Chandigarh University

About: Chandigarh University is a education organization based out in Mohali, India. It is known for research contribution in the topics: Computer science & Chemistry. The organization has 1358 authors who have published 2104 publications receiving 10050 citations.

γ-Aminobutyric acid (GABA) mitigates drought and heat stress in sunflower (Helianthus annuus L.) by regulating its physiological, biochemical and molecular pathways.

Abstract: Drought and heat stress are two dominant abiotic stress factors that often occur simultaneously in nature causing oxidative damage in plants and thus decline in yield. The present study was conducted to examine the γ-aminobutyric acid (GABA)-induced heat and drought tolerance in sunflower through physiological, biochemical and molecular analysis. The results showed that drought and heat stress triggered oxidative stress as revealed by enhanced level in hydrogen peroxide, malondialdehyde and electrolyte leakage. Moreover, the photosynthetic attributes such as photosynthetic rate, stomatal conductance and quantum efficiency declined when subjected to drought and heat stress. In this study, GABA treatment effectively alleviated the drought and heat-induced stress as reflected by significantly higher levels of proline, soluble sugar and total protein content. Besides, the data also revealed the direct relationship between antioxidant enzyme activities (superoxide dismutase, peroxidase, glutathione reductase, monodehydroascorbate peroxidase, ascorbate peroxidase) and the relative expression of genes (Heat Shock Proteins, Dehydrin, Osmotin, Aquaporin, Leaf Embryogenesis Protein), under drought and heat stress. Moreover, a significant increase in gene expression was observed upon GABA treatment with respect to control. This data suggest that GABA-induced drought and heat tolerance in sunflower could involve the improvement in osmolyte metabolism, gene expression and antioxidant enzyme activities and thus a rise in the GABA shunt which in turn provides intermediates during long-term drought and heat stress, thus maintaining homeostasis.

Surface active magnetic iron oxide nanoparticles for extracting metal nanoparticles across an aqueous–organic interface

Abstract: Highly surface active magnetic nanoparticles (Fe3O4 NPs) were synthesized by using tetraalkylammonium and imidazolium Gemini surfactants. They were further used in the extraction of metallic Au and Ag NPs from the aqueous bulk through NP–NP interactions to demonstrate the extraction efficiency and environmental sustainability of Fe3O4 NPs. The Fe3O4 NPs were synthesized by a hydrothermal synthesis at 150 °C, which allowed the Gemini surfactant molecules to simultaneously adsorb and stabilize the Fe3O4 NPs. The surface adsorption of Gemini surfactant molecules occurred through the head group region, which helped the double hydrocarbon tails to induce aqueous–organic surface active ability in the Fe3O4 NPs. The surface active NPs thus obtained were subjected to the extraction process to extract the aqueous solubilized Au and Ag NPs from the aqueous bulk. The extraction efficiency was driven by the length of double hydrocarbon chains and the head group modifications of Gemini surfactants. Although both hydrophobic and hydrophilic interactions participated in the extraction process, the extraction was mainly facilitated by the hydrophobic interactions operating between the surface active Fe3O4 NPs and bulk solubilized Au and Ag NPs.

Scaling Down Power Utilization with Optimal Virtual Machine Placement Scheme for Cloud Data Center Resources: A Performance Evaluation

Abstract: Cloud computing provides IT Services to the user throughout the world according to their needs. There is a huge usage of electric power dues to the accelerating demand for large scale data centres required for processing potential, by scientific web operations. To provide high-level computation in large scale for a distributed system such as clouds an enormous amount of energy is consumed and handling this energy by applying an optimal virtual machine scheme is a major task. We have defined an architectural framework for energy conscious mapping of available virtual machines to appropriate data center resources in addition to dynamic combination of virtual machine scheduling scheme in this paper. Clusters of the server are contained by the cloud infrastructure modelled. It also represents the cluster management and the factors inside the clusters. Also, the data recovery is presented in a best possible way, taking in consideration that backup not only act as a backup but also helpful in the energy consideration process, by using two space backup (one in guiding cluster and one at secondary cluster) making model more powerful and resistible in case of data recovery. Experiments results demonstrate that the performance of the proposed scheme is found to be remarkable in comparison to the other state-of-the-art competing scheme of its class.

A multilevel thresholding algorithm using LebTLBO for image segmentation

Abstract: Segmentation is considered as one of the most significant tasks in image processing. It consists of separating the pixels into different segments based on their intensity level according to threshold values. Selecting the optimal threshold value is the key to best quality segmentation. Multilevel thresholding (MT) is an essential approach for image segmentation, and it has become very popular during the past few years, but while increasing the level of thresholds, computational complexity also increases exponentially. In order to overcome this drawback, several metaheuristics-based algorithms have been used for determining the optimal MT levels. Learning enthusiasm-based teaching–learning-based optimization (LebTLBO) is a recently developed efficient, simple-to-implement and computationally inexpensive algorithm. It simulates the behaviors of the teaching and learning process in a classroom and gives the probability of getting the amount of information by the learner (student) from the educator. In this paper, LebTLBO is applied on ten standard test images having a diverse histogram, which are taken from Berkeley Segmentation Dataset 500 (BSDS500) (Martin et al. in a database of human segmented natural images and its application to evaluate segmentation algorithms and measure ecological statistics, 2001) benchmark image set for segmentation. The search capability of the algorithm is combined with Otsu and Kapur’s entropy MT objective functions for image segmentation. The proposed approach is compared with the existing state-of-the-art optimization algorithms such as MTEMO, GA, PSO and BF for both Otsu and Kapur’s entropy methods. Qualitative experimental outcomes demonstrate that LebTLBO is highly efficient in terms of performance metrics such as PSNR, mean, threshold values, number of iterations taken to converge and image segmentation quality.

Retrospection of the Optimization Model for Designing the Power Train of a Formula Student Race Car

Abstract: This article describes the power train design specifics in Formula student race vehicles used in the famed SAE India championship. To facilitate the physical validation of the design of the power train system of a formula student race car category vehicle engine of 610 cc displacement bike engine (KTM 390 model), a detailed design has been proposed with an approach of easing manufacturing and assembly along with full-scale prototype manufacturing. Many procedures must be followed while selecting a power train, such as engine displacement, fuel type, cooling type, throttle actuation, and creating the gear system to obtain the needed power and torque under various loading situations. Keeping the rules in mind, a well-suited engine was selected for the race track and transmission train was selected which gives the maximum performance. Based on the requirement, a power train was designed with all considerations we need to follow. Aside from torque and power, we designed an air intake with fuel efficiency in mind. Wireless sensors and cloud computing were used to monitor transmission characteristics such as transmission temperature management and vibration. The current study describes the design of an air intake manifold with a maximum restrictor diameter of 20 mm.