Wellbore Heat Transfer Model for Wax Deposition in Permafrost Region

Producing waxy oil in arctic area may cause wax deposited on the well wall. Since wax deposition is strongly thermal related, accurate heat transfer model is necessary in predicting and preventing wax depostion. A mathematical model was derived based on energy balances for heat exchange between the producing fluids and production string as well as the formation/permafrost. To simplify the calculation, oil and gas were assumed well mixed as one single-phase in the tubing. Furthermore, Singh's model for wax deposition was coupled with the heat transfer model. Wax concentration and effective diameter were updated with time in the temperature calculation. Pressure distribution was calculated over time to check whether the reservoir energy was sufficient to produce the oil during the production process. Besides, a user friendly GUI was developed by VB and MATLAB to run the simulation. The effects of permafrost, thermal insulation, well geometry and wax deposition on the heat transfer calculation were studied. Simulation results illustrated insulating the wellbore and evacuating the production casing annulus effectively reduced the wellbore heat loss. The model can be used in the temperature prediction of an injection well or production well in permafrost region or non-permafrost region

Achieving quantum advantages for image filtering

Image processing is a fascinating field for exploring quantum algorithms. However, achieving quantum speedups turns out to be a significant challenge. In this work, we focus on image filtering to identify a class of images that can achieve a substantial speedup. We show that for images with efficient encoding and a lower bound on the signal-to-noise ratio, a quantum filtering algorithm can be constructed with a polynomial complexity in terms of the qubit number. Our algorithm combines the quantum Fourier transform with the amplitude amplification technique. To demonstrate the advantages of our approach, we apply it to three typical filtering problems. We highlight the importance of efficient encoding by illustrating that for images that cannot be efficiently encoded, the quantum advantage will diminish. Our work provides insights into the types of images that can achieve a substantial quantum speedup.Comment: 8 pages, 9 figure

Adaptive Control of a Class of Switched Nonlinear System with Partial State Constraints Using a Barrier Lyapunov Function

This paper discusses partial state constraint adaptive tracking control problem of switched nonlinear systems with uncertain parameters. In order to ensure boundedness of the outputs and prevent the states from violating the constraints, a barrier Lyapunov function (BLF) is employed. Based on backstepping method, an adaptive controller for the switched system is designed. Furthermore, the state-constrained asymptotic tracking under arbitrary switching is performed. The closed-loop signals keep bounded when the initial states and control parameters are given. Finally, examples and simulation results are reported to illustrate the effectiveness of the proposed controller

Treatment of landfill leachate using magnetically attracted zero-valent iron powder electrode in an electric field

This study combined electro-oxidation (EO) and electrocoagulation (EC) process (EO/EC) to treat landfill leachate by using RuO2-IrO2/Ti plate and microscale zero-valent iron powder composite anode. EO was achieved by direct oxidation and indirect oxidation on RuO2-IrO2/Ti plate, whereas EC was achieved using iron powder to lose electrons and produce coagulants in situ. The influences of variables including type of anode material, applied voltage, zero-valent iron dosage, interelectrode gap, and reaction temperature on EO/EC were evaluated. Results showed that at an applied voltage of 10 V, zero-valent iron dosage of 0.2 g, interelectrode gap of 1 cm, and non-temperature-controlled mode, the removal efficiencies were 72.5% for total organic carbon (TOC), 98.5% for ammonia, and 98.6% for total phosphorus (TP). Some heavy metals and hardness were also removed. Further analysis indicated that the removal of TOC, ammonia, and TP followed pseudo-first order, pseudo-zero order, and pseudo-second order kinetic models, respectively. Other characteristics were examined by scanning electron microscopy–energy dispersive spectrometry, X-ray diffraction, and X-ray photoelectron spectroscopy. Overall, our results showed that EO/EC can be used to efficiently remove organic matter, ammonia, TP, and heavy metals from landfill leachate

Carbon Monitor Cities, near-real-time daily estimates of CO2 emissions from 1500 cities worldwide

Building on near-real-time and spatially explicit estimates of daily carbon dioxide (CO2) emissions, here we present and analyze a new city-level dataset of fossil fuel and cement emissions. Carbon Monitor Cities provides daily, city-level estimates of emissions from January 2019 through December 2021 for 1500 cities in 46 countries, and disaggregates five sectors: power generation, residential (buildings), industry, ground transportation, and aviation. The goal of this dataset is to improve the timeliness and temporal resolution of city-level emission inventories and includes estimates for both functional urban areas and city administrative areas that are consistent with global and regional totals. Comparisons with other datasets (i.e. CEADs, MEIC, Vulcan, and CDP) were performed, and we estimate the overall uncertainty to be 21.7%. Carbon Monitor Cities is a near-real-time, city-level emission dataset that includes cities around the world, including the first estimates for many cities in low-income countries

miR-486-3p Influences the Neurotoxicity of a-Synuclein by Targeting the SIRT2 Gene and the Polymorphisms at Target Sites Contributing to Parkinson’s Disease

Background/Aims: Increasing evidence suggests the important role of sirtuin 2 (SIRT2) in the pathology of Parkinson’s disease (PD). However, the association between potential functional polymorphisms in the SIRT2 gene and PD still needs to be identified. Exploring the molecular mechanism underlying this potential association could also provide novel insights into the pathogenesis of this disorder. Methods: Bioinformatics analysis and screening were first performed to find potential microRNAs (miRNAs) that could target the SIRT2 gene, and molecular biology experiments were carried out to further identify the regulation between miRNA and SIRT2 and characterize the pivotal role of miRNA in PD models. Moreover, a clinical case-control study was performed with 304 PD patients and 312 healthy controls from the Chinese Han population to identify the possible association of single nucleotide polymorphisms (SNPs) within the miRNA binding sites of SIRT2 with the risk of PD. Results: Here, we demonstrate that miR-486-3p binds to the 3’ UTR of SIRT2 and influences the translation of SIRT2. MiR-486-3p mimics can decrease the level of SIRT2 and reduce a-synuclein (α-syn)-induced aggregation and toxicity, which may contribute to the progression of PD. Interestingly, we find that a SNP, rs2241703, may disrupt miR-486-3p binding sites in the 3’ UTR of SIRT2, subsequently influencing the translation of SIRT2. Through the clinical case-control study, we further verify that rs2241703 is associated with PD risk in the Chinese Han population. Conclusion: The present study confirms that the rs2241703 polymorphism in the SIRT2 gene is associated with PD in the Chinese Han population, provides the potential mechanism of the susceptibility locus in determining PD risk and reveals a potential target of miRNA for the treatment and prevention of PD