Numerical evaluations on the fluid production in the in-situ conversion of continental shale oil reservoirs

In-situ conversion presents a promising technique for exploiting continental oil shale formations,characterized by highly fractured organic-rich rock.A 3D in-situ conversion model,which incorporates a discrete fracture network,is developed using a self-developed thermal-flow-chemical(TFC)simulator.Analysis of the model elucidates the in-situ conversion process in three stages and defines the transformation of fluids into three distinct outcomes according to their end stages.The findings indicate that kerogen decomposition increases fluid pressure,activating fractures and subsequently enhancing permeability.A comprehensive analysis of activated fracture permeability and heating power reveals four distinct production modes,highlighting that increasing heating power correlates with higher cumulative fluid production.Activated fractures,with heightened permeability,facilitate the mobility of heavy oil toward production wells but hinder its cracking,thereby limiting light hydrocarbon production.Additionally,energy efficiency research demonstrates the feasibility of the in-situ conversion in terms of energy utilization,especially when considering the surplus energy from high-fluctuation energy sources such as wind and solar power to provide heating.

Spatiotemporal patterns and drivers of cultivated land conversion in Inner Mongolia Autonomous Region,northern China

Protection and optimization of cultivated land resources are of great significance to national food security.Cultivated land conversion in northern China has increased in recent years due to the industrialization and urbanization of society.However,the assessment of cultivated land conversion in this area is insufficient,posing a potential risk to cultivated land resources.This study evaluated the evolution and spatiotemporal patterns of cultivated land conversion in Inner Mongolia Autonomous Region,China,and the driving factors to improve rational utilization and to protect cultivated land resources.The spatiotemporal patterns of cultivated land conversion in Inner Mongolia were analyzed using the cultivated land conversion index,kernel density analysis,a standard deviation ellipse model,and a geographic detector.Results showed that from 2000 to 2020,the trends in cultivated land conversion area and rate in Inner Mongolia exhibited fluctuating growth,with the total area of cultivated land conversion reaching 7307.59 km^(2) at a rate of 6.69%.Spatial distribution of cultivated land conversion was primarily concentrated in the Hetao Plain,Nengjiang Plain,Liaohe Plain,and the Hohhot-Baotou-Ordos urban agglomeration.Moreover,the standard deviational ellipse of cultivated land conversion in Inner Mongolia exhibited a directional southwest-northeast-southwest-northeast distribution,with the northeast-southwest direction identified as the main driving force of spatial change in cultivated land conversion.Meanwhile,cultivated land conversion exhibited an increase-decrease-increase change process,indicating that spatial distribution of cultivated land conversion in Inner Mongolia became gradually apparent within the study period.The geographic detector results further revealed that the main driving factors of cultivated land conversion in Inner Mongolia were the share of secondary and tertiary industries and per-unit area yield of grain,with explanatory rates of 57.00%,55.00%,and 51.00%,respectively.Additionally,improved agricultural production efficiency and the coordinated development of population urbanization and industry resulted in cultivated land conversion.Collectively,the findings of this study indicated that,from 2000 to 2020,the cultivated land conversion in Inner Mongolia was significant and fluctuated in time,and had strong spatial heterogeneity.The primary drivers of these events included the effects of agriculture,population,and social economy.

Classification of Conversational Sentences Using an Ensemble Pre-Trained Language Model with the Fine-Tuned Parameter

Sentence classification is the process of categorizing a sentence based on the context of the sentence.Sentence categorization requires more semantic highlights than other tasks,such as dependence parsing,which requires more syntactic elements.Most existing strategies focus on the general semantics of a conversation without involving the context of the sentence,recognizing the progress and comparing impacts.An ensemble pre-trained language model was taken up here to classify the conversation sentences from the conversation corpus.The conversational sentences are classified into four categories:information,question,directive,and commission.These classification label sequences are for analyzing the conversation progress and predicting the pecking order of the conversation.Ensemble of Bidirectional Encoder for Representation of Transformer(BERT),Robustly Optimized BERT pretraining Approach(RoBERTa),Generative Pre-Trained Transformer(GPT),DistilBERT and Generalized Autoregressive Pretraining for Language Understanding(XLNet)models are trained on conversation corpus with hyperparameters.Hyperparameter tuning approach is carried out for better performance on sentence classification.This Ensemble of Pre-trained Language Models with a Hyperparameter Tuning(EPLM-HT)system is trained on an annotated conversation dataset.The proposed approach outperformed compared to the base BERT,GPT,DistilBERT and XLNet transformer models.The proposed ensemble model with the fine-tuned parameters achieved an F1_score of 0.88.

MeshCNN-based BREP to CSG conversion algorithm for 3D CAD models and its application

In the field of neutronics analysis, it is imperative to develop computer-aided modeling technology for Monte Carlo codes to address the increasing complexity of reactor core components by converting 3D CAD model(boundary representation, BREP) to MC model(constructive solid geometry, CSG). Separation-based conversion from BREP to CSG is widely used in computer-aided modeling MC codes because of its high efficiency, reliability, and easy implementation. However, the current separation-based BREP-CSG conversion is poor for processing complex CAD models, and it is necessary to divide a complex model into several simple models before applying the separation-based conversion algorithm, which is time-consuming and tedious. To avoid manual segmentation, this study proposed a MeshCNN-based 3D-shape segmentation algorithm to automatically separate a complex model. The proposed 3D-shape segmentation algorithm was combined with separation-based BREP-CSG conversion algorithms to directly convert complex models.The proposed algorithm was integrated into the computeraided modeling software cosVMPT and validated using the Chinese fusion engineering testing reactor model. The results demonstrate that the MeshCNN-based BREP-CSG conversion algorithm has a better performance and higher efficiency, particularly in terms of CPU time, and the conversion result is more intuitive and consistent with the intention of the modeler.

Power Allocation for Wireless Powered MIMO Transmissions with Non-Linear RF Energy Conversion Models

We study a radio frequency(RF) wireless energy transfer(WET) enabled multiple input multiple output(MIMO) system. A time slotted transmission pattern is considered. Each slot can be divided into two phases, downlink(DL) WET and uplink(UL) wireless information transmission(WIT). Since energy conversion efficiency of the energy harvesting circuits are non.linear, the conventional linear model leads to a mismatch for resource allocation. In this paper, the power allocation algorithm considering the practical non.linear energy harvesting circuits is studied. The optimization problem is formulated to maximize the energy efficiency of system with multiple constraints, i.e., the transmission power, the received power and the minimum harvested energy, which is a non.convex problem. We transform the objective function from fractional form into an equivalent objective function in subtractive form and provide an iterative power allocation algorithm to achieve the optimal solution. Numerical results show that our proposed algorithm with the non.linear RF energy conversion models can achieve much better performance than the algorithm with the conventional linear model.

Model-based evaluation on the conversion ratio of ammonium to nitrite in a nitritation process for ammonium-rich wastewater treatment

Modeling for nitritation process was discussed and analyzed quantitatively for the factors that influence nitrite accumulation. The results indicated that pH, inorganic carbon source and Hydraulic Retention Time(HRT) as well as biomass concentration are the main factors that influenced the conversion ratio of ammonium to nitrite. A constant high pH can lead to a high nitritation rate and results in high conversion ratio on condition that free ammonia inhibition do not happen. In a CSTR system, without pH control, this conversion ratio can be monitored by pH variation in the reactor. The pH goes down far from the inlet level means a strongly nitrite accumulation. High concentration of alkalinity can promoted the conversion ratio by means of accelerating the nitritation rate through providing sufficient inorganic carbon source(carbon dioxide). When inorganic carbon source was depleted, the nitritation process stopped. HRT adjustment could be an efficient way to make the nitritation system run more flexible, which to some extent can meet the requirements of the fluctuant of inlet parameters such as ammonium concentration, pH, and temperature and so on. Biomass concentration is the key point, especially for a CSTR system in steady state, which was normally circumscribed by the characteristics of bacteria and may also affected by aeration mode and can be increased by prolonging the HRT on the condition of no nitrate accumulation when no recirculation available. The higher the biomass concentration is, the better the nitrite accumulation can be obtained.

Impact of Labor Transfer on Agricultural Land Use Conversion at Rural Household Level Based on Logit Model

Since land and labor force are primary resources to be used and controlled by rural households, the allocation of labor forces will influence land uses, and further lead to land use conversion. The present study used the Binary Logit model to investigate the influence of labor force transfer, characteristics of rural households, location, and land market on agricultural land use conversion at rural household level. This study was conducted based on 329 valid questionnaires, which were obtained in Changshu, Rudong, and Tongshan counties, respectively representing the southern, middle and northern areas of Jiangsu Province. The results showed that land market participation, location, zonal difference and labor transfer had strong influences on agricultural land use conversion. The participation of land market had a strong positive effect on land use conversion, especially for the farmland converted to the fishpond. The nearer to the county seat, the more conversion of land use occurred. Particularly, the labor force transfer caused by wage employment decreased this conversion probability, while the labor transfer caused by self-employment led to more conversion; and the increasing of income from labor transfer increased the conversion. Moreover, land use con- versions demonstrated zonal difference, which were more in Rudong and Changshu counties than in Tongshan County, and the factors influencing this conversion were different in the three regions.

Incorporating Linguistic Rules in Statistical Chinese Language Model for Pinyin-to-character Conversion

An N-gram Chinese language model incorporating linguistic rules is presented. By constructing elements lattice, rules information is incorporated in statistical frame. To facilitate the hybrid modeling, novel methods such as MI-based rule evaluating, weighted rule quantification and element-based n-gram probability approximation are presented. Dynamic Viterbi algorithm is adopted to search the best path in lattice. To strengthen the model, transformation-based error-driven rules learning is adopted. Applying proposed model to Chinese Pinyin-to-character conversion, high performance has been achieved in accuracy, flexibility and robustness simultaneously. Tests show correct rate achieves 94.81% instead of 90.53% using bi-gram Markov model alone. Many long-distance dependency and recursion in language can be processed effectively.

Risk-stratification model to select conversion surgery for advanced gastric cancer patients

Objective: Conversion surgery is a surgery with a purpose of R0 resection in primary advanced gastric cancer(GC) that responded well to systemic chemotherapy. This study aimed to explore the efficacy of conversion surgery for advanced GC.Methods: A total of 618 advanced GC patients receiving systemic chemotherapy were stratified into low-,moderate-and high-risk groups based on a nomogram-predicted probability of overall survival. The survival of conversion surgery and chemotherapy alone groups was compared using the log-rank test and Cox regression analysis after propensity score matching(PSM).Results: A nomogram with good discrimination(concordance index: 0.65) and accurate calibration was constructed. After PSM, the median survival time(MST) of conversion surgery was 26.80 months, compared with16.60 months of chemotherapy alone(P<0.001). Conversion surgery was associated with a longer MST for patients in the low-risk group(30.40 months vs. 20.90 months, P=0.013), whereas it was not associated with prolonged survival in the moderate-and high-risk groups(P=0.221 and P=0.131, respectively).Conclusions: Conversion surgery was associated with longer survival, especially for low-risk population.

Parameters affecting reaction rate and conversion of TiO_2 chlorination in a fluidized bed reactor: Experimental and modeling approach

Pilot scale chlorination of TiO2 was carried out with CO as reducing agent.The experimental analysis and modeling of chlorination process of TiO2 in the presence of CO and Cl2 in a semi-continuous fluidized bed reactor were aimed.Chlorination process was continuously monitored by measuring the amount of produced TiCl4 with time.The effects of different operating parameters including chlorination temperature,feedstock particle size and size distribution,amount of feedstock and Cl2 and CO flow rates on the conversion were systematically investigated.A gradual increase in chlorination temperature led to monotonous increase of conversion rate.Conversion decreased with increased particle size of feedstock.An increase in loaded feedstock led to a decrease in reaction conversion.A model was proposed to predict conversion,particle size distribution and mole fraction of components in gas phase as reaction proceeds.A good agreement between conversions predicted by the model and experimental data under various operating conditions was observed.

RESEARCH OF PINYIN-TO-CHARACTER CONVERSION BASED ON MAXIMUM ENTROPY MODEL

This paper applied Maximum Entropy (ME) model to Pinyin-To-Character (PTC) conversion in-stead of Hidden Markov Model (HMM) that could not include complicated and long-distance lexical informa-tion. Two ME models were built based on simple and complex templates respectively, and the complex one gave better conversion result. Furthermore, conversion trigger pair of y A → y B cBwas proposed to extract the long-distance constrain feature from the corpus; and then Average Mutual Information (AMI) was used to se-lect conversion trigger pair features which were added to the ME model. The experiment shows that conver-sion error of the ME with conversion trigger pairs is reduced by 4% on a small training corpus, comparing with HMM smoothed by absolute smoothing.

Maximum initial primary wave model for low-Froude-number reservoir landslides based on wave theory

The impulse waves induced by large-reservoir landslides can be characterized by a low Froude number.However,systematic research on predictive models specifically targeting the initial primary wave is lacking.Taking the Shuipingzi 1#landslide that occurred in the Baihetan Reservoir area of the Jinsha River in China as an engineering example,this study established a large-scale physical model(with dimensions of 30 m×29 m×3.5 m at a scale of 1:150)and conducted scaled experiments on 3D landslide-induced impulse waves.During the process in which a sliding mass displaced and compressed a body of water to generate waves,the maximum initial wave amplitude was found to be positively correlated with the sliding velocity and the volume of the landslide.With the increase in the water depth,the wave amplitude initially increased and then decreased.The duration of pressure exertion by the sliding mass at its maximum velocity directly correlated with an elevated wave amplitude.Based on the theories of low-amplitude waves and energy conservation,while considering the energy conversion efficiency,a predictive model for the initial wave amplitude was derived.This model could fit and validate the functions of wavelength and wave velocity.The accuracy of the initial wave amplitude was verified using physical experiment data,with a prediction accuracy for the maximum initial wave amplitude reaching 90%.The conversion efficiency(η)directly determined the accuracy of the estimation formula.Under clear conditions for landslide-induced impulse wave generation,estimating the value ofηthrough analogy cases was feasible.This study has derived the landslide-induced impulse waves amplitude prediction formula from the standpoints of wave theory and energy conservation,with greater consideration given to the intrinsic characteristics in the formation process of landslide-induced impulse waves,thereby enhancing the applicability and extensibility of the formula.This can facilitate the development of empirical estimation methods for landslide-induced impulse waves toward universality.

Low-power system model for quantum entangled photon-pair source

The quantum entangled photon-pair source,as an essential component of optical quantum systems,holds great potential for applications such as quantum teleportation,quan-tum computing,and quantum imaging.The current workhorse technique for preparing photon pairs involves performing spon-taneous parametric down conversion(SPDC)in bulk nonlinear crystals.However,the current power consumption and cost of preparing entangled photon-pair sources are relatively high,pos-ing challenges to their integration and scalability.In this paper,we propose a low-power system model for the quantum entan-gled photon-pair source based on SPDC theory and phase matching technology.This model allows us to analyze the per-formance of each module and the influence of component cha-racteristics on the overall system.In our experimental setup,we utilize a 5 mW laser diode and a typical type-II barium metabo-rate(BBO)crystal to prepare an entangled photon-pair source.The experimental results are in excellent agreement with the model,indicating a significant step towards achieving the goal of low-power and low-cost entangled photon-pair sources.This achievement not only contributes to the practical application of quantum entanglement lighting,but also paves the way for the widespread adoption of optical quantum systems in the future.

Velocity model and time-depth conversion for the northwestern South China Sea deepwater areas

There are rich natural gas resources in the northwestern South China Sea deepwater areas, with poor degree of exploration. Because of the unique tectonic, sedimentary background of the region, velocity model building and time-depth conversion have been an important and difficult problem for a long time. Recent researches in this direction have revealed three major problems for deepwater areas, i.e., the way to determine error correction for drilling velocity, the optimization of velocity modeling, and the understanding and analysis of velocity variations in the slope areas. The present contribution proposes technical solutions to the problems：（1） velocity correction version can be established by analyzing the geology, reservoir, water depths and velocity spectrum characteristics;（2） a unified method can be adopted to analyze the velocity variation patterns in drilled pale structural positions;and （3） across-layer velocity is analyzed to establish the velocity model individually for each of the layers. Such a solution is applicable, as shown in an example from the northwestern South China Sea deepwater areas, in which an improved prediction precision is obtained.

ANALYSIS AND MODELING ON CULTIVATED LAND CONVERSION——Case Study of Hebei Province

： With the acceleration of thc urbanization and industrialization of China, it is inevitable that cultivated land convcrts to built-up land for industrial, commercial and residential uses, which would impose pressure both on food security and on the sustainability of urbanization itself tbr such a country with large population and few cultivated land. Based on thc three-time Landsat Thematic Mapper （TM） digital imagcs and statistic data of Hebei Province, the general facts of cultivated land conversion and its driving forces were analyzcd by establishing econometric model in this papcr. Some conclusions werc drawn as the following： during 1985 2000, the rate of cultivated land converting to built-up arca in Hebei was 4.01% or 0.27% pcr year. Of all the converted cultivated land, 20.96% was converted to built-up area and of all the new built-up areas, 83.4% was converted from cultivated land; meanwhile the conversion is uneven not only in time but also in space; factors such as edgc length shared by cultivated land and built-up land, agricultural value per hectare, non-agriculture value per hectarc, GDP, total population, farmer＇s net income per capita and time had significant effects on this conversion.

ON USING NON-LINEAR CANONICAL CORRELATION ANALYSIS FOR VOICE CONVERSION BASED ON GAUSSIAN MIXTURE MODEL

Voice conversion algorithm aims to provide high level of similarity to the target voice with an acceptable level of quality.The main object of this paper was to build a nonlinear relationship between the parameters for the acoustical features of source and target speaker using Non-Linear Canonical Correlation Analysis(NLCCA) based on jointed Gaussian mixture model.Speaker indi-viduality transformation was achieved mainly by altering vocal tract characteristics represented by Line Spectral Frequencies(LSF).To obtain the transformed speech which sounded more like the target voices,prosody modification is involved through residual prediction.Both objective and subjective evaluations were conducted.The experimental results demonstrated that our proposed algorithm was effective and outperformed the conventional conversion method utilized by the Minimum Mean Square Error(MMSE) estimation.

Conversion of Object Oriented System into Software Product Line with Delta Modeling Abstract Behavioral Specification

This article contains a system conversion from object oriented design into Software Product Line (SPL) using delta modeling of Abstract Behavioral Specification (ABS). ABS is a modeling language which targets system with high level of variety and supports SPL development with delta modeling. The case study of this thesis is a digital library system called Library Automation and Digital Archive (LONTAR). Originally, LONTAR only uses SOAP-based web service. With ABS, LONTAR will be converted into SPL and implement another web service called REST. The motivation of this conversion of LONTAR from object oriented into SPL is because it is easier to develop system with ABS than using regular object oriented. Product definition in ABS is relatively easier than creating a new subclass and do customization to make it works well.

Modeling the kinetics of methane conversion in steam reforming process of coke-oven gas based on experimental data

Steam-reforming is an effective approach for upgrading methane and hydrocarbon of coke-oven gas into CO and HE, but the kinetic behavior needs more study. We investigated the conversion of methane in coke-oven gas by steam reforming process in an electric tubular flow at 14 kPa with temperature varying from .500 ℃ to 9.50 ℃, and developed a kenetic model for, ignoring the effects of adsorption and diffusion. The optimal dynamic conditions for methane conversion 14 kPa are as follows： the ratio of the amount of water to the amount of methane is from 1.1 to 1.3; the reaction temperature is from 1 223 K to 1 273 K. The methane conversion rate is larger than 95% when the ratio of the amount of water to the amount of methane is 1.2 at a temperature above 1 223 K with the residence time up to 0.75 s.

Solution and Application about Conversion Tensor of Motion in Dynamic Modeling of 6-HTRT Parallel Robot

Equivalent integrated finite element method is a canonical and efficient modeling method in dynamic analysis of complex mechanism. The key of establishing dynamic equations of spatial mechanism by the method is to confirm Jacobian matrix reflecting relations of all joints,nodes,and generalized coordinates,namely,relations of second-order and corresponding third-order conversion tensors. For complex motion relations of components in a parallel robot,it gives second-order and third-order conversion tensors of dynamic equations for the 6-HTRT parallel robot based on equivalent integrated finite element method. The method is suitable for the typical robots whose positions of work space and sizes of mechanism are different. The solving course of the method is simple and convenient,so the method lays the foundation of dynamic analysis for robots.

Factors and mechanism driving the land-use conversion in Jiangxi Province

This article explores the factors and mechanism driving the land-use conversion at regional level by developing and using an econometric approach which is called the simultaneous equations model （SEM）. A case study in Jiangxi Province of China is conducted by establishing the SEM, which consists of three equations including agricultural production, land conversion of cultivated land to built-up area and land conversion of cultivated land to forest cover/grassland from 1988 to 2005. And then this paper employs the method of piecewise estimation to represent the influences of the factors such as population, society, economy, location and geophysical conditions on the process of land-use conversion in Jiangxi Province. Estimation results show that population is a predominant factor driving the land-use conversion at counties, while social and economic factors are determinant factors in the short term for the entire Jiangxi Province. Specifically, the size of agricultural population and the magnitude of agricultural input determine the agricultural production to a large extent; population size, plain area proportion at counties and land management policies together affect the direction and magnitude of conversion between cultivated land and built-up area; agricultural population proportion, terrain slope, grain production and non-agricultural industry promote the conversion of cultivated land to forest cover/grassland. Furthermore, the explored mechanism also reveals the underlying causes of the land use changes driven by a series of factors in Jiangxi Province. Finally, this paper concludes that factors proven to play an important role in driving the land-use conversion need to be considered when the land management agencies make out the land use planning to optimize the land use, expand the agricultural production, and conserve the cultivated land.