A Stochastic Search on the Line-Based Solution to Discretized Estimation

Recently, Oommen and Rueda [11] presented a strategy by which the parameters of a binomial/multinomial distribution can be estimated when the underlying distribution is nonstationary. The method has been referred to as the Stochastic Learning Weak Estimator (SLWE), and is based on the principles of continuous stochastic Learning Automata (LA). In this paper, we consider a new family of stochastic discretized weak estimators pertinent to tracking time-varying binomial distributions. As opposed to the SLWE, our proposed estimator is discretized , i.e., the estimate can assume only a finite number of values. It is well known in the field of LA that discretized schemes achieve faster convergence speed than their corresponding continuous counterparts. By virtue of discretization, our estimator realizes extremely fast adjustments of the running estimates by jumps, and it is thus able to robustly, and very quickly, track changes in the parameters of the distribution after a switch has occurred in the environment. The design principle of our strategy is based on a solution, pioneered by Oommen [7], for the Stochastic Search on the Line (SSL) problem. The SSL solution proposed in [7], assumes the existence of an Oracle which informs the LA whether to go “right” or “left”. In our application domain, in order to achieve efficient estimation, we have to first infer (or rather simulate ) such an Oracle. In order to overcome this difficulty, we rather intelligently construct an “Artificial Oracle” that suggests whether we are to increase the current estimate or to decrease it. The paper briefly reports conclusive experimental results that demonstrate the ability of the proposed estimator to cope with non-stationary environments with a high adaptation rate, and with an accuracy that depends on its resolution. The results which we present are, to the best of our knowledge, the first reported results that resolve the problem of discretized weak estimation using a SSL-based solution

Optimisation of foliar application of zinc and boron in small cardamom (Elettaria cardamomum Maton)

A field experiment was conducted at Indian Cardamom Research Institute, Spices Board, Myladumpara, Idukki district, Kerala during 2006-09 to study the response of foliar application of zinc and boron on growth, yield and its content in index leaves in small cardamom. The experiment was laid out in randomized block design with twelve treatments replicated thrice. The treatments were various levels of zinc (0.1, 0.25, 0.5, 0.75 and 0.9 %) as zinc sulphate and boron (0.2, 0.4, 0.6, 0.8, 1.0 and 1.2 %) as borax with a control. The zinc content in the leaves of zinc treated plants ranged from 53.79 mg kg-1 to 116.67 mg kg-1. The boron content in leaves of the boron treated plants ranged from 20.62 mg kg-1 to 34.37 mg kg-1. The DTPA extractable zinc in soil was 0.756 to 0.917 mg kg-1 in zinc treatments and 0.93 mg kg-1 in control plot. Hot water extractable boron in soil ranged between 0.90 mg kg-1 to 2.2 mg kg-1 in boron treatments and 0.850 mg kg-1 in control plot. Application of boron at 0.6 and 0.8 % significantly improved the yield of cardamom compared to control. A significant quadratic relationship was established between yield and various levels of zinc and the quadratic curve gives the zinc optimum dose as 0.38 %. The yield attributing characters like number of panicles per clump and number of racemes per panicle were positively influenced by the foliar application of zinc and boron

Gold nanoparticles approach to detect chondroitin sulphate and hyaluronic acid urothelial coating

This study investigated the location of hyaluronic acid (HA)-and chondroitin sulphate (CS)-coated gold nanoparticles in rabbit bladder and evaluated gene expression of CD44, RHAMM and ICAM-1 receptors involved in HA and CS transport into the cell. Gold nanoparticles were synthesised by reduction of gold salts with HA or CS to form HA-AuNPs and CS-AuNPs. Bladder samples were incubated with CS-AuNPs and HA-AuNPs or without glycosaminoglycans. Transmission electron microscopy, optic microscopy and scanning electron microscopy were used to determine the location of the synthesised AuNPs. Real-time PCR was used to analyse expression of urothelial cell receptors CD44, RHAMM, ICAM-1, after ex vivo administration of CS-AuNPs and HA-AuNPs. We showed that HA-AuNPs and CS-AuNPs were located in the cytoplasm and tight junctions of urothelial umbrella cells; this appearance was absent in untreated bladders. There were no significant differences in gene expression levels for CD44, RHAMM and ICAM-1 receptors in treated versus control bladder tissues. In conclusion, we clearly showed the presence of exogenous GAGs in the bladder surface and the tight junctions between umbrella cells, which is important in the regeneration pathway of the urothelium. The GAGs-AuNPs offer a promising approach to understanding the biophysical properties and imaging of urothelial tissue

Phylogenetic relationships of Indian caecilians (Amphibia: Gymnophiona) inferred from mitochondrial rRNA gene sequences

India has a diverse caecilian fauna, including representatives of three of the six currently recognized families, the Caeciliidae, Ichthyophiidae, the endemic Uraeotyphlidae, but previous molecular phylogenetic studies of caecilians have not included sequences for any Indian caecilians. Partial 12S and 16S mitochondrial gene sequences were obtained for a single representative of each of the caecilian families found in India and aligned against previously reported sequences for 13 caecilian species. The resulting alignment (16 taxa, 1200 sites, of which 288 cannot be aligned unambiguously) was analyzed using parsimony, maximum-likelihood, and distance methods. As judged by bootstrap proportions, decay indices, and leaf stabilities, well-supported relationships of the Indian caecilians are recovered from the alignment. The data (1) corroborate the hypothesis, based on morphology, that the Uraeotyphlidae and Ichthyophiidae are sister taxa, (2) recover a monophyletic Ichthyophiidae, including Indian and South East Asian representatives, and (3) place the Indian caeciliid Gegeneophis ramaswamii as the sister group of the caeciliid caecilians of the Seychelles. Rough estimates of divergence times suggest an origin of the Uraeotyphlidae and Ichthyophiidae while India was isolated from Laurasia and Africa and are most consistent with an Indian origin of these families and subsequent dispersal of ichthyophiids into South East Asia

On Invoking Transitivity to Enhance the Pursuit-oriented Object Migration Automata

From the earliest studies in graph theory [2], [5], the phenomenon of transitivity has been used to design and analyze problems that can be mapped onto graphs. Some of the practical examples of this phenomenon are the “Transitive Closure” algorithm, the multiplication of Boolean matrices, the determination of Communicating States in Markov Chains etc. The use of transitivity, however, to catalyze the partitioning problems is, to our knowledge, unreported, and it is by no means trivial considering the pairwise occurrences of the queries in the query stream. This paper pioneers such a mechanism. In particular, we consider the Object Migrating Automaton (OMA) that has been used for decades to solve the Equi-Partitioning Problem (EPP) where W objects are placed in R partitions of equal sizes so that objects accessed together fall in to the same partition. The OMA, which encountered certain deadlock configurations, was enhanced by Gale et al. to yield the Enhanced OMA (EOMA). Both the OMA and the EOMA were significantly improved by incorporating into them, the recently-introduced “Pursuit” phenomenon from the field of Learning Automata (LA). In this paper1 we shall show that the Pursuit matrix that consists of the estimates of the probabilities of the pairs presented to the LA, possesses the property of transitivity akin to the property found in graph-related problems. By making use of this observation, transitive-closure-like arguments can be made to invoke reward and penalty operations on the POMA and the PEOMA. This implies that objects can be moved towards their correct partitions even when the system is dormant, i.e., when the Environment does not present any queries or partitioning information to the learning algorithm. The results that we present demonstrate that the newly-designed transitive-based algorithms are about 20% faster than their non-transitive versions. As far as we know, these are the fastest partitioning algorithms to-date

Computerized adaptive measurement of depression: A simulation study

BACKGROUND: Efficient, accurate instruments for measuring depression are increasingly important in clinical practice. We developed a computerized adaptive version of the Beck Depression Inventory (BDI). We examined its efficiency and its usefulness in identifying Major Depressive Episodes (MDE) and in measuring depression severity. METHODS: Subjects were 744 participants in research studies in which each subject completed both the BDI and the SCID. In addition, 285 patients completed the Hamilton Depression Rating Scale. RESULTS: The adaptive BDI had an AUC as an indicator of a SCID diagnosis of MDE of 88%, equivalent to the full BDI. The adaptive BDI asked fewer questions than the full BDI (5.6 versus 21 items). The adaptive latent depression score correlated r = .92 with the BDI total score and the latent depression score correlated more highly with the Hamilton (r = .74) than the BDI total score did (r = .70). CONCLUSIONS: Adaptive testing for depression may provide greatly increased efficiency without loss of accuracy in identifying MDE or in measuring depression severity

Semi-supervised classification using tree-based self-organizing maps

This paper presents a classifier which uses a tree-based Neural Network (NN), and uses both, unlabeled and labeled instances. First, we learn the structure of the data distribution in an unsupervised manner. After convergence, and once labeled data become available, our strategy tags each of the clusters according to the evidence provided by the instances. Unlike other neighborhood-based schemes, our classifier uses only a small set of representatives whose cardinality can be much smaller than that of the input set. Our experiments show that, on average, the accuracy of such classifier is reasonably comparable to those obtained by some of the state-of-the-art classification schemes that only use labeled instances during the training phase. The experiments also show that improved levels of accuracy can be obtained by imposing trees with a larger number of nodes

Posterior Reconstruction Before Anastomosis Improves the Anastomosis Time During Robot-Assisted Radical Prostatectomy

Posterior reconstruction prior to anastomosis decreased anastomotic time for robotic surgeons in training