Numerical Simulation-Based Analysis of the Impact of Overloading on Segmentally Assembled Bridges

Segmentally assembled bridges are increasinglyfinding engineering applications in recent years due to their unique advantages,especially as urban viaducts.Vehicle loads are one of the most important variable loads acting on bridge structures.Accordingly,the influence of overloaded vehicles on existing assembled bridge structures is an urgent concern at present.This paper establishes thefinite element model of the segmentally assembled bridge based on ABAQUS software and analyzes the influence of vehicle overload on an assembled girder bridge struc-ture.First,afinite element model corresponding to the target bridge is established based on ABAQUS software,and the load is controlled to simulate vehicle movement in each area of the traveling zone at different times.Sec-ond,the key cross-sections of segmental girder bridges are monitored in real time based on the force character-istics of continuous girder bridges,and they are compared with the simulation results.Finally,a material damage ontology model is introduced,and the structural damage caused by different overloading rates is compared and analyzed.Results show that thefinite element modeling method is accurate by comparing with on-site measured data,and it is suitable for the numerical simulation of segmental girder bridges;Dynamic sensors installed at 1/4L,1/2L,and 3/4L of the segmental girder main beams could be used to identify the dynamic response of segmental girder bridges;The bottom plate of the segmental girder bridge is mostly damaged at the position where the length of the precast beam section changes and the midspan position.With the increase in load,damage in the direction of the bridge develops faster than that in the direction of the transverse bridge.Thefindings of this study can guide maintenance departments in the management and maintenance of bridges and vehicles.

Male parent birds exert more effort to reproduce in two desert passerines

Background:Parental investment by birds is limited by the habitat environment,and a male parent increases its effort to reproduce in birds that live in high-altitude areas.Methods:A study of the reproductive behaviour of the Saxaul Sparrow(Passer ammodendri)and the Isabelline Shrike(Lanius isabellinus)was carried out at the Gansu An’xi Extremely Arid Desert National Nature Reserve in northwest China to determine the reproductive input of passerine species in desert habitats.Results:In Saxaul Sparrows,compared to the female parent,the male parent exhibited a significantly higher fre-quency of nest-defense behaviour(chirping and warning)during nesting,hatching and feeding periods.In addition,in comparison to the female parent,the male parent exhibited almost equal frequencies of nesting and incubation but fed nestlings significantly more times.Similar to the male sparrows,the feeding rates of the male Isabelline Shrikes were significantly higher than those of the females.The hatching rate and fledging rate of the Saxaul Sparrow on aver-age in this study were 81.99 and 91.92%,respectively,while those of the shrike were 69.00 and 96.53%,respectively.Conclusions:These two different passerine species living in the same desert environment exhibited the same trend in their reproductive investments.Adapting to desert environments is a strategy that may have evolved in passerines where male parent birds put more effort than females into reproduction to ensure high reproductive output.

Enhanced Reconfigurable Intelligent Surface Assisted mmWave Communication: A Federated Learning

Reconfigurable intelligent surface(RIS)has been proposed as a potential solution to improve the coverage and spectrum efficiency for future wireless communication.However,the privacy of users’data is often ignored in previous works,such as the user’s location information during channel estimation.In this paper,we propose a privacy-preserving design paradigm combining federated learning(FL)with RIS in the mmWave communication system.Based on FL,the local models are trained and encrypted using the private data managed on each local device.Following this,a global model is generated by aggregating them at the central server.The optimal model is trained for establishing the mapping function between channel state information(CSI)and RIS’configuration matrix in order to maximize the achievable rate of the received signal.Simulation results demonstrate that the proposed scheme can effectively approach to the theoretical value generated by centralized machine learning(ML),while protecting user’privacy.

Egg investment strategies adopted by a desertic passerine, the Saxaul Sparrow(Passer ammodendri)

Background:As one of the reproductive strategies adopted by bird species,variation in investment in egg production and its influencing factors are important and well-studied subjects.Intraclutch changes in egg size associated with laying order may reflect a strategy of"brood survival"or"brood reduction"adopted by female birds in different situations.Methods:We conducted field studies on the breeding parameters of the Saxaul Sparrow(Passer ammodendri)in Gansu Province,China from 2010 to 2017,to clarify the factors affecting the egg investment and reproductive performance of this passerine species.Results:Our results revealed significant differences in clutch size,egg size and the fledging rate between the first and second brood of Saxaul Sparrows and suggested that this typical desert species allocates more breeding resources to the more favourable second brood period,leading to greater reproductive output.Female body size presented a positive relationship with egg size,and male body size presented positive relationships with clutch size and hatchability.The females that started their clutches later laid more eggs,and hatchability and the fledging rate also increased with a later laying date in the first brood period.With successive eggs laid within the 5-egg clutches(the most frequent clutch size),egg size increased for the first three eggs and then significantly decreased.Conclusions:Our results indicate that female Saxaul Sparrows increased egg investment because of good quality of paired males and good environmental conditions.The intraclutch variation of egg size suggests that this species inhabiting an arid environment adopts a"brood reduction"strategy.

Electrical transport properties of Fe Se single crystal under high magnetic field

Understanding the normal electronic state is crucial for unveiling the mechanism of unconventional superconductivity(SC). In this paper, by applying a magnetic field of up to 37T on FeSe single crystals, we could reveal the normal-state transport properties after SC was completely suppressed. The normal-state resistivity exhibited a Fermi liquid behavior at low temperatures. Large orbital magnetoresistance(MR) was observed in the nematic state with H//c, whereas MR was negligible with H//ab. The magnitude of the orbital MR showed an unusual reduction, and Kohler’s rule was severely violated below 10-25 K;these were attributable to spin fluctuations. The results indicated that spin fluctuations played a paramount role in the normalstate transport properties of FeSe albeit the Fermi liquid nature was at low temperature.

利用红外相机监测甘肃安西极旱荒漠国家级自然保护区鸟兽物种多样性

为了系统掌握甘肃安西极旱荒漠国家级自然保护区野生动物的种类、数量、分布以及种群动态变化趋势,我们于2017年8月至2019年9月,在保护区选取3个样地布设60台红外相机,对保护区兽类和鸟类多样性进行调查。红外相机累计观测29,147个工作日,采集独立有效照片11,134张。共观测到兽类6目10科18种,鸟类7目16科31种。国家I级重点保护野生动物有5种,国家Ⅱ级重点保护野生动物有11种。兽类中相对多度较高的物种有蒙古兔(Lepus tolai,RAI=12.749)、岩羊(Pseudoisnayaur,RAI=4.690)、北山羊(Caprasibirica,RAI=4.333)、蒙古野驴(Equus hemionus,RAI=3.163)、赤狐(Vulpes vulpes,RAI=2.601),分布最普遍的是赤狐和蒙古兔;鸟类中相对多度较高的物种有石鸡(Alectoris chukar,RAI=1.678)、岩鸽(Columba rupestris,RAI=1.142)、漠?(Oenanthe deserti,RAI=0.865)、赭红尾鸲(Phoenicurus ochruros,RAI=0.374)和沙?(Oenanthe isabellina,RAI=0.196),其中漠?和石鸡的分布最广。豺(Cuon alpinus)、石貂(Martes foina)、黄鼬(Mustela sibirica)和白唇鹿(Cervus albirostris)为保护区新记录物种,雪豹(Pantherauncia)也是保护区建立以来首次观测到。保护区人为干扰减少是造成物种新分布、数量增多的主要原因。

Levels,distributions,and sources of legacy and novel per-and perfluoroalkyl substances(PFAS)in the topsoil of Tianjin,China

Soil is a major sink for per-and perfluoroalkyl substances(PFAS),wherein PFAS may be transferred through the food chain to predators at upper trophic levels,which poses a threat to human health.Herein,the concentrations and distributions of legacy and novel PFAS in topsoil samples from different functional areas in Tianjin were comprehensively investigated.Seventeen PFAS congeners were identified,with concentrations ranging from 0.21 ng/g to 5.35 ng/g,with a mean concentration of 1.25 ng/g.The main PFAS in the topsoil was perfluorooctanoic acid(PFOA).6:2 chlorinated polyfluorinated ether sulfonate(6:2 ClPFESA;<MDL–1.95 ng/g,mean 0.11 ng/g),as an emerging substitute for perfluorooctane sulfonate(PFOS),was also detected in the topsoil.It showed slightly higher concentrations than PFOS(<MDL–1.62 ng/g,mean 0.10 ng/g),indicating it has gradually replaced legacy PFOS in this area.Based on the positive-definite matrix factor(PMF)receptor model,the major PFAS sources was dominated by textile treatment,metal electroplating plants,and some potential precursors of PFAS with longer chains(>C8)were the major sources(43.4%),followed by food packaging as well as coating materials(25.5%).In addition,Spearman correlation analysis and the structural equation model showed that population density significantly impacted the PFAS distribution in the topsoil of Tianjin.

FLIGHT:Federated Learning with IRS for Grouped Heterogeneous Training

In recent years,federated learning(FL)has played an important role in private data-sensitive scenarios to perform learning tasks collectively without data exchange.However,due to the centralized model aggregation for heterogeneous devices in FL,the last updated model after local training delays the convergence,which increases the economic cost and dampens clients’motivations for participating in FL.In addition,with the rapid development and application of intelligent reflecting surface(IRS)in the next-generation wireless communication,IRS has proven to be one effective way to enhance the communication quality.In this paper,we propose a framework of federated learning with IRS for grouped heterogeneous training(FLIGHT)to reduce the latency caused by the heterogeneous communication and computation of the clients.Specifically,we formulate a cost function and a greedy-based grouping strategy,which divides the clients into several groups to accelerate the convergence of the FL model.The simulation results verify the effectiveness of FLIGHT for accelerating the convergence of FL with heterogeneous clients.Besides the exemplified linear regression(LR)model and convolutional neural network(CNN),FLIGHT is also applicable to other learning models.