A doublet microlens array for imaging micron-sized objects

We present a high-numerical aperture, doublet microlens array for imaging micron-sized objects. The proposed doublet architecture consists of glass microspheres trapped on a predefined array of silicon microholes and covered with a thin polymer layer. A standard silicon microfabrication process and a novel fluidic assembly technique were combined to obtain an array of 56 µm diameter microlenses with a numerical aperture of ~0.5. Using such an array, we demonstrated brightfield and fluorescent image formation of objects directly on a CCD sensor without the use of intermediate lenses. The proposed technology is a significant advancement toward the unmet need of inexpensive, miniaturized optical modules which can be further integrated with lab-on-chip microfluidic devices and photonic chips for a variety of high-end imaging/detection applications.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90795/1/0960-1317_21_10_105024.pd

An evaluation of policies for fiscal and external sustainability during the recent Greek economic crisis

The scope of this note is to point out that high growth rates must be accompanied by current account surpluses financing the internal debt service as a necessary and sufficient condition for a debt-reduction strategy. The recipe is applied in the case of Greece which, looking back at the pre-crisis period, has been experiencing substantial consumptionled growth following extensive foreign borrowing.peer-reviewe

An evaluation of policies for fiscal and external sustainability during the recent Greek economic crisis

The scope of this note is to point out that high growth rates must be accompanied by current account surpluses financing the internal debt service as a necessary and sufficient condition for a debt-reduction strategy. The recipe is applied in the case of Greece which, looking back at the pre-crisis period, has been experiencing substantial consumptionled growth following extensive foreign borrowing.peer-reviewe

Neighbourhood Shading Impacts on Passive Adaptive Façade Collective Behaviour

The past decade witnessed a shift in adaptive facades from energy-intensive complex systems to material-based actuated facades. The latter, however, were only developed with limited control in shape memory alloy applications, and more generally designed as independent components. The perception of the component within a system as a self-regulating entity was shown to widen the behavioural response and intelligence of an adaptive system in several projects. On the other hand, its range of impact and integration as a design factor were not targeted at full breadth in the literature. The study’s objective was to investigate the incorporation of neighbourhood shading behaviour of a shape memory alloy-actuated façade component on the entire system. Based on a designed adaptive component, the research identifies the shading impact on the actuators’ incident solar radiation as well as its hourly and seasonal range, and thus encourages a better prediction of collective behaviour

Geometry-material coordination for passive adaptive solar morphing envelopes

The cost-intensive and mechanical complexity natures of the adaptive facades of the past decades drifted designers and researchers’ interest towards passive material-based actuation systems. Architectural applications using the latter showed, however, a few limitations restricting the output possibility space to options that rely entirely on one material’s phase characteristic. This study aims to investigate the potential of expanding a shape memory alloy-actuated facade’s output from one that is limited and hardly controllable in the case of entirely passive actuation to one that can produce a specific desired performative target. This is explored through coordinating between geometry movement connections of an adaptive component of four integrated shape memory alloys, which work on tailoring the geometry-material-climate relations of the responsive system. The research findings suggest that the integration of geometry, material, and their connections in the design of a SMA solar morphing envelope lead to the development of a wider range of behavioural system outputs. The variety instilled through these added dimensions promoted diversity and adaptability of output for a flexible range of responses and higher performative gains

Understanding participation through a data-driven approach

Participatory models of urban regeneration have been increasingly integrated in local agendas. Yet there is still a need for evaluation methodologies of those models and their impact. This paper presents a data-driven and computational methodology to measure the impact of the BIP/ZIP Program in Lisbon. Using qualitative coding, data integration, unsupervised machine learning models for data clustering and interactive visualization dashboards the study aims to explore the large and complex dataset of the projects of the BIP/ZIP program and identify correlation patterns between their areas of implementation, the networks of project partners and the identified activities of the projects. The proposed methodology is a first step towards the development of a generalizable evaluation framework for participatory models and aims to inform the further development of similar participatory models of urban regeneration.info:eu-repo/semantics/publishedVersio

An Evaluation of Policies for Fiscal and External Sustainability during the Recent Greek Economic Crisis

The scope of this note is to point out that high growth rates must be accompanied by current account surpluses financing the internal debt service as a necessary and sufficient condition for a debt-reduction strategy. The recipe is applied in the case of Greece which, looking back at the pre-crisis period, has been experiencing substantial consumption-led growth following extensive foreign borrowing

Adaptive behavior of structural systems in unpredictable changing environments by using self-learning algorithms: A case study

Adaptive architecture is expected to improve the performance of buildings and create more efficient building systems. One of the major research areas under this scope is the adaptive behavior of structural elements affected by load distribution. In order to achieve this, current studies develop structures that adapt by either following a database of pre-calculated equilibrium solutions or using self-learning algorithms to acquire active control systems to structures. This paper examined a case study element, which demonstrates an adaptive behavior in real time, based on self-learning abilities. The focus of this experiment was to gain control over a structural system as a whole (not only on a singular component) according to both objective and subjective parameters, that is, both load distribution parameters and spatial parameters, which are design related. The examined structural element was a canopy, situated in a dynamic environment that brought a change in the element’s load distribution. The learning ability was given by applying a supervised learning algorithm—Artificial Neural Network (ANN)—on a physical prototype. The ANN was trained by an optimized database of finite solutions, which was created by a Genetic Algorithm. Through this method, complex calculations are conducted “offline”, and the component operates in a “decision-making” mode in real time, adapting to a versatile environment while using minimal computational resources. Results show that the case study successfully exhibited self-learning and acquired the ability to adapt to unpredictable changing forces while keeping certain design requirements. This method can be applied over different structural elements (façade elements, canopies, structural components, etc.) to achieve adaptation to various parameters with an unpredictable pattern, such as human behavior or weather conditions

BIM enabled optimisation framework for environmentally responsible and structurally efficient design systems

The present research investigates the potential for reducing the environmental impacts of structural systems through a more efficient use of materials. The main objective of this research is to explore and to develop a holistic and integrated methodology that utilises Building Information Modelling's (BIM) capabilities combined with structural analysis and Life Cycle Assessment (LCA) as well as a two-staged structural optimisation solver that achieves efficient and environmentally responsible steel design solutions. The implemented workflow utilises Autodesk Revit-BIM, Tally-LCA and Autodesk Robot-Structural Analysis. RobOpt is the plug-in that has been established using the Application Programming Interface (API) of Robot and the .NET framework of C?, and it inherits several structural functionalities based on Robot Finite Element Method (FEM) engine. The proposed RobOpt application can be accessed via a graphic user interface (GUI) within the Robot software. The developed BIM-enabled optimisation methodology could be utilised as a design tool to inform early stage structural design solutions. A prototypical steel framed structural system under certain loads has been explored. The resulting bespoke I-beam sections from the custom genetic algorithm (GA) optimisation demonstrate that significant savings-up to 21%-can be achieved in all tested environmental indicators when compared to the standard UK catalogue of steel sections. Considering all, the proposed framework constitutes a useful and an intuitive workflow, which aims to quantify the environmental savings of structural systems by utilising, advanced computational analysis and common construction techniques