398 research outputs found
Research synthesis, translation and implementation of non-invasive liver tests
The development of medical diagnostic tests has been an exciting field of research, filled with enormous potential and, at the same time, uncertainty. Despite the great enthusiasm and substantial investment in the biomarker development, there is a paucity of approved diagnostic tests in the clinic. One explanation for this imbalance can be the complicated path for biomarkers from bench to bedside. This lengthy and costly process can be challenging and even frustrating, not only for the test developers, but also for researchers and clinicians. This thesis report studies that highlighted the challenges in the biomarker evaluation field. We observed that in addition to the common methodological challenges in health research, evidence synthesis for evaluating medical tests may face added challenges in many cases. For instance, when more than one threshold is reported by each primary study in a meta-analysis of accuracy studies or when a reference standard is imperfect, or a gold standard is missing (Chapter 2-4). We also observed that in addition to the limitations of risk-of-bias assessments in comparative accuracy studies, these studies commonly miss or incompletely report essential information about comparisons, which may mislead the interpretation of the findings (Chapter 5-7). Moreover, our findings showed that implementation of the medical diagnostic tests in clinical practice is a complex and challenging process, which can be promoted and hindered by different factors (Chapter 8). These resulting findings offer a starting point for improving current research practices in evaluation and implementation of biomarker-based tests
Secure Data Transactions in Mobile Cloud Computing using FAAS
In recent times, security breaches have come to light in mobile cloud transactions, raising concerns about the vulnerability of data stored in mobile clouds. This data is at risk of tampering or unauthorized modification by external users, especially because it resides within a public cloud infrastructure managed by organizations. Such breaches can significantly impact the authenticity and integrity of the stored data. Mobile cloud computing (MCC) is a technology designed to facilitate the transfer of data and communication with end-users over the internet through a mobile cloud infrastructure. To address the urgent need to secure and protect data stored in mobile clouds, we propose the implementation of the Mobile Cloud-Security Model (MCSM). This innovative model is poised to provide an elevated level of data security and integrity for user data by harnessing the power of Federated Learning (FL) and Federation as a Service (FaaS). Federated Learning (FL) seamlessly integrates into the data training process, culminating in the generation of a model using the data hosted in the mobile cloud. This pioneering approach enables collaborative model training while steadfastly upholding data privacy and security. Federation as a Service (FaaS) represents a cloud-based solution that streamlines collaboration and data sharing among diverse organizations or entities. It simplifies the complex processes of configuring trust relationships, managing identities, and establishing data exchange agreements among federated entities, all made possible through the provision of Service Level Agreements (SLAs) for data stored in the mobile cloud. The user data stored in the mobile cloud will be retrieved using Machine Learning (ML) algorithms that learn from user data. Subsequently, this data is offloaded from the edge devices. The outcome of this research is to maintain user data within the FAAS cloud service with higher-level of confidentiality, security and integrity of user’s data
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Model Predictive Active Power Control for Optimal Structural Load Equalization in Waked Wind Farms
In this paper, we propose a model predictive active power control (APC) enhanced by the optimal coordination of the structural loadings of wind turbines operating with fully developed wind farm flows that have extensive interactions with the atmospheric boundary layer. In general, the APC problem, that is, distributing a wind farm power reference among the operating wind turbines, does not have a unique solution; this fact can be exploited for structural load alleviation of the individual wind turbines. Therefore, we formulated a constrained optimization problem to simultaneously minimize the wind farm power reference tracking errors and the structural load deviations of the wind turbines from their mean value. Thewind power plant is represented by a dynamic 3D large–eddy simulation model, whereas the predictive controller employs a simplified, computationally inexpensive model to predict the dynamic power and load responses of the turbines that experience turbulent wind farm flows and wakes. An adjoint approach is an efficient tool used to iteratively compute the gradient of the formulated parameter-varying optimal control problem over a finite prediction horizon. We have discussed the applicability, key features, and computational complexity of the controller by using a wind farm example consisting of 3�4 turbines with different wake interactions for each row. The performance of the proposed adjoint–based model predictive control for APC was evaluated by measuring power reference tracking errors and the corresponding damage equivalent fatigue loads of the wind turbine towers; we compared our proposed control design with recently published proportional–integral–based APC approaches.</p
An active power control approach for wake-induced load alleviation in a fully developed wind farm boundary layer
This paper
studies a closed-loop wind farm control framework for active power control
(APC) with a simultaneous reduction of wake-induced structural loads within a
fully developed wind farm flow interacting with the atmospheric boundary
layer. The main focus is on a classical feedback control, which features a
simple control architecture and a practical measurement system that are
realizable for real-time control of large wind farms. We demonstrate that the
wake-induced structural loading of the downstream turbines can be alleviated,
while the wind farm power production follows a reference signal. A
closed-loop APC is designed first to improve the power-tracking performance
against wake-induced power losses of the downwind turbines. Then, the
nonunique solution of APC for the wind farm is exploited for aggregated
structural load alleviation. The axial induction factors of the individual
wind turbines are considered control inputs to limit the power production of
the wind farm or to switch to greedy control when the demand exceeds the
power available in the wind. Furthermore, the APC solution domain is enlarged
by an adjustment of the power set-points according to the locally available
power at the waked wind turbines. Therefore, the controllability of the wind
turbines is improved for rejecting the intensified load fluctuations inside
the wake. A large-eddy simulation model is employed for resolving the
turbulent flow, the wake structures, and its interaction with the atmospheric
boundary layer. The applicability and key features of the controller are
discussed with a wind farm example consisting of 3×4 turbines with
different wake interactions for each row. The performance of the proposed APC
is evaluated using the accuracy of the wind farm power tracking and the
wake-induced damage equivalent fatigue loads of the towers of the individual
wind turbines.</p
Peroxisome division in the yeast Yarrowia lipolytica is regulated by a signal from inside the peroxisome
We describe an unusual mechanism for organelle division. In the yeast Yarrowia lipolytica, only mature peroxisomes contain the complete set of matrix proteins. These mature peroxisomes assemble from several immature peroxisomal vesicles in a multistep pathway. The stepwise import of distinct subsets of matrix proteins into different immature intermediates along the pathway causes the redistribution of a peroxisomal protein, acyl-CoA oxidase (Aox), from the matrix to the membrane. A significant redistribution of Aox occurs only in mature peroxisomes. Inside mature peroxisomes, the membrane-bound pool of Aox interacts with Pex16p, a membrane-associated protein that negatively regulates the division of early intermediates in the pathway. This interaction inhibits the negative action of Pex16p, thereby allowing mature peroxisomes to divide
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An active power control approach for wake-induced load alleviation in a fully developed wind farm boundary layer
This paper studies a closed-loop wind farm control framework for active power control (APC) with a simultaneous reduction of wake-induced structural loads within a fully developed wind farm flow interacting with the atmospheric boundary layer. The main focus is on a classical feedback control, which features a simple control architecture and a practical measurement system that are realizable for real-time control of large wind farms. We demonstrate that the wake-induced structural loading of the downstream turbines can be alleviated, while the wind farm power production follows a reference signal. A closed-loop APC is designed first to improve the power-tracking performance against wake-induced power losses of the downwind turbines. Then, the nonunique solution of APC for the wind farm is exploited for aggregated structural load alleviation. The axial induction factors of the individual wind turbines are considered control inputs to limit the power production of the wind farm or to switch to greedy control when the demand exceeds the power available in the wind. Furthermore, the APC solution domain is enlarged by an adjustment of the power set-points according to the locally available power at the waked wind turbines. Therefore, the controllability of the wind turbines is improved for rejecting the intensified load fluctuations inside the wake. A large-eddy simulation model is employed for resolving the turbulent flow, the wake structures, and its interaction with the atmospheric boundary layer. The applicability and key features of the controller are discussed with a wind farm example consisting of 3×4 turbines with different wake interactions for each row. The performance of the proposed APC is evaluated using the accuracy of the wind farm power tracking and the wake-induced damage equivalent fatigue loads of the towers of the individual wind turbines.
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Adjoint-based model predictive control for optimal energy extraction in waked wind farms
In this paper, a model predictive control (MPC) is proposed for wind farms to minimize wake-induced power losses. A constrained optimization problem is formulated to maximize the total power production of a wind farm. The developed controller employs a two-dimensional dynamic wind farm model to predict wake interactions in advance. An adjoint approach as an efficient tool is utilized to compute the gradient of the performance index for such a large-scale system. The wind turbine axial induction factors are considered as the control inputs to influence the overall performance by taking the wake interactions into account. A layout of a 2 × 3 wind farm is considered in this study. The parameterization of the controller is discussed in detail for a practical optimal energy extraction. The performance of the adjoint-based model predictive control (AMPC) is investigated with time-varying changes in wind direction. The simulation results show the effectiveness of the proposed approach. The computational complexity of the developed AMPC is also outlined with respect to the real time control implementation.
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The relativistic Sagnac Effect: two derivations
The phase shift due to the Sagnac Effect, for relativistic matter and
electromagnetic beams, counter-propagating in a rotating interferometer, is
deduced using two different approaches. From one hand, we show that the
relativistic law of velocity addition leads to the well known Sagnac time
difference, which is the same independently of the physical nature of the
interfering beams, evidencing in this way the universality of the effect.
Another derivation is based on a formal analogy with the phase shift induced by
the magnetic potential for charged particles travelling in a region where a
constant vector potential is present: this is the so called Aharonov-Bohm
effect. Both derivations are carried out in a fully relativistic context, using
a suitable 1+3 splitting that allows us to recognize and define the space where
electromagnetic and matter waves propagate: this is an extended 3-space, which
we call "relative space". It is recognized as the only space having an actual
physical meaning from an operational point of view, and it is identified as the
'physical space of the rotating platform': the geometry of this space turns out
to be non Euclidean, according to Einstein's early intuition.Comment: 49 pages, LaTeX, 3 EPS figures. Revised (final) version, minor
corrections; to appear in "Relativity in Rotating Frames", ed. G. Rizzi and
M.L. Ruggiero, Kluwer Academic Publishers, Dordrecht, (2003). See also
http://digilander.libero.it/solciclo
The relevance of nanoscale biological fragments for ice nucleation in clouds
Most studies of the role of biological entities as atmospheric ice-nucleating particles have focused on relatively rare supermicron particles such as bacterial cells, fungal spores and pollen grains. However, it is not clear that there are sufficient numbers of these particles in the atmosphere to strongly influence clouds. Here we show that the ice-nucleating activity of a fungus from the ubiquitous genus Fusarium is related to the presence of nanometre-scale particles which are far more numerous, and therefore potentially far more important for cloud glaciation than whole intact spores or hyphae. In addition, we quantify the ice-nucleating activity of nano-ice nucleating particles (nano-INPs) washed off pollen and also show that nano-INPs are present in a soil sample. Based on these results, we suggest that there is a reservoir of biological nano-INPs present in the environment which may, for example, become aerosolised in association with fertile soil dust particles
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