Ring seine fishery of Kerala: An overview

Among the various fishing gears employed for pelagic schooling fishes along the Kerala coast, seines are the most efficient. Contribution of ring seine to total marine fish landings of Kerala has steadily increased since its introduction during the early eighties. It was 21.4 % in the nineties rising to 36.7 % during the period 2000-2004 and contributing more than 50 % since then. In recent years, about 90 % of the oil sardine and about 60 % of the mackerel landed in Kerala were caught in ring seines. Ring seines were introduced during the early eighties by traditional fishers of Alappuzha District which became highly successful

Systematics, fishery and biology of the white sardine Escualosa thoracata (Valenciennes, 1847) exploited off Kerala, south-west coast of India

Landings of the white sardine Escualosa thoracata (Valenciennes, 1847) indicated a shift in their abundance from north-east to south-west coast of India and a sharp decline in the resource landings during the last decade along the entire range of its distribution. High local demand coupled with competitive price for the species might have led to overexploitation of this otherwise seasonal resources along the major areas of its abundance along the Indian coast. Detailed study on the systematics, fishery and biology of the species landed along Kerala coast was undertaken during 2015 and 2016. Stock assessment studies indicated near optimum fishing pressure on the resource along the Kerala coast

Unusual heavy landings of flying gurnards at Munambam Fishing Harbour

Flying gurnards belongs to the familyDactylopteridae, distributed in tropical Indo-Pacificand Atlantic oceans. From the 7 speciesrepresenting two genera, Dactylopterus andDactyloptena only four species such asDactyloptena gilberti, D. macracantha,D. orientalis and D. peterseni are found in thewestern Indian Ocean. These are small to moderatesized marine bottom dwelling fish and mostlycaught by bottom trawls as by-catch in the nearshore waters and not having much commercialvalue

Record sized longnose trevally landed

A large sized longnose trevally Carangoideschrysophrys (Cuvier, 1833) was landed at CochinFisheries Harbour on 19th September 2015. Belongingto the family Carangidae, it was caught by a hookand line unit operated near Lakshadweep waters

Occurrence of macro plastic in the stomach of flat needlefish

On 6th January 2016, biological samples ofAblennes hians were collected from the hook andline fishing boats based at Munambam FishingHarbour, Kochi. While analysing the gut contents inthe laboratory, the stomach of one specimen (weight380 gm, total length 687 mm) contained macroplastic material having about 0.02 gm weight.Stomach also contained partially digested shrimps,sea snails (Diacavolinia longirostris, Cavoliniatridentata) and digested matter

Emergent complex neural dynamics

A large repertoire of spatiotemporal activity patterns in the brain is the basis for adaptive behaviour. Understanding the mechanism by which the brain's hundred billion neurons and hundred trillion synapses manage to produce such a range of cortical configurations in a flexible manner remains a fundamental problem in neuroscience. One plausible solution is the involvement of universal mechanisms of emergent complex phenomena evident in dynamical systems poised near a critical point of a second-order phase transition. We review recent theoretical and empirical results supporting the notion that the brain is naturally poised near criticality, as well as its implications for better understanding of the brain

Chemical Composition and Larvicidal Activities of the Himalayan Cedar, Cedrus deodara Essential Oil and Its Fractions Against the Diamondback Moth, Plutella xylostella

Plants and plant-derived materials play an extremely important role in pest management programs. Essential oil from wood chips of Himalayan Cedar, Cedrus deodara (Roxburgh) Don (Pinales: Pinaceae), was obtained by hydrodistillation and fractionated to pentane and acetonitrile from which himachalenes and atlantones enriched fractions were isolated. A total of forty compounds were identified from these fractions using GC and GC-MS analyses. Essential oils and fractions were evaluated for insecticidal activities against second instars of the diamondback moth, Plutella xylostella L. (Lepidoptera: Yponomeutidae), using a leaf dip method. All samples showed promising larvicidal activity against larvae of P. xylostella. The pentane fraction was the most toxic with a LC50 value of 287 µg/ml. The himachalenes enriched fraction was more toxic (LC50 = 362 µg/ml) than the atlantones enriched fraction (LC50 = 365 µg/ml). LC50 of crude oil was 425 µg/ml and acetonitrile fraction was LC50 = 815 µg/ml. The major constituents, himachalenes and atlantones, likely accounted for the insecticidal action. Present bioassay results revealed the potential for essential oil and different constituents of C. deodara as botanical larvicides for their use in pest management

Failure of adaptive self-organized criticality during epileptic seizure attacks

Critical dynamics are assumed to be an attractive mode for normal brain functioning as information processing and computational capabilities are found to be optimized there. Recent experimental observations of neuronal activity patterns following power-law distributions, a hallmark of systems at a critical state, have led to the hypothesis that human brain dynamics could be poised at a phase transition between ordered and disordered activity. A so far unresolved question concerns the medical significance of critical brain activity and how it relates to pathological conditions. Using data from invasive electroencephalogram recordings from humans we show that during epileptic seizure attacks neuronal activity patterns deviate from the normally observed power-law distribution characterizing critical dynamics. The comparison of these observations to results from a computational model exhibiting self-organized criticality (SOC) based on adaptive networks allows further insights into the underlying dynamics. Together these results suggest that brain dynamics deviates from criticality during seizures caused by the failure of adaptive SOC.Comment: 7 pages, 5 figure

Emergent Oscillations in Networks of Stochastic Spiking Neurons

Networks of neurons produce diverse patterns of oscillations, arising from the network's global properties, the propensity of individual neurons to oscillate, or a mixture of the two. Here we describe noisy limit cycles and quasi-cycles, two related mechanisms underlying emergent oscillations in neuronal networks whose individual components, stochastic spiking neurons, do not themselves oscillate. Both mechanisms are shown to produce gamma band oscillations at the population level while individual neurons fire at a rate much lower than the population frequency. Spike trains in a network undergoing noisy limit cycles display a preferred period which is not found in the case of quasi-cycles, due to the even faster decay of phase information in quasi-cycles. These oscillations persist in sparsely connected networks, and variation of the network's connectivity results in variation of the oscillation frequency. A network of such neurons behaves as a stochastic perturbation of the deterministic Wilson-Cowan equations, and the network undergoes noisy limit cycles or quasi-cycles depending on whether these have limit cycles or a weakly stable focus. These mechanisms provide a new perspective on the emergence of rhythmic firing in neural networks, showing the coexistence of population-level oscillations with very irregular individual spike trains in a simple and general framework

Avalanches in a Stochastic Model of Spiking Neurons

Neuronal avalanches are a form of spontaneous activity widely observed in cortical slices and other types of nervous tissue, both in vivo and in vitro. They are characterized by irregular, isolated population bursts when many neurons fire together, where the number of spikes per burst obeys a power law distribution. We simulate, using the Gillespie algorithm, a model of neuronal avalanches based on stochastic single neurons. The network consists of excitatory and inhibitory neurons, first with all-to-all connectivity and later with random sparse connectivity. Analyzing our model using the system size expansion, we show that the model obeys the standard Wilson-Cowan equations for large network sizes ( neurons). When excitation and inhibition are closely balanced, networks of thousands of neurons exhibit irregular synchronous activity, including the characteristic power law distribution of avalanche size. We show that these avalanches are due to the balanced network having weakly stable functionally feedforward dynamics, which amplifies some small fluctuations into the large population bursts. Balanced networks are thought to underlie a variety of observed network behaviours and have useful computational properties, such as responding quickly to changes in input. Thus, the appearance of avalanches in such functionally feedforward networks indicates that avalanches may be a simple consequence of a widely present network structure, when neuron dynamics are noisy. An important implication is that a network need not be “critical” for the production of avalanches, so experimentally observed power laws in burst size may be a signature of noisy functionally feedforward structure rather than of, for example, self-organized criticality