Prediction of Concrete Faced Rock Fill Dams Settlements Using Genetic Programming Algorithm

In the present study a Genetic Programing model (GP) proposed for the prediction of relative crest settlement of concrete faced rock fill dams. To this end information of 30 large dams constructed in seven countries across the world is gathered with their reported settlements. The results showed that the GP model is able to estimate the dam settlement properly based on four properties, void ratio of dam’s body (e), height (H), vertical deformation modulus (Ev) and shape factor (Sc) of the dam. For verification of the model applicability, obtained results compared with other research methods such as Clements’s formula and the finite element model. The comparison showed that in all cases the GP model led to be more accurate than those of performed in literature. Also a proper compatibility between the GP model and the finite element model was perceived.

FACED评分评估慢性阻塞性肺疾病合并支气管扩张患者急性加重期的作用

目的分析不同FACED评分评估慢性阻塞性肺疾病(COPD)合并支气管扩张患者急性加重期的作用。方法收集2015-01~2015-12在福建医科大学附属宁德市医院呼吸内科住院的81例COPD合并支气管扩张患者的临床资料,包括年龄、临床症状、胸部高分辨率CT(HRCT)、细菌感染、肺功能、C-反应蛋白(CRP)、血气分析[动脉血氧分压(PO2),动脉血二氧化碳分压(PCO2)]、血清白蛋白等,并随访出院后1年内急性加重次数(急性加重门诊及住院次数)。以FACED评分量表为依据进行评估。结果 1年随访中FACED评分5~7分的COPD合并支气管扩张组的急性加重次数为(8.46±2.10)次,3~4分组的急性加重次数为(6.62±2.41)次,0~2分组的急性加重次数为(2.92±1.49)次,差异具有统计学意义(P<0.05)。FACED评分与急性加重次数相关分析呈正相关(r=0.753)。结论 FACED评分越高的COPD合并支气管扩张患者急性加重越频繁,FACED评分对于辨别频繁加重型COPD患者存在指导意义。

Study on the Technique of Double-faced Embroidery on Chinese Palace Fans

Double - faced iso - object embroidery is carried out byusing the uneven intercalated stitch crafts of the parallel- lines stitch as a main body, being accompanied by oth-er stitch crafts and miscellaneous stitches, done on thesame textile material. This paper deals with the flower -bird double - faced embroidery fan of the Qing Dynasty,from pattern design, stitching formation and techniqueof color arrangement, describes the possible way of mak-ing double - faced embroidery with iso - object effectboth in the front and in the back.

Editorial's note: The Opportunity and Challenge Faced by Molecular Medicine

Since 1980’s,life science has been holding a prominent place in the development ofscience and it is expected to become one of the leading disciplines in the 21 century.Currently the development of life science presents the following characteristics:1.The understanding of life was deepened to the molecule level.

The Think Following High Rise——Problem faced and Countermeasures for Export Firms Producing New and High-tech Products

China’sexportofnewandhigh-techproductsincreasedbymorethan30percentforthepastsuccessive4years.Indeed,itisnoteasytokeepsuchextraordinarymomentumofhigh-speedriseundercircumstancesofglobalslowpick-upinnewandhigh-techindustry.However,thehighriseinexportwithdifferenttradeformsadoptedbyvariedcompanieshidanumberofissuestobeconcerned:

Opportunities and Challenges Faced by Realization of World Equilibrium——Speech at the″International Conference for World Equilibrium″held in Cuba

犤Editer’snote犦:The″InternationalConferenceforWorldEquilibrium″washeldinHavanaofCubaonJanuary27-29,2003.Outstandingstatesmen,personages,expertsandscholarsfromover30countriesaswellasleadingmembersofinternationalorga-nizationsattendedtheconference.ACAFIUdelegationwerealsopresent.Mr.HeLiansheng,CouncilMemberandResearchFellowofCAFIU,deliveredaspeechonaspecialsubject.Followingisthetextofthespeech:

Challenges faced by SOE reform

State-owned enterprises’(SOE) greater independence from government offices as well as property rights reform have optimized SOEs’ shareholding structure. But the reform has to clear several hurdles before it can be fully realized. In 1998, the central government dismantled ministries that had been the direct administrators of large SOEs. Most functions of those ministries were transferred to industry associations. Only a few considered indispensable were taken over by other government offices. The move has pushed forward the SOE reform to some extent. On the other hand, being State-owned, those enterprises have to find new links with the government.

Main Problems Faced by Chinese RE Permanent Magnetic Industry

Under over 50 years' development, Chinese rare earth magnetic industry developed into the global AINiCo, ferrite permanent magnets and NdFeB magnets manufacturing center, and average consumption of magnets per person in China increased to 1.026 tons in 2003 from 0.217 ton in 1990. Although China has been the large producing country of rare earth permanent magnetic materials, to be the strongest one, there are many problems to solve. Main Problems Faced By Chinese Permanent Magnet

Influence of seismic wave type and incident direction on the dynamic response of tall concrete-faced rockfill dams

Owing to the stochastic behavior of earthquakes and complex crustal structure,wave type and incident direction are uncertain when seismic waves arrive at a structure.In addition,because of the different types of the structures and terrains,the traveling wave effects have different influences on the dynamic response of the structures.For the tall concrete-faced rockfill dam(CFRD),it is not only built in the complex terrain such as river valley,but also its height has reached 300 m level,which puts forward higher requirements for the seismic safety of the anti-seepage system mainly comprising concrete face slabs,especially the accurate location of the weak area in seism.Considering the limitations of the traditional uniform vibration analysis method,we implemented an efficient dynamic interaction analysis between a tall CFRD and its foundation using a non-uniform wave input method with a viscous-spring artificial boundary and equivalent nodal loads.This method was then applied to investigate the dynamic stress distribution on the concrete face slabs for different seismic wave types and incident directions.The results indicate that dam-foundation interactions behave differently at different wave incident angles,and that the traveling wave effect becomes more evident in valley topography.Seismic wave type and incident direction dramatically influenced stress in the face slab,and the extreme stress values and distribution law will vary under oblique wave incidence.The influence of the incident direction on slab stress was particularly apparent when SH-waves arrived from the left bank.Specifically,the extreme stress values in the face slab increased with an increasing incident angle.Interestingly,the locations of the extreme stress values changed mainly along the axis of the dam,and did not exhibit large changes in height.The seismic safety of CFRDs is therefore lower at higher incident angles from an anti-seepage perspective.Therefore,it is necessary to consider both the seismic wave type and incident direction during seismic capacity evaluations of tall CFRDs.

长期自由大气CO_(2)富集下稻田土壤有机碳分布结构与红外光谱特征研究

为探究野外自由大气CO_(2)浓度长期升高对不同深度农田土壤碳、氮含量和分布的影响,依托中国FACE(Free-air CO_(2) enrichment)系统平台,以15年试验区的土壤为研究样本,分析不同深度土壤总碳和全氮含量的变化,基于湿筛法区分颗粒态有机质(POM)和矿质结合态有机质(MAOM),并通过傅里叶红外光谱法研究不同深度土壤有机碳官能团的变化。结果表明:FACE处理有提高0~15、15~30 cm土壤总碳、全氮含量的趋势,其中0~15 cm土壤总碳、全氮含量较对照分别增加12.52%和14.32%,而15~30 cm分别增加21.74%和33.33%。0~15、15~30 cm土壤POM和MAOM的碳、氮含量均高于30~45、45~60 cm土壤,且土壤总碳、全氮更多地分布于MAOM中。FACE处理极显著增加0~15 cm土层POM的碳、氮含量,其增幅分别为25.92%和24.45%;极显著提高0~15和15~30 cm土层MAOM的碳、氮含量,增幅分别为0~15 cm的32.62%(碳)和59.52%(氮)以及15~30 cm的42.34%(碳)和31.06%(氮)。FACE处理与对照各深度土壤有机碳红外特征峰形态基本一致,但主要吸收峰相对强度存在差异。与对照相比,FACE显著减小45~60 cm土壤芳香族官能团(1630 cm-1)的峰面积,增加0~15、15~30 cm土壤但降低30~45、45~60 cm土壤吸收峰峰面积的比值。综上,长期FACE处理有提高表层土壤总碳、全氮含量的趋势,其增量碳、氮更多地分布于MOAM中,同时提高表层土壤有机碳化学结构的稳定性,有利于表层土壤固碳。

Key technical problems of extra-high concrete faced rock-fill dam

This paper summarizes the main technical points related to 100 m-height-scale concrete faced rock-fill dams and analyzes the main problems and their causes occurring during construction of 200 m-height-scale concrete faced rock-fill dams. This paper has raised the key technical problems which need to study for construction of 300 m-height-scale concrete faced rock-fill dams based on the main experiences on the extra-high concrete faced rock-fill dams built after the year of 2000.

Black fungus derived aerogel with double faced properties

Black fungus derived carbonaceous aerogel (BFA) was prepared via a convenient and energy efficient ultrasonic disposal process. The adsorption experiments of atmospheric pollutants demonstrated the superior adsorbability of black fungus aerogel on PM2.5, PM10 and formaldehyde. More importantly, black fungus aerogel (BFA) exhibited intriguing double-faced properties. We explored properties of each side of the black fungus from three aspects: water contact angle measurements, liquid selective absorption capacity and air pollutant adsorption abilities. The subsequent modification of ZnO nanosheets endowed the prepared black fungus aerogel with several valuable properties, including broad-spectrum antibacterial capability and high-efficient adsorption ability. These valuable characters implied the BFA to be a promising bacteriostat and cleaner for air and water pollution treatment.

Inverse reliability analysis and design for tunnel face stability considering soil spatial variability

The traditional deterministic analysis for tunnel face stability neglects the uncertainties of geotechnical parameters,while the simplified reliability analysis which models the potential uncertainties by means of random variables usually fails to account for soil spatial variability.To overcome these limitations,this study proposes an efficient framework for conducting reliability analysis and reliability-based design(RBD)of tunnel face stability in spatially variable soil strata.The three-dimensional(3D)rotational failure mechanism of the tunnel face is extended to account for the soil spatial variability,and a probabilistic framework is established by coupling the extended mechanism with the improved Hasofer-Lind-Rackwits-Fiessler recursive algorithm(iHLRF)as well as its inverse analysis formulation.The proposed framework allows for rapid and precise reliability analysis and RBD of tunnel face stability.To demonstrate the feasibility and efficacy of the proposed framework,an illustrative case of tunnelling in frictional soils is presented,where the soil's cohesion and friction angle are modelled as two anisotropic cross-correlated lognormal random fields.The results show that the proposed method can accurately estimate the failure probability(or reliability index)regarding the tunnel face stability and can efficiently determine the required supporting pressure for a target reliability index with soil spatial variability being taken into account.Furthermore,this study reveals the impact of various factors on the support pressure,including coefficient of variation,cross-correlation between cohesion and friction angle,as well as autocorrelation distance of spatially variable soil strata.The results also demonstrate the feasibility of using the forward and/or inverse first-order reliability method(FORM)in high-dimensional stochastic problems.It is hoped that this study may provide a practical and reliable framework for determining the stability of tunnels in complex soil strata.

Thermal and mechanical behavior of casting copper alloy wheel during wheel and belt continuous casting process

To investigate the thermal and mechanical behavior of casting wheel,a two-dimensional thermoelastic-plastic finite element model was used to predict the temperature,stress and distortion distribution of the casting wheel during the wheel and belt continuous casting process.The effects of grinding thickness and casting speed on the thermal and mechanical behaviors of the center of the hot face of the casting wheel were discussed in detail.In each rotation,the casting wheel passes through four different spray zones.The results show that the temperature distribution of the casting wheel in different spray zones is similar,the temperature of the hot face is the highest and the temperature reaches the peak in the spray zoneⅢ.The stress and distortion depend on the temperature distribution,and the maximum stress and distortion of the hot face are 358.2 MPa and 1.82 mm,respectively.The temperature at the center of the hot face decreases with increasing grinding thickness and increases with increasing casting speed.

Enhancing Identity Protection in Metaverse-Based Psychological Counseling System

Non-face-to-face psychological counseling systems rely on network technologies to anonymize information regard-ing client identity.However,these systems often face challenges concerning voice data leaks and the suboptimal communication of the client’s non-verbal expressions,such as facial cues,to the counselor.This study proposes a metaverse-based psychological counseling system designed to enhance client identity protection while ensuring efficient information delivery to counselors during non-face-to-face counseling.The proposed systemincorporates a voicemodulation function that instantlymodifies/masks the client’s voice to safeguard their identity.Additionally,it employs real-time client facial expression recognition using an ensemble of decision trees to mirror the client’s non-verbal expressions through their avatar in the metaverse environment.The system is adaptable for use on personal computers and smartphones,offering users the flexibility to access metaverse-based psychological counseling across diverse environments.The performance evaluation of the proposed system confirmed that the voice modulation and real-time facial expression replication consistently achieve an average speed of 48.32 frames per second or higher,even when tested on the least powerful smartphone configurations.Moreover,a total of 550 actual psychological counseling sessions were conducted,and the average satisfaction rating reached 4.46 on a 5-point scale.This indicates that clients experienced improved identity protection compared to conventional non-face-to-face metaverse counseling approaches.Additionally,the counselor successfully addressed the challenge of conveying non-verbal cues from clients who typically struggled with non-face-to-face psychological counseling.The proposed systemholds significant potential for applications in interactive discussions and educational activities in the metaverse.

Sparse representation scheme with enhanced medium pixel intensity for face recognition

Sparse representation is an effective data classification algorithm that depends on the known training samples to categorise the test sample.It has been widely used in various image classification tasks.Sparseness in sparse representation means that only a few of instances selected from all training samples can effectively convey the essential class-specific information of the test sample,which is very important for classification.For deformable images such as human faces,pixels at the same location of different images of the same subject usually have different intensities.Therefore,extracting features and correctly classifying such deformable objects is very hard.Moreover,the lighting,attitude and occlusion cause more difficulty.Considering the problems and challenges listed above,a novel image representation and classification algorithm is proposed.First,the authors’algorithm generates virtual samples by a non-linear variation method.This method can effectively extract the low-frequency information of space-domain features of the original image,which is very useful for representing deformable objects.The combination of the original and virtual samples is more beneficial to improve the clas-sification performance and robustness of the algorithm.Thereby,the authors’algorithm calculates the expression coefficients of the original and virtual samples separately using the sparse representation principle and obtains the final score by a designed efficient score fusion scheme.The weighting coefficients in the score fusion scheme are set entirely automatically.Finally,the algorithm classifies the samples based on the final scores.The experimental results show that our method performs better classification than conventional sparse representation algorithms.

Rock mass quality prediction on tunnel faces with incomplete multi-source dataset via tree-augmented naive Bayesian network

Rock mass quality serves as a vital index for predicting the stability and safety status of rock tunnel faces.In tunneling practice,the rock mass quality is often assessed via a combination of qualitative and quantitative parameters.However,due to the harsh on-site construction conditions,it is rather difficult to obtain some of the evaluation parameters which are essential for the rock mass quality prediction.In this study,a novel improved Swin Transformer is proposed to detect,segment,and quantify rock mass characteristic parameters such as water leakage,fractures,weak interlayers.The site experiment results demonstrate that the improved Swin Transformer achieves optimal segmentation results and achieving accuracies of 92%,81%,and 86%for water leakage,fractures,and weak interlayers,respectively.A multisource rock tunnel face characteristic(RTFC)dataset includes 11 parameters for predicting rock mass quality is established.Considering the limitations in predictive performance of incomplete evaluation parameters exist in this dataset,a novel tree-augmented naive Bayesian network(BN)is proposed to address the challenge of the incomplete dataset and achieved a prediction accuracy of 88%.In comparison with other commonly used Machine Learning models the proposed BN-based approach proved an improved performance on predicting the rock mass quality with the incomplete dataset.By utilizing the established BN,a further sensitivity analysis is conducted to quantitatively evaluate the importance of the various parameters,results indicate that the rock strength and fractures parameter exert the most significant influence on rock mass quality.

Learning to represent 2D human face with mathematical model

How to represent a human face pattern?While it is presented in a continuous way in human visual system,computers often store and process it in a discrete manner with 2D arrays of pixels.The authors attempt to learn a continuous surface representation for face image with explicit function.First,an explicit model(EmFace)for human face representation is pro-posed in the form of a finite sum of mathematical terms,where each term is an analytic function element.Further,to estimate the unknown parameters of EmFace,a novel neural network,EmNet,is designed with an encoder-decoder structure and trained from massive face images,where the encoder is defined by a deep convolutional neural network and the decoder is an explicit mathematical expression of EmFace.The authors demonstrate that our EmFace represents face image more accurate than the comparison method,with an average mean square error of 0.000888,0.000936,0.000953 on LFW,IARPA Janus Benchmark-B,and IJB-C datasets.Visualisation results show that,EmFace has a higher representation performance on faces with various expressions,postures,and other factors.Furthermore,EmFace achieves reasonable performance on several face image processing tasks,including face image restoration,denoising,and transformation.

Advancing Wound Filling Extraction on 3D Faces:An Auto-Segmentation and Wound Face Regeneration Approach

Facial wound segmentation plays a crucial role in preoperative planning and optimizing patient outcomes in various medical applications.In this paper,we propose an efficient approach for automating 3D facial wound segmentation using a two-stream graph convolutional network.Our method leverages the Cir3D-FaIR dataset and addresses the challenge of data imbalance through extensive experimentation with different loss functions.To achieve accurate segmentation,we conducted thorough experiments and selected a high-performing model from the trainedmodels.The selectedmodel demonstrates exceptional segmentation performance for complex 3D facial wounds.Furthermore,based on the segmentation model,we propose an improved approach for extracting 3D facial wound fillers and compare it to the results of the previous study.Our method achieved a remarkable accuracy of 0.9999993% on the test suite,surpassing the performance of the previous method.From this result,we use 3D printing technology to illustrate the shape of the wound filling.The outcomes of this study have significant implications for physicians involved in preoperative planning and intervention design.By automating facial wound segmentation and improving the accuracy ofwound-filling extraction,our approach can assist in carefully assessing and optimizing interventions,leading to enhanced patient outcomes.Additionally,it contributes to advancing facial reconstruction techniques by utilizing machine learning and 3D bioprinting for printing skin tissue implants.Our source code is available at https://github.com/SIMOGroup/WoundFilling3D.

Face animation based on multiple sources and perspective alignment

Background Face image animation generates a synthetic human face video that harmoniously integrates the identity derived from the source image and facial motion obtained from the driving video.This technology could be beneficial in multiple medical fields,such as diagnosis and privacy protection.Previous studies on face animation often relied on a single source image to generate an output video.With a significant pose difference between the source image and the driving frame,the quality of the generated video is likely to be suboptimal because the source image may not provide sufficient features for the warped feature map.Methods In this study,we propose a novel face-animation scheme based on multiple sources and perspective alignment to address these issues.We first introduce a multiple-source sampling and selection module to screen the optimal source image set from the provided driving video.We then propose an inter-frame interpolation and alignment module to further eliminate the misalignment between the selected source image and the driving frame.Conclusions The proposed method exhibits superior performance in terms of objective metrics and visual quality in large-angle animation scenes compared to other state-of-the-art face animation methods.It indicates the effectiveness of the proposed method in addressing the distortion issues in large-angle animation.