Pigeonpea (Cajanus cajan L. Millsp.)

Pigeonpea [Cajanus cajan (L.) Millsp.], also known as redgram, is one of the major grain legume (pulses) crops grown in the semiarid tropics (SAT) extending between 30°N and 30°S; it is the second most important food legume of India. It is cultivated in about 50 countries of Asia, Africa, and the Americas for a variety of uses (food, fodder, fuel wood, rearing lac insects, hedges, wind breaks, soil conservation, green manure, roofing, and so on). The constraints of enhancing its productivity include the damage caused by various fungi, bacteria, viruses, and insect pests. Conventional plant breeding methods have not been successful for the improvement of pigeonpea because of genetic variation and incompatibility among the wild varieties. Genetic engineering technology can therefore be used as an additional tool for the introduction of agronomically useful traits into established varieties. The development of plant transformation techniques has been a major breakthrough in overcoming constraints to achieve precision in genetic manipulation. The development of efficient plant regeneration protocols is a prerequisite for recombinant technology to carry out genetic transformation. This chapter describes an Agrobacterium-mediated transformation protocol for pigeonpea, a simple, efficient, and reproducible method that is applicable across diverse genotypes of pigeonpea

Time evolution of the Rabi Hamiltonian from the unexcited vacuum

The Rabi Hamiltonian describes a single mode of electromagnetic radiation interacting with a two-level atom. Using the coupled cluster method, we investigate the time evolution of this system from an initially empty field mode and an unexcited atom. We give results for the atomic inversion and field occupation, and find that the virtual processes cause the field to be squeezed. No anti-bunching occurs.Comment: 25 pages, 8 figures, RevTe

On the development of exponential ansatze for quantum dynamics in finite dimensional vector spaces

A Wei-Norman type of exponential ansatz is constructed for the time evolution operator in finite dimensional vector spaces. Based on an analysis of the structure of the concerned operator algebra, it is shown that a reduction principle exists even for simple algebras that goes beyond the Wei-Norman result when a specific ordering of the operators is used such that the equations of motion for different generators belonging to different classes are decoupled. It is shown that the solution in this case is global. Some specific approximation schemes are considered and their strengths and weaknesses are analyzed. Model calculations are presented to bring out these features

Detection of Data Integrity Attack Using Model and Data-Driven-Based Approach in CPPS

The cyber-physical power system (CPPS) is a modern infrastructure utilising information and communication technology that has become more vulnerable to cyberattacks in recent years. The attack magnitude injected by the adversary is stealthier and it cannot be detected using conventional bad data detection techniques. Protecting sensitive data from data integrity attacks (DIA) is essential for ensuring system security and reliability. A tragic event will occur if the attack goes unreported. Therefore, DIA detection is highly vital for the operator in the control centre to make important decisions. This paper addresses the attack impact on WAC applications and attack detection using the model-based method and data-driven-based methods. On the basis of the validation of performance indicators, various detection approaches are simulated and compared to determine the best detection strategy. Simulation results show that in the model-based anomaly detection method, the recursive polynomial model estimator (RPME) has better detection performance than the recursive least square estimator (RLSE). The convolutional neural network- (CNN-) based data-driven anomaly detection technique outperforms other machine learning (ML) techniques such as support vector machine (SVM), K-nearest neighbour (KNN), and random forest (RF). On the WSCC 3 machine 9-bus system, the efficacy of the suggested methods is evaluated

Lie-algebraic construction of time evolution operator. Application to intramolecular vibrational energy relaxation

A Lie-algebraic construction of a time evolution operator is used to study the intramolecular vibrational relaxation process in a model hydrocarbon. The survival probability of the initial state is calculated. It is found that the Lie-algebraic approach provides a very good description of the decay dynamics of the initially prepared state up to 150 fs even at the one-boson level of approximation

Time-dependent coupled cluster approach to multimode vibronic dynamics

The time-dependent coupled cluster method is used to calculate the dynamics on coupled surfaces. The time-dependent self-consistent-field solution of the initial doorway state is used as the reference state. Autocorrelation functions and spectra of two model systems are presented. It is found that the spurious recurrences in the self-consistent-field autocorrelation functions are eliminated in the coupled cluster approach and the spectral features are correctly reproduced at T=T1+T2 level of approximation

A multireference time-dependent coupled cluster study of the intramolecular vibrational relaxation process

A multireference time-dependent coupled cluster (MRTDCCM) study of the intramolecular vibrational relaxation process in a model hydrocarbon is presented. Two Ansatze, the ordinary exp(S) and the normally ordered exp(S) are used to map the model space component to the exact wavefunction. The survival probability of the initial state and the energy in the CH mode are calculated. It is found that the ordinary MRTDCCM provides a better description than the normally ordered approach for the short-time dynamics