–65 km. The presence of the eclogites and high-pressure granulite suggests deep-seated subduction of crustal complexes with metamorphism at different crustal levels. The eclogites were exhumed quickly resulting in near- isothermal decompression. On the other hand, the multistage exhumation of the high-pressure granulites suggests retrograde overprinting after initial decompression. The similarity of these petrological characteristics, metamorphic conditions and also the regional structural styles with those of the Sulu belt (China) strongly suggests the existence of a Permo-Triassic Alpine-type “Korean collision belt” in Far East Asia. This model provides a better understanding of the paleogeograpic evolution of Permo-Triassic East Asia, including a robust tectonic correlation of the Korean collision belt with the Qinling–Dabie–Sulu collision belt.

A blind indic script recognizer for multi-script documents

We report a hierarchical blind script identifier for 11 different Indian scripts. An initial grouping of the 11 scripts is accomplished at the first level of this hierarchy. At the subsequent level, we recognize the script in each group. The various nodes of this tree use different feature-classifier combinations. A database of 20,000 words of different font styles and sizes is collected and used for each script. Effectiveness of Gabor and Discrete Cosine Transform features has been independently, evaluated using nearest neighbor linear discriminant and support vector machine classifiers. The minimum and maximum accuracies obtained, using this hierarchical mechanism, are 92.2% and 97.6%, respectively.

Creation of a Huge Annotated Database for Tamil and Kannada OHR

This paper describes the efforts at MILE lab, IISc, to create a 100,000-word database each in Kannada and Tamil for the design and development of Online Handwritten Recognition. It has been collected from over 600 users in order to capture the variations in writing style. We describe features of the scripts and how the number of symbols were reduced to be able to effectively train the data for recognition. The list of words include all the characters, Kannada and Indo-Arabic numerals, punctuations and other symbols. A semi-automated tool for the annotation of data from stroke to word level is used. It segments each word into stroke groups and also acts as a validation mechanism for segmentation. The tool displays the stroke, stroke groups and aksharas of a word and hence can be used to study the various styles of writing, delayed strokes and for assigning quality tags to the words. The tool is currently being used for annotating Tamil and Kannada data. The output is stored in a standard XML format.

Comparison of HMM and SDTW for Tamil handwritten character recognition

In this paper, we compare the experimental results for Tamil online handwritten character recognition using HMM and Statistical Dynamic Time Warping (SDTW) as classifiers. HMM was used for a 156-class problem. Different feature sets and values for the HMM states & mixtures were tried and the best combination was found to be 16 states & 14 mixtures, giving an accuracy of 85%. The features used in this combination were retained and a SDTW model with 20 states and single Gaussian was used as classifier. Also, the symbol set was increased to include numerals, punctuation marks and special symbols like $, & and #, taking the number of classes to 188. It was found that, with a small addition to the feature set, this simple SDTW classifier performed on par with the more complicated HMM model, giving an accuracy of 84%. Mixture density estimation computations was reduced by 11 times. The recognition is writer independent, as the dataset used is quite large, with a variety of handwriting styles.

Improved recognition of aged Kannada documents by effective segmentation of merged characters

In optical character recognition of very old books, the recognition accuracy drops mainly due to the merging or breaking of characters. In this paper, we propose the first algorithm to segment merged Kannada characters by using a hypothesis to select the positions to be cut. This method searches for the best possible positions to segment, by taking into account the support vector machine classifier's recognition score and the validity of the aspect ratio (width to height ratio) of the segments between every pair of cut positions. The hypothesis to select the cut position is based on the fact that a concave surface exists above and below the touching portion. These concave surfaces are noted down by tracing the valleys in the top contour of the image and similarly doing it for the image rotated upside-down. The cut positions are then derived as closely matching valleys of the original and the rotated images. Our proposed segmentation algorithm works well for different font styles, shapes and sizes better than the existing vertical projection profile based segmentation. The proposed algorithm has been tested on 1125 different word images, each containing multiple merged characters, from an old Kannada book and 89.6% correct segmentation is achieved and the character recognition accuracy of merged words is 91.2%. A few points of merge are still missed due to the absence of a matched valley due to the specific shapes of the particular characters meeting at the merges.

A glucose-centric perspective of hyperglycemia

Digestion of food in the intestines converts the compacted storage carbohydrates, starch and glycogen, to glucose. After each meal, a flux of glucose (>200 g) passes through the blood pool (4-6 g) in a short period of 2 h, keeping its concentration ideally in the range of 80-120 mg/100 mL. Tissue-specific glucose transporters (GLUTs) aid in the distribution of glucose to all tissues. The balance glucose after meeting the immediate energy needs is converted into glycogen and stored in liver (up to 100 g) and skeletal muscle (up to 300 g) for later use. High blood glucose gives the signal for increased release of insulin from pancreas. Insulin binds to insulin receptor on the plasma membrane and activates its autophosphorylation. This initiates the post-insulin-receptor signal cascade that accelerates synthesis of glycogen and triglyceride. Parallel control by phos-dephos and redox regulation of proteins exists for some of these steps. A major action of insulin is to inhibit gluconeogensis in the liver decreasing glucose output into blood. Cases with failed control of blood glucose have alarmingly increased since 1960 coinciding with changed life-styles and large scale food processing. Many of these turned out to be resistant to insulin, usually accompanied by dysfunctional glycogen storage. Glucose has an extended stay in blood at 8 mM and above and then indiscriminately adds on to surface protein-amino groups. Fructose in common sugar is 10-fold more active. This random glycation process interferes with the functions of many proteins (e.g., hemoglobin, eye lens proteins) and causes progressive damage to heart, kidneys, eyes and nerves. Some compounds are known to act as insulin mimics. Vanadium-peroxide complexes act at post-receptor level but are toxic. The fungus-derived 2,5-dihydroxybenzoquinone derivative is the first one known to act on the insulin receptor. The safe herbal products in use for centuries for glucose control have multiple active principles and targets. Some are effective in slowing formation of glucose in intestines by inhibiting alpha-glucosidases (e.g., salacia/saptarangi). Knowledge gained from French lilac on active guanidine group helped developing Metformin (1,1-dimethylbiguanide) one of the popular drugs in use. One strategy of keeping sugar content in diets in check is to use artificial sweeteners with no calories, no glucose or fructose and no effect on blood glucose (e.g., steviol, erythrytol). However, the three commonly used non-caloric artificial sweetener's, saccharin, sucralose and aspartame later developed glucose intolerance, the very condition they are expected to evade. Ideal way of keeping blood glucose under 6 mM and HbAlc, the glycation marker of hemoglobin, under 7% in blood is to correct the defects in signals that allow glucose flow into glycogen, still a difficult task with drugs and diets.

Generic identity of Camptorrhiza indica (Colchicaceae) based on cytogenetics and molecular phylogenetics

The tribe Iphigenieae (Colchicaceace, Liliales) includes two genera, viz. Camptorrhiza and Iphigenia, which are distributed in Africa, India, and Australasia. Iphigenia is represented by 12 species, of which six occur in India while Camptorrhiza comprises one species each in Africa (C. strumosa) and India (C. indica). The genus Camptorrhiza possesses a knee-shaped tuber attached to the corms, filaments with a thick bulge in the middle and styles with single stigma. Iphigenia on the other hand lacks knee-shaped tuber, bears linear filaments and has styles with three stigmas. Camptorrhiza indica possesses ovoid corms, linear filaments and styles with a single stigma. These characters are intermediate between Iphigenia and Camptorrhiza and hence we studied the cytogenetics and phylogenetic placement of this species to ascertain its generic identity. Somatic chromosome count (2n = 22) and karyotypic features of C. indica are very similar to that of Iphigenia species. Molecular phylogenetic studies based on atpB-rbcL, rps16, trnL, and trnL-F regions showed that C. indica is nested within a lineage of Indian Iphigenia species. Thus, C. indica was reduced to a species of Iphigenia, i.e., I. ratnagirica. Camptorrhiza is now a monotypic genus restricted only to southern Africa. A key to the Indian Iphigenia species is provided. In addition, a new combination Wurmbea novae-zelandiae is proposed for Iphigenia novae-zelandiae.