Predkliničke studije [61Cu]ATSM kao PET radiofarmaka za snimanje fibrosarkoma

[61Cu]diacetyl-bis(N4-methylthiosemicarbazone) ([61Cu]ATSM) was prepared using in house-made diacetyl-bis(N4-methylthiosemicarbazone) (ATSM) ligand and [61Cu]CuCl2 produced via the natZn(p,x)61Cu (180 μA proton irradiation, 22 MeV, 3.2 h) and purified by a ion chromatography method. [61Cu]ATSM radiochemical purity was >98%, as shown by HPLC and RTLC methods. [61Cu]ATSM was administered into normal and tumor bearing rodents for up to 210 minutes, followed by biodistribution and co-incidence imaging studies. Significant tumor/non-tumor accumulation was observed either by animal sacrification or imaging. [61Cu]ATSM is a positron emission tomography (PET) radiotracer for tumor hypoxia imaging.[61Cu]diacetil-bis(N4-metiltiosemikarbazon) ([61Cu]ATSM) dobiven je iz liganda diacetil-bis(N4-metiltiosemikarbazona) (ATSM) pripravljenog u vlastitom laboratoriju i [61Cu]CuCl2 dobivenog iz natZn(p,x)61Cu (180 μA protonskim zračenjem, 22 MeV, 3.2 h). [61Cu]ATSM je čišćen ionskom kromatografijom. Prema HPLC i RTLC radiokemijska čistoća bila je > 98%. [61Cu]ATSM je davan zdravim glodavcima i glodavcima s tumorom tijekom 210 minuta te je praćena biodistribucija. Žrtvovanjem testiranih životinja te snimanjem primijećena je značajna razlika u akumulaciji [61Cu]ATSM u tumorskom tkivu u odnosu na zdravo tkivo. [61Cu]ATSM je pogodan za dijagnostiku hipoksije tumora pozitron emisijskom tomografijom (PET)

Distributed Data-Driven Decision Making in Uncertain Networked Systems with Applications in Smart Energy Systems

This dissertation aims to develop a rigorous distributed approach to decision making using scenario-based techniques for large-scale networks of interconnected uncertain dynamical systems (called agents). A scenario program is a finite-dimensional optimization problem in which an objective function is minimized under constraints that are associated with finitely many, independently and identically distributed (i.i.d.), scenarios of a random parameter. Theoretical and practical interest in scenario programs originates from the fact that these problems are typically efficiently solvable while being closely related to robust and chance-constrained programs. In the former, the constraint is enforced for all admissible random parameters, whereas in the latter, the constraint is enforced up to a given level of probability. However, finding solutions of the resulting large-scale scenario optimization problem for uncertain networked systems poses several difficulties, e.g., computational cost for a central control unit. The main contribution of this dissertation is the design of a technique to decompose a large-scale scenario program into small-scale distributed scenario programs for each agent. Building on existing results in literature, we provide novel guarantees to quantify the robustness of the resulting solutions in a distributed framework. In this setting, each agent needs to exchange some information with its neighboring agents that is necessary due to the statistical learning features of the proposed setup. However, this inter-agent communication scheme might give rise to some concerns about the agents' private information. We therefore present a novel privatized distributed framework, based on the so-called differential privacy concept, such that each agent can share requested information while preserving its privacy. In addition, a soft communication scheme based on a set parameterization technique, along with the notion of probabilistically reliable set, is introduced to reduce the required communication burden. Such a reliability measure is incorporated into the feasibility guarantees of agent decisions in a probabilistic sense. The theoretical guarantees of the proposed distributed scenario-based decision making framework coincide with the centralized counterpart, however the scaling of the results with the number of agents remains an issue.Networked Cyber-Physical System

Numerical Study of Wheat Conveying in Separator Cyclone using Computational Fluid Dynamics

IntroductionCyclones are widely used to separate solid particles from the fluid phase. Due to the ease of construction, low running costs, and hard-working conditions at high temperatures, people's interest in using cyclones is increasing day by day. Engineers are generally interested in two parameters to perform a complete evaluation of the design and operation of a cyclone. These parameters are the particle collecting efficiency and the pressure drop inside the cyclone. The precise prediction of the pressure drop in cyclone is very important which it is directly related to operating costs.Computational Fluid Dynamics (CFD) is a diversified tool for predicting flow behavior in a wide range of design and operational conditions. Numerical solution of Navier-Stokes equations is the basis of all CFD techniques, which is the result of fast computer upgrades and a better understanding of the numerical resolution of turbulence.Materials and MethodsRegarding preliminary experimental tests and understanding the fluid flow, the flow rate of 0.08 kg s-1 was selected as the flow rate. Six levels of inlet velocities 10, 12, 14, 16, 18, and 20 m s-1 were selected for understanding the effect of inlet velocity on the cyclone performance. The measurements were carried out using a hot-air anemometer (TSI-8484model with a resolution of 0.07 m s-1 and an operating range of 0.125 to 50 m s-1), and a pressure differential meter instrument (CPE310s-KIMO model) with an accuracy of 0.1 Pa.The region is discretized as a finite volume in a set, called the region grid or mesh after discretization. For incompressible fluids, pressure-based and density-based solvers are used, respectively. Regarding the velocity of the material entering the cyclone and low Mach number, a pressure-based solver could be used in this study.The shear stress transport model (SST) is a modified version of the k-ω 2-equation model. This model combines the two turbulence k-ω and k-ε models. The Lagrangian discrete phase model in Ansys Fluent follows to the Euler-Lagrangian model.Defining the best type of boundary condition is important for solving the problem and extracting solving fields. The boundary conditions used in this study include the inlet velocity in the entrance of cyclone and output pressure in both the upper and lower output sections.Results and DiscussionIn the results section, the results are initially validated by experimental results. Then, the parameters relating to separation efficiency and pressure drop are discussed. Finally, the tangential and axial velocities are considered as important parameters in the cyclone performance.One of the important issues in the cyclones is the static pressure because it completely affects the phenomenon of separation in the cyclone. The velocities of 16 m s-1 and 18 m s-1 have a good potential for use as the base velocity of the inlet fluid to the cyclone. The velocity of 20 m s-1 is not suitable for separation due to high-pressure drop related to high static pressure.The separation efficiency in the cyclone was 92 to 99% at all levels, the highest separation efficiency of 99% occurred at the velocity of 16 m s-1 and the lowest separation efficiency of 9% happened at the velocity of 20 m s-1.An increasing trend in axial and radial velocities occurred and the highest tangential velocity occurring in the input section. Considering the working conditions, the inlet velocities of 10 m s-1 to 16 m s-1 are appropriate for the turbulence intensity viewpoint.Conclusions(1): The speeds 16 m s-1 and 18 m s-1 showed a good potential for use as a base velocity of the fluid to the cyclone.(2): The highest separation efficiency for the velocity of 16 m s-1 (99%) and lower isolation efficiency was obtained at velocity of 20 m s-1 (92%).(3): The velocities of 10 m s-1 to 16 m s-1 are suitable input rates from the point of view of turbulence intensity.(4): It is concluded that from the point of view of wear to the velocity of 10 to 16 m s-1, practical use is possible, and the velocity of 18 m s-1 and 20 m s-1 require the reinforcement of the relevant sections

Adaptive governance of aquifers with ATES: Use it or lose it (PPT)

Betreft PPT-presentatie t.b.v. conferentieWater ResourcesPolicy AnalysisNetworked Cyber-Physical System

A control-oriented model for combined building climate comfort and aquifer thermal energy storage system

This paper presents a control-oriented model for combined building climate comfort and aquifer thermal energy storage (ATES) system. In particular, we first provide a description of building operational systems together with control framework variables. We then focus on the derivation of an analytical model for ATES system dynamics. The dynamics of stored thermal energy over time in each well of an ATES system is the most important concept for a building climate control framework. This concept is proportional to the volume and temperature of water in each well of an ATES system at each sampling time. In this paper we develop a novel mathematical model for both dynamical behavior of volume and temperature of water in each well of an ATES system and provide detailed steps for estimating the model parameters. To illustrate the applicability of our proposed model, a comparison based on an extensive simulation study using an aquifer groundwater simulation environment (MODFLOW) is provided

Stochastic unit commitment and reserve scheduling: A tractable formulation with probabilistic certificates

The increased penetration of renewable energy sources to the network highlights the necessity of constructing stochastic variants of the standard unit commitment and reserve scheduling problems. Earlier approaches to such problems are either restricted to ad-hoc methodologies (at the expense of a suboptimal solution), or lead to computationally intractable formulations. In this paper we provide a unified framework to deal with such planning problems for systems with uncertain generation, while providing a-priori probabilistic certificates for the robustness properties of the resulting solution. Our methodology is based on a mixture of randomized and robust optimization and leads to a tractable problem formulation. To illustrate the performance of the proposed methodology we apply it to the IEEE 30-bus network, and compare it by means of Monte Carlo simulations against an algorithm based on a deterministic variant of the unit commitment problem

A control-oriented model for combined building climate comfort and aquifer thermal energy storage system

This paper presents a control-oriented model for combined building climate comfort and aquifer thermal energy storage (ATES) system. In particular, we first provide a description of building operational systems together with control framework variables. We then focus on the derivation of an analytical model for ATES system dynamics. The dynamics of stored thermal energy over time in each well of an ATES system is the most important concept for a building climate control framework. This concept is proportional to the volume and temperature of water in each well of an ATES system at each sampling time. In this paper we develop a novel mathematical model for both dynamical behavior of volume and temperature of water in each well of an ATES system and provide detailed steps for estimating the model parameters. To illustrate the applicability of our proposed model, a comparison based on an extensive simulation study using an aquifer groundwater simulation environment (MODFLOW) is provided.Hybrid, Adaptive and NonlinearWater ResourcesPolicy Analysi

Building climate energy management in smart thermal grids via aquifer thermal energy storage systems

This paper proposes a building energy management framework, described by mixed logical dynamical systems due to operating constraints and logic rules, together with an aquifer thermal energy storage (ATES) model. We develop a deterministic model predictive control strategy to meet building thermal energy demand. At each sampling a mixed integer quadratic optimization problem is formulated. We then provide a simulation study using an agent-based model and a geohydrological simulation environment (MODFLOW) to illustrate the performance of the framework.</p