A Simplified Method for the Stress Analysis of Underground Transfer Structures Crossing Multiple Subway Tunnels

According to the design specifications,the construction of extended piles involves traversing the tunnel’s upper region and extending to the underlying rock layer.To address this challenge,a subterranean transfer structure spanning multiple subway tunnels was proposed.Deliberating on the function of piles in the transfer structure as springs with axial and bending stiffness,and taking into account the force balance and deformation coordination conditions of beams and plates within the transfer structure,we established a simplified mechanical model that incorporates soil stratification by combining it with the Winkler elastic foundation beam model.The resolved established simplifiedmechanicalmodel employed finite difference technology and the Newton-Simpsonmethod,elucidating the mechanical mechanism of the transfer structure.The research findings suggest that the load carried by the upper structural columns can be transferred to the pile foundation beneath the beams through the transfer structure,subsequently reaching the deep soil layer and ensuring minimal impact on adjacent tunnels.The established simplified analysis method can be used for stress analysis of the transfer structure,concurrently considering soil stratification,pile foundation behavior,and plate action.The pile length,pile section size,and beam section size within the transfer structure should account for the characteristics of the upper load,ensuring an even distribution of the beam bending moment.

Magnetic Field Curves and Magnetic Equipotential Surfaces around Crossing Electrical Wires Replacing Classical Magnetic Field Lines

This article is based on a recent model specifically defining magnetic field values around electrical wires. With this model, calculations of field around parallel wires were obtained. Now, this model is extended with the new concept of magnetic equipotential surface to magnetic field curves around crossing wires. Cases of single, double, and triple wires are described. Subsequent article will be conducted for more general scenarios where wires are neither infinite nor parallel.

基于遗传算法与Hardy-Cross方法的矿井通风机控制

针对矿井通风机系统控制的复杂问题,提出了一种遗传算法与Hardy-Cross方法相结合的矿井通风控制,强化了其在处理离散变量和非凸搜索空间中寻找全局最优解的能力。通过数学形式化定义问题并结合基尔霍夫定律,确立了通风机网络的优化模型。根据实际用风情况智能调节通风机的供风量,以实现能源节约和安全生产的目标。通过对某煤矿的通风案例深入研究和验证,风扇的配置在优化气流方面表现出了卓越性能。该研究不仅为矿山工程领域提供了新的优化思路和方法,也为通风机系统的管理提供了重要参考。

LEO支架构建crossing Y形支架辅助栓塞治疗颅内动脉分叉部宽颈动脉瘤的安全性和有效性分析

目的探讨使用LEO支架构建crossing Y形支架辅助栓塞治疗颅内动脉分叉部宽颈动脉瘤的安全性和有效性。方法收集2018-2022年陆军军医大学第一附属医院神经外科收治的336例颅内动脉分叉部宽颈动脉瘤患者的临床资料及随访影像,其中55例患者采用LEO支架构建crossing Y形支架辅助栓塞治疗。观察使用LEO支架构建crossing Y形支架辅助栓塞治疗动脉瘤的成功率、手术相关并发症、围手术期缺血和出血并发症的发生率。采用改良Rankin评分(modified Rankin scale,mRS)量表评价患者出院及临床随访时的神经功能恢复情况,使用术后即刻及随访脑血管造影Raymond分级评估栓塞效果、术后随访CTA及MRA评估有无复发。结果55例颅内动脉分叉部宽颈动脉瘤患者均成功栓塞,未见支架打开不良、支架打折等不良事件;术中支架内血栓形成1例(1.82%),迟发性缺血2例(3.64%),未见围手术期出血事件。术后即刻造影致密栓塞(RaymondⅠ级)50例(90.91%),瘤颈残留(RaymondⅡ级)3例(5.45%),RaymondⅢ级2例(3.64%)。40例患者于术后6~24个月获得影像随访,造影RaymondⅠ级38例(95%),RaymondⅡ级2例(5%);9例患者行CTA或MRA复查未见复发;术后随访动脉瘤栓塞效果较术后即刻好转。出院时mRS评分0~1分50例,2分1例,3分1例,4分2例,5分1例。获得4~24个月临床随访预后,mRS评分0~1分50例,2分2例,3分1例,4分1例,6分1例;出院时mRS评分较差患者临床随访mRS评分好转。结论使用LEO支架构建crossing Y形支架辅助栓塞治疗颅内动脉分叉部宽颈动脉瘤成功率及安全性高,复发率低,围手术期缺血事件发生率低,近期疗效可,远期疗效待进一步观察。

Evolution of polarization singularities accompanied by avoided crossing in plasmonic system

The evolution of polarization singularities supported in a one-dimensional periodic plasmonic system is studied.The lateral inversion symmetry of the system,which breaks the in-plane inversion symmetry and up-down mirror symmetry simultaneously,yields abundant polarization states.A complete evolution process with geometry for the polarization states is traced.In the evolution,circularly polarized points(C points)can stem from 3 different processes.In addition to the previously reported processes occurring in an isolated band,a new type of C point appearing in two bands simultaneously due to the avoided band crossing,is observed.Unlike the dielectric system with a similar structure which only supports at-Γbound states in the continuum(BICs),accidental BICs off theΓpoint are realized in this plasmonic system.This work provides a new scheme of polarization manipulation for the plasmonic systems.

The asymptotic relation between the first crossing point and the last exit time of Gaussian order statistics sequences

In this paper,we study the asymptotic relation between the first crossing point and the last exit time for Gaussian order statistics which are generated by stationary weakly and strongly dependent Gaussian sequences.It is shown that the first crossing point and the last exit time are asymptotically independent and dependent for weakly and strongly dependent cases,respectively.The asymptotic relations between the first crossing point and the last exit time for stationary weakly and strongly dependent Gaussian sequences are also obtained.

Cross section determination of^(27)Al(n,2n)^(26)Al reaction induced by 14-MeV neutrons uniting with D-T neutron activation and AMS techniques

Aluminum is the primary structural material in nuclear engineering,and its cross section induced by 14-MeV neutrons is of great significance.To address the issue of insufficient accuracy for the^(27)Al(n,2n)^(26)Al reaction cross section,the activation method and accelerator mass spectrometry(AMS)technique were used to determine the^(27)Al(n,2n)^(26)Al cross section,which could be used as a D-T plasma ion temperature monitor in fusion reactors.At the China Academy of Engineering Physics,neutron activation was performed using a K-400 neutron generator produced by the T(d,n)4He reaction.The^(26)Al∕^(27)Al isotope ratios were measured using the newly installed GYIG 1 MV AMS at the Institute of Geochemistry,Chinese Academy of Sciences.The neutron flux was monitored by measuring the activity of 92mNb produced by the 93Nb(n,2n)92mNb reaction.The measured results were compared with available data in the experimental nuclear reaction database,and the measured values showed a reasonable degree of consistency with partially available literature data.The newly acquired cross-sectional data at 12 neutron energy points through systematic measurements clarified the divergence,which has two different growth trends from the existing experimental values.The obtained results are also compared with the corresponding evaluated database,and the newly calculated excitation functions with TALYS−1.95 and EMPIRE−3.2 codes,the agreement with CENDL−3.2,TENDL-2021 and EMPIRE−3.2 results are generally acceptable.A substantial improvement in the knowledge of the^(27)Al(n,2n)^(26)Al reaction excitation function was obtained in the present work,which will lay the foundation for the diagnosis of the fusion ion temperature,testing of the nuclear physics model,evaluation of nuclear data,etc.

Synthesis and Charcterization of Silane Crosslinked Hydrogel to pH Sensitive Study

Eco-friendly and biodegradable novel hydrogel were prepared by blending and solution casting method. The designed hydrogel is based on chitosan/ PEG600/Gurgam with carbon nanofiller along silane crosslinked (TEOS) with pH sensitive response to controlled release of drug in biomedical materials and agriculture industry. The various concentration of carbon nanofiller is used to analyze its effect on the fabricated hydrogel characteristics by using FTIR, SEM, TGA, swelling studies (water, buffer and ionic solution). Spectra of FTIR reflected both established and newly developed groups (like hydrogel). COOH group presence is clearly observed in this range in the carbon filler reinforced hydrogel. The SEM micrographs show that CPG0.003 had a collection of polysaccharide chains as thin helices, which is attributed to the increase in the size of porosity. TGA shows to increase concentration of nanofiller enhanced the thermal stability of the designed hydrogels at temperature 25˚C to 550˚C mass loss percentage decrease upto 20% and increase thermal stability. This pH response made these resultant hydrogels as fruitful competitor against the many reported controlled release application.

Asymmetric expression of CA2 and CA13 linked to calcification in the bilateral mandibular condyles cause crossed beaks in chickens

Crossed beak is a complex mode of inheritance with prevalence ranging from 0.2 to 7.4% in at least 12 chicken strains worldwide.To reveal the intrinsic factors causing crossed beaks,genes expression patterns in bilateral mandibular condyle between affected and normal birds were characterized by RNA sequencing analysis in the present studies.Crossed beak was induced by short length of unilateral mandibular ramus,and a total of 110differentially expressed genes were up-or down-regulated in the affected(short)mandibular condyle side as compared to the normal side.Carbonic anhydrase 2(CA2)and Carbonic anhydrase 13(CA13)were enriched in the carbonate dehydratase activity,and high-expressed in mandibular condyle and osteoblasts(P<0.05).However,both were low-expressed in short mandibular condyle side of affected birds(P<0.05).The carbonate dehydratase inhibitor experiments confirmed that there is positive association between the calcification and carbonic anhydrase isoenzymes.Quantitative analysis with cetylpyridinium chloride showed a decrease in calcification when the cells were transfected with an anti-CA13 shRNA.Our research suggested that CA2 and CA13 are down-calcified in shortside mandibular condyle,and caused mandibular ramus to grow slowly.CA2 and CA13 have the critical role in crossed beaks by regulating calcification of mandibular condyle.

Atomic transport dynamics in crossed optical dipole trap

We study the dynamical evolution of cold atoms in crossed optical dipole trap theoretically and experimentally. The atomic transport process is accompanied by two competitive kinds of physical mechanics, atomic loading and atomic loss.The loading process normally is negligible in the evaporative cooling experiment on the ground, while it is significant in preparation of ultra-cold atoms in the space station. Normally, the atomic loading process is much weaker than the atomic loss process, and the atomic number in the central region of the trap decreases monotonically, as reported in previous research. However, when the atomic loading process is comparable to the atomic loss process, the atomic number in the central region of the trap will initially increase to a maximum value and then slowly decrease, and we have observed the phenomenon first. The increase of atomic number in the central region of the trap shows the presence of the loading process, and this will be significant especially under microgravity conditions. We build a theoretical model to analyze the competitive relationship, which coincides with the experimental results well. Furthermore, we have also given the predicted evolutionary behaviors under different conditions. This research provides a solid foundation for further understanding of the atomic transport process in traps. The analysis of loading process is of significant importance for preparation of ultra-cold atoms in a crossed optical dipole trap under microgravity conditions.

Tailoring the texture and mechanical properties of 3%Y_(2)O_(3)p/ZGK200 composites fabricated by unidirectional and cross rolling followed by annealing

3%Y_(2)O_(3)p/ZGK200 composites were subjected to unidirectional rolling(UR)and cross rolling(CR)at 400℃and 350℃followed by annealing at 300℃for 1 h.The microstructure,texture and mechanical properties of rolled and annealed composites were systematically studied.The rolled composites exhibited a heterogeneous microstructure,consisting of deformed grains elongated along rolling direction(RD)and Y_(2)O_(3)particles bands distributed along RD.After annealing,static recrystallization(SRX)occurred and most deformed grains transformed into equiaxed grains.A non-basal texture with two strong T-texture components was obtained after UR while a non-basal elliptical/circle texture with circle multi-peaks was obtained after CR,indicating that rolling path had great influences on texture of the composites.After annealing process,R-texture component disappeared or weakened,as results,a non-basal texture with double peaks tilting from normal direction(ND)to transverse direction(TD)and a more random non-basal texture with circle multi-peaks were obtained for UR and CR composites,respectively.The yield strength of rolled composites after UR showed obvious anisotropy along RD and TD while a low anisotropic yield strength was obtained after CR.Some Y_(2)O_(3)particles broke during rolling.The fracture of the composites was attributed to the existence of Y_(2)O_(3)clusters and interfacial debonding between particles and matrix during tension,as a result,the ductility was not as superior as matrix alloy.

State-selective charge exchange cross sections in collisions of highly-charged sulfur ions with helium and molecular hydrogen

The state-selective cross section data are useful for understanding and modeling the x-ray emission in celestial observations.In the present work,using the cold target recoil ion momentum spectroscopy,for the first time we investigated the state-selective single electron capture processes for S^(q+)–He and H_(2)(q=11–15)collision systems at an impact energy of q×20 keV and obtained the relative state-selective cross sections.The results indicate that only a few principal quantum states of the projectile energy level are populated in a single electron capture process.In particular,the increase of the projectile charge state leads to the population of the states with higher principal quantum numbers.It is also shown that the experimental averaged n-shell populations are reproduced well by the over-barrier model.The database is openly available in Science Data Bank at 10.57760/sciencedb.j00113.00091.

Nonlinear Registration of Brain Magnetic Resonance Images with Cross Constraints of Intensity and Structure

Many deep learning-based registration methods rely on a single-stream encoder-decoder network for computing deformation fields between 3D volumes.However,these methods often lack constraint information and overlook semantic consistency,limiting their performance.To address these issues,we present a novel approach for medical image registration called theDual-VoxelMorph,featuring a dual-channel cross-constraint network.This innovative network utilizes both intensity and segmentation images,which share identical semantic information and feature representations.Two encoder-decoder structures calculate deformation fields for intensity and segmentation images,as generated by the dual-channel cross-constraint network.This design facilitates bidirectional communication between grayscale and segmentation information,enabling the model to better learn the corresponding grayscale and segmentation details of the same anatomical structures.To ensure semantic and directional consistency,we introduce constraints and apply the cosine similarity function to enhance semantic consistency.Evaluation on four public datasets demonstrates superior performance compared to the baselinemethod,achieving Dice scores of 79.9%,64.5%,69.9%,and 63.5%for OASIS-1,OASIS-3,LPBA40,and ADNI,respectively.

Absolute partial and total ionization cross sections of carbon monoxide with electron collision from 350 eV to 8000 eV

The absolute partial and total cross sections for electron impact ionization of carbon monoxide are reported for electron energies from 350 eV to 8000 eV.The product ions(CO^(+),C^(+),O^(+),CO^(2+),C^(2+),and O^(2+))are measured by employing an ion imaging mass spectrometer and two ion-pair dissociation channels(C^(+)+O^(+)and C^(2+)+O^(+))are identified.The absolute cross sections for producing individual ions and their total,as well as for the ion-pair dissociation channels are obtained by normalizing the data of CO^(+)to that of Ar^(+)from CO-Ar mixture target with a fixed 1:1 ratio.The overall errors are evaluated by considering various kinds of uncertainties.A comprehensive comparison is made with the available data,which shows a good agreement with each other over the energy ranges that are overlapped.This work presents new cross-section data with electron energies above 1000 eV.

Three‑dimensional numerical simulation of dynamic strength and failure mode of a rock mass with cross joints

To study the dynamic mechanical properties and failure characteristics of intersecting jointed rock masses with different joint distributions under confining pressure,considering the cross angleαand joint persistence ratioη,a numerical model of the biaxial Hopkinson bar test system was established using the finite element method–discrete-element model coupling method.The validity of the model was verified by comparing and analyzing it in conjunction with laboratory test results.Dynamics-static combined impact tests were conducted on specimens under various conditions to investigate the strength characteristics and patterns of crack initiation and expansion.The study revealed the predominant factors influencing intersecting joints with different angles and penetrations under impact loading.The results show that the peak stress of the specimens decreases first and then increases with the increase of the cross angle.Whenα<60°,regardless of the value ofη,the dynamic stress of the specimens is controlled by the main joint.Whenα≥60°,the peak stress borne by the specimens decreases with increasingη.Whenα<60°,the initiation and propagation of cracks in the cross-jointed specimens are mainly controlled by the main joint,and the final failure surface of the specimens is composed of the main joint and wing cracks.Whenα≥60°orη≥0.67,the secondary joint guides the expansion of the wing cracks,and multiple failure surfaces composed of main and secondary joints,wing cracks,and co-planar cracks are formed.Increasing lateral confinement significantly increases the dynamic peak stress able to be borne by the specimens.Under triaxial conditions,the degree of failure of the intersecting jointed specimens is much lower than that under uniaxial and biaxial conditions.

Using Cross Entropy as a Performance Metric for Quantifying Uncertainty in DNN Image Classifiers: An Application to Classification of Lung Cancer on CT Images

Cross entropy is a measure in machine learning and deep learning that assesses the difference between predicted and actual probability distributions. In this study, we propose cross entropy as a performance evaluation metric for image classifier models and apply it to the CT image classification of lung cancer. A convolutional neural network is employed as the deep neural network (DNN) image classifier, with the residual network (ResNet) 50 chosen as the DNN archi-tecture. The image data used comprise a lung CT image set. Two classification models are built from datasets with varying amounts of data, and lung cancer is categorized into four classes using 10-fold cross-validation. Furthermore, we employ t-distributed stochastic neighbor embedding to visually explain the data distribution after classification. Experimental results demonstrate that cross en-tropy is a highly useful metric for evaluating the reliability of image classifier models. It is noted that for a more comprehensive evaluation of model perfor-mance, combining with other evaluation metrics is considered essential. .

Measurement of the neutron-induced total cross sections of ^(nat)Pb from 0.3 eV to 20 MeV on the Back-n at CSNS

The neutron-induced total cross sections of natural lead have been measured in a wide energy range(0.3 eV-20 MeV)on the back-streaming white neutron beamline(Back-n)at the China Spallation Neutron Source.Neutron energy was determined by the neutron total cross-section spectrometer using the time-of-flight technique.A fast multi-cell fission chamber was used as the neutron detector,and a 10-mm-thick high-purity natural lead sample was employed for the neutron transmission measurements.The on-beam background was determined using Co,In,Ag,and Cd filters.The excitation function of ^(nat)Pb(n,tot)reaction below 20 MeV was calculated using the TALYS-1.96 nuclear-reaction modeling program.The present results were compared with previous results,the evaluated data available in the five major evaluated nuclear data libraries(i.e.,ENDF/B-VIII.0,JEFF-3.3,JENDL-5,CENDL-3.2,and BROND-3.1),and the theoretical calculation curve.Good agreement was found between the new results and those of previous experiments and with the theoretical curves in the corresponding region.This measurement obtained the neutron total cross section of natural lead with good accuracy over a wide energy range and added experimental data in the resonance energy range.This provides more reliable experimental data for nuclear engineering design and nuclear data evaluation of lead.

DCFNet:An Effective Dual-Branch Cross-Attention Fusion Network for Medical Image Segmentation

Automatic segmentation of medical images provides a reliable scientific basis for disease diagnosis and analysis.Notably,most existing methods that combine the strengths of convolutional neural networks(CNNs)and Transformers have made significant progress.However,there are some limitations in the current integration of CNN and Transformer technology in two key aspects.Firstly,most methods either overlook or fail to fully incorporate the complementary nature between local and global features.Secondly,the significance of integrating the multiscale encoder features from the dual-branch network to enhance the decoding features is often disregarded in methods that combine CNN and Transformer.To address this issue,we present a groundbreaking dual-branch cross-attention fusion network(DCFNet),which efficiently combines the power of Swin Transformer and CNN to generate complementary global and local features.We then designed the Feature Cross-Fusion(FCF)module to efficiently fuse local and global features.In the FCF,the utilization of the Channel-wise Cross-fusion Transformer(CCT)serves the purpose of aggregatingmulti-scale features,and the Feature FusionModule(FFM)is employed to effectively aggregate dual-branch prominent feature regions from the spatial perspective.Furthermore,within the decoding phase of the dual-branch network,our proposed Channel Attention Block(CAB)aims to emphasize the significance of the channel features between the up-sampled features and the features generated by the FCFmodule to enhance the details of the decoding.Experimental results demonstrate that DCFNet exhibits enhanced accuracy in segmentation performance.Compared to other state-of-the-art(SOTA)methods,our segmentation framework exhibits a superior level of competitiveness.DCFNet’s accurate segmentation of medical images can greatly assist medical professionals in making crucial diagnoses of lesion areas in advance.

A method for Improving the Efficiency of Pear Tree Crossbreeding

In view of the short blooming period of pear tree crossbreeding and the complexity of pollination process, a method that can improve the efficiency of crossbreeding of pear trees was provided. Meanwhile, this method can also be applied to the study of pollen xenia effect, pollination tree selection and pure pollen collection in pear tree cultivation.

Performance Comparison of Vision Transformer- and CNN-Based Image Classification Using Cross Entropy: A Preliminary Application to Lung Cancer Discrimination from CT Images

This study evaluates the performance and reliability of a vision transformer (ViT) compared to convolutional neural networks (CNNs) using the ResNet50 model in classifying lung cancer from CT images into four categories: lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), large cell carcinoma (LULC), and normal. Although CNNs have made significant advancements in medical imaging, their limited capacity to capture long-range dependencies has led to the exploration of ViTs, which leverage self-attention mechanisms for a more comprehensive global understanding of images. The study utilized a dataset of 748 lung CT images to train both models with standardized input sizes, assessing their performance through conventional metrics—accuracy, precision, recall, F1 score, specificity, and AUC—as well as cross entropy, a novel metric for evaluating prediction uncertainty. Both models achieved similar accuracy rates (95%), with ViT demonstrating a slight edge over ResNet50 in precision and F1 scores for specific classes. However, ResNet50 exhibited higher recall for LULC, indicating fewer missed cases. Cross entropy analysis showed that the ViT model had lower average uncertainty, particularly in the LUAD, Normal, and LUSC classes, compared to ResNet50. This finding suggests that ViT predictions are generally more reliable, though ResNet50 performed better for LULC. The study underscores that accuracy alone is insufficient for model comparison, as cross entropy offers deeper insights into the reliability and confidence of model predictions. The results highlight the importance of incorporating cross entropy alongside traditional metrics for a more comprehensive evaluation of deep learning models in medical image classification, providing a nuanced understanding of their performance and reliability. While the ViT outperformed the CNN-based ResNet50 in lung cancer classification based on cross-entropy values, the performance differences were minor and may not hold clinical significance. Therefore, it may be premature to consider replacing CNNs with ViTs in this specific application.