Studies On The Effect Of Laser Radiation And Other Mutagens On Plants

The effect of lasers of three wavelengths in the visible region - 476, 488 and 514 nm on mitotic and meiotic cell divisions, growth, yield and activity of specific enzymes were studied in two taxonomically diverse plant species — A/lium cepa L. and Vicia faba. The effect of laser exposures was compared with the effect of two physical mutagens (Gamma and Ultraviolet radiations) and two chemical mutagens (Ethyl Methane Sulphonate and Hydroxyl amine). The study indicated that lasers could be mutagenic causing aberration in the mitotic and meiotic cell divisions while also producing changes in the growth and yield of the plants. Lasers of higher wavelengths 488 and 514 nm caused aberrations in the early stages of mitotic cell division whereas lasers of lower wavelengths (476 nm) caused more aberrations in the later stages of mitotic cell division. Laser exposure of 488 nm wavelength at power density 400 mW induced higher mitotic and meiotic aberrations and also induced higher pollen sterility than lasers of 476 and 514 nm. The frequency of mitotic aberrations induced by lasers was lesser than that caused by y-irradiation but comparable to that induced by EMS and HA. Lasers cause mutations in higher frequencies than UV. Lasers had a stimulatory effect on growth and yield in both plant species. This stimulatory effect of lasers on germination could not however be correlated to the activity of amylase and protease, the key enzymes in seed gennination. Enzymes such as peroxidase and catalase, involved in scavenging of free oxygen radicals often produced by irradiation, did not show increased activity in laser irradiated samples. Further studies are required for elucidating the exact mechanisms by which lasers cause mutations

On the generalized obnoxious center problem: antimedian subsets

The set of vertices that maximize (minimize) the remoteness is the antimedian (median) set of the profile. It is proved that for an arbitrary graph G and S V (G) it can be decided in polynomial time whether S is the antimedian set of some profile. Graphs in which every antimedian set is connected are also considered.

Microstrip Antennas For Mobile Telephone Handset With Reduced Radiation Hazards

A novel antenna configuration comprised of two circular microstrip antennas (CMAs) resonating in the TMtt and TM2, modes, producing radiation characteristics suitable for a mobile telephone handset, is presented. The antennas operating at the same frequency are placed back to back with a separation comparable to the thickness of a typical handset. The radiation pattern consists of a region of reduced radiation intensity, which minimizes the radiation hazards to the user

Reinforcement Learning approaches to Economic Dispatch problem

This paper presents Reinforcement Learning (RL) approaches to Economic Dispatch problem. In this paper, formulation of Economic Dispatch as a multi stage decision making problem is carried out, then two variants of RL algorithms are presented. A third algorithm which takes into consideration the transmission losses is also explained. Efficiency and flexibility of the proposed algorithms are demonstrated through different representative systems: a three generator system with given generation cost table, IEEE 30 bus system with quadratic cost functions, 10 generator system having piecewise quadratic cost functions and a 20 generator system considering transmission losses. A comparison of the computation times of different algorithms is also carried out.

Reinforcement Learning Solution for Unit Commitment Problem Considering Minimum Start Up and Shut Down Times

Unit Commitment Problem (UCP) in power system refers to the problem of determining the on/ off status of generating units that minimize the operating cost during a given time horizon. Since various system and generation constraints are to be satisfied while finding the optimum schedule, UCP turns to be a constrained optimization problem in power system scheduling. Numerical solutions developed are limited for small systems and heuristic methodologies find difficulty in handling stochastic cost functions associated with practical systems. This paper models Unit Commitment as a multi stage decision making task and an efficient Reinforcement Learning solution is formulated considering minimum up time /down time constraints. The correctness and efficiency of the developed solutions are verified for standard test systems

Reinforcement Learning solution for Unit Commitment Problem through pursuit method

Unit commitment is an optimization task in electric power generation control sector. It involves scheduling the ON/OFF status of the generating units to meet the load demand with minimum generation cost satisfying the different constraints existing in the system. Numerical solutions developed are limited for small systems and heuristic methodologies find difficulty in handling stochastic cost functions associated with practical systems. This paper models Unit Commitment as a multi stage decision task and Reinforcement Learning solution is formulated through one efficient exploration strategy: Pursuit method. The correctness and efficiency of the developed solutions are verified for standard test systems

Testing Isotropy and a related Random Walk problem

One comes across directions as the observations in a number of situations. The first inferential question that one should answer when dealing with such data is, “Are they isotropic or uniformly distributed?” The answer to this question goes back in history which we shall retrace a bit and provide an exact and approximate solution to this so-called “Pearson’s Random Walk” problem.

Employment Realm in Technical Education in Kerala-A Study on the Problem of Unemployment among Engineers

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