Bivariate extreme value analysis of extreme temperature and mortality in Canada, 2000-2020.

Climate change increases the risk of illness through rising temperature, severe precipitation and worst air pollution. This paper investigates how monthly excess mortality rate is associated with the increasing frequency and severity of extreme temperature in Canada during 2000-2020. The extreme associations were compared among four age groups across five sub-blocks of Canada based on the datasets of monthly T90 and T10, the two most representative indices of severe weather monitoring measures developed by the actuarial associations in Canada and US. We utilize a combined seasonal Auto-regressive Integrated Moving Average (ARIMA) and bivariate Peaks-Over-Threshold (POT) method to investigate the extreme association via the extreme tail index χ and Pickands dependence function plots. It turns out that it is likely (more than 10%) to occur with excess mortality if there are unusual low temperature with extreme intensity (all χ > 0.1 except Northeast Atlantic (NEA), Northern Plains (NPL) and Northwest Pacific (NWP) for age group 0-44), while extreme frequent high temperature seems not to affect health significantly (all χ ≤ 0.001 except NWP). Particular attention should be paid to NWP and Central Arctic (CAR) since population health therein is highly associated with both extreme frequent high and low temperatures (both χ = 0.3182 for all age groups). The revealed extreme dependence is expected to help stakeholders avoid significant ramifications with targeted health protection strategies from unexpected consequences of extreme weather events. The novel extremal dependence methodology is promisingly applied in further studies of the interplay between extreme meteorological exposures, social-economic factors and health outcomes.

Association between nutritional status assessed by a digital self-administered tool (R+ dietitian) and clinicopathologic factors in cancer patients: A comprehensive analysis.

Objective: Malnutrition is prevalent among cancer patients, smartphone-based self-administered nutritional assessment tools offer a promising solution for effective nutritional screening. This study aims to retrospectively analyze the relationships between nutritional status evaluated by the digital tool (R+ Dietitian) and clinicopathologic factors of cancer patients. Methods: Cancer patients who met the inclusion criteria were divided into two subgroups based on age, Nutritional Risk Screening-2002, Patient-Generated Subjective Global Assessment Short Form, body mass index, and hospital stays for comparison. Correlation and regression analysis were used to comprehensively assess the relationship between nutritional status and clinicopathologic factors. Findings: A total of 535 hospitalized cancer patients (58.32 ± 11.24 years old) were recruited. Patients identified with nutritional risk assessed by R+ Dietitian were significantly older, had lower body weight, lower body mass index, greater weight loss, and longer hospital stays (all of above, P < 0.01). Multiple logistic regression analysis indicated that serum prealbumin concentration (odds ratio: 0.992, 95% confidence interval: 0.987-0.997, P = 0.001), weight loss (odds ratio: 7.309, 95% confidence interval: 4.026-13.270, P < 0.001), and body mass index < 18.5 (odds ratio: 5.882, 95% confidence interval: 2.695-12.821, P < 0.001) predicted nutritional risk indicated by Nutritional Risk Screening-2002 score ≥3. Hemoglobin concentration (odds ratio: 0.983, 95% confidence interval: 0.970-0.996, P = 0.011), weight (odds ratio: 1.111, 95% confidence interval: 1.056-1.169, P < 0.001), weight loss (odds ratio: 7.502, 95% confidence interval: 4.394-12.810, P < 0.001), body mass index (odds ratio: 0.661, 95% confidence interval: 0.564-0.775, P < 0.001), and energy intake (odds ratio: 0.996, 95% confidence interval: 0.995-0.997, P < 0.001) predicted nutritional risk indicated by Patient-Generated Subjective Global Assessment Short Form score ≥4. Multiple linear regression analysis revealed that Patient-Generated Subjective Global Assessment Short Form scores ≥3 (b = 2.032, P = 0.008) were significantly associated with longer hospital stays. Conclusions: The nutritional risks assessed by R+ Dietitian accurately reflected the characteristics of malnutrition in cancer patients and predicted hospital stay and cost, indicating the applicability of R+ Dietitian to improving the efficiency of nutritional management for cancer patients.

Spatial-temporal distribution characteristics of pulmonary tuberculosis in eastern China from 2011 to 2021.

China is still among the 30 high-burden tuberculosis (TB) countries in the world. Few studies have described the spatial epidemiological characteristics of pulmonary TB (PTB) in Jiangsu Province. The registered incidence data of PTB patients in 95 counties of Jiangsu Province from 2011 to 2021 were collected from the Tuberculosis Management Information System. Three-dimensional spatial trends, spatial autocorrelation, and spatial-temporal scan analysis were conducted to explore the spatial clustering pattern of PTB. From 2011 to 2021, a total of 347,495 newly diagnosed PTB cases were registered. The registered incidence rate of PTB decreased from 49.78/100,000 in 2011 to 26.49/100,000 in 2021, exhibiting a steady downward trend (χ2 = 414.22, P < 0.001). The average annual registered incidence rate of PTB was higher in the central and northern regions. Moran's I indices of the registered incidence of PTB were all >0 (P< 0.05) except in 2016, indicating a positive spatial correlation overall. Local autocorrelation analysis showed that 'high-high' clusters were mainly distributed in northern Jiangsu, and 'low-low' clusters were mainly concentrated in southern Jiangsu. The results of this study assist in identifying settings and locations of high TB risk and inform policy-making for PTB control and prevention.

m6ACali: machine learning-powered calibration for accurate m6A detection in MeRIP-Seq.

We present m6ACali, a novel machine-learning framework aimed at enhancing the accuracy of N6-methyladenosine (m6A) epitranscriptome profiling by reducing the impact of non-specific antibody enrichment in MeRIP-Seq. The calibration model serves as a genomic feature-based classifier that refines the identification of m6A sites, distinguishing those genuinely present from those that can be detected in in-vitro transcribed (IVT) control experiments. We find that m6ACali effectively identifies non-specific binding peaks reported by exomePeak2 and MACS2 in novel MeRIP-Seq datasets without the need for paired IVT controls. The model interpretation revealed that off-target antibody binding sites commonly occur at short exons and short mRNAs, originating from high read coverage regions that share the motif sequence with true m6A sites. We also reveal that the ML strategy can efficiently adjust differentially methylated peaks and other antibody-dependent, base-resolution m6A detection techniques. As a result, m6ACali offers a promising method for the universal enhancement of m6A profiles generated by MeRIP-Seq experiments, elevating the benchmark for omics-level m6A data integration.

Characteristics of exopolysaccharides from Paecilomyces hepiali and their simulated digestion and fermentation in vitro by human intestinal microbiota.

The metabolic process of polysaccharides in gastrointestinal digestions and the effects of the resulting carbohydrates on the composition of gut microbes are important to explore their prebiotic properties. Therefore, the purpose of this study was to investigate the simulated digestion and fecal fermentation in vitro of three fractions (PHEPSs-1, PHEPSs-2 and PHEPSs-3) purified from the crude exopolysaccharides of Paecilomyces hepiali HN1 (PHEPSs) and to explore the potential prebiotic mechanisms. The three purified fractions were characterized by HPLC, UV, FT-IR, SEM and AFM, and they were all of galactoglucomannan family with molecular weight of 178, 232 and 119 kDa, respectively. They could resist the simulated gastrointestinal digestions, but they were metabolized in fecal fermentation in vitro. Furthermore, the mannose in PHEPSs showed a higher utilization rate than that of glucose or galactose. The proliferation effects of PHEPSs on Bifidobacterium and Lactobacillus were weaker significantly than those of fructooligosaccharides before 12 h of fecal fermentation, but stronger after 24 h of fecal fermentation. Meanwhile, higher levels of short-chain fatty acids were found in PHEPSs groups when the fecal fermentation extended to 36 h. Therefore, PHEPSs are expected to have a potent gut healthy activity and can be explored as functional food ingredients.

A Generalized Bootstrap Procedure of the Standard Error and Confidence Interval Estimation for Inverse Probability of Treatment Weighting.

The inverse probability of treatment weighting (IPTW) approach is commonly used in propensity score analysis to infer causal effects in regression models. Due to oversized IPTW weights and errors associated with propensity score estimation, the IPTW approach can underestimate the standard error of causal effect. To remediate this, bootstrap standard errors have been recommended to replace the IPTW standard error, but the ordinary bootstrap (OB) procedure might still result in underestimation of the standard error because of its inefficient resampling scheme and untreated oversized weights. In this paper, we develop a generalized bootstrap (GB) procedure for estimating the standard error and confidence intervals of the IPTW approach. Compared with the OB procedure and other three procedures in comparison, the GB procedure has the highest precision and yields conservative standard error estimates. As a result, the GB procedure produces short confidence intervals with highest coverage rates. We demonstrate the effectiveness of the GB procedure via two simulation studies and a dataset from the National Educational Longitudinal Study-1988 (NELS-88).

Joint extremes in precipitation and infectious disease in the USA: A bivariate POT study.

Mounting heavy precipitation events (HPEs) caused by the climate change have drawn wide attention. Increased incidences of infectious diseases are known as the common following health impact, while little has been studied about the extremal relationship in between. Therefore, this study aims to investigate the joint extremes of precipitation and infectious disease mortality rate in the USA, using publicly accessible data from the National Centers for Environmental Information and the Centers for Disease Control and Prevention. The study reveals the positive association between heavy precipitations and infectious diseases with slight national and regional differences using multivariate Peaks-Over-Threshold modelling. The strength of extremal dependence is measured by the extreme parameter α from a logistic dependence model in multivariate extreme value theory. The Midwestern USA shows an excessive impact of HPEs on infectious disease mortality (α=0.7524), while the other regions show similar extremal dependence strength with the national one (α values all approximate 0.77). The study also discovered spatial disparities in the extremal dependences for five sub-categories of infectious diseases in each census region, among which mycoses show the strongest extremal dependence with precipitation in almost all regions. These spatial differences of extremal dependence may be attributed to geographic, social-economic factors and the self-inherited characteristics of certain diseases. The findings are expected to assist in developing strategies counteracting extreme risks resulting from weather events and health issues as well. The cutting-edge multivariate Peaks-Over-Threshold (POT) approach employed herein also shows promise for a wide range of extreme risk assessment topics.

Mixed-valence gold-porphyrin two-dimensional coordination networks for repurposing of chrysotherapy.

Catalytic gold nanomaterials typically exhibit antibacterial properties, albeit significantly weaker than ionic gold in chrysotherapy. The inherent stability of gold nanoparticles prevents the release of gold ions, limiting their ability to achieve efficient antibacterial therapy. To address this limitation, we propose a novel sustained ionic gold release strategy through the construction of a mixed-valence gold-porphyrin coordination network (Au-Por). By adjusting the ratio of Au to porphyrin molecule, an ultrathin two-dimensional Au-Por nanosheet was successfully synthesized, which contains 85.9 % of Au (III). In addition, the remaining gold existed in the form of uniformly distributed ultrasmall nanoclusters on the Au-Por nanosheet. Notably, the Au-Por nanosheet exhibited a sustained release of gold ions. Thus, a multimodal antibacterial therapy was achieved by integrating the direct bactericidal action of ionic gold and lethal reactive oxygen species (ROS) generated through the peroxidase (POD)-like activity of gold nanoclusters and photodynamic therapy (PDT) using porphyrins. The innovative Au-Por exerted broad-spectrum bactericidal activity against both Gram-negative Escherichia coli and Gram-positive Staphylococcus aureus bacteria mediated by bacterial membrane disruption and DNA damage. Moreover, in vivo studies demonstrated the synergistic effect of Au-Por on combating skin wound infections and facilitating wound healing. Comprehensive safety evaluations proved that Au-Por exhibited no hematotoxicity or hepatorenal toxicity, and it also displayed rapid renal clearance after treatment, indicating favorable biocompatibility. The repurposing of chrysotherapy has revolutionized the antibacterial strategy of nanoscale gold, resulting in a dramatic boost in antibacterial activity and valuable insights for designing highly efficient nanoscale antibacterial agents.

Nonlinear spectral compression in high-power narrow-linewidth polarization maintaining fiber amplifiers for SBS suppression.

In this paper, we propose a method for narrowing the spectrum in high-power narrow-linewidth polarization-maintaining (PM) fiber amplifiers and investigate its potential for suppressing the stimulated Brillouin scattering (SBS). In this method, in addition to common phase modulation to suppress SBS, precisely designed amplitude modulation is induced to generate self-phase modulation in a high-power PM fiber amplifier. In this co-modulation way, the spectrum can be gradually compressed along the fiber. Compared to phase modulation alone or fiber-Bragg-gratings (FBGs) based narrow-linewidth fiber oscillator schemes, in which the spectrum remains the same or broadens, this scheme can achieve a higher SBS threshold for the same output spectral linewidth. Experiments on a ∼ 3 kW peak power quasi-continuous wave (QCW) fiber amplifier show that the co-modulation scheme can compress the spectrum from 0.25 nm to 0.084 nm as output peak power increases from 13 W to 3.2 kW and enhances the SBS threshold by ∼1.7 times compared to traditional FBGs-based fiber oscillator schemes, and by ∼1.4 times compared to common phase modulation schemes. This co-modulation scheme has the potential for mitigating SBS in high-power fiber amplifiers.

Investigating the Marginal and Herd Effects of COVID-19 Vaccination for Reducing Case Fatality Rate: Evidence from the United States between March 2021 to January 2022.

Vaccination campaigns have been rolled out in most countries to increase vaccination coverage and protect against case mortality during the ongoing pandemic. To evaluate the effectiveness of COVID-19 vaccination, it is vital to disentangle the herd effect from the marginal effect and parameterize them separately in a model. To demonstrate this, we study the relationship between the COVID-19 vaccination coverage and case fatality rate (CFR) based on U.S. vaccination coverage at county level, with daily records from 11 March 2021 to 26 January 2022 for 3109 U.S. counties. Using segmented regression, we discovered three breakpoints of the vaccination coverage, at which herd effects could potentially exist. Controlling for county heterogeneity, we found the size of the marginal effect was not constant but actually increased as the vaccination coverage increased, and only the herd effect at the first breakpoint to be statistically significant, which implied an indirect benefit of vaccination may exist at the early stage of a vaccination campaign. Our results demonstrated that public-health researchers should carefully differentiate and quantify the herd and marginal effects when analyzing vaccination data, to better inform vaccination-campaign strategies as well as evaluate vaccination effectiveness.

Human amniotic mesenchymal stem cell-conditioned medium inhibited LPS-induced cell injury and inflammation by modulating CD14/TLR4-mediated signaling pathway in monocytes.

Human amniotic mesenchymal stem cells (hAMSCs) have attracted considerable attention as a promising regenerative therapy. Many studies reported that the conditioned medium of hAMSCs (AM-CM) exerted anti-inflammatory and immunomodulatory functions, while its underlying mechanism is poorly understood. In this study, we first confirmed that AM-CM (25%, 50%, 100%) was optimal for anti-inflammation at 24 h. Lipopolysaccharide (LPS)-induced alteration of cell morphology, the decrease of cell proliferation, and the upregulation of cell apoptosis were significantly reversed in AM-CM-treated THP-1 cells. 25% and 50% AM-CM significantly decreased LPS-induced intracellular reactive oxygen species (ROS) production and proinflammatory cytokines secretion. Mechanistically, we found that AM-CM treatment suppressed LPS-induced activation of MAPK and NF-κB pathways by inhibiting CD14/TLR4 in THP-1 cells. Meanwhile, activation of NLRP3 inflammasome was also dose-dependently attenuated by AM-CM treatment. Thus, AM-CM may exert positive influences on the inflammation microenvironment and provide a novel strategy for improving tissue regeneration.

[Experimental study of improved sclerotherapy injection in rat model of vertebral arteriocervical spondylopathy].

OBJECTIVE: To improve the rat model of cervical spondylosis of vertebral artery type (CSA) induced by injecting sclerosing agent. To evaluate the efficacy of injecting sclerosing agent to induce CSA. METHODS: Forty Health SPF SD rats(20 males and 20 females), were randomly divided into two groups:the model group (20) and the blank group (20). All the animals were followed up for 4 weeks for the observation of general situation, transcranial Doppler(TCD) detection of blood flow velocity, pulsatility index and resistive index of the vertebral artery, measurement of mental distress by open-field test. RESULTS: One to two days after establish the animal model, rats in the model group appeared apathetic with decreased autonomic activities, trembling, squinting, increased eye excrement, etc., and no rats died during the experiment. The mean blood flow velocity of the model group was lower than that of the blank group (P<0.05), and the pulsatilit index and resistive index of the model group were higher than that of the blank group (P<0.05). The mental distress of the model group was significantly higher than that of the blank group. CONCLUSION: The modified injection of sclerosing agent is a practical method to establish the rat model of CSA, with high success rate, high stability, low mortality and simple operation.

Overcoming the impacts of two-step batch effect correction on gene expression estimation and inference.

Nonignorable technical variation is commonly observed across data from multiple experimental runs, platforms, or studies. These so-called batch effects can lead to difficulty in merging data from multiple sources, as they can severely bias the outcome of the analysis. Many groups have developed approaches for removing batch effects from data, usually by accommodating batch variables into the analysis (one-step correction) or by preprocessing the data prior to the formal or final analysis (two-step correction). One-step correction is often desirable due it its simplicity, but its flexibility is limited and it can be difficult to include batch variables uniformly when an analysis has multiple stages. Two-step correction allows for richer models of batch mean and variance. However, prior investigation has indicated that two-step correction can lead to incorrect statistical inference in downstream analysis. Generally speaking, two-step approaches introduce a correlation structure in the corrected data, which, if ignored, may lead to either exaggerated or diminished significance in downstream applications such as differential expression analysis. Here, we provide more intuitive and more formal evaluations of the impacts of two-step batch correction compared to existing literature. We demonstrate that the undesired impacts of two-step correction (exaggerated or diminished significance) depend on both the nature of the study design and the batch effects. We also provide strategies for overcoming these negative impacts in downstream analyses using the estimated correlation matrix of the corrected data. We compare the results of our proposed workflow with the results from other published one-step and two-step methods and show that our methods lead to more consistent false discovery controls and power of detection across a variety of batch effect scenarios. Software for our method is available through GitHub (https://github.com/jtleek/sva-devel) and will be available in future versions of the $\texttt{sva}$ R package in the Bioconductor project (https://bioconductor.org/packages/release/bioc/html/sva.html).

Evaluation of toxicological effects of bisphenol S with an in vitro human bone marrow mesenchymal stem cell: Implications for bone health.

As the use of bisphenol A (BPA) has been restricted in consumer products, bisphenol S (BPS) is one major alternative to BPA for various materials, leading to growing concerns about its health risks in human beings. However, little is known about the toxic effects of BPS on bone health. We employed human bone marrow mesenchymal stem cells (hBMSCs) for the in vitro assessment of BPS on cell proliferation, differentiation, and self-renewal. Our study revealed that BPS at concentrations of 10-10-10-7 M increased cell viability but induced the morphological changes of hBMSCs. Moreover, BPS decreased ROS generation and increased Nrf2 expression. Furthermore, BPS not only activated ERα/ß expression but also increased ß-catenin expression and induced the replicative senescence of hBMSCs. Furthermore, we found that the upregulation of ß-catenin induced by BPS was mediated, in part, by ER signaling. Overall, our results suggested BPS exposure caused the homeostatic imbalance of hBMSCs.

Factors Associated with the Uptake of Genetic Testing for Cancer Risks: A Pathway Analysis Using the Health Information National Trends Survey Data.

Our study aimed to identify pathways from the source of information to the uptake of cancer genetic testing, with consideration of intermediate variables including perceptional, attitudinal and psychosocial factors. We used the Health Information National Trends Survey (2020 database) and constructed a structural equation model for pathway analysis (using SPSS version 24). Variables for socio-demographic, lifestyle and health information were also collected and used for confounding adjustment. A total of 2941 participants were analyzed (68.5%, non-Hispanic white; 59.7%, females; 58 years, median age; and 142 (4.8%) had undertaken genetic testing for cancer risk previously). Our pathway analysis found that only information from particular sources (i.e., healthcare providers and genetic counsellors) had positive and significant effects on people's perceptions of cancer regarding its prevention, detection and treatment (standardized ß range, 0.15−0.31, all p-values < 0.01). Following the paths, these perceptional variables (cancer prevention, detection and treatment) showed considerable positive impacts on the uptake of genetic testing (standardized ß (95% CIs): 0.25 (0.20, 0.30), 0.28 (0.23, 0.33) and 0.12 (0.06, 0.17), respectively). Pathways involving attitudinal and psychosocial factors showed much smaller or insignificant effects on the uptake of genetic testing. Our study brings several novel perspectives to the behavior model and may underpin certain issues regarding cancer risk genetic testing.

Amplified effect of social vulnerability on health inequality regarding COVID-19 mortality in the USA: the mediating role of vaccination allocation.

BACKGROUND: Vaccination reduces the overall burden of COVID-19, while its allocation procedure may introduce additional health inequality, since populations characterized with certain social vulnerabilities have received less vaccination and been affected more by COVID-19. We used structural equation modeling to quantitatively evaluate the extent to which vaccination disparity would amplify health inequality, where it functioned as a mediator in the effect pathways from social vulnerabilities to COVID-19 mortality. METHODS: We used USA nationwide county (n = 3112, 99% of the total) level data during 2021 in an ecological study design. Theme-specific rankings of social vulnerability index published by CDC (latest data of 2018, including socioeconomic status, household composition & disability, minority status & language, and housing type & transportation) were the exposure variables. Vaccination coverage rate (VCR) during 2021 published by CDC was the mediator variable, while COVID-19 case fatality rate (CFR) during 2021 published by John Hopkinson University, the outcome variable. RESULTS: Greater vulnerabilities in socioeconomic status, household composition & disability, and minority status & language were inversely associated with VCR, together explaining 11.3% of the variance of VCR. Greater vulnerabilities in socioeconomic status and household composition & disability were positively associated with CFR, while VCR was inversely associated with CFR, together explaining 10.4% of the variance of CFR. Our mediation analysis, based on the mid-year data (30th June 2021), found that 37.6% (mediation/total effect, 0.0014/0.0037), 10% (0.0003/0.0030) and 100% (0.0005/0.0005) of the effects in the pathways involving socioeconomic status, household composition & disability and minority status & language, respectively, were mediated by VCR. As a whole, the mediation effect significantly counted for 30.6% of COVID-19 CFR disparity. Such a mediation effect was seen throughout 2021, with proportions ranging from 12 to 32%. CONCLUSIONS: Allocation of COVID-19 vaccination in the USA during 2021 led to additional inequality with respect to COVID-19 mortality. Viable public health interventions should be taken to guarantee an equitable deployment of healthcare recourses across different population groups.

Edaravone Ameliorates Cerebral Ischemia-Reperfusion Injury by Downregulating Ferroptosis via the Nrf2/FPN Pathway in Rats.

Edaravone, an antioxidant protective agent, has anti-cerebral ischemic reperfusion injury (CIRI) effects, but its anti-CIRI mechanism is unclear. The aim of this study is to investigate the anti-CIRI mechanism of edaravone based on the nuclear factor-E2-related factor 2 (Nrf2)/ferroportin (FPN) pathway that regulates ferroptosis-mediated cerebral ischemia-reperfusion injury. We evaluated the brain injury by constructing a middle cerebral artery occlusion and reperfusion (MCAO/R) model in rats. The results showed that cerebral infarct volume and neurological impairment scores were increased in cerebral ischemia-reperfusion rats, with impaired sensorimotor ability; furthermore, brain tissue glutathione (GSH) content was decreased, Fe2+, malondialdehyde (MDA) and lipide peroxide (LPO) content were increased, and the expression level of glutathione peroxidase 4 (GPX4), a key protein of ferroptosis, was also decreased. Meanwhile, the Nrf2 expression level was increased and the FPN expression level was decreased after cerebral ischemia-reperfusion, while the levels of interleukin (IL)-6, IL-1ß, tumor necrosis factor (TNF)-α, and myeloperoxidase (MPO) were increased. However, edaravone exhibited a protective effect on cerebral infarct and neurological and sensorimotor function in relevant tests. In addition, we also found that edaravone decreased the contents of Fe2+, MDA, and LPO in the brain tissue of MCAO/R rats and increased GSH content to inhibit ferroptosis. Furthermore, Western blot showed that after treatment with edaravone, the expression of Nrf2, GPX4, and FPN was up-regulated, the nuclear location of Nrf2 was increased, and the levels of inflammation-related indicators IL-6, IL-1ß, TNF-α, and MPO were lower than in the MCAO/R group. Our results demonstrated that edaravone inhibits ferroptosis to attenuate CIRI, probably through the activation of the Nrf2/FPN pathway.

Bayesian back-calculation and nowcasting for line list data during the COVID-19 pandemic.

Surveillance is critical to mounting an appropriate and effective response to pandemics. However, aggregated case report data suffers from reporting delays and can lead to misleading inferences. Different from aggregated case report data, line list data is a table contains individual features such as dates of symptom onset and reporting for each reported case and a good source for modeling delays. Current methods for modeling reporting delays are not particularly appropriate for line list data, which typically has missing symptom onset dates that are non-ignorable for modeling reporting delays. In this paper, we develop a Bayesian approach that dynamically integrates imputation and estimation for line list data. Specifically, this Bayesian approach can accurately estimate the epidemic curve and instantaneous reproduction numbers, even with most symptom onset dates missing. The Bayesian approach is also robust to deviations from model assumptions, such as changes in the reporting delay distribution or incorrect specification of the maximum reporting delay. We apply the Bayesian approach to COVID-19 line list data in Massachusetts and find the reproduction number estimates correspond more closely to the control measures than the estimates based on the reported curve.

Failure Process of Modeled Recycled Aggregate Concrete under Uniaxial Compression.

This paper investigates the failure processes of recycled aggregate concrete by a model test and numerical simulations. A micromechanical numerical modeling approach to simulate the progressive cracking behavior of the modeled recycled aggregate concrete, considering its actual meso-structures, is established based on the discrete element method (DEM). The determination procedure of contact microparameters is analyzed, and a series of microscopic contact parameters for different components of modeled recycled aggregate concrete (MRAC) is calibrated using nanoindentation test results. The complete stress-strain curves, cracking process, and failure pattern of the numerical model are verified by the experimental results, proving their accuracy and validation. The initiation, growth, interaction, coalescence of microcracks, and subsequent macroscopic failure of the MRAC specimen are captured through DEM numerical simulations and compared with digital image correlation (DIC) results. The typical cracking modes controlled by meso-structures of MRAC are concluded according to numerical observations. A parameter study indicates the dominant influence of the macroscopic mechanical behaviors from the shear strength of the interfacial transition zones (ITZs).