Captive Breeding and Nursery Rearing of the Indian Seahorse, Hippocampus kuda (Teleostei: Syngnathidae)

Breeding of laboratory-reared 21 pairs of broodstock Hippocampus kuda (Bleeker 1852) and rearing of their young ones indicated that 262.00 ± 59.00 offsprings were released during each spawning. A newly born seahorse was (mean ± SE) 7.83 ± 0.11 mm in length with a weight of 1.17 ± 0.009 mg. It could attain a mean length of 31.14 ± 0.66 mm with a mean weight of 16.13 ± 0.60 mg in 30 days when fed ad libitum with Artemia nauplii. The mean survival per brood cycle was enhanced to 65.22 ± 1.87% from almost less than 1.0% by improving the rearing conditions

Efficient Dynamic Approximate Distance Oracles for Vertex-Labeled Planar Graphs

Let $G$ be a graph where each vertex is associated with a label. A Vertex-Labeled Approximate Distance Oracle is a data structure that, given a vertex $v$ and a label $\lambda$, returns a $(1+\varepsilon)$-approximation of the distance from $v$ to the closest vertex with label $\lambda$ in $G$. Such an oracle is dynamic if it also supports label changes. In this paper we present three different dynamic approximate vertex-labeled distance oracles for planar graphs, all with polylogarithmic query and update times, and nearly linear space requirements

Linear-Space Approximate Distance Oracles for Planar, Bounded-Genus, and Minor-Free Graphs

A (1 + eps)-approximate distance oracle for a graph is a data structure that supports approximate point-to-point shortest-path-distance queries. The most relevant measures for a distance-oracle construction are: space, query time, and preprocessing time. There are strong distance-oracle constructions known for planar graphs (Thorup, JACM'04) and, subsequently, minor-excluded graphs (Abraham and Gavoille, PODC'06). However, these require Omega(eps^{-1} n lg n) space for n-node graphs. We argue that a very low space requirement is essential. Since modern computer architectures involve hierarchical memory (caches, primary memory, secondary memory), a high memory requirement in effect may greatly increase the actual running time. Moreover, we would like data structures that can be deployed on small mobile devices, such as handhelds, which have relatively small primary memory. In this paper, for planar graphs, bounded-genus graphs, and minor-excluded graphs we give distance-oracle constructions that require only O(n) space. The big O hides only a fixed constant, independent of \epsilon and independent of genus or size of an excluded minor. The preprocessing times for our distance oracle are also faster than those for the previously known constructions. For planar graphs, the preprocessing time is O(n lg^2 n). However, our constructions have slower query times. For planar graphs, the query time is O(eps^{-2} lg^2 n). For our linear-space results, we can in fact ensure, for any delta > 0, that the space required is only 1 + delta times the space required just to represent the graph itself

Evaluating Matrix Circuits

The circuit evaluation problem (also known as the compressed word problem) for finitely generated linear groups is studied. The best upper bound for this problem is $\mathsf{coRP}$, which is shown by a reduction to polynomial identity testing. Conversely, the compressed word problem for the linear group $\mathsf{SL}_3(\mathbb{Z})$ is equivalent to polynomial identity testing. In the paper, it is shown that the compressed word problem for every finitely generated nilpotent group is in $\mathsf{DET} \subseteq \mathsf{NC}^2$. Within the larger class of polycyclic groups we find examples where the compressed word problem is at least as hard as polynomial identity testing for skew arithmetic circuits

Localization Recall Precision (LRP): A New Performance Metric for Object Detection

Average precision (AP), the area under the recall-precision (RP) curve, is the standard performance measure for object detection. Despite its wide acceptance, it has a number of shortcomings, the most important of which are (i) the inability to distinguish very different RP curves, and (ii) the lack of directly measuring bounding box localization accuracy. In this paper, we propose 'Localization Recall Precision (LRP) Error', a new metric which we specifically designed for object detection. LRP Error is composed of three components related to localization, false negative (FN) rate and false positive (FP) rate. Based on LRP, we introduce the 'Optimal LRP', the minimum achievable LRP error representing the best achievable configuration of the detector in terms of recall-precision and the tightness of the boxes. In contrast to AP, which considers precisions over the entire recall domain, Optimal LRP determines the 'best' confidence score threshold for a class, which balances the trade-off between localization and recall-precision. In our experiments, we show that, for state-of-the-art object (SOTA) detectors, Optimal LRP provides richer and more discriminative information than AP. We also demonstrate that the best confidence score thresholds vary significantly among classes and detectors. Moreover, we present LRP results of a simple online video object detector which uses a SOTA still image object detector and show that the class-specific optimized thresholds increase the accuracy against the common approach of using a general threshold for all classes. At https://github.com/cancam/LRP we provide the source code that can compute LRP for the PASCAL VOC and MSCOCO datasets. Our source code can easily be adapted to other datasets as well.Comment: to appear in ECCV 201

The use of an electronic computer in the estimation of sampling errors in a nutritional survey

RESP-355

Antibacterial activity of aqueous extract from selected macroalgae of southwest coast of India

Aqueous extract of seven species of marine macroalgae were screened for their antimicrobial potency against ten pathogenic bacterial strains. Ulva fasciata, Gracilaria corticata, Sargassum wightii and Padina tetrastromatica showed significantly higher activity against 70% of the tested bacterial isolates. The maximum zone of inhibition was noted for the red alga G.corticata against Proteus mirabilis (17mm) and brown alga P. tetrastromatica against the pathogens Staphylococcus aureus and Vibrio harveyi (15mm). The general trend of inhibitory activity was higher towards Gram negative bacteria

Convexity-Increasing Morphs of Planar Graphs

We study the problem of convexifying drawings of planar graphs. Given any planar straight-line drawing of an internally 3-connected graph, we show how to morph the drawing to one with strictly convex faces while maintaining planarity at all times. Our morph is convexity-increasing, meaning that once an angle is convex, it remains convex. We give an efficient algorithm that constructs such a morph as a composition of a linear number of steps where each step either moves vertices along horizontal lines or moves vertices along vertical lines. Moreover, we show that a linear number of steps is worst-case optimal. To obtain our result, we use a well-known technique by Hong and Nagamochi for finding redrawings with convex faces while preserving y-coordinates. Using a variant of Tutte's graph drawing algorithm, we obtain a new proof of Hong and Nagamochi's result which comes with a better running time. This is of independent interest, as Hong and Nagamochi's technique serves as a building block in existing morphing algorithms.Comment: Preliminary version in Proc. WG 201

Polymicrobial skin lesions in the red spot emperor, Lethrinus lentjan (Lacepede 1802) during mass incursion towards shore along Kanyakumari coast, south India

Mass incursion of fishes with polymicrobial skin lesions, fin erosions and scale loss was recorded in the red spot emperor Lethrinus lentjan (Lacepede 1802) along the Kanyakumari coast, south India during August 2009. An estimated 2.5 t of fish, mostly the red spot emperors were found to migrate in live condition to the shore areas in a stressful state. Microbiological analyses of tissue from sampled fishes revealed three distinct types of bacterial colonies forming 5.2 x 105 CFU g-1 of the infected tissues. The predominant bacterial colonies were characterized as Aeromonas sp. (70.0%) followed by Flavobacterium sp. (20%) and Vibrio sp. (10%). The Aeromonas isolate was highly susceptible to norfloxacin while the Flavobacterium and Vibrio isolates were susceptible to chloramphenicol. The Aeromonas and Vibrio isolates exhibited protease and amylase enzyme activities in vitro, suggesting their possible role in the progression of skin lesions and scale loss. The possibilities of ambient unknown stressors weakening the fish and subsequent infections by these bacterial isolates are discussed