On Optimal and Fair Service Allocation in Mobile Cloud Computing

This paper studies the optimal and fair service allocation for a variety of mobile applications (single or group and collaborative mobile applications) in mobile cloud computing. We exploit the observation that using tiered clouds, i.e. clouds at multiple levels (local and public) can increase the performance and scalability of mobile applications. We proposed a novel framework to model mobile applications as a location-time workflows (LTW) of tasks; here users mobility patterns are translated to mobile service usage patterns. We show that an optimal mapping of LTWs to tiered cloud resources considering multiple QoS goals such application delay, device power consumption and user cost/price is an NP-hard problem for both single and group-based applications. We propose an efficient heuristic algorithm called MuSIC that is able to perform well (73% of optimal, 30% better than simple strategies), and scale well to a large number of users while ensuring high mobile application QoS. We evaluate MuSIC and the 2-tier mobile cloud approach via implementation (on real world clouds) and extensive simulations using rich mobile applications like intensive signal processing, video streaming and multimedia file sharing applications. Our experimental and simulation results indicate that MuSIC supports scalable operation (100+ concurrent users executing complex workflows) while improving QoS. We observe about 25% lower delays and power (under fixed price constraints) and about 35% decrease in price (considering fixed delay) in comparison to only using the public cloud. Our studies also show that MuSIC performs quite well under different mobility patterns, e.g. random waypoint and Manhattan models

Oxidation of Hydrazine, Phenylhydrazine & Substituted henylhydrazines by Thallium (III) - Substituent Effects & Mechanism

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Social and technological dimensions; and constraint analysis in sugarcane cultivation of Theni district of Tamil Nadu, India

Bridging the yield gap in any crop cultivation should be the prime objective of any research efforts. By following the recommended production-cum-protection technologies, farmers can bridge the yield gap in any crop. As per sugarcane is concerned, the average cane yield in Tamil Nadu is 101 t/ha, which is lower than the potential yield of 203.7 t/ha resulting in yield gap of 50.42%. With this in mind, a study has been initiated to explore the social and technology dimensions and constraints involved in cane cultivation to addressing the issue of yield gap. Six blocks from Theni district under Rajshree Sugars & Chemicals Ltd were selected as study area. Information collected from sixty sugarcane farmers with semi structured interview schedule. The study revealed that majority (91.7%) of the respondents had more than 5 years of experience in sugarcane cultivation. Further, it revealed that the technologies, seed rate (83.3%), planting season (75.00%), primary tillage with mould board / disc plough (67%), gap filling, two split application of N and K (58.3%) and Organic fertilizer application  (58.3%), stubble shaving, off baring (50.0%) had adoption rate of more than 50 percentage. Major constraints faced by cent per cent of the respondents were; non availability of labour and high labour cost, prolonged drought and water scarcity, low procuring cost per by sugar factory, yield reduction due to continuous cultivation of sugarcane. The novelty and importance of the study is that it mainly analysis all the sugarcane production and protection technologies from seed rate to harvest in three point continuum viz., fully adopted, partially adopted and not adopted

Inverse relationship between serum high density lipoprotein and negative syndrome in antipsychotic-naive schizophrenia

Background: Recent literature suggests a role for apolipoprotein L (apoL) aberrations in the pathogenesis of schizophrenia. ApoL is almost exclusively associated with apolipoprotein A-I in high-density lipoproteins (HDLs). The objective of this study was to examine the correlation between symptom scores and serum HDL in antipsychotic-naive schizophrenia patients. Methods: In this cross-sectional study, 60 antipsychotic-naive schizophrenia patients were systematically examined for their symptom scores, with good inter-rater reliability. Concurrently, an overnight fasting serum lipid profile from these patients was assessed. Results: Serum HDL had a significant inverse correlation with a total negative syndrome score (ρ=−0.43; p=0.001). Conclusions: The study observation supports the potential role for HDL abnormalities in the genesis of negative symptoms in schizophrenia. Clin Chem Lab Med 2010;48:95–8.Peer Reviewe

Comparison of Time Domain Reflectometry Performance Factors for Several Dielectric Geometries: Theory and Experiments

We propose three nontraditional dielectric geometries and present an experimental and theoretical analysis and comparison of time domain reflectometry (TDR) performances for them. The traditional geometry (the probes inserted in material of essentially infinite extent) is compared to three nontraditional geometries where the probes are affixed outside of a core sample, inside of a bore, or flat on the surface of a semi‐infinite solid. Our derivation relates the velocity of electromagnetic wave propagation to the complex permittivities and permeabilities of the media and the geometry for the three nontraditional configurations. Experimental results for air, styrofoam, dry sand, wet sand of varying water content, nylon, dry wood, and ferromagnetic steel are obtained for the three proposed configurations and are in fair agreement with the literature within the experimental uncertainties. Through experiments and theoretical analysis, the TDR performance is found to be the same within the experimental uncertainties for the three nontraditional geometries. The proposed geometries yield slightly lower sensitivities compared to the traditional geometry. Advantages and disadvantages of the geometries compared to the traditional geometry are also discussed

Spectral Graph Analysis for Process Monitoring

Process monitoring is a fundamental task to support operator decisions under ab- normal situations. Most process monitoring approaches, such as Principal Components Analysis and Locality Preserving Projections, are based on dimensionality reduction. In this paper Spectral Graph Analysis Monitoring (SGAM) is introduced. SGAM is a new process monitoring technique that does not require dimensionality reduction techniques. The approach it is based on the spectral graph analysis theory. Firstly, a weighted graph representation of process measurements is developed. Secondly, the process behavior is parameterized by means of graph spectral features, in particular the graph algebraic connectivity and the graph spectral energy. The developed methodology has been illustrated in autocorrelated and non-linear synthetic cases, and applied to the well known Tennessee Eastman process benchmark with promising results.Fil: Musulin, Estanislao. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Rosario. Centro Internacional Franco Argentino de Ciencias de la Información y Sistemas; Argentin

Minimum Thermal Conductivity of Superlattices

The phonon thermal conductivity of a multilayer is calculated for transport perpendicular to the layers. There is a cross over between particle transport for thick layers to wave transport for thin layers. The calculations shows that the conductivity has a minimum value for a layer thickness somewhat smaller then the mean free path of the phonons.Comment: new results added, to appear in PR

Emotion Processing Deficit in Euthymic Bipolar Disorder: A Potential Endophenotype

Background: Emotion processing deficits have been described in patients with bipolar disorder (BD) and are considered one of the core cognitive abnormalities in BD with endophenotype potential. However, the literature on specific impairments in emotion processing cognitive strategies (directive/cortical/higher versus intuitive/limbic/lower) in euthymic adult BD patients and healthy first-degree relatives/high-risk (HR) subjects in comparison with healthy controls (HCs) is sparse. Methods: We examined facial emotion recognition deficits (FERD) in BD (N = 30), HR (N = 21), and HC (N = 30) matched for age (years), years of education, and sex using computer-administered face emotions–Matching And Labeling Task (eMALT). Results: The three groups were significantly different based on labeling accuracy scores for fear and anger (FA) (P \u3c 0.001) and sad and disgust (SD) (P \u3c 0.001). On post-hoc analysis, HR subjects exhibited a significant deficit in the labeling accuracy of FA facial emotions (P \u3c 0.001) compared to HC. The BD group was found to have significant differences in all FA (P = 0.004) and SD (P = 0.003) emotion matching as well as FA (P = 0.001) and SD (P \u3c 0.001) emotion labeling accuracy scores. Conclusions: BD in remission exhibits FERD in general, whereas specific labeling deficits of fear and anger emotions, indicating impaired directive higher order aspect of emotion processing, were demonstrated in HR subjects. This appears to be a potential endophenotype. These deficits could underlie the pathogenesis in BD, with possible frontolimbic circuitry impairment. They may have potential implications in functional recovery and prognosis of BD