Climate-related electricity demand-side management in oil-exporting countries—the case of the United Arab Emirates

The oil crisis of the 1970s has increased the concern about the continuity of oil imports flow to major oil-importing developed countries. Numerous policy measures including electricity demand-side management (DSM) programs have been adopted in such countries. These measures aim at reducing the growing need for electricity power that increases the dependency on imported foreign oil and damages the environment. On the other hand, the perception that energy can be obtained at very low cost in oil-rich countries led to less attention being paid to the potential of DSM policies in these countries. This paper discusses such potential using the case of the United Arab Emirates (UAE). Since air conditioning is a major source of electric energy consumption, the relationship between climate conditions and electric energy consumption is considered. An electricity demand model is constructed using time series techniques. The fitted model seems to represent these relationships rather well. Forecasts for electricity consumption using the estimated model indicate that a small reduction in cooling degrees requirement might induce a significant reduction in electric energy demand. Hence, a DSM program is proposed with policy actions to include, among others, measures to reduce cooling degrees requirement.     

Transmission pricing and recovery of investment costs in the deregulated power system based on optimal circuit prices

Transmission pricing has become a major issue in the discussions about the deregulated electricity markets.Consequently,open access to the transmission system is one of the basic topics to allow competition among participants in the energy market.Transmission costs have an important impact on relative competition among participants in the energy market as well as on short-and long-term economic efficiencies of the whole electricity industry,although they represent only close to 10% of the energy market price.This paper deals with the design and tests of a transmission pricing method based on the optimal circuit prices derived from the economically adapted network(EAN).Prices derived from the EAN have the advantage of being in tune with the maximum revenue allowed to the owner of transmission assets and simplifying the optimal allocation of transmission costs among participants.Beginning from the conceptual design,the proposed method is tested on a three-bus network and on the IEEE 24-bus reliability test system.     

A novel Jacob spectral method for multi-dimensional weakly singular nonlinear Volterra integral equations with nonsmooth solutions

The main purpose of this work is to develop a spectrally accurate collocation method for solving weakly singular integral equations of the second kind with nonsmooth solutions in high dimensions. The proposed spectral collocation method is based on a multivariate Jacobi approximation in the frequency space. The essential idea is to adopt a smoothing transformation for the spectral collocation method to circumvent the curse of singularity at the beginning of time. As such, the singularity of the numerical approximation can be tailored to that of the singular solutions. A rigorous convergence analysis is provided and confirmed by numerical tests with nonsmooth solutions in two dimensions. The results in this paper seem to be the first spectral approach with a theoretical justification for high-dimensional nonlinear weakly singular Volterra type equations with nonsmooth solutions.

     

An evolutionary lion optimization algorithm‐based image compression technique for biomedical applications

Recently, medical image compression becomes essential to effectively handle large amounts of medical data for storage and communication purposes. Vector quantization (VQ) is a popular image compression technique, and the commonly used VQ model is Linde–Buzo–Gray (LBG) that constructs a local optimal codebook to compress images. The codebook construction was considered as an optimization problem, and a bioinspired algorithm was employed to solve it. This article proposed a VQ codebook construction approach called the L2‐LBG method utilizing the Lion optimization algorithm (LOA) and Lempel Ziv Markov chain Algorithm (LZMA). Once LOA constructed the codebook, LZMA was applied to compress the index table and further increase the compression performance of the LOA. A set of experimentation has been carried out using the benchmark medical images, and a comparative analysis was conducted with Cuckoo Search‐based LBG (CS‐LBG), Firefly‐based LBG (FF‐LBG) and JPEG2000. The compression efficiency of the presented model was validated in terms of compression ratio (CR), compression factor (CF), bit rate, and peak signal to noise ratio (PSNR). The proposed L2‐LBG method obtained a higher CR of 0.3425375 and PSNR value of 52.62459 compared to CS‐LBG, FA‐LBG, and JPEG2000 methods. The experimental values revealed that the L2‐LBG process yielded effective compression performance with a better‐quality reconstructed image.     

Automatic Channel Detection Using DNN on 2D Seismic Data

Geologists interpret seismic data to understand subsurface properties and subsequently to locate underground hydrocarbon resources. Channels are among the most important geological features interpreters analyze to locate petroleum reservoirs. However, manual channel picking is both time consuming and tedious. Moreover, similar to any other process dependent on human intervention, manual channel picking is error prone and inconsistent. To address these issues, automatic channel detection is both necessary and important for efficient and accurate seismic interpretation. Modern systems make use of real-time image processing techniques for different tasks. Automatic channel detection is a combination of different mathematical methods in digital image processing that can identify streaks within the images called channels that are important to the oil companies. In this paper, we propose an innovative automatic channel detection algorithm based on machine learning techniques. The new algorithm can identify channels in seismic data/images fully automatically and tremendously increases the efficiency and accuracy of the interpretation process. The algorithm uses deep neural network to train the classifier with both the channel and non-channel patches. We provide a field data example to demonstrate the performance of the new algorithm. The training phase gave a maximum accuracy of 84.6% for the classifier and it performed even better in the testing phase, giving a maximum accuracy of 90%.     

X-ray and electron microscopical studies of thin films of (Cd1−xZnx)S solid solution

A series of (Cd_1–x Zn _x )S powders phosphors and thin layers prepared by thermal evaporation of solid solution were studied. The phosphors used were 41% ZnS: 59% CdS with a cobalt concentration from 0 to 0.325%. The analysis of the structure of films of different thicknesses using X-ray diffraction technique confirms that the calculated relative intensities of the planes show considerable differences from the experimental results. For film thicknesses 70 nm thea axis is normal to the substrate, while at greater thicknesses (273 nm) thec axis is practically normal to the substrate. The effect of the electron beam on the solid solution indicates that layers decomposed leaving the grain boundaries decorated by metallic cadmium and zinc particles.     

Pharmacological Evidence on Augmented Antiallodynia Following Systemic Co-Treatment with GlyT-1 and GlyT-2 Inhibitors in Rat Neuropathic Pain Model

The limited effect of current medications on neuropathic pain (NP) has initiated large efforts to develop effective treatments. Animal studies showed that glycine transporter (GlyT) inhibitors are promising analgesics in NP, though concerns regarding adverse effects were raised. We aimed to study NFPS and Org-25543, GlyT-1 and GlyT-2 inhibitors, respectively and their combination in rat mononeuropathic pain evoked by partial sciatic nerve ligation. Cerebrospinal fluid (CSF) glycine content was also determined by capillary electrophoresis. Subcutaneous (s.c.) 4 mg/kg NFPS or Org-25543 showed analgesia following acute administration (30–60 min). Small doses of each compound failed to produce antiallodynia up to 180 min after the acute administration. However, NFPS (1 mg/kg) produced antiallodynia after four days of treatment. Co-treatment with subanalgesic doses of NFPS (1 mg/kg) and Org-25543 (2 mg/kg) produced analgesia at 60 min and thereafter meanwhile increased significantly the CSF glycine content. This combination alleviated NP without affecting motor function. Test compounds failed to activate G-proteins in spinal cord. To the best of our knowledge for the first time we demonstrated augmented analgesia by combining GlyT-1 and 2 inhibitors. Increased CSF glycine content supports involvement of glycinergic system. Combining selective GlyT inhibitors or developing non-selective GlyT inhibitors might have therapeutic value in NP.     

Investigation of transport phenomena in a hybrid ion exchange-electrodialysis system for the removal of copper ions

Hybrid ion exchange electrodialysis processes allow the removal of metal ions from dilute waste liquids and the recovery of more concentrated solutions. The work reported here was aimed at investigating the two steps in the treatment process, namely, adsorption of metal ions onto the packed bed of resin and electromigration (i.e., the transport of these ions in the complex system under the applied electrical field). The case of copper sulfate was investigated. Dowex resins with a cross-linking degree of 2 and 8% were used. The flux of copper through the resin bed and the current efficiency for ion transfer to the cathode compartment were determined as a function of potential gradient and copper ionic fraction in the bed. Apparent diffusion coefficients of Cu²⁺ in the overall system were deduced from the experimental data.