老年脑血管疾病的影响因素及防治策略

脑血管疾病是威胁老年人健康的主要疾病之一,其预防和管理对于降低发病率、减轻医疗负担以及提高患者生活质量具有重要意义。随着医学及相关学科的不断发展,脑血管疾病的预防和管理策略也在持续更新与完善。然而,在实际操作中仍存在诸多问题,如预防意识不足、管理体系不完善以及跨学科合作缺乏等。现代医疗技术的发展为提高老年人的生存质量、防止突发事件发生开辟了新途径。本文对相关内容进行综述,提出目前医疗技术在降低老年人脑血管病发病风险方面的成就以及今后的发展趋势。在本章中,将对该系统进行进一步研究,并对其未来发展及可能的变化进行探讨。

Spectral CT imaging parameters and Ki-67 labeling index in lung adenocarcinoma

Objective: To explore the correlation between the spectral computed tomography(CT) imaging parameters and the Ki-67 labeling index in lung adenocarcinoma.Methods: Spectral CT imaging parameters [iodine concentrations of lesions(ICLs) in the arterial phase(ICLa)and venous phase(ICLv), normalized IC in the aorta(NICa/NICv), slope of the spectral HU curve(λHUa/λHUv)and monochromatic CT number enhancement on 40 keV and 70 keV images(CT40 keVa/v, CT70keVa/v)] in 34 lung adenocarcinomas were analyzed, and common molecular markers, including the Ki-67 labeling index, were detected with immunohistochemistry. Different Ki-67 labeling indexes were measured and grouped into four grades according to the number of positive-stained cells(grade 0, ≤1%;1%<grade 1≤10%;10%<grade 2≤30%;and grade 3, >30%). One-way analysis of variance(ANOVA) was used to compare the four different grades, and the Bonferroni method was used to correct the P value for multiple comparisons. A Spearman correlation analysis was performed to further research a quantitative correlation between the Ki-67 labeling index and spectral CT imaging parameters.Results: CT40keVa, CT40 keVv, CT70keVa and CT70keVv increased as the grade increased, and CT70keVa and CT70keVv were statistically significant(P<0.05). These four parameters and the Ki-67 labeling index showed a moderate positive correlation with lung adenocarcinoma nodules. ICL, NIC and λHU in the arterial and venous phases were not significantly different among the four grades.Conclusions: The spectral CT imaging parameters CT40keVa, CT40keVv, CT70keVa and CT70keVv gradually increased with Ki-67 expression and showed a moderate positive correlation with lung adenocarcinomas.Therefore, spectral CT imaging parameter-enhanced monochromatic CT numbers at 70 keV may indicate the extent of proliferation of lung adenocarcinomas.

Prognostic factors for transarterial chemoembolization combined with sustained oxaliplatin-based hepatic arterial infusion chemotherapy of colorectal cancer liver metastasis

Objective： To investigate the prognostic factors in chemorefractory colorectal cancer liver metastasis（CRCLM）patients treated by transarterial chemoembolization（TACE） and sustained hepatic arterial infusion chemotherapy（HAIC）.Methods： Between 2006 and 2015, 162 patients who underwent 763 TACE and HAIC in total were enrolled in this retrospective study, including 110 males and 52 females, with a median age of 60（range, 26–83） years.Prognostic factors were assessed with Log-rank test, Cox univariate and multivariate analyses.Results： The median survival time（MST） and median progression-free survival（PFS） of the 162 patients from first TACE/HAIC were 15.6 months and 5.5 months respectively. Normal serum carbohydrate antigen 19-9（CA19-9, 〈37 U/m L）（P〈0.001） and carbohydrate antigen 72-4（CA72-4, 〈6.7 U/m L）（P=0.026）, combination with other local treatment（liver radiotherapy or liver radiofrequency ablation）（P=0.034） and response to TACE/HAIC（P〈0.001） were significant factors related to survival after TACE/HAIC in univariate analysis. A multivariate analysis revealed that normal serum CA19-9（P〈0.001）, response to TACE/HAIC（P〈0.001） and combination with other local treatment（P=0.001） were independent factors among them.Conclusions： Our findings indicate that serum CA19-9 〈37 U/m L and response to TACE/HAIC are significant prognostic indicators for this combined treatment, and treated with other local treatment could reach a considerable survival benefit for CRCLM. This could be useful for making decisions regarding the treatment of CRCLM.

Local inhibition of GABA affects precedence effect in the inferior colliculus

The precedence effect is a prerequisite for faithful sound localization in a complex auditory environment, and is a physiological phenomenon in which the auditory system selectively suppresses the directional information from echoes. Here we investigated how neurons in the inferior colliculus respond to the paired sounds that produce precedence-effect illusions, and whether their firing behavior can be modulated through inhibition with gamma-aminobutyric acid （GABA）. We recorded extracellularly from 36 neurons in rat inferior colliculus under three conditions： no injection, injection with saline, and injection with gamma-aminobutyric acid. The paired sounds that produced precedence effects were two identical 4-ms noise bursts, which were delivered contralaterally or ipsilaterally to the recording site. The normalized neural responses were measured as a function of different inter-stimulus delays and half-maximal interstimulus delays were acquired. Neuronal responses to the lagging sounds were weak when the inter-stimulus delay was short, but increased gradually as the delay was lengthened. Saline injection produced no changes in neural responses, but after local gamma-arninobutyric acid application, responses to the lagging stimulus were suppressed. Application of gamma-aminobutyric acid affected the normalized response to lagging sounds, independently of whether they or the paired sounds were contralateral or ipsilateral to the recording site. These observations suggest that local inhibition by gamma-aminobutyric acid in the rat inferior colliculus shapes the neural responses to lagging sounds, and modulates the precedence effect.

Utility of CT in differentiating liver metastases of well-differentiated gastroenteropancreatic neuroendocrine neoplasms from poorly-differentiated neuroendocrine neoplasms

Objective： To determine the capability of dynamic enhanced computed tomography（CT） to differentiate liver metastases（LMs） of well-differentiated from poorly-differentiated gastroenteropancreatic neuroendocrine neoplasms（GEP-NENs）.Methods： Patients with LMs of GEP-NENs who underwent dynamic enhanced CT examination in Peking University Cancer Hospital from January 2009 to October 2015 were included and data were retrospectively analyzed. We assessed the qualitative and quantitative CT features to identify the significant differentiating CT features of LMs of poorly-differentiated GEP-NENs from those of well-differentiated GEP-NENs using univariate analysis and a multivariate logistic regression model.Results： The study included 22 patients with LMs of well-differentiated GEP-NENs and 32 patients with LMs of poorly-differentiated GEP-NENs. Univariate analysis revealed statistically significant differences between the LMs of well-and poorly-differentiated GEP-NENs in terms of feeding arteries（36.4% vs. 75.0%, χ2=8.061,P=0.005）, intratumoral neovascularity（18.2% vs. 59.4%, χ2=9.047, P=0.003）, lymphadenopathy（27.3% vs. 81.2%,χ2=15.733, P〈0.001）, tumor-to-aortic ratio in the hepatic arterial and portal venous phase（T-A/AP： 0.297±0.080 vs.0.251±0.059, t=2.437, P=0.018; T-A/PVP： 0.639±0.138 vs. 0.529±0.117, t=3.163, P=0.003） and tumor-to-liver ratio in the hepatic arterial phase（T-L/AP： 1.108±0.267 vs. 0.907±0.240, t=2.882, P=0.006）. The LMs of poorlydifferentiated GEP-NENs showed more feeding arteries, more intratumoral neovascularity, more lymphadenopathy and a lower tumor-to-aortic ratio. Multivariate analysis suggested that intratumoral neovascularity [P=0.015, OR=0.108, 95% confidence interval（95% CI）, 0.018–0.646], lymphadenopathy（P=0.001,OR=0.055, 95% CI, 0.009–0.323） and T-A/PVP（P=0.004, OR=5.3 E–5, 95% CI, 0.000–0.044） were independent factors for differentiating LMs of poorly-differentiated from well-differentiated GEP-NENs.Conclusions： Dynamic enhanced CT features（intratumoral neovascularity, lymphadenopathy and T-A/PVP）are useful in the pathological classification of LMs of GEP-NENs.

Research on variance of subnets in network sampling

In the recent research of network sampling, some sampling concepts are misunderstood, and the variance of subnets is not taken into account. We propose the correct definition of the sample and sampling rate in network sampling, as well as the formula for calculating the variance of subnets. Then, three commonly used sampling strategies are applied to databases of the connecting nearest-neighbor（CNN） model, random network and small-world network to explore the variance in network sampling. As proved by the results, snowball sampling obtains the most variance of subnets, but does well in capturing the network structure. The variance of networks sampled by the hub and random strategy are much smaller. The hub strategy performs well in reflecting the property of the whole network, while random sampling obtains more accurate results in evaluating clustering coefficient.

Advancing large-scale thin-film PPLN nonlinear photonics with segmented tunable micro-heaters

Thin-film periodically poled lithium niobate(TF-PPLN)devices have recently gained prominence for efficient wavelength conversion processes in both classical and quantum applications.However,the patterning and poling of TF-PPLN devices today are mostly performed at chip scales,presenting a significant bottleneck for future largescale nonlinear photonic systems that require the integration of multiple nonlinear components with consistent performance and low cost.Here,we take a pivotal step towards this goal by developing a wafer-scale TF-PPLN nonlinear photonic platform,leveraging ultraviolet stepper lithography and an automated poling process.To address the inhomogeneous broadening of the quasi-phase matching(QPM)spectrum induced by film thickness variations across the wafer,we propose and demonstrate segmented thermal optic tuning modules that can precisely adjust and align the QPM peak wavelengths in each section.Using the segmented micro-heaters,we show the successful realignment of inhomogeneously broadened multi-peak QPM spectra with up to 57%enhancement of conversion efficiency.We achieve a high normalized conversion efficiency of 3802%W-1cm-2in a 6 mm long PPLN waveguide,recovering 84%of the theoretically predicted efficiency in this device.The advanced fabrication techniques and segmented tuning architectures presented herein pave the way for wafer-scale integration of complex functional nonlinear photonic circuits with applications in quantum information processing,precision sensing and metrology,and low-noise-figure optical signal amplification.

MPFracNet:A Deep Learning Algorithm for Metacarpophalangeal Fracture Detection with Varied Difficulties

Due to small size and high occult,metacarpophalangeal fracturediagnosis displays a low accuracy in terms of fracture detection and locationin X-ray images.To efficiently detect metacarpophalangeal fractures on Xrayimages as the second opinion for radiologists,we proposed a novel onestageneural network namedMPFracNet based onRetinaNet.InMPFracNet,a deformable bottleneck block(DBB)was integrated into the bottleneckto better adapt to the geometric variation of the fractures.Furthermore,an integrated feature fusion module(IFFM)was employed to obtain morein-depth semantic and shallow detail features.Specifically,Focal Loss andBalanced L1 Loss were introduced to respectively attenuate the imbalancebetween positive and negative classes and the imbalance between detectionand location tasks.We assessed the proposed model on the test set andachieved an AP of 80.4%for the metacarpophalangeal fracture detection.To estimate the detection performance for fractures with different difficulties,the proposed model was tested on the subsets of metacarpal,phalangeal andtiny fracture test sets and achieved APs of 82.7%,78.5%and 74.9%,respectively.Our proposed framework has state-of-the-art performance for detectingmetacarpophalangeal fractures,which has a strong potential application valuein practical clinical environments.

Variability of urban fractional vegetation cover and its driving factors in 328 cities in China

Urban green space promotes the health of urban residents,enhances urban ecosystem biodiversity,mitigates environmental pollution,and attenuates urban heat island effect.However,urban vegetation cover is highly heterogeneous and difficult to quantify.In this study,the variation of urban fractional vegetation cover(FVC)in 328 cities in China from 1990 to2022 was quantified based on Landsat satellite data at a 30-m resolution.It was found that from 1990 to 2005,due to increases in building density and impervious surfaces in cities,the national mean urban vegetation cover decreased from 0.38 to 0.35.After2005,urban vegetation cover began to reverse,reaching 0.45 in 2022.This increasing trend was most pronounced in newly built urban districts.The decrease in average urban vegetation cover before 2005 was mainly due to the expansion of low vegetation cover areas,while the increase in urban vegetation cover after 2005 manifested as the expansion of high vegetation cover areas.The reversal in the trend of urban vegetation cover change after 2004 is related to the gradual implementation of national policies requiring increased urban green space coverage.The urban gross domestic product(GDP)showed the highest correlation with changes in urban vegetation cover.For large and medium-sized cities,the top three factors influencing vegetation cover were GDP,urban population,and temperature.However,for cities in arid/semi-arid regions,changes in vegetation cover were more sensitive to climatic factors(such as precipitation).Although the urban vegetation cover in China has substantially increased in recent years,the urban green space in small-sized cities and in the old urban districts of large-sized cities still have room to improve.

Characterization of ferroptosis-triggered pyroptotic signaling in heart failure

Pressure overload–induced cardiac hypertrophy is a common cause of heart failure(HF),and emerging evidence suggests that excessive oxidized lipids have a detrimental effect on cardiomyocytes.However,the key regulator of lipid toxicity in cardiomyocytes during this pathological process remains unknown.Here,we used lipidomics profiling and RNA-seq analysis and found that phosphatidylethanolamines(PEs)and Acsl4 expression are significantly increased in mice with transverse aortic constriction(TAC)–induced HF compared to sham-operated mice.In addition,we found that overexpressing Acsl4 in cardiomyocytes exacerbates pressure overload‒induced cardiac dysfunction via ferroptosis.Notably,both pharmacological inhibition and genetic deletion of Acsl4 significantly reduced left ventricular chamber size and improved cardiac function in mice with TAC-induced HF.Moreover,silencing Acsl4 expression in cultured neonatal rat ventricular myocytes was sufficient to inhibit hypertrophic stimulus‒induced cell growth.Mechanistically,we found that Acsl4-dependent ferroptosis activates the pyroptotic signaling pathway,which leads to increased production of the proinflammatory cytokine IL-1β,and neutralizing IL-1βimproved cardiac function in Acsl4 transgenic mice following TAC.These results indicate that ACSL4 plays an essential role in the heart during pressure overload‒induced cardiac remodeling via ferroptosis-induced pyroptotic signaling.Together,these findings provide compelling evidence that targeting the ACSL4-ferroptosis-pyroptotic signaling cascade may provide a promising therapeutic strategy for preventing heart failure.

Diffusion-tensor imaging as an adjunct to dynamic contrastenhanced MRI for improved accuracy of differential diagnosis between breast ductal carcinoma in situ and invasive breast carcinoma

Objective： To determine the value of diffusion-tensor imaging （DTI） as an adjunct to dynamic contrastenhanced magnetic resonance imaging （DCE-MRI） for improved accuracy of differential diagnosis between breast ductal carcinoma in situ （DCIS） and invasive breast carcinoma （IBC）. Methods： The MRI data of 63 patients pathologically confirmed as breast cancer were analyzed. The conventional MRI analysis metrics included enhancement style, initial enhancement characteristic, maximum slope of increase, time to peak, time signal intensity curve （TIC） pattern, and signal intensity on FS- T2WI. The values of apparent diffusion coefficient （ADC）, directionally-averaged mean diffusivity （D^vg）, exponential attenuation （EA）, fractional anisotropy （FA）, volume ratio （VR） and relative anisotropy （RA） were calculated and compared between DCIS and IBC. Multivariate logistic regression was used to identify independent factors for distinguishing IBC and DCIS. The diagnostic performance of the diagnosis equation was evaluated using the receiver operating characteristic （ROC） curve. The diagnostic efficacies of DCE- MRI, DWI and DTI were compared independently or combined. Results： EA value, lesion enhancement style and TIC pattern were identified as independent factor for differential diagnosis of IBC and DCIS. The combination diagnosis showed higher diagnostic efficacy than a single use of DCE-MRI （P=0.02）, and the area of the curve was improved from 0.84 （95% CI, 0.67-0.99） to 0.94 （95% CI, 0.85-1.00）. Conclusions： Quantitative DTI measurement as an adjunct to DCE-MRI could improve the diagnostic performance of differential diagnosis between DCIS and IBC compared to a single use of DCE-MRI.

Prediction of pathological nodal stage of locally advanced rectal cancer by collective features of multiple lymph nodes in magnetic resonance images before and after neoadjuvant chemoradiotherapy

Objective:To predict pathological nodal stage of locally advanced rectal cancer by a radiomic method that uses collective features of multiple lymph nodes(LNs)in magnetic resonance images before and after neoadjuvant chemoradiotherapy(NCRT).Methods:A total of 215 patients were included in this study and chronologically divided into the discovery cohort(n=143)and validation cohort(n=72).In total,2,931 pre-NCRT LNs and 1,520 post-NCRT LNs were delineated from all visible rectal LNs in magnetic resonance images.Geometric,first-order and texture features were extracted from each LN before and after NCRT.Collective features are defined as the maximum,minimum,mean,median value and standard deviation of each feature from all delineated LNs of each participant.LN-model is constructed from collective LN features by logistic regression model with L1 regularization to predict pathological nodal stage(ypN0 or ypN+).Tumor-model is constructed from tumor features for comparison by using DeLong test.Results:The LN-model selects 7 features from 412 LN features,and the tumor-model selects 7 features from 82 tumor features.The area under the receiver operating characteristic curve(AUC)of LN-model in the discovery cohort is 0.818[95%confidence interval(95%CI):0.745-0.878],significantly(Z=2.09,P=0.037)larger than 0.685(95%CI:0.602-0.760)of the tumor-model.The AUC of LN-model in validation cohort is 0.812(95%CI:0.703-0.895),significantly(Z=3.106,P=0.002)larger than 0.517(95%CI:0.396-0.636)of the tumor-model.Conclusions:The usage of collective features from all visible rectal LNs performs better than the usage of tumor features for the prediction of pathological nodal stage of locally advanced rectal cancer.

Better prognostic determination of cT3 rectal cancer through measurement of distance to mesorectal fascia:A multicenter study

Objective:To forward the magnetic resonance imaging(MRI)based distance between the deepest tumor invasion and mesorectal fascia(DMRF),and to explore its prognosis differentiation value in cT3 stage rectal cancer with comparison of cT3 substage.Methods:This was a retrospective,multicenter cohort study including cT3 rectal cancer patients undergoing neoadjuvant chemoradiotherapy followed by radical surgery from January 2013 to September 2014.DMRF and cT3 substage were evaluated from baseline MRI.The cutoff of DMRF was determined by disease progression.Multivariate cox regression was used to test the prognostic values of baseline variables.Results:A total of 804 patients were included,of which 226(28.1%)developed progression.A DMRF cutoff of7 mm was chosen.DMRF category,the clock position of the deepest position of tumor invasion(CDTI)and extramural venous invasion(EMVI)were independent predictors for disease progression,and hazard ratios(HRs)were 0.26[95%confidence interval(95%CI),0.13-0.56],1.88(95%CI,1.33-2.65)and 1.57(95%CI,1.13-2.18),respectively.cT3 substage was not a predictor for disease progression.Conclusions:The measurement of DMRF value on baseline MRI can better distinguish cT3 rectal cancer prognosis rather than cT3 substage,and was recommended in clinical evaluation.

Deep learning model improves radiologists'performance in detection and classification of breast lesions

Objective:Computer-aided diagnosis using deep learning algorithms has been initially applied in the field of mammography,but there is no large-scale clinical application.Methods:This study proposed to develop and verify an artificial intelligence model based on mammography.Firstly,mammograms retrospectively collected from six centers were randomized to a training dataset and a validation dataset for establishing the model.Secondly,the model was tested by comparing 12 radiologists’performance with and without it.Finally,prospectively enrolled women with mammograms from six centers were diagnosed by radiologists with the model.The detection and diagnostic capabilities were evaluated using the freeresponse receiver operating characteristic(FROC)curve and ROC curve.Results:The sensitivity of model for detecting lesions after matching was 0.908 for false positive rate of 0.25 in unilateral images.The area under ROC curve(AUC)to distinguish the benign lesions from malignant lesions was0.855[95%confidence interval(95%CI):0.830,0.880].The performance of 12 radiologists with the model was higher than that of radiologists alone(AUC:0.852 vs.0.805,P=0.005).The mean reading time of with the model was shorter than that of reading alone(80.18 s vs.62.28 s,P=0.032).In prospective application,the sensitivity of detection reached 0.887 at false positive rate of 0.25;the AUC of radiologists with the model was 0.983(95%CI:0.978,0.988),with sensitivity,specificity,positive predictive value(PPV),and negative predictive value(NPV)of94.36%,98.07%,87.76%,and 99.09%,respectively.Conclusions:The artificial intelligence model exhibits high accuracy for detecting and diagnosing breast lesions,improves diagnostic accuracy and saves time.

Novel magnetic field computation model in pattern classification

Field computation, an emerging computation technique, has inspired passion of intelligence science research. A novel field computation model based on the magnetic field theory is constructed. The proposed magnetic field computation （MFC） model consists of a field simulator, a non-derivative optimization algo- rithm and an auxiliary data processing unit. The mathematical model is deduced and proved that the MFC model is equivalent to a quadratic discriminant function. Furthermore, the finite element prototype is derived, and the simulator is developed, combining with particle swarm optimizer for the field configuration. Two benchmark classification experiments are studied in the numerical experiment, and one notable advantage is demonstrated that less training samples are required and a better generalization can be achieved.

Bna A02.YTG1,encoding a tetratricopeptide repeat protein,is required for early chloroplast biogenesis in Brassica napus

Chloroplasts are essential for plant growth and development,as they play a key role in photosynthesis.The chloroplast biogenesis process is complex and its regulatory mechanism remains elusive.We characterized a spontaneous Brassica napus(rapeseed)mutant,ytg,that showed a delayed greening phenotype in all green organs and retarded growth.We identified Bna A02.YTG1 encoding a chloroplastlocalized tetratricopeptide repeat protein widely expressed in rapeseed tissues.We speculated that the ytg phenotype was caused by the deletion of Bna A02.YTG1 based on sequence comparison of 4608(with normal green leaves,isolated from the elite Chinese rapeseed cultivar ZS11)and ytg combined with transcriptome data and CRISPR/Cas9 gene editing results.The homologous gene(Bna C02.YTG1)restored the phenotype of the mutant.Bna A02.YTG1 interacted with MORF2,MORF8,and OZ1.RNA editing of the ndh D-2,ndh F-290,pet L-5,and ndh G-50 plastid transcripts was affected in ytg.These findings suggested that Bna A02.YTG1 participates in RNA editing events.We predicted 29 RNA editing sites in the chloroplast of Brassica napus by comparison with the Arabidopsis chloroplast genome.We conclude that Bna A02.YTG1 affects the posttranscriptional regulation of plastid gene expression and suggest that a tetratricopeptide repeat protein is involved in the chloroplast RNA editing in rapeseed.

Correlation between imaging features on computed tomography and combined positive score of PD-L1 expression in patients with gastric cancer

Objective:To explore the correlation between computed tomography(CT)features and combined positive score(CPS)of programmed cell death ligand 1(PD-L1)expression in patients with gastric cancer(GC).Methods:This study reviewed an institutional database of patients who underwent GC operation without neoadjuvant chemotherapy between December 2019 and September 2020.The CPS results of PD-L1 expression of postoperative histological examination were recorded by pathology.Baseline CT features were measured,and their correlation with CPS 5 or 10 score groups of PD-L1 expression was analyzed.Results:Data for 153 patients with GC were collected.Among them,124 were advanced GC patients,and 29were early GC patients.None of the CT features significantly differed between CPS groups with a cutoff score of 5and a score of 10 in patients with early GC.In advanced GC,the presence of lymph nodes with short diameters>10mm was significantly different(P=0.024)between the CPS<5 and CPS≥5 groups.CT features such as tumor attenuation in the arterial phase,long and short diameter of the largest lymph node,the sum of long diameter of the two largest lymph nodes,the sum of short diameter of the two largest lymph nodes,and the presence of lymph nodes with short diameters>10 mm significantly differed between the CPS<10 and CPS≥10 groups in advanced GC.The sensitivity,specificity and area under receiver operating characteristic(ROC)curve of logistic regression model for predicting CPS≥10 was 71.7%,50.0%and 0.671,respectively.Microsatellite instability(MSI)status was significantly different in CPS groups with cutoff score of 5 and 10 in advanced GC patients.Conclusions:CT findings of advanced GC patients with CPS≥10 showed greater arterial phase enhancement and larger lymph nodes.CT has the potential to help screen patients suitable for immunotherapy.

X-ray absorption investigation of the site occupancies of the copper element in nominal Cu_(3)Zn(OH)_(6)FBr

With Zn substitution to the three-dimensional antiferromagnetically ordered barlowite Cu_(4)(OH)_(6)FBr,Cu_(3)Zn(OH)_(6)FBr shows no magnetic phase transition down to 50 mK,and the system is suggested to be a two-dimensional kagomé quantum spin liquid[Chin.Phys.Lett.34077502(2017)].A key issue to identify such phase diagram is the exact chemical formula of the substituted compound.With Cu L-edge x-ray absorption spectrum(XAS)combined with the MultiX XAS calculations,we evaluate the Cu concentration in a nominal Cu_(3)Zn(OH)_(6)FBr sample.Our results show that although the Cu concentration is 2.80,close to the expected value,there is 34%residual Cu occupation in intersite layers between kagomé layers.Thus the Zn substitution of the intersite layers is not complete,and likely it intrudes the kagomé layers.

Development and Prospect of Process Models and Simulation Methods for Atomic Layer Deposition

Thin film deposition is one of the most important processes in IC manufacturing. In this paper, several typical models and numerical simulation methods for thin film deposition and atomic layer deposition are introduced. Several modeling methods based on the characteristics of atomic layer deposition are introduced, it includes geometric method, cellular automata and multiscale simulation. The principle of each model and simulation method is explained, and their advantages and disadvantages are analyzed. Finally, the development direction of thin film deposition and atomic layer deposition modeling is prospected, and some modeling ideas are also provided.

Analysis of Current Research Status of Plasma Etch Process Model

This paper summarizes the status of the plasma etch process modeling research.It mainly introduces typical etching models employing the analytical method,geometric method,system identification method,basic principle simulation method,as well as empirical model.Each model’s basic principles,application scopes,advantages and disadvantages are discussed.Based on these,the development history of the etch process modeling is summarized,and the development opportunities of the etch model are prospected.This paper provides a brief view for establishment of the plasma etching process model.