Temporal behaviour of marine landings along coastal Karnataka 1. Relative distribution and secular trends

Landing data of 21 fisheries from Karnataka (quarterly landings for the period 1956 to 1978 and annual landings for the period 1979 to 1981) were analysed to study the te111poral behaviour of the landings. The relative distribution and secular trends in each of the fisheries are reported. On an average, mackerel and oil sardine together account for about 70% of the annual landings. The fluctuation in the landings in all the fisheries was very high with the coefficient of variation attaining a minimum value of 61.53%. The inverse relationship between the landings of oil sardine and mackerel was found to be statistically significant. It is suggested that fishing effort be further increased in fisheries that have demonstrated a rising trend (about 73% of the total annual landings) as also in the case of the fisheries whose trends appear stagnant (about 21% of the annual landings). However, there seems to be some evidence of a need for regulating fishing in Hemirhamphus and Belone, Caranx and penaeid prawns. Regulations need to be made authentic with the help of sufficient information on not merely the fishery but on the whole population.

Temporal behaviour of marine landing in Karnataka 2. Seasonal patterns

Seasonal patterns of 21 fisheries in Karnataka (after isolation from time-series components) are presented. Depending on the pattern of seasonal fluctuation in landings, 19 fisheries have been grouped into five patterns, A, B, C, D and E. Ribbon fishes and 'other clupeids' did not exhibit any significant seasonal pattern. Pattern A with highest landings in the 4th quarter (October to December), followed by the 1, 2 and 3 quarters, is the most common in 10 species/groups (comprising 78% of the total landings). Harmonic analysis has been carried out using the seasonal indices.

Temporal behaviour of marine landings along coastal Karnataka 3. Cyclical patterns

Marine landing data for Karnataka during 1956-1978 were subjected to time series analysis and cyclical periodicities isolated in the case of seven fisheries namely, ribbon fish (five year cycle); Caranx spp., Leiognathus spp, and mackerel (six year cycle each); the combined landings of Hemirhamphus spp. and Belone spp.,'Lesser Sardines' and 'Other Clupeids' (seven year cycle each). 'Total' demonstrated an eight-year cyclical periodicity.

Breathers and thermal relaxation as a temporal process: A possible way to detect breathers in experimental situations

Breather stability and longevity in thermally relaxing nonlinear arrays is investigated under the scrutiny of the analysis and tools employed for time series and state reconstruction of a dynamical system. We briefly review the methods used in the analysis and characterize a breather in terms of the results obtained with such methods. Our present work focuses on spontaneously appearing breathers in thermal Fermi-Pasta-Ulam arrays but we believe that the conclusions are general enough to describe many other related situations; the particular case described in detail is presented as another example of systems where three incommensurable frequencies dominate their chaotic dynamics (reminiscent of the Ruelle-Takens scenario for the appearance of chaotic behavior in nonlinear systems). This characterization may also be of great help for the discovery of breathers in experimental situations where the temporal evolution of a local variable (like the site energy) is the only available/measured data. © 2005 American Institute of Physics.

Spatial and temporal sensitivity degradation of primary visual cortical cells in senescent rhesus monkeys

Human visual function declines with age. Much of this decline is mediated by changes in the central visual pathways. In this study we compared the spatial and temporal sensitivities of striate cortical cells in young and old paralysed macaque monkeys. Ext

Temporal and spatial distribution of phytoplankton with emphasis on Skeletonema costatum in the Mathamuhuri river – estuary (Chakaria mangrove ecosystem), Bangladesh

A total of 91 species under 44 genera were identified among the phytoplankton community during the course of one year's investigation between May 1982 and April 1983. Bacillariophyta was the most dominant group with 72 specie, Chlorophyta 11 spp, Cyanophyta 6 spp and Pyrrophyta was represented by 2 species. The yearly percentage composition of 4 groups of phytoplankton in order of abundance were Bacillariophyta 50.77%, Cyanophyta 47.70%, Chlorophyta 1.5% and Pyrrophyta 0.02%. The highest densities of phytoplankton were recorded in monsoon months (June-July) with a peak in July (31550 cells/l) and the minimum in February (770 cells/1). Higher concentration of phytoplankton was recorded at station 2, nearer to the Chakaria Sundarbans (mangroves), but abundance of phytoplankton showed no significant difference in the two stations (Mann Whitney U test, P=0.64, Z=-0.642, U=64). Phytoplankton population in this area were positively correlated with rainfall (r=0.655, P=<0.5, df.22) and water temperature (r=0.523, P=<0.05). Skeletonema costatum was the dominant member of phytoplankton and occupied 35.23% of the annual population and occurred throughout the period of study except in September and January. Its abundance was recorded during the monsoon months (April- July) with a maximum density (24185 cells/l) in July. No significant correlation was found between abundance of S. costatum and the hydro-meteorological parameters recorded in the Chakaria mangrove area.

Facilitation of learning induced by both random and gradual visuomotor task variation.

Motor task variation has been shown to be a key ingredient in skill transfer, retention, and structural learning. However, many studies only compare training of randomly varying tasks to either blocked or null training, and it is not clear how experiencing different nonrandom temporal orderings of tasks might affect the learning process. Here we study learning in human subjects who experience the same set of visuomotor rotations, evenly spaced between -60° and +60°, either in a random order or in an order in which the rotation angle changed gradually. We compared subsequent learning of three test blocks of +30°→-30°→+30° rotations. The groups that underwent either random or gradual training showed significant (P < 0.01) facilitation of learning in the test blocks compared with a control group who had not experienced any visuomotor rotations before. We also found that movement initiation times in the random group during the test blocks were significantly (P < 0.05) lower than for the gradual or the control group. When we fit a state-space model with fast and slow learning processes to our data, we found that the differences in performance in the test block were consistent with the gradual or random task variation changing the learning and retention rates of only the fast learning process. Such adaptation of learning rates may be a key feature of ongoing meta-learning processes. Our results therefore suggest that both gradual and random task variation can induce meta-learning and that random learning has an advantage in terms of shorter initiation times, suggesting less reliance on cognitive processes.

Image sequence segmentation using mixture-models with uniqueness and spatio-temporal consistency constraints

The use of mixture-model techniques for motion estimation and image sequence segmentation was discussed. The issues such as modeling of occlusion and uncovering, determining the relative depth of the objects in a scene, and estimating the number of objects in a scene were also investigated. The segmentation algorithm was found to be computationally demanding, but the computational requirements were reduced as the motion parameters and segmentation of the frame were initialized. The method provided a stable description, in whichthe addition and removal of objects from the description corresponded to the entry and exit of objects from the scene.

Spatio-temporal clustering of probabilistic region trajectories

We propose a novel model for the spatio-temporal clustering of trajectories based on motion, which applies to challenging street-view video sequences of pedestrians captured by a mobile camera. A key contribution of our work is the introduction of novel probabilistic region trajectories, motivated by the non-repeatability of segmentation of frames in a video sequence. Hierarchical image segments are obtained by using a state-of-the-art hierarchical segmentation algorithm, and connected from adjacent frames in a directed acyclic graph. The region trajectories and measures of confidence are extracted from this graph using a dynamic programming-based optimisation. Our second main contribution is a Bayesian framework with a twofold goal: to learn the optimal, in a maximum likelihood sense, Random Forests classifier of motion patterns based on video features, and construct a unique graph from region trajectories of different frames, lengths and hierarchical levels. Finally, we demonstrate the use of Isomap for effective spatio-temporal clustering of the region trajectories of pedestrians. We support our claims with experimental results on new and existing challenging video sequences. © 2011 IEEE.

Differences between FRP bond behavior in cracked and uncracked regions

Based on an analysis of the experimental results of a proposed bond test method, significant differences are shown to exist between the local FRP bond stress-slip relationships in the uncracked anchorage regions and in the regions between cracks. The proposed method simulates the bond behavior between the flexural cracks and anchorage regions of a flexurally FRP-strengthened RC beam. The boundary conditions, including the presence of cracks and steel, are shown to have significant effects on the local bond stress-slip models. The results showed that, at the same force, the bond stresses in the regions between cracks were lower than in regions outside the cracks, so the debonding formed in the anchorage regions. The local bond stress-slip models in the anchorage regions can be obtained from the conventional bond test methods but these do not mimic the conditions between the cracks.

Sexual differences in vigilance of paired Ruddy Shelduck in winter

The effect of distance between members of pairs of the Ruddy Shelduck (Tadorna ferruginea) during vigilance behavior was studied during winter at Lijiang Lashihai Lake Reserve, southwest China. The distance between the paired birds while feeding was grouped into three categories: <1 m, 1-3 to and >3 m. Nearly 90% of the distances recorded between paired males and females were within three meters. The degree of vigilance increased with distance apart for females, but not for males. The scanning rate of males was significantly, higher than that of females at <1 m and at 1-3 m respectively, but no significant difference occurred when the distance between them was >3 m. These results are discussed in relation to mate competition and wintering strategy; it is suggested that staving close together is the optimal strategy for members of Ruddy Shelduck pairs.

Internal representations of temporal statistics and feedback calibrate motor-sensory interval timing.

Humans have been shown to adapt to the temporal statistics of timing tasks so as to optimize the accuracy of their responses, in agreement with the predictions of Bayesian integration. This suggests that they build an internal representation of both the experimentally imposed distribution of time intervals (the prior) and of the error (the loss function). The responses of a Bayesian ideal observer depend crucially on these internal representations, which have only been previously studied for simple distributions. To study the nature of these representations we asked subjects to reproduce time intervals drawn from underlying temporal distributions of varying complexity, from uniform to highly skewed or bimodal while also varying the error mapping that determined the performance feedback. Interval reproduction times were affected by both the distribution and feedback, in good agreement with a performance-optimizing Bayesian observer and actor model. Bayesian model comparison highlighted that subjects were integrating the provided feedback and represented the experimental distribution with a smoothed approximation. A nonparametric reconstruction of the subjective priors from the data shows that they are generally in agreement with the true distributions up to third-order moments, but with systematically heavier tails. In particular, higher-order statistical features (kurtosis, multimodality) seem much harder to acquire. Our findings suggest that humans have only minor constraints on learning lower-order statistical properties of unimodal (including peaked and skewed) distributions of time intervals under the guidance of corrective feedback, and that their behavior is well explained by Bayesian decision theory.