52 research outputs found
Biomarkers of response to immune checkpoint therapy
No full textImmune checkpoint therapy leads to durable objective response in a subset of patients with metastatic cancer in many different cancer types, but the mechanisms and biomarkers of response to immune checkpoint therapy is not fully understood. Through pan-cancer analysis of the Cancer Genome Atlas, I have so far identified 2 types of predictors of immune activation and checkpoint pathway upregulation in a total of 10 solid cancer types (skin melanoma, lung adenocarcinoma, colon, endometrial, gastric, cervical, ER+ HER2− breast, bladder, clear-cell kidney, and head-neck squamous-cell cancer): (1) hyper-mutation in tumor due to DNA proofreading defect (Chapter 2) or some other etiologies (Chapter 3), and (2) expression of exogenous (Chapter 4) or endogenous (Chapter 5) viral RNA in tumor. I also validated these predictors as biomarkers of response to immune checkpoint therapy in some of the above 10 cancer types where I had access to good quality data, using published datasets of patients treated with immune checkpoint therapy for retrospective validation, and de-identified data of patients treated with immune checkpoint therapy at the Rutgers Cancer Institute of New Jersey and the Vanderbilt Ingram Cancer Center for prospective validation.Ph.D.Includes bibliographical referencesby Anshuman Pand
Auto-Scaling Techniques for Clouds Processing Requests with Service Level Agreements
No full textAuto-scaling mechanisms allow applications running on Cloud environments to maintain a guaranteed Quality of Service while efficiently utilizing resources and keeping operational costs low for the service providers. However, creating such an auto-scaling framework may be challenging due to the need to precisely estimate resource usage while the workload patterns vary significantly.The research presented in this thesis focuses on automatic provisioning of compute resources in the Cloud performed by an intermediary enterprise for a single client enterprise. The enterprise hosting a broker uses techniques for dynamically controlling the number of resources used by the client enterprise. The research introduces three auto-scaling techniques: a reactive, a proactive and a hybrid technique. These techniques allow resources to be scaled based on user demand.The primary goal of these auto-scaling techniques is to achieve a profit for the intermediary enterprise while maintaining the desired grade of service for the client enterprise. A secondary goal is to generate a lower cost for the client enterprise in comparison to the situation in which the client acquires resources directly from the cloud provider. The techniques support both on-demand requests as well as requests with service level agreements (SLAs). The effectiveness of the proposed auto-scaling techniques is demonstrated through experiments performed on proof of concept prototypes and simulations. The experimental results show that for a number of different combinations of system and workload parameters experimented with, the proposed algorithms lead to a significant broker profit and a lower user cost in comparison to a conventional non-auto-scaling system
A note on the magnitude of the flux superpotential
No full textThe magnitude of the flux superpotential W flux plays a crucial role in determining the scales of IIB string compactifications after moduli stabilisation. It has been argued that values of W flux ≠1 are preferred, and even required for physical and consistency reasons. This note revisits these arguments. We establish that the couplings of heavy Kaluza-Klein modes to light states scale with the internal volume as g ∼ M KK /M P ∼ -2/3 ≠1 and argue that consistency of the superspace derivative expansion requires gF/M 2 ∼ m 3/2 /M KK ≠1, where F is the auxiliary field of the light fields and M the ultraviolet cutoff. This gives only a mild constraint on the flux superpotential, W flux ≠1/3, which can be easily satisfied for (1) values of W flux. This regime is also statistically favoured and makes the Bousso-Polchinski mechanism for the vacuum energy hierarchically more efficient. © 2014 The Author(s)
Fault Classification for DG integrated Hybrid Power System using Wavelet Neural Network Approach
No full textEngineering Models for Shear Crack Width and Shear Deflection in Slender Reinforced Concrete Beams
No full textShear cracking in slender reinforced concrete beams with thin webs can result in significant shear crack width and deflection which is usually ignored in practice due to lack of availability of the engineering models in design codes. This can lead to unconservative predictions of the crack width and total deflection in the SLS (Serviceability Limit State). The large crack widths can cause problems related to durability, aesthetic appeal, maintainability and fluid tightness of the structure. An inspection in 2001 reveals extensive shear cracks in Grondal and Alvik bridges in Sweden. The problem is so severe that the bridges are temporarily closed. Later, the investigations reveal that although the bridges are designed according to Swedish codes, the provided shear reinforcement is insufficient for crack width control under service loads on the bridge. Therefore, it becomes imperative to evaluate the available crack width models and develop robust models for shear crack width prediction. A literature review of the available models for shear crack width is performed to identify the crucial parameters influencing shear crack width. Shear crack width is influenced by several parameters, but the most critical parameters are shear crack spacing, shear stirrup strain, principle strain in the cracked concrete and diagonal compression strut angle. Thereafter, various models available to evaluate these parameters are reviewed to understand their applicability and limitations.This is followed by a study for the analysis of performance of the models with respect to the experimental observations. Based on the limited experimental dataset, it is found that the Zakaria et al. (2011) shear crack spacing model, and the fib MC 2010 (Model Code 2010) crack spacing model (for members with orthogonal reinforcement) provide a conservative estimate for the shear crack spacing in RC (reinforced concrete) beams. The predictions from the current EC2 crack spacing model are slightly unconservative. All the three crack spacing models take into account the influence of bond transfer length on the stress distribution in concrete and reinforcement. It is also found that the SMCFT (Simplified Modified Compression Field Theory), CFT (Compression Field Theory) and CCC (Compression Chord Capacity) model provide estimates for the shear crack angle with small deviations from the experimentally observed values. However, all these three models predict flatter (smaller) mean shear crack angles as compared to the experimentally observed values. The SMCFT and CFT determine the diagonal compression strut angle with a consideration of deformations of reinforcement (transverse and longitudinal) and diagonally cracked concrete. On the other hand, the CCC model predicts the diagonal shear crack angle based on the assumption that the horizontal projection of the first branch of flexural-shear crack is equal to 0.85d where d is the effective depth to the longitudinal tensile reinforcement. According to comparison with the experimental observations referred in this study, the CCC model provides a conservative estimate for the concrete contribution to shear resistance which is required to evaluate the shear stirrup strains. Using concrete contribution to shear resistance from this model, an engineering strategy to estimate the concrete contribution to shear resistance at service loads is proposed. Thereafter, five different models for mean shear crack width (the first three models with two variants each) and four different models for shear deflection are proposed. The comparison of the predictions from the mean shear crack width models with the experimental data reveals that a conservative estimate for the shear crack width can be made by equating shear crack width as the product of mean principle tensile strain in the cracked concrete and the shear crack spacing (ModelIIIB, Model-IV and Model-V). It is observed that the assumption of zero concrete contribution to shear resistance (shear-force transfer) at service loads (in B variants of Models-I, II and III) result in relatively higher predicted mean shear crack widths (as compared to the corresponding A variants) and therefore, more conservative estimates. Moreover, the assumption of mean shear crack angle equal to 45 degrees also leads to relatively more conservative estimates of mean shear crack width. Model-IV and Model-V seem to outperform other mean shear crack width models considering mean and consistency of the models together as a metric. The mean and SD of the predictions from Model-IV are 0.85 and 0.30 for the original formulation of the model. However, with the assumption of mean shear crack angle equal to 45 degrees, the mean and SD values are observed to be 0.37 and 0.13 respectively. It is found that a conservative estimate for shear deflection can be obtained by assuming a linear shear force versus deflection response for a slender reinforced concrete beam (Model-I). The ratio of the experimentally observed to predict shear deflection for Model-I is 0.85 with a SD (Standard Deviation) of 0.31. The proposed Models-IIIB, IV and V (in their original formulation) and Models- IB, IIA, IIB, IIIA, IIIB and IV (with an assumption of mean shear crack angle equal to 45 degrees) for the shear crack width and Model-I for shear deflection provide a conservative estimate for the range of experimental beam specimen data covered in this MSc thesis. These models (especially Model-IV for mean shear crack width and Model-I for shear deflection) seem to be potentially useful engineering models for use in engineering practice to evaluate mean shear crack width and shear deflection for slender beams with thin webs (for example slender webs of bridge girders). However, the models require further validation with an experimental study to assess and establish suitability for wider application in design practice
Optimal Container Design Using Mathematical Models and Program PACKIT
No full textThis Dissertation / Report is the outcome of investigation carried out by the creator(s) / author(s) at the department/division of Central Food Technological Research Institute (CFTRI), Mysore mentioned below in this page
Title: Towards an Encoding for Coptic Numbers in the UCS Source: Script Encoding Initiative (SEI)
No full textA set of characters used for representing numbers in Coptic was described by the present author in L2/09-163R (“Proposal to Encode Coptic Numerals in ISO/IEC 10646”). Several changes to the original document have beenmade, including change of name of the script block from “Coptic Numerals ” to “Coptic Numbers”; development of a draft font; addition of a code chart and names list; and allocation of the block in th
Preliminary Proposal to Encode Dhives Akuru in ISO/IEC 10646
No full textThis is a preliminary proposal to encode the Dhives Akuru script in the Universal Character Set (ISO/IEC 10646). The intent is to bring the script to the attention of the Unicode Technical Committee, to seek advice regarding the encoding of the script in the UCS, and to allocate it in the Unicode Roadmap. Research on Dhives Akuru is ongoing and the present author will provide additional information as it is discovered
Load frequency control in renewable based micro grid with Deep Neural Network based controller
No full textMicrogrids (MGs) offer numerous technical, economic, and environmental benefits, yet they face challenges due to high-frequency deviations caused by the unpredictable nature of the renewable energy source, and variable loads with the integration of Electric Vehicles (EVs). Numerous methods, algorithms, and controllers have been created to address these issues and preserve system stability and efficient load frequency control (LFC). This paper introduces a novel control strategy to optimise the load frequency model in a microgrid (MG) with vehicle-to-grid interactions using Particle Swarm Optimisation - deep Artificial Neural Network (PSO-DNN). The performance of the suggested controller is evaluated against traditional techniques, including dynamic EV charging and discharging, renewable energy integration, and fluctuating generation, using the proportional integral derivative (PID) controller and the PSO-PID controller. The PSO-DNN controller achieves 99.308 % efficiency, with a minimal mean squared error and an integrated time absolute error reduced to. It achieves a transient time of 18.5626 s, demonstrating quick response, accurate control, and quick peak output capabilities with little undershoot and overshoot. This analysis for stability confirms that the PSO-DNN controller effectively ensures stability in the microgrid's LFC system amidst uncertainties and disturbances, as compared to PID and fuzzy controllers. This approach enhances resilience, reduces settling time, and ensures reliable frequency control, validating its efficacy in maintaining stable and efficient microgrid operations
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