Over the past decade or so, the wealth produced by Qatar's oil and gas exports has generated a construction development boom in its capital city of Doha and the surrounding vicinity. Since the late ...1990s, the number of inhabitants has grown from less than 400,000 to more than 1.7 million today. In many respects, Doha is portrayed as an important emerging global capital in the Gulf region, which has been positioning and re-inventing itself on the map of international architecture and urbanism, with a global image of building clusters of glass office towers, as well as cultural and educational facilities. While focusing on the architectural and planning aspects of Doha's intensive urbanization, this first comprehensive examination of the city sets this within the socio-political and economic context of the wider Arabian Peninsula. 'Demystifying Doha - On Architecture and Urbanism in an Emerging City' features a comprehensive discussion on contemporary architecture and urbanism of Doha as an emerging regional metropolis. It provides a critical analysis of the evolution of architecture and urbanism as products of the contemporary global condition. Issues that pertain to emerging service hubs, decentralised urban governance, integrated urban development strategies, image-making practices, urban identity, the dialectic relations between the city and its society and sustainable urbanism are all examined to elucidate the urban evolution and the contemporary condition of Doha. 'Demystifying Doha - On Architecture and Urbanism in an Emerging City' concludes by suggesting a framework for future studies of the city as well as for investigating the future of similar cities, setting out an agenda for sustainable urban growth, while invigorating the multiple roles urban planners and architects can play in shaping this future.
Photovoltaic (PV) systems are presently allowed to inject into the grid all the power they can generate. However, in the near future, utilities are expected to impose additional regulations and ...restrictions on the power being injected by large centralized PV systems because of their possible adverse impacts. One of the main issues associated with large PV systems is the fluctuation of their output power. These fluctuations can negatively impact the performance of the electric networks to which these systems are connected, especially if the penetration levels of these systems are high. Moreover, the fluctuations in the power of PV systems make it difficult to predict their output, and thus, to consider them when scheduling the generating units in the network. The main objective of this paper is to investigate some methods that can be used to reduce the fluctuations in the power generated from a large customer-owned PV system, in the order of megawatts. This paper focuses on three methods: 1) the use of battery storage systems; 2) the use of dump loads; and 3) curtailment of the generated power by operating the power-conditioning unit of the PV system below the maximum power point. The emphasis in the analysis presented in this paper is on investigating the impacts of implementing these methods on the economical benefits that the PV system owner gains. To estimate the maximum revenues gained by the system owner, an linear programming optimization problem is formulated and solved. Moreover, the effect of varying different parameters of the problem is investigated through sensitivity analysis.
It is widely accepted that renewable energy sources are the key to a sustainable energy supply infrastructure since they are both inexhaustible and nonpolluting. A number of renewable energy ...technologies are now commercially available, the most notable being wind power, photovoltaic, solar thermal systems, biomass, and various forms of hydraulic power. In this paper, a methodology has been proposed for optimally allocating different types of renewable distributed generation (DG) units in the distribution system so as to minimize annual energy loss. The methodology is based on generating a probabilistic generation-load model that combines all possible operating conditions of the renewable DG units with their probabilities, hence accommodating this model in a deterministic planning problem. The planning problem is formulated as mixed integer nonlinear programming (MINLP), with an objective function for minimizing the system's annual energy losses. The constraints include the voltage limits, the feeders' capacity, the maximum penetration limit, and the discrete size of the available DG units. This proposed technique has been applied to a typical rural distribution system with different scenarios, including all possible combinations of the renewable DG units. The results show that a significant reduction in annual energy losses is achieved for all the proposed scenarios.
Keen interest in the development and utilization of renewable distributed generation (DG) has been currently observed worldwide. The reliability impact of this highly variable energy source is an ...important aspect that needs to be assessed as renewable power penetration becomes increasingly significant. Distribution system adequacy assessment including wind-based and solar DG units during different modes of operation is described in this paper. Monte Carlo simulation (MCS) and analytical technique are used in this work with a novel utilization of the clearness index probability density function (pdf) to model the solar irradiance using MCS. The results show that there is no significant difference between the outcomes of the two proposed techniques; however, MCS requires much longer computational time. The effect of islanding appears in the improvement of the loss of load expectation (LOLE) and loss of energy expectation (LOEE).
Sharpness is an important determinant in visual assessment of image quality. The human visual system is able to effortlessly detect blur and evaluate sharpness of visual images, but the underlying ...mechanism is not fully understood. Existing blur/sharpness evaluation algorithms are mostly based on edge width, local gradient, or energy reduction of global/local high frequency content. Here we understand the subject from a different perspective, where sharpness is identified as strong local phase coherence (LPC) near distinctive image features evaluated in the complex wavelet transform domain. Previous LPC computation is restricted to be applied to complex coefficients spread in three consecutive dyadic scales in the scale-space. Here we propose a flexible framework that allows for LPC computation in arbitrary fractional scales. We then develop a new sharpness assessment algorithm without referencing the original image. We use four subject-rated publicly available image databases to test the proposed algorithm, which demonstrates competitive performance when compared with state-of-the-art algorithms.
Sandia frequency shift (SFS) falls under the active islanding detection methods that rely on frequency drift to detect an islanding condition for inverter-based distributed generation. Active ...islanding detection methods are commonly tested on constant RLC loads where the load's active power is directly proportional to the square of voltage and is independent on the system frequency. Since the SFS method relies primarily on frequency to detect islanding, the load's active power frequency dependence could have an impact on its performance and the nondetection zone (NDZ). In this paper, the impact of the load's active power frequency dependence on the performance of the SFS method, during an islanding condition, is analyzed. A NDZ model that takes into account the load's frequency dependence parameter is derived mathematically and validated through digital simulation. The results show that the load's frequency dependence has a significant impact on the NDZ of the SFS method and thus is an important factor to consider when designing and testing this method.
Between 2016 and 2018, the Agriculture Research Center's Sakha Agriculture Research Station conducted two rounds of pedigree selection on a segregating population of cotton (Gossypium barbadense L.) ...using the F
, F
, and F
generations resulting from crossing Giza 94 and Suvin. In 2016, the top 5% of plants from the F
population were selected based on specific criteria. The superior families from the F
generation were then selected to produce the F
families in 2017, which were grown in the 2018 summer season in single plant progeny rows and bulk experiments with a randomized complete block design of three replications. Over time, most traits showed increased mean values in the population, with the F
generation having higher Genotypic Coefficient of Variance (GCV) and Phenotypic Coefficient of Variance (PCV) values compared to the succeeding generations for the studied traits. The magnitude of GCV and PCV in the F
and F
generations was similar, indicating that genotype had played a greater role than the environment. Moreover, the mean values of heritability in the broad sense increased from generation to generation. Selection criteria I2, I4, and I5 were effective in improving most of the yield and its component traits, while selection criterion I1 was efficient in improving earliness traits. Most of the yield and its component traits showed a positive and significant correlation with each other, highlighting their importance in cotton yield. This suggests that selecting to improveone or more of these traits would improve the others. Families number 9, 13, 19, 20, and 21 were the best genotypes for relevant yield characters, surpassing the better parent, check variety, and giving the best values for most characters. Therefore, the breeder could continue to use these families in further generations as breeding genotypes to develop varieties with high yields and its components.
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The present study aimed to explore the potential ameliorative effect of apigenin (APG) against diabetes-associated genitourinary complications in rats. A diabetic rat model was induced by the ...intraperitoneal injection of streptozotocin (STZ). All experimental animals were treated with vehicle or vehicle plus APG at a dose of 0.78 mg/kg/day for 10 days, either once diabetes was confirmed or at the end of the 3rd week after confirmation of diabetes. Rats were sacrificed at the end of the fifth week. In addition to the histological assessment, an analysis of kidney function tests and serum testosterone was performed to assess diabetic genitourinary complications. Gene expression of the mitochondrial fission protein, dynamin related protein 1 (Drp1), was measured in renal and testicular tissues using qRT PCR. APG can increase body weight, reduce blood glucose levels, and improve renal and testicular functions in diabetic rats. APG decreased Drp1 overexpression in diabetic animals' kidneys and testes. In summary, our current work discloses that APG attenuates diabetic genitourinary lesions in rats via suppressing Drp1 overexpression.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
The recent deployment of distributed generation has led to a revolution in the use of distribution systems and the emergence of "smart grid" concepts. Smart grids are intended primarily as a means of ...facilitating the integration of renewable energy sources and of achieving greater system reliability and efficiency. Energy storage systems (ESSs) offer a number of benefits that can help utilities move toward those goals. One of those benefits is the capacity to improve the utilization of network infrastructure by means of proper load management. This paper proposes a methodology for allocating ESSs in distribution systems in order to defer system upgrades, minimize system losses, and take advantage of the arbitrage benefit. The cost and arbitrage benefit of energy storage installation are optimized with respect to system upgrade and energy losses costs. The primary goal of this research is to determine the optimal size and location of storage units to be installed, in addition to their optimal operation, so that total system costs are minimized, while system benefits are maximized. In this paper, a probabilistic load model is adopted instead of utilizing time-series based models, which provide an optimal solution that is valid only for the time-series pattern that is applied.
Microgrid planning philosophies are changing from islanding in the case of abnormal conditions to independent sustainability for constant secure, reliable operation. Large independent operators ...foresee a shift from gigantic-grid bulk generation and transmission to distributed generation (DG) from smaller, interlinked grid clusters. Customers and the community will benefit, but system operators and utilities will face challenges. Introduced to enhance electricity exchange and the energy market structure in such grids, transactive energy networks favor customers and DG owners, establish a utility business model, and enable power system innovation. Planners are also increasingly interested in blockchains for secure transactions. Blockchain-based transactive energy markets promise flexibility, transparency, security, competition, and superlative low-cost reliability, offering ideal energy-trading solutions in isolated microgrids and distribution-level markets. This article presents the development and case-study validation of a comprehensive transactive energy market framework with linked blockchain and power system layers, a novel market structure based on an end-user marginal price, and an adapted blockchain that fits intrinsic power system requirements. A new slot-ahead electricity market model is established through integration with the modified blockchain. With blockchain operation, monetary funds are managed equitably so that wallet billing rates for customers, utilities, and DG owners match broadcast smart-meter data.
