Engineering Quantum Jump Superoperators for Single Photon Detectors

We study the back-action of a single photon detector on the electromagnetic field upon a photodetection by considering a microscopic model in which the detector is constituted of a sensor and an amplification mechanism. Using the quantum trajectories approach we determine the Quantum Jump Superoperator (QJS) that describes the action of the detector on the field state immediately after the photocount. The resulting QJS consists of two parts: the bright counts term, representing the real photoabsorptions, and the dark counts term, representing the amplification of intrinsic excitations inside the detector. First we compare our results for the counting rates to experimental data, showing a good agreement. Then we point out that by modifying the field frequency one can engineer the form of QJS, obtaining the QJS's proposed previously in an ad hoc manner

Unleashing the Power of VGG16: Advancements in Facial Emotion Recognization

In facial emotion detection, researchers are actively exploring effective methods to identify and understand facial expressions. This study introduces a novel mechanism for emotion identification using diverse facial photos captured under varying lighting conditions. A meticulously pre-processed dataset ensures data consistency and quality. Leveraging deep learning architectures, the study utilizes feature extraction techniques to capture subtle emotive cues and build an emotion classification model using convolutional neural networks (CNNs). The proposed methodology achieves an impressive 97% accuracy on the validation set, outperforming previous methods in terms of accuracy and robustness. Challenges such as lighting variations, head posture, and occlusions are acknowledged, and multimodal approaches incorporating additional modalities like auditory or physiological data are suggested for further improvement. The outcomes of this research have wide-ranging implications for affective computing, human-computer interaction, and mental health diagnosis, advancing the field of facial emotion identification and paving the way for sophisticated technology capable of understanding and responding to human emotions across diverse domains

A Routing Delay Predication Based on Packet Loss and Explicit Delay Acknowledgement for Congestion Control in MANET

In Mobile Ad hoc Networks congestion control and prevention are demanding because of network node mobility and dynamic topology. Congestion occurs primarily due to the large traffic volume in the case of data flow because the rate of inflow of data traffic is higher than the rate of data packets on the node. This alteration in sending rate results in routing delays and low throughput. The Rate control is a significant concern in streaming applications, especially in wireless networks. The TCP friendly rate control method is extensively recognized as a rate control mechanism for wired networks, which is effective in minimizing packet loss (PL) in the event of congestion. In this paper, we propose a routing delay prediction based on PL and Explicit Delay Acknowledgement (EDA) mechanism for data rate and congestion control in MANET to control data rate to minimize the loss of packets and improve the throughput. The experiment is performed over a reactive routing protocol to reduce the packet loss, jitter, and improvisation of throughput

Climate change adaptation and mitigation strategies for sustainable crop production

Climate change is the main environmental problem facing humanity. Evidences over the past few decades show that significant changes in climate are taking place all over the world as a result of enhanced human activities through deforestation emission of various greenhouse gases and indiscriminate use of fossil fuels. Carbon dioxide (CO2) Methane and Nitrous Oxide are the major greenhouse gases. CO2 enters the atmosphere mostly through burning fossil fuels. Methane emissions also result from livestock and other agricultural practices and Nitrous Oxide is emitted during agricultural and industrial activities. Global atmospheric concentration of CO2 has increased from pre-industrial level of 280 parts per million (ppm) to 408 ppm in Feb 2018. Global projections indicate higher temperature of 1.5 to 4.5°C by the year 2050 as a result of enhanced greenhouse gases. There is medium confidence in that the Indian summer monsoon circulation weakens but this is compensated by increased atmospheric moisture content leading to more rainfall. There is medium confidence in an increase of Indian summer monsoon rainfall and its extremes throughout the 21st century under all RCP (Representative Concentration Pathways) scenarios

Apoptosis induction of Centella asiatica on human breast cancer cells

The present study evaluated the ability of methanolic extract of Centella asiatica (Linn) Urban (Umbelliferae) to induce apoptosis in different cancer cell lines. MCF-7 cells emerged as the most sensitive cell line for in vitro growth inhibitory activity. C. asiatica extract induced apoptosis in MCF-7 cells as indicated by nuclear condensation, increased annexin staining, loss of mitochondrial membrane potential and induction of DNA breaks identified by TUNEL reactivity. It is possible that the use of C. asiatica extract as a component in herbal medicines could be justifiable.Key words: Apoptosis, Cancer, Centella asiatic

Onion and Garlic Research in India

Onion and garlic research in India has produced 45 open-pollinated and two F1 hybrids in onion and approximately 25 varieties in garlic. Red onion is used for domestic consumption and export while the white onion is used mostly for processing. Improvement in garlic has been largely through clonal selection and mutation breeding. Somaclonal variations for development of varieties have not been used till now. Research on biotechnology for crop improvement in onion and garlic in India is in a nascent stage. While research on crop production has seen tremendous improvement, research on organic production and precision farming, good agricultural practices and mechanization needs to be carried out in future. Similarly, studies on plant protection have identified researchable issues for future work. This paper gives a brief overview of onion and garlic research scenario in India and technologies needed to be developed and practiced

Observation of direct and indirect magnetoelectricity in lead free ferroelectric (Na 0.5Bi 0.5TiO 3)-magnetostrictive (CoFe 2O 4) particulate composite

A particulate composite consisting of 65 mol. % Na 0.5Bi 0.5TiO 3 and 35 mol. % CoFe 2O 4 was synthesized, and it's structure, microstructure, ferroelectric, magnetostrictive, magnetic, and direct/indirect magnetoelectric properties were studied. The composite showed different magnetization behaviour under electrically poled and un-poled conditions. The percentage change in magnetization as a result of poling is approximately -15% at 500 Oe magnetic field. Magnetostriction measurements displayed a value of λ 11 = -57 × 10 -6 and piezomagnetic coefficient δλ 11/δH = 0.022 × 10 -6 kOe -1 at 2.2 kOe for the composite. The maximum magnetoelectric output varied from 1350 mV/cm to 2000 mV/cm with change in the electrical poling condition

Measurements continuous in time and a posteriori states in quantum

Measurements continuous in time were consistently introduced in quantum mechanics and applications worked out, mainly in quantum optics. In this context a quantum filtering theory has been developed giving the reduced state after the measurement when a certain trajectory of the measured observables is registered (the a posteriori states). In this paper a new derivation of filtering equations is presented, in the cases of counting processes and of measurement processes of diffusive type. It is also shown that the equation for the a posteriori dynamics in the diffusive case can be obtained, by a suitable limit, from that one in the counting case. Moreover, the paper is intended to clarify the meaning of the various concepts involved and to discuss the connections among them. As an illustration of the theory, simple models are worked out.Comment: 31 page. See also related papers at http://www.maths.nott.ac.uk/personal/vpb/research/mes_fou.html and http://www.maths.nott.ac.uk/personal/vpb/research/fil_con.htm

Understanding the Evolution of Plant Growth-Promoting Rhizobacteria

Soil is an integral part of the complicated natural environment which is very much alive with complex ecosystem of microbes. Among them, the symbiotic association of rhizobacteria with plants especially on agriculturally important crops is very much advantageous in improving the soil and plant health. These plant growth-promoting rhizobacteria (PGPR) have evolved over the years and involved in many plant functions such as growth promotion, root development, colonization, production of metabolites and in eliciting plant defence mechanism against abiotic and biotic agents. The PGPR’s ability to fix the atmospheric nitrogen, solubilize phosphate, potassium and zinc, produce siderophore along with wide variety of phytohormones and secondary metabolites such as antibiotics have attributed to their significance as biocontrol agents. These functions lead to their application as biofertilizers, biopesticides, bioprotectants and phytostimulators. The employment of these PGPR is very much important in agricultural fields as they reduce the burden of chemical fertilizers and pesticides to the farmers and in turn promises an increased crop yield. This chapter discusses the symbiotic association of PGPR with plants in detail including their direct and indirect mechanisms and basis of their induced systemic defence mechanism. It also highlights the use of bioinoculants and nanoformulations of PGPR as an effective tool towards enhanced agricultural production and to combat the plant diseases in an eco-friendly manner

Management of Fungal Diseases of Chickpea (Cicer arietinum L.) through Plant Growth Promoting Actinobacteria and Their Secondary Metabolites

Chickpea (Cicer arietinum L.) is an important pulse crop and ranks third in overall production after bean and pea on a world basis. It is grown in 33 countries over an area of about 11.5 million hectares (Bidyarani et al. 2016). Chickpea is mainly used as food because of its high protein (12−31%) and carbohydrate (52−71%) contents (Mergaand Haji 2019). Global yields of chickpea (968 kg ha−1) have been stagnant for the past five decades in spite of using various conventional and molecular breeding approaches and extensive use of synthetic fertilizers and pesticides (FAOSTAT 2014). Productivity of chickpea may be considerably improved if the adverse effects of biotic stresses (such as Ascochyta blight, dry root rot, Fusarium wilt, collar rot, and Botrytis gray mold) are addressed. Management of fungal diseases of chickpea is difficult, as no single control measure is fully effective. Some of the control measures such as advanced sowing date, solarization of soil, use of pathogen-free seed and fungicide-treated seed are usually employed to control the diseases, but with limited success. The use of resistant cultivar is the most efficient control measure but the effectiveness of disease resistance is restricted by the occurrence of several races of the pathogen. Hence, there is a need to use biological options to manage plant pathogens