Influence of environmental variations on physiological attributes of sunflower

High degree of adaptability, wide range of climatic conditions, high photosynthetic capacity, maximum stomatal conductance and efficient hydraulic mechanism allow sunflower crop to be productive in broad range of environments. Combined effects of environmental factors not only modify plant phenology but also cause many physiological changes. Field experiments, one each in spring and autumn were conducted at Pir Mehr Ali Shah, Arid Agriculture University Rawalpindi, Pakistan for 2 years (2007 and 2008) to document the effect of environmental variations on the physiological functions of sunflower hybrids. Four sunflower hybrids, Alisson-RM, Parasio-24, MG-2 and S-278 were planted in randomized complete block design with 4 replications. The data on physiological attributes like photosynthetic rate, stomatal conductance and transpiration rate at 10 days interval after complete emergence to 60 days after emergence (DAE) was recorded. Overall higher values of photosynthetic rate, stomatal conductance and transpiration rate were recorded during spring as compared to autumn for both the years. Photosynthates accumulation and utilization was depressed in cold imposing a restriction on biomass production than at warm temperature. Physiological performance of all the hybrids during spring at the start was slower as compared to autumn. Progressive increase in photosynthetic rate, stomatal conductance and transpiration was recorded with the gradual increase in temperature up to a certain level during spring but further increase in temperature caused decline in these attributes. However during autumn, values of all these 3 physiological attributes were higher at the start those declined with gradual decrease in temperature later in the season

Material Characterization of 316L Stainless Steel After Being Subjected To Cryogenic Treatment

Post processing of materials is necessary to suit them for the intended requirements. The properties of stainless steel of grade 316L cannot be influenced with further processing such as hot working [1]. Thus the current study aims at investigating the properties of stainless steel of grade 316L after being subjected to deep cryogenic treatment. The specimens from both cryogenically treated and untreated conditions were subjected to Tensile Test, Charpy Impact Test, Rockwell Hardness Test, Microstructure and Percentage Shear Area Analysis and the results thus obtained are discussed in this paper. The results have shown that cryogenic treatment has improved the hardness and strength

Theoretical framework of the causes of construction time and cost overruns

Any construction practitioner fundamental goal is to complete the projects within estimated duration and budgets, and expected quality targets. However, time and cost overruns are regular and universal phenomenon in construction projects and the construction projects in Malaysia has no exemption from the problems of time overrun and cost overrun. In order to accomplish the successful completion of construction projects on specified time and within planned cost, there are various factors that should be given serious attention so that issues such as time and cost overrun can be addressed. This paper aims to construct a framework for the causes of time overrun and cost overrun in construction projects of Malaysia. Based on the relevant literature review, causative factors of time overrun and cost overrun in Malaysian construction projects are summarized and the theoretical frameworks of the causes of construction time overrun and cost overrun is constructed. The developed frameworks for construction time and cost overruns based on the existing literature will assist the construction practitioners to plan the efficient approaches for achieving successful completion of the projects

Growth rhythms in sunflower (Helianthus annuus L.) in response to environmental disparity

Sunflower hybrids maintain high level of stability in a variety of environments. Environmental variations affect and modify plant attributes like growth, development and assimilation through physio-morphicfunctions, thus modifying plant phenology. Field experiments, one each in spring and autumn, were conducted at Pir Mehr Ali Shah, Arid Agriculture University, Rawalpindi, Pakistan for two years (2007 and 2008) to document the effect of environmental variations on growth rhythms of sunflower hybrids. Four Sunflower hybrids, Alisson-RM, Parasio-24, MG-2 and S-278 were planted in randomized complete block design with four replications. The data based on physiological attributes like leaf area (LA),specific leaf area (SLA), crop growth rate (CGR) and net assimilation rate (NAR) at 10 days interval after complete emergence to 60 days after emergence (DAE) were recorded. Overall higher values of LA, SLA, CGR and NAR were recorded during spring as compared to autumn for both years. LA, CGR and NAR of all the hybrids followed a sigmoid curve pattern during both seasons; however, at the start of the season lesser values were observed during spring as compared to autumn. SLA exhibited anopposite trend and continuously decreased till the end. Sigmoid curve pattern of LA, CGR and NAR may be related to environmental variables like temperature and sunshine hours. The decrease after a peak may be due to senescence of older leaves and shifting of crop from vegetative to reproductive phase

Human Behavior Analysis Using Intelligent Big Data Analytics.

Intelligent big data analysis is an evolving pattern in the age of big data science and artificial intelligence (AI). Analysis of organized data has been very successful, but analyzing human behavior using social media data becomes challenging. The social media data comprises a vast and unstructured format of data sources that can include likes, comments, tweets, shares, and views. Data analytics of social media data became a challenging task for companies, such as Dailymotion, that have billions of daily users and vast numbers of comments, likes, and views. Social media data is created in a significant amount and at a tremendous pace. There is a very high volume to store, sort, process, and carefully study the data for making possible decisions. This article proposes an architecture using a big data analytics mechanism to efficiently and logically process the huge social media datasets. The proposed architecture is composed of three layers. The main objective of the project is to demonstrate Apache Spark parallel processing and distributed framework technologies with other storage and processing mechanisms. The social media data generated from Dailymotion is used in this article to demonstrate the benefits of this architecture. The project utilized the application programming interface (API) of Dailymotion, allowing it to incorporate functions suitable to fetch and view information. The API key is generated to fetch information of public channel data in the form of text files. Hive storage machinist is utilized with Apache Spark for efficient data processing. The effectiveness of the proposed architecture is also highlighted

Effect of growing degree days on autumn planted sunflower

Sunflower (Helianthus annus L.) having high degree of adaptability under wide range of climatic conditions, allow the crop to be productive in broad range of environments. Field experiments in autumn were laid out at Pir Mehr Ali Shah, Arid Agriculture University Rawalpindi, Pakistan for two years (2007 and 2008), to document the effect of growing degree days (GDD) on the performance of sunflower hybrids. Four sunflower hybrids, Alisson-RM, Parasio-24, MG-2 and S-278 were planted in randomized complete block design with four replications during autumn season. The data on growing degree days accumulation during autumn and their effect on achene, oil yield and yield components of sunflower like number of achenes per head, hundred achenes weight, biological and achene yield was recorded. All these agronomic characters as well as oil characteristics were influenced by prevailing temperature. GDD collected during autumn season was the same for both years of study. Amongst hybrids, the hybrid MG-2 showed the maximum values for all the agronomic as well as oil parameters during the autumn season. At the late planting of sunflower during autumn season, crop completes its life cycle in short duration and accumulates less heat units, thus, achene and oil yield along with yield attributes are affected accordingly.Key words: Growing degree days (GDD), yield and yield components, sunflower

Cooperative kernels: GPU multitasking for blocking algorithms

There is growing interest in accelerating irregular data-parallel algorithms on GPUs. These algorithms are typically blocking , so they require fair scheduling. But GPU programming models (e.g. OpenCL) do not mandate fair scheduling, and GPU schedulers are unfair in practice. Current approaches avoid this issue by exploit- ing scheduling quirks of today’s GPUs in a manner that does not allow the GPU to be shared with other workloads (such as graphics rendering tasks). We propose cooperative kernels , an extension to the traditional GPU programming model geared towards writing blocking algorithms. Workgroups of a cooperative kernel are fairly scheduled, and multitasking is supported via a small set of language extensions through which the kernel and scheduler cooperate. We describe a prototype implementation of a cooperative kernel frame- work implemented in OpenCL 2.0 and evaluate our approach by porting a set of blocking GPU applications to cooperative kernels and examining their performance under multitasking

Beyond Crossing Fibers: Bootstrap Probabilistic Tractography Using Complex Subvoxel Fiber Geometries

Diffusion magnetic resonance imaging fiber tractography is a powerful tool for investigating human white matter connectivity in vivo. However, it is prone to false positive and false negative results, making interpretation of the tractography result difficult. Optimal tractography must begin with an accurate description of the subvoxel white matter fiber structure, includes quantification of the uncertainty in the fiber directions obtained, and quantifies the confidence in each reconstructed fiber tract. This paper presents a novel and comprehensive pipeline for fiber tractography that meets the above requirements. The subvoxel fiber geometry is described in detail using a technique that allows not only for straight crossing fibers but for fibers that curve and splay. This technique is repeatedly performed within a residual bootstrap statistical process in order to efficiently quantify the uncertainty in the subvoxel geometries obtained. A robust connectivity index is defined to quantify the confidence in the reconstructed connections. The tractography pipeline is demonstrated in the human brain