Search

Treatment of osteochondral (OC) defects is still an immense challenge in clinic due to lack of satisfactory strategy to simultaneously regenerate both cartilage and subchondral bone. Herein, we propose an effective bottom-up strategy by developing a type of multifunctional chitosan-based nanocomposite microgels as the building blocks to repair OC defects. The microgels are biocompatible, and biodegradable, and have a hierarchical nanofibrous structure, mimicking the structural feature of extracellular matrix (ECM) to facilitate cell attachment and proliferation. Additionally, β-tricalcium phosphate (β-TCP) nanoparticles are incorporated in the microgels not only to promote the osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs), but also to facilitate the loading of transforming growth factor beta 1 (TGF-β1). For reconstructing OC defects, pure microgels are implanted at the bottom layer of the OC defects in rat knee joints to promote osteogenesis, while the microgels loaded with TGF-β1 are implanted at the top layer of the OC defects to promote cartilage regeneration. This modular microgel system results in simultaneous regeneration of cartilage and subchondral bone in OC defects, which is expected as a promising way for repairing other complex tissue defects in the field of tissue engineering.

Abstract Background The associations between short- and long-term exposure to ambient fine particulate matter with an aerodynamic diameter ≤ 2.5 µm (PM2.5) and allergic symptoms in middle-aged and elderly populations remain unclear, particularly in China, where most cities have severe air pollution. Methods Participants (n = 10,142; age = 40–75 years) were recruited from ten regions in China from 2018 to 2021 for the Predictive Value of Inflammatory Biomarkers and Forced Expiratory Volume in 1 s (FEV1) for Chronic Obstructive Pulmonary Disease (PIFCOPD) study. Short-term (lag0 and lag0–7 day) and long-term (1-, 3- and 5-year) PM2.5 concentrations at residences were extracted from the air pollutant database known as Tracking Air Pollution (TAP) in China. Multivariate logistic regression models were used to estimate associations for short- and long-term PM2.5 exposure concentrations and long-term exposure models were additionally adjusted for short-term deviations. Results A 10 µg/m3 increase in PM2.5 on the day the allergic symptoms questionnaire was administered (lag0 day) was associated with higher odds of allergic nasal (1.09, 95% CI 1.05, 1.12) and eye symptoms (1.08, 95% CI 1.05, 1.11), worsening dyspnea caused by allergens (1.06, 95% CI 1.02, 1.10), and ≥ 2 allergic symptoms (1.07, 95% CI 1.03, 1.11), which was similar in the lag0–7 day concentrations. A 10 µg/m3 increase in the 1-year average PM2.5 concentration was associated with an increase of 23% for allergic nasal symptoms, 22% for eye symptoms, 20% for worsening dyspnea caused by allergens, and 21% for ≥ 2 allergic symptoms, similar to the 3- and 5-year average PM2.5 concentrations. These associations between long-term PM2.5 concentration and allergic symptoms were generally unchanged after adjustment for short-term deviations. Conclusions Short- and long-term exposure to ambient PM2.5 was associated with an increased risk of allergic nasal and eye symptoms, worsening dyspnea caused by allergens, and ≥ 2 allergic symptoms. Trial registration Clinical trial ID: NCT03532893 (29 Mar 2018).

In order for user-side resources to participate in demand response (DR) more accurately, schedulable potential assessment of user-side resources is required. An improved G1 method using Spearman rank correlation (SRC) has been proposed to evaluate the schedulable potential for user-side resources. First, the DR potential evaluation indicator is established on the basis of the characteristics of user-side resources. Second, the resource potential score is calculated by using the improved G1 method using SRC, and the DR potential is obtained. Finally, the resource schedulable capacity of a certain region is obtained. The results show that the method realizes the potential evaluation of user-side resources in a region to participate in DR and provides data support for the power supply company to reasonably schedule user-side resources. Moreover, when compared with existing methods, the proposed method greatly improves the availability of the power company–scheduled regional resources to participate in DR.

Abstract An arc fault is the most common cause of charging pile fire. The series arc fault current is usually lower than the short‐circuit fault current and is challenging to detect, resulting in the inaction of the circuit breaker. Therefore, a method for detecting series arc faults of charging piles based on generalized Stockwell transform (GST) is proposed in this paper. First, an real time digital simulation system (RTDS)‐based charging pile arc experimental platform is constructed, and the point contact and the carbonization path arc fault current are measured. Then, the fault information is extracted using GST, and the 250‐Hz component is selected as the arc fault identification feature. On this basis, an improved sampling point selection method is proposed. Finally, multiple feature quantities are constructed as feature vectors, and the trained particle swarm optimization _support vector machine (PSO_SVM) is used for arc fault detection. The experimental results show that the accuracy rate reaches 98.75%; thus, the scheme proposed by this paper could detect the series arc fault current accurately and avoid the incorrect action of the circuit breaker.

Abstract Objectives The global coronavirus disease 2019 (COVID‐19) pandemic has not been well controlled, and vaccination could be an effective way to prevent this pandemic. By accommodating attribute nonattendance (ANA) in a discrete choice experiment (DCE), this paper aimed to examine Chinese public preferences and willingness to pay (WTP) for COVID‐19 vaccine attributes, especially the influence of ANA on the estimated results. Methods A DCE was designed with four attributes: effectiveness, protection period, adverse reactions and price. A random parameter logit model with an error component (RPL‐EC) was used to analyse the heterogeneity of respondents' preferences for COVID‐19 vaccine attributes. Two equality constraint latent class (ECLC) models were used to consider the influence of ANA on the estimated results in which the ECLC‐homogeneity model considered only ANA and the ECLC‐heterogeneity model considered both ANA and preference heterogeneity. Results Data from 1,576 samples were included in the analyses. Effectiveness had the highest relative importance, followed by adverse reactions and protection period, which were determined by the attributes and levels presented in this study. The ECLC‐heterogeneity model improved the goodness of fit of the model and obtained a lower probability of ANA. In the ECLC‐heterogeneity model, only a small number of respondents (29.09%) considered all attributes, and price was the most easily ignored attribute (64.23%). Compared with the RPL‐EC model, the ECLC‐homogeneity model obtained lower WTPs for COVID‐19 vaccine attributes, and the ECLC‐heterogeneity model obtained mixed WTP results. In the ECLC‐heterogeneity model, preference group 1 obtained higher WTPs, and preference groups 2 and 3 obtained lower WTPs. Conclusions The RPL‐EC, ECLC‐homogeneity and ECLC‐heterogeneity models obtained inconsistent WTPs for COVID‐19 vaccine attributes. The study found that the results of the ECLC‐heterogeneity model considering both ANA and preference heterogeneity may be more plausible because ANA and low preference may be confused in the ECLC‐homogeneity model and the RPL‐EC model. The results showed that the probability of ANA was still high in the ECLC‐heterogeneity model, although it was lower than that in the ECLC‐homogeneity model. Therefore, in future research on DCE (such as the field of vaccines), ANA should be considered as an essential issue. Public Contribution Chinese adults from 31 provinces in mainland China participated in the study. All participants completed the COVID‐19 vaccine choice questions generated through the DCE design.

Abstract An increasing number of studies have indicated that red blood cell distribution width (RDW) may be a novel biomarker for the diagnosis and prognosis of various malignancies. However, to date, data on the association of RDW with non-small cell lung cancer (NSCLC) are unclear. Our present study aimed to explore the value of RDW in NSCLC patients. A total of 338 NSCLC patients, 109 small cell lung cancer (SCLC) patients, and 302 healthy participants were retrospectively analyzed between January 2016 and December 2018. In the present study, we found that RDW was significantly increased in NSCLC patients. Receiver-operating characteristic (ROC) analysis showed that the area under the ROC curve (AUC) of RDW was 0.753 in discriminating NSCLC patients from healthy participants, the optimal cut-off value of RDW was 12.95, and the specificity and sensitivity were 76.33% and 76.16%, respectively. Further analysis found that RDW can enhance the diagnostic performance of Cyfra21-1 and NSE in discriminating NSCLC patients from healthy participants or SCLC patients. Among NSCLC patients, RDW was significantly correlated with TNM stage, T stage, N stage, M stage, and Cyfra21-1, indicating that RDW may be helpful for predicting the prognosis of NSCLC patients. Our findings suggest that RDW can be used as an auxiliary marker for the diagnosis and prognosis of NSCLC.

The significance of sensing hydrogen peroxide (H2O2) is due to its ubiquity, being a potential biomarker as well as an end-product of several oxidation reactions. Herein, based on gold nanoparticles (AuNPs) and coupled with single-stranded DNA (ssDNA) and ceria nanoparticles (CeO2), we developed a novel colorimetric method to detect H2O2 and glucose in NaCl solutions. In the presence of H2O2, ssDNA adsorbed on the surface of CeO2 could be released and subsequently decorated AuNPs, resulting in a distinct color change of the aqueous solution from purple to red, which could be observed by the naked eye. Since H2O2 can be produced in the process of glucose oxidation by glucose oxidase (GOx), this approach can also be employed to detect glucose. By employing this sensing system, the detection limits for H2O2 and glucose are about 0.21 μM and 3.01 µM, respectively. Additionally, monitoring the content of glucose in blood serum samples was successfully achieved by the proposed strategy. This work opens a potential avenue for the quantitative detection of H2O2 and glucose in clinical diagnostics.

An embedded CMOS digital dual tuner for DOCSIS 3.0 and set-top box applications is presented. The dual tuner down-converts a total of ten 6 MHz Annex B channels or eight 8 MHz Annex A channels, for a maximum data rate of 320 Mb/s in Annex B and 400 Mb/s in Annex A mode. The dual tuner exceeds all the stringent SCTE 40 specifications over the 48-1004 MHz bandwidth, without using any external components or SAW filters. Enabling technologies are a harmonic rejection front-end, a low-noise highfrequency resolution PLL, and digital image rejection. To our knowledge this is the first reported multichannel broadband tuner embedded in a DOCSIS 3.0 System on a chip implemented in 65 nm pure digital CMOS technology. [ABSTRACT FROM AUTHOR]

An embedded CMOS digital dual tuner for DOCSIS 3.0 and set-top box applications is presented. The dual tuner down-converts a total of ten 6 MHz Annex B channels or eight 8 MHz Annex A channels, for a maximum data rate of 320 Mb/s in Annex B and 400 Mb/s in Annex A mode. The dual tuner exceeds all the stringent SCTE 40 specifications over the 48-1004 MHz bandwidth, without using any external components or SAW filters. Enabling technologies are a harmonic rejection front-end, a low-noise high-frequency resolution phase-locked loop (PLL) and digital image rejection. To our knowledge this is the first reported multi-channel Broadband Tuner embedded in a DOCSIS 3.0 System on a Chip implemented in a 65 nm pure digital CMOS technology. [ABSTRACT FROM AUTHOR]

A high dynamic range RF variable gain amplifier (RFVGA) suitable for mobile digital television (DTV) tuners is presented. Variable gain is achieved using a capacitive attenuator and current-steering transconductance (Gm) stages, which provide high linearity with relatively low power consumption. A novel broadband input impedance matching scheme based on resistive shunt-feedback is proposed. This scheme allows the RFVGA to achieve a low noise figure. A gain control technique suitable for CMOS current-steering variable gain amplifiers is described; it features 1 dB per step resolution, independent of process and temperature variations. The chip is fabricated in six-metal 0.18 μm CMOS technology and consumes 12.2 mA current from 1.8 V supply. The RFVGA achieves 16 dB maximum gain, 33 dB gain control range, a 4.3 dB noise figure, and an IIP3 higher than 25 dBm. [ABSTRACT FROM AUTHOR]

In order to explore the productivity characteristics of coalbed methane（ＣＢＭ） wells and reasonably allocate the development sequence, according to the actual production data analysis of CBM production wells in Shizhuang south area of Qinshui Basin, four types of characteristic values of the drainage curve were extracted: average daily gas production, peak daily gas production, the time to reach the peak and the production time. Combining the shape of the drainage curve and the 4 characteristic values, three production capacity modes were established, and the production characteristics of the three production capacity modes were analyzed. The random forest algorithm is used to establish the nonlinear relationship between the three productivity models and the geophysical logging data corresponding to the No.3 coal seam. The hyperparameters of the random forest model are determined by grid search combined with cross-validation, and the log curve is established. Classify the prediction model for the capacity pattern of the feature vector. Comparing the predicted category with the actual category, the accuracy rate of prediction reached 91.7%. This shows that the CBM productivity pattern recognition based on the random forest algorithm has high prediction accuracy.