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Understanding construction sector policy through narrative analysis: A critical perspective
No full textConstruction management researchers are too often subservient to the accepted orthodoxy of construction sector policy. They thereby abrogate their academic responsibility to challenge taken-for-granted assumptions. Policy is seen to be formulated and enacted through the medium of narrative. The constituent storylines are further shaped and conditioned by the meta narratives which characterise the political economies within which they are embedded. Published policy reports hence comprise rich empirical data sources which lend themselves to critical deconstruction through narrative analysis. Insights can be gained not only from the content of such reports, but also from the way in which they are scripted. Research of this nature holds policy makers to account for their actions. It is contended that the supposed ‘dysfunctional’ nature of the construction sector can often be ascribed to the unintended consequences of previous policy initiatives. Particular attention is given to the topical narrative of modern methods of construction (MMC)
FE-Simulation of Metal Cutting Processes
Get PDFMachining a new component or a new material requires the selection of the cutting conditions, the tool material and the tool geometry. The selections should be also optimized for the existing components and materials to improve the quality of the produced components and reduce the cost of production. Selecting the most suitable and optimum conditions for the metal cutting processes can be done by performing finite element (FE) simulations which provide more in-depth and detailed information about the cutting processes and also reduce the experimental effort compared to trial-and-error approach.In this thesis, the challenges and complexities that are needed to be considered in FE simulations of cutting processes are addressed. Firstly, the type of FE simulation should be selected according to the purpose of performing the simulation. Different types of FE simulations of metal cutting such as chip forming, heat transfer and material flow simulations are discussed while explaining their purpose and advantages. These simulations are also combined with semi-analytical methods and machine learning approaches to improve the performance of the simulations in terms of both accuracy and time consumption. Secondly, the selection of the suitable material model for the workpiece and the identification process of the material model parameters are crucial to obtain realistic results from FE simulations. In this aspect, an efficient and robust method of inverse identification of the material model parameters is presented in the scope of the thesis to improve the results of the metal cutting simulations. This identification approach is also implemented to identify the parameters of different material models to find the best-suited model to represent the behavior of the presented carbon steel workpiece material under different cutting conditions. In addition, different effects such as elastic, plastic, viscous and damage behaviors in the material modeling are also discussed throughout the thesis while touching upon their indicators in metal cutting.There are many more effects and parameters that can be implemented in FE simulations which make the simulations more in-depth and accurate in exchange for computational time. That is why finding the optimum point between the accuracy and time consumption for metal cutting simulations is of interest to many researchers and engineers. The aim of this thesis is to accomplish this while assessing the different aspects of FE simulations of metal cutting processes and discussing the mentioned challenges and complexities in more detail
Evaluation of heterogeneous AIoT Accelerators within VEDLIoT
No full textWithin VEDLIoT, a project targeting the development of energy-efficient Deep Learning for distributed AIoT applications, several accelerator platforms based on technologies like CPUs, embedded GPUs, FPGAs, or specialized ASICs are evaluated. The VEDLIoT approach is based on modular and scalable cognitive IoT hardware platforms. Modular microserver technology enables the integration of different, heterogeneous accelerators into one platform. Benchmarking of the different accelerators takes into account performance, energy efficiency and accuracy. The results in this paper provide a solid overview regarding available accelerator solutions and provide guidance for hardware selection for AIoT applications from far edge to cloud. VEDLIoT is an H2020 EU project which started in November 2020. It is currently in an intermediate stage. The focus is on the considerations of the performance and energy efficiency of hardware accelerators. Apart from the hardware and accelerator focus presented in this paper, the project also covers toolchain, security and safety aspects. The resulting technology is tested on a wide range of AIoT applications
Varying Road Surface Condition Estimation in Ego and Adjacent Lanes
No full textImages from a front-facing camera on a vehicle can be used to estimate the varying Road Surface Conditions (RSC) ahead to warn the driver or to initiate automatic speed reduction in slippery road conditions. Previous works have successfully used deep-learning models to identify the RSC in the ego lane. Here, we focused on developing a model for predicting the RSC in multiple lanes simultaneously, relevant if changing lanes is an option. The proposed model estimate the RSC on the ego lane as well as in the adjacent lanes only if the adjacent lanes exists in the image. Furthermore, a data set is developed using more than 12,000 images from public benchmarks and privately captured images to facilitate multi-lane RSC estimation. Each image is assigned three RSC labels: with one for the ego, left and right lanes. The classes used are dry, wet, snow and snow-tracks. Our analysis with several network architectures has revealed that the model is capable of estimating the RSC in adjacent lanes with a similar level of performance as of the ego-lane
Targeted In Vivo Mutagenesis in Yeast Using CRISPR/Cas9 and Hyperactive Cytidine and Adenine Deaminases
Get PDFDirected evolution is a preferred strategy to improvethe functionof proteins such as enzymes that act as bottlenecks in metabolic pathways.Common directed evolution approaches rely on error-prone PCR-basedlibraries where the number of possible variants is usually limitedby cellular transformation efficiencies. Targeted in vivo mutagenesis can advance directed evolution approaches and help toovercome limitations in library generation. In the current study,we aimed to develop a high-efficiency time-controllable targeted mutagenesistoolkit in the yeast Saccharomyces cerevisiae by employing the CRISPR/Cas9 technology. To that end, we fused thedCas9 protein with hyperactive variants of adenine and cytidine deaminasesaiming to create an inducible CRISPR-based mutagenesis tool targetinga specific DNA sequence in vivo with extended editingwindows and high mutagenesis efficiency. We also investigated theeffect of guide RNA multiplexing on the mutagenesis efficiency bothphenotypically and on the DNA level
Enhanced Second-Order Nonlinearities at Strained Ultrasharp Zigzag Edges in Multilayer MoS2
Get PDFTransition metal dichalcogenide (TMD) materials attract significant research attention thanks to their exceptional excitonic and optical properties. In this work, we analyze the formation of strained ultrasharp zigzag edges in MoS2 multilayers produced by anisotropic wet etching. The topography of the edges is determined by the relative stability of the different crystallographic directions of the multilayer as well as the interlayer interactions. Furthermore, we study the linear (Raman) and nonlinear (second-harmonic generation) spectroscopic characteristics of such edges and observe enhanced second-order nonlinearity originating from the strained zigzag edges. We also confirm that ultrasharp hexagonal nanoholes in MoS2 grow along the most stable crystallographic directions despite potential stacking faults or instabilities in the crystal quality. Our results open the way to exploit a broad range of phenomena occurring at the edges of MoS2 material, including the unique determination of crystal orientation for moir\ue9 engineering and strongly correlated phenomena in 2D material-based systems, as well as potential applications in TMD-based electrocatalysis and gas sensing
Star cluster formation from turbulent clumps – III. Across the mass spectrum
No full textWe study the formation and early evolution of star clusters that have a wide range of masses and background cloud mass surface densities, ∑cloud, which help set the initial sizes, densities, and velocity dispersions of the natal gas clumps. Initial clump masses of 300, 3000, and 30 000 M☉ are considered, from which star clusters are born with an assumed 50 per cent overall star formation efficiency and with 50 per cent primordial binarity. This formation is gradual, i.e. with a range of star formation efficiencies per free-fall time from 1 to 100 per cent, so that the formation time can range from 0.7 Myr for low-mass, high-∑cloud clumps to ∼30 Myr for high-mass, low-∑cloud clumps. Within this framework of the turbulent clump model, for a given ∑cloud, clumps of higher mass are of lower initial volume density, but their dynamical evolution leads to higher bound fractions and causes them to form much higher density cluster cores and maintain these densities for longer periods. This results in systematic differences in the evolution of binary properties, degrees of mass segregation, and rates of creation of dynamically ejected runaways. We discuss the implications of these results for observed star clusters and stellar populations
Improved control of a prosthetic limb by surgically creating electro-neuromuscular constructs with implanted electrodes
No full textRemnant muscles in the residual limb after amputation are the most common source of control signals for prosthetic hands, because myoelectric signals can be generated by the user at will. However, for individuals with amputation higher up the arm, such as an above-elbow (transhumeral) amputation, insufficient muscles remain to generate myoelectric signals to enable control of the lost arm and hand joints, thus making intuitive control of wrist and finger prosthetic joints unattainable. We show that severed nerves can be divided along their fascicles and redistributed to concurrently innervate different types of muscle targets, particularly native denervated muscles and nonvascularized free muscle grafts. We engineered these neuromuscular constructs with implanted electrodes that were accessible via a permanent osseointegrated interface, allowing for bidirectional communication with the prosthesis while also providing direct skeletal attachment. We found that the transferred nerves effectively innervated their new targets as shown by a gradual increase in myoelectric signal strength. This allowed for individual flexion and extension of all five fingers of a prosthetic hand by a patient with a transhumeral amputation. Improved prosthetic function in tasks representative of daily life was also observed. This proof-of-concept study indicates that motor neural commands can be increased by creating electro-neuromuscular constructs using distributed nerve transfers to different muscle targets with implanted electrodes, enabling improved control of a limb prosthesis
Thermal conductivity vs depth profiling using the hot disk technique-Analysis of anisotropic, inhomogeneous structures
Get PDFA recently developed method for analyzing the thermal conductivity vs depth variation near a sample surface has been extended to include inhomogeneous samples with anisotropy. If not considered, the anisotropy ratio in the sample structure can distort the depth-position data of the original test method. The anisotropy ratio is introduced in the original computational scheme in order to improve the depth-position estimations for inhomogeneous structures with anisotropy. The proposed approach has been tested in experiments and shown to improve depth position mapping
Multiscale X-ray imaging and characterisation of pharmaceutical dosage forms
Get PDFA correlative, multiscale imaging methodology for visualising and quantifying the morphology of solid dosage forms by combining ptychographic X-ray computed nanotomography (PXCT) and scanning small- and wide-angle X-ray scattering (S/WAXS) is presented. The methodology presents a workflow for multiscale analysis, where structures are characterised from the nanometre to millimetre regime. Here, the method is demonstrated by characterising a hot-melt extruded, partly crystalline, solid dispersion of carbamazepine in ethyl cellulose. Characterisation of the morphology and solid-state phase of the drug in solid dosage forms is central as this affects the performance of the final formulation. The 3D morphology was visualised at a resolution of 80 nm over an extended volume through PXCT, revealing an oriented structure of crystalline drug domains aligned in the direction of extrusion. Scanning S/WAXS showed that the nanostructure is similar over the cross section of the extruded filament, with minor radial changes in domain sizes and degree of orientation. The polymorphic forms of carbamazepine were qualified with WAXS, showing a heterogeneous distribution of the metastable forms I and II. This demonstrates the methodology for multiscale structural characterization and imaging to enable a better understanding of the relationships between morphology, performance, and processing conditions of solid dosage forms