A model for the development of a power production system in Greece,Part I: Where RES do not meet EU targets

This paper studies the electricity production system of the Greek Interconnected Electric Production System using a model created with the software package WASP-IV. The period of study is from 2009 to 2030. It consists of three scenarios using three different criteria: energy, environmental and economic. The three scenarios are the business as usual, the lignite and the natural gas. Subsequently, a sensitivity analysis is carried out for the annual growth rate of electricity consumption and load demand. The paper examines how the three criteria change, when there are no other energy sources beyond those already in use (lignite, oil, natural gas, biomass, solar, wind and hydropower) with no CO₂ capture policies and with the electricity production from Renewable Energy Sources not to reach the targets of the European Union for 2020. In a second paper, three other scenarios examine production with the Renewable Energy Sources to reach the targets of the European Union for 2020.     

Estimating ground-level PM2.5 in the eastern United States using satellite remote sensing

An empirical model based on the regression between daily PM2.5 (particles with aerodynamic diameters of less than 2.5 microm) concentrations and aerosol optical thickness (AOT) measurements from the multiangle imaging spectroradiometer (MISR) was developed and tested using data from the eastern United States during the period of 2001. Overall, the empirical model explained 48% of the variability in PM2.5 concentrations. The root-mean-square error of the model was 6.2 microg/m3 with a corresponding average PM2.5 concentration of 13.8 microg/m3. When PM2.5 concentrations greater than 40 microg/m3 were removed, model results were shown to be unbiased estimators of observations. Several factors, such as planetary boundary layer height, relative humidity, season, and other geographical attributes of monitoring sites, were found to influence the association between PM2.5 and AOT. The findings of this study illustrate the strong potential of satellite remote sensing in regional ambient air quality monitoring as an extension to ground networks. With the continual advancement of remote sensing technology and global data assimilation systems, AOT measurements derived from satellite remote sensors may provide a cost-effective approach as a supplemental source of information for determining ground-level particle concentrations.     

A multilevel sampled‐data approach for resilient navigation and control of autonomous systems

Autonomous systems are rapidly becoming an integrated part of the modern life. Safe and secure navigation and control of these systems present significant challenges in the presence of uncertainties, physical failures, and cyber attacks. In this paper, we formulate a navigation and control problem for autonomous systems using a multilevel control structure, in which the high‐level reference commands are limited by a saturation function, whereas the low‐level controller tracks the reference by compensating for disturbances and uncertainties. For this purpose, we consider a class of nested, uncertain, multiple‐input–multiple‐output systems subject to reference command saturation, possibly with nonminimum phase zeros. A multirate output‐feedback adaptive controller is developed as the low‐level controller. The sampled‐data (SD) design of this controller facilitates the direct implementation on digital computers, where the input/output signals are available at discrete time instances with different sampling rates. In addition, stealthy zero‐dynamics attacks become detectable by considering a multirate SD formulation. Robust stability and performance of the overall closed‐loop system with command saturation and multirate adaptive control are analyzed. Simulation scenarios for navigation and control of a fixed‐wing drone under failures/attacks are provided to validate the theoretical findings.     

Fibro/chondrogenic differentiation of dental stem cells into chitosan/alginate scaffolds towards temporomandibular joint disc regeneration

Tissue engineering (TE) may provide effective alternative treatment for challenging temporomandibular joint (TMJ) pathologies associated with disc malpositioning or degeneration and leading to severe masticatory dysfunction. Aim of this study was to evaluate the potential of chitosan/alginate (Ch/Alg) scaffolds to promote fibro/chondrogenic differentiation of dental pulp stem cells (DPSCs) and production of fibrocartilage tissue, serving as a replacement of the natural TMJ disc. Ch/Alg scaffolds were fabricated by crosslinking with CaCl2 combined or not with glutaraldehyde, resulting in two scaffold types that were physicochemically characterized, seeded with DPSCs or human nucleus pulposus cells (hNPCs) used as control and evaluated for cell attachment, viability, and proliferation. The DPSCs/scaffold constructs were incubated for up to 8 weeks and assessed for extracellular matrix production by means of histology, immunofluorescence, and thermomechanical analysis. Both Ch/Alg scaffold types with a mass ratio of 1:1 presented a gel-like structure with interconnected pores. Scaffolds supported cell adhesion and long-term viability/proliferation of DPSCs and hNPCs. DPSCs cultured into Ch/Alg scaffolds demonstrated a significant increase of gene expression of fibrocartilaginous markers (COLI, COL X, SOX9, COM, ACAN) after up to 3 weeks in culture. Dynamic thermomechanical analysis revealed that scaffolds loaded with DPSCs significantly increased storage modulus and elastic response compared to cell-free scaffolds, obtaining values similar to those of native TMJ disc. Histological data and immunochemical staining for aggrecan after 4 to 8 weeks indicated that the scaffolds support abundant fibrocartilaginous tissue formation, thus providing a promising strategy for TMJ disc TE-based replacement.

Open image in new window

     

Topological Based Scan Matching – Odometry Posterior Sampling in RBPF Under Kinematic Model Failures

Rao-Blackwellized Particle Filters (RBPF) have been utilized to provide a solution to the SLAM problem. One of the main factors that cause RBPF failure is the potential particle impoverishment. Another popular approach to the SLAM problem are Scan Matching methods, whose good results require environments with lots of information, however fail in the lack thereof. To face these issues, in the current work techniques are presented to combine Rao-Blackwellized particle filters with a scan matching algorithm (CRSM SLAM). The particle filter maintains the correct hypothesis in environments lacking features and CRSM is employed in feature-rich environments while simultaneously reduces the particle filter dispersion. Since CRSM’s good performance is based on its high iteration frequency, a multi-threaded combination is presented which allows CRSM to operate while RBPF updates its particles. Additionally, a novel method utilizing topological information is proposed, in order to reduce the number of particle filter resamplings. Finally, we present methods to address anomalous situations where scan matching can not be performed and the vehicle displays behaviors not modeled by the kinematic model, causing the whole method to collapse. Numerous experiments are conducted to support the aforementioned methods’ advantages.     

In vivo imaging of hydrogen peroxide with chemiluminescent nanoparticles

The overproduction of hydrogen peroxide is implicated in the development of numerous diseases and there is currently great interest in developing contrast agents that can image hydrogen peroxide in vivo. In this report, we demonstrate that nanoparticles formulated from peroxalate esters and fluorescent dyes can image hydrogen peroxide in vivo with high specificity and sensitivity. The peroxalate nanoparticles image hydrogen peroxide by undergoing a three-component chemiluminescent reaction between hydrogen peroxide, peroxalate esters and fluorescent dyes. The peroxalate nanoparticles have several attractive properties for in vivo imaging, such as tunable wavelength emission (460-630 nm), nanomolar sensitivity for hydrogen peroxide and excellent specificity for hydrogen peroxide over other reactive oxygen species. The peroxalate nanoparticles were capable of imaging hydrogen peroxide in the peritoneal cavity of mice during a lipopolysaccharide-induced inflammatory response. We anticipate numerous applications of peroxalate nanoparticles for in vivo imaging of hydrogen peroxide, given their high specificity and sensitivity and deep-tissue-imaging capability.     

Steady state behaviour of three phase air lift bioreactors – an integrated model and experimental verification

Beneckea natriegens growing both in suspension and immobilised on diatomaceous earth (silica) support particles, in a 3 dm three phase air lift bioreactor (TPALB), was employed to demonstrate the relationship between substrate loading rate and immobilised biomass loading at steady state. Sterile conditions were maintained during the experiments, while the hydraulic conditions and the inlet flowrate remained constant. The experiment ran for 12 days, whilst the inlet substrate (n‐propanol) concentration was varied both upwards and downwards between 250 and 750 mg dm⁻³. The bulk liquid substrate concentration and the immobilised biomass loading were found to vary between 6–120 mg dm⁻³ and 71–159 mg(dry biomass) g⁻¹ (silica), respectively. The experimental results demonstrated that there is a positive relationship between substrate loading and immobilised biomass loading. A mathematical model is proposed to calculate biofilm thickness and bulk liquid substrate concentration (for steady state) using the inlet flowrate and the inlet substrate concentration as input parameters. The model was able to predict both biofilm thickness and immobilised biomass loading for the lower substrate loading rates applied. © 1999 Society of Chemical Industry     

Three-dimensional nonlinear invisible boundary detection.

The human vision system can discriminate regions which differ up to the second-order statistics only. We present an algorithm designed to reveal "hidden" boundaries in gray level images, by computing gradients in higher order statistics of the data. We demonstrate it by applying it to the identification of possible "hidden" boundaries of glioblastomas as manifest themselves in three-dimensional (3-D) MRI scans, using a model driven approach. We also demonstrate the method using a nonmodel driven approach where we have no prior information about the location of possible boundaries. In this case, we use 3-D MRI data concerning schizophrenic patients and normal controls.     

基于分形的从明暗恢复形状算法研究

从明暗恢复形状是计算机视觉领域中的经典病态问题，传统方法是通过引入光滑约束等条件来获得问题的解，但传统方法存在因过平滑而失真的缺点。针对传统方法恢复结果的局限性，提出了一种基于分形约束的从明暗恢复形状的新算法，该方法首先给出分形约束条件，之后结合反射图线性化与最小能量法来计算出曲面高度。该方法不仅克服了传统算法因基于光滑假设所造成的恢复结果过分平滑而失真的缺点，且不需要可积性的约束条件，也不需要对边界条件的假设，实验结果表明，该方法用于自然景物的三维表面重构，可获得比传统方法更好的恢复效果。