71 research outputs found

    Analysis of Wastewater Membrane Pollutants in Joint Station and Research on Biological Control Technology

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    In view of the serious membrane pollution and short stable operation period of the existing heavy oil wastewater treatment process in a combined station of an oil field, the organic pollution is determined to be the main cause of the membrane pollution on the basis of the analysis of the wastewater quality and membrane pollutants. In view of the characteristic pollutants in heavy oil wastewater, the efficient degrading bacteria were screened by restrictive culture technology, and the strains were identified as Pseudomonas and Bacillus. The effects of environmental conditions on the growth of bacteria and the degradation of heavy oil by bacteria were investigated. In the existing process, biological treatment unit was added, simulation process was established, and long-term operation experiment was carried out. The results show that after biological treatment, the oil content of wastewater is less than 1 mg/L, COD is less than 100 mg/L, suspended matter is less than 1 mg/L, and the median particle size is 0.92 um, which is better than the first kind of water injection index (SY/T 5329-2012). Biological treatment effectively degraded organic pollutants in heavy oil wastewater and delayed membrane fouling. The loss rate of membrane flux was less than 15%. The microscopic morphology of membrane surface also showed that membrane fouling was effectively suppressed

    Net Phosphorus Requirements of Dorper×Thin-tailed Han Crossbred Ram Lambs

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    A comparative slaughter trial was conducted to estimate the phosphorus (P) requirement for maintenance and growth of crossbred lambs of Dorper with a Chinese indigenous sheep breed, thin-tailed Han sheep. Thirty-five Dorper×thin-tailed Han crossbred, noncastrated ram lambs (20.3±0.22 kg of shrunk body weight (SBW)) were used. Seven lambs were randomly chosen and slaughtered at 20 kg SBW as the baseline group for measuring initial body composition. Another seven lambs were also randomly chosen and offered a pelleted mixed diet for ad libitum intake and slaughtered at 28 kg SBW. The remaining 21 sheep were randomly divided into 3 groups with 7 sheep each and subject to the same diet of either 70 or 40% of ad libitum intake. The 3 groups were slaughtered when the sheep fed ad libitum reached 35 kg of SBW. Body P contents were determined after slaughter. The results showed that the net P requirement for maintenance was 30.0 mg/kg of empty body weight (EBW) or 23.4 mg/kg body weight (BW), and the P requirement for growth decreased from 5.3 to 5.0 g/kg of EBW gain as the lamb grew from 20 to 35 kg. The net P requirement for growth of Dorper×thin-tailed Han crossbred ram lambs was lower than that of sheep adopted by the American nutritional system

    The traceability of sudden water pollution in river canals based on the pollutant diffusion quantification formula

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    For the problem that the traceability parameters of sudden water pollution are difficult to determine, a fast traceability model based on a simplified mechanistic model coupled with an optimization algorithm is proposed to improve the accuracy of sudden water pollution traceability. In this paper, according to the diffusion law of pollutants, a quantitative formula of pollutant diffusion is proposed, and the differential calculation process of the pollutant convection equation is optimized. The Dynamic Programming and Beetle Antennae Search algorithm (DP-BAS) with dynamic step size is used in the reverse optimization process, which can avoid the problem of entering the local optimal solution in the calculation process. The DP-BAS is used to inverse solve the quantization equation to realize the decoupling of pollutant traceability parameters, transforming the multi-parameter coupled solution into a single-parameter solution, reducing the solution dimension, and optimizing the difficulty and solution complexity of pollutant traceability. The proposed traceability model is applied to the simulation case, the results show that the mean square errors of pollutant placement mass, location, and time are 2.39, 1.16, and 1.19 percent, respectively. To further verify the model reliability, the Differential Evolution and Markov Chain Monte Carlo simulation method (DE-MCMC) as well as Genetic Algorithms (GA) were introduced to compare with the proposed model to prove that the model has certain reliability and accuracy

    RPU: The Ring Processing Unit

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    Ring-Learning-with-Errors (RLWE) has emerged as the foundation of many important techniques for improving security and privacy, including homomorphic encryption and post-quantum cryptography. While promising, these techniques have received limited use due to their extreme overheads of running on general-purpose machines. In this paper, we present a novel vector Instruction Set Architecture (ISA) and microarchitecture for accelerating the ring-based computations of RLWE. The ISA, named B512, is developed to meet the needs of ring processing workloads while balancing high-performance and general-purpose programming support. Having an ISA rather than fixed hardware facilitates continued software improvement post-fabrication and the ability to support the evolving workloads. We then propose the ring processing unit (RPU), a high-performance, modular implementation of B512. The RPU has native large word modular arithmetic support, capabilities for very wide parallel processing, and a large capacity high-bandwidth scratchpad to meet the needs of ring processing. We address the challenges of programming the RPU using a newly developed SPIRAL backend. A configurable simulator is built to characterize design tradeoffs and quantify performance. The best performing design was implemented in RTL and used to validate simulator performance. In addition to our characterization, we show that a RPU using 20.5mm2 of GF 12nm can provide a speedup of 1485x over a CPU running a 64k, 128-bit NTT, a core RLWE workloa

    TREBUCHET: Fully Homomorphic Encryption Accelerator for Deep Computation

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    Secure computation is of critical importance to not only the DoD, but across financial institutions, healthcare, and anywhere personally identifiable information (PII) is accessed. Traditional security techniques require data to be decrypted before performing any computation. When processed on untrusted systems the decrypted data is vulnerable to attacks to extract the sensitive information. To address these vulnerabilities Fully Homomorphic Encryption (FHE) keeps the data encrypted during computation and secures the results, even in these untrusted environments. However, FHE requires a significant amount of computation to perform equivalent unencrypted operations. To be useful, FHE must significantly close the computation gap (within 10x) to make encrypted processing practical. To accomplish this ambitious goal the TREBUCHET project is leading research and development in FHE processing hardware to accelerate deep computations on encrypted data, as part of the DARPA MTO Data Privacy for Virtual Environments (DPRIVE) program. We accelerate the major secure standardized FHE schemes (BGV, BFV, CKKS, FHEW, etc.) at >=128-bit security while integrating with the open-source PALISADE and OpenFHE libraries currently used in the DoD and in industry. We utilize a novel tile-based chip design with highly parallel ALUs optimized for vectorized 128b modulo arithmetic. The TREBUCHET coprocessor design provides a highly modular, flexible, and extensible FHE accelerator for easy reconfiguration, deployment, integration and application on other hardware form factors, such as System-on-Chip or alternate chip area
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