Indigenous techniques of catching the mud eel, <i style="mso-bidi-font-style:normal">Monopterus cuchia</i> (Ham.) in Goalpara district, Assam

109-115Fishing techniques for catching the mud eel, Monopterus cuchia (Ham.) in Goalpara district, Assam was investigated during 2007-10 during the course of a base line survey conducted by the KVK Goalpara, Assam. The complexities of its habitat, behavior and life history characteristics, makes it difficult to catch the fish. Documentation on the fishing methods for catching the mud eel is scanty. This paper is an attempt to record the different technique employed traditionally by the ethnic communities of the district to catch the mud eel based on the information collected during the course of survey. The results revealed use of different wounding gears, ichthyotoxic plants, handline and traps. Wounding gears included spear, knives and sickle. Among plants, Derris elliptica (Wall.) Benth. and Milletia pachycarpa Benth. were used. Spindle shaped and cubical traps are commonly used by the common folks. Other method includes bunding and digging, and light fishing

Adaptive TS-ANFIS neuro-fuzzy controller based single phase shunt active power filter to mitigate sensitive power quality issues in IoT devices

The emergence of Internet of Things (IoT) offers numerous functions, such as intelligent sensor integration, remote sensing, and high-speed data transmission, which have found widespread applications in the smart industry and commercial applications. The associative nonlinear effects of a variety of undesirable power quality concerns were resolved by using harmonic mitigation in nonlinear loads and high-performance converters were built on power electronics in conventional systems. Among other performance objectives, total harmonic (THD) distortion analysis and higher order harmonics mitigation is given main concern in smart electronics equipment. This paper proposes an approach to minimize higher-order harmonics due to nonlinear load disturbances in smart IoT devices using the Takagi–Sugeno (TS) Neuro Fuzzy (TS-ANFIS) supervised shunt APF. The proposed work elicits the novel adaptive harmonic mitigation technique in hybrid IoT embedded systems to protect from malfunctioning and to deal with the uncertainty of harmonic signal stimuli in sensitive sensors-based IoT systems. Hysteresis current control is used for the ignition of reference signal under uncertainty of harmonic stimuli. The single phase shunt APF is used to mitigate higher-order harmonics from supply mains, while the implementation of TS-ANFIS supervises the controller action to generate a trigger signal for adequate single phase APF gate excitation. The higher order harmonic current data set is used for error deviation for training neural networks and adaptive control. The estimated adoption of the neuron's empirical weight reduces the total THD to a significant reduction rate of 72.8 % to 0.78 %. The control mechanism is feasible for a range of smart IoT systems to adhere to the standard of 519 (IEEE)

Development of Cooling System for Gyrotron Collector

In this paper, the development of cooling system for 42 GHz, 200 kW gyrotron collector is presented. The design of the cooling duct has been finalized after different analyses such as, the fluid analysis, the thermal analysis, the structural analysis, etc. All analyses have been carried out by ANSYS software and the development of the cooling system based on the final design is performed

Functional populations among interneurons in the dorsal horn

The superficial dorsal horn of the spinal cord receives input from primary sensory neurons conveying information that is perceived as pain and itch. The vast majority of neurons in this area are interneurons, which form circuits that are essential for the behavioral expression of these percepts. The classes of neuron involved in these circuits and their functions are poorly understood, although recent studies have developed categorization schemes that account for most of these cells. This chapter highlights the important methodologies for identifying interneuron populations in the dorsal horn and discusses these populations in the light of their predicted functions