温度影响下能量桩-土接触面剪切特性试验研究

能量桩工作过程中,桩体受温度变化影响会产生热变形,进而引起桩周土体的循环剪切作用,弱化地基承载力,给桩基的正常使用带来风险。由于传统直剪仪无法模拟能量桩工作过程中的温度变化,因此对桩-土接触面力学特性受温度影响的变化规律研究较少。对传统直剪仪进行改造,使其可以改变剪切试样温度;所用土体从重庆某施工现场取样,开展不同温度变化下桩-土接触面的室内土工直剪试验,分析单次温度变化和循环温度变化对桩-土接触面力学性能的影响,并对温度影响下桩-土接触面力学特性与土体力学特性的差异进行比较。结果表明,能量桩-土接触面的抗剪强度受温度影响较大;随着温度的升高,能量桩-土界面摩擦角和黏聚力先减小后增大;低法向应力下温度循环对桩-土接触面力学特性影响较大,而高法向应力下温度循环对桩-土接触面力学特性影响不显著;土体的抗剪强度、黏聚力和摩擦角随温度变化规律与桩-土界面类似。

归白祛斑汤结合强脉冲光治疗黄褐斑(肝郁气滞型)临床疗效观察

目的观察黄褐斑(肝郁气滞型)患者采取归白祛斑汤结合强脉冲光治疗的临床效果。方法将纳入的78例肝郁气滞型黄褐斑患者以随机数字表法分为观察组和对照组,每组39例,对照组口服维生素C与维生素E治疗,并给予强脉冲光治疗,而观察组在对照组治疗基础上结合归白祛斑汤治疗。数据观察:临床治疗效果、治疗前后中医证候积分(面部黄褐色斑片、胁胀胸痞、性情急躁易怒、乳房作胀或疼痛)变化、皮损面积与皮损颜色评分变化、皮肤病生活质量指数(dermatology life quality index,DLQI评分)变化、皮肤角质层含水量变化、焦虑自评量表(Self-Rating Anxiety Scale,SAS)评分变化、治疗不良反应。结果对照组与观察组患者治疗总有效率比较[82.05%(32/39)vs97.44%(38/39)],观察组更高,P<0.05;治疗前,两组患者中医证候积分(面部黄褐色斑片、胁胀胸痞、性情急躁易怒及乳房作胀或疼痛)、皮损面积及颜色评分、皮肤角质层含水量与DLQI评分、SAS评分等指标比较,P>0.05,治疗后两组患者中医证候积分(面部黄褐色斑片、胁胀胸痞、性情急躁易怒、乳房作胀或疼痛)、皮损面积与皮损颜色评分、DLQI评分、皮肤角质层含水量、SAS评分均改善,治疗后观察组患者的中医证候积分(面部黄褐色斑片、胁胀胸痞、性情急躁易怒、乳房作胀或疼痛)、皮损面积与皮损颜色评分、DLQI评分、皮肤角质层含水量、SAS评分等指标均优于对照组患者,P<0.05;对照组与观察组患者不良反应均较少,P>0.05。结论归白祛斑汤结合强脉冲光治疗黄褐斑(肝郁气滞型)临床疗效显著,患者症状改善,心理状态改善,生活质量明显提升,且不良反应少,治疗较为安全可靠,值得应用。

加拿大科技“超级集群”计划建设及启示

结合加拿大近年经济形势、研发投入、政策支撑等方面,分析加拿大提出“超级集群”计划的背景,同时介绍“超级集群”遴选过程,分析组建构成,调研近年来数字技术超级集群、蛋白质产业超级集群、下一代制造业超级集群、人工智能驱动的供应链超级集群、海洋超级集群5个超级集群建设运行成效。作为加拿大政府从国家层面设计的科技战略,加拿大政府重视产学研结合与多学科融合,通过超级集群构建科技创新生态系统,对我国创新科研组织方式具有较强借鉴意义,据此可以从强化战略目标、聚焦投入领域,打造战略科技力量、推动各主体协同创新,加强政策引导支持、营造创新生态环境等方面提升我国科研管理水平。

2.7~3.0μm波段高反镜反射率测量研究

中红外激光领域广泛使用高性能高反射光学元件,高反射率高精度测试技术是制备高性能反射光学元件的基础。针对2.7~3.0μm波段光学元件高反射率测量的实际需求,基于量子级联激光器建立了连续光腔衰荡反射率测试实验装置,通过优选2.7~3.0μm波段反射带内水汽吸收较弱的测试波长,分析空气中水汽吸收对衰荡时间和反射率测量的影响,并比较空气和氮气环境下反射率测量结果,实现了2.7~3.0μm波段高反镜反射率的准确测量,在反射率约99.95%时绝对测量精度优于2×10-5。实验结果显示,采用测试波长2.9μm并在测量时保证初始腔和测试腔腔长相同,无需使用氮气环境,直接在实验室空气环境可实现高反射率的精确测量。

老年脑小血管病总负荷与穿支动脉粥样硬化病预后不良的相关性研究

目的探讨老年患者脑小血管病(cerebral small vessel disease,CSVD)总负荷与穿支动脉粥样硬化病(branch atheromatous disease,BAD)预后不良的相关性。方法选取2021年1月至2023年3月于上海市第八人民医院就诊的BAD患者114例,根据发病90 d时改良的Rankin量表(modified Rankin scale,mRS)评分分为预后良好组67例(mRS评分≤2分)和预后不良组47例(mRS评分>2分)。分析所有患者的临床和影像学特征,采用logistic回归分析CSVD总负荷与BAD临床预后的关系。通过ROC曲线确定CSVD总负荷预测不良结局的临界值,并评估其敏感性和特异性。结果预后良好组年龄、糖尿病、收缩压、入院时美国国立卫生研究院卒中量表(NIHSS)评分、脑白质疏松、脑微出血比例较预后不良组明显降低,差异有统计学意义(P<0.05,P<0.01)。2组CSVD总负荷评分比较,差异有统计学意义(P<0.01)。二元logistic回归分析显示,CSVD总负荷评分和入院时NIHSS评分是BAD患者不良预后的独立预测因素(OR=3.350,95%CI:1.439~7.798,P=0.005;OR=2.814,95%CI:1.586~4.993,P=0.001)。ROC曲线分析显示,CSVD总负荷评分临界值为1.5分,预测BAD患者预后不良的敏感性为63.8%,特异性为86.6%。结论CSVD总负荷是BAD不良预后的独立预测因素。

复杂工况下选择性催化还原脱硝系统的迁移强化学习控制

针对复杂工况下选择性催化还原(SCR)系统难以实现精确脱硝控制的问题,本文提出一种基于迁移强化学习的智能控制方法.首先根据机组负荷的变化将整体运行过程划分为不同阶段.然后训练了强化学习控制器以分别学习各个阶段的不同特征,从而实现了变工况下SCR脱硝系统的精确控制.此外,借鉴了迁移学习的思路以应对预料之外的未知工况,避免了因工况未知所造成的不利影响.最后将训练好的控制器用于实际SCR脱硝系统的控制中,实验结果表明所提方法可以有效地控制复杂工况下燃煤机组NOx的排放量,为复杂工况下SCR脱硝系统的智能控制提供了借鉴.

中国农业碳排放的时空演化及影响因素分析

研究农业碳排放的区域异质性、动态演进及影响因素对于合理推进绿色农业及低碳发展具有重要意义。本文基于2000−2021年我国31个省份数据(不包括港澳台地区数据),测算农业碳排放总量和强度,采用标准差椭圆、Theil指数、核密度估计等方法分析时空特征并探讨区域异质性,最后利用LMDI模型从全国、粮食功能区、省域三大层面分析其影响因素。结果表明:①时间上,2000−2021年我国农业碳排放总量呈波动上升趋势,年均增长率为0.23%;农业碳排放强度呈下降趋势,降幅为52.08%。②空间上,标准差椭圆呈“东北−西南”空间分布格局且重心向西北方向移动。碳排放强度的区域差异主要源于区域内差异,而区域内差异呈粮食产销平衡区>粮食主产区>粮食主销区的特征。此外,核密度估计显示,三大粮食功能区多表现为双峰或三峰格局,存在一定程度的区域分化。③影响因素上,经济产出效应和城镇化效应会促进农业碳排放的增长,而生产效率效应、农业产业结构效应、经济结构效应以及农村人口效应一定程度上起抑制作用。研究显示,我国农业碳排放地区差异显著,需要制定差异化的减排策略,推动农业低碳与高质量发展。

化学转化驱动杂质分离在实验教学中的应用——氟代扁桃酸的纯化新方法

基于“问题导向、兴趣驱动、自主探究”的综合实验教学理念,在有机化学实验教学中融入“化学转化驱动杂质分离”理论知识,设计创新综合实验。运用化学转化实现待纯化目标分子(α-氟苯基乙酸,简称“氟代扁桃酸”)与杂质(扁桃酸)的有效分离,产物纯度分别可达到98.7%和97.0%。整个实验中使用到的主要药品试剂价格低廉,易获取,且可回收再利用,充分体现了原子经济性和绿色化学思想。实验过程中,应用了多种有机化学实验的基本技能,包括减压蒸馏、浓缩脱溶、重结晶、过滤等必要实验技能,以及薄层色谱法、核磁共振等重要分析手段。熟练掌握这些重要的实验技能和分析手段,能够培养学生以基础理论指导实验、有效分离性质差异小的待测有机化合物、分析实验现象的能力,进一步提升本科生的学术修养、科学素养和综合运用知识解决实际问题的能力。

风药治疗恶性肿瘤的研究进展

总结、分析近年风药治疗恶性肿瘤的理论、临床和实验研究等方面文献,发现风药对肺癌、肝癌、脑瘤、大肠癌等多种癌种均有确切疗效,其主要通过调控信号通路诱导细胞凋亡自噬及增殖转移、抑制肿瘤血管生成、增强免疫力、逆转细胞多药耐药等机制发挥抗癌作用。目前治疗恶性肿瘤主流思想仍是从痰浊、瘀血等有形实邪着手,风药在抗癌领域的应用尚未得到广泛认可,仍需进一步开展风药治疗恶性肿瘤的临床规范化研究及微观机制探索,为临床治疗恶性肿瘤提供新思路。

基于LightGBM与SHAP的信贷违约预测方法研究

机器学习方法在信贷领域取得了较好的成果,但由于缺乏可解释性,应用受到限制,为增加其可信度和透明度,克服“黑盒”模型缺乏可解释性的缺陷,基于LightGBM算法建立信贷违约预测模型,并设计SHAP算法对模型的结果进行解释。结果表明,模型性能更好,预测精度更高,其精度高达88.61%;SHAP算法解释结果表明“信用组合的分类”“要支付的剩余债务”“每月EMI付款”等因素对信贷决策有着重要影响。

Review on laser directed energy deposited aluminum alloys

Lightweight aluminum(Al)alloys have been widely used in frontier fields like aerospace and automotive industries,which attracts great interest in additive manufacturing(AM)to process high-value Al parts.As a mainstream AM technique,laser-directed energy deposition(LDED)shows good scalability to meet the requirements for large-format component manufacturing and repair.However,LDED Al alloys are highly challenging due to their inherent poor printability(e.g.low laser absorption,high oxidation sensitivity and cracking tendency).To further promote the development of LDED high-performance Al alloys,this review offers a deep understanding of the challenges and strategies to improve printability in LDED Al alloys.The porosity,cracking,distortion,inclusions,element evaporation and resultant inferior mechanical properties(worse than laser powder bed fusion)are the key challenges in LDED Al alloys.Processing parameter optimizations,in-situ alloy design,reinforcing particle addition and field assistance are the efficient approaches to improving the printability and performance of LDED Al alloys.The underlying correlations between processes,alloy innovation,characteristic microstructures,and achievable performances in LDED Al alloys are discussed.The benchmark mechanical properties and primary strengthening mechanism of LDED Al alloys are summarized.This review aims to provide a critical and in-depth evaluation of current progress in LDED Al alloys.Future opportunities and perspectives in LDED high-performance Al alloys are also outlined.

Effects of surface chlorine atoms on charge distribution and reaction barriers for photocatalytic CO_(2)reduction

Photocatalytic CO_(2)reduction to produce high value-added carbon-based fuel has been proposed as a promising approach to mitigate global warming issues.However,the conversion efficiency and product selectivity are still low due to the sluggish dynamics of transfer processes involved in proton-assisted multi-electron reactions.Lowering the formation energy barriers of intermediate products is an effective method to enhance the selectivity and productivity of final products.In this study,we aim to regulate the surface electronic structure of Bi_(2)WO_(6)by doping surface chlorine atoms to achieve effective photocatalytic CO_(2)reduction.Surface Cl atoms can enhance the absorption ability of light,affect its energy band structure and promote charge separation.Combined with DFT calculations,it is revealed that surface Cl atoms can not only change the surface charge distribution which affects the competitive adsorption of H_(2)O and CO_(2),but also lower the formation energy barrier of intermediate products to generate more intermediate*COOH,thus facilitating CO production.Overall,this study demonstrates a promising surface halogenation strategy to enhance the photocatalytic CO_(2)reduction activity of a layered structure Bi-based catalyst.

Shallow sub-lakes are essential for sustaining the successful wintering of waterbirds in Poyang Lake,China

For migratory waterbirds,the quality of wintering habitat is related to spring migration and successful breeding in the next year.The availability of food resources in the habitat is critical and varies within water levels.Although the water-level fluctuations in Poyang Lake have been extremely variable interannually in recent years,the wintering waterbird populations have remained relatively stable.Hence,the mechanism of maintaining the stability is worth exploring.This study aimed to compare the distribution of vegetation and herbivorous wa-terbirds in 2015-2016 and 2016-2017,focusing on three shallow sub-lakes and one main lake are.The results showed that the emergence of tubers and the growth of Carex spp.provided a continuous food supply and habitat for wintering waterbirds with a gradual decline in the water level.Shallow sub-lakes supported almost all of the tuber-eating waterbirds(1.42-1.62×10^(5))and most geese(1.34-1.53×10^(6)).However,the main lake area,covered with Persicaria hydropiper,did not provide adequate and accessible food.This resulted in almost no distribution of tuber-eating waterbirds,with only a few geese congregating in early winter.Our results demonstrated that the shallow sub-lakes under human control provided a different environment from the main lake and are key to sustaining the successful wintering of hundreds of thousands of migratory waterbirds in Poyang Lake.Therefore,we recommend refining the anthropogenic management of the shallow sub-lakes to regulate the water level to ensure the carrying capacity of Poyang Lake.

Proactive Caching at the Wireless Edge:A Novel Predictive User Popularity-Aware Approach

Mobile Edge Computing(MEC)is a promising technology that provides on-demand computing and efficient storage services as close to end users as possible.In an MEC environment,servers are deployed closer to mobile terminals to exploit storage infrastructure,improve content delivery efficiency,and enhance user experience.However,due to the limited capacity of edge servers,it remains a significant challenge to meet the changing,time-varying,and customized needs for highly diversified content of users.Recently,techniques for caching content at the edge are becoming popular for addressing the above challenges.It is capable of filling the communication gap between the users and content providers while relieving pressure on remote cloud servers.However,existing static caching strategies are still inefficient in handling the dynamics of the time-varying popularity of content and meeting users’demands for highly diversified entity data.To address this challenge,we introduce a novel method for content caching over MEC,i.e.,PRIME.It synthesizes a content popularity prediction model,which takes users’stay time and their request traces as inputs,and a deep reinforcement learning model for yielding dynamic caching schedules.Experimental results demonstrate that PRIME,when tested upon the MovieLens 1M dataset for user request patterns and the Shanghai Telecom dataset for user mobility,outperforms its peers in terms of cache hit rates,transmission latency,and system cost.

A Novel Graph Structure Learning Based Semi-Supervised Framework for Anomaly Identification in Fluctuating IoT Environment

With the rapid development of Internet of Things(IoT)technology,IoT systems have been widely applied in health-care,transportation,home,and other fields.However,with the continuous expansion of the scale and increasing complexity of IoT systems,the stability and security issues of IoT systems have become increasingly prominent.Thus,it is crucial to detect anomalies in the collected IoT time series from various sensors.Recently,deep learning models have been leveraged for IoT anomaly detection.However,owing to the challenges associated with data labeling,most IoT anomaly detection methods resort to unsupervised learning techniques.Nevertheless,the absence of accurate abnormal information in unsupervised learning methods limits their performance.To address these problems,we propose AS-GCN-MTM,an adaptive structural Graph Convolutional Networks(GCN)-based framework using a mean-teacher mechanism(AS-GCN-MTM)for anomaly identification.It performs better than unsupervised methods using only a small amount of labeled data.Mean Teachers is an effective semi-supervised learning method that utilizes unlabeled data for training to improve the generalization ability and performance of the model.However,the dependencies between data are often unknown in time series data.To solve this problem,we designed a graph structure adaptive learning layer based on neural networks,which can automatically learn the graph structure from time series data.It not only better captures the relationships between nodes but also enhances the model’s performance by augmenting key data.Experiments have demonstrated that our method improves the baseline model with the highest F1 value by 10.4%,36.1%,and 5.6%,respectively,on three real datasets with a 10%data labeling rate.

Development of a rapid and efficient system for CR genes identification based on hairy root transformation in Brassicaceae

Many economically important crops and vegetables belonging to the cruciferous family are heavily endangered by clubroot disease caused by Plasmodiophora brassicae infection.Breeding of clubroot resistant cultivars based on mapping and cloning of resistant genes is commonly regarded as the most cost-effective and efficient way to fight against this disease.The traditional way of R gene functional validation requires stable transformation that is both time-and labor-consuming.In this study,a rapid and efficient hairy-root transgenic protocol mediated by Agrobacterium rhizogenes was developed.The transformation positive rate was over 80%in Brassica napus showed by GUS reporter gene and this transformation only took 1/6 of the time compared with stable transformation.The system was applicable to different B.napus varieties and other cruciferous crops including Brassica rapa and Brassica oleracea.In particular,two known CR genes,CRA3.7.1 and CRA8.2.4 were used respectively,as example to show that the system works well for CR gene study combined with subsequent P.brassicae infection in B.napus.Most importantly,it works both in over-expression that led to disease resistance,as well as in RNAi which led to disease susceptible phenotype.Therefore,this system can be used in batch-wise identification of CR genes,and also offered the possibility of manipulating key genes within the P.brassicae genome that could improve our knowledge on host-pathogen interaction.

Multi-dimensional multiplexing optical secret sharing framework with cascaded liquid crystal holograms

Secret sharing is a promising technology for information encryption by splitting the secret information into different shares.However,the traditional scheme suffers from information leakage in decryption process since the amount of available information channels is limited.Herein,we propose and demonstrate an optical secret sharing framework based on the multi-dimensional multiplexing liquid crystal(LC)holograms.The LC holograms are used as spatially separated shares to carry secret images.The polarization of the incident light and the distance between different shares are served as secret keys,which can significantly improve the information security and capacity.Besides,the decryption condition is also restricted by the applied external voltage due to the variant diffraction efficiency,which further increases the information security.In implementation,an artificial neural network(ANN)model is developed to carefully design the phase distribution of each LC hologram.With the advantage of high security,high capacity and simple configuration,our optical secret sharing framework has great potentials in optical encryption and dynamic holographic display.

Layer-Valley Hall Effect under Inversion and Time-Reversal Symmetries

Hall effects have been the central paradigms in modern physics,materials science and practical applications,and have led to many exciting breakthroughs,including the discovery of topological Chern invariants and the revolution of metrological resistance standard.To date,the Hall effects have mainly focused on a single degree of freedom(Do F),and most of them require the breaking of spatial-inversion and/or time-reversal symmetries.Here we demonstrate a new type of Hall effect,i.e.,layer-valley Hall effect,based on a combined layer-valley Do F characterized by the product of layer and valley indices.The layer-valley Hall effect has a quantum origin arising from the layer-valley contrasting Berry curvature,and can occur in nonmagnetic centrosymmetric crystals with both spatial-inversion and time-reversal symmetries,transcending the symmetry constraints of single Do F Hall effect based on the constituent layer or valley index.Moreover,the layer-valley Hall effect is highly tunable and shows a W-shaped pattern in response to the out-of-plane electric fields.Additionally,we discuss the potential detection approaches and material-specific design principles of layer-valley Hall effect.Our results demonstrate novel Hall physics and open up exotic paradigms for new research direction of layer-valleytronics that exploits the quantum nature of the coupled layer-valley DoF.

Bone marrow edema in a postpartum female following ankle sprain: a case report

Bone marrow edema(BME)is characterized by an accumulation of interstitial fluid within the bone marrow,the cancellous,hematopoietic compartment within bones.[1]BME is divided into two principal categories:idiopathic or primary BME,with an unknown etiology,and secondary BME,which occurs as a result of an identifiable underlying pathology.[2]Although the prevalence of BME is not limited to specific demographic parameters,it shows a predilection for males or individuals assigned male at birth,predominantly aged between the ages of 30 and 60 years,especially in cases of bone marrow edema syndrome(BMES),a rare idiopathic variant.[3]The etiological spectrum of BME is diverse,including oncological entities(such as acute myeloid leukemia and osteosarcoma),degenerative diseases(such as osteoarthritis),infectious processes(osteomyelitis),ischemic conditions(avascular necrosis),metabolic dysfunctions(osteoporosis),inflammatory disorders(rheumatoid arthritis),and traumatic injuries(such as stress fractures).[1,2]Clinically,BME primarily manifests as localized pain,often accompanied by joint effusion and warmth near the affected joint.Diagnostic protocols typically include physical examination,serological assays,bone marrow biopsies,dual-energy X-ray absorptiometry(DEXA)scans,magnetic resonance imaging(MRI),and ultrasonography,with computed tomography(CT)scans and radiographs being less effective.

Gigantic occipital epidermal cyst in a 56-year-old female:A case report

BACKGROUND Gigantic epidermal cysts(GECs)are rare benign skin appendicular tumours also known as keratinocysts.GECs have a high incidence and their wall is made up of epidermis.Epidermal cysts can occur in any part of the skin;clinical manifestations include skin colour hemispherical swelling;cystic;mobile;0.5 cm to several centimetres in diameter;and slow growth.CASE SUMMARY Herein,we report a case involving a 56-year-old female with a GEC in the occipitalia.On July 25,2023,a patient with a GEC was admitted to the neurosurgery Department of the Second Affiliated Hospital of Xi'an Medical University.The phyma was shown to be a solid mass during the operation and was confirmed to be a GEC based on pathological examination.CONCLUSION Epidermal cysts are common cystic nodules on the surface of the body,the aetiology is unclear,the clinical manifestations can vary,and the misdiagnosis rate is high.However,giant epidermal cysts are rare.In most cases,however,the prognosis is satisfactory.This paper analyses and summarizes the population,location,clinical and pathological characteristics and pathogenesis of the disease to strengthen the understanding of this disease and improve the accuracy of clinical diagnosis.