A Data-driven Approach for Detecting Stress in Plants Using Hyperspectral Imagery

A phenotype is an observable characteristic of an individual and is a function of its genotype and its growth environment. Individuals with different genotypes are impacted differently by exposure to the same environment. Therefore, phenotypes are often used to understand morphological and physiological changes in plants as a function of genotype and biotic and abiotic stress conditions. Phenotypes that measure the level of stress can help mitigate the adverse impacts on the growth cycle of the plant. Image-based plant phenotyping has the potential for early stress detection by means of computing responsive phenotypes in a non-intrusive manner. A large number of plants grown and imaged under a controlled environment in a high-throughput plant phenotyping (HTPP) system are increasingly becoming accessible to research communities. They can be useful to compute novel phenotypes for early stress detection. In early stages of stress induction, plants manifest responses in terms of physiological changes rather than morphological, making it difficult to detect using visible spectrum cameras which use only three wide spectral bands in the 380nm - 740 nm range. In contrast, hyperspectral imaging can capture a broad range of wavelengths (350nm - 2500nm) with narrow spectral bands (5nm). Hyperspectral imagery (HSI), therefore, provides rich spectral information which can help identify and track even small changes in plant physiology in response to stress. In this research, a data-driven approach has been developed to identify regions in plants that manifest abnormal reflectance patterns after stress induction. Reflectance patterns of age-matched unstressed plants are first characterized. The normal and stressed reflectance patterns are used to train a classifier that can predict if a point in the plant is stressed or not. Stress maps of a plant can be generated from its hyperspectral image and can be used to track the temporal propagation of stress. These stress maps are used to compute novel phenotypes that represent the level of stress in a plant and the stress trajectory over time. The data-driven approach is validated using a dataset of sorghum plants exposed to drought stress in a LemnaTec Scanalyzer 3D HTPP system. Advisers: Ashok Samal and Sruti Das Choudhur

Work Alienation and its Gravediggers: Social Class, Class Consciousness, and Activism

Work activity is central to human psychology. However, working conditions under capitalist socioeconomic relations have been posited as psychologically alienating. Given the negative impact of work alienation on well-being and mental health, we conducted two studies of the relations between social class, work conditions, and alienation. We also examined factors that might counteract alienation – class consciousness and activism. The utility of a Marxist measure of social class – based on objective work relations – was compared with that of SES and subjective class measures. Study 1 surveyed 240 U.S. adults from diverse socioeconomic backgrounds using Amazon’s Mechanical Turk; Study 2 was a replication with 717 adults recruited via a sampling company. Across studies, alienation was predicted by perceived work exploitation, poor work relationships, and lack of self-expression, meaningfulness, self-actualization, autonomy, and intrinsic motivation at work. Only the Marxist class measure – not SES or subjective class measures – predicted alienation and alienating work conditions across studies. Working-class participants experienced more alienating work conditions and greater alienation. Alienation was correlated with class consciousness, and class consciousness was associated with activism. While SES measures have dominated the psychological study of social class, results suggest benefits to integrating Marxist measures and conceptions of social class

Steam Turbine Design, Operation, and Maintenance

Discussion GroupOverhaul intervals Maintenance practices Solid particle erosion Contract versus in-house maintenance Mechanical driver turbine issues - design et al Steam path repairs Turbine casing and alignment issues Steam turbine performance, degradation, etc. Reliability/availabilit

Sales Management Portal

The sales management portal is online web based application where the user will be able to keep a track of all the sales made by an organization with respect to the projects being handled by the organization. Apart from tracking the sales data the other features include creation of projects, teams, managing the team members, communication among the users, search functionality for the projects, teams and users and project tracking. The application supports three levels of users where each user with respect to the role will have different functionality and user authorization is made at even page level to make sure that only authorized data updates are made on the database

Steam Turbine Design, Operation, and Maintenance

Discussion Grou

Driver Selection for Mechanical Drive Service

TutorialThis panel will cover different types of drivers for mechanical drive service including steam and gas turbines, electric motors and heat recovery cycles. Panel members will discuss the different technologies available, and how they fit into a decision matrix for different projects. The discussion will be technology neutral, with a focus only on approaches for driver selection, technical aspects, pros and cons of different technologies, and a brief discussion relating to key issues such as life cycle costs, reliability, efficiency, maintenance, larger driver sizes, new technologies and trends in the Oil and Gas Industry

Electric Vehicle Charging Load Allocation at Residential Locations Utilizing the Energy Savings Gained by Optimal Network Reconductoring

In this study, a two-stage methodology based on the energy savings gained by optimal network reconductoring was developed for the sizing and allocation of electric vehicle (EV) charging load at the residential locations in urban distribution systems. During the first stage, the Flower Pollination Algorithm (FPA) was applied to minimize the annual energy losses of the radial distribution system through optimum network reconductoring. A multi-objective function was formulated to minimize investment, peak loss, and annual energy loss costs at different load factors. The results obtained with the flower pollination algorithm were compared with the particle swarm optimization algorithm. In the second stage, a simple heuristic procedure was developed for the sizing and allocation of EV charging load at every node of the distribution system utilizing part of the annual energy savings obtained by optimal network reconductoring. The number of electric cars, electric bikes, and electric scooters that can be charged at every node was computed while maintaining the voltage and branch current constraints. The simulation results were demonstrated on 123 bus and 51 bus radial distribution networks to validate the effectiveness of the proposed methodology

Enantioselective method development and validation of proline by using high performance liquid chromatography

Chirality is a major concern in the modern pharmaceutical industry. The separation of chiral compounds has been of great interest because the majority of bioorganic and synthetic molecules are chiral. Aim of the present investigation was to develop a stereo specific, simple and precise normal phase high performance liquid chromatography (NP - HPLC) method for the separation and enantiopurity of Dextro (D) and Levo (L) enantiomers of proline (PRO) by using Lux 5m Amylose 1 LC column (250.6mm) by using n- Hexane: Iso propyl alcohol (IPA)as mobile phase in the ratios of 90:10 v/v at flow rate of 1.2 ml/ min. D and L forms of PRO was detected at 210nm with retention time of 8.1min and 9 min respectively with correlation coefficient (R 2 ) of 0.999.The method was validated with reference to International conference of harmonization (ICH) in terms of linearity, accuracy, precision (Inter - day and intra - day precision), limit of detection (LOD), limit of quantification (LOQ), stability of test solutions, specificity, system suitability, robustness and ruggedness