Deep learning-based automatic pipeline system for predicting lateral cervical lymph node metastasis in patients with papillary thyroid carcinoma using computed tomography:A multi-center study

Objective:The assessment of lateral lymph node metastasis(LLNM)in patients with papillary thyroid carcinoma(PTC)holds great significance.This study aims to develop and evaluate a deep learning-based automatic pipeline system(DLAPS)for diagnosing LLNM in PTC using computed tomography(CT).Methods:A total of 1,266 lateral lymph nodes(LLNs)from 519 PTC patients who underwent CT examinations from January 2019 to November 2022 were included and divided into training and validation set,internal test set,pooled external test set,and prospective test set.The DLAPS consists of an auto-segmentation network based on RefineNet model and a classification network based on ensemble model(ResNet,Xception,and DenseNet).The performance of the DLAPS was compared with that of manually segmented DL models,the clinical model,and Node Reporting and Data System(Node-RADS).The improvement of radiologists’diagnostic performance under the DLAPS-assisted strategy was explored.In addition,bulk RNA-sequencing was conducted based on 12 LLNs to reveal the underlying biological basis of the DLAPS.Results:The DLAPS yielded good performance with area under the receiver operating characteristic curve(AUC)of 0.872,0.910,and 0.822 in the internal,pooled external,and prospective test sets,respectively.The DLAPS significantly outperformed clinical models(AUC 0.731,P<0.001)and Node-RADS(AUC 0.602,P<0.001)in the internal test set.Moreover,the performance of the DLAPS was comparable to that of the manually segmented deep learning(DL)model with AUCs ranging 0.814−0.901 in three test sets.Furthermore,the DLAPSassisted strategy improved the performance of radiologists and enhanced inter-observer consistency.In clinical situations,the rate of unnecessary LLN dissection decreased from 33.33%to 7.32%.Furthermore,the DLAPS was associated with the cell-cell conjunction in the microenvironment.Conclusions:Using CT images from PTC patients,the DLAPS could effectively segment and classify LLNs non-invasively,and this system had a good generalization ability and clinical applicability.

Floating periodic pontoons for broad bandgaps of water waves

The narrow attenuation bands of traditional marine structures have long been a challenge in mitigating water waves.In this paper,a metastructure(MS)composed of floating periodic pontoons is proposed for broadband water wave attenuation.The interaction of surface gravity waves with the MS is investigated using linear wave theory.The potential solutions of water waves by the MS with a finite array are developed by using the eigenfunction expansion matching method(EEMM),and the band structure of the MS is calculated by the transfer matrix method(TMM),in which the evanescent modes of waves are considered.The solution is verified against the existing numerical result for a special case.Based on the present solution,the association between Bragg resonance reflection and Bloch bandgaps is examined,the effects of pontoon geometry are analyzed,and the comparison between floating MS and bottom-mounted periodic structures is conducted.A computational fluid dynamics(CFD)model is further developed to assess the structures in practical fluid environments,and the floating MS presents excellent wave attenuation performance.The study presented here may provide a promising solution for protecting the coast and offshore structures.

热暴露对7A85铝合金微观组织和力学性能的影响

选用7A85-T74锻造铝合金为实验材料,研究室温至240℃内热暴露5 h后的合金微观组织、拉伸性能及冲击吸收能量,并结合透射电子显微镜分析微观组织对合金力学性能的影响机理。结果表明:在80~240℃热暴露温度范围内,7A85-T74铝合金晶粒尺寸变化不大,但沉淀相随温度升高有显著变化;在120℃以内,随热暴露温度的升高,析出物尺寸、拉伸性能和冲击吸收能量整体变化不大,沉淀强化机制为位错切过析出物和位错绕过析出物的混合机制;随着热暴露温度由120℃升高至240℃,析出物的平均半径由室温下的3.8 nm增加至12.3 nm,析出物由η'相向η相转变,合金的屈服强度和抗拉强度显著下降,较室温分别下降45.7%和33.5%,伸长率、断面收缩率和冲击吸收能量显著升高,沉淀强化机制转变为位错绕过析出物,断裂方式由沿晶断裂和韧窝型穿晶断裂组成的混合断裂转变为韧窝型穿晶断裂。基于沉淀强化理论讨论析出物尺寸对合金强度与冲击吸收能量的影响,理论分析结果与实验结果相符。

Detection and classification of breast lesions using multiple information on contrast-enhanced mammography by a multiprocess deep-learning system: A multicenter study

Objective: Accurate detection and classification of breast lesions in early stage is crucial to timely formulate effective treatments for patients. We aim to develop a fully automatic system to detect and classify breast lesions using multiple contrast-enhanced mammography(CEM) images.Methods: In this study, a total of 1,903 females who underwent CEM examination from three hospitals were enrolled as the training set, internal testing set, pooled external testing set and prospective testing set. Here we developed a CEM-based multiprocess detection and classification system(MDCS) to perform the task of detection and classification of breast lesions. In this system, we introduced an innovative auxiliary feature fusion(AFF)algorithm that could intelligently incorporates multiple types of information from CEM images. The average freeresponse receiver operating characteristic score(AFROC-Score) was presented to validate system’s detection performance, and the performance of classification was evaluated by area under the receiver operating characteristic curve(AUC). Furthermore, we assessed the diagnostic value of MDCS through visual analysis of disputed cases,comparing its performance and efficiency with that of radiologists and exploring whether it could augment radiologists’ performance.Results: On the pooled external and prospective testing sets, MDCS always maintained a high standalone performance, with AFROC-Scores of 0.953 and 0.963 for detection task, and AUCs for classification were 0.909[95% confidence interval(95% CI): 0.822-0.996] and 0.912(95% CI: 0.840-0.985), respectively. It also achieved higher sensitivity than all senior radiologists and higher specificity than all junior radiologists on pooled external and prospective testing sets. Moreover, MDCS performed superior diagnostic efficiency with an average reading time of 5 seconds, compared to the radiologists’ average reading time of 3.2 min. The average performance of all radiologists was also improved to varying degrees with MDCS assistance.Conclusions: MDCS demonstrated excellent performance in the detection and classification of breast lesions,and greatly enhanced the overall performance of radiologists.

Recent advances in wave energy converters based on nonlinear stiffness mechanisms

Wave energy is one of the most abundant renewable clean energy sources,and has been widely studied because of its advantages of continuity and low seasonal variation.However,its low capture efficiency and narrow capture frequency bandwidth are still technical bottlenecks that restrict the commercial application of wave energy converters(WECs).In recent years,using a nonlinear stiffness mechanism(NSM)for passive control has provided a new way to solve these technical bottlenecks.This literature review focuses on the research performed on the use of nonlinear mechanisms in wave energy device utilization,including the conceptual design of a mechanism,hydrodynamic models,dynamic characteristics,response mechanisms,and some examples of experimental verification.Finally,future research directions are discussed and recommended.

Connector configuration effect on the dynamic characteristics of multi-modular floating structure

In this study,a wave flume experiment is implemented in order to investigate the effect of connector topology on the dynamic characteristics of a modular floating structure.Three configurations of flexible connectors were designed for the experiment tests of a three-modular floating platform under various wave conditions.The results illustrate the module responses,relative displacements of connecting points between adjacent modules,and connector loads for floating structures with different types of connectors in the parameters region of non-dimensional module length.The comparison study demonstrates that the connector type III,which can provide appropriate constraint stiffness in all three degrees of freedom,generally delivers better dynamic stability to the floating platform.The longitudinal loads for the three types of connectors remain at the same level.Additionally,the mechanism of different types of connec-tors on the dynamic features of system is analyzed.This work can provide a few experimental guidelines for the connector design of floating structure in engineering practice.

Indices and c-vectors in extriangulated categories

Let C be an extriangulated category and T be any n-cluster tilting subcategory of C.We consider the index with respect to T and introduce the index Grothendieck group of T.Using the index,we prove that the index Grothendieck group of T is isomorphic to the Grothendieck group of C,which implies that the index Grothendieck groups of any two n-cluster tilting subcategories are isomorphic.In particular,we show that the split Grothendieck groups of any two 2-cluster tilting subcategories are isomorphic.Then we develop a general framework for c-vectors of 2-Calabi-Yau extriangulated categories with respect to arbitrary 2-cluster tilting subcategories.We show that the c-vectors have the sign-coherence property and provide some formulas for calculating c-vectors.

Soil erosion affects variations of soil organic carbon and soil respiration along a slope in Northeast China

Background:Although soil erosion plays a key role in the carbon cycle,a holistic and mechanistic understanding of the soil erosion process within the cycle is still lacking.The aim of this study was therefore to improve our mechanistic understanding of soil organic carbon(SOC)and soil respiration dynamics through an experiment conducted in an eroding black soil farmland landscape in Northeast China.Results:The depositional profiles store 5.9 times more SOC than the eroding profiles and 3.3 times more SOC than the non-eroding profiles.A linear correlation between the SOC and 137Cs(Caesium-137)was observed in our study,suggesting that the SOC decreased with increased soil erosion.Furthermore,the fractions of intermediate C and the microaggregate C were lowest at the eroding position and highest at the depositional position.In the depositional topsoil,the input of labile materials plays a promotional role in soil respiration.Conversely,in the subsoil(i.e.,below 10 cm),the potential mineralization rates were lowest at the depositional position—due to effective stabilization by physical protection within soil microaggregates.The field results of soil surface respiration also suggest that the depositional topsoil SOC is prone to be mineralized and that SOC at this depositional context is stabilized at subsoil depth.In addition,the high water contents at the depositional position can limit the decomposition rates and stabilize the SOC at the same time.Conclusions:The findings from this study support that a majority of the SOC at footslope is stored within most of the soil profile(i.e.,below 10 cm)and submitted to long-term stabilization,and meanwhile support that the depositional profile emits more CO2 than the summit due to its high amount and quality of SOC.

n-正合函子诱导的(n＋2)-角函子

设(A,X)和(A′,X′)是两个Frobenius n-正合范畴,F:A→A′是n-正合函子.如果F把A中的X-内射对象映为A′中的X′-内射对象,则F诱导了稳定范畴间的一个(n+2)-角函子F:→A′.此外,本文将这个主要结果应用到伴随对和Galois覆盖函子上.

A comprehensive framework for seasonal controls of leaf abscission and productivity in evergreen broadleaved tropical and subtropical forests

Relationships among productivity,leaf phenology,and seasonal variation in moisture and light availability are poorly understood for evergreen broadleaved tropical/subtropical forests,which contribute 25% of terrestrial productivity.On the one hand,as moisture availability declines,trees shed leaves to reduce transpiration and the risk of hydraulic failure.On the other hand,increases in light availability promote the replacement of senescent leaves to increase productivity.Here,we provide a comprehensive framework that relates the seasonality of climate,leaf abscission,and leaf productivity across the evergreen broadleaved tropical/subtropical forest biome.The seasonal correlation between rainfall and light availability varies from strongly negative to strongly positive across the tropics and maps onto the seasonal correlation between litterfall mass and productivity for 68 forests.Where rainfall and light covary positively,litterfall and productivity also covary positively and are always greater in the wetter sunnier season.Where rainfall and light covary negatively,litterfall and productivity are always greater in the drier and sunnier season if moisture supplies remain adequate;otherwise productivity is smaller in the drier sunnier season.This framework will improve the representation of tropical/subtropical forests in Earth system models and suggests how phenology and productivity will change as climate change alters the seasonality of cloud cover and rainfall across tropical/subtropical forests.

非定常扩散方程基于调和平均点插值的有限体积格式

本文研究非定常扩散方程适用于扭曲和非结构网格的单元中心型的有限体积格式.在网格边上离散法向流时,选取当前网格边及与其相邻网格边上的调和平均点作为辅助插值点,通过它们与单元中心点不同的组合形式给出4类法向流的离散近似,最后通过调和平均点的两点插值算法,将其替换成相邻单元的中心未知量,进而建立4种单元中心型有限体积格式.时间导数项采用向后Euler格式进行离散.该格式具有模板小、易实现的优点,满足局部守恒和二阶收敛的特性.在一定网格假设前提下,理论上证明了算法的稳定性和收敛性.数值上考虑扩散系数是连续的、间断的、各向异性的甚至依赖于未知量是非线性的等情形,分别在非结构三角形、四边形和多边形网格上进行求解.结果表明,前两种算法对不同网格不同类型扩散系数问题上的鲁棒性更好,L^(2)误差均可达到二阶收敛,H^(1)误差接近一阶甚至高于一阶收敛;后两种算法对网格的依赖性更强.