Aerothermal modeling program. Phase 2, element B: Flow interaction experiment

NASA has instituted an extensive effort to improve the design process and data base for the hot section components of gas turbine engines. The purpose of element B is to establish a benchmark quality data set that consists of measurements of the interaction of circular jets with swirling flow. Such flows are typical of those that occur in the primary zone of modern annular combustion liners. Extensive computations of the swirling flows are to be compared with the measurements for the purpose of assessing the accuracy of current physical models used to predict such flows

Parental rearing style as a predictor of attachment and psychosocial adjustment during young adulthood

Parental rearing-styles are crucial for psychosocial adjustment both during childhood and adulthood. The current study examined whether: (a) parental rearing-styles predicted psychosocial adjustment in young-adulthood, (b) this relationship was mediated by attachment styles , and ( c ) gender differences occur in these relationships. Two hundred and forty (103 male and 132 female) university students completed measures assessing parental rearing-style , current attachment style, romantic relationship satisfaction, friendship quality, self-esteem, and social competence. Multigroup structural equation modelling, conducted separately by gender, revealed that parental rearing-style predicted psychosocial adjustment during young-adulthood. Further, there was also evidence of gender differences and that self-models and other-models of attachment mediated this relationship. Together, these findings reinforce the importance of perceived parental rearing-style for subsequent psychosocial adjustment

Master of Science

thesisThe purpose of this study was to examine the associations of a child's early relationship with his or her primary caregiver, his or her representation of that relationship, and his or her status within a peer group or, more specifically, between the quality of a preschooler's internal representations of attachment and the peer status he or she achieves in the context; of the classroom. This study was conducted over an 8-month period and involved two interviews: (a) one assessing representational models and (b) one assessing peer status. Results showed that (a) there is a difference in the quality of the representational model and (b) the model does have an impact on later behavior (as measured through peer status). Research results are discussed, and implications are presented

Diffusion Imaging in the Rat Cervical Spinal Cord

Magnetic resonance imaging (MRI) is the state of the art approach for assessing the status of the spinal cord noninvasively, and can be used as a diagnostic and prognostic tool in cases of disease or injury. Diffusion weighted imaging (DWI), is sensitive to the thermal motion of water molecules and allows for inferences of tissue microstructure. This report describes a protocol to acquire and analyze DWI of the rat cervical spinal cord on a small-bore animal system. It demonstrates an imaging setup for the live anesthetized animal and recommends a DWI acquisition protocol for high-quality imaging, which includes stabilization of the cord and control of respiratory motion. Measurements with diffusion weighting along different directions and magnitudes (b-values) are used. Finally, several mathematical models of the resulting signal are used to derive maps of the diffusion processes within the spinal cord tissue that provide insight into the normal cord and can be used to monitor injury or disease processes noninvasively. The video component of this article can be found at http://www.jove.com/video/52390/ Introduction Magneti

The need for a process mining evaluation framework in research and practice

Although there has been much progress in developing process mining algorithms in recent years, no effort has been put in developing a common means of assessing the quality of the models discovered by these algorithms. In this paper, we motivate the need for such an evaluation mechanism, and outline elements of an evaluation framework that is intended to enable (a) process mining researchers to compare the performance of their algorithms, and (b) end users to evaluate the validity of their process mining results

Analytical Formulas for Risk Assessment for a Class of Problems where Risk Depends on Three Interrelated Variables

We derive general analytical formulas for assessing risks in a problem domain where the risk depends on three interrelated variables. More specifically, we derive general analytical formulas for propagating beliefs in a network where three binary variables, A, B and C, are related to a fourth binary variable Z through an ‘AND’ relationship. In addition, we assume that variables A, B and C are interrelated in that a change in one variable may affect the value of each of the other two. The analytical formulas derived in this article determine the overall belief and plausibility that Z is true or not true, given that we have beliefs on variables A, B and/or C. To demonstrate the importance of the general results, we use the results to develop models applicable to three real-world situations. The first model can aid external auditors in assessing the quality of an audit client’s internal audit function to determine the extent to which the internal auditor’s work can be relied on in the conduct of a financial audit while the second can aid in assessing the risk of impaired auditor independence when conducting a financial statement audit. The third model can be used to assess the risk of management fraud in financial reporting. Assessment of such risks is of critical importance to external auditors, regulators, and the investing public. Analytical formulas to help address these types of important business and economic problems have not been available prior to these derivations

Instrumental variable methods to assess quality of care the marginal effects of process-of-care on blood pressure change and treatment costs

Background: Hypertension is poorly controlled. Team-based care and changes in the process of care have been proposed to address these quality problems. However, assessing care processes is difficult because they are often confounded even in randomized behavioral studies by unmeasured confounders based on discretion of health care providers. Objective: To evaluate the effects of process measures including number of counseling sessions about lifestyle modification and number of antihypertensive medications on blood pressure change and payer-perspective treatment costs. Methods: Data were obtained from two prospective, cluster randomized controlled clinical trials (Trial A and B) implementing physician-pharmacist collaborative interventions compared with usual care over six months in community-based medical offices in the Midwest. Multivariate linear regression models with both instrumental variable methods and as-treated methods were utilized. Instruments were indicators for trial and study arms. Models of blood pressure change and costs included both process measures, demographic variables, and clinical variables. Results: The analysis included 496 subjects. As-treated methods showed no significant associations between process and outcomes. The instruments used in the study were insufficient to simultaneously identify distinct process effects. However, the post-hoc instrumental variable models including one process measure at a time while controlling for the other process demonstrated significant associations between the processes and outcomes with estimates considerably larger than as-treated estimates. Conclusions: Instrumental variable methods with combined randomized behavioral studies may be useful to evaluate the effects of different care processes. However, substantial distinct process variation across studies is needed to fully capitalize on this approach. Instrumental variable methods focusing on individual processes provided larger and stronger outcome relationships than those found using as-treated methods which are subject to confounding

Towards an evaluation framework for process mining algorithms

Although there has been a lot of progress in developing process mining algorithms in recent years, no effort has been put in developing a common means of assessing the quality of the models discovered by these algorithms. In this paper, we outline elements of an evaluation framework that is intended to enable (a) process mining researchers to compare the performance of their algorithms, and (b) end users to evaluate the validity of their process mining results. Furthermore, we describe two possible approaches to evaluate a discovered model (i) using existing comparison metrics that have been developed by the process mining research community, and (ii) based on the so-called k-fold-cross validation known from the machine learning community. To illustrate the application of these two approaches, we compared a set of models discovered by different algorithms based on a simple example log

Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Vision

The rapid evolution of Multi-modality Large Language Models (MLLMs) has catalyzed a shift in computer vision from specialized models to general-purpose foundation models. Nevertheless, there is still an inadequacy in assessing the abilities of MLLMs on low-level visual perception and understanding. To address this gap, we present Q-Bench, a holistic benchmark crafted to systematically evaluate potential abilities of MLLMs on three realms: low-level visual perception, low-level visual description, and overall visual quality assessment. a) To evaluate the low-level perception ability, we construct the LLVisionQA dataset, consisting of 2,990 diverse-sourced images, each equipped with a human-asked question focusing on its low-level attributes. We then measure the correctness of MLLMs on answering these questions. b) To examine the description ability of MLLMs on low-level information, we propose the LLDescribe dataset consisting of long expert-labelled golden low-level text descriptions on 499 images, and a GPT-involved comparison pipeline between outputs of MLLMs and the golden descriptions. c) Besides these two tasks, we further measure their visual quality assessment ability to align with human opinion scores. Specifically, we design a softmax-based strategy that enables MLLMs to predict quantifiable quality scores, and evaluate them on various existing image quality assessment (IQA) datasets. Our evaluation across the three abilities confirms that MLLMs possess preliminary low-level visual skills. However, these skills are still unstable and relatively imprecise, indicating the need for specific enhancements on MLLMs towards these abilities. We hope that our benchmark can encourage the research community to delve deeper to discover and enhance these untapped potentials of MLLMs. Project Page: https://vqassessment.github.io/Q-Bench.Comment: 25 pages, 14 figures, 9 tables, preprint versio

Increasing the Availability of Skilled Birth Attendance in Rural India

Key considerations in the availability of skilled birth attendance will be a critical component in national efforts towards ensuring universal health coverage in India. This paper aims to examine opportunities for strengthening skilled birth attendance at the primary level by (a) exploring relevant models of rural primary and community-level skilled attendance, both India and internationally, that have achieved positive health outcomes; (b) assessing the current skilled birth attendance coverage in India and means to achieving greater coverage of skilled attendance and enhanced linkages in the continuum of care; and (c) recommending opportunities and required investment for scaling-up skilled attendance within NRHM. Our primary research highlights immediate requirements for more targeted systems strengthening, particularly for sub-centres that can provide intranatal care, and for PHCs depending on their delivery caseload and accessibility to other referral facilities. This requires significantly more strategic planning at the district level, and creating or reinforcing full-time support structures that can focus on quality assurance of care, including training and skills development, facility quality management, and linkages between care provider