Technical Analysis of Highway Bridge Static Load Test

Highway bridges are an important part of the transportation industry and can promote social economic construction and development.In actual operation,highway bridges are often damaged due to overload and natural factors,which tend to affect the safety and shorten the service life of these bridges.Assessing the overall state and performance of highway bridges is therefore a key element.Static load test,which is a type of sustainable detection experiment,has many advantages,including low cost,high efficiency,and high accuracy.In this paper,the bridge structure is analyzed through the application of theoretical calculations and relevant comparisons,so as to judge the operating state of the bridge.

Analysis on On-Site Asphalt Pavement Quality Inspection Technology in Highway Engineering

The acceleration of urbanization has promoted the increase in the number of urban highway projects,resulting in an increase of emphasis on the quality of urban highway projects.The quality and safety of highway construction directly affects the driving comfort,safety,and service life after it is put into operation.Among them,asphalt pavement is an important structure in highway construction,and it is also a key link that directly affects the construction quality.In order to ensure the quality of construction,it is necessary to strengthen on-site testing during the construction process to discover problems in time,and to ensure that the construction is up to standard.This paper mainly presents an analysis on the necessity and application of on-site quality inspection technology for asphalt pavement construction of highway engineering,and outlines measures to improve highway engineering construction testing technology.

Application of Long-Span Continuous Bridge Technology in Bridge Construction

In order to promote the rapid development of urbanization in our country,it is necessary to improve the construction level and technology of bridge engineering.For long-span continuous bridge technology,it has the characteristics of wide application range,various applicable conditions,and short construction period.Therefore,it is necessary to pay attention to the application of long-span continuous bridge technology.This article mainly analyzes its application in bridge construction,hoping to provide some reference for future use.

Analysis of Highway Roadbed Performance Evaluation Technology

With the continuous development of China,the requirements for road construction are also increasing.Among them,strengthening the performance of roadbed test can effectively improve road construction.Besides,it is also crucial to perform suitable tests in a timely manner.Therefore,highway inspection technology should be improved for the continuous development of highway construction,which will be explained in this paper,in hopes of improving the construction of highway in China.

Load Test Analysis and Research on Long-Span Concrete Continuous Rigid Frame Bridge

Based on the as-built load test of a large bridge,this paper introduces the procedure of the prestressed concrete continuous rigid frame bridge load test.Numerical analysis of the bridge was carried out by simulating and establishing a finite element model,and comparative analysis was carried out with the measured values.The results show that the calculated values were basically consistent with the measured values,which showed that the establishment method of the model was reasonable,and the mechanical performance of the bridge met the service requirements of the designed live load.

Quality Control Measures of Bored Pile in Bridge Construction

In order to improve the quality of bored piles in bridge construction and ensure the overall quality of the bridge,we analyzed a series of problems in the construction process of bored piles,then propose corresponding quality control measures,in hopes of improving quality control of bored piles in bridge construction in our country.

Transcriptome profiling and RXR gene family identification reveals the molecular mechanism of rapid aging after spawning of cuttlefish Sepiella japonica

Sepiella japonica is a worldwide marine cuttlefish species of high economic value.S.japonica routinely modifying behaviors in reproductive life,such as rapid aging until death after spawning,has been recognized in artificial breeding.However,reproductive behavior at the level of genes is rarely reported,thus,the research on the genetic basis of behavior,reproduction,and artificial breeding was limited.We applied RNA-seq in different stages of reproduction to investigate the reason of rapid aging after spawning,pre-maturity,pre-spawning after maturity,and post-spawning.The retinoid X receptor(RXR)gene family in S.japonica was identified,and 1343–1452 differentially expressed genes(DEGs)in all 3 stages of reproductive life were identified from pairwise m RNA comparisons.Furthermore,through the GO term and KEGG analysis,S.japonica could handle neuronal development and network formation before maturity and have a functional degradation of neural communication,signal transduction,vision,and gene expression after spawning.Eight Sj RXRαs have been identified and they played different roles in growth development or reproduction.Therefore,the regulation of several channels and receptors is the intrinsic molecular mechanism of rapid aging after spawning in S.japonica.This study revealed the survival strategy and provided fundamental data on the level of genes for understanding the reproductive behavior and the reproduction of S.japonica.

Responses of soil nematode community to monoculture or mixed culture of a grass and a legume forage species in China

Mixed cultivation of fast-growing grasses and nitrogen(N)-fixing legumes for forage production is widely considered effective for obtaining sustained high forage yields without depleting soil N levels.However,the effects of monoculture and mixed culture of these species on soil food webs are poorly understood.In this study,soil nematode communities were examined as indicators of the soil food web structure of monoculture and mixed culture of grass and legume at three N levels,i.e.,338(low),450(moderate),and 675(high)kg N ha-1 year-1,across 2 years in wet and dry seasons,using the grass Paspalum wetsfeteini and the legume Medicago sativa(alfalfa),both commonly cultivated worldwide.Repeated-measures analysis of covariance showed that compared with grass monoculture,legume monoculture and grass-legume mixture increased abundances of herbivorous,bacterivorous,and fungivorous nematodes in the soil food web under the low and moderate N fertilization levels.Principal response curve results showed that the abundance of Helicotylenchus,a plant parasite,was significantly higher under legume monoculture than other planting systems at the low N fertilization level.Structural equation model analysis indicated that the legume increased bacterivore abundance,while increasing N fertilization decreased omnivore abundance.The legume might increase the quantity and quality of food resources for soil biota,resulting in the bottom-up control of soil nematode communities.Our results indicate that targeted control of a soilborne pathogen,Helicotylenchus,is required in alfalfa-based planting systems.In addition,high inorganic N application,which is detrimental to legume-rhizobia symbiosis,nullified the otherwise positive effects of legumes on soil nematodes.

Deep Learning-Assisted Visualized Fluorometric Sensor Array for Biogenic Amines Detection

Biogenic amines(BAs)are important biomarkers for monitoring food quality and assisting in the diagnosis of disease.Facial,portable,accurate and high-throughput BAs detection is still challenging by the specific sensor compounds development or the complicated instrument operation.Deep learning(DL)algorithms are blooming for their superiority on the nonlinear and multidimensional data analysis,which endow the great advantage for the artificial intelligence assisted large sample analysis of the environmental or daily health monitoring.In this work,we developed a deep learning-assisted visualized fluorometric array-based sensing method.Two commercial fluorescent dyes were selected and combined into sensor arrays.Variation in the alkalinity of BAs causes significant and distinct fluorescence changes of the dyes.In conjunction with pattern recognition by the pretrained CNN models,the sensor array clearly differentiates seven BAs with 99.29%prediction accuracy and allows rapid single and multi-component quantification with a volume fraction range from 200 cm^(3)/m^(3)to 2500 cm^(3)/m^(3).This method also provides a new way for meat freshness monitoring.We envision that this novel analytical method for BAs can be used as an alternative and promising tool for the detection of a wider variety of analytes.