Life-Cycle Bearing Capacity for Pre-Stressed T-beams Based on Full-Scale Destructive Test

To investigate the evolution of load-bearing characteristics of pre-stressed beams throughout their service life and to provide a basis for accurately assessing the actual working state of damaged pre-stressed concrete T-beams,destructive tests were conducted on full-scale pre-stressed concrete beams.Based on the measurement and ana-lysis of beam deflection,strain,and crack development under various loading levels during the research tests,combined with the verification coefficient indicators specified in the codes,the verification coefficients of bridges at different stages of damage can be examined.The results indicate that the T-beams experience complete,incom-plete linear,and non-linear stages during the destructive test process.In the complete linear elastic stage,both the deflection and bottom strain verification coefficients comply with the specifications,indicating a good structural load-bearing capacity no longer adheres to the code’s requirements.In the non-linear stage,both coefficients exhi-bit a sharp increase,resulting in a further decrease in the structure’s load-bearing capacity.According to the pro-visions of the current code,the beam can be in the incomplete linear stage when both values fall within the code’s specified range.The strain verification coefficient sourced from the compression zone at the bottom of theflange is not recommended for assessing the bridge’s load-bearing capacity.

Approach to estimating non-point pollutant load removal rates based on water environmental capacity: a case study in Shenzhen

An innovative approach based on water environmental capacity for non-point source NPS pollution removal rate estimation was discussed by using both univariate and multivariate data analysis.Taking Shenzhen city as the study case a 67% to 74% NPS pollutant load removal rate can lead to meeting the chemical oxygen demand COD pollution control target for most watersheds.In contrast it is hardly to achieve the ammonia nitrogen NH4-N total phosphorus TP and biological oxygen demand BOD5 pollution control target by simply removing NPS pollutants. This highlights that the pollution control strategies should be taken according to different pollutant species and sources in different watersheds rather than one-size-fits-all .

Estimating model for urban carrying capacity on bike-sharing

As the demand for bike-sharing has been increasing,the oversupply problem of bike-sharing has occurred,which leads to the waste of resources and disturbance of the urban environment.In order to regulate the supply volume of bike-sharing reasonably,an estimating model was proposed to quantify the urban carrying capacity(UCC)for bike-sharing through the demand data.In this way,the maximum supply volume of bike-sharing that a city can accommodate can be obtained.The UCC on bike-sharing is reflected in the road network carrying capacity(RNCC)and parking facilities’carrying capacity(PFCC).The space-time consumption method and density-based spatial clustering of application with noise(DBSCAN)algorithm were used to explore the RNCC and PFCC for bike-sharing.Combined with the users’demand,the urban load ratio on bike-sharing can be evaluated to judge whether the UCC can meet users’demand,so that the supply volume of bike-sharing and distribution of the related facilities can be adjusted accordingly.The application of the model was carried out by estimating the UCC and load ratio of each traffic analysis zone in Nanjing,China.Compared with the field survey data,the effect of the proposed algorithm was verified.

A comparison study on structure-function relationship of polysaccharides obtained from sea buckthorn berries using different methods:antioxidant and bile acid-binding capacity

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.

An analysis of four methodologies for estimating highway capacity from ITS data

With the recent advent of Intelligent Transporta- tion Systems （ITS）, and their associated data collection and archiving capabilities, there is now a rich data source for transportation professionals to develop capacity values for their own jurisdictions. Unfortunately, there is no consensus on the best approach for estimating capacity from ITS data. The motivation of this paper is to compare and contrast four of the most popular capacity estimation techniques in terms of （1） data requirements, （2） modeling effort required, （3） esti- mated parameter values, （4） theoretical background, and （5） statistical differences across time and over geographically dispersed locations. Specifically, the first method is the maximum observed value, the second is a standard funda- mental diagram curve fitting approach using the popular Van Aerde model, the third method uses the breakdown identifi- cation approach, and the fourth method is the survival prob- ability based on product limit method. These four approaches were tested on two test beds： one is located in San Diego, California, U.S., and has data from 112 work days; the other is located in Shanghai, China, and consists of 81 work days. It was found that, irrespective of the estimation methodology and the definition of capacity, the estimated capacity can vary considerably over time. The second finding was that, as ex- pected, the different approaches yielded different capacity results. These estimated capacities varied by as much as 26 % at the San Diego test site and by 34 % at the Shanghai test site. It was also found that each of the methodologies has advantages and disadvantages, and the best method will be the function of the available data, the application, and the goals of the modeler. Consequently, it is critical for users of automatic capacity estimation techniques, which utilize ITS data, to understand the underlying assumptions of each of the different approaches.

A comparative study of data-driven battery capacity estimation based on partial charging curves

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.

Durable K-ion batteries with 100% capacity retention up to 40,000 cycles

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.

Borana rangeland of southern Ethiopia:Estimating biomass production and carrying capacity using field and remote sensing data

Assessing rangeland productivity is critical to reduce ecological degradation and promote sustainable livestock management.Here,we estimated biomass productivity and carrying capacity dynamics in the Borana rangeland of southern Ethiopia by using field-based data and remote sensing data(i.e.,normalized difference vegetation index(NDVI)).Data was collected from both rainy and dry seasons when biomass production was high and low respectively.Results of linear regression showed that both biomass production(R^(2)_(adj)=0.672)and NDVI value(R^(2)_(adj)=0.471)were significantly decreased from 1990 to 2019.Field data and NDVI values for mean annual biomass showed a significant linear relationship.The model accuracy in the annual relationship between the observed and predicted biomass values was strong(R^(2)_(adj)=0.986)but with high standard error,indicating that the observed biomass production in the rangeland area was not in good condition as compared with the predicted one.This study suggests that,using NDVI data and field-based data in combined way has high potential to estimate rangeland biomass and carrying capacity dynamics at extensively grazed arid and semi-arid rangelands.And to use for estimating stoking rates and predicting future management techniques for decision making.

Implications of 1.5 K climate warming on warm-season ozone exposure and atmospheric oxidation capacity in China

Surface ozone(O_(3))poses significant threats to public health,agricultural crops,and plants in natural ecosystems.Global warming is likely to increase future O_(3)mainly by altering atmospheric photochemical reactions and enhancing biogenic volatile organic compound(BVOC)emissions.To assess the impacts of the future 1.5 K climate target on O_(3)concentrations and ecological O_(3)exposure in China,numerical simulations were conducted using the CMAQ(Community Multiscale Air Quality)model during April-October 2018.Ecological O_(3)exposure was estimated using six indices(i.e.,M7,M24,N100,SUM60,W126,and AOT40f).The results show that the temperature rise increases the MDA8 O_(3)(maximum daily eight-hour average O_(3))concentrations by∼3 ppb and the number of O_(3)exceedance days by 10-20 days in the North China Plain(NCP),Yangtze River Delta(YRD),and Sichuan Basin(SCB)regions.All O_(3)exposure indices show substantial increases.M24 and M7 in eastern and southern China will rise by 1-3 ppb and 2-4 ppb,respectively.N100 increases by more than 120 h in the surrounding regions of Beijing.SUM60 increases by greater than 9 ppm h^(−1),W126 increases by greater than 15 ppm h^(−1)in Shaanxi and SCB,and AOT40f increases by 6 ppm h^(−1)in NCP and SCB.The temperature increase also promotes atmospheric oxidation capacity(AOC)levels,with the higher AOC contributed by OH radicals in southern China but by NO_(3)radicals in northern China.The change in the reaction rate caused by the temperature increase has a greater influence on O_(3)exposure and AOC than the change in BVOC emissions.

Sealing capacity evaluation of underground gas storage under intricate geological conditions

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.

Methods for Estimating the Ultimate Bearing Capacity of Layered Foundations

The Meyerhof and Hanna′s(M-H) method to estimate the ultimate bearing capacity of layered foundations was improved. The experimental results of the load tests in Tianjin New Harbor were compared with predictions with the method recommended by the code for the foundations of harbor engineering, i.e. Hansen′s method and the improved M-H method. The results of the comparisons implied that the code and the improved M-H method could give a better prediction.

Mating model on production capacity for the system of cutting coal and drawing top-coal in FMMSC

Being a safe and highly-efficient mining method, fully mechanized mining with sublevel caving （FMMSC） was extensively employed in Chinese coal mines with thick seam. In order to make drawing top-coal furthest to parallel work with shearer cutting coal, decrease failure ratio of rear scraper conveyor and increase safe production capacity of equipments, based on production technology, set up the mating model of safe production capacity of equipments for the system of drawing top-coal and shearer cutting coal in coal face with sublevel caving. It is mean capability of drawing top-coal adapted to the capability of shearer cutting coal in a working circle in the coal face that was deduced. The type selection of equipment of rear scraper conveyor can be tackled with this mating model. The model was applied in FMMSC in Yangcun Coal Mine, Yima Coal Group of China. With the mating light-equipments, the coal output in coal face attained 1.05 Mt in 2004. It gained better technical-economic benefit.

Insight into the capacity degradation and structural evolution of single-crystal Ni-rich cathodes

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.

Effect of Trimetazidine on Functional Capacity in Patient with Ischaemic Cardiomyopathy (TOFCAPI)

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.

Effect of Cardiac Rehabilitation on Physical Capacity of Heart Failure Patients in Senegal

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.

Functional Capacity of Patients with Venous Thromboembolic Disease Six to Twelve Months after Treatment

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.

Dust-Holding Capacity and Bio-Chemical Changes of Plant Species Growing in an Around Opencast Mining Area of Bundelkhand Region of Uttar Pradesh, India

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.

An Improved Image Steganography Security and Capacity Using Ant Colony Algorithm Optimization

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.

Effect of speed humps on instantaneous traffic emissions in a microscopic model with limited deceleration capacity

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.

Prediction of Damping Capacity Demand in Seismic Base Isolators via Machine Learning

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.