Structure of a fig wasp community: Temporal segregation of oviposition and larval diets

Observations were made on six fig wasp species on Ficus racemosa growing in the Xishuangbanna Tropical Botanic Garden, Yunnan Province, China. The oviposition sequence was determined for Apocryptophagus testacea, Apocrypta sp2, Apocryptophagus mayri, Cera

Temporal and Spatial Expression Patterns of Sox1 Gene in Xenopus laevis

克隆了非洲爪蟾的Sox1基因并研究了它在非洲爪蟾早期发育过程中的时空表达图式,比较了Sox1-3基因在发育的脑和眼中的表达图式.序列比对分析显示Sox1-3蛋白在其HMG框结构域具有高度的保守性.通过RT-PCR方法分析了Sox1基因在爪蟾早期不同发育时段的表达情况,结果显示Sox1基因从未受精卵到尾芽期均有表达,但表达强度有所差异.原位杂交结果显示,在早期卵裂阶段和囊胚期,Sox1基因主要在动物极表达;从神经板期开始,Sox1基因主要在中枢神经系统和眼原基中表达.在蝌蚪期,Sox1与Sox2、Sox3在脑部和眼睛的表达区域有所不同.对于爪蟾Sox1基因时空表达图式的研究将有助于阐明SoxB1基因家族在脊椎动物神经系统发生过程中的作用.

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.

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.

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.

Temporal difference models describe higher-order learning in humans.

The ability to use environmental stimuli to predict impending harm is critical for survival. Such predictions should be available as early as they are reliable. In pavlovian conditioning, chains of successively earlier predictors are studied in terms of higher-order relationships, and have inspired computational theories such as temporal difference learning. However, there is at present no adequate neurobiological account of how this learning occurs. Here, in a functional magnetic resonance imaging (fMRI) study of higher-order aversive conditioning, we describe a key computational strategy that humans use to learn predictions about pain. We show that neural activity in the ventral striatum and the anterior insula displays a marked correspondence to the signals for sequential learning predicted by temporal difference models. This result reveals a flexible aversive learning process ideally suited to the changing and uncertain nature of real-world environments. Taken with existing data on reward learning, our results suggest a critical role for the ventral striatum in integrating complex appetitive and aversive predictions to coordinate behaviour.