Synergistic Model of Cardiac Function with a Heart Assist Device

The breakdown of cardiac self-organization leads to heart diseases and failure, the number one cause of death worldwide. The left ventricular pressure–volume relation plays a key role in the diagnosis and treatment of heart diseases. Lumped-parameter models combined with pressure–volume loop analysis are very effective in simulating clinical scenarios with a view to treatment optimization and outcome prediction. Unfortunately, often invoked in this analysis is the traditional, time-varying elastance concept, in which the ratio of the ventricular pressure to its volume is prescribed by a periodic function of time, instead of being calculated consistently according to the change in feedback mechanisms (e.g., the lack or breakdown of self-organization) in heart diseases. Therefore, the application of the time-varying elastance for the analysis of left ventricular assist device (LVAD)–heart interactions has been questioned. We propose a paradigm shift from the time-varying elastance concept to a synergistic model of cardiac function by integrating the mechanical, electric, and chemical activity on microscale sarcomere and macroscale heart levels and investigating the effect of an axial rotary pump on a failing heart. We show that our synergistic model works better than the time-varying elastance model in reproducing LVAD–heart interactions with sufficient accuracy to describe the left ventricular pressure–volume relation

Artificial Intelligence Assisted Dynamic Control of Environmental Emissions From Hybrid Energy Process Plants (HEPP)

A model digital data processing platform is proposed based on “deep-learning” methodology that can be used to identify the emissions patterns from process plants with hybrid energy recovery and energy generation facilities. The non-invasive dynamic monitoring and correlation of particulate, VOCs and other greenhouse gas emissions from semi-batch and continuous process plants is demonstrated with use of neural encoding and pattern recognition using a multi-layer perceptron and multi-stack encoder configuration. A multi-layer environmental perceptron (MLEP) is developed based on the above analyses that aims to detect patterns of emission types, rates and concentrations as a function of variation of plant operational conditions and process variables. Four different task algorithms are constructed and are currently trained for use in (i) In-Plant Product Quality Control Domain and (ii) In-Plant Process Efficiency Target Control Domain. As a further consequence, environmental impact assessment is considered within the hazards and process safety frameworks that conventionally issue sanctions and penalize non-compliance with imposition of environmental levy scales rather than offering process improvement incentives. The latter is demonstrated to be possible by facilitating dynamic corrective action and hazard prevention using MLEP platforms should emission ceilings be frequently and/or periodically exceeded in 24/7 continuous plant operations. Potential applications of the MLEP (MLEP) are illustrated in the context of dynamic emissions control and abatement in hybrid energy process plants (HEPP) and combined power plants using process-integrated CO2 capture and storage schemes

Essays on Empirical Market Microstructure

The first essay examines the events of May 6, 2010: the ``Flash Crash". The Flash Crash, a brief period of extreme market volatility on May 6, 2010 raised questions about the current structure of the U.S. financial markets. Audit-trail data from U.S. Commodity Futures Trading Commission (CFTC) is used to describe the structure of the E-mini S\&P 500 stock index futures market on May 6. In this study, three questions are asked. How did High Frequency Traders (HFTs) trade on May 6? What may have triggered the Flash Crash? What role did HFTs play in the Flash Crash? There is evidence which supports that HFTs did not trigger the Flash Crash, but their responses to the unusually large selling pressure on that day exacerbated market volatility. The second essay examines the relationship between mutual fund trading and liquidity consumption in financial markets. Using Thompson Mutual Funds holdings data and the Trade and Quotes (TAQ) data, we relate the mutual fund trading to liquidity consumption. Mutual fund trading is positively correlated with liquidity consumption. Mutual fund sensitivity to liquidity consumption differs based on mutual fund investment style. Large trades reveal the trading activity of actively managed mutual funds whereas the trading activity of index funds can be explained by small trades. This is consistent with a plausible explanation that index funds need to use small trades to rebalance their portfolios and information motivates the large trades of active mutual funds. The third essay tests the predictions of trading game invariance using the sample of trades from TAQ dataset from 1993 to 2008. The theory of trading game invariance predicts that the distribution of trade sizes as a fraction of trading volume should vary across stocks proportionally to their trading activity in -2/3 power and that the number of trades should vary across stocks proportionally to their trading activity in 2/3 power. The data supports predictions of the invariance theory. For the number of trades, the estimated power coefficient of 0.69 (with standard errors of 0.001) is especially close to the predicted one of 2/3 on the subsample before 2001. These estimates increases to 0.79 (with standard errors of 0.004) after 2001 following a structural break related to a reduction in tick size and a consequent spread of algorithmic trading. Furthermore, the entire distribution of trade size shifts with the trading activity in a manner predicted by invariance theory. When trade sizes are adjusted for differences in trading activity, then their distribution is stable across stocks and similar to the distribution of a log-normal variable, truncated at the 100-share threshold

The ERASMUS Teaching Staff Mobility: The Perspectives and Experiences of Turkish ELT Academics

The purpose of this study is to investigate the perspectives and experiences of the Turkish ELT academics about joining ERASMUS Teaching Staff Mobility Program. Under the light of former studies and literature, this study attempts to investigate the preferences of the ELT academics for participating in the ERASMUS Teaching Staff Mobility, to examine the contribution of the enrollment in this program to their professional development and home institution, and finally, to learn about the problems they faced during the mobility period(s). Purposive sample method was used to select seventeen Turkish ELT academics to participate in this study. The data were obtained through a triangulated approach, in which questionnaires, semi-structured interviews and reflective essays were administered to the participants. The findings revealed that apart from some problems experienced before and during the program, the Turkish ELT academics preferred to participate in the ERASMUS Teaching Staff Mobility due to its positive impact on their professional development and their home institution

Analyzing impact of experience curve on ROI in the software product line adoption process

Cataloged from PDF version of article.Context: Experience curve is a well-known concept in management and education science, which explains the phenomenon of increased worker efficiency with repetitive production of a good or service. Objective: We aim to analyze the impact of the experience curve effect on the Return on Investment (ROI) in the software product line engineering (SPLE) process. Method: We first present the results of a systematic literature review (SLR) to explicitly depict the studies that have considered the impact of experience curve effect on software development in general. Subsequently, based on the results of the SLR, the experience curve effect models in the literature, and the SPLE cost models, we define an approach for extending the cost models with the experience curve effect. Finally, we discuss the application of the refined cost models in a real industrial context. Results: The SLR resulted in 15 primary studies which confirm the impact of experience curve effect on software development in general but the experience curve effect in the adoption of SPLE got less attention. The analytical discussion of the cost models and the application of the refined SPLE cost models in the industrial context showed a clear impact of the experience curve effect on the time-to-market, cost of development and ROI in the SPLE adoption process. Conclusions: The proposed analysis with the newly defined cost models for SPLE adoption provides a more precise analysis tool for the management, and as such helps to support a better decision making. © 2014 Elsevier B.V. All rights reserved

Detrimental effects of species of Tenthredinidae (Insecta: Hymenoptera) on plants and control methods

Tenthredinidae family is included in suborder Symphyta of order Hymenoptera (Insecta). The species belonging to this family is harmful by feeding on leaf, stem, bud, flower, etc., of plants. The detrimental effects of these species are especially constituted by larval forms. Larva damages plants by eatingplant tissue, forming gal and opening galleries in leaf, stem and bud of plants. These harmful species can be controlled with biological, cultural and chemical methods. The control methods change according to the species. However, although chemical control is harmful for nature on a large scale, itis generally being used

An Enrichment Workshop using Argumentation-Based Forensic Chemistry Activities to Improve the Critical Thinking of Gifted Students

This research aims to evaluate a workshop using argumentation-based forensic chemistry activities to enhance gifted students' critical thinking. A workshop program, consisting of seven argumentation-based forensic chemistry activities, was conducted with 20 students at a gifted school in Turkey.  A qualitative experimental design was used. An experiment or drawing activity was first carried out. Following this step, the gifted students reconstructed the activity as an argument after an extensive group discussion. The data collected in the student-constructed arguments and evaluation were analyzed for content. The study's findings show that argumentation-based forensic chemistry activities contributed positively to these gifted students' critical thinking development