913 resultados para Power Differential Scale


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Network reconfiguration for service restoration (SR) in distribution systems is a complex optimization problem. For large-scale distribution systems, it is computationally hard to find adequate SR plans in real time since the problem is combinatorial and non-linear, involving several constraints and objectives. Two Multi-Objective Evolutionary Algorithms that use Node-Depth Encoding (NDE) have proved able to efficiently generate adequate SR plans for large distribution systems: (i) one of them is the hybridization of the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) with NDE, named NSGA-N; (ii) the other is a Multi-Objective Evolutionary Algorithm based on subpopulation tables that uses NDE, named MEAN. Further challenges are faced now, i.e. the design of SR plans for larger systems as good as those for relatively smaller ones and for multiple faults as good as those for one fault (single fault). In order to tackle both challenges, this paper proposes a method that results from the combination of NSGA-N, MEAN and a new heuristic. Such a heuristic focuses on the application of NDE operators to alarming network zones according to technical constraints. The method generates similar quality SR plans in distribution systems of significantly different sizes (from 3860 to 30,880 buses). Moreover, the number of switching operations required to implement the SR plans generated by the proposed method increases in a moderate way with the number of faults.

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[EN] This paper presents an interpretation of a classic optical flow method by Nagel and Enkelmann as a tensor-driven anisotropic diffusion approach in digital image analysis. We introduce an improvement into the model formulation, and we establish well-posedness results for the resulting system of parabolic partial differential equations. Our method avoids linearizations in the optical flow constraint, and it can recover displacement fields which are far beyond the typical one-pixel limits that are characteristic for many differential methods for optical flow recovery. A robust numerical scheme is presented in detail. We avoid convergence to irrelevant local minima by embedding our method into a linear scale-space framework and using a focusing strategy from coarse to fine scales. The high accuracy of the proposed method is demonstrated by means of a synthetic and a real-world image sequence.

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Introduction 1.1 Occurrence of polycyclic aromatic hydrocarbons (PAH) in the environment Worldwide industrial and agricultural developments have released a large number of natural and synthetic hazardous compounds into the environment due to careless waste disposal, illegal waste dumping and accidental spills. As a result, there are numerous sites in the world that require cleanup of soils and groundwater. Polycyclic aromatic hydrocarbons (PAHs) are one of the major groups of these contaminants (Da Silva et al., 2003). PAHs constitute a diverse class of organic compounds consisting of two or more aromatic rings with various structural configurations (Prabhu and Phale, 2003). Being a derivative of benzene, PAHs are thermodynamically stable. In addition, these chemicals tend to adhere to particle surfaces, such as soils, because of their low water solubility and strong hydrophobicity, and this results in greater persistence under natural conditions. This persistence coupled with their potential carcinogenicity makes PAHs problematic environmental contaminants (Cerniglia, 1992; Sutherland, 1992). PAHs are widely found in high concentrations at many industrial sites, particularly those associated with petroleum, gas production and wood preserving industries (Wilson and Jones, 1993). 1.2 Remediation technologies Conventional techniques used for the remediation of soil polluted with organic contaminants include excavation of the contaminated soil and disposal to a landfill or capping - containment - of the contaminated areas of a site. These methods have some drawbacks. The first method simply moves the contamination elsewhere and may create significant risks in the excavation, handling and transport of hazardous material. Additionally, it is very difficult and increasingly expensive to find new landfill sites for the final disposal of the material. The cap and containment method is only an interim solution since the contamination remains on site, requiring monitoring and maintenance of the isolation barriers long into the future, with all the associated costs and potential liability. A better approach than these traditional methods is to completely destroy the pollutants, if possible, or transform them into harmless substances. Some technologies that have been used are high-temperature incineration and various types of chemical decomposition (for example, base-catalyzed dechlorination, UV oxidation). However, these methods have significant disadvantages, principally their technological complexity, high cost , and the lack of public acceptance. Bioremediation, on the contrast, is a promising option for the complete removal and destruction of contaminants. 1.3 Bioremediation of PAH contaminated soil & groundwater Bioremediation is the use of living organisms, primarily microorganisms, to degrade or detoxify hazardous wastes into harmless substances such as carbon dioxide, water and cell biomass Most PAHs are biodegradable unter natural conditions (Da Silva et al., 2003; Meysami and Baheri, 2003) and bioremediation for cleanup of PAH wastes has been extensively studied at both laboratory and commercial levels- It has been implemented at a number of contaminated sites, including the cleanup of the Exxon Valdez oil spill in Prince William Sound, Alaska in 1989, the Mega Borg spill off the Texas coast in 1990 and the Burgan Oil Field, Kuwait in 1994 (Purwaningsih, 2002). Different strategies for PAH bioremediation, such as in situ , ex situ or on site bioremediation were developed in recent years. In situ bioremediation is a technique that is applied to soil and groundwater at the site without removing the contaminated soil or groundwater, based on the provision of optimum conditions for microbiological contaminant breakdown.. Ex situ bioremediation of PAHs, on the other hand, is a technique applied to soil and groundwater which has been removed from the site via excavation (soil) or pumping (water). Hazardous contaminants are converted in controlled bioreactors into harmless compounds in an efficient manner. 1.4 Bioavailability of PAH in the subsurface Frequently, PAH contamination in the environment is occurs as contaminants that are sorbed onto soilparticles rather than in phase (NAPL, non aqueous phase liquids). It is known that the biodegradation rate of most PAHs sorbed onto soil is far lower than rates measured in solution cultures of microorganisms with pure solid pollutants (Alexander and Scow, 1989; Hamaker, 1972). It is generally believed that only that fraction of PAHs dissolved in the solution can be metabolized by microorganisms in soil. The amount of contaminant that can be readily taken up and degraded by microorganisms is defined as bioavailability (Bosma et al., 1997; Maier, 2000). Two phenomena have been suggested to cause the low bioavailability of PAHs in soil (Danielsson, 2000). The first one is strong adsorption of the contaminants to the soil constituents which then leads to very slow release rates of contaminants to the aqueous phase. Sorption is often well correlated with soil organic matter content (Means, 1980) and significantly reduces biodegradation (Manilal and Alexander, 1991). The second phenomenon is slow mass transfer of pollutants, such as pore diffusion in the soil aggregates or diffusion in the organic matter in the soil. The complex set of these physical, chemical and biological processes is schematically illustrated in Figure 1. As shown in Figure 1, biodegradation processes are taking place in the soil solution while diffusion processes occur in the narrow pores in and between soil aggregates (Danielsson, 2000). Seemingly contradictory studies can be found in the literature that indicate the rate and final extent of metabolism may be either lower or higher for sorbed PAHs by soil than those for pure PAHs (Van Loosdrecht et al., 1990). These contrasting results demonstrate that the bioavailability of organic contaminants sorbed onto soil is far from being well understood. Besides bioavailability, there are several other factors influencing the rate and extent of biodegradation of PAHs in soil including microbial population characteristics, physical and chemical properties of PAHs and environmental factors (temperature, moisture, pH, degree of contamination). Figure 1: Schematic diagram showing possible rate-limiting processes during bioremediation of hydrophobic organic contaminants in a contaminated soil-water system (not to scale) (Danielsson, 2000). 1.5 Increasing the bioavailability of PAH in soil Attempts to improve the biodegradation of PAHs in soil by increasing their bioavailability include the use of surfactants , solvents or solubility enhancers.. However, introduction of synthetic surfactant may result in the addition of one more pollutant. (Wang and Brusseau, 1993).A study conducted by Mulder et al. showed that the introduction of hydropropyl-ß-cyclodextrin (HPCD), a well-known PAH solubility enhancer, significantly increased the solubilization of PAHs although it did not improve the biodegradation rate of PAHs (Mulder et al., 1998), indicating that further research is required in order to develop a feasible and efficient remediation method. Enhancing the extent of PAHs mass transfer from the soil phase to the liquid might prove an efficient and environmentally low-risk alternative way of addressing the problem of slow PAH biodegradation in soil.

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Electronic applications are nowadays converging under the umbrella of the cloud computing vision. The future ecosystem of information and communication technology is going to integrate clouds of portable clients and embedded devices exchanging information, through the internet layer, with processing clusters of servers, data-centers and high performance computing systems. Even thus the whole society is waiting to embrace this revolution, there is a backside of the story. Portable devices require battery to work far from the power plugs and their storage capacity does not scale as the increasing power requirement does. At the other end processing clusters, such as data-centers and server farms, are build upon the integration of thousands multiprocessors. For each of them during the last decade the technology scaling has produced a dramatic increase in power density with significant spatial and temporal variability. This leads to power and temperature hot-spots, which may cause non-uniform ageing and accelerated chip failure. Nonetheless all the heat removed from the silicon translates in high cooling costs. Moreover trend in ICT carbon footprint shows that run-time power consumption of the all spectrum of devices accounts for a significant slice of entire world carbon emissions. This thesis work embrace the full ICT ecosystem and dynamic power consumption concerns by describing a set of new and promising system levels resource management techniques to reduce the power consumption and related issues for two corner cases: Mobile Devices and High Performance Computing.

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Wireless sensor networks can transform our buildings in smart environments, improving comfort, energy efficiency and safety. Today however, wireless sensor networks are not considered reliable enough for being deployed on large scale. In this thesis, we study the main failure causes for wireless sensor networks, the existing solutions to improve reliability and investigate the possibility to implement self-diagnosis through power consumption measurements on the sensor nodes. Especially, we focus our interest on faults that generate in-range errors: those are wrong readings but belong to the range of the sensor and can therefore be missed by external observers. Using a wireless sensor network deployed in the R\&D building of NXP at the High Tech Campus of Eindhoven, we performed a power consumption characterization of the Wireless Autonomous Sensor (WAS), and studied through some experiments the effect that faults have in the power consumption of the sensor.

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In the thesis we present the implementation of the quadratic maximum likelihood (QML) method, ideal to estimate the angular power spectrum of the cross-correlation between cosmic microwave background (CMB) and large scale structure (LSS) maps as well as their individual auto-spectra. Such a tool is an optimal method (unbiased and with minimum variance) in pixel space and goes beyond all the previous harmonic analysis present in the literature. We describe the implementation of the QML method in the {\it BolISW} code and demonstrate its accuracy on simulated maps throughout a Monte Carlo. We apply this optimal estimator to WMAP 7-year and NRAO VLA Sky Survey (NVSS) data and explore the robustness of the angular power spectrum estimates obtained by the QML method. Taking into account the shot noise and one of the systematics (declination correction) in NVSS, we can safely use most of the information contained in this survey. On the contrary we neglect the noise in temperature since WMAP is already cosmic variance dominated on the large scales. Because of a discrepancy in the galaxy auto spectrum between the estimates and the theoretical model, we use two different galaxy distributions: the first one with a constant bias $b$ and the second one with a redshift dependent bias $b(z)$. Finally, we make use of the angular power spectrum estimates obtained by the QML method to derive constraints on the dark energy critical density in a flat $\Lambda$CDM model by different likelihood prescriptions. When using just the cross-correlation between WMAP7 and NVSS maps with 1.8° resolution, we show that $\Omega_\Lambda$ is about the 70\% of the total energy density, disfavouring an Einstein-de Sitter Universe at more than 2 $\sigma$ CL (confidence level).

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In the present work, a multi physics simulation of an innovative safety system for light water nuclear reactor is performed, with the aim to increase the reliability of its main decay heat removal system. The system studied, denoted by the acronym PERSEO (in Pool Energy Removal System for Emergency Operation) is able to remove the decay power from the primary side of the light water nuclear reactor through a heat suppression pool. The experimental facility, located at SIET laboratories (PIACENZA), is an evolution of the Thermal Valve concept where the triggering valve is installed liquid side, on a line connecting two pools at the bottom. During the normal operation, the valve is closed, while in emergency conditions it opens, the heat exchanger is flooded with consequent heat transfer from the primary side to the pool side. In order to verify the correct system behavior during long term accidental transient, two main experimental PERSEO tests are analyzed. For this purpose, a coupling between the mono dimensional system code CATHARE, which reproduces the system scale behavior, with a three-dimensional CFD code NEPTUNE CFD, allowing a full investigation of the pools and the injector, is implemented. The coupling between the two codes is realized through the boundary conditions. In a first analysis, the facility is simulated by the system code CATHARE V2.5 to validate the results with the experimental data. The comparison of the numerical results obtained shows a different void distribution during the boiling conditions inside the heat suppression pool for the two cases of single nodalization and three volume nodalization scheme of the pool. Finaly, to improve the investigation capability of the void distribution inside the pool and the temperature stratification phenomena below the injector, a two and three dimensional CFD models with a simplified geometry of the system are adopted.

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Power electronic converters are extensively adopted for the solution of timely issues, such as power quality improvement in industrial plants, energy management in hybrid electrical systems, and control of electrical generators for renewables. Beside nonlinearity, this systems are typically characterized by hard constraints on the control inputs, and sometimes the state variables. In this respect, control laws able to handle input saturation are crucial to formally characterize the systems stability and performance properties. From a practical viewpoint, a proper saturation management allows to extend the systems transient and steady-state operating ranges, improving their reliability and availability. The main topic of this thesis concern saturated control methodologies, based on modern approaches, applied to power electronics and electromechanical systems. The pursued objective is to provide formal results under any saturation scenario, overcoming the drawbacks of the classic solution commonly applied to cope with saturation of power converters, and enhancing performance. For this purpose two main approaches are exploited and extended to deal with power electronic applications: modern anti-windup strategies, providing formal results and systematic design rules for the anti-windup compensator, devoted to handle control saturation, and “one step” saturated feedback design techniques, relying on a suitable characterization of the saturation nonlinearity and less conservative extensions of standard absolute stability theory results. The first part of the thesis is devoted to present and develop a novel general anti-windup scheme, which is then specifically applied to a class of power converters adopted for power quality enhancement in industrial plants. In the second part a polytopic differential inclusion representation of saturation nonlinearity is presented and extended to deal with a class of multiple input power converters, used to manage hybrid electrical energy sources. The third part regards adaptive observers design for robust estimation of the parameters required for high performance control of power systems.

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Das A4-Experiment bestimmt den Beitrag der Strangequarks zu den elektromagnetischen Formfaktoren des Nukleons durch Messung der Paritätsverletzung in der elastischen Elektron-Nukleon-Streuung. Diese Messungen werden mit dem spinpolarisierten Elektronenstrahl des Mainzer Mikrotrons (MAMI) bei Strahlenergien zwischen 315 und 1508 MeV ndurchgeführt. Die Bestimmung des Strahlpolarisationsgrades ist für die Analyse der Daten unerläßlich, um die physikalische Asymmetrie aus der gemessenen paritätsverletzenden Asymmetrie extrahieren zu können. Aus diesem Grund wird von der A4-Kollaboration ein neuartiges Compton-Laserrückstreupolarimeter entwickelt, das eine zerstörungsfreie Messung der Strahlpolarisation, parallel zum laufenden Paritätsexperiment erlaubt. Um den zuverlässigen Dauerbetrieb des Polarimeters zu ermöglichen, wurde das Polarimeter im Rahmen dieser Arbeit weiterentwickelt. Das Datenerfassungssystem für Photonen- und Elektronendetektor wurde neu aufgebaut und im Hinblick auf die Verarbeitung hoher Raten optimiert. Zum Nachweis der rückgestreuten Photonen wurde ein neuartiger Detektor (LYSO) in Betrieb genommen. Darüber hinaus wurden GEANT4-Simulationen der Detektoren durchgeführt und eine Analyseumgebung für die Extraktion von Comptonasymmetrien aus den Rückstreudaten entwickelt. Das Analyseverfahren nutzt die Möglichkeit, die rückgestreuten Photonen durch koinzidente Detektion der gestreuten Elektronen energiemarkiert nachzuweisen (Tagging). Durch die von der Energiemarkierung eingeführte differentielle Energieskala wird somit eine präzise Bestimmung der Analysierstärke möglich. In der vorliegenden Arbeit wurde die Analysierstärke des Polarimeters bestimmt, so daß nun das Produkt von Elektronen- und Laserstrahlpolarisation bei einem Strahlstrom von 20 muA, parallel zum laufenden Paritätsexperiment, mit einer statistischen Genauigkeit von 1% in 24 Stunden bei 855 MeV bzw. <1% in 12 Stunden bei 1508 MeV gemessen werden kann. In Kombination mit der Bestimmung der Laserpolarisation in einer parallelen Arbeit (Y. Imai) auf 1% kann die statistische Unsicherheit der Strahlpolarisation im A4-Experiment von zuvor 5% auf nun 1,5% bei 1508MeV verringert werden. Für die Daten zur Messung der paritätsverletzenden Elektronenstreuung bei einem Viererimpulsübertrag von $Q^2=0,6 (GeV/c)^2$ beträgt die Rohasymmetrie beim derzeitigen Stand der Analyse $A_{PV}^{Roh} = ( -20,0 pm 0,9_{stat} ) cdot 10^{-6}$. Für eine Strahlpolarisation von 80% erhält man einen Gesamtfehler von $1,68 cdot 10^{-6}$ für $Delta P_e/P_e = 5 %$. Als Ergebnis dieser Arbeit wird sich dieser Fehler durch Analyse der Daten des Compton-Laserrückstreupolarimeters um 29% auf $1,19 cdot 10^{-6}$ ($Delta P_e/P_e = 1,5 %$) verringern lassen.

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Quando la probabilità di misurare un particolare valore di una certa quantità varia inversamente come potenza di tale valore, il quantitativo è detto come seguente una power-law, conosciuta anche come legge di Zipf o distribuzione di Pareto. Obiettivo di questa tesi sarà principalmente quello di verificare se il campione esteso di imprese segue la power-law (e se sì, in che limiti). A tale fine si configureranno i dati in un formato di rete monomodale, della quale si studieranno alcune macro-proprietà di struttura a livllo complessivo e con riferimento alle componenti (i singoli subnet distinti) di maggior dimensione. Successivamente si compiranno alcuni approfondimenti sulla struttura fine di alcuni subnet, essenzialmente rivolti ad evidenziare la potenza di unapproccio network-based, anche al fine di rivelare rilevanti proprietà nascoste del sistema economico soggiacente, sempre, ovviamente, nei limiti della modellizzazione adottata. In sintesi, ciò che questo lavoro intende ottenere è lo sviluppo di un approccio alternativo al trattamento dei big data a componente relazionale intrinseca (in questo caso le partecipazioni di capitale), verso la loro conversione in "big knowledge": da un insieme di dati cognitivamente inaccessibili, attraverso la strutturazione dell'informazione in modalità di rete, giungere ad una conoscenza sufficientemente chiara e giustificata.

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The recent advent of Next-generation sequencing technologies has revolutionized the way of analyzing the genome. This innovation allows to get deeper information at a lower cost and in less time, and provides data that are discrete measurements. One of the most important applications with these data is the differential analysis, that is investigating if one gene exhibit a different expression level in correspondence of two (or more) biological conditions (such as disease states, treatments received and so on). As for the statistical analysis, the final aim will be statistical testing and for modeling these data the Negative Binomial distribution is considered the most adequate one especially because it allows for "over dispersion". However, the estimation of the dispersion parameter is a very delicate issue because few information are usually available for estimating it. Many strategies have been proposed, but they often result in procedures based on plug-in estimates, and in this thesis we show that this discrepancy between the estimation and the testing framework can lead to uncontrolled first-type errors. We propose a mixture model that allows each gene to share information with other genes that exhibit similar variability. Afterwards, three consistent statistical tests are developed for differential expression analysis. We show that the proposed method improves the sensitivity of detecting differentially expressed genes with respect to the common procedures, since it is the best one in reaching the nominal value for the first-type error, while keeping elevate power. The method is finally illustrated on prostate cancer RNA-seq data.

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In the last years, the European countries have paid increasing attention to renewable sources and greenhouse emissions. The Council of the European Union and the European Parliament have established ambitious targets for the next years. In this scenario, biomass plays a prominent role since its life cycle produces a zero net carbon dioxide emission. Additionally, biomass can ensure plant operation continuity thanks to its availability and storage ability. Several conventional systems running on biomass are available at the moment. Most of them are performant either in the large-scale or in the small power range. The absence of an efficient system on the small-middle scale inspired this thesis project. The object is an innovative plant based on a wet indirectly fired gas turbine (WIFGT) integrated with an organic Rankine cycle (ORC) unit for combined heat and power production. The WIFGT is a performant system in the small-middle power range; the ORC cycle is capable of giving value to low-temperature heat sources. Their integration is investigated in this thesis with the aim of carrying out a preliminary design of the components. The targeted plant output is around 200 kW in order not to need a wide cultivation area and to avoid biomass shipping. Existing in-house simulation tools are used: They are adapted to this purpose. Firstly the WIFGT + ORC model is built; Zero-dimensional models of heat exchangers, compressor, turbines, furnace, dryer and pump are used. Different fluids are selected but toluene and benzene turn out to be the most suitable. In the indirectly fired gas turbine a pressure ratio around 4 leads to the highest efficiency. From the thermodynamic analysis the system shows an electric efficiency of 38%, outdoing other conventional plants in the same power range. The combined plant is designed to recover thermal energy: Water is used as coolant in the condenser. It is heated from 60°C up to 90°C, ensuring the possibility of space heating. Mono-dimensional models are used to design the heat exchange equipment. Different types of heat exchangers are chosen depending on the working temperature. A finned-plate heat exchanger is selected for the WIFGT heat transfer equipment due to the high temperature, oxidizing and corrosive environment. A once-through boiler with finned tubes is chosen to vaporize the organic fluid in the ORC. A plate heat exchanger is chosen for the condenser and recuperator. A quasi-monodimensional model for single-stage axial turbine is implemented to design both the WIFGT and the ORC turbine. The system simulation after the components design shows an electric efficiency around 34% with a decrease by 10% compared to the zero-dimensional analysis. The work exhibits the system potentiality compared to the existing plants from both technical and economic point of view.

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Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20\% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning.

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My purpose in this essay is to explore how ideas about women and development are created and circulated at the moment of consumption of wares produced at a women's development project in Nepal. I analyze the project as an example of the ways that women's development is an object of material and discursive consumption. Artifacts produced and sold by Nepali women, and purchased by tourists from the "first world," become part of an international exchange of power, money, and meaning. Based on a survey of consumers and ethnographic observations, I conclude that feminist tourists forge relations with disempowered "Others" through the pleasurable activity of an alienated market transaction. Consumers of crafts produced at a women's development project assume a position of empowerment and enlightenment, ready to help out their "women" counterparts through their support of an enterprise with circular logic: within the industry of development (although not necessarily for feminist tourists themselves), at least one of the central projects of development is the development project itself. At the same time, feminist tourists locate themselves outside the oppressive structures and ideologies affecting their "third-world sisters." This is a relation of sympathy and imagined empathy, with no sense of differential location within systems of oppression. They fail to examine or articulate the global link between their own purchasing power and local living conditions of Maithil women; the connection is effectively built out of the discourse.

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Solar energy is the most abundant persistent energy resource. It is also an intermittent one available for only a fraction of each day while the demand for electric power never ceases. To produce a significant amount of power at the utility scale, electricity generated from solar energy must be dispatchable and able to be supplied in response to variations in demand. This requires energy storage that serves to decouple the intermittent solar resource from the load and enables around-the-clock power production from solar energy. Practically, solar energy storage technologies must be efficient as any energy loss results in an increase in the amount of required collection hardware, the largest cost in a solar electric power system. Storing solar energy as heat has been shown to be an efficient, scalable, and relatively low-cost approach to providing dispatchable solar electricity. Concentrating solar power systems that include thermal energy storage (TES) use mirrors to focus sunlight onto a heat exchanger where it is converted to thermal energy that is carried away by a heat transfer fluid and used to drive a conventional thermal power cycle (e.g., steam power plant), or stored for later use. Several approaches to TES have been developed and can generally be categorized as either thermophysical (wherein energy is stored in a hot fluid or solid medium or by causing a phase change that can later be reversed to release heat) or thermochemical (in which energy is stored in chemical bonds requiring two or more reversible chemical reactions).