π−N\pi-N Drell-Yan process in TMD factorization

This article presents the review of the current understanding on the pion-nucleon Drell-Yan process from the point of view of the TMD factorization. Using the evolution formalism for the unpolarized and polarized TMD distributions developed recently, we provide the theoretical expression of the relevant physical observables, namely, the unpolarized cross section, the Sivers asymmetry, and the $\cos2\phi$ asymmetry contributed by the double Boer-Mulders effects. The corresponding phenomenology, particularly at the kinematical configuration of the COMPASS $\pi N$ Drell-Yan facility, is displayed numerically.Comment: Version published in Advances in High Energy Physic

Transverse momentum spectrum of dilepton pair in the unpolarized π−N\pi^-N Drell-Yan process within TMD factorization

We study the transverse momentum spectrum of dilepton produced in the unpolarized $\pi^- N$ Drell-Yan process, using transverse momentum dependent factorization up to next-to-logarithmic order of QCD. We extract the nonperturbative Sudakov form factor for the pion in the evolution formalism of the unpolarized TMD distribution function, by fitting the experimental data collected by the E615 Collaboration at Fermilab. With the extracted Sudakov factor, we calculate the normalized differential cross section with respect to transverse momentum of the dimuon and compare it with the recent measurement by the COMPASS Collaboration.Comment: 17 pages, 3 figure

The application of Bayesian adaptive design and Markov model in clinical trials

In this research, two new designs in clinical trials are proposed. The first problem is a new Bayesian adaptive dose-finding design and its application in an oncology clinical trial. This design is used for phase IB studies with the biomarker as the endpoint and with the fewer patients. The second problem is another new Bayesian adaptive dose-finding design with longitudinal analysis and its application in phase II depression clinical trial. This design is best fit for phase II dosing-finding clinical trials with clinical endpoints. MTD information has been obtained before the trials. In adaptive dose-finding clinical trials, the strategy is to reduce the allocation of patients to non-informative doses and also save the trial cost. Bayesian adaptive dose finding design has the ability to utilize accumulating data obtained in real time to alter the course of the trial, thereby enabling dynamic allocation to different dosing groups and dropping of ineffective dosing group earlier. In this research, Bayesian adaptive method is used as a new and useful approach that applies to phase IB and phase II dose-finding clinical trials to evaluate safety and efficacy of the study treatment. Response model and Normal Dynamic Linear Models (NDLMs) are applied in stages 1-4. Conditional probability for each parameter in the model is derived using appropriate prior distributions. Markov Chain Monte Carlo (MCMC) method is used to do the simulation. Model parameters with meaningful prior distributions and the posterior quantities are obtained to evaluate the trial results and they help to determine the optimal dose level which can be used in later studies. Simulations are done for different scenarios in the two designs and used to validate the model. Five-thousand simulation trials are conducted to verify the repeatability of the results. The posterior probability of success for the trial is greater than 90% based on the simulation results. The results give clearer idea if one needs to go further to test new dose levels based on the thorough evaluation of the existing partial data. Compared with the other adaptive dose finding strategy, the proposed Bayesian adaptive designs are sensitive and robust to help the investigators draw conclusion as early as possible. The designs can also reduce sample size substantially which in turn leads to savings in cost and time. Continuous-time Markov model has the advantage over the traditional survival model and can be used to describe disease as a series of probable transitions between health states. This is an attractive feature since it provides the ability to describe the course of disease over time. It can also describe and estimate expected survival in clinical cohort. In this research, continuous-time Markov model is used in the time-to-event analysis in a phase II oncology trial. Six states are defined in the Markov chain which is used in time to progression analysis for 36 patients with neuroendocrine carcinoma. The transition probability matrix P is defined and used to iterate future transition and survival probabilities. The estimate from matrix analysis shows that the results are reliable and comparable with the Kaplan-Meier results

Analyzing evolution of rare events through social media data

Recently, some researchers have attempted to find a relationship between the evolution of rare events and temporal-spatial patterns of social media activities. Their studies verify that the relationship exists in both time and spatial domains. However, few of those studies can accurately deduce a time point when social media activities are most highly affected by a rare event because producing an accurate temporal pattern of social media during the evolution of a rare event is very difficult. This work expands the current studies along three directions. Firstly, we focus on the intensity of information volume and propose an innovative clustering algorithm-based data processing method to characterize the evolution of a rare event by analyzing social media data. Secondly, novel feature extraction and fuzzy logic-based classification methods are proposed to distinguish and classify event-related and unrelated messages. Lastly, since many messages do not have ground truth, we execute four existing ground-truth inference algorithms to deduce the ground truth and compare their performances. Then, an Adaptive Majority Voting (Adaptive MV) method is proposed and compared with two of the existing algorithms based on a set containing manually-labeled social media data. Our case studies focus on Hurricane Sandy in 2012 and Hurricane Maria in 2017. Twitter data collected around them are used to verify the effectiveness of the proposed methods. Firstly, the results of the proposed data processing method not only verify that a rare event and social media activities have strong correlations, but also reveal that they have some time difference. Thus, it is conducive to investigate the temporal pattern of social media activities. Secondly, fuzzy logic-based feature extraction and classification methods are effective in identifying event-related and unrelated messages. Lastly, the Adaptive MV method deduces the ground truth well and performs better on datasets with noisy labels than other two methods, Positive Label Frequency Threshold and Majority Voting

Sediment Dynamics and Channel Connectivity on Hillslopes

The pattern, magnitude, and frequency of hillslope erosion and deposition are spatially varied under the influence of micro-topography and channel geometry. This research investigates the interrelationships between erosion/deposition, micro-topography, and channel connectivity on a hillslope in Loudon, Tennessee using the centimeter (cm) level temporal Digital Elevation Models collected using laser scanning. This research addressed (1) the effect of spatial resolution on the erosion/deposition quantification, and rill delineation; (2) the influences of micro-topographic factors (e.g. slope, roughness, aspect) on erosion and deposition; (3) the relationship between the structural connectivity -- depressions and confluence of rills -- and the sedimentological connectivity. I conducted (1) visual and quantitative assessments for the erosion and deposition, and the revised automated proximity and conformity analysis for the rill network; (2) quantile regression for micro-topographic factors using segmented rill basins; and (3) cross-correlation analysis using erosion and deposition series along the channels.Overall, rills are sedimentologically more dynamic than the interrill areas. A larger grid size reduces the detectable changes in both areal and volumetric quantities, and also decreases the total length and number of rills. The offset between delineated rills and the reference increases with larger grid sizes. A larger rill basin has higher erosion and deposition with the magnitude of erosion greater than deposition. The slope has a positive influence on erosion and a negative one on deposition; roughness has a positive influence on deposition and a negative one on erosion. Areas that are more north-facing experience higher erosion and lower deposition. Rill length explains 46% of the variability for erosion and 24% for deposition. The depressions are associated with higher erosion in the downslope direction. The correlations between the erosion and the confluence are positive; the correlation between the deposition and the sink is positive. Overall, the influence of structural connectivity on the sedimentological connectivity is within 25 cm in both upstream and downstream directions. This research contributes to the understanding in how the sediment movement on hillslopes is governed by topographic variations and channel connectivity, and future work may explore hillslope channels at broader geographical and temporal scales

Petri net models of microgrids with distributed generators

This thesis introduces some basic concepts and control methods about a microgrid. Then, two hot issues are investigated. One is how to control multiple distributed generators; and another is how to model both discrete event and continuous behaviors of a microgrid. To address these two issues, this thesis work applies Petri nets to both modeling and control of a microgrid. Ordinary Petri nets, hybrid Petri nets, and finite capacity Petri nets, are introduced with their examples targeted at modeling the behavior of a microgrid. Coordination control of multiple distributed generators based on a Petri net model is proposed. Compared with multi-V/f control, the Petri net based control enables the system to operate with a longer stable time interval. Finally, a hybrid Petri net model is constructed to model both discrete event and continuous behaviors of an on-load tap changing transformer system. Compared with an algebraic method, the hybrid Petri net offers a clear and easy-to-understand method to describe such a system

An Engineering Analysis Method for Deep Geothermal Energy

At present there are already many deep geothermal projects allowing us to have a better understanding of deep geothermal energy. However, there are still many issues to be solved for more reliable use of deep geothermal energy. This thesis proposes an engineering analysis method to assess the performance of a typical deep geothermal system, which is a doublet system with one injection well and one extraction well. A convective heat transfer boundary between the aquifer and overburden layers is applied for the axisymmetric problem based on the Lauwerier model for the first time. A new analytical solution is deduced using a series of Laplace transforms. The interaction between the injection well and extraction well is first neglected. Compared with other relevant analytical solutions, this new analytical solution comprehensively includes both heat conduction and heat advection in the aquifer and the heat flux between the aquifer and overburden layer. As long as the relevant parameters are obtained, the new analytical solution can intuitively illustrate the temporal and spatial temperature distribution within the aquifer. It can be used to determine the location of the extraction well and to evaluate the extracted geothermal power of the hot water aquifer. The convective heat transfer boundary at the interface does not only reflect the actual heat transfer process at the interface, but also models the heat transfer process in the overburden layer. It is shown that the dimensionless equivalent heat transfer coefficient is expressed as a function of the dimensionless injection rate and the dimensionless thermal conductivity of the overburden layer so the new analytical solution effectively incorporates the properties of the overburden layer. A series of FE simulations are conducted, and the analytical model is curve fitted to the FE results to evaluate the values of the dimensionless equivalent heat transfer coefficient. Based on the results of the curve fitting exercise, two empirical equations are proposed for typical cases. Applying the analytical solution coupled with these empirical equations and along with proper error estimates, it is possible to conduct a simple and rapid evaluation of the geothermal potential of a particular site. The revised analytical solution in this thesis is novel as there is no other analytical or semi analytical solution for the doublet system considering the heat conduction and heat advection in the aquifer and the heat flux between the aquifer and overburden layer. The revised analytical solution extended the analytical solution for a single injection well to a doublet scheme by considering the interaction effect between the injection well and the extraction well. The expression of the critical distance between two wells is obtained so that the best location of the extraction well in a doublet system can be determined. The spatial and temporal temperature distribution in the aquifer for a doublet scheme can be given by the revised analytical solution when the well distance is greater than the critical distance. It is found that it is valid to use a single well model to simplify a doublet scheme when the extraction well is far away from the injection well. The temperature of the extracted water against different time, injection rates and well distances can be obtained via the revised analytical solution. The revised analytical solution is compared with the experimental data and the numerical solutions and it is found that they match with each other well. The effect of a natural fault/fracture that exists in the aquifer on the performance of a doublet system, namely the temperature distribution and extracted temperature, is evaluated. By comparing the line model with the domain model, it is found that the line model is valid and computationally efficient. It is found that the acceleration effect of the fracture on thermal movement is the greatest when the fracture is located at the midpoint of the two wells. When the fracture is shifted towards the injection (extraction) well, the acceleration effect decreases and then becomes the deceleration effect. The deceleration effect of the fracture is the greatest when the fracture is located at the injection (extraction) well. The expressions of the critical angle for any position of the fracture in the doublet system are obtained. Equipped with these expressions, it is possible to decide whether the doublet system is still efficient during its life span once the cold water injection rate and the geometry and properties of the fracture are given.B