mlsa-iai-msu-lab/ru_sci_bench_zho_cite_reranking huggingface dataset:
Efficient electro-magnetic analysis of a GPU bitsliced AES implementation

The advent of CUDA-enabled GPU makes it possible to provide cloud applications with high-performance data security services. Unfortunately, recent studies have shown that GPU-based applications are also susceptible to side-channel attacks. These published work studied the side-channel vulnerabilities of GPU-based AES implementations by taking the advantage of the cache sharing among multiple threads or high parallelism of GPUs. Therefore, for GPU-based bitsliced cryptographic implementations, which are immune to the cache-based attacks referred to above, only a power analysis method based on the high-parallelism of GPUs may be effective. However, the leakage model used in the power analysis is not efficient at all in practice. In light of this, we investigate electro-magnetic (EM) side-channel vulnerabilities of a GPU-based bitsliced AES implementation from the perspective of bit-level parallelism and thread-level parallelism in order to make the best of the localization effect of EM leakage with parallelism. Specifically, we propose efficient multi-bit and multi-thread combinational analysis techniques based on the intrinsic properties of bitsliced ciphers and the effect of multi-thread parallelism of GPUs, respectively. The experimental result shows that the proposed combinational analysis methods perform better than non-combinational and intuitive ones. Our research suggests that multi-thread leakages can be used to improve attacks if the multi-thread leakages are not synchronous in the time domain.
Vector Control Strategy of a T-type Three-level Converter Driving a Switched Reluctance Motor

A novel 12 voltage vector control strategy for switched reluctance motors (SRM) with a T-type three-level converter is proposed in this study. Based on a causal analysis of torque ripple under the control of conventional six voltage vectors, six new voltage vectors are added for further reduction of torque ripple. An optimized control rule is adopted based on the division method of the 12 new voltage vectors. A zero-voltage vector is used to adjust the duration of the 12 voltage vectors, the time of which is varied at different parts of the vector sectors according to the torque error. In addition, the windings are connected in a delta configuration, therefore, the number of connections between the converter and SRM is reduced. Finally, the results of MATLAB/Simulink and RT-LAB are presented to verify the validity of the proposed scheme.
A Missing Power Data Filling Method Based on Improved Random Forest Algorithm

Missing data filling is a key step in power big data preprocessing, which helps to improve the quality and the utilization of electric power data. Due to the limitations of the traditional methods of filling missing data, an improved random forest filling algorithm is proposed. As a result of the horizontal and vertical directions of the electric power data are based on the characteristics of time series. Therefore, the method of improved random forest filling missing data combines the methods of linear interpolation, matrix combination and matrix transposition to solve the problem of filling large amount of electric power missing data. The filling results show that the improved random forest filling algorithm is applicable to filling electric power data in various missing forms. What's more, the accuracy of the filling results is high and the stability of the model is strong, which is beneficial in improving the quality of electric power data.
Development of a Self-Recording Per-Minute Precipitation Dataset for China

The establishment of self-recording precipitation observation systems in China began in 1951, and strips of self-recording precipitation graph paper have been archived since then. More than 9 million sheets of self-recording graph paper from 2253 stations in 31 provinces have been digitized by using image scanning and curve extraction technology. Format specification and quality control have been applied to the digitized data, and the China Surface Self-Recording Per-Minute Precipitation Dataset (V1.0) has been developed. The integrity and accuracy of this dataset are evaluated. This is the first attempt in China to establish a per-minute precipitation dataset that covers the period from 1951 to present. Preliminary evaluation reveals that the station density is high and the data continuity is good in most areas of China. However, the integrity of stations in some areas of western China is relatively poor. The availability rate and accuracy rate in summer are higher than 99% at most stations, with the overall availability and accuracy rates reaching as much as 99.42% and 99.22%, respectively.
Homogenization of Surface Pressure Data in Tianjin, China

Based on a hydrostatic check, a preliminary quality control procedure was applied to the hourly surface air pressure (SAP) and sea level pressure (SLP) data from 13 surface observation stations in Tianjin, China. The daily and monthly series of the two pressures were tested for homogeneity with the RHtestsV5 software package and corrected by using the surface air temperature data as a reference. The results showed that 5 and 3 of the 13 stations had significant breakpoints in their SAP and SLP data, respectively, mainly caused by station relocation. Quantile matching adjustments showed that both pressures were dominated by positive deviation corrections and adjustments, with probability densities > 0.2 concentrated in the ranges 0.02 to 1.80 and –0.02 to 1.64 hPa. Comparison of the variances and trends of the two pressures before and after adjustment showed that homogeneity correction can greatly reduce the influence of abnormal discrete pressure data and make the long-term trends of the series more reasonable. Taking Baodi station (54525), which has the most significant correction results, as an example, the trend amplitude of the adjusted SAP and SLP was increased by 0.316 and 0.294 hPa (10 yr)–1 (95% confidence level), respectively, clearly weakening the sudden reduction induced in the two pressure series by the relocation of this station. Comparison with similar products showed that the adjusted data were better than those from the China Meteorological Administration. Therefore, the reliability of the surface pressure data and the processing techniques have been improved.
In polytocous mammals, weakling neonates, but not their stronger littermates, benefit from specialized foraging

Adjusting foraging strategies is a common phenomenon within groups of animals competing for the same resource. In polytocous mammals, neonates concurrently compete for limited milk and alternate between two foraging (suckling) strategies: adaptable exploratory foraging with random sampling of teats, and ordered foraging with a tendency towards exploiting a particular suckling position. Some theoretical (game theory) models have shown that weaker siblings in particular benefit from foraging specialization (suckling order). Neonate piglets establish a well-defined suckling order that develops gradually and fluctuates throughout the lactation period, implying the existence of inter-individual differences in foraging strategies. We therefore analyzed suckling behavior in pigs to determine whether one foraging strategy was more beneficial to neonates in terms of their body weight and foraging environment. We found that intermediate and heavy littermates tended to adjust their suckling strategy according to the foraging environment; however, the selected foraging strategy did not affect their overall growth performance. Lighter individuals that consumed significantly less milk did not greatly alternate their foraging strategy according to the foraging environment, but their growth rate was significantly higher whenever they performed less-exploratory foraging behavior. Although suckling order appeared to be a relatively stable behavioral phenotype, it was beneficial exclusively for weaklings. These results confirm theoretical predictions and indicate that specializing in a suckling position is a beneficial strategy for weaker, light neonates. These findings suggest that physically weaker neonates might have driven the evolution of neonatal foraging specialization.
A model for transient diffusion in bidisperse pore structures

A bidisperse model for transient diffusion and adsorption processes in porous materials is presented in this paper. The mathematical model is solved by numerical methods based on finite elements combined with the linear driving force approximation. A criterion based on the model to identify the diffusion controlling mechanism (macropore diffusion, micropore diffusion, or both) is proposed. The effects of different adsorption isotherms (linear, Freundlich, or Langmuir) on the concentration profiles and on curves of fractional uptake versus time are investigated. In addition, the influences of model parameters concerning the pore networks on the fractional uptake are studied as well.
Effect of overburden pressure on determination of reservoir rock types using RQI/FZI, FZI* and Winland methods in carbonate rocks

Rock typing is an important tool in evaluation and performance prediction of reservoirs. Different techniques such as flow zone indicator (FZI), FZI* and Winland methods are used to categorize reservoir rocks into distinct rock types. Generally, these methods are applied to petrophysical data that are measured at a pressure other than reservoir pressure. Since the pressure changes the pore structure of rock, the effect of overburden pressure on rock typing should be considered. In this study, porosity and permeability of 113 core samples were measured at five different pressures. To investigate the effect of pressure on determination of rock types, FZI, FZI* and Winland methods were applied. Results indicated that although most of the samples remain in the same rock type when pressure changes, some of them show different trends. These are related to the mineralogy and changes in pore system of the samples due to pressure change. Additionally, the number of rock types increases with increasing pressure. Furthermore, the effect of overburden pressure on determination of rock types is more clearly observed in the Winland and FZI* methods. Also, results revealed that a more precise reservoir dynamic simulation can be obtained by considering the reservoir rock typing process at reservoir conditions.
Integrated asset management: a case study of technical and economic optimization of surface and well facilities

Oil production could be increased by using optimization techniques in each stage of oil production system from field to production unit. However, the maximum profit will be obtained once integrated optimization of surface and subsurface components of the oil production system is implemented. In addition, when using high-tech equipment and facilities, an integrated study of well and surface facilities aff ects the economic benefits significantly. In this work, one of the Iranian brown fields (mature or declining production fields) was studied to find the best renovation plan with maximum profits. The base scenario was designed with four stages of separation, and the high-pressure gases from the first and the second separator were planned to be sold, while the low-pressure gases from subsequent stages were supposed to be flared. In this paper, two additional scenarios, namely separator optimization and full optimization, were proposed and 12 cases were defined. In the full optimization scenario, low-pressure gases were prevented from being flared. It was observed that by stopping the flaring systems, gas production rate increases as high as 20% and 150 to 200 MW power will be generated in all cases during the next 20 years. Finally, economic evaluation for all of the cases was done and diff erent cases were compared in terms of incremental annual worth and payback period.
Sweet spot prediction in tight sandstone reservoir based on well-bore rock physical simulation

To establish the relationship among reservoir characteristics and rock physical parameters, we construct the well-bore rock physical models firstly,considering the influence factors, such as mineral composition, shale content, porosity, fluid type and saturation. Then with analyzing the change rules of elastic parameters along with the above influence factors and the cross-plots among elastic parameters, the sensitive elastic parameters of tight sandstone reservoir are determined, and the rock physics template of sweet spot is constructed to guide pre-stack seismic inversion. The results show that velocity ratio and Poisson impedance are the most sensitive elastic parameters to indicate the lithologic and gas-bearing properties of sweet spot in tight sandstone reservoir. The high-quality sweet spot is characterized by the lower velocity ratio and Poisson impedance. Finally, the actual seismic data are selected to predict the sweet spots in tight sandstone gas reservoirs, so as to verify the validity of the rock physical simulation results. The significant consistency between the relative logging curves and inversion results in different wells implies that the utilization of well-bore rock physical simulation can guide the prediction of sweet spot in tight sandstone gas reservoirs.
Eff ect of graphene functionalizing on the performance of NiMo/ graphene in HDS and HDN reactions

In this research, to remove sulfur and nitrogen compounds from heavy naphtha, various nanocatalysts were prepared through supporting NiMo over nanoporous graphene and evaluated in hydrodesulfurization and hydrodenitrogenation reactions. The nanoporous graphene was initially functionalized in order to facilitate the metal being loaded on it. Three diff erent methods were used to functionalize the nanoporous graphene. The NiMo/nanoporous graphene nanocatalysts were characterized by field emission scanning electron microscopy, Fourier transform infrared spectroscopy, X-ray diff raction, inductively coupled plasma optical emission spectrometry, temperature-programmed reduction, nitrogen adsorption–desorption isotherms and transmission electron microscopy techniques. Catalyst performance was evaluated in terms of conversions of sulfur, mercaptans (R-SH) and nitrogen compounds. It was found that the functionalized nanoporous graphene support could significantly enhance the catalytic performance in comparison with the industrial NiMo/alumina catalyst. Among the functionalized graphene supports, amine-functionalized graphene exhibited the best results. By using NiMo supported over amine-functionalized graphene, the conversions of total sulfur and R-SH reached 97.8% and 98.1%, respectively.
Detection performance and inversion processing of logging-while-drilling extra-deep azimuthal resistivity measurements

We present systematic investigations on the physics, detection performance and inversion of logging-while-drilling extradeep azimuthal resistivity measurements (EDARM). First, the definitions of EDRAM measurements are discussed, followed by the derivation of the attenuation and phase-shift geometrical factors to illustrate the relative contributions of formation units to the observed signals. Then, a new definition of detection depth, which considers the uncertainty of inversion results caused by the data noise, is proposed to quantify the detection capability of EDARM. Finally, the Bayesian theory associated with Markov chain Monte Carlo sampling is introduced for fast processing of EDARM data. Numerical results show that EDARM is capable of detecting the azimuth and distance of remote bed boundaries, and the detection capability increases with increasing spacing and resistivity contrast. The EDARM tool can accommodate a large range of formation resistivity and is able to provide the resistivity anisotropy at arbitrary relative dipping angles. In addition, multiple bed boundaries and reservoir images near the borehole are readily obtained by using the Bayesian inversion.
Performance evaluation of laponite as a mud-making material for drilling fluids

In this study,laponite was tested as a mud-making material for drilling fluids.Laponite is a synthetic smectite clay with a structure and composition closely resembling the natural clay mineral hectorite.Commercially available laponite was characterized by X-ray diffractometry,scanning electron microscopy and infrared spectrometry.Its dispersibility,salt resistance and high-temperature resistance were evaluated.The results showed that laponite possessed superior cation exchange capacity(140.4 mmol/100 g)with interlayer cations of Na~+ and Li~+.Laponite could easily be dispersed in water to yield increased viscosity with no influence from hydration time or temperature.On the other hand,laponite dispersions displayed an excellent heat resistance,with invariant apparent viscosity at high temperatures.For instance,the apparent viscosity of the 2 wt% laponite dispersion underwent changes between 22 and 24 mPa s after hot rolling at 180–240 °C for 16 h.Compared to existing mud-making materials,laponite exhibited better mud-making properties.Furthermore,laponite revealed good compatibility with other additives,and the water-based drilling fluids prepared with laponite as mud-making material showed an excellent stability at elevated temperatures and superior performance–cost ratios.Overall,these findings indicated that laponite had an excellent dispersibility at high temperatures and hence would have promising applications as high-temperature mud-making material for preparing water-based drilling fluids designed for ultra-high-temperature environments.
State of the art of synthetic threshold scale inhibitors for mineral scaling in the petroleum industry:a review

Inorganic scale deposits are a major water-related problem encountered in producing oil and gas wells.The harshness of scale deposits is dependent on the field operating conditions.Scale deposits can vary from mild scaling tendencies to extreme.In general,the scale deposit will cause a reduction in formation pores,declining productivity and eventually blockage of the wellbore and hence unexpected downtime if it is allowed to persevere.To overcome this,the productivity of an oil and gas well is ensured by handling scale deposits via removal or prevention methods.Scale prevention is the best and cost-effective method for handling scale deposits that ensures production continuity.Inhibition through “threshold” scale inhibitor treatment is the most common method that is proven to prevent or reduce likely deposits.This paper examines the art of synthetic scale inhibitors,in particular,threshold scale inhibitors in oil and gas production.It discusses the chemistry of those inhibitors,inhibition mechanisms,treatment methods and key properties for their applications.It also highlights the chemistry of the synthetic routes often used to produce them in the laboratory and/or industry.Finally,it highlights the environmental concerns for the applicability of threshold scale inhibitors.
Gclust:A Parallel Clustering Tool for Microbial Genomic Data

The accelerating growth of the public microbial genomic data imposes substantial burden on the research community that uses such resources.Building databases for non-redundant reference sequences from massive microbial genomic data based on clustering analysis is essential.However,existing clustering algorithms perform poorly on long genomic sequences.In this article,we present Gclust,a parallel program for clustering complete or draft genomic sequences,where clustering is accelerated with a novel parallelization strategy and a fast sequence comparison algorithm using sparse suffix arrays(SSAs).Moreover,genome identity measures between two sequences are calculated based on their maximal exact matches(MEMs).In this paper,we demonstrate the high speed and clustering quality of Gclust by examining four genome sequence datasets.Gclust is freely available for non-commercial use at https://github.com/niu-lab/gclust.We also introduce a web server for clustering user-uploaded genomes at http://niulab.scgrid.cn/gclust.
Parameters and performance analysis of quantum wireless sensor network for monitoring the activities of tibetan antelope in Hoh Xil

Hoh Xil is the national nature reserve in China,and Tibetan antelope is a research hotspot of wildlife protection in this area.In order to track the population and activity of Tibetan antelope in Hoh Xil,a quantum wireless sensor monitoring network(QWSMN)based on the quantum satellite wide-area communication networks was proposed.This network consists of quantum wireless sensors installed on the Tibetan antelope,small quantum base stations,quantum satellite signal transmitting stations,quantum satellite and quantum satellite signal receiving stations.The simulation results show that under the interference of the sandstorm,a quantum satellite signal transmitting station can cover the monitoring area of 20 106 km~2,and the network throughput reaches 40 KB/s.This network can realize large-scale monitoring of Tibetan antelope in Hoh Xil and provide theoretical basis for the construction of global wildlife monitoring network.
Fuzzy comprehensive assessment of running condition for a large-scale centrifugal compressor set

A fuzzy comprehensive assessment method of running condition was constructed and applied to a large-scale centrifugal compressor set in a petrochemical corporation aiming at the monitoring and early warning of abnormal conditions in industry.The maximal information coefficient(MIC)correlation analysis of indexes was introduced to determine the independent indexes to be assessed,and the dynamic deterioration degree was calculated using the predicted independent indexes by the second-order Markov chain model.The fuzzy membership degreeweightingmethodwasemployed to assess the running condition of all units in the set.Simple and direct radar chart was used to visualize condition assessment grades.Results showed that the proposed fuzzy comprehensive assessment method successfully assessed the running condition of the set.The constructed method achieved 10 min earlier alarm than the traditional threshold alarm occurred at the specific moment of 00:44 on April 7 of 2018.The method would provide a valuable tool and have a wide engineering application in ensuring the safety and reliability of industrial production.
Optimization of the N_2 generation selectivity in aqueous nitrate reduction using internal circulation micro-electrolysis

The reduction of nitrate using internal circulation micro-electrolysis technology(ICE)was investigated.The effect of the reaction time,initial pH,Fe/C ratio,and aeration rate on the nitrate reduction was investigated using a single factor experiment.Based on the results of the single factor experiment,a response surface methodology(RSM)was applied to optimize the N_2 generation selectivity.The effects and interactions of three independent variables were estimated using a Box–Behnken design.Using the RSM analysis,a quadratic polynomial model with optimal conditions at pH = 8.8,Fe/C = 1:1,and an aeration rate of 30 L·min~(–1) was developed by means of the regression analysis of the experimental data.Using the RSM optimization,the optimal conditions yielded aN_2 generation selectivity of 72.0%,which is in good agreementwith experimental result(73.2%±0.5%)and falls within the 95% confidence interval(IC:66.8%–77.3%)of the model results.This indicates that the model obtained in this study effectively predicts the N_2 generation selectivity for nitrate reduction by the ICE process,thus providing a theoretical basis for process design.