Bending response of carbon fiber composite sandwich beams with three dimensional honeycomb cores

Bending properties and failure modes of carbon fiber composite egg and pyramidal honeycomb beams were studied and presented in this paper. Three point bending responses of both sandwich beams were tested. Face wrinkling, face crushing, core member crushing and debonding were considered, and theoretical relationships for predicting the failure load associated with each mode were presented under three point bending load. Failure mechanism maps were constructed to predict the failure of composite sandwich beams with pyramidal and egg honeycomb cores subjected to bending. Face wrinkling and core debonding have been investigated under three point bending and the maximum displacement was studied using analytical and experimental methods. The finite element method was employed to determine the ratio (maximum displacement/applied load) of sandwich beam with two different honeycomb cores. Comparisons between two kinds of honeycomb beams were also conducted.Fil: Xiong, Jian. Harbin Institute of Technology. Center for Composite Materials and Structures; ChinaFil: Ma, Li. Harbin Institute of Technology. Center for Composite Materials and Structures; ChinaFil: Stocchi, Ariel Leonardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Mar del Plata. Instituto de Investigación En Ciencia y Tecnología de Materiales (i); ArgentinaFil: Yang, Jinshui. Harbin Institute of Technology. Center for Composite Materials and Structures; ChinaFil: Wu, Linzhi. Harbin Institute of Technology. Center for Composite Materials and Structures; ChinaFil: Pan, Shidong. Harbin Institute of Technology; Chin

Study on the Spatial-Temporal Evolution of Land Use Ecosystem Service Value and Its Zoning Management and Control in the Typical Alpine Valley Area of Southeast Tibet—Empirical Analysis Based on Panel Data of 97 Villages in Chayu County

Under the background of ecological civilization construction and the overall planning of land and space, it is particularly important to explore the land use ecosystem service value and its zoning control. This paper, taking Chayu County, a typical alpine valley area of southeast Tibet as an example and based on the remote sensing interpretation data of three periods in 2000, 2010 and 2020, employs the three-level spatial scale from the village level, the township level to the county level to converge step by step, and uses a series of model algorithms to analyze and calculate the regional ecosystem service value and their dynamic changes, as well as spatial agglomeration and regional type division. The research shows that the land use types mainly consist of forest land, grassland and unused land, whose overall change range is small during the study period. The conversion of land use types is mainly between forest land, grassland and unused land and the land use index generally presents a spatial pattern of “high in the southwest and low in the northeast”, showing a decreasing trend to some degree. ESVI generally presents a differentiation pattern of “high in the west and low in the east”, with obvious spatial differentiation characteristics of kernel density, significant clustering and distribution characteristics and stable variation range, displaying an overall spatial pattern with characteristics of “dense in the west and sparse in the east, high in the north and low in the south”. Based on the administrative village scale, the study area is divided into three different types of land use ecological function areas: habitat maintenance function area, biological protection function area and production support function area. Differentiated approaches to appropriate development and construction and the corresponding optimization paths of ecological protection will be put forward

Supplementary Information 1 from Urinary Tumor DNA MRD Analysis to Identify Responders to Neoadjuvant Immunotherapy in Muscle-invasive Bladder Cancer

Supplementary methods and clinical trial protocol</p

Figure S1-S6 from Urinary Tumor DNA MRD Analysis to Identify Responders to Neoadjuvant Immunotherapy in Muscle-invasive Bladder Cancer

Figure S1. (A) Representative MRI images for radiographic evaluation of neoadjuvant toripalimab. (B) Representative hematoxylin and eosin staining for histopathological evaluation of neoadjuvant toripalimab. CR = complete response; PR = partial response; SD = stable disease; PD = progressive disease. A modifier “p” refers to pathologic staging after cystectomy. Figure S2. (A) Stacked bar plot shows the percentage of patients with negative or positive PD-L1, low or high TMB, and negative or positive TLS. (B) Oncoprint chart for the mutational landscape of tDNA in patients with ypCR or non-ypCR. Samples were analyzed by whole exome sequencing, and the mutation frequencies of each gene are shown on the right. (C) The line plot illustrates tumor size changes measured by MRI imaging before and after neoadjuvant toripalimab. PD-L1 = programmed death ligand 1; TMB = tumor mutation burden; TLS = tertiary lymphoid structure; ypCR = pathological complete response; pre-tx = pre-treatment; post-tx = post-treatment; MRI = magnetic resonance imaging. Figure S3. (A) Oncoprint chart for the mutational landscape of tDNA and utDNA. Samples were analyzed by whole exome sequencing, and the mutation frequencies of each gene are shown on the right. (B) TMB correlation between tDNA and utDNA as assessed by whole exome sequencing. Red shading indicates 95% confidence interval. Spearman correlation coefficient (r) and P value are shown. tDNA = tumor DNA; utDNA = urinary tumor DNA; TMB = tumor mutation burden. Figure S4. (A) Box plot compares TFsm in utDNA versus ctDNA samples collected at baseline. (B) Venn plots show the number of shared and unique variants in matched utDNA and ctDNA samples. (C) Box plot compares TFcn in utDNA versus ctDNA samples at baseline. (D) Copy number gain (red) and loss (blue) of utDNA and ctDNA, as identified by GISTIC2.0. TFsm = tumor fraction estimate based on somatic mutations; utDNA = urinary tumor DNA; ctDNA = circulating tumor DNA; TFcn = tumor fraction estimate based on copy numbers. Figure S5. (A) The line plot illustrates TFsm changes in utDNA samples upon neoadjuvant toripalimab. (B) The line plot illustrates TFcn changes in utDNA samples before and after neoadjuvant toripalimab. (C) Stacked bar plot showed the percentage of patients with low or high pre-treatment TFsm, TFcn, and MRI measurements according to the optimal cutoff points defined by ROC analysis. (D) Stacked bar plot showed the percentage of patients with low or high post-treatment TFsm, TFcn, and MRI measurements according to the optimal cutoff points defined by ROC analysis. (E) Waterfall plot for the best change of target lesions in 20 patients. The post-treatment urinary MRD status of each patient are arranged along the x-axis. Bar color indicates the pathologic outcome of neoadjuvant toripalimab. TFsm = tumor fraction estimate based on somatic mutations; TFcn = tumor fraction estimate based on copy numbers; MRI = magnetic resonance imaging; utDNA = urinary tumor DNA; utDNA-pre = pre-treatment utDNA; utDNA-post =post-treatment utDNA; ypCR = pathological complete response; pre-tx = pre-treatment; post-tx = post-treatment; MRD = minimal residual disease. Figure S6. (A) Spider plot indicating dynamic changes of TFsm, TFcn, and MRI measurements for each patient during neoadjuvant toripalimab. (B) Box plot illustrates utDNA reduction (defined by TFsm + TFcn < 10%) in utDNA-pre versus utDNA-post samples. (C) IGV plot showing the FGFR3 S249C mutation in patient RZ12 detected by MRD panel sequencing or whole exome sequencing. (D) VAF changes of the FGFR3 S249C mutation in patient RZ12 with progressive disease. TFsm = tumor fraction estimate based on somatic mutations; TFcn = tumor fraction estimate based on copy numbers; MRI = magnetic resonance imaging; C1 = cycle 1; C2 = cycle 2; C3 = cycle 3; C4 = cycle 4; RC = radical cystectomy; ypCR = pathological complete response; MRD = minimal residual disease; WES = whole exome sequencing; tDNA = tumor DNA; utDNA = urinary tumor DNA; utDNA-pre = pretreatment utDNA; utDNA-post = post-treatment utDNA; C2D1 = cycle 2 day 1; VAF = variant allele frequency; PD = progressive disease.</p

Table S1-S8 from Urinary Tumor DNA MRD Analysis to Identify Responders to Neoadjuvant Immunotherapy in Muscle-invasive Bladder Cancer

Table S1. Clinicopathological characteristics of 20 patients in our study. Table S2. Representativeness of study participants. Table S3. Adverse events associated with toripalimab. Table S4. SNVs and InDels of therapy-naïve neoplastic tissues detected by whole exome sequencing. Table S5. SNVs and InDels of basal urine samples detected by whole exome sequencing. Table S6. SNVs and InDels detected by personalized MRD panel sequencing. Table S7. SNVs and InDels detected by the fixed actionable/hotspot panel sequencing. Table S8. Mutational measurements of each urine/plasma sample in our study.</p