Investigation of sensitivity of surface deformation to subsurface properties and reservoir operations

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 60).An experimental study is performed to understand the sensitivity of ground deformation to subsurface properties and operations of oil and gas fields. Ground deformation, or more severely subsidence, may pose concerns for human settlements situated above the reservoir. This Masters thesis will study a realistic sample problem on its surface deformation sensitivity, in hopes of providing a sound basis for future characterization of subsurface properties and the forecast of surface deformation due to oil and gas production. Iteratively coupled simulations are performed to test how sensitive the surface deformation is to changing subsurface parameters. To test the validity of such coupled simulator, comparison of the displacement results with those of another commercially available software is also carried out. Results show that the change of surface displacement particularly in the vertical direction tends to be within the range of detection of satellites, of which data will serve as the input of future inversions with the Ensemble Kalman Filter (EnKF).by Pui-Wa Li.S.M

Neumann (water level gradient) boundaries in TELEMAC 2D and their application to wave-current interaction

Water Qualit

Poststroke depression and risk of stroke recurrence and mortality:protocol of a meta-analysis and systematic review

Introduction A number of observational studies have indicated that poststroke depression could increase the risk of stroke outcomes. There is a meta-analysis indicating that poststroke depression is a risk factor of all-cause mortality. This paper reports the protocol for a systematic review and meta-analysis to clarify the associations of poststroke depression with stroke recurrence and mortality in order to determine whether poststroke depression is a predictor of stroke outcomes according to data extracted from relevant observational studies.Methods and analysis MEDLINE, Web of Science databases, EMBASE, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews will be used to conduct the search. Published studies written in English will be included. The risk of bias for the studies included in the systematic review or meta-analysis will be assessed by the Newcastle–Ottawa Quality Assessment Scale. HRs for stroke recurrence and mortality with 95% CIs will be included as primary outcomes. Subgroup analyses and meta-regression will be performed.Ethics and dissemination Ethics approval will not be needed because the data used in this systematic review will be extracted from published studies. The results of the systematic review focusing on whether depression after stroke is a predictor for stroke recurrence and mortality will be disseminated by publication in a peer-reviewed journal.PROSPERO registration number CRD42018107944

MoodScope: Building a Mood Sensor from Smartphone Usage Patterns

MoodScope is a first-of-its-kind smartphone software system that learns the mood of its user based on how the smartphone is used. While commonly available sensors on smartphones measure physical properties, MoodScope is a sensor that measures an important mental state of the user and brings mood as an important context into context-aware computing. We design MoodScope using a formative study with 32 participants and collect mood journals and usage data from them over two months. Through the study, we find that by analyzing communication history and application usage patterns, we can statistically infer a user’s daily mood average with 93% accuracy after a two-month training period. To a lesser extent, we can also estimate Sudden Mood Change events with reasonable accuracy (74%). Motivated by these results, we build a service, MoodScope, which analyzes usage history to act as a sensor of the user’s mood. We provide a MoodScope API for developers to use our system to create mood-enabled applications and create and deploy sample applications

The critical success factors of customer relationship management (CRM) technological initiatives

Customers are any organizations' best assets. As an increasing number of organizations realize the importance of becoming more customer-centric in today's competitive economy, they are also discovering that they must deliver knowledge about their customers, products, and services internally (i.e across multiple organizational functions) and externally (i.e at all customer touch points). Therefore, enterprise executives are interested in knowing the Critical Success Factors that will drive their Customer Relationship Management (CRM) technological initiatives. CRM technological initiatives help foster a customer-centric business strategy, the diffusion of knowledge, a unified face to all customers, and a holistic view of customers. There is no empirical research, to our knowledge, that delves into an understanding of the Critical Success Factors behind CRM technological initiatives. Nor has it been demonstrated that different profiles of Critical Success Factors exist for specific CRM technological initiatives such as Customer Support and Service (CSS), Sales Force Automation (SFA), and Enterprise Marketing Automation (EMA). This thesis compiles the Critical Success Factors of CRM technological initiatives using empirical data from 101 organizations across Canada. The Partial Least Squares (PLS) Structural Equation Modeling method was used to analyze the collected data. A comparison between 57 adopters of CRM technology and 44 non-adopters of CRM technology indicates that the levels of strategic perceived benefits, top management support, and knowledge management capabilities differ between these two independent groups. The core finding of this study reveals that technological readiness, alone, does not lead to successful CRM technological initiatives. Possessing knowledge management capabilities emerges as the most significant critical success factor of CRM technological initiatives and is strongly related to technological readiness. Top management support is significant for all CRM technological initiatives with the exception of the SFA CRM Infrastructure

Development of Novel Therapeutics Targeting the Blood–Brain Barrier: From Barrier to Carrier

The blood–brain barrier (BBB) is a highly specialized neurovascular unit, initially described as an intact barrier to prevent toxins, pathogens, and potentially harmful substances from entering the brain. An intact BBB is also critical for the maintenance of normal neuronal function. In cerebral vascular diseases and neurological disorders, the BBB can be disrupted, contributing to disease progression. While restoration of BBB integrity serves as a robust biomarker of better clinical outcomes, the restrictive nature of the intact BBB presents a major hurdle for delivery of therapeutics into the brain. Recent studies show that the BBB is actively engaged in crosstalk between neuronal and the circulatory systems, which defines another important role of the BBB: as an interfacing conduit that mediates communication between two sides of the BBB. This role has been subject to extensive investigation for brain-targeted drug delivery and shows promising results. The dual roles of the BBB make it a unique target for drug development. Here, recent developments and novel strategies to target the BBB for therapeutic purposes are reviewed, from both barrier and carrier perspectives

Reliable Eigenspectra for New Generation Surveys

We present a novel technique to overcome the limitations of the applicability of Principal Component Analysis to typical real-life data sets, especially astronomical spectra. Our new approach addresses the issues of outliers, missing information, large number of dimensions and the vast amount of data by combining elements of robust statistics and recursive algorithms that provide improved eigensystem estimates step-by-step. We develop a generic mechanism for deriving reliable eigenspectra without manual data censoring, while utilising all the information contained in the observations. We demonstrate the power of the methodology on the attractive collection of the VIMOS VLT Deep Survey spectra that manifest most of the challenges today, and highlight the improvements over previous workarounds, as well as the scalability of our approach to collections with sizes of the Sloan Digital Sky Survey and beyond.Comment: 7 pages, 3 figures, accepted to MNRA