The Design of High Performance, High Resolution Two-Order Delta-Sigma Modulator

The design of single loop two-order Delta-Sigma modulator with feed forward structure is presented in this thesis. Oversampled analog-to-digital converters based on second-order delta-sigma modulation are attractive for VLSI implementation because they are especially tolerant of circuit nonidealities and component mismatch. The noise shaping and oversampling are used in this modulator, the oversampling rate (OSR) is 256 and the resolution could be reached 14 bits. The integrally design of Delta-Sigma modulator is argued in deep in the paper, since the behavior model is tested efficiently by Simulink, the time of design has been cut to the bone. As the fully differential structure is used, the system to inhibit the ability of common-mode interference improved and the sampling rate is also raised, the fully differential switching capacity structure is used in the circuit design of modulator. And because of the fully differential structure, the input noise is reduced, the output slewrate of op-amp is greatly improved and the whole circuit is more stable. The 0.5 ?m CMOS process is used in simulation of circuit, the results of simulation are shown that the amplifier gain is 82.3 dB, the Phase Margin is 71.34°, the output slewrate of op-amp is 202 V/?s, the unit GainBandWidth is 102 MHz. the whole circuit of modulator is tested with 10.24 MHz of the clock frequency, the SNDR reached to 93.2 dB, the Dynamic Range (DR) is 100 dB. In summary, this Delta-Sigma modulator could be used in Portable, Audio system and so on

Coefficient of variation method combined with XGboost ensemble model for wheat growth monitoring

IntroductionObtaining wheat growth information accurately and efficiently is the key to estimating yields and guiding agricultural development.MethodsThis paper takes the precision agriculture demonstration area of Jiaozuo Academy of Agriculture and Forestry in Henan Province as the research area to obtain data on wheat biomass, nitrogen content, chlorophyll content, and leaf area index. By using the coefficient of variation method, a Comprehensive Growth Monitoring Indicator (CGMI) was constructed to perform fractional derivative processing on drone spectral data, and correlation analysis was performed on the fractional derivative spectra with a single indicator and CGMI, respectively. Then, grey correlation analysis was carried out on differential spectral bands with high correlation, the grey correlation coefficients between differential spectral bands were calculated, and spectral bands with high correlation were screened and taken as input variables for the model. Next, ridge regression, random forest, and XGboost models were used to establish a wheat CGMI inversion model, and the coefficient of determination (R2) and root mean squared error (RMSE) were adopted for accuracy evaluation to optimize the wheat optimal growth inversion model.Results and discussionThe results of the study show that: using the data of wheat biomass, nitrogen content, chlorophyll content and leaf area index to construct the comprehensive growth monitoring indicators, the correlation between the wheat growth monitoring indicators and the spectra was calculated, and the results showed that the correlation between the comprehensive growth monitoring indicators and the single indicator correlation had different degrees of increase, and the growth rate could reach 82.22%. The correlation coefficient between the comprehensive growth monitoring indexes and the differential spectra reached 0.92 at the flowering stage, and compared with the correlation coefficient with the original spectra at the same period, the correlation coefficients increased to different degrees, which indicated that the differential processing of spectral data could effectively enhance the spectral correlation. The three models of Random Forest, Ridge Regression and XGBoost were used to construct the wheat growth inversion model with the best effect at the flowering stage, and the XGBoost model had the highest inversion accuracy when comparing in the same period, with the training and test sets reaching 0.904 and 0.870, and the RMSEs were 0.050 and 0.079, so that the XGBoost model can be used as an effective method of monitoring the growth of wheat. To sum up, this study demonstrates that the combination of constructing comprehensive growth monitoring indicators and differential processing spectra can effectively improve the accuracy of wheat growth monitoring, bringing new methods for precision agriculture management

A neutralizing monoclonal antibody-based competitive ELISA for classical swine fever C-strain post–vaccination monitoring

Background: Virus neutralization test (VNT) is widely used for serological survey of classical swine fever (CSF) and efficacy evaluation of CSF vaccines. However, VNT is a time consuming procedure that requires cell culture and live virus manipulation. C-strain CSF vaccine is the most frequently used vaccine for CSF control and prevention. In this study, we presented a neutralizing monoclonal antibody (mAb) based competitive enzyme-linked immunosorbent assay (cELISA) with the emphasis on the replacement of VNT for C-strain post–vaccination monitoring. Results: One monoclonal antibody (6B211) which has potent neutralizing activity against C-strain was generated. A novel cELISA was established and optimized based on the strategy that 6B211 can compete with C-strain induced neutralizing antibodies in pig serum to bind capture antigen C-strain E2. By testing C-strain VNT negative pig sera (n = 445) and C-strain VNT positive pig sera (n = 70), the 6B211 based cELISA showed 100% sensitivity (95% confidence interval: 94.87 to 100%) and 100% specificity (95% confidence interval: 100 to 100%). The C-strain antibody can be tested in pigs as early as 7 days post vaccination with the cELISA. By testing pig sera (n = 139) in parallel, the cELISA showed excellent agreement (Kappa = 0.957) with VNT. The inhibition rate of serum samples in the cELISA is highly correlated with their titers in VNT (r2 = 0.903, p < 0.001). In addition, intra- and inter-assays of the cELISA exhibited acceptable repeatability with low coefficient of variations (CVs). Conclusions: This novel cELISA demonstrated excellent agreement and high level correlation with VNT. It is a reliable tool for sero-monitoring of C-strain vaccination campaign because it is a rapid, simple, safe and cost effective assay that can be used to monitor vaccination-induced immune response at the population level.info:eu-repo/semantics/publishedVersio

Antibodies to SARS Coronavirus in Civets

Using three different assays, we examined 103 serum samples collected from different civet farms and a market in China in June 2003 and January 2004. While civets on farms were largely free from SARS-CoV infection, ≈80% of the animals from one animal market in Guangzhou contained significant levels of antibody to SARS-CoV, which suggests no widespread infection among civets resident on farms, and the infection of civets in the market might be associated with trading activities under the conditions of overcrowding and mixing of various animal species

Metformin improves polycystic ovary syndrome in mice by inhibiting ovarian ferroptosis

Background and objectivePCOS is a common metabolic disorder in women of reproductive age, which pathogenesis is very complex. The role of ferroptosis in PCOS is a novel finding, and the mechanistic studies are not clear. Metformin is a commonly used drug of PCOS but few studies on whether metformin can improve the follicle development and ovarian function in PCOS. We aims to use PCOS mouse model to study the effect of metformin on PCOS based on the ovarian function and explored the regulation of metformin in PCOS mice by intervening in ferroptosis pathway.Materials and methodsC57 BL/6J female mice aged 4-5 weeks were purchased and gavaged with letrozole (1 mg/kg/day) combined with high-fat diet for 21days to establish PCOS model, and control group was set up. After modeling, the mice were divided into PCOS model group and metformin treatment group (Met) (n=6).The Met group were gavaged metformin (200 mg/kg/day) for 28 days. The body weight, estrous cycle, glucose tolerance test (OGTT)and insulin resistance test (ITT) were monitored. Then, The mice were euthanized to collect serum and ovaries. Elisa was used to detect changes in related serum hormones (E2, LH, FSH, TP). Ovaries used for molecular biology experiments to detect changes in GPX4, SIRT3, AMPK/p-AMPK, and mTOR/p-mTOR by Western blot and qPCR.ResultsCompared with the model group mice, body weight was significantly reduced, and their estrous cycle was restored in Met group. The results of OGTT and ITT showed an improvment of glucose tolerance and insulin resistance. Morphological results showed that after metformin treatment, polycystic lesions in ovaries were reduced, the ovarian function was restored, and the expressions of SIRT3 and GPX4 were elevated. WB results demonstrated that the expressions of p-mTOR and p-AMPK in ovaries were significantly reduced in Model group, but reversed in MET group.ConclusionOur study confirmed metformin could not only improve body weight and metabolism disorders, but also improve ovarian dysfunction in PCOS mice.In addition, we explored metformin could regulate ferroptosis to improve PCOS via the SIRT3/AMPK/mTOR pathway. Our study complements the mechanisms by which metformin improves PCOS

Adenovirus Gene Transfer to Amelogenesis Imperfecta Ameloblast-Like Cells

To explore gene therapy strategies for amelogenesis imperfecta (AI), a human ameloblast-like cell population was established from third molars of an AI-affected patient. These cells were characterized by expression of cytokeratin 14, major enamel proteins and alkaline phosphatase staining. Suboptimal transduction of the ameloblast-like cells by an adenovirus type 5 (Ad5) vector was consistent with lower levels of the coxsackie-and-adenovirus receptor (CAR) on those cells relative to CAR-positive A549 cells. To overcome CAR -deficiency, we evaluated capsid-modified Ad5 vectors with various genetic capsid modifications including “pK7” and/or “RGD” motif-containing short peptides incorporated in the capsid protein fiber as well as fiber chimera with the Ad serotype 3 (Ad3) fiber “knob” domain. All fiber modifications provided an augmented transduction of AI-ameloblasts, revealed following vector dose normalization in A549 cells with a superior effect (up to 404-fold) of pK7/RGD double modification. This robust infectivity enhancement occurred through vector binding to both αvβ3/αvβ5 integrins and heparan sulfate proteoglycans (HSPGs) highly expressed by AI-ameloblasts as revealed by gene transfer blocking experiments. This work thus not only pioneers establishment of human AI ameloblast-like cell population as a model for in vitro studies but also reveals an optimal infectivity-enhancement strategy for a potential Ad5 vector-mediated gene therapy for AI

Notch1 Augments Intracellular Trafficking of Adeno-Associated Virus Type 2

We report here the significance of the Notch1 receptor in intracellular trafficking of recombinant adeno-associated virus type 2 (rAAV2). RNA profiling of human prostate cancer cell lines with various degrees of AAV transduction indicated a correlation of the amount of Notch1 with rAAV transgene expression. A definitive role of Notch1 in enhancing AAV transduction was confirmed by developing clonal derivatives of DU145 cells overexpressing either full-length or intracellular Notch1. To discern stages of AAV2 transduction influenced by Notch1, competitive binding with soluble heparin and Notch1 antibody, intracellular trafficking using Cy3-labeled rAAV2, and blocking assays for proteasome and dynamin pathways were performed. Results indicated that in the absence or low-level expression of Notch1, only binding of virus was found on the cell surface and internalization was impaired. However, increased Notch1 expression in these cells allowed efficient perinuclear accumulation of labeled capsids. Nuclear transport of the vector was evident by transgene expression and real-time PCR analyses. Dynamin levels were not found to be different among these cell lines, but blocking dynamin function abrogated AAV2 transduction in DU145 clones overexpressing full-length Notch1 but not in clones overexpressing intracellular Notch1. These studies provide evidence for the role of activated Notch1 in intracellular trafficking of AAV2, which may have implications in the optimal use of AAV2 in human gene therapy

Editorial for the Special Issue “Electromagnetic Exploration: Theory, Methods and Applications”

Electromagnetic (EM) methods, both airborne and ground, are some of the most widely used geophysical techniques in mineral exploration, in which natural or controlled sources are used to transmit EM waves to the Earth and measure the reflected EM signal [...

Real-Time Monitoring of Bond Slip between GFRP Bar and Concrete Structure Using Piezoceramic Transducer-Enabled Active Sensing

Glass fiber-reinforced polymers (GFRPs) have received increasing attention in recent years due to their overall performance of light weight, low cost and corrosion resistance, and they are increasingly used as reinforcement in concrete structures. However, GFRP material has low elastic modulus and linear elastic properties compared with steel bars, which introduces different bonding characteristics between bars and concrete. Therefore, a reliable monitoring method is urgently needed to detect the bond slip in GFRP-reinforced concrete structures. In this paper, a piezoceramic-based active sensing approach is proposed and developed to find the debonding between a GFRP bar and the concrete structure. In the proposed method, we utilize PZT (lead zirconate titanate) as two transducers. One acts as an actuator which is buried in the concrete structure, and the other acts as a sensor which is attached to the GFRP bar by taking advantage of machinability of the GRRP material. Both transducers are strategically placed to face each other across from the interface between the GFRP bar and the concrete. The actuator provokes a stress wave that travels through the interface. Meanwhile, the PZT patch that is attached to the GFRP bar is used to detect the propagating stress wave. The bonding condition determines how difficult it is for the stress wave traveling through the interface. The occurrence of a bond slip leads to cracks between the bar and the concrete, which dramatically reduces the energy carried by the stress wave through the interface. In this research, two specimens equipped with the PZT transducers are fabricated, and pull-out tests are conducted. To analyze the active sensing data, we use wavelet packet analysis to compute the energy transferred to the sensing PZT patch throughout the process of debonding. Experimental results illustrate that the proposed method can accurately capture the bond slip between the GFRP bar and the concrete