Comparative evaluation of commercial Douchi by different molds:biogenic amines,non-volatile and volatile compounds

To provide new insights into the development and utilization of Douchi artificial starters,three common strains(Aspergillus oryzae,Mucor racemosus,and Rhizopus oligosporus)were used to study their influence on the fermentation of Douchi.The results showed that the biogenic amine contents of the three types of Douchi were all within the safe range and far lower than those of traditional fermented Douchi.Aspergillus-type Douchi produced more free amino acids than the other two types of Douchi,and its umami taste was more prominent in sensory evaluation(P<0.01),while Mucor-type and Rhizopus-type Douchi produced more esters and pyrazines,making the aroma,sauce,and Douchi flavor more abundant.According to the Pearson and PLS analyses results,sweetness was significantly negatively correlated with phenylalanine,cysteine,and acetic acid(P<0.05),bitterness was significantly negatively correlated with malic acid(P<0.05),the sour taste was significantly positively correlated with citric acid and most free amino acids(P<0.05),while astringency was significantly negatively correlated with glucose(P<0.001).Thirteen volatile compounds such as furfuryl alcohol,phenethyl alcohol,and benzaldehyde caused the flavor difference of three types of Douchi.This study provides theoretical basis for the selection of starting strains for commercial Douchi production.

Spectral purification improves monitoring accuracy of the comprehensive growth evaluation index for film-mulched winter wheat

In order to further improve the utility of unmanned aerial vehicle(UAV)remote-sensing for quickly and accurately monitoring the growth of winter wheat under film mulching, this study examined the treatments of ridge mulching,ridge–furrow full mulching, and flat cropping full mulching in winter wheat.Based on the fuzzy comprehensive evaluation (FCE) method, four agronomic parameters (leaf area index, above-ground biomass, plant height, and leaf chlorophyll content) were used to calculate the comprehensive growth evaluation index (CGEI) of the winter wheat, and 14 visible and near-infrared spectral indices were calculated using spectral purification technology to process the remote-sensing image data of winter wheat obtained by multispectral UAV.Four machine learning algorithms, partial least squares, support vector machines, random forests, and artificial neural network networks(ANN), were used to build the winter wheat growth monitoring model under film mulching, and accuracy evaluation and mapping of the spatial and temporal distribution of winter wheat growth status were carried out.The results showed that the CGEI of winter wheat under film mulching constructed using the FCE method could objectively and comprehensively evaluate the crop growth status.The accuracy of remote-sensing inversion of the CGEI based on the ANN model was higher than for the individual agronomic parameters, with a coefficient of determination of 0.75,a root mean square error of 8.40, and a mean absolute value error of 6.53.Spectral purification could eliminate the interference of background effects caused by mulching and soil, effectively improving the accuracy of the remotesensing inversion of winter wheat under film mulching, with the best inversion effect achieved on the ridge–furrow full mulching area after spectral purification.The results of this study provide a theoretical reference for the use of UAV remote-sensing to monitor the growth status of winter wheat with film mulching.

Landslide hazard susceptibility evaluation based on SBAS-InSAR technology and SSA-BP neural network algorithm:A case study of Baihetan Reservoir Area

Landslide hazard susceptibility evaluation takes on critical significance in early warning and disaster prevention and reduction.In order to solve the problems of poor effectiveness of landslide data and complex calculation of weights for multiple evaluation factors in the existing landslide susceptibility evaluation models,in this study,a method of landslide hazard susceptibility evaluation is proposed by combining SBAS-InSAR(Small Baseline Subsets-Interferometric Synthetic Aperture Radar)and SSA-BP(Sparrow Search Algorithm-Back Propagation)neural network algorithm.The SBAS-InSAR technology is adopted to identify potential landslide hazards in the study area,update the cataloging data of landslide hazards,and 11 evaluation factors are chosen for constructing the SSA-BP model for training and validation.Baihetan Reservoir area is selected as a case study for validation.As indicated by the results,the application of SBAS-InSAR technology,combined with both ascending and descending orbit data,effectively addresses the incomplete identification of landslide hazards caused by geometric distortion of single orbit SAR data(e.g.,shadow,overlay,and perspective contraction)in deep canyon areas,thereby enabling the acquisition of up-to-date landslide hazard data.Moreover,in comparison to the conventional BP(Back Propagation)algorithm,the accuracy of the model constructed by the SSA-BP algorithm exhibits a significant increase,with mean squared error and mean absolute error reduced by 0.0142 and 0.0607,respectively.Additionally,during the process of susceptibility evaluation,the SSA-BP model effectively circumvents the issue of considerable manual interventions in calculating the weight of evaluation factors.The area under the curve of this model reaches 0.909,surpassing BP(0.835),random forest(0.792),and the information value method(0.699).The risk of landslide occurrence in the Baihetan Reservoir area is positively correlated with slope,surface temperature,and deformation rate,while it is negatively correlated with fault distance and normalized difference vegetation index.Geological lithology exerts minimal influence on the occurrence of landslides,with the risk being low in forest land and high in grassland.The method proposed in this study provides a useful reference for disaster prevention and mitigation departments to perform landslide hazard susceptibility evaluations in deep canyon areas under complex geological conditions.

A Trust Evaluation Mechanism Based on Autoencoder Clustering Algorithm for Edge Device Access of IoT

First,we propose a cross-domain authentication architecture based on trust evaluation mechanism,including registration,certificate issuance,and cross-domain authentication processes.A direct trust evaluation mechanism based on the time decay factor is proposed,taking into account the influence of historical interaction records.We weight the time attenuation factor to each historical interaction record for updating and got the new historical record data.We refer to the beta distribution to enhance the flexibility and adaptability of the direct trust assessment model to better capture time trends in the historical record.Then we propose an autoencoder-based trust clustering algorithm.We perform feature extraction based on autoencoders.Kullback leibler(KL)divergence is used to calculate the reconstruction error.When constructing a convolutional autoencoder,we introduce convolutional neural networks to improve training efficiency and introduce sparse constraints into the hidden layer of the autoencoder.The sparse penalty term in the loss function measures the difference through the KL divergence.Trust clustering is performed based on the density based spatial clustering of applications with noise(DBSCAN)clustering algorithm.During the clustering process,edge nodes have a variety of trustworthy attribute characteristics.We assign different attribute weights according to the relative importance of each attribute in the clustering process,and a larger weight means that the attribute occupies a greater weight in the calculation of distance.Finally,we introduced adaptive weights to calculate comprehensive trust evaluation.Simulation experiments prove that our trust evaluation mechanism has excellent reliability and accuracy.

Comprehensive Evaluation of Distributed PV Grid-Connected Based on Combined Weighting Weights and TOPSIS-RSR Method

To effectively quantify the impact of distributed photovoltaic(PV)access on the distribution network,this paper proposes a comprehensive evaluation method of distributed PV grid connection combining subjective and objective combination of assignment and technique for order preference by similarity to an ideal solution(TOPSIS)—rank sum ratio(RSR)(TOPSIS-RSR)method.Based on the traditional distribution network evaluation system,a comprehensive evaluation system has been constructed.It fully considers the new development requirements of distributed PV access on the environmental friendliness and absorptive capacity of the distribution grid and comprehensively reflects the impact of distributed PV grid connection.The analytic hierarchy process(AHP)was used to determine the subjective weights of the primary indicators,and the Spearman consistency test was combined to determine the weights of the secondary indicators based on three objective assignment methods.The subjective and objective combination weights of each assessment indicator were calculated through the principle of minimum entropy.Calculate the distance between the indicators to be evaluated and the positive and negative ideal solutions,the relative closeness ranking,and qualitative binning by TOPSIS-RSR method to obtain the comprehensive evaluation results of different scenarios.By setting up different PV grid-connected scenarios and utilizing the IEEE33 node simulation algorithm,the correctness and effectiveness of the proposed subject-object combination assignment and integrated assessment method are verified.

Unequal Distribution of Innovation Efforts for Neglected Tropical Diseases: The Role of Funding Evaluation Criteria

Background: International research and innovation efforts for neglected tropical diseases have increased in recent decades due to disparities in overall health research funding in relation to global burden of disease. However, within the field of neglected tropical diseases some seem far more neglected than others. In this research the aim is to investigate the distribution of resources and efforts, as well as the mechanisms that underpin funding allocation for neglected tropical diseases. Methodology: A systematic literature review was conducted to establish a comprehensive overview of known indicators for innovation efforts related to a wide range of neglected tropical diseases. Articles were selected based on a subjective evaluation of their relevance, the presence of original data, and the breadth of their scope. This was followed by thirteen in-depth open-ended interviews with representatives of private, public and philanthropic funding organizations, concerning evaluation criteria for funding research proposals. Results: The findings reveal a large difference in the extent to which the individual diseases are neglected with notable differences between absolute and relative efforts. Criteria used in the evaluation of research proposals relate to potential impact, the probability of success and strategic fit. Private organizations prioritize strategic fit and economic impact;philanthropic organizations prioritize short-term societal impact;and public generally prioritize the probability of success by accounting for follow-up funding and involvement of industry. Funding decisions of different types of organizations are highly interrelated. Conclusions: This study shows that the evaluation of funding proposals introduces and retains unequal funding distribution, reinforcing the relative neglect of diseases. Societal impact is the primary rationale for funding but application of it as a funding criterion is associated with significant challenges. Furthermore, current application of evaluation criteria leads to a primary focus on short-term impact. Through current practice, the relatively most neglected diseases will remain so, and a long-term strategy is needed to resolve this.

Prevention and Control Strategies of Nosocomial Infection and Effectiveness Evaluation in a Tertiary Teaching Hospital during the Epidemic of COVID-19

Objective: To evaluate the role of prevention and control strategies for nosocomial infection in a tertiary teaching hospital during the sudden outbreak of Corona Virus Disease 2019 (COVID-19). Methods: The hospital initiated an emergency plan involving multi-departmental defense and control. It adopted a series of nosocomial infection prevention and control measures, including strengthening pre-examination and triage, optimizing the consultation process, improving the hospital’s architectural composition, implementing graded risk management, enhancing personal protection, and implementing staff training and supervision. Descriptive research was used to evaluate the short-term effects of these in-hospital prevention and control strategies. The analysis compared changes in related evaluation indicators between January 24, 2020 and February 12, 2020 (Chinese Lunar New Year’s Eve 2020 to lunar January 19) and the corresponding lunar period of the previous year. Results: Compared to the same period last year, the outpatient fever rate increased by 1.85-fold (P P Conclusion: The nosocomial infection prevention and control strategies implemented during this specific period improved the detection and control abilities for the COVID-19 source of infection and enhanced the compliance with measures. This likely contributed significantly to avoiding the occurrence of nosocomial infection.

Full-domain collaborative deployment method of multiple interference sources and evaluation of its deployment effect

This paper realizes the full-domain collaborative deployment of multiple interference sources of the global satellite navigation system(GNSS)and evaluates the deployment effect to enhance the ability to disturb the attacker and the capability to defend the GNSS during navigation countermeasures.Key evaluation indicators for the jamming effect of GNSS suppressive and deceptive jamming sources are first created,their evaluation models are built,and their detection procedures are sorted out,as the basis for determining the deployment principles.The principles for collaboratively deploying multi-jamming sources are developed to obtain the deployment structures(including the required number,structures in demand,and corresponding positions)of three single interference sources required by collaboratively deploying.Accordingly,simulation and hardware-in-loop testing results are presented to determine a rational configuration of the collaborative deployment of multi-jamming sources in the set situation and further realize the full-domain deployment of an interference network from ground,air to space.Varied evaluation indices for the deployment effect are finally developed to evaluate the deployment effect of the proposed configuration and further verify its reliability and rationality.

I-DCGAN and TOPSIS-IFP:A simulation generation model for radiographic flaw detection images in light alloy castings and an algorithm for quality evaluation of generated images

The intelligent detection technology driven by X-ray images and deep learning represents the forefront of advanced techniques and development trends in flaw detection and automated evaluation of light alloy castings.However,the efficacy of deep learning models hinges upon a substantial abundance of flaw samples.The existing research on X-ray image augmentation for flaw detection suffers from shortcomings such as poor diversity of flaw samples and low reliability of quality evaluation.To this end,a novel approach was put forward,which involves the creation of the Interpolation-Deep Convolutional Generative Adversarial Network(I-DCGAN)for flaw detection image generation and a comprehensive evaluation algorithm named TOPSIS-IFP.I-DCGAN enables the generation of high-resolution,diverse simulated images with multiple appearances,achieving an improvement in sample diversity and quality while maintaining a relatively lower computational complexity.TOPSIS-IFP facilitates multi-dimensional quality evaluation,including aspects such as diversity,authenticity,image distribution difference,and image distortion degree.The results indicate that the X-ray radiographic images of magnesium and aluminum alloy castings achieve optimal performance when trained up to the 800th and 600th epochs,respectively.The TOPSIS-IFP value reaches 78.7%and 73.8%similarity to the ideal solution,respectively.Compared to single index evaluation,the TOPSIS-IFP algorithm achieves higher-quality simulated images at the optimal training epoch.This approach successfully mitigates the issue of unreliable quality associated with single index evaluation.The image generation and comprehensive quality evaluation method developed in this paper provides a novel approach for image augmentation in flaw recognition,holding significant importance for enhancing the robustness of subsequent flaw recognition networks.

Research Progress of Volatile Substances Analysis and Sensory Evaluation of Soymilk

Soybean is one of the important crops in China. Soymilk, a traditional neutral plant-based protein drink, is rich in high quality proteins. Although soybean milk is rich in nutrients, its marketing among consumers, especially those in Western countries who are used to peaceful flavor, has been limited due to the adverse flavor impact brought by its special composition. In recent years, with the increasing attention to the nutritional value of soymilk, the flavor of soymilk has become a popular research object for scholars at home and abroad. The flavor components of soymilk are mainly volatile small molecular compounds produced by enzymatic reactions catalyzed by lipoxygenase(LOX). After formation, they interact with protein macromolecules to form the overall flavor of soymilk. At present, there are many methods to control the off-odor of soymilk at home and abroad, including physical heating methods, chemical methods, biological enzymatic digestion methods, mask methods, and a variety of breeding methods. These methods effectively reduce the off-odor of soymilk, but all of them have shortcomings. Currently, the sensory characteristics of the beany odor in soymilk are evaluated mainly by traditional human sensory scoring along with the assistance of modern instrument analysis of volatile flavor substances using headspace solid phase microextraction(SPME) gas chromatography coupled with-mass spectrometry(GC-MS). This paper summarized the research results of volatile flavor substances in soymilk in recent years and the sensory evaluation methods of soymilk at home and abroad, and looked forward to the future development direction, hoping to provide some theoretical bases and reference detection methods for solving the problem of soymilk flavor in the future.

Evaluation of a software positioning tool to support SMEs in adoption of big data analytics

Big data analytics has been widely adopted by large companies to achieve measurable benefits including increased profitability,customer demand forecasting,cheaper development of products,and improved stock control.Small and medium sized enterprises(SMEs)are the backbone of the global economy,comprising of 90%of businesses worldwide.However,only 10%SMEs have adopted big data analytics despite the competitive advantage they could achieve.Previous research has analysed the barriers to adoption and a strategic framework has been developed to help SMEs adopt big data analytics.The framework was converted into a scoring tool which has been applied to multiple case studies of SMEs in the UK.This paper documents the process of evaluating the framework based on the structured feedback from a focus group composed of experienced practitioners.The results of the evaluation are presented with a discussion on the results,and the paper concludes with recommendations to improve the scoring tool based on the proposed framework.The research demonstrates that this positioning tool is beneficial for SMEs to achieve competitive advantages by increasing the application of business intelligence and big data analytics.

Evaluation of Clinician Training in Autism Screening, Care Management, and Patient Education

Objective: The demand for pediatric developmental evaluations has far exceeded the workforce available to perform them, which creates long significant wait times for services. A year-long clinician training using the Extension for Community Healthcare Outcomes (ECHO®) model with monthly meetings was conducted and evaluated for its impact on primary care clinicians’ self-reported self-efficacy, ability to administer autism screening and counsel families, professional fulfillment, and burnout. Methods: Participants represented six community health centers and a hospital-based practice. Data collection was informed by participant feedback and the Normalization Process Theory via online surveys and focus groups/interviews. Twelve virtual monthly trainings were delivered between November 2020 and October 2021. Results: 30 clinicians participated in data collection. Matched analyses (n = 9) indicated statistically significant increase in self-rated ability to counsel families about autism (Pre-test Mean = 3.00, Post-test Mean = 3.89, p = 0.0313), manage autistic patients’ care (Pre-test Mean = 2.56, Post-test Mean = 4.11, p = 0.0078), empathy toward patients (Pre-test Mean = 2.11, Post-test Mean = 1.22, p = 0.0156) and colleagues (Pre-test Mean = 2.33, Post-test Mean = 1.22, respectively, p = 0.0391). Unmatched analysis revealed increases in participants confident about educating patients about autism (70.59%, post-test n = 12 vs. 3.33%, pre-test n = 1, p = 0.0019). Focus groups found increased confidence in using the term “autism”. Conclusion: Participants reported increases in ability and confidence to care for autistic patients, as well as empathy toward patients and colleagues. Future research should explore long-term outcomes in participants’ knowledge retention, confidence in practice, and improvements to autism evaluations and care.

Establishment of acquired tracheoesophageal fistula using a modified magnetic compression technique in rabbits and its postmodeling evaluation

BACKGROUND Previous studies have validated the efficacy of both magnetic compression and surgical techniques in creating rabbit tracheoesophageal fistula(TEF)models.Magnetic compression achieves a 100%success rate but requires more time,while surgery,though less frequently successful,offers rapid model establishment and technical maturity in larger animal models.AIM To determine the optimal approach for rabbit disease modeling and refine the process.METHODS TEF models were created in 12 rabbits using both the modified magnetic compression technique and surgery.Comparisons of the time to model establishment,success rate,food and water intake,weight changes,activity levels,bronchoscopy findings,white blood cell counts,and biopsies were performed.In response to the failures encountered during modified magnetic compression modeling,we increased the sample size to 15 rabbit models and assessed the repeatability and stability of the models,comparing them with the original magnetic compression technique.RESULTS The modified magnetic compression technique achieved a 66.7%success rate,whereas the success rate of the surgery technique was 33.3%.Surviving surgical rabbits might not meet subsequent experimental requirements due to TEF-related inflammation.In the modified magnetic compression group,one rabbit died,possibly due to magnet corrosion,and another died from tracheal magnet obstruction.Similar events occurred during the second round of modified magnetic compression modeling,with one rabbit possibly succumbing to aggravated lung infection.The operation time of the first round of modified magnetic compression was 3.2±0.6 min,which was significantly reduced to 2.1±0.4 min in the second round,compared to both the first round and that of the original technique.CONCLUSION The modified magnetic compression technique exhibits lower stress responses,a simple procedure,a high success rate,and lower modeling costs,making it a more appropriate choice for constructing TEF models in rabbits.

Similarity evaluation model for the internal defect detection of strip steel

An internal defect meter is an instrument to detect the internal inclusion defects of cold-rolled strip steel.The detection accuracy of the equipment can be evaluated based on the similarity of the multiple detection data obtained for the same steel coil.Based on the cosine similarity model and eigenvalue matrix model,a comprehensive evaluation method to calculate the weighted average of similarity is proposed.Results show that the new method is consistent with and can even replace artificial evaluation to realize the automatic evaluation of strip defect detection results.

Evaluation of Economical and Intensive Use of Construction Land in a County Town:A case study of Wan’an County,Ji’an City

Taking the changes of construction land in Wan’an County over the years as the research object,the quantity and spatial characteristics of construction land in Wan’an County were analyzed,and the overall situation and regional differences of construction land utilization in Wan’an County were revealed.From the aspects of main influencing factors such as land use structure,land use intensity,land input intensity and output benefit,an evaluation indicator system was established to evaluate the economical and intensive use level of construction land in Wan’an County.The results show that the score of the economical and intensive use level of construction land in Wan’an County was 56.92,which was the lowest among all the districts and counties in Ji’an City.Based on the evaluation results,the corresponding economizing and intensive strategies were put forward,and the safeguard measures for its implementation were explored.The purpose is to provide some support for the preparation of territorial spatial planning,the delineation of urban development boundaries,and the potential exploitation of construction land stock,hoping to improve the utilization efficiency and benefit of construction land in Wan’an County,and promote the economic growth of Wan’an County to the stage of high-quality development.

Evaluation of Trace Elements in the Soil of Typical Peach Orchards in Zunyi City

[Objectives]This study was conducted to clarify the enrichment and paucity of trace elements in the soil environment of peach orchards in Zunyi City,and to provide reference for supplementary application of microelement fertilizers and high-quality peach production in peach orchards.[Methods]Taking the soil of three typical peach orchards(Taoli Renjia peach orchard,Pengrui peach orchard and Taohuadao peach orchard)in Shenxi Town,Honghuagang District,Zunyi City as the research object,the contents of trace elements in soil were analyzed through field sampling and indoor determination of trace elements.[Results]The effective contents of trace elements in the soil of peach orchard bases in the study area were at a medium level,and the soil of the peach orchards was rich in available Fe and Se.The contents of available Cu,Mo and Mn were relatively rich.The contents of available B were not high overall.The contents of available Zn were at a moderate to low level overall.The soil of Taoli Renjia peach orchard was relatively rich in trace elements.[Conclusions]The research results can provide a scientific basis for the production of high-quality crispy peaches in peach orchards.

Research on the prognostic value of adjusting intraperitoneal threedimensional quality evaluation mode in laparoscopic cholecystectomy patients

BACKGROUND Benign gallbladder diseases have become a high-prevalence condition not only in China but also worldwide.The main types of benign gallbladder diseases include gallbladder polyps,acute and chronic cholecystitis,and gallstones,with gallstones being the most common,accounting for over 70%of cases.Although the mortality rate of benign gallbladder diseases is low,they carry obvious potential risks.Studies have shown that an increased incidence of benign gallbladder diseases can increase the risk of cardiovascular diseases and gallbladder cancer,resulting in a substantial disease burden on patients and their families.AIM To assess the medical utility of the Configuration-Procedure-Consequence(CPC)three-dimensional quality evaluation model in modulating the prognosis of laparoscopic cholecystectomy patients.METHODS A total of 98 patients who underwent laparoscopic cholecystectomy in our hospital from February 2020 to January 2022 were selected as the subjects.According to the random number table method,they were divided into a study group and a control group,with 49 patients in each group.The control group received routine perioperative care,while the study group had the addition of the CPC three-dimensional quality evaluation.The postoperative recovery-related indicators(time to first flatus,time to oral intake,time to ambulation,hospital stay),stress indicators(cortisol and adrenaline levels),distinctions in anxiety and RESULTS The time to first flatus,time to oral intake,time to ambulation,and hospital stay of the study group patients were obviously lower than those of the control group patients,with statistical significance(P<0.05).On the 1st day after admission,there were no obvious distinctions in cortisol and adrenaline levels in blood samples,as well as in the Self-Rating Anxiety Scale(SAS)and Self-Rating Depression Scale(SDS)scores between the study group and the control group(P>0.05).However,on the 3rd day after surgery,the cortisol and adrenaline levels,as well as SAS and SDS scores of the study group patients,were obviously lower than those of the control group patients(P<0.05).The study group had 2 cases of incisional infection and 1 case of pulmonary infection,with a total incidence of complications of 6.12%(3/49),which was obviously lower than the 20.41%(10/49)in the control group(P<0.05).CONCLUSION Implementing the CPC three-dimensional quality evaluation model for patients undergoing laparoscopic cholecystectomy can help accelerate their perioperative recovery process,alleviate perioperative stress symptoms,mitigate anxiety,depression,and other adverse emotions,and to some extent,reduce the incidence of perioperative complications.

Teachers’Perception for Evaluation of the Primary School Students With Final Grade

The most difficult and delicate part of the learning process is assessment.Assessment is difficult because during his/her accomplishment the teacher has to consider not only the acquisition of knowledge from students,but also the overall degree of development of their competencies.It is delicate,because through assessment we can influence the emotional side of students and their“willingness”to learn.Despite these facts,teachers need to evaluate students during the learning process.The purpose of the research is to find out what is the perception of teachers about the level of evaluation of students with final grade.The overall results showed that 89%of teachers agree,9%of them have a neutral attitude,and 2%do not agree that the evaluation of students with a final grade is done taking into account many aspects and using many methods,the overall average of the results,M=4.36.Based on the empirical results,it was found that teachers who have completed assessment training have a more positive approach to student assessment,as the average score is higher than teachers who have not completed assessment training.From the qualitative results it was understood that the Teachers did not encounter any difficulties during the assessment of the students.

Identification and evaluation of shale oil micromigration and its petroleum geological significance

Taking the Lower Permian Fengcheng Formation shale in Mahu Sag of Junggar Basin,NW China,as an example,core observation,test analysis,geological analysis and numerical simulation were applied to identify the shale oil micro-migration phenomenon.The hydrocarbon micro-migration in shale oil was quantitatively evaluated and verified by a self-created hydrocarbon expulsion potential method,and the petroleum geological significance of shale oil micro-migration evaluation was determined.Results show that significant micro-migration can be recognized between the organic-rich lamina and organic-poor lamina.The organic-rich lamina has strong hydrocarbon generation ability.The heavy components of hydrocarbon preferentially retained by kerogen swelling or adsorption,while the light components of hydrocarbon were migrated and accumulated to the interbedded felsic or carbonate organic-poor laminae as free oil.About 69% of the Fengcheng Formation shale samples in Well MY1 exhibit hydrocarbon charging phenomenon,while 31% of those exhibit hydrocarbon expulsion phenomenon.The reliability of the micro-migration evaluation results was verified by combining the group components based on the geochromatography effect,two-dimension nuclear magnetic resonance analysis,and the geochemical behavior of inorganic manganese elements in the process of hydrocarbon migration.Micro-migration is a bridge connecting the hydrocarbon accumulation elements in shale formations,which reflects the whole process of shale oil generation,expulsion and accumulation,and controls the content and composition of shale oil.The identification and evaluation of shale oil micro-migration will provide new perspectives for dynamically differential enrichment mechanism of shale oil and establishing a“multi-peak model in oil generation”of shale.

Evaluation of the Reliability of a System: Approach by Monte Carlo Simulation and Application

The objective of this paper is to evaluate the reliability of a system in its different states (absence of failures, partial failure and total failure) and to propose actions to improve this reliability by an approach based on Monte Carlo simulation. It consists of a probabilistic evaluation based on Markov Chains. In order to achieve this goal, the functionalities of Markov Chains and Monte Carlo simulation steps are deployed. The application is made on a production system. .