Time-invariant Discord: High Temperature Limit and Initial Environmental Correlations

We present a thorough investigation of the phenomena of frozen and time-invariant quantum discord for two-qubit systems independently interacting with local reservoirs. Our work takes into account several significant effects present in decoherence models, which have not been yet explored in the context of time-invariant quantum discord, but which in fact must be typically considered in almost all realistic models. Firstly, we study the combined influence of dephasing, dissipation and heating reservoirs at finite temperature. Contrarily to previous claims in the literature, we show the existence of time-invariant discord at high temperature limit in the weak coupling regime, and also examine the effect of thermal photons on the dynamical behaviour of frozen discord. Secondly, we explore the consequences of having initial correlations between the dephasing reservoirs. We demonstrate in detail how the time-invariant discord is modified depending on the relevant system parameters such as the strength of the initial amount of entanglement between the reservoirs.Comment: 10 pages, 7 figure

Some reflections on the building and calibration of useful network models

Over the past 10 years or so in the UK much effort has gone into the construction of computerised network models of water supply and distribution networks. At best such models offer an approximation of reality, their performance in simulation being constrained, in many cases, by the uncertainties present in the data upon which they were compiled. Most notable are the problems of demand specification, including leakage evaluation. In the UK this exercise is compounded by the unmetered nature of most domestic consumption. Reconciliation of the output of this process is invariably and inextricably linked to such matters as flow-meter accuracy, network and district metered area (DMA) connectivity, and monitored pressure regime, as well as precision in property allocation and quality of billing records. For large networks the task of the modeller is most arduous since the exercise of pipe calibration, leading to production of the 'verified' model, is itself highly dependent upon the distribution of flows generated in the network. The paper elaborates on these problems and introduces outlines for systematic treatments of the data reconciliation processes, with the aim of producing usable models which 'best' represent reality from the information available

Risk factors of metastasis in women with breast cancer in Isfahan, Iran

Background: Breast cancer is one of the most common malignancies in women and its metastasis plays an important role in mortality, treatment failures and complications. The objective of this study was to evaluate the risk factors of metastatic breast cancer. Methods: In a retrospective cohort study, breast cancer patients in Isfahan, Iran were followed up for ten years. The existence of metastasis was considered as the dependent variable while independent variables included age at diagnosis, hormone receptor status, family history, number of lymph nodes dissected in surgery and involved ones, number of pregnancies, age at first pregnancy and menarche, menstrual status, histopathology and tumor size. All data was collected from patients' profiles and analyzed using logistic regression in SPSS16. Findings: A total of 685 patients with breast cancer were studied during 1999-2009. While 91.4 of cases had no metastasis, distant metastasis was found in 8.6 of subjects. Sites of metastasis according to prevalence were lung (4.7), bone (2.6), other organs (1.1), and liver (0.3). Number of involved lymph nodes (P = 0.043) and number of pregnancies (P = 0.022) had significant relationships with metastasis. Conclusion: We concluded that less pregnancies and more involved lymph nodes indicate a high probability of metastasis occurrence. Therefore, survival improvement might be possible with early diagnosis of breast cancer, using prophylactic treatments, and identifying metastatic cases by diagnostic tests

Pressure-dependent EPANET extension

In water distribution systems (WDSs), the available flow at a demand node is dependent on the pressure at that node. When a network is lacking in pressure, not all consumer demands will be met in full. In this context, the assumption that all demands are fully satisfied regardless of the pressure in the system becomes unreasonable and represents the main limitation of the conventional demand driven analysis (DDA) approach to WDS modelling. A realistic depiction of the network performance can only be attained by considering demands to be pressure dependent. This paper presents an extension of the renowned DDA based hydraulic simulator EPANET 2 to incorporate pressure-dependent demands. This extension is termed “EPANET-PDX” (pressure-dependent extension) herein. The utilization of a continuous nodal pressure-flow function coupled with a line search and backtracking procedure greatly enhance the algorithm’s convergence rate and robustness. Simulations of real life networks consisting of multiple sources, pipes, valves and pumps were successfully executed and results are presented herein. Excellent modelling performance was achieved for analysing both normal and pressure deficient conditions of the WDSs. Detailed computational efficiency results of EPANET-PDX with reference to EPANET 2 are included as well

From Data to Decision: An Implementation Model for the Use of Evidence-based Medicine, Data Analytics, and Education in Transfusion Medicine Practice

Healthcare in the United States is underperforming despite record increases in spending. The causes are as myriad and complex as the suggested solutions. It is increasingly important to carefully assess the appropriateness and cost-effectiveness of treatments especially the most resource-consuming clinical interventions. Healthcare reimbursement models are evolving from fee-for-service to outcome-based payment. The Patient Protection and Affordable Care Act has added new incentives to address some of the cost, quality, and access issues related to healthcare, making the use of healthcare data and evidence-based decision-making essential strategies. However, despite the great promise of these strategies, the transition to data-driven, evidence-based medical practice is complex and faces many challenges. This study aims to bridge the gaps that exist between data, knowledge, and practice in a healthcare setting through the use of a comprehensive framework to address the administrative, cultural, clinical, and technical issues that make the implementation and sustainability of an evidence-based program and utilization of healthcare data so challenging. The study focuses on promoting evidence-based medical practice by leveraging a performance management system, targeted education, and data analytics to improve outcomes and control costs. The framework was implemented and validated in transfusion medicine practice. Transfusion is one of the top ten coded hospital procedures in the United States. Unfortunately, the costs of transfusion are underestimated and the benefits to patients are overestimated. The particular aim of this study was to reduce practice inconsistencies in red blood cell transfusion among hospitalists in a large urban hospital using evidence-based guidelines, a performance management system, recurrent reporting of practice-specific information, focused education, and data analytics in a continuous feedback mechanism to drive appropriate decision-making prior to the decision to transfuse and prior to issuing the blood component. The research in this dissertation provides the foundation for implementation of an integrated framework that proved to be effective in encouraging evidence-based best practices among hospitalists to improve quality and lower costs of care. What follows is a discussion of the essential components of the framework, the results that were achieved and observations relative to next steps a learning healthcare organization would consider

Realization of an electromechanical nano-string device

Electromechanics is the field of studying the interaction between microwave resonators and mechanical oscillators. It has been an interesting topic in the recent decade due to its numerous potential applications in science and technology, including ground-state cooling of macroscopic objects, quantum sensing, quantum memory, and quantum transduction. This thesis presents a comprehensive analysis of a project focused on simulating, designing, and modeling electromechanical devices with the ultimate objective of achieving their successful implementation. Through the thesis, after an overview of the theoretical model of electromechanics, I will introduce our design for the device and explain how we simulated it to optimize its characteristics. Next, I will discuss the nanofabrication process we have developed for the device, along with the fundamental aspects of the characterization method and setup. Subsequently, I will present the theoretical model I have developed based on electromechanics. This model has significant potential to open up new avenues for future research, building upon the foundation laid by the current project.Comment: Master's thesi

Hedging price risk to soybean producers with futures and options: a case study

Soybean producers have faced considerable price risk in recent years. The large variations in soybean prices have been increasingly noticeable in the last 15 years or so as compared with the 1950s and 1960s. Harvest cash returns have been highly volatile and frequently low. Soybean producers have available a number of marketing alternatives which they can use to help reduce price risks for their product. These alternatives include futures as well as options markets for soybeans. However, less than ten percent of U.S. major-crop farmers currently employ futures and/or options contracts in the marketing of their products. This situation stems mainly from lack of enough information currently available on how the use of these contracts affects the prices received by farmers for their products. Relatively little research has been done thus far on marketing strategies for major-crop farmers. The purpose of this study is to partially remedy this situation;Forty-two marketing strategies involving cash sales, futures market contracts, and options market contracts for soybean farmers in Northcentral Iowa were simulated over the period of 1975 through 1985. Because soybean option contracts were not traded in the U.S. before November 1984, options premiums were estimated for the 1975-84 period with a modified version of the Cox, Ross, and Rubinstein (1979) model. An attractive feature of this model is that it takes into account the effects of government price supports on options prices. The results of mean-variance and mean-semi-variance analysis (both in current and constant dollars) indicated that most of the pre-harvest routine hedging strategies, routine at-the-money puts purchasing strategies, and post-harvest selective hedging strategies based on cost of production increased the average net returns and reduced the variability of returns relative to the cash only strategy. However, post-harvest put option purchasing strategies and routine storage strategies did not perform well in comparison with the cash market