An approximate analytical model for unconventional reservoir considering variable matrix blocks and simultaneous matrix depletion

In regard to unconventional oil reservoirs,the transient dual-porosity and triple-porosity models have been adopted to describe the fluid flow in the complex fracture network.It has been proven to cause inaccurate production evaluations because of the absence of matrix-macrofracture communication.In addition,most of the existing models are solved analytically based on Laplace transform and numerical inversion.Hence,an approximate analytical solution is derived directly in real-time space considering variable matrix blocks and simultaneous matrix depletion.To simplify the derivation,the simultaneous matrix depletion is divided into two parts:one part feeding the macrofractures and the other part feeding the microfractures.Then,a series of partial differential equations(PDEs)describing the transient flow and boundary conditions are constructed and solved analytically by integration.Finally,a relationship between oil rate and production time in real-time space is obtained.The new model is verified against classical analytical models.When the microfracture system and matrix-macrofracture communication is neglected,the result of the new model agrees with those obtained with the dual-porosity and triple-porosity model,respectively.Certainly,the new model also has an excellent agreement with the numerical model.The model is then applied to two actual tight oil wells completed in western Canada sedimentary basin.After identifying the flow regime,the solution suitably matches the field production data,and the model parameters are determined.Through these output parameters,we can accurately forecast the production and even estimate the petrophysical properties.

Scheme Based on Multi-Level Patch Attention and Lesion Localization for Diabetic Retinopathy Grading

Early screening of diabetes retinopathy(DR)plays an important role in preventing irreversible blindness.Existing research has failed to fully explore effective DR lesion information in fundus maps.Besides,traditional attention schemes have not considered the impact of lesion type differences on grading,resulting in unreasonable extraction of important lesion features.Therefore,this paper proposes a DR diagnosis scheme that integrates a multi-level patch attention generator(MPAG)and a lesion localization module(LLM).Firstly,MPAGis used to predict patches of different sizes and generate a weighted attention map based on the prediction score and the types of lesions contained in the patches,fully considering the impact of lesion type differences on grading,solving the problem that the attention maps of lesions cannot be further refined and then adapted to the final DR diagnosis task.Secondly,the LLM generates a global attention map based on localization.Finally,the weighted attention map and global attention map are weighted with the fundus map to fully explore effective DR lesion information and increase the attention of the classification network to lesion details.This paper demonstrates the effectiveness of the proposed method through extensive experiments on the public DDR dataset,obtaining an accuracy of 0.8064.

Simultaneous Waveform Inverse Modelling for Litho-Fluid Prediction in an Old Marginal, “Agbbo”Field, Onshore Niger Delta, Nigeria

Simultaneous waveform inversion was used to predict lithofacies and fluid type across the field. Very often, characterizing reservoirs in terms of lithology and fluid type using conventional methods is replete with uncertainties, especially in marginal fields. An approach is employed in this study that integrated rock physics and waveform inverse modelling for lithology and fluid-type characterization to appropriately identify potential hydrocarbon saturated zones and their corresponding lithology. Seismic and well-log data were analyzed using Hampson Russel software. The method adopted includes lithofacies and fluid content analysis using rock physics parameters and seismic simultaneous inverse modelling. Rock physics analysis identified 2 broad reservoirs namely: HDZ1 and HDZ2 reservoirs. Results from the inverse modelling showed that low values of acoustic impedance from 19,743 to 20,487 (ft/s)(g/cc) reflect hydrocarbon-bearing reservoirs while medium to high values shows brine and shale respectively, with brine zone ranging from 20,487 to 22,531 (ft/s)(g/cc) and shale above 22,531 (ft/s)(g/cc). Two lithofacies were identified from inversion analysis of Vp/Vs and Mu-Rho, namely: sand and shale with VpVs 1.95 values respectively. Mu-Rho > 12.29 (GPa)(g/cc) and <12.29 (GPa) (g/cc) represent sand and shale respectively. From 3D volume, it was observed that a high accumulation of hydrocarbon was observed to be saturated at the north to the eastern part of the field forming a meandering channel. Sands were mainly distributed around the northeastern to the southwestern part of the field, that tends to be away from Well 029. This was also validated by the volume of rigidity modulus (Mu-Rho) showing high values indicating sands fall within the northeastern part of the field.

A universal probe for simultaneous detection of six pospiviroids and natural infection of potato spindle tuber viroid(PSTVd) in tomato in China

Several viroids in the genus Pospiviroid can infect tomato(Solanum lycopersicum)and cause severe diseases,posing a serious threat to tomato production.For simultaneous detection of six tomato-infecting pospiviroids-columnea latent viroid(CLVd),pepper chat fruit viroid(PCFVd),potato spindle tuber viroid(PSTVd),tomato apical stunt viroid(TASVd),tomato chlorotic dwarf viroid(TCDVd),and tomato planta macho viroid(TPMVd),we developed a universal probe based on a highly conserved 61 nt long sequence shared among them.Compared with their specific probes,the universal probe has a similar,though slightly reduced,detection sensitivity and has the advantages of simple and cost-effective preparation and simultaneous detection of the six pospiviroids.In addition,the universal probe was used in dot-blot hybridization assays for a large-scale survey of viroid(s)in tomato plantings in China.Only PSTVd was detected in a few greenhouse-planted tomato plants.Sequence analysis revealed that these tomato PSTVd isolates may have been introduced from tomato seeds imported from abroad.

FPGA based hardware platform for trapped-ion-based multi-level quantum systems

We report a design and implementation of a field-programmable-gate-arrays(FPGA)based hardware platform,which is used to realize control and signal readout of trapped-ion-based multi-level quantum systems.This platform integrates a four-channel 2.8 Gsps@14 bits arbitrary waveform generator,a 16-channel 1 Gsps@14 bits direct-digital-synthesisbased radio-frequency generator,a 16-channel 8 ns resolution pulse generator,a 10-channel 16 bits digital-to-analogconverter module,and a 2-channel proportion integration differentiation controller.The hardware platform can be applied in the trapped-ion-based multi-level quantum systems,enabling quantum control of multi-level quantum system and highdimensional quantum simulation.The platform is scalable and more channels for control and signal readout can be implemented by utilizing more parallel duplications of the hardware.The hardware platform also has a bright future to be applied in scaled trapped-ion-based quantum systems.

A Fiber Optic Sensor for the Simultaneous Measurement of Dual-parameter Based on Hydrogel-immobilized Enzyme Complex

A novel fiber optic sensor based on hydrogel-immobilized enzyme complex was developed for the simultaneous measurement of dual-parameter,the leap from a single parameter detecting fiber optic sensor to a fiber optic sensor that can continuously detect two kinds of parameters was achieved.By controlling the temperature from high to low,the function of fiber sulfide sensor and fiber DCP sensor can be realized,so as to realize the continuous detection of dual-parameter.The different variables affecting the sensor performance were evaluated and optimized.Under the optimal conditions,the response curves,linear detection ranges,detection limits and response times of the dual-parameter sensor for testing sulfide and DCP were obtained,respectively.The sensor displays high selectivity,good repeatability and stability,which have good potentials in analyzing sulfide and DCP concentration of practical water samples.

Deep reinforcement learning based multi-level dynamic reconfiguration for urban distribution network:a cloud-edge collaboration architecture

With the construction of the power Internet of Things(IoT),communication between smart devices in urban distribution networks has been gradually moving towards high speed,high compatibility,and low latency,which provides reliable support for reconfiguration optimization in urban distribution networks.Thus,this study proposed a deep reinforcement learning based multi-level dynamic reconfiguration method for urban distribution networks in a cloud-edge collaboration architecture to obtain a real-time optimal multi-level dynamic reconfiguration solution.First,the multi-level dynamic reconfiguration method was discussed,which included feeder-,transformer-,and substation-levels.Subsequently,the multi-agent system was combined with the cloud-edge collaboration architecture to build a deep reinforcement learning model for multi-level dynamic reconfiguration in an urban distribution network.The cloud-edge collaboration architecture can effectively support the multi-agent system to conduct“centralized training and decentralized execution”operation modes and improve the learning efficiency of the model.Thereafter,for a multi-agent system,this study adopted a combination of offline and online learning to endow the model with the ability to realize automatic optimization and updation of the strategy.In the offline learning phase,a Q-learning-based multi-agent conservative Q-learning(MACQL)algorithm was proposed to stabilize the learning results and reduce the risk of the next online learning phase.In the online learning phase,a multi-agent deep deterministic policy gradient(MADDPG)algorithm based on policy gradients was proposed to explore the action space and update the experience pool.Finally,the effectiveness of the proposed method was verified through a simulation analysis of a real-world 445-node system.

Simultaneous nitrification and autotrophic denitrification in fluidized bed reactors using pyrite and elemental sulfur as electron donors

In this study, simultaneous nitrification and autotrophic denitrification (SNAD) with either elemental sulfur or pyrite were investigated in fluidized bed reactors in mesophilic conditions. The reactor performance was evaluated at different ammonium (12-40 mg/L of NH4+-N), nitrate (35-45 mg/L of NO3--N), and dissolved oxygen (DO) (0.1-1.5 mg/L) concentrations, with a hydraulic retention time of 12 h. The pyrite reactor supported the SNAD process with a maximum nitrogen removal efficiency of 139.5 mg/(L·d) when the DO concentration was in the range of 0.8-1.5 mg/L. This range, however, limited the denitrification efficiency of the reactor, which decreased from 90.0% ± 5.3% in phases II-V to 67.9% ± 7.2% in phases VI and VII. Sulfate precipitated as iron sulfate (FeSO4/Fe2(SO4)3) and sodium sulfate (Na2SO4) minerals during the experiment. The sulfur reactor did not respond well to nitrification with a low and unstable ammonium removal efficiency, while denitrification occurred with a nitrate removal efficiency of 97.8%. In the pyrite system, the nitrifying bacterium Nitrosomonas sp. was present, and its relative abundance increased from 0.1% to 1.1%, while the autotrophic denitrifying genera Terrimonas, Ferruginibacter, and Denitratimonas dominated the community. Thiobacillus, Sulfurovum, and Trichlorobacter were the most abundant genera in the sulfur reactor during the entire experiment.

Simultaneous resonance of an axially moving ferromagnetic thin plate under a line load in a time-varying magnetic field

In this paper,the simultaneous resonance of a ferromagnetic thin plate in a time-varying magnetic field,having axial speed and being subjected to a periodic line load,is studied.Based on the large deflection theory of thin plates and electromagnetic field theory,the nonlinear vibration differential equation of the plate is obtained by using the Hamilton′s principle and the Galerkin method.Then the boundary condition in which the longer opposite sides are clamped and hinged is considered.The dimensionless nonlinear differential equations are solved by using the method of multiple scales,and the analytical solution is given.In addition,the stability analysis is also carried out by using Lyapunov stability theory.Through numerical analysis,the variation curves of system resonance amplitude with frequency tuning parameter,magnetic field strength and external excitation amplitude are obtained.Different parameters that have significant effects on the response of the system,such as the thickness,the axial velocity,the magnetic field intensity,the position,and the frequency of external excitation,are considered and analyzed.The results show that the system has multiple solution regions and obvious nonlinear coupled characteristics.

Repeat peroral endoscopic myotomy with simultaneous submucosal and muscle dissection as a salvage option for recurrent achalasia

BACKGROUND For recurrent achalasia after initial peroral endoscopic myotomy(POEM)failure,repeat POEM(Re-POEM)has been reported as a treatment option.However,severe esophageal interlayer adhesions caused by previous procedures impede the successful establishment of a submucosal tunnel and lead to aborted Re-POEM procedures.Our team previously described POEM with simultaneous submucosal and muscle dissection(POEM-SSMD)as a feasible solution for achalasia with severe interlayer adhesions.AIM To investigate the effectiveness and safety of Re-POEM with simultaneous submucosal and muscle dissection(Re-POEM-SSMD).METHODS A total of 1049 patients with achalasia who underwent successful endoscopic myotomy at the Digestive Endoscopic Center of Chinese PLA General Hospital from December 2014 to May 2022 were reviewed.Patients with recurrent achalasia who experienced initial POEM clinical failure were retrospectively included in this study.The primary endpoint was retreatment clinical success,defined as an Eckardt score≤3 during the postretreatment follow-up and no need for additional treatment.Procedure-related adverse events,changes in manometric lower esophageal sphincter(LES)pressure and reflux complications,as well as procedure-related parameters,were recorded.RESULTS Sixteen patients underwent Re-POEM(9 patients)or Re-POEM-SSMD(7 patients)successfully at a median of 45.5 mo(range,4-95 mo)after initial POEM.During a median followup period of 31 mo(range,7-96 mo),clinical success(Eckardt score≤3)was achieved in 8(88.9%)and 6(85.7%)patients after Re-POEM and Re-POEM-SSMD,respectively(P=0.849).The median Eckardt score dropped from 4(range,3-8)at preretreatment to 1(range,0-5)at postretreatment in the Re-POEM group(P=0.025)and from 5(range,2-8)to 2(range,0-4)in the Re-POEM-SSMD group(P<0.001).The mean manometric LES pressure decreased from 23.78±9.04 mmHg to 11.45±5.37 mmHg after Re-POEM(P<0.001)and from 26.80±7.48 mmHg to 11.05±4.38 mmHg after Re-POEM-SSMD(P<0.001).No serious adverse events were recorded in both groups.CONCLUSION In conclusion,Re-POEM-SSMD appears to be a safe and effective salvage therapy for recurrent achalasia with severe interlayer adhesions.

Cooperative Sampling Path Planning of Underwater Glider Fleet with Simultaneous Launch and Recovery

As low-cost and highly autonomous ocean observation platforms,underwater gliders encounter risks during their launch and recovery,especially when coordinating multi-glider deployments.This work focuses on cooperative path planning of an underwater glider fleet with simultaneous launch and recovery to enhance the autonomy of sampling and reduce deployment risks.Specifically,the gliders collaborate to achieve sampling considering the specified routines of interest.The overall paths to be planned are divided into four rectangular parts with the same starting point,and each glider is assigned a local sampling route.A clipped-oriented line-of-sight algorithm is proposed to ensure the coverage of the desired edges.The pitch angle of the glider is selected as the optimizing parameter to coordinate the overall progress considering the susceptibility of gliders to currents and the randomness of paths produced by complex navigational strategies.Therefore,a multi-actuation deep-Q network algorithm is proposed to ensure simultaneous launch and recovery.Simulation results demonstrate the acceptable effectiveness of the proposed method.

Simultaneous denoising and resolution enhancement of seismic data based on elastic convolution dictionary learning

Enhancing seismic resolution is a key component in seismic data processing, which plays a valuable role in raising the prospecting accuracy of oil reservoirs. However, in noisy situations, existing resolution enhancement methods are difficult to yield satisfactory processing outcomes for reservoir characterization. To solve this problem, we develop a new approach for simultaneous denoising and resolution enhancement of seismic data based on convolution dictionary learning. First, an elastic convolution dictionary learning algorithm is presented to efficiently learn a convolution dictionary with stronger representation capability from the noisy data to be processed. Specifically, the algorithm introduces the elastic L1/2 norm as a sparsity constraint and employs a steepest gradient descent strategy to efficiently solve the frequency-domain linear system with substantial computational cost in a half-quadratic splitting framework. Then, based on the learned convolution dictionary, a weighted convolutional sparse representation paradigm is designed to encode the noisy data to acquire an optimal sparse approximation of the effective signal. Subsequently, a high-resolution dictionary with a broadband spectrum is constructed by the proposed parameter scaling strategy and matched filtering technique on the basis of atomic spectrum modeling. Finally, the optimal sparse approximation of the effective signal and the constructed high-resolution dictionary are used for data reconstruction to obtain the seismic signal with high resolution and high signal-to-noise ratio. Synthetic and field dataset examples are executed to check the effectiveness and reliability of the developed method. The results indicate that this method has a more competitive performance in seismic applications compared with the conventional deconvolution and spectral whitening methods.

Simultaneous detection of CH_(4)and CO_(2)through dual modulation off-axis integrated cavity output spectroscopy

This study established a novel method for the simultaneous detection of two-component gases.Radio frequency(RF)white noise disturbance laser current and wavelength modulation were simultaneously used to improve the off-axis integrated cavity output spectroscopy technique,and a high-precision dual modulation OA-ICOS(RF-WM-OA-ICOS)system was established.The two laser beams were coupled into one laser beam that was applied incident to the cavity of RF-WM-OA-ICOS system.The second harmonic signals of CH_(4)and CO_(2)gas simultaneously appeared in the rising or falling edge of a triangular wave.This method was used to measure CH_(4)and CO_(2)with different concentrations.The results indicated that the proposed system has high stability and can accurately and simultaneously measure the concentrations of CH_(4)and CO_(2),with an optimal integration time of 220 s.The minimum detection limit was 10 ppb for CH_(4)and 1.5 ppm for CO_(2).The corresponding noise equivalent absorption sensitivity values were calculated as 2.67×10^(-13)cm^(-1)·Hz^(-1/2)and 5.18×10^(-11)cm^(-1)·Hz^(-1/2),respectively.The proposed dual-component gas simultaneous detection method can also be used for high-precision simultaneous detection of other gases.Therefore,this study may serve as a reference for developing portable multicomponent gas analyzers.

Review of Simultaneous Localization and Mapping Technology in the Agricultural Environment

Simultaneous localization and mapping(SLAM)is one of the most attractive research hotspots in the field of robotics,and it is also a prerequisite for the autonomous navigation of robots.It can significantly improve the autonomous navigation ability of mobile robots and their adaptability to different application environments and contribute to the realization of real-time obstacle avoidance and dynamic path planning.Moreover,the application of SLAM technology has expanded from industrial production,intelligent transportation,special operations and other fields to agricultural environments,such as autonomous navigation,independent weeding,three-dimen-sional(3D)mapping,and independent harvesting.This paper mainly introduces the principle,sys-tem framework,latest development and application of SLAM technology,especially in agricultural environments.Firstly,the system framework and theory of the SLAM algorithm are introduced,and the SLAM algorithm is described in detail according to different sensor types.Then,the devel-opment and application of SLAM in the agricultural environment are summarized from two aspects:environment map construction,and localization and navigation of agricultural robots.Finally,the challenges and future research directions of SLAM in the agricultural environment are discussed.

Acute myelomonocytic leukemia and T-lymphoblastic lymphoma as simultaneous bilineage hematologic malignancy treated with decitabine:A case report

BACKGROUND Simultaneous bilineage hematologic malignancies are rare;however,several cases of acute myeloid leukemia(AML)and T-lymphoblastic lymphoma(T-LBL)cooccurrence have been reported.A standard treatment for simultaneous AML and T-LBL has not yet been established,and its prognosis is very poor.Further studies to develop standard treatments are required to increase patient survival rates.CASE SUMMARY A 69-year-old man complaining of pleuritic chest pain visited the emergency room.Computed tomography revealed multiple enlarged lymph nodes(LNs)in the neck and groin and pulmonary thromboembolism with pulmonary infarction.Furthermore,a peripheral blood smear performed due to leukocytosis revealed circulating blasts.Acute myelomonocytic leukemia(AMML)was diagnosed after bone marrow examination,and T-LBL positivity for terminal deoxynucleotidyl transferase,cluster of differentiation(CD)34,and CD4 was confirmed by cervical LN biopsy.Decitabine and dexamethasone were administered because he could not receive intensive chemotherapy due to poor performance status.Complete remission of AMML and T-LBL was achieved after 4 cycles of decitabine plus dexamethasone.CONCLUSION We report the therapeutic effect of decitabine,a hypomethylating agent(HMA),in patients with concurrent bilineage hematologic malignancies and suggest that further studies are required to evaluate the therapeutic effect of HMAs on both lymphoid and bilineage hematologic malignancies.

Neighborhood Effects and Political Trust: A Multi-level Analysis of Chinese Rural-to-Urban Migrants’ Trust in County Government

Massive rural-to-urban migration in China is consequential for political trust: rural-to-urban migrants have been found to hold lower levels of trust in local government than their rural peers who choose to stay in the countryside (mean 4.92 and 6.34 out of 10, respectively, p < 0.001). This article explores why migrants have a certain level of political trust in their county-level government. Using data of rural-to-urban migrants from the China Family Panel Survey, this study performs a hierarchical linear modeling (HLM) to unpack the multi-level explanatory factors of rural-to-urban migrants’ political trust. Findings show that the individual-level socio-economic characteristics and perceptions of government performance (Level-1), the neighborhood-level characteristics-the physical and social status and environment of neighborhoods (Level-2), and the objective macroeconomic performance of county-level government (Level-3), work together to explain migrants’ trust levels. These results suggest that considering the effects of neighborhood-level factors on rural-to-urban migrants’ political trust merits policy and public management attention in rapidly urbanizing countries.

Simultaneous pancreas-kidney transplantation for end-stage renal failure in type 1 diabetes mellitus: Current perspectives

Type 1 diabetes mellitus(T1DM)is one of the important causes of chronic kidney disease(CKD)and end-stage renal failure(ESRF).Even with the best available treatment options,management of T1DM poses significant challenges for clinicians across the world,especially when associated with CKD and ESRF.Substantial increases in morbidity and mortality along with marked rise in treatment costs and marked reduction of quality of life are the usual consequences of onset of CKD and progression to ESRF in patients with T1DM.Simultaneous pancreas-kidney transplant(SPK)is an attractive and promising treatment option for patients with advanced CKD/ESRF and T1DM for potential cure of these diseases and possibly several complications.However,limited availability of the organs for transplantation,the need for long-term immunosuppression to prevent rejection,peri-and post-operative complications of SPK,lack of resources and the expertise for the procedure in many centers,and the cost implications related to the surgery and postoperative care of these patients are major issues faced by clinicians across the globe.This clinical update review compiles the latest evidence and current recommendations of SPK for patients with T1DM and advanced CKD/ESRF to enable clinicians to care for these diseases.

Empirical Research on the Relationship between Education Poverty Alleviation and Rural Revitalization—Spatial Panel Simultaneous Equation Model Based on Provincial Panel Data

On the basis of using entropy weight method to measure China’s education poverty alleviation and rural revitalization evaluation indicators, using the panel data of 30 provinces in China (excluding Xizang, Hong Kong, Macao and Taiwan) from 2012 to 2021, a spatial panel simultaneous equation model is constructed based on adjacency matrix, geographical distance matrix and economic geographical distance matrix deeply study the interaction mechanism and spatial spillover effects between education poverty alleviation and rural revitalization through the generalized spatial three-stage least squares method (GS3SLS). The results indicate that there is a significant spatial spillover effect and a positive spatial correlation between education poverty alleviation and rural revitalization, and there is a significant interactive effect between the two variables, while promoting each other positively. Therefore, the government should clarify the deep relationship between education poverty alleviation and rural revitalization based on the current background, and better consolidate and expand the effective connection between the achievements of education poverty alleviation and rural revitalization.

视觉SLAM方法综述

实时定位与建图(SLAM)技术搭载特定传感器,使移动机器人在无任何环境先验条件下,在运动过程中自主建立环境模型来计算自身位姿,大幅提高其自主导航能力,以及对不同应用环境的适应性。视觉SLAM方法以相机作为外部传感器,通过采集周围环境信息来创建地图并实时估计机器人自身位姿。为此,介绍了具有代表性的经典视觉SLAM方法及与深度学习相结合的视觉SLAM方法,分析了视觉SLAM方法中采用的不同特征检测方法、后端优化、闭环检测,以及动态环境下视觉SLAM方法的应用,总结了视觉SLAM方法的问题,并探讨了视觉SLAM方法在未来的热点研究方向和发展前景。