Meltem Elitas

Bio: Meltem Elitas is an academic researcher from Sabancı University. The author has contributed to research in topics: Motion control & Glioma. The author has an hindex of 11, co-authored 52 publications receiving 513 citations. Previous affiliations of Meltem Elitas include Yale University & École Polytechnique Fédérale de Lausanne.

Distribution system state estimation-A step towards smart grid

Abstract: State estimation (SE) is well-established at the transmission system level of the electricity grid, where it has been in use for the last few decades and is a most vital component of energy management systems employed in the monitoring and control centers of electric transmission systems. However, its use for the monitoring and control of power distribution systems (DSs) has not yet been widely implemented because DSs have been majorly passive with uni-directional power flows. This scenario is now changing with the advent of smart grid, which is changing the nature of electric distribution networks by embracing more dispersed generation, demand responsive loads, and measurements devices with different data rates. Thus, the development of distribution system state estimation (DSSE) tool is inevitable for the implementation of protection, optimization, and control techniques, and various other features envisioned by the smart grid concept. Due to the inherent characteristics of DS different from those of transmission systems, transmission system state estimation (TSSE) is not applicable directly to DSs. This paper is an attempt to present the state-of-the-art on DSSE as an enabler function for smart grid features. It broadly reviews the development of DSSE, challenges faced by its development, and various DSSE algorithms. Additionally, it identifies some future research lines for DSSE.

Sliding Modes in Constrained Systems Control

Abstract: In this paper, a sliding-mode-based design framework for fully actuated mechanical multibody system is discussed. The framework is based on the possibility to represent complex motion as a collection of tasks and to find effective mapping of the system coordinates that allows decoupling task and constraint control so one is able to enforce concurrently, or in certain time succession, the task and the constraints. The approach seems naturally encompassing the control of motion systems in interaction, and it allows application to bilateral control, multilateral control, etc. Such an approach leads to a more natural interpretation of the system tasks, simpler controller design, and easier establishment of the systems hierarchy. It allows a unified mathematical treatment of task control in the presence of constraints required to be satisfied by the system coordinates. In order to show the applicability of the proposed techniques, simulation and experimental results for high-precision systems in microsystem assembly tasks and bilateral control systems are presented.

Dielectrophoresis-based purification of antibiotic-treated bacterial subpopulations

Abstract: Persistence of bacteria during antibiotic therapy is a widespread phenomenon, of particular importance in refractory mycobacterial infections such as leprosy and tuberculosis. Persistence is characterized by the phenotypic tolerance of a subpopulation of bacterial cells to antibiotics. Characterization of these “persister” cells is often difficult due to the transient, non-heritable nature of the phenotype and due to the presence of contaminating material from non-persisting cells, which usually comprise the larger fraction. In this study, we use 3D carbon-electrode arrays for dielectrophoresis-based separation of intact cells from damaged cells, revealed by differential staining with propidium iodide, and we use this procedure to purify intact cells from cultures of Mycobacterium smegmatis treated with isoniazid, a frontline anti-tuberculosis drug. The method presented in this study could be used for rapid label-free enrichment of intact persister cells from antibiotic-treated cultures while preserving the metastable persister phenotype. This approach would facilitate the downstream analysis of low-frequency subpopulations of cells using conventional omics techniques, such as transcriptomic and proteomic analysis.

Dielectrophoretic separation of live and dead monocytes using 3D carbon-electrodes

Abstract: Blood has been the most reliable body fluid commonly used for the diagnosis of diseases. Although there have been promising investigations for the development of novel lab-on-a-chip devices to utilize other body fluids such as urine and sweat samples in diagnosis, their stability remains a problem that limits the reliability and accuracy of readouts. Hence, accurate and quantitative separation and characterization of blood cells are still crucial. The first step in achieving high-resolution characteristics for specific cell subpopulations from the whole blood is the isolation of pure cell populations from a mixture of cell suspensions. Second, live cells need to be purified from dead cells; otherwise, dead cells might introduce biases in the measurements. In addition, the separation and characterization methods being used must preserve the genetic and phenotypic properties of the cells. Among the characterization and separation approaches, dielectrophoresis (DEP) is one of the oldest and most efficient label-free quantification methods, which directly purifies and characterizes cells using their intrinsic, physical properties. In this study, we present the dielectrophoretic separation and characterization of live and dead monocytes using 3D carbon-electrodes. Our approach successfully removed the dead monocytes while preserving the viability of the live monocytes. Therefore, when blood analyses and disease diagnosis are performed with enriched, live monocyte populations, this approach will reduce the dead-cell contamination risk and achieve more reliable and accurate test results.

Microchip platforms for multiplex single-cell functional proteomics with applications to immunology and cancer research

Abstract: Single-cell functional proteomics assays can connect genomic information to biological function through quantitative and multiplex protein measurements. Tools for single-cell proteomics have developed rapidly over the past 5 years and are providing approaches for directly elucidating phosphoprotein signaling networks in cancer cells or for capturing high-resolution snapshots of immune system function in patients with various disease conditions. We discuss advances in single-cell proteomics platforms, with an emphasis on microchip methods. These methods can provide a direct correlation of morphological, functional and molecular signatures at the single-cell level. We also provide examples of how those platforms are being applied to both fundamental biology and clinical studies, focusing on immune-system monitoring and phosphoprotein signaling networks in cancer.

Numerical methods for engineers

Abstract: The fifth edition of "Numerical Methods for Engineers" continues its tradition of excellence. Instructors love this text because it is a comprehensive text that is easy to teach from. Students love it because it is written for them--with great pedagogy and clear explanations and examples throughout. The text features a broad array of applications, including all engineering disciplines. The revision retains the successful pedagogy of the prior editions. Chapra and Canale's unique approach opens each part of the text with sections called Motivation, Mathematical Background, and Orientation, preparing the student for what is to come in a motivating and engaging manner. Each part closes with an Epilogue containing sections called Trade-Offs, Important Relationships and Formulas, and Advanced Methods and Additional References. Much more than a summary, the Epilogue deepens understanding of what has been learned and provides a peek into more advanced methods. Approximately 80% of the end-of-chapter problems are revised or new to this edition. The expanded breadth of engineering disciplines covered is especially evident in the problems, which now cover such areas as biotechnology and biomedical engineering. Users will find use of software packages, specifically MATLAB and Excel with VBA. This includes material on developing MATLAB m-files and VBA macros.

Forecasting methods and applications.

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Industrial Applications of the Kalman Filter: A Review

Abstract: The Kalman filter (KF) has received a huge interest from the industrial electronics community and has played a key role in many engineering fields since the 1970s, ranging, without being exhaustive, trajectory estimation, state and parameter estimation for control or diagnosis, data merging, signal processing, and so on. This paper provides a brief overview of the industrial applications and implementation issues of the KF in six topics of the industrial electronics community, highlighting some relevant reference papers and giving future research trends.

Single-cell analysis tools for drug discovery and development

Abstract: The genetic, functional or compositional heterogeneity of healthy and diseased tissues presents major challenges in drug discovery and development. Such heterogeneity hinders the design of accurate disease models and can confound the interpretation of biomarker levels and of patient responses to specific therapies. The complex nature of virtually all tissues has motivated the development of tools for single-cell genomic, transcriptomic and multiplex proteomic analyses. Here, we review these tools and assess their advantages and limitations. Emerging applications of single cell analysis tools in drug discovery and development, particularly in the field of oncology, are discussed.

Collective motion and density fluctuations in bacterial colonies

Abstract: Flocking birds, fish schools, and insect swarms are familiar examples of collective motion that plays a role in a range of problems, such as spreading of diseases. Models have provided a qualitative understanding of the collective motion, but progress has been hindered by the lack of detailed experimental data. Here we report simultaneous measurements of the positions, velocities, and orientations as a function of time for up to a thousand wild-type Bacillus subtilis bacteria in a colony. The bacteria spontaneously form closely packed dynamic clusters within which they move cooperatively. The number of bacteria in a cluster exhibits a power-law distribution truncated by an exponential tail. The probability of finding clusters with large numbers of bacteria grows markedly as the bacterial density increases. The number of bacteria per unit area exhibits fluctuations far larger than those for populations in thermal equilibrium. Such “giant number fluctuations” have been found in models and in experiments on inert systems but not observed previously in a biological system. Our results demonstrate that bacteria are an excellent system to study the general phenomenon of collective motion.