Coherent optical frequency transfer via 972-km fiber link

We demonstrate coherent optical frequency dissemination over a distance of 972 km by cascading two spans where the phase noise is passively compensated for.Instead of employing a phase discriminator and a phase locking loop in the conventional active phase control scheme,the passive phase noise cancellation is realized by feeding double-trip beat-note frequency to the driver of the acoustic optical modulator at the local site.This passive scheme exhibits fine robustness and reliability,making it suitable for long-distance and noisy fiber links.An optical regeneration station is used in the link for signal amplification and cascaded transmission.The phase noise cancellation and transfer instability of the 972-km link is investigated,and transfer instability of 1.1×10^(-19)at 10^(4)s is achieved.This work provides a promising method for realizing optical frequency distribution over thousands of kilometers by using fiber links.

广州市痴呆共病患者疾病直接经济负担及影响因素分析

目的:分析广州市痴呆共病患者直接经济负担及其影响因素,为痴呆共病患者的经济成本测算与家庭照护负担评估提供参考依据。方法:采用自编问卷,收集广州市痴呆共病患者社会人口学特征、治疗情况、疾病直接经济负担等情况;使用Charlson查尔森合并症指数(charlson comorbidity index,CCI)评估共病负担;使用直接法估算直接经济负担费用,经正态性检验服从偏态分布,对数转换使其呈近似正态化后应用于多元线性回归模型。结果:广州市痴呆共病患者过去1年产生的人均直接经济负担费用为7180.00(3600.00,15568.67)元,其中人均直接医疗费用为6150.00(3185.00,12590.00)元,人均直接非医疗费用为0.00(0.00,2082.50);CCI共病负担指数为5.00(5.00,6.00),共病负担与直接经济负担均较重。多元线性回归结果显示疾病直接经济负担的主要影响因素为患者所在区域、就诊地点、合并慢性阻塞性肺疾病(chronic obstructive pulmonary disease,COPD)或老年慢性支气管炎、合并心脏病及服用痴呆药物种类。结论:广州市痴呆共病患者直接经济负担较重,影响因素具有多维度与复杂性的特征,需要政府、社会和医疗机构等多方面共同努力与探索。

A theoretical framework for improved fire suppression by linking management models with smart early fire detection and suppression technologies

Bushfires are devastating to forest managers,owners,residents,and the natural environment.Recent tech-nological advances indicate a potential for faster response times in terms of detecting and suppressing fires.However,to date,all these technologies have been applied in isola-tion.This paper introduces the latest fire detection and sup-pression technologies from ground to space.An operations research method was used to assemble these technologies into a theoretical framework for fire detection and suppres-sion.The framework harnesses the advantages of satellite-based,drone,sensor,and human reporting technologies as well as image processing and artificial intelligence machine learning.The study concludes that,if a system is designed to maximise the use of available technologies and carefully adopts them through complementary arrangements,a fire detection and resource suppression system can achieve the ultimate aim:to reduce the risk of fire hazards and the dam-age they may cause.

Evolutionary Variational YOLOv8 Network for Fault Detection in Wind Turbines

Deep learning has emerged in many practical applications,such as image classification,fault diagnosis,and object detection.More recently,convolutional neural networks(CNNs),representative models of deep learning,have been used to solve fault detection.However,the current design of CNNs for fault detection of wind turbine blades is highly dependent on domain knowledge and requires a large amount of trial and error.For this reason,an evolutionary YOLOv8 network has been developed to automatically find the network architecture for wind turbine blade-based fault detection.YOLOv8 is a CNN-backed object detection model.Specifically,to reduce the parameter count,we first design an improved FasterNet module based on the Partial Convolution(PConv)operator.Then,to enhance convergence performance,we improve the loss function based on the efficient complete intersection over the union.Based on this,a flexible variable-length encoding is proposed,and the corresponding reproduction operators are designed.Related experimental results confirmthat the proposed approach can achieve better fault detection results and improve by 2.6%in mean precision at 50(mAP50)compared to the existing methods.Additionally,compared to training with the YOLOv8n model,the YOLOBFE model reduces the training parameters by 933,937 and decreases the GFLOPS(Giga Floating Point Operations Per Second)by 1.1.

Research on the IL-Bagging-DHKELM Short-Term Wind Power Prediction Algorithm Based on Error AP Clustering Analysis

With the continuous advancement of China’s“peak carbon dioxide emissions and Carbon Neutrality”process,the proportion of wind power is increasing.In the current research,aiming at the problem that the forecasting model is outdated due to the continuous updating of wind power data,a short-term wind power forecasting algorithm based on Incremental Learning-Bagging Deep Hybrid Kernel Extreme Learning Machine(IL-Bagging-DHKELM)error affinity propagation cluster analysis is proposed.The algorithm effectively combines deep hybrid kernel extreme learning machine(DHKELM)with incremental learning(IL).Firstly,an initial wind power prediction model is trained using the Bagging-DHKELM model.Secondly,Euclidean morphological distance affinity propagation AP clustering algorithm is used to cluster and analyze the prediction error of wind power obtained from the initial training model.Finally,the correlation between wind power prediction errors and Numerical Weather Prediction(NWP)data is introduced as incremental updates to the initial wind power prediction model.During the incremental learning process,multiple error performance indicators are used to measure the overall model performance,thereby enabling incremental updates of wind power models.Practical examples show the method proposed in this article reduces the root mean square error of the initial model by 1.9 percentage points,indicating that this method can be better adapted to the current scenario of the continuous increase in wind power penetration rate.The accuracy and precision of wind power generation prediction are effectively improved through the method.

Manipulating the Spatial Structure of Second-Order Quantum Coherence Using Entangled Photons

High-order quantum coherence reveals the statistical correlation of quantum particles. Manipulation of quantum coherence of light in the temporal domain enables the production of the single-photon source, which has become one of the most important quantum resources. High-order quantum coherence in the spatial domain plays a crucial role in a variety of applications, such as quantum imaging, holography, and microscopy. However, the active control of second-order spatial quantum coherence remains a challenging task. Here we predict theoretically and demonstrate experimentally the first active manipulation of second-order spatial quantum coherence,which exhibits the capability of switching between bunching and anti-bunching, by mapping the entanglement of spatially structured photons. We also show that signal processing based on quantum coherence exhibits robust resistance to intensity disturbance. Our findings not only enhance existing applications but also pave the way for broader utilization of higher-order spatial quantum coherence.

Novel insights into immune-related genes associated with type 2 diabetes mellitus-related cognitive impairment

BACKGROUND The cognitive impairment in type 2 diabetes mellitus(T2DM)is a multifaceted and advancing state that requires further exploration to fully comprehend.Neu-roinflammation is considered to be one of the main mechanisms and the immune system has played a vital role in the progression of the disease.AIM To identify and validate the immune-related genes in the hippocampus associated with T2DM-related cognitive impairment.METHODS To identify differentially expressed genes(DEGs)between T2DM and controls,we used data from the Gene Expression Omnibus database GSE125387.To identify T2DM module genes,we used Weighted Gene Co-Expression Network Analysis.All the genes were subject to Gene Set Enrichment Analysis.Protein-protein interaction network construction and machine learning were utilized to identify three hub genes.Immune cell infiltration analysis was performed.The three hub genes were validated in GSE152539 via receiver operating characteristic curve analysis.Validation experiments including reverse transcription quantitative real-time PCR,Western blotting and immunohistochemistry were conducted both in vivo and in vitro.To identify potential drugs associated with hub genes,we used the Comparative Toxicogenomics Database(CTD).RESULTS A total of 576 DEGs were identified using GSE125387.By taking the intersection of DEGs,T2DM module genes,and immune-related genes,a total of 59 genes associated with the immune system were identified.Afterward,machine learning was utilized to identify three hub genes(H2-T24,Rac3,and Tfrc).The hub genes were associated with a variety of immune cells.The three hub genes were validated in GSE152539.Validation experiments were conducted at the mRNA and protein levels both in vivo and in vitro,consistent with the bioinformatics analysis.Additionally,11 potential drugs associated with RAC3 and TFRC were identified based on the CTD.CONCLUSION Immune-related genes that differ in expression in the hippocampus are closely linked to microglia.We validated the expression of three hub genes both in vivo and in vitro,consistent with our bioinformatics results.We discovered 11 compounds associated with RAC3 and TFRC.These findings suggest that they are co-regulatory molecules of immunometabolism in diabetic cognitive impairment.

Coordinated Voltage Control of Distribution Network ConsideringMultiple Types of Electric Vehicles

The couple between the power network and the transportation network(TN)is deepening gradually with the increasing penetration rate of electric vehicles(EV),which also poses a great challenge to the traditional voltage control scheme.In this paper,we propose a coordinated voltage control strategy for the active distribution networks considering multiple types of EV.In the first stage,the action of on-load tap changer and capacitor banks,etc.,are determined by optimal power flow calculation,and the node electricity price is also determined based on dynamic time-of-use tariff mechanism.In the second stage,multiple operating scenarios of multiple types of EVs such as cabs,private cars and buses are considered,and the scheduling results of each EV are solved by building an optimization model based on constraints such as queuing theory,Floyd-Warshall algorithm and traffic flow information.In the third stage,the output power of photovoltaic and energy storage systems is fine-tuned in the normal control mode.The charging power of EVs is also regulated in the emergency control mode to reduce the voltage deviation,and the amount of regulation is calculated based on the fair voltage control mode of EVs.Finally,we test the modified IEEE 33-bus distribution system coupled with the 24-bus Beijing TN.The simulation results show that the proposed scheme can mitigate voltage violations well.

Dermal thickness,rather than drug concentration and injection speed,influences the effective area of botulinum toxin type A in the dermis

Background:Recently,microbotulinum,a new technique that involves injecting botulinum toxin type A(BoNTA)microdroplets into superficial cutaneous tissue,has gained popularity.The precise distribution of BoNTA in the targeted area profoundly affects outcomes.Many factors may influence the effective area of BoNTA in the dermis.This study aimed to determine the dermal distribution properties of BoNTA to guide microbotulinum injection.Methods:Ten healthy males aged 18–65 years without BoNTA treatment in the previous year were recruited to receive intradermal injections in the chest and back.Ultrasound was used to ensure the intradermal delivery of injections and measure the dermal thickness.The minor iodine starch test was performed at baseline and 3 days,7 days,21 days,1 month,and 2 months after treatment.Results:All participants received intradermal injections.The dermis was thinner on the chest(thickness,0.20±0.03 cm)than on the back(thickness,0.39±0.07 cm)(P<0.05).An injection in the thicker dermis had a significantly smaller effective area at every follow-up visit.The drug concentration did not affect the effective area except at 3 days after treatment.Injection speed did not influence the effective area at any follow-up visits.Conclusion:An injection in a thicker dermis leads to a smaller effective area for intradermal injections.When the BoNTA dose is the same,the drug concentration and injection speed do not matter.

Practice of Perioperative Rational Use of Antibacterial Drugs Based on Drug Pathway

[Objectives]To establish a new management model for rational use of perioperative antibacterial drugs in surgical departments.[Methods]Based on evidence-based medicine,the department s drug pathway was formulated,and the new mode of rational drug use control was established by using fine pharmaceutical technology intervention,and the intervention effect was evaluated by the intensity of antibacterial drug use,per capita drug costs and the proportion of drugs.[Results]After adopting drug pathway in departments,the intensity of antibacterial drug use,per capita drug costs and the proportion of drugs decreased significantly,and the effect of rational drug use control was remarkable.[Conclusions]The drug pathway provides a new management and control mode for the rational use of perioperative antibacterial drugs in surgical departments of hospitals.Thus,it is worthy of popularization and application.

Advances in Research of Anti-tumor Effect of Aconiti Radix

In this paper,the anti-tumor effects of Aconiti Radix were reviewed and summarized,and the clinical feasibility of Aconiti Radix as a potential anti-tumor drug was analyzed,in order to provide a useful reference for the future research and development of new anti-cancer drugs of Aconiti Radix.

Three-Dimensional Multi-Phase Microscopic Simulation of Service Life of Recycled Large Aggregate Self-Compacting Concrete

Recycled large aggregate self-compacting concrete (RLA-SCC) within multiple weak areas. These weak areas have poor resistance to chloride ion erosion, which affects the service life of RLA-SCC in the marine environment. A three-dimensional multi-phase mesoscopic numerical model of RLA-SCC was established to simulate the chloride ions transportation in concrete. Experiments of RLA-SCC immersing in chloride solution were carried out to verify the simulation results. The effects of recycled large aggregate (RLA) content and RLA particle size on the service life of concrete were explored. The results indicate that the mesoscopic numerical simulation results are in good agreement with the experimental results. At the same depth, the closer to the surface of the RLA, the greater the chloride ion concentration. The service life of RLA-SCC in marine environment decreases with the increase of RLA content. Compared with the service life of 20% content, the service life of 25% and 30% content decreased by 20% and 42% respectively. Increasing the particle size of RLA can effectively improve the service life of RLA-SCC in chloride environment. Compared with the service life of 50 mm particle size, the service life of 70 mm and 90 mm increased by 61% and 163%, respectively. .

Development and validation of a nomogram for predicting survival in patients with acute pancreatitis

BACKGROUND:Acute pancreatitis(AP)is a complex and heterogeneous disease.We aimed to design and validate a prognostic nomogram for improving the prediction of short-term survival in patients with AP.METHODS:The clinical data of 632 patients with AP were obtained from the Medical Information Mart for Intensive Care(MIMIC)-IV database.The nomogram for the prediction of 30-day,60-day and 90-day survival was developed by incorporating the risk factors identified by multivariate Cox analyses.RESULTS:Multivariate Cox proportional hazard model analysis showed that age(hazard ratio[HR]=1.06,95%confidence interval[95%CI]1.03-1.08,P<0.001),white blood cell count(HR=1.03,95%CI 1.00-1.06,P=0.046),systolic blood pressure(HR=0.99,95%CI 0.97-1.00,P=0.015),serum lactate level(HR=1.10,95%CI 1.01-1.20,P=0.023),and Simplified Acute Physiology Score II(HR=1.04,95%CI 1.02-1.06,P<0.001)were independent predictors of 90-day mortality in patients with AP.A prognostic nomogram model for 30-day,60-day,and 90-day survival based on these variables was built.Receiver operating characteristic(ROC)curve analysis demonstrated that the nomogram had good accuracy for predicting 30-day,60-day,and 90-day survival(area under the ROC curve:0.796,0.812,and 0.854,respectively;bootstrap-corrected C-index value:0.782,0.799,and 0.846,respectively).CONCLUSION:The nomogram-based prognostic model was able to accurately predict 30-day,60-day,and 90-day survival outcomes and thus may be of value for risk stratification and clinical decision-making for critically ill patients with AP.

采用旋转圆盘膜技术从水溶液中选择性分离La(Ⅲ)和Ce(Ⅲ)

以聚丙烯酸酯钠(PAAS)为络合剂,采用旋转圆盘膜(RDM)络合−超滤和剪切诱导解离耦合超滤的方法,从水溶液中选择性分离La(Ⅲ)和Ce(Ⅲ)。考察PAAS与稀土离子的质量比(m(P)/m(RE))和pH对离子截留率的影响,确定合适的络合条件为m(P)/m(RE)=4.0和pH 5.0~7.0。在pH 5.0的条件下,PAA-La和PAA-Ce络合物的临界剪切速率分别为8.5×10^(4)和9.0×10^(4) s^(−1)。通过前线轨道理论对配合物的能量进行计算,得到能隙值ΔE。结果表明,PAA-Ce配合物更稳定,这与临界剪切速率的结果一致。在pH为5.0和6.0、转速为1500 r/min时,两种离子的最大选择分离系数(β_(La/Ce))分别为49.3和16.6。最后,考察再生PAAS的络合性能。

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.

Intrinsic thermal stability of inverted perovskite solar cells based on electrochemical deposited PEDOT

Thermal stability of perovskite materials is an issue impairing the long-term operation of inverted perovskite solar cells(PSCs). Herein, the thermal attenuation mechanism of the MAPb I3films that deposited on two different hole transport layers(HTL), poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(PEDOT:PSS) and poly(3,4-ethylenedioxythiophene)(PEDOT), is comprehensively studied by applying a heat treatment at 85℃. The thermal stress causes the mutual ions migration of I, Pb and Ag through the device, which leads to the thermal decomposition of perovskite to form Pb I2. Interestingly, we find that I ions tend to migrate more towards electron transport layer(ETL) during heating, which is different with the observation of I ions migration towards HTL when bias pressure is applied. Moreover, the use of electrochemical deposited PEDOT as HTL significantly decreases the defect density of MAPb I3films as compared to PEDOT:PSS supported one. The electrochemical deposition PEDOT has good carrier mobility and low acidity, which avoids the drawbacks of aqueous PEDOT:PSS. Accordingly, the inverted PSCs based on PEDOT show superior durability than that with PEDOT:PSS. Our results reveal detailed degradation routes of a new kind of inverted PSCs which can contribute to the understanding of the failure of thermal-aged inverted PSCs.

Subcellular Distribution and Chemical Forms of Cadmium in the Medicine Food Homology Plant Platycodon grandiflorum(Jacq.)A.DC.

Although Platycodon grandiflorum(Jacq.)A.DC.is a renowned medicine food homology plant,reports of excessive cadmium(Cd)levels are common,which affects its safety for clinical use and food consumption.To enable its Cd levels to be regulated or reduced,it is necessary to first elucidate the mechanism of Cd uptake and accumulation in the plant,in addition to its detoxification mechanisms.This present study used inductively couple plasma-mass-spectrometry to analyze the subcellular distribution and chemical forms of Cd in different tissues of P.grandiflorum.The experimental results showed that Cd was mainly accumulated in the roots[predominantly in the cell wall(50.96%-61.42%)],and it was found primarily in hypomobile and hypotoxic forms.The proportion of Cd in the soluble fraction increased after Cd exposure,and the proportion of insoluble phosphate Cd and oxalate Cd increased in roots and leaves,with a higher increase in oxalate Cd.Therefore,it is likely that root retention mechanisms,cell wall deposition,vacuole sequestration,and the formation of low mobility and low toxicity forms are tolerance strategies for Cd detoxification used by P.grandiflorum.The results of this study provide a theoretical grounding for the study of Cd accumulation and detoxification mechanisms in P.grandiflorum,and they can be used as a reference for developing Cd limits and standards for other medicine food homology plants.

MDNN:Predicting Student Engagement via Gaze Direction and Facial Expression in Collaborative Learning

Prediction of students’engagement in aCollaborative Learning setting is essential to improve the quality of learning.Collaborative learning is a strategy of learning through groups or teams.When cooperative learning behavior occurs,each student in the group should participate in teaching activities.Researchers showed that students who are actively involved in a class gain more.Gaze behavior and facial expression are important nonverbal indicators to reveal engagement in collaborative learning environments.Previous studies require the wearing of sensor devices or eye tracker devices,which have cost barriers and technical interference for daily teaching practice.In this paper,student engagement is automatically analyzed based on computer vision.We tackle the problem of engagement in collaborative learning using a multi-modal deep neural network(MDNN).We combined facial expression and gaze direction as two individual components of MDNN to predict engagement levels in collaborative learning environments.Our multi-modal solution was evaluated in a real collaborative environment.The results show that the model can accurately predict students’performance in the collaborative learning environment.

Analysis of EGFR gene mutations in lung adenocarcinoma in Karamay,Xinjiang,China

Background:To investigate the mutation types and mutation rate of the epidermal growth factor receptor(EGFR)gene in patients with lung adenocarcinoma and the clinical features of lung adenocarcinoma with EGFR gene mutations in Karamay,Xinjiang,China.Methods:Paraffin-embedded tissue samples of adenocarcinoma patients were collected in the Karamay Central Hospital from March 2016 to June 2019,and mutations in exon 18–21 of the EGFR gene were detected by the allele-specific amplification polymerase chain reaction(Amplification RefractoryMutation System–PCR)method.The relationships between themutation types,mutation incidence,and clinical features were analyzed.Results:Of the 170 patients with lung adenocarcinoma,83 had EGFR mutations.The total mutation rate of EGFR in patients with lung adenocarcinoma was 48.8%,which included mutations in exons 18(1.2%[2/170]),19(19.4%[33/170]),20(2.4%[4/170]),and 21(20.6%[35/170]).Intriguingly,there was a case with 9 mutations in exons 20 and 21.The mutations in exon 19 of EGFR resulted in the deletion of codons 746 to 750.The main mutation in exon 21 was L858R(91.4%[32/35]).There was no significant difference in exons 19 and 21 mutation rates(P>0.05).The mutation rate of EGFR in female patients was significantly higher than that in male patients(P<0.05)but had no correlation with the age,smoking status,and clinical stage of patients with non–small cell lung cancer(P>0.05).The EGFR mutation rate may be related to the degree of tumor differentiation.Conclusions:Among patients with lung adenocarcinoma in Kelamayi(city in Xinjiang),EGFR mutations were more frequently detected in female patients,and the main sites of mutations were exons 19 and 21.

屈光参差性弱视与斜视性弱视的电生理研究

目的分析屈光参差性弱视和斜视性弱视的视觉诱发电位(VEP)与对比敏感度(CS)的特征性变化,并探讨2种弱视不同的致病机制。方法采用德国罗兰公司RETI scan 3.15系统对20例屈光参差性弱视、9例斜视性弱视和18例非弱视性儿童的双眼行VEP和CS检查,进行弱视眼、对侧眼及非弱视眼之间的对比研究。结果与对侧眼或非弱视眼相比,屈光参差性弱视眼在高空间频率条件下潜时延长,而斜视性弱视眼在全空间频率条件下潜时延长。2种弱视眼的振幅在低频时均下降。屈光参差性弱视对侧眼与非弱视眼比较差异无统计学意义(P>0.05),而斜视性弱视对侧眼的潜时在低频下较非弱视眼延长,差异有统计学意义(P<0.05)。屈光参差性弱视眼和对侧眼的CS与非弱视眼比较差异无统计学意义(P>0.05)。斜视性弱视眼表现为全空间频率上的CS下降,差异有统计学意义(P<0.05),其对侧眼的CS则优于非弱视眼。结论本研究结果支持斜视性弱视与屈光参差性弱视拥有不同神经机制的观点。斜视性弱视的对侧眼并非"健眼"。VEP与CS检查对弱视诊断具有临床意义。