An Approach of Stipulation Change Management Using Cloud Computing

Every technology project's successful implementation depends on the requirements. Changes in stipulations at any point of the software development life cycle are considered a healthy operation. Nevertheless, this transition is a little simpler in a co-located setting than in a decentralized system in which participants are spread over more than one area. This presents numerous challenges, such as coordination, communication & control, effective and efficient management of changes and the management of central repositories. Cloud computing can therefore be used to mitigate these stakeholder problems. We used a case study to test the system of cloud computing

Microscopic observations and simulations of Bloch walls in nematic thin films

© 2006 American Physical Society. The electronic version of this article is the complete one and can be found online at: http://link.aps.org/doi/10.1103/PhysRevLett.97.157801DOI: 10.1103/PhysRevLett.97.157801We study Bloch wall defects formed by quenching nematic thin films from planar anchoring to homeotropic anchoring through a temperature-driven anchoring transition. The director profiles of the walls are directly visualized using fluorescence confocal polarizing microscopy, and shown to agree well with the simulation based on the Frank elasticity theory. A pure twist wall exists if the ratio of sample thickness to surface extrapolation length p is smaller than or close to 1; while a diffuse Bloch wall is obtained if p is much greater than 1

Cost regulation and power quality enhancement for PV-wind-battery system using grasshopper optimisation approach

Renewable energy sources perform a potential role in the electrical industry for meeting the required load demand. However, the difficult aspect is to be reduced the entire cost including initial cost, operational cost, replacement cost and maintenance cost. Hence, to achieve this target, a grasshopper optimisation algorithm (GOA) is suggested in this work for optimum sizing of the off-grid. In this study, various power-generating renewable sources such as photovoltaic (PV), wind turbines (WTs) and batteries are integrated into the off-grid system. Moreover, solar irradiance, wind speed and required load are simulated by the HOMER software for 12 months of a year. Further, the performance of the suggested GOA is compared by hybrid genetic algorithm (GA) with particle swarm optimisation (PSO) (GA-PSO) for optimum sizing of the WTs and PV. As per the simulation outcome, the suggested GOA shows better performance and contributes the less levelised cost of energy factor (LFC = 0.502) as compared to studied GA-PSO

New Symmetries in Crystals and Handed Structures

For over a century, the structure of materials has been described by a combination of rotations, rotation-inversions and translational symmetries. By recognizing the reversal of static structural rotations between clockwise and counterclockwise directions as a distinct symmetry operation, here we show that there are many more structural symmetries than are currently recognized in right- or left-handed handed helices, spirals, and in antidistorted structures composed equally of rotations of both handedness. For example, though a helix or spiral cannot possess conventional mirror or inversion symmetries, they can possess them in combination with the rotation reversal symmetry. Similarly, we show that many antidistorted perovskites possess twice the number of symmetry elements as conventionally identified. These new symmetries predict new forms for "roto" properties that relate to static rotations, such as rotoelectricity, piezorotation, and rotomagnetism. They also enable symmetry-based search for new phenomena, such as multiferroicity involving a coupling of spins, electric polarization and static rotations. This work is relevant to structure-property relationships in all material structures with static rotations such as minerals, polymers, proteins, and engineered structures.Comment: 15 Pages, 4 figures, 3 Tables; Fig. 2b has error

Association of the resolvin precursor 17-HDHA, but not D- or E- series resolvins, with heat pain sensitivity and osteoarthritis pain in humans

Resolvins are omega-3 fatty acid derived potent bioactive lipids that resolve inflammation and modulate transient receptor potential channels. Exogenous administration of the resolvin precursor 17-HDHA shows a strong analgesic effect in animal models of osteoarthritis and acute inflammatory pain, but has not been studied in humans. Our aim was to assess the role of 17-HDHA and resolvins in heat pain sensitivity and in osteoarthritis pain in humans. Resolvins D1, D2, D3, D5, E1 and 17-HDHA, were measured by liquid chromatography-mass spectrometry and tested for association with heat pain thresholds in 250 healthy volunteers who had undergone quantitative sensory testing. Resolvins D1, D2 and 17-HDHA were then tested in 62 individuals affected with knee osteoarthritis and 52 age matched controls and tested for association with knee pain. Circulating levels of docosahexaenoic acid (DHA) were also measured. Levels of 17-HDHA, but not those of the other 5 resolvins tested, were associated with increased heat pain thresholds (beta = 0.075; 95%CI 0.024, 0.126; p<0.0046). 17-DHDA was associated with lower pain scores in OA patients (beta -0.41; 95%CI-0.69, -0.12; p<0.005; adjusted for covariates) but not with osteoarthritis. The associations of 17-HDHA associations with heat pain sensitivity and osteoarthritis pain were independent of DHA levels

Ultra-short-term PV power forecasting based on a support vector machine with improved dragonfly algorithm

Photo-voltaic (PV) is one of the most abundant sources on the earth for the generation of electricity. Although, due to the stochastic nature of PV characteristics to sustain constant power, an accurate PV power prediction is needed for a grid-connected PV system. The proposed model of support vector machine (SVM) with improved dragonfly algorithm(IDA) is used to forecast the PV power. Previously, Theexecution can be done by dragonfly algorithm (DA) through adaptive learning factor along with the differential evolution technique. The IDA is used to select the best support vector machine parameters. Eventually, the suggested model provides better performance as compared to the other algorithm such as SVM with dragonfly algorithm(SVM-DA). It is suitable for forecasting ultra-short-term PV power

Plasma lipid biomarker signatures in squamous carcinoma and adenocarcinoma lung cancer patients

There is a clinical need for reliable biomarkers for lung cancer that permit early diagnosis of the disease and provide prediction of histological phenotype. A prospective study design was used with a study population of patients with suspected lung cancer. Blood samples were collected from 17 patients with histologically confirmed squamous cell lung carcinoma, 17 individuals with adenocarcinoma, and 17 control individuals who did not subsequently have a diagnosis of lung cancer or any other cancer. Blood plasma samples were analysed for their lipid profiles using liquid chromatography coupled with high resolution mass spectrometry. Data were analysed using multivariate statistical methods. There was good separation between histological subtypes and control groups and also between individuals with a subsequent diagnosis of adenocarcinoma and squamous cell carcinoma (sensitivity 80 %, specificity 83 %, Q2 = 0.70). Alterations in the levels of different classes of lipids including triglycerides (TGs), phosphatidylinositols (PIs), phosphatidylcholines (PCs), phosphatidylethanolamines (PEs), free fatty acids, lysophospholipids and sphingolipids were observed in squamous carcinoma and adenocarcinoma lung cancer patients when compared with control patients. In conclusion, this study has identified candidate lipid biomarkers of non-small cell lung cancer patients which may be helpful to indicate the tumour subtype and to differentiate them from patients who do not have lung cancer. Measuring these biomarkers has the potential to improve diagnosis in patients with suspected lung cancer and risk stratification in screening