In this study,the structural characters,antioxidant activities and bile acid-binding ability of sea buckthorn polysaccharides(HRPs)obtained by the commonly used hot water(HRP-W),pressurized hot water(HRP-H),ultrasonic...In this study,the structural characters,antioxidant activities and bile acid-binding ability of sea buckthorn polysaccharides(HRPs)obtained by the commonly used hot water(HRP-W),pressurized hot water(HRP-H),ultrasonic(HRP-U),acid(HRP-C)and alkali(HRP-A)assisted extraction methods were investigated.The results demonstrated that extraction methods had significant effects on extraction yield,monosaccharide composition,molecular weight,particle size,triple-helical structure,and surface morphology of HRPs except for the major linkage bands.Thermogravimetric analysis showed that HRP-U with filamentous reticular microstructure exhibited better thermal stability.The HRP-A with the lowest molecular weight and highest arabinose content possessed the best antioxidant activities.Moreover,the rheological analysis indicated that HRPs with higher galacturonic acid content and molecular weight showed higher viscosity and stronger crosslinking network(HRP-C,HRP-W and HRP-U),which exhibited stronger bile acid binding capacity.The present findings provide scientific evidence in the preparation technology of sea buckthorn polysaccharides with good antioxidant and bile acid binding capacity which are related to the structure affected by the extraction methods.展开更多
Currently,the major challenge in terms of research on K-ion batteries is to ensure that they possess satisfactory cycle stability and specific capacity,especially in terms of the intrinsically sluggish kinetics induce...Currently,the major challenge in terms of research on K-ion batteries is to ensure that they possess satisfactory cycle stability and specific capacity,especially in terms of the intrinsically sluggish kinetics induced by the large radius of K+ions.Here,we explore high-performance K-ion half/full batteries with high rate capability,high specific capacity,and extremely durable cycle stability based on carbon nanosheets with tailored N dopants,which can alleviate the change of volume,increase electronic conductivity,and enhance the K+ion adsorption.The as-assembled K-ion half-batteries show an excellent rate capability of 468 mA h g^(−1) at 100 mA g^(−1),which is superior to those of most carbon materials reported to date.Moreover,the as-assembled half-cells have an outstanding life span,running 40,000 cycles over 8 months with a specific capacity retention of 100%at a high current density of 2000 mA g^(−1),and the target full cells deliver a high reversible specific capacity of 146 mA h g^(−1) after 2000 cycles over 2 months,with a specific capacity retention of 113%at a high current density of 500 mA g^(−1),both of which are state of the art in the field of K-ion batteries.This study might provide some insights into and potential avenues for exploration of advanced K-ion batteries with durable stability for practical applications.展开更多
With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair compar...With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair comparison, and performance rationalization of these methods are lacking, due to the scattered existing studies. To address these issues, we develop 20 capacity estimation methods from three perspectives:charging sequence construction, input forms, and ML models. 22,582 charging curves are generated from 44 cells with different battery chemistry and operating conditions to validate the performance. Through comprehensive and unbiased comparison, the long short-term memory(LSTM) based neural network exhibits the best accuracy and robustness. Across all 6503 tested samples, the mean absolute percentage error(MAPE) for capacity estimation using LSTM is 0.61%, with a maximum error of only 3.94%. Even with the addition of 3 m V voltage noise or the extension of sampling intervals to 60 s, the average MAPE remains below 2%. Furthermore, the charging sequences are provided with physical explanations related to battery degradation to enhance confidence in their application. Recommendations for using other competitive methods are also presented. This work provides valuable insights and guidance for estimating battery capacity based on partial charging curves.展开更多
Evaluating underground gas storage(UGS)sealing capacity is essential for its safe construction and operational efficiency.This involves evaluating both the static sealing capacity of traps during hydrocarbon accumulat...Evaluating underground gas storage(UGS)sealing capacity is essential for its safe construction and operational efficiency.This involves evaluating both the static sealing capacity of traps during hydrocarbon accumulation and the dynamic sealing capacity of UGS under intensive gas injection and withdrawal,and alternating loads.This study detailed the methodology developed by Sinopec.The approach merges disciplines like geology,geomechanics,and hydrodynamics,employing both dynamic-static and qualitative-quantitative analyses.Sinopec's evaluation methods,grounded in the in situ stress analysis,include mechanistic studies,laboratory tests,geological surveys,stress analysis,and fluid-solid interactions.Through tests on the static and dynamic sealing capacity of UGS,alongside investigations into sealing mechanisms and the geological and geomechanical properties of cap rocks and faults,A geomechanics-rock damage-seepage mechanics dynamic coupling analysis method has been developed to predict in situ stress variations relative to pore pressure changes during UGS operations and evaluate fault sealing capacity and cap rock integrity,thereby setting the maximum operational pressures.Utilizing this evaluation technique,Sinopec has defined performance metrics and criteria for evaluating the sealing capacity of depleted gas reservoirs,enabling preliminary sealing capacity evaluations at UGS sites.These evaluations have significantly informed the design of UGS construction schemes and the evaluation of fault sealing capacity and cap rock integrity during UGS operations.展开更多
Single-crystal Ni-rich cathodes are a promising candidate for high-energy lithium-ion batteries due to their higher structural and cycling stability than polycrystalline materials.However,the phase evolution and capac...Single-crystal Ni-rich cathodes are a promising candidate for high-energy lithium-ion batteries due to their higher structural and cycling stability than polycrystalline materials.However,the phase evolution and capacity degradation of these single-crystal cathodes during continuous lithation/delithation cycling remains unclear.Understanding the mapping relationship between the macroscopic electrochemical properties and the material physicochemical properties is crucial.Here,we investigate the correlation between the physical-chemical characteristics,phase transition,and capacity decay using capacity differential curve feature identification and in-situ X-ray spectroscopic imaging.We systematically clarify the dominant mechanism of phase evolution in aging cycling.Appropriately high cut-off voltages can mitigate the slow kinetic and electrochemical properties of single-crystal cathodes.We also find that second-order differential capacity discharge characteristic curves can be used to identify the crystal structure disorder of Ni-rich cathodes.These findings constitute a step forward in elucidating the correlation between the electrochemical extrinsic properties and the physicochemical intrinsic properties and provide new perspectives for failure analysis of layered electrode materials.展开更多
Objective: This study aimed to evaluate the efficacy of trimetazidine on exercise capacity via a six-minute walk test in patients with ischaemic cardiomyopathy and also evaluate the effect of trimetazidine on left ven...Objective: This study aimed to evaluate the efficacy of trimetazidine on exercise capacity via a six-minute walk test in patients with ischaemic cardiomyopathy and also evaluate the effect of trimetazidine on left ventricular function via echocardiography in the same population. Methods: This prospective observational study, conducted at the National Institute of Cardiovascular Diseases in Dhaka, Bangladesh, enrolled 200 patients with ischaemic cardiomyopathy and a depressed left ventricular ejection fraction (LVEF Results: In this study (n = 200) of ischaemic cardiomyopathy patients, the mean age was 58 years, with 76% of the patients being male. All study subjects received GDMT (Guideline-Directed Medical Therapy) for angina and heart failure. Those who received the modified released form of trimetazidine developed lesions during the 1st and 2nd follow-ups, during which the LVEF, LVIDd, and six-minute walk distance significantly improved (p Conclusion: The findings of the present study demonstrated that the addition of modified-release trimetazidine to GDMT can improve exercise capacity and left ventricular function in patients with ischaemic cardiomyopathy.展开更多
Background: Heart failure is a chronic and severe condition that often results from various heart diseases. Cardiac rehabilitation (CR) is currently a crucial component in managing this condition. The aim was to asses...Background: Heart failure is a chronic and severe condition that often results from various heart diseases. Cardiac rehabilitation (CR) is currently a crucial component in managing this condition. The aim was to assess the effects of cardiac rehabilitation on physical capacity of heart failure patients. Methods: This was a cross-sectional study conducted from February 1, 2021, to June 30, 2023. We included all patients with heart failure who underwent cardiac rehabilitation. Data analysis was performed using SPSS software version 24.0, with a significance level set at p Results: The study included 87 heart failure patients, with a male-to-female ratio of 1.8. Mean age was 57.10 years (±11.75). Coronary artery disease was the primary cause of heart failure, accounting for 75.9% of cases. Atrial fibrillation was present in 4.7% of cases. Following cardiac rehabilitation, Left Ventricular Ejection Fraction increased from 40.15% to 49.48% (p = 0.001). Resting heart rate decreased significantly from 81.4 bpm to 68.3 bpm (p = 0.000), and the number of METS increased from 4.3 to 6.57 (+56.8%;p = 0.000). The mean distance covered in the 6-minute walk test significantly increased from 337.8 meters to 522.7 meters (p = 0.000), reflecting a gain of 183.5 meters. Moreover, the increase in the number of METS was more pronounced in females (p = 0.001), non-obese individuals (p = 0.000), non-diabetics (p = 0.001), non-sedentary individuals (p = 0.000), and non-smokers (p = 0.000). The study reported a low readmissions rate of 2.2% and a mortality rate of 1.1%. Conclusion: Our study demonstrates that cardiac rehabilitation is beneficial for black African heart failure patients, resulting in significant improvements in symptoms, physical and capacity.展开更多
Background: Venous thromboembolism (VTE) is among the leading causes of hospital-related disability-adjusted life years lost. We aimed to determine the prevalence and determinants of functional capacity impairment six...Background: Venous thromboembolism (VTE) is among the leading causes of hospital-related disability-adjusted life years lost. We aimed to determine the prevalence and determinants of functional capacity impairment six to twelve months after an acute VTE event. Methods: This was a cross-sectional study conducted between January and April 2021 in two referral hospitals of Yaoundé, including consenting adult patients admitted to these hospitals six to twelve months ago for VTE. We excluded dead patients and those with any comorbidity or symptoms limiting physical activity. The functional outcome was assessed with the six-minute walk test. Functional capacity impairment was defined as walking distance lower than the expected value. Results: We included 27 cases in this study with a mean age of 53.2 ± 14.4 years. The prevalence of functional capacity impairment was 29.6% (95% CI: 14.8 - 48.1). Factors associated with poor functional outcome were obesity (OR: 59.5;95% CI: 4.6 - 767.2;p - 207.4;p = 0.017), massive PE (OR: 30;95% CI: 2.5 - 354;p = 0.004), and poor adherence to treatment (OR: 30.3;95% CI: 2.5 - 333.3;p = 0.004). Conclusion: Functional capacity impairment is common in the medium-term after VTE and factors associated with this poor outcome are obesity, the severity of the VTE, and poor adherence to treatment.展开更多
The present study has been carried out on a total of 50 available plant species to assess their dust-capturing capacity and biochemical performances in and around open cast granite mine areas of Jhansi district and Bu...The present study has been carried out on a total of 50 available plant species to assess their dust-capturing capacity and biochemical performances in and around open cast granite mine areas of Jhansi district and Bundelkhand University campus treated as control site. Plant species existing under a polluted environment for a long time may be considered as potentially resistant species and recommended for green belt design in mining areas, especially to cope with dust pollution. Results showed the pollution level, especially of mining-originated dust particles holding capacity of leaves and effects of different biochemical parameters (Total Chlorophyll, Protein and Carotenoid) of existing plant species both from mining areas as well as from Bundelkhand University campus. Based on their performances, Tectona grandis L., Ficus hispida L., Calotropis procera Aiton., Butea monosperma Lam. and Ficus benghalensis L., etc. are highly tolerant species while Ficus infectoria L., Artocarpus heterophyllus Lam., Ipomoea purpurea L., Allianthus excelsa Roxb. and Bauhinia variegata L. are intermediate tolerant species. T. grandis had shown the highest dust-holding capacity (2.566 ± 0.0004 mg/cm2) whereas Albizia procera (0.018 ± 0.0002 mg/cm2) was found to be the lowest dust-holding capacity. Our findings also showed that the T. grandis and F. hispida have significant dust deposition with minimal effect of dust on their leaf chlorophyll (17.447 ± 0.019 mg/g and 14.703 ± 0.201 mg/g), protein (0.699 ± 0.001 mg/g and 0.604 ± 0.002 mg/g) and carotenoid (0.372 ± 0.003 mg/g and 0.354 ± 0.003 mg/g) content respectively among all selected plant species. Therefore, in the present investigation, plant species with high tolerance to high dust-holding capacity on their leaf surfaces are preferable for green corridors as open cast granite mines and their adjacent areas.展开更多
This paper introduces an innovative approach to the synchronized demand-capacity balance with special focus on sector capacity uncertainty within a centrally controlled collaborative air traffic flow management(ATFM)f...This paper introduces an innovative approach to the synchronized demand-capacity balance with special focus on sector capacity uncertainty within a centrally controlled collaborative air traffic flow management(ATFM)framework.Further with previous study,the uncertainty in capacity is considered as a non-negligible issue regarding multiple reasons,like the impact of weather,the strike of air traffic controllers(ATCOs),the military use of airspace and the spatiotemporal distribution of nonscheduled flights,etc.These recessive factors affect the outcome of traffic flow optimization.In this research,the focus is placed on the impact of sector capacity uncertainty on demand and capacity balancing(DCB)optimization and ATFM,and multiple options,such as delay assignment and rerouting,are intended for regulating the traffic flow.A scenario optimization method for sector capacity in the presence of uncertainties is used to find the approximately optimal solution.The results show that the proposed approach can achieve better demand and capacity balancing and determine perfect integer solutions to ATFM problems,solving large-scale instances(24 h on seven capacity scenarios,with 6255 flights and 8949 trajectories)in 5-15 min.To the best of our knowledge,our experiment is the first to tackle large-scale instances of stochastic ATFM problems within the collaborative ATFM framework.展开更多
This advanced paper presents a new approach to improving image steganography using the Ant Colony Optimization(ACO)algorithm.Image steganography,a technique of embedding hidden information in digital photographs,shoul...This advanced paper presents a new approach to improving image steganography using the Ant Colony Optimization(ACO)algorithm.Image steganography,a technique of embedding hidden information in digital photographs,should ideally achieve the dual purposes of maximum data hiding and maintenance of the integrity of the cover media so that it is least suspect.The contemporary methods of steganography are at best a compromise between these two.In this paper,we present our approach,entitled Ant Colony Optimization(ACO)-Least Significant Bit(LSB),which attempts to optimize the capacity in steganographic embedding.The approach makes use of a grayscale cover image to hide the confidential data with an additional bit pair per byte,both for integrity verification and the file checksumof the secret data.This approach encodes confidential information into four pairs of bits and embeds it within uncompressed grayscale images.The ACO algorithm uses adaptive exploration to select some pixels,maximizing the capacity of data embedding whileminimizing the degradation of visual quality.Pheromone evaporation is introduced through iterations to avoid stagnation in solution refinement.The levels of pheromone are modified to reinforce successful pixel choices.Experimental results obtained through the ACO-LSB method reveal that it clearly improves image steganography capabilities by providing an increase of up to 30%in the embedding capacity compared with traditional approaches;the average Peak Signal to Noise Ratio(PSNR)is 40.5 dB with a Structural Index Similarity(SSIM)of 0.98.The approach also demonstrates very high resistance to detection,cutting down the rate by 20%.Implemented in MATLAB R2023a,the model was tested against one thousand publicly available grayscale images,thus providing robust evidence of its effectiveness.展开更多
As a common transportation facility, speed humps can control the speed of vehicles on special road sections to reduce traffic risks. At the same time, they also cause instantaneous traffic emissions. Based on the clas...As a common transportation facility, speed humps can control the speed of vehicles on special road sections to reduce traffic risks. At the same time, they also cause instantaneous traffic emissions. Based on the classic instantaneous traffic emission model and the limited deceleration capacity microscopic traffic flow model with slow-to-start rules, this paper has investigated the impact of speed humps on traffic flow and the instantaneous emissions of vehicle pollutants in a single lane situation. The numerical simulation results have shown that speed humps have significant effects on traffic flow and traffic emissions. In a free-flow region, the increase of speed humps leads to the continuous rise of CO_(2), NO_(X) and PM emissions. Within some density ranges, one finds that these pollutant emissions can evolve into some higher values under some random seeds. Under other random seeds, they can evolve into some lower values. In a wide moving jam region, the emission values of these pollutants sometimes appear as continuous or intermittent phenomenon. Compared to the refined Na Sch model, the present model has lower instantaneous emissions such as CO_(2), NO_(X) and PM and higher volatile organic components(VOC) emissions. Compared to the limited deceleration capacity model without slow-to-start rules, the present model also has lower instantaneous emissions such as CO_(2), NO_(X) and PM and higher VOC emissions in a wide moving jam region. These results can also be confirmed or explained by the statistical values of vehicle velocity and acceleration.展开更多
Base isolators used in buildings provide both a good acceleration reduction and structural vibration control structures.The base isolators may lose their damping capacity over time due to environmental or dynamic effe...Base isolators used in buildings provide both a good acceleration reduction and structural vibration control structures.The base isolators may lose their damping capacity over time due to environmental or dynamic effects.This deterioration of them requires the determination of the maintenance and repair needs and is important for the long-termisolator life.In this study,an artificial intelligence prediction model has been developed to determine the damage and maintenance-repair requirements of isolators as a result of environmental effects and dynamic factors over time.With the developed model,the required damping capacity of the isolator structure was estimated and compared with the previously placed isolator capacity,and the decrease in the damping property was tried to be determined.For this purpose,a data set was created by collecting the behavior of structures with single degrees of freedom(SDOF),different stiffness,damping ratio and natural period isolated from the foundation under far fault earthquakes.The data is divided into 5 different damping classes varying between 10%and 50%.Machine learning model was trained in damping classes with the data on the structure’s response to random seismic vibrations.As a result of the isolator behavior under randomly selected earthquakes,the recorded motion and structural acceleration of the structure against any seismic vibration were examined,and the decrease in the damping capacity was estimated on a class basis.The performance loss of the isolators,which are separated according to their damping properties,has been tried to be determined,and the reductions in the amounts to be taken into account have been determined by class.In the developed prediction model,using various supervised machine learning classification algorithms,the classification algorithm providing the highest precision for the model has been decided.When the results are examined,it has been determined that the damping of the isolator structure with the machine learning method is predicted successfully at a level exceeding 96%,and it is an effective method in deciding whether there is a decrease in the damping capacity.展开更多
Accurate capacity estimation is of great importance for the reliable state monitoring,timely maintenance,and second-life utilization of lithium-ion batteries.Despite numerous works on battery capacity estimation using...Accurate capacity estimation is of great importance for the reliable state monitoring,timely maintenance,and second-life utilization of lithium-ion batteries.Despite numerous works on battery capacity estimation using laboratory datasets,most of them are applied to battery cells and lack satisfactory fidelity when extended to real-world electric vehicle(EV)battery packs.The challenges intensify for large-sized EV battery packs,where unpredictable operating profiles and low-quality data acquisition hinder precise capacity estimation.To fill the gap,this study introduces a novel data-driven battery pack capacity estimation method grounded in field data.The proposed approach begins by determining labeled capacity through an innovative combination of the inverse ampere-hour integral,open circuit voltage-based,and resistance-based correction methods.Then,multiple health features are extracted from incremental capacity curves,voltage curves,equivalent circuit model parameters,and operating temperature to thoroughly characterize battery aging behavior.A feature selection procedure is performed to determine the optimal feature set based on the Pearson correlation coefficient.Moreover,a convolutional neural network and bidirectional gated recurrent unit,enhanced by an attention mechanism,are employed to estimate the battery pack capacity in real-world EV applications.Finally,the proposed method is validated with a field dataset from two EVs,covering approximately 35,000 kilometers.The results demonstrate that the proposed method exhibits better estimation performance with an error of less than 1.1%compared to existing methods.This work shows great potential for accurate large-sized EV battery pack capacity estimation based on field data,which provides significant insights into reliable labeled capacity calculation,effective features extraction,and machine learning-enabled health diagnosis.展开更多
Ionic liquids(ILs),because of the advantages of low volatility,good thermal stability,high gas solubility and easy recovery,can be regarded as the green substitute for traditional solvent.However,the high viscosity an...Ionic liquids(ILs),because of the advantages of low volatility,good thermal stability,high gas solubility and easy recovery,can be regarded as the green substitute for traditional solvent.However,the high viscosity and synthesis cost limits their application,the hybrid solvent which combining ILs together with others especially water can solve this problem.Compared with the pure IL systems,the study of the ILs-H_(2)O binary system is rare,and the experimental data of corresponding thermodynamic properties(such as density,heat capacity,etc.)are less.Moreover,it is also difficult to obtain all the data through experiments.Therefore,this work establishes a predicted model on ILs-water binary systems based on the group contribution(GC)method.Three different machine learning algorithms(ANN,XGBoost,LightBGM)are applied to fit the density and heat capacity of ILs-water binary systems.And then the three models are compared by two index of MAE and R^(2).The results show that the ANN-GC model has the best prediction effect on the density and heat capacity of ionic liquid-water mixed system.Furthermore,the Shapley additive explanations(SHAP)method is harnessed to scrutinize the significance of each structure and parameter within the ANN-GC model in relation to prediction outcomes.The results reveal that system components(XIL)within the ILs-H_(2)O binary system exert the most substantial influence on density,while for the heat capacity,the substituents on the cation exhibit the greatest impact.This study not only introduces a robust prediction model for the density and heat capacity properties of IL-H_(2)O binary mixtures but also provides insight into the influence of mixture features on its density and heat capacity.展开更多
A theoretical analysis of upward deflection and midspan deflection of prestressed bamboo-steel composite beams is presented in this study.The deflection analysis considers the influences of interface slippage and shea...A theoretical analysis of upward deflection and midspan deflection of prestressed bamboo-steel composite beams is presented in this study.The deflection analysis considers the influences of interface slippage and shear deformation.Furthermore,the calculation model for flexural capacity is proposed considering the two stages of loading.The theoretical results are verified with 8 specimens considering different prestressed load levels,load schemes,and prestress schemes.The results indicate that the proposed theoretical analysis provides a feasible prediction of the deflection and bearing capacity of bamboo-steel composite beams.For deflection analysis,the method considering the slippage and shear deformation provides better accuracy.The theoretical method for bearing capacity matches well with the test results,and the relative errors in the serviceability limit state and ultimate limit state are 4.95%and 5.85%,respectively,which meet the accuracy requirements of the engineered application.展开更多
Conventional machine learning(CML)methods have been successfully applied for gas reservoir prediction.Their prediction accuracy largely depends on the quality of the sample data;therefore,feature optimization of the i...Conventional machine learning(CML)methods have been successfully applied for gas reservoir prediction.Their prediction accuracy largely depends on the quality of the sample data;therefore,feature optimization of the input samples is particularly important.Commonly used feature optimization methods increase the interpretability of gas reservoirs;however,their steps are cumbersome,and the selected features cannot sufficiently guide CML models to mine the intrinsic features of sample data efficiently.In contrast to CML methods,deep learning(DL)methods can directly extract the important features of targets from raw data.Therefore,this study proposes a feature optimization and gas-bearing prediction method based on a hybrid fusion model that combines a convolutional neural network(CNN)and an adaptive particle swarm optimization-least squares support vector machine(APSO-LSSVM).This model adopts an end-to-end algorithm structure to directly extract features from sensitive multicomponent seismic attributes,considerably simplifying the feature optimization.A CNN was used for feature optimization to highlight sensitive gas reservoir information.APSO-LSSVM was used to fully learn the relationship between the features extracted by the CNN to obtain the prediction results.The constructed hybrid fusion model improves gas-bearing prediction accuracy through two processes of feature optimization and intelligent prediction,giving full play to the advantages of DL and CML methods.The prediction results obtained are better than those of a single CNN model or APSO-LSSVM model.In the feature optimization process of multicomponent seismic attribute data,CNN has demonstrated better gas reservoir feature extraction capabilities than commonly used attribute optimization methods.In the prediction process,the APSO-LSSVM model can learn the gas reservoir characteristics better than the LSSVM model and has a higher prediction accuracy.The constructed CNN-APSO-LSSVM model had lower errors and a better fit on the test dataset than the other individual models.This method proves the effectiveness of DL technology for the feature extraction of gas reservoirs and provides a feasible way to combine DL and CML technologies to predict gas reservoirs.展开更多
Gut microbiota plays an important role in food allergy.The immunoglobulin G(IgG)/immunoglobulin E(IgE)binding capacity and human gut microbiota changes of digestion products derived from glycated ovalbumin(OVA)were in...Gut microbiota plays an important role in food allergy.The immunoglobulin G(IgG)/immunoglobulin E(IgE)binding capacity and human gut microbiota changes of digestion products derived from glycated ovalbumin(OVA)were investigated.Gastrointestinal digestion effectively destroyed the primary structure of glycated OVA,resulting in a significantly higher digestibility than gastric digestion,and more abundant peptides<3 kDa.Moreover,gastric and gastrointestinal digestion products have different fluorescence quenching and red shift of fluorescence peaks,and possess different conformational structures.These changes resulted in a decrease in 28.7%of the IgE binding capacity of gastrointestinal digestion products beyond that of pepsin.Moreover,gastrointestinal digestion products of glycated OVA increased significantly the proportion of Subdoligranulum,Collinsella,and Bifidobacterium.Therefore,gastrointestinal digestion products of glycated OVA altered human intestinal microbiota,reducing the risk of potential allergy.展开更多
A dent is a common type of defects for submarine pipeline.For submarine pipelines,high hydrostatic pressure and internal pressure are the main loads.Once pipelines bend due to complex subsea conditions,the compression...A dent is a common type of defects for submarine pipeline.For submarine pipelines,high hydrostatic pressure and internal pressure are the main loads.Once pipelines bend due to complex subsea conditions,the compression strain capacity may be exceeded.Research into the local buckling failure and accurate prediction of the compressive strain capacity are important.A finite element model of a pipeline with a dent is established.Local buckling failure under a bending moment is investigated,and the compressive strain capacity is calculated.The effects of different parameters on pipeline local buckling are analyzed.The results show that the dent depth,external pressure and internal pressure lead to different local buckling failure modes of the pipeline.A higher internal pressure indicates a larger compressive strain capacity,and the opposite is true for external pressure.When the ratio of external pressure to collapse pressure of intact pipeline is greater than 0.1,the deeper the dent,the greater the compressive strain capacity of the pipeline.And as the ratio is less than 0.1,the opposite is true.On the basis of these results,a regression equation for predicting the compressive strain capacity of a dented submarine pipeline is proposed,which can be referred to during the integrity assessment of a submarine pipeline.展开更多
Background: In the context of the fight against HIV, a lack of skills in monitoring and evaluating the personnel in charge of activities has been identified at the national level. It was the subject of a priority axis...Background: In the context of the fight against HIV, a lack of skills in monitoring and evaluating the personnel in charge of activities has been identified at the national level. It was the subject of a priority axis of the national plan for monitoring and evaluating the fight against HIV (2006-2010) that was aimed at strengthening the capacities of actors in this area. To increase the critical mass of competent human resources in the short term, the National Institute of Public Health (NIPH) of Côte d’Ivoire organized monitoring and evaluation training sessions for healthcare professionals from 2011 to 2016. Methods: A single case study with multiple levels of analysis was carried out, combining a qualitative survey and a literature review. An evaluation was carried out six months after each training session. In addition, the results of the pre- and post-tests and of the daily and final evaluations that accompanied the various training sessions were used to provide further information. The qualitative data collected were analyzed using INVIVO 15 software. Results: Some 89 health professionals (69% men and 31% women) working at the national level (51% at the central level, including 58% in health programs) and in development partner agencies (37%) participated in this capacity building program. Most participants were senior health managers (56%), data managers (23%), and statisticians and computer scientists (10%). Almost all the trainings were financed by 16 technical and financial partners (85%), mainly the MEASURE Evaluation project (27%). Conclusion: M&E training, despite all its imperfections, has made it possible to identify M&E training needs at the national level and to increase the critical mass of national skills and to have some culture in M&E.展开更多
基金The Guangdong Basic and Applied Basic Research Foundation(2022A1515010730)National Natural Science Foundation of China(32001647)+2 种基金National Natural Science Foundation of China(31972022)Financial and moral assistance supported by the Guangdong Basic and Applied Basic Research Foundation(2019A1515011996)111 Project(B17018)。
文摘In this study,the structural characters,antioxidant activities and bile acid-binding ability of sea buckthorn polysaccharides(HRPs)obtained by the commonly used hot water(HRP-W),pressurized hot water(HRP-H),ultrasonic(HRP-U),acid(HRP-C)and alkali(HRP-A)assisted extraction methods were investigated.The results demonstrated that extraction methods had significant effects on extraction yield,monosaccharide composition,molecular weight,particle size,triple-helical structure,and surface morphology of HRPs except for the major linkage bands.Thermogravimetric analysis showed that HRP-U with filamentous reticular microstructure exhibited better thermal stability.The HRP-A with the lowest molecular weight and highest arabinose content possessed the best antioxidant activities.Moreover,the rheological analysis indicated that HRPs with higher galacturonic acid content and molecular weight showed higher viscosity and stronger crosslinking network(HRP-C,HRP-W and HRP-U),which exhibited stronger bile acid binding capacity.The present findings provide scientific evidence in the preparation technology of sea buckthorn polysaccharides with good antioxidant and bile acid binding capacity which are related to the structure affected by the extraction methods.
基金National Natural Science Foundation of China,Grant/Award Numbers:51972178,52202061Hunan Provincial Nature Science Foundation,Grant/Award Number:2022JJ40068。
文摘Currently,the major challenge in terms of research on K-ion batteries is to ensure that they possess satisfactory cycle stability and specific capacity,especially in terms of the intrinsically sluggish kinetics induced by the large radius of K+ions.Here,we explore high-performance K-ion half/full batteries with high rate capability,high specific capacity,and extremely durable cycle stability based on carbon nanosheets with tailored N dopants,which can alleviate the change of volume,increase electronic conductivity,and enhance the K+ion adsorption.The as-assembled K-ion half-batteries show an excellent rate capability of 468 mA h g^(−1) at 100 mA g^(−1),which is superior to those of most carbon materials reported to date.Moreover,the as-assembled half-cells have an outstanding life span,running 40,000 cycles over 8 months with a specific capacity retention of 100%at a high current density of 2000 mA g^(−1),and the target full cells deliver a high reversible specific capacity of 146 mA h g^(−1) after 2000 cycles over 2 months,with a specific capacity retention of 113%at a high current density of 500 mA g^(−1),both of which are state of the art in the field of K-ion batteries.This study might provide some insights into and potential avenues for exploration of advanced K-ion batteries with durable stability for practical applications.
基金supported by the National Natural Science Foundation of China (52075420)the National Key Research and Development Program of China (2020YFB1708400)。
文摘With its generality and practicality, the combination of partial charging curves and machine learning(ML) for battery capacity estimation has attracted widespread attention. However, a clear classification,fair comparison, and performance rationalization of these methods are lacking, due to the scattered existing studies. To address these issues, we develop 20 capacity estimation methods from three perspectives:charging sequence construction, input forms, and ML models. 22,582 charging curves are generated from 44 cells with different battery chemistry and operating conditions to validate the performance. Through comprehensive and unbiased comparison, the long short-term memory(LSTM) based neural network exhibits the best accuracy and robustness. Across all 6503 tested samples, the mean absolute percentage error(MAPE) for capacity estimation using LSTM is 0.61%, with a maximum error of only 3.94%. Even with the addition of 3 m V voltage noise or the extension of sampling intervals to 60 s, the average MAPE remains below 2%. Furthermore, the charging sequences are provided with physical explanations related to battery degradation to enhance confidence in their application. Recommendations for using other competitive methods are also presented. This work provides valuable insights and guidance for estimating battery capacity based on partial charging curves.
文摘Evaluating underground gas storage(UGS)sealing capacity is essential for its safe construction and operational efficiency.This involves evaluating both the static sealing capacity of traps during hydrocarbon accumulation and the dynamic sealing capacity of UGS under intensive gas injection and withdrawal,and alternating loads.This study detailed the methodology developed by Sinopec.The approach merges disciplines like geology,geomechanics,and hydrodynamics,employing both dynamic-static and qualitative-quantitative analyses.Sinopec's evaluation methods,grounded in the in situ stress analysis,include mechanistic studies,laboratory tests,geological surveys,stress analysis,and fluid-solid interactions.Through tests on the static and dynamic sealing capacity of UGS,alongside investigations into sealing mechanisms and the geological and geomechanical properties of cap rocks and faults,A geomechanics-rock damage-seepage mechanics dynamic coupling analysis method has been developed to predict in situ stress variations relative to pore pressure changes during UGS operations and evaluate fault sealing capacity and cap rock integrity,thereby setting the maximum operational pressures.Utilizing this evaluation technique,Sinopec has defined performance metrics and criteria for evaluating the sealing capacity of depleted gas reservoirs,enabling preliminary sealing capacity evaluations at UGS sites.These evaluations have significantly informed the design of UGS construction schemes and the evaluation of fault sealing capacity and cap rock integrity during UGS operations.
文摘Single-crystal Ni-rich cathodes are a promising candidate for high-energy lithium-ion batteries due to their higher structural and cycling stability than polycrystalline materials.However,the phase evolution and capacity degradation of these single-crystal cathodes during continuous lithation/delithation cycling remains unclear.Understanding the mapping relationship between the macroscopic electrochemical properties and the material physicochemical properties is crucial.Here,we investigate the correlation between the physical-chemical characteristics,phase transition,and capacity decay using capacity differential curve feature identification and in-situ X-ray spectroscopic imaging.We systematically clarify the dominant mechanism of phase evolution in aging cycling.Appropriately high cut-off voltages can mitigate the slow kinetic and electrochemical properties of single-crystal cathodes.We also find that second-order differential capacity discharge characteristic curves can be used to identify the crystal structure disorder of Ni-rich cathodes.These findings constitute a step forward in elucidating the correlation between the electrochemical extrinsic properties and the physicochemical intrinsic properties and provide new perspectives for failure analysis of layered electrode materials.
文摘Objective: This study aimed to evaluate the efficacy of trimetazidine on exercise capacity via a six-minute walk test in patients with ischaemic cardiomyopathy and also evaluate the effect of trimetazidine on left ventricular function via echocardiography in the same population. Methods: This prospective observational study, conducted at the National Institute of Cardiovascular Diseases in Dhaka, Bangladesh, enrolled 200 patients with ischaemic cardiomyopathy and a depressed left ventricular ejection fraction (LVEF Results: In this study (n = 200) of ischaemic cardiomyopathy patients, the mean age was 58 years, with 76% of the patients being male. All study subjects received GDMT (Guideline-Directed Medical Therapy) for angina and heart failure. Those who received the modified released form of trimetazidine developed lesions during the 1st and 2nd follow-ups, during which the LVEF, LVIDd, and six-minute walk distance significantly improved (p Conclusion: The findings of the present study demonstrated that the addition of modified-release trimetazidine to GDMT can improve exercise capacity and left ventricular function in patients with ischaemic cardiomyopathy.
文摘Background: Heart failure is a chronic and severe condition that often results from various heart diseases. Cardiac rehabilitation (CR) is currently a crucial component in managing this condition. The aim was to assess the effects of cardiac rehabilitation on physical capacity of heart failure patients. Methods: This was a cross-sectional study conducted from February 1, 2021, to June 30, 2023. We included all patients with heart failure who underwent cardiac rehabilitation. Data analysis was performed using SPSS software version 24.0, with a significance level set at p Results: The study included 87 heart failure patients, with a male-to-female ratio of 1.8. Mean age was 57.10 years (±11.75). Coronary artery disease was the primary cause of heart failure, accounting for 75.9% of cases. Atrial fibrillation was present in 4.7% of cases. Following cardiac rehabilitation, Left Ventricular Ejection Fraction increased from 40.15% to 49.48% (p = 0.001). Resting heart rate decreased significantly from 81.4 bpm to 68.3 bpm (p = 0.000), and the number of METS increased from 4.3 to 6.57 (+56.8%;p = 0.000). The mean distance covered in the 6-minute walk test significantly increased from 337.8 meters to 522.7 meters (p = 0.000), reflecting a gain of 183.5 meters. Moreover, the increase in the number of METS was more pronounced in females (p = 0.001), non-obese individuals (p = 0.000), non-diabetics (p = 0.001), non-sedentary individuals (p = 0.000), and non-smokers (p = 0.000). The study reported a low readmissions rate of 2.2% and a mortality rate of 1.1%. Conclusion: Our study demonstrates that cardiac rehabilitation is beneficial for black African heart failure patients, resulting in significant improvements in symptoms, physical and capacity.
文摘Background: Venous thromboembolism (VTE) is among the leading causes of hospital-related disability-adjusted life years lost. We aimed to determine the prevalence and determinants of functional capacity impairment six to twelve months after an acute VTE event. Methods: This was a cross-sectional study conducted between January and April 2021 in two referral hospitals of Yaoundé, including consenting adult patients admitted to these hospitals six to twelve months ago for VTE. We excluded dead patients and those with any comorbidity or symptoms limiting physical activity. The functional outcome was assessed with the six-minute walk test. Functional capacity impairment was defined as walking distance lower than the expected value. Results: We included 27 cases in this study with a mean age of 53.2 ± 14.4 years. The prevalence of functional capacity impairment was 29.6% (95% CI: 14.8 - 48.1). Factors associated with poor functional outcome were obesity (OR: 59.5;95% CI: 4.6 - 767.2;p - 207.4;p = 0.017), massive PE (OR: 30;95% CI: 2.5 - 354;p = 0.004), and poor adherence to treatment (OR: 30.3;95% CI: 2.5 - 333.3;p = 0.004). Conclusion: Functional capacity impairment is common in the medium-term after VTE and factors associated with this poor outcome are obesity, the severity of the VTE, and poor adherence to treatment.
文摘The present study has been carried out on a total of 50 available plant species to assess their dust-capturing capacity and biochemical performances in and around open cast granite mine areas of Jhansi district and Bundelkhand University campus treated as control site. Plant species existing under a polluted environment for a long time may be considered as potentially resistant species and recommended for green belt design in mining areas, especially to cope with dust pollution. Results showed the pollution level, especially of mining-originated dust particles holding capacity of leaves and effects of different biochemical parameters (Total Chlorophyll, Protein and Carotenoid) of existing plant species both from mining areas as well as from Bundelkhand University campus. Based on their performances, Tectona grandis L., Ficus hispida L., Calotropis procera Aiton., Butea monosperma Lam. and Ficus benghalensis L., etc. are highly tolerant species while Ficus infectoria L., Artocarpus heterophyllus Lam., Ipomoea purpurea L., Allianthus excelsa Roxb. and Bauhinia variegata L. are intermediate tolerant species. T. grandis had shown the highest dust-holding capacity (2.566 ± 0.0004 mg/cm2) whereas Albizia procera (0.018 ± 0.0002 mg/cm2) was found to be the lowest dust-holding capacity. Our findings also showed that the T. grandis and F. hispida have significant dust deposition with minimal effect of dust on their leaf chlorophyll (17.447 ± 0.019 mg/g and 14.703 ± 0.201 mg/g), protein (0.699 ± 0.001 mg/g and 0.604 ± 0.002 mg/g) and carotenoid (0.372 ± 0.003 mg/g and 0.354 ± 0.003 mg/g) content respectively among all selected plant species. Therefore, in the present investigation, plant species with high tolerance to high dust-holding capacity on their leaf surfaces are preferable for green corridors as open cast granite mines and their adjacent areas.
文摘This paper introduces an innovative approach to the synchronized demand-capacity balance with special focus on sector capacity uncertainty within a centrally controlled collaborative air traffic flow management(ATFM)framework.Further with previous study,the uncertainty in capacity is considered as a non-negligible issue regarding multiple reasons,like the impact of weather,the strike of air traffic controllers(ATCOs),the military use of airspace and the spatiotemporal distribution of nonscheduled flights,etc.These recessive factors affect the outcome of traffic flow optimization.In this research,the focus is placed on the impact of sector capacity uncertainty on demand and capacity balancing(DCB)optimization and ATFM,and multiple options,such as delay assignment and rerouting,are intended for regulating the traffic flow.A scenario optimization method for sector capacity in the presence of uncertainties is used to find the approximately optimal solution.The results show that the proposed approach can achieve better demand and capacity balancing and determine perfect integer solutions to ATFM problems,solving large-scale instances(24 h on seven capacity scenarios,with 6255 flights and 8949 trajectories)in 5-15 min.To the best of our knowledge,our experiment is the first to tackle large-scale instances of stochastic ATFM problems within the collaborative ATFM framework.
文摘This advanced paper presents a new approach to improving image steganography using the Ant Colony Optimization(ACO)algorithm.Image steganography,a technique of embedding hidden information in digital photographs,should ideally achieve the dual purposes of maximum data hiding and maintenance of the integrity of the cover media so that it is least suspect.The contemporary methods of steganography are at best a compromise between these two.In this paper,we present our approach,entitled Ant Colony Optimization(ACO)-Least Significant Bit(LSB),which attempts to optimize the capacity in steganographic embedding.The approach makes use of a grayscale cover image to hide the confidential data with an additional bit pair per byte,both for integrity verification and the file checksumof the secret data.This approach encodes confidential information into four pairs of bits and embeds it within uncompressed grayscale images.The ACO algorithm uses adaptive exploration to select some pixels,maximizing the capacity of data embedding whileminimizing the degradation of visual quality.Pheromone evaporation is introduced through iterations to avoid stagnation in solution refinement.The levels of pheromone are modified to reinforce successful pixel choices.Experimental results obtained through the ACO-LSB method reveal that it clearly improves image steganography capabilities by providing an increase of up to 30%in the embedding capacity compared with traditional approaches;the average Peak Signal to Noise Ratio(PSNR)is 40.5 dB with a Structural Index Similarity(SSIM)of 0.98.The approach also demonstrates very high resistance to detection,cutting down the rate by 20%.Implemented in MATLAB R2023a,the model was tested against one thousand publicly available grayscale images,thus providing robust evidence of its effectiveness.
基金funded by the National Natural Science Foundation of China (Grant No. 11875031)the key research projects of Natural Science of Anhui Provincial Colleges and Universities (Grant No. 2022AH050252)。
文摘As a common transportation facility, speed humps can control the speed of vehicles on special road sections to reduce traffic risks. At the same time, they also cause instantaneous traffic emissions. Based on the classic instantaneous traffic emission model and the limited deceleration capacity microscopic traffic flow model with slow-to-start rules, this paper has investigated the impact of speed humps on traffic flow and the instantaneous emissions of vehicle pollutants in a single lane situation. The numerical simulation results have shown that speed humps have significant effects on traffic flow and traffic emissions. In a free-flow region, the increase of speed humps leads to the continuous rise of CO_(2), NO_(X) and PM emissions. Within some density ranges, one finds that these pollutant emissions can evolve into some higher values under some random seeds. Under other random seeds, they can evolve into some lower values. In a wide moving jam region, the emission values of these pollutants sometimes appear as continuous or intermittent phenomenon. Compared to the refined Na Sch model, the present model has lower instantaneous emissions such as CO_(2), NO_(X) and PM and higher volatile organic components(VOC) emissions. Compared to the limited deceleration capacity model without slow-to-start rules, the present model also has lower instantaneous emissions such as CO_(2), NO_(X) and PM and higher VOC emissions in a wide moving jam region. These results can also be confirmed or explained by the statistical values of vehicle velocity and acceleration.
基金the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(2020R1A2C1A01011131)the Energy Cloud R&D Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Science,ICT(2019M3F2A1073164).
文摘Base isolators used in buildings provide both a good acceleration reduction and structural vibration control structures.The base isolators may lose their damping capacity over time due to environmental or dynamic effects.This deterioration of them requires the determination of the maintenance and repair needs and is important for the long-termisolator life.In this study,an artificial intelligence prediction model has been developed to determine the damage and maintenance-repair requirements of isolators as a result of environmental effects and dynamic factors over time.With the developed model,the required damping capacity of the isolator structure was estimated and compared with the previously placed isolator capacity,and the decrease in the damping property was tried to be determined.For this purpose,a data set was created by collecting the behavior of structures with single degrees of freedom(SDOF),different stiffness,damping ratio and natural period isolated from the foundation under far fault earthquakes.The data is divided into 5 different damping classes varying between 10%and 50%.Machine learning model was trained in damping classes with the data on the structure’s response to random seismic vibrations.As a result of the isolator behavior under randomly selected earthquakes,the recorded motion and structural acceleration of the structure against any seismic vibration were examined,and the decrease in the damping capacity was estimated on a class basis.The performance loss of the isolators,which are separated according to their damping properties,has been tried to be determined,and the reductions in the amounts to be taken into account have been determined by class.In the developed prediction model,using various supervised machine learning classification algorithms,the classification algorithm providing the highest precision for the model has been decided.When the results are examined,it has been determined that the damping of the isolator structure with the machine learning method is predicted successfully at a level exceeding 96%,and it is an effective method in deciding whether there is a decrease in the damping capacity.
基金supported in part by the National Key Research and Development Program of China(No.2022YFB3305403)Project of basic research funds for central universities(2022CDJDX006)+1 种基金Talent Plan Project of Chongqing(No.cstc2021ycjhbgzxm0295)National Natural Science Foundation of China(No.52111530194)。
文摘Accurate capacity estimation is of great importance for the reliable state monitoring,timely maintenance,and second-life utilization of lithium-ion batteries.Despite numerous works on battery capacity estimation using laboratory datasets,most of them are applied to battery cells and lack satisfactory fidelity when extended to real-world electric vehicle(EV)battery packs.The challenges intensify for large-sized EV battery packs,where unpredictable operating profiles and low-quality data acquisition hinder precise capacity estimation.To fill the gap,this study introduces a novel data-driven battery pack capacity estimation method grounded in field data.The proposed approach begins by determining labeled capacity through an innovative combination of the inverse ampere-hour integral,open circuit voltage-based,and resistance-based correction methods.Then,multiple health features are extracted from incremental capacity curves,voltage curves,equivalent circuit model parameters,and operating temperature to thoroughly characterize battery aging behavior.A feature selection procedure is performed to determine the optimal feature set based on the Pearson correlation coefficient.Moreover,a convolutional neural network and bidirectional gated recurrent unit,enhanced by an attention mechanism,are employed to estimate the battery pack capacity in real-world EV applications.Finally,the proposed method is validated with a field dataset from two EVs,covering approximately 35,000 kilometers.The results demonstrate that the proposed method exhibits better estimation performance with an error of less than 1.1%compared to existing methods.This work shows great potential for accurate large-sized EV battery pack capacity estimation based on field data,which provides significant insights into reliable labeled capacity calculation,effective features extraction,and machine learning-enabled health diagnosis.
基金financially supported by the National Natural Science Foundation of China(22208253)the Key Laboratory of Hubei Province for Coal Conversion and New Carbon Materials(Wuhan University of Science and Technology,WKDM202202).
文摘Ionic liquids(ILs),because of the advantages of low volatility,good thermal stability,high gas solubility and easy recovery,can be regarded as the green substitute for traditional solvent.However,the high viscosity and synthesis cost limits their application,the hybrid solvent which combining ILs together with others especially water can solve this problem.Compared with the pure IL systems,the study of the ILs-H_(2)O binary system is rare,and the experimental data of corresponding thermodynamic properties(such as density,heat capacity,etc.)are less.Moreover,it is also difficult to obtain all the data through experiments.Therefore,this work establishes a predicted model on ILs-water binary systems based on the group contribution(GC)method.Three different machine learning algorithms(ANN,XGBoost,LightBGM)are applied to fit the density and heat capacity of ILs-water binary systems.And then the three models are compared by two index of MAE and R^(2).The results show that the ANN-GC model has the best prediction effect on the density and heat capacity of ionic liquid-water mixed system.Furthermore,the Shapley additive explanations(SHAP)method is harnessed to scrutinize the significance of each structure and parameter within the ANN-GC model in relation to prediction outcomes.The results reveal that system components(XIL)within the ILs-H_(2)O binary system exert the most substantial influence on density,while for the heat capacity,the substituents on the cation exhibit the greatest impact.This study not only introduces a robust prediction model for the density and heat capacity properties of IL-H_(2)O binary mixtures but also provides insight into the influence of mixture features on its density and heat capacity.
基金supported by the National Natural Science Foundation of China(51978345,52278264).
文摘A theoretical analysis of upward deflection and midspan deflection of prestressed bamboo-steel composite beams is presented in this study.The deflection analysis considers the influences of interface slippage and shear deformation.Furthermore,the calculation model for flexural capacity is proposed considering the two stages of loading.The theoretical results are verified with 8 specimens considering different prestressed load levels,load schemes,and prestress schemes.The results indicate that the proposed theoretical analysis provides a feasible prediction of the deflection and bearing capacity of bamboo-steel composite beams.For deflection analysis,the method considering the slippage and shear deformation provides better accuracy.The theoretical method for bearing capacity matches well with the test results,and the relative errors in the serviceability limit state and ultimate limit state are 4.95%and 5.85%,respectively,which meet the accuracy requirements of the engineered application.
基金funded by the Natural Science Foundation of Shandong Province (ZR2021MD061ZR2023QD025)+3 种基金China Postdoctoral Science Foundation (2022M721972)National Natural Science Foundation of China (41174098)Young Talents Foundation of Inner Mongolia University (10000-23112101/055)Qingdao Postdoctoral Science Foundation (QDBSH20230102094)。
文摘Conventional machine learning(CML)methods have been successfully applied for gas reservoir prediction.Their prediction accuracy largely depends on the quality of the sample data;therefore,feature optimization of the input samples is particularly important.Commonly used feature optimization methods increase the interpretability of gas reservoirs;however,their steps are cumbersome,and the selected features cannot sufficiently guide CML models to mine the intrinsic features of sample data efficiently.In contrast to CML methods,deep learning(DL)methods can directly extract the important features of targets from raw data.Therefore,this study proposes a feature optimization and gas-bearing prediction method based on a hybrid fusion model that combines a convolutional neural network(CNN)and an adaptive particle swarm optimization-least squares support vector machine(APSO-LSSVM).This model adopts an end-to-end algorithm structure to directly extract features from sensitive multicomponent seismic attributes,considerably simplifying the feature optimization.A CNN was used for feature optimization to highlight sensitive gas reservoir information.APSO-LSSVM was used to fully learn the relationship between the features extracted by the CNN to obtain the prediction results.The constructed hybrid fusion model improves gas-bearing prediction accuracy through two processes of feature optimization and intelligent prediction,giving full play to the advantages of DL and CML methods.The prediction results obtained are better than those of a single CNN model or APSO-LSSVM model.In the feature optimization process of multicomponent seismic attribute data,CNN has demonstrated better gas reservoir feature extraction capabilities than commonly used attribute optimization methods.In the prediction process,the APSO-LSSVM model can learn the gas reservoir characteristics better than the LSSVM model and has a higher prediction accuracy.The constructed CNN-APSO-LSSVM model had lower errors and a better fit on the test dataset than the other individual models.This method proves the effectiveness of DL technology for the feature extraction of gas reservoirs and provides a feasible way to combine DL and CML technologies to predict gas reservoirs.
基金sopported by National Natural Science Foundation of China(31960457)Jiangxi Province National Science and Technology Prizes Backup Project and Cultivation Plan(20212AEI91001).
文摘Gut microbiota plays an important role in food allergy.The immunoglobulin G(IgG)/immunoglobulin E(IgE)binding capacity and human gut microbiota changes of digestion products derived from glycated ovalbumin(OVA)were investigated.Gastrointestinal digestion effectively destroyed the primary structure of glycated OVA,resulting in a significantly higher digestibility than gastric digestion,and more abundant peptides<3 kDa.Moreover,gastric and gastrointestinal digestion products have different fluorescence quenching and red shift of fluorescence peaks,and possess different conformational structures.These changes resulted in a decrease in 28.7%of the IgE binding capacity of gastrointestinal digestion products beyond that of pepsin.Moreover,gastrointestinal digestion products of glycated OVA increased significantly the proportion of Subdoligranulum,Collinsella,and Bifidobacterium.Therefore,gastrointestinal digestion products of glycated OVA altered human intestinal microbiota,reducing the risk of potential allergy.
基金financially supported by the National Natural Science Foundation of China(Grant No.52171285)。
文摘A dent is a common type of defects for submarine pipeline.For submarine pipelines,high hydrostatic pressure and internal pressure are the main loads.Once pipelines bend due to complex subsea conditions,the compression strain capacity may be exceeded.Research into the local buckling failure and accurate prediction of the compressive strain capacity are important.A finite element model of a pipeline with a dent is established.Local buckling failure under a bending moment is investigated,and the compressive strain capacity is calculated.The effects of different parameters on pipeline local buckling are analyzed.The results show that the dent depth,external pressure and internal pressure lead to different local buckling failure modes of the pipeline.A higher internal pressure indicates a larger compressive strain capacity,and the opposite is true for external pressure.When the ratio of external pressure to collapse pressure of intact pipeline is greater than 0.1,the deeper the dent,the greater the compressive strain capacity of the pipeline.And as the ratio is less than 0.1,the opposite is true.On the basis of these results,a regression equation for predicting the compressive strain capacity of a dented submarine pipeline is proposed,which can be referred to during the integrity assessment of a submarine pipeline.
文摘Background: In the context of the fight against HIV, a lack of skills in monitoring and evaluating the personnel in charge of activities has been identified at the national level. It was the subject of a priority axis of the national plan for monitoring and evaluating the fight against HIV (2006-2010) that was aimed at strengthening the capacities of actors in this area. To increase the critical mass of competent human resources in the short term, the National Institute of Public Health (NIPH) of Côte d’Ivoire organized monitoring and evaluation training sessions for healthcare professionals from 2011 to 2016. Methods: A single case study with multiple levels of analysis was carried out, combining a qualitative survey and a literature review. An evaluation was carried out six months after each training session. In addition, the results of the pre- and post-tests and of the daily and final evaluations that accompanied the various training sessions were used to provide further information. The qualitative data collected were analyzed using INVIVO 15 software. Results: Some 89 health professionals (69% men and 31% women) working at the national level (51% at the central level, including 58% in health programs) and in development partner agencies (37%) participated in this capacity building program. Most participants were senior health managers (56%), data managers (23%), and statisticians and computer scientists (10%). Almost all the trainings were financed by 16 technical and financial partners (85%), mainly the MEASURE Evaluation project (27%). Conclusion: M&E training, despite all its imperfections, has made it possible to identify M&E training needs at the national level and to increase the critical mass of national skills and to have some culture in M&E.
