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It is difficult to adjust the pH of oil acidized wastewater rich in Ca2+, thus hindering the polyacrylamide (PAM) flocculation. This study aims at accelerating the flocculation process by introducing CO2 into the water to induce the formation of CaCO3 nuclei. The order in which CO2 and NaOH were added affected the floc structures. Compared with CO2-NaOH-PAM, the flocs of NaOH-CO2-PAM were more compact and more CaCO3 crystals were formed. The aqueous Ca2+ involved in the reaction reached 20%, and CO2 utilization was enhanced. The settling time was shortened by half (from 20 to 3 min), and NaOH consumption was reduced by one-tenth (from 0.03 to 0.003 mol), hence significantly reducing the costs. Due to the higher settling rate and shorter contact time, the NaOH-CO2-PAM flocs adsorbed less so that the residual oil was 124 mg·L−1, while in the case of CO2-NaOH-PAM it was 88 mg·L−1. As a promising coagulation aid, CO2 can also be used to mineralize pollutants in wastewater.

Vehicle counting and traffic volume estimation on traffic videos has gained extensive attention from multimedia and computer vision communities. Recent vehicle counting and volume estimation methods, including detection based and time-spatial image (TSI) based methods have achieved significant improvements. However, how to balance the accuracy and speed is still a challenge to this task. In this paper, we design a fast and accurate vehicle counting and traffic volume estimation method. Firstly, traffic videos are converted to TSIs and we annotate the vehicle locations in TSIs manually. Then, we design a simple TSI density map estimation network which utilizes attention mechanism to strengthen the features in the traffic locations for vehicle counting. Finally, we use the parameters obtained from the vehicle counting network to further estimate the traffic volume. Experiments on UA-DETRAC dataset demonstrate that the vehicle counting network not only takes a balance between counting accuracy and speed, but also well estimates the traffic volume when the video data is insufficient.

We propose a novel variable step size predictor design method for a class of linear discrete-time censored system. We divide the censored system into two parts. The system measurement equation in one part doesn't contain the censored data, and the system measurement equation in the other part is the censored signal. For the normal one, we use the Kalman filtering technology to design one-step predictor. For the one that the measurement equation is censored, we determine the predictor step size according to the censored data length and give the gain compensation parameter matrix $β(\mathfrak{s})$ for the case predictor with obvious errors applying the minimum error variance trace, projection formula, and empirical analysis, respectively. Finally, a simulation example shows that the variable step size predictor based on empirical analysis has better estimation performance.

Seasonal influenza causes mild to severe respiratory infections and significant morbidity, especially in older adults. Transcriptomic analysis in populations across multiple flu seasons has provided insights into the molecular determinants of vaccine response. Still, the metabolic changes that underlie the immune response to influenza vaccination remain poorly characterized. We performed untargeted metabolomics to analyze plasma metabolites in a cohort of younger and older subjects before and after influenza vaccination to identify vaccine-induced molecular signatures. Metabolomic and transcriptomic data were combined to define networks of gene and metabolic signatures indicative of high and low antibody response in these individuals. We observed age-related differences in metabolic baselines and signatures of antibody response to influenza vaccination and the abundance of α-linolenic and linoleic acids, sterol esters, fatty-acylcarnitines, and triacylglycerol metabolism. We identified a metabolomic signature associated with age-dependent vaccine response, finding increased tryptophan and decreased polyunsaturated fatty acids (PUFAs) in young high responders (HRs), while fatty acid synthesis and cholesteryl esters accumulated in older HRs. Integrated metabolomic and transcriptomic analysis shows that depletion of PUFAs, which are building blocks for prostaglandins and other lipid immunomodulators, in young HR subjects at Day 28 is related to a robust immune response to influenza vaccination. Increased glycerophospholipid levels were associated with an inflammatory response in older HRs to flu vaccination. This multi-omics approach uncovered age-related molecular markers associated with influenza vaccine response and provides insight into vaccine-induced metabolic responses that may help guide development of more effective influenza vaccines.

Vaccines are among the most cost-effective public health interventions for preventing infection-induced morbidity and mortality, yet much remains to be learned regarding the mechanisms by which vaccines protect. Systems immunology combines traditional immunology with modern ‘omic profiling techniques and computational modeling to promote rapid and transformative advances in vaccinology and vaccine discovery. The NIH/NIAID Human Immunology Project Consortium (HIPC) has leveraged systems immunology approaches to identify molecular signatures associated with the immunogenicity of many vaccines, including those targeting seasonal influenza, yellow fever, and hepatitis B. These data are made available to the broader scientific community through the ImmuneSpace data portal and analysis engine leveraging the NIH/NIAID ImmPort repository1,2. However, a barrier to progress in this area is that comparative analyses have been limited by the distributed nature of some data, potential batch effects across studies, and the absence of multiple relevant studies from non-HIPC groups in ImmPort. To support comparative analyses across different vaccines, we have created the Immune Signatures Data Resource, a compendium of standardized systems vaccinology datasets. This data resource is available through ImmuneSpace, along with code to reproduce the processing and batch normalization starting from the underlying study data in ImmPort and the Gene Expression Omnibus (GEO). The current release comprises 1405 participants from 53 cohorts profiling the response to 24 different vaccines and includes transcriptional profiles and antibody response measurements. This novel systems vaccinology data release represents a valuable resource for comparative and meta-analyses that will accelerate our understanding of mechanisms underlying vaccine responses.

The linear phase is a major characteristic of digital differentiators in many signal processing applications. This study presents a sequential partial optimization method for designing a fullband infinite impulse response digital differentiator with a near linear phase. To achieve a near linear phase, the group delay is treated as an optimization variable, and the maximum phase error is minimized within a constrained domain. During each iteration of the algorithm, in addition to the whole numerator and group delay, only one secondorder denominator factor is optimized. The necessary and sufficient stability triangles are applied to insure the stability of the differentiators, and the Gauss-Newton strategy is used to handle the nonconvexity of the design problems. Design examples show that the proposed method outperforms several state-of-the-art methods in terms of the maximum phase deviation from the desired linear phase.

Optimal designs of finite impulse response (FIR) digital filters with prescribed magnitude and phase responses have found many applications in signal processing. To deal with the nonconvexity of the constraint region in the phase-error and magnitude-error constrained design, a new error constraint method based on a modified annulus sector (MAS) is proposed. With the new constraint method, the phase-error and magnitude-error constrained least squares, phase-error constrained minimax, and iterative reweighted phase-error constrained minimax designs of FIR filters are studied. Analyses and design examples demonstrate the higher accuracy of the MAS constraint and better filter performance by the constraint method than existing constraint methods. An application in the design of digital differentiators with flatness constraints is also provided.

It is difficult to adjust the pH of oil acidized wastewater rich in Ca

The skin lesion erythema migrans (EM) is an initial sign of the Ixodes tick-transmitted Borreliella spirochetal infection known as Lyme disease. T cells and innate immune cells have previously been shown to predominate the EM lesion and promote the reaction. Despite the established importance of B cells and antibodies in preventing infection, the role of B cells in the skin immune response to Borreliella is unknown. Here, we used single-cell RNA-Seq in conjunction with B cell receptor (BCR) sequencing to immunophenotype EM lesions and their associated B cells and BCR repertoires. We found that B cells were more abundant in EM in comparison with autologous uninvolved skin; many were clonally expanded and had circulating relatives. EM-associated B cells upregulated the expression of MHC class II genes and exhibited preferential IgM isotype usage. A subset also exhibited low levels of somatic hypermutation despite a gene expression profile consistent with memory B cells. Our study demonstrates that single-cell gene expression with paired BCR sequencing can be used to interrogate the sparse B cell populations in human skin and reveals that B cells in the skin infection site in early Lyme disease expressed a phenotype consistent with local antigen presentation and antibody production.

A dysregulated immune response against the SARS-CoV-2 virus plays a critical role in severe COVID-19. However, the molecular and cellular mechanisms by which the virus causes lethal immunopathology are poorly understood. Here, we utilize multiomics single-cell analysis to probe dynamic immune responses in patients with stable or progressive manifestations of COVID-19, and assess the effects of tocilizumab, an anti-IL-6 receptor monoclonal antibody. Coordinated profiling of gene expression and cell lineage protein markers reveals a prominent type-1 interferon response across all immune cells, especially in progressive patients. An anti-inflammatory innate immune response and a pre-exhaustion phenotype in activated T cells are hallmarks of progressive disease. Skewed T cell receptor repertoires in CD8+ T cells and uniquely enriched V(D)J sequences are also identified in COVID-19 patients. B cell repertoire and somatic hypermutation analysis are consistent with a primary immune response, with possible contribution from memory B cells. Our in-depth immune profiling reveals dyssynchrony of the innate and adaptive immune interaction in progressive COVID-19, which may contribute to delayed virus clearance and has implications for therapeutic intervention.

QRS complex detection plays an important role in the identification and classification of ECG signals. In this paper , a new QRS complex detection algorithm named II-P&T algorithm is proposed based on I-P&T algorithm by means of the IPCMM algorithm rather than fdatool to generate a bandpass digital filter and a lowpass digital filter. Simulation demonstrates that on the MIT-BIH database, the performance of the proposed II-P&T algorithm is better than P&T and I-P&T algorithm in terms of sensitivity (Se), positive predictivity (PP), detection error (DER) of the proposed algorithm with results of Se = 99.62%, PP = 99.54%, and DER = 0.84%. The ECG classification accuracy of the II-P&T+SVM algorithm reaches 97.68%, which is higher than the I-P&T+SVM algorithm. Therefore, II-P&T algorithm can accurately locate the QRS complex wave and reduce the number of false detections and can be used to the process of the feature extraction of ECG signal.

Challenges for optimal design of infinite impulse response digital filters include the high nonconvexity of design problem and inevitable stability constraints on the filters. To reduce the nonconvexity and tackle the stability constraints, a sequential partial optimization (SPO) algorithm was recently developed to divide the design problem into a sequence of subproblems, each updating only two second-order denominator factors. But the convergence of that algorithm is not guaranteed. By applying an incremental update with an optimized step length in each subproblem, this paper presents an improved SPO algorithm which is guaranteed to converge to a Karush–Kuhn–Tucker (not necessarily global) solution of the design problem. This paper also extends the SPO algorithm to a more general case where the number of denominator factors optimized in the subproblems can be any positive number smaller than half of the denominator order. Convergence performance of the algorithm is shown by the design of two example filters with typical specifications widely adopted in the literature. Comparisons with state-of-the-art methods demonstrate that the improved SPO algorithm obtains better filters than the competing methods in terms of the maximum magnitude of frequency-response error.

The extended Kalman filter (EKF) has a wide range of applications (especially in power battery management systems) with a rapidly increasing market share. It aims to minimize the symmetric loss function (mean square error) and it has high accuracy and efficiency in battery state estimation. This study deals with the second-order extended Kalman filter-based process and the measurement white noise estimation problem for nonlinear continuous-discrete systems. The design of the white noise filter and smoother were, firstly, converted into a linear estimation problem by the second-order Taylor series expansion approximation and the function that makes the second-order term approximately equivalent to the estimation error variance. Secondly, based on the projection formula of the Kalman filtering (KF) theory and the Lemma of expectation for quadratic and quartic product traces of random vectors, the second-order EKF was derived. Then, to generate white noise estimators in the forms of filtering and smoothing, we derived a recursive solution, using an innovation method. Finally, a numerical example is given to show the effectiveness of the proposed method.

CoCuMnO x as one solar energy absorbing coating was synthesized by a facile co-precipitation approach for photocatalytic oxidation of gaseous toluene under visible light, and characterized by UV–Vis-DRS, BET, SEM, XRD and XPS, respectively. It demonstrated that CoCuMnO x owned photocatalytic activity and 57% of toluene with an initial concentration of 400 mg/m3 was degraded by 1 g CoCuMnO x under 6 h irradiation with a 100 W halogen tungsten lamp. The degradation of toluene was mainly attributed to photolysis and photocatalysis, and the thermal effect of CoCuMnO x had little effect. The degradation efficiency of toluene decreased gradually from 57 to 32% after five consecutive cycles. High active spinels like Cu1.5Mn1.5O4, CuMn2O4, CuCoO2 and Co2MnO4 existed onto the CoCuMnO x surface, which accelerated electron transfer so as to form various free radicals, such as h+, .OH, and ·O2 − etc. Toluene was oxidized evidently by these radicals so that the aromatic ring itself was cleaved to generate alcoholic, aldehydic and acidic intermediates.

A sequential partial optimization method is presented in this paper for the minimax design of two-dimensional infinite impulse response filters with separable denominator. The method converts the minimax design problem into a sequence of smaller subproblems, each updating only one pair of second-order denominator factors. The necessary and sufficient stability triangles for one-dimensional filters are used as the stability constraints on the two-dimensional filters. The first-order Taylor expansion and a trust-region method are used to deal with the nonconvexity of the subproblems and guarantee the convergence of the solution algorithm. By comparing with a corresponding joint optimization method, the sequential partial optimization algorithm is shown to converge faster for filters with relatively high denominator order. This is mainly due to the observation that the trust region to assure the convergence is usually much smaller for the joint optimization method. Moreover, the limit solution of the sequential partial optimization algorithm has been proved to be a Karush–Kuhn–Tucker point of the design problem. Design examples demonstrate that the proposed algorithm has obtained smaller maximum frequency response errors than the competing methods both for filters with separable denominator of the same order and for filters with nonseparable denominator of about the same implementation complexity.

The seasonal influenza vaccine is an important public health tool but is only effective in a subset of individuals. The identification of molecular signatures provides a mechanism to understand the drivers of vaccine-induced immunity. Most previously reported molecular signatures of influenza vaccination were derived from a single age group or season, ignoring the effects of immunosenescence or vaccine composition. Thus, it remains unclear how immune signatures of vaccine response change with age across multiple seasons. Here we profile the transcriptional landscape of young and older adults over five consecutive vaccination seasons to identify shared signatures of vaccine response as well as marked seasonal differences. Along with substantial variability in vaccine-induced signatures across seasons, we uncovered a common transcriptional signature 28 days post-vaccination in both young and older adults. However, gene expression patterns associated with vaccine-induced antibody responses were distinct in young and older adults; for example, increased expression of Killer Cell Lectin Like Receptor B1 (KLRB1;CD161) 28 days post-vaccination positively and negatively predicted vaccine-induced antibody responses in young and older adults, respectively. These findings contribute new insights for developing more effective influenza vaccines, particularly in older adults.

Small sample sizes combined with high person-to-person variability can make it difficult to detect significant gene expression changes from transcriptional profiling studies. Subtle, but coordinated, gene expression changes may be detected using gene set analysis approaches. Meta-analysis is another approach to increase the power to detect biologically relevant changes by integrating information from multiple studies. Here, we present a framework that combines both approaches and allows for meta-analysis of gene sets. QuSAGE meta-analysis extends our previously published QuSAGE framework, which offers several advantages for gene set analysis, including fully accounting for gene-gene correlations and quantifying gene set activity as a full probability density function. Application of QuSAGE meta-analysis to influenza vaccination response shows it can detect significant activity that is not apparent in individual studies.

Ammonium persulphate (APS) was used as a novel additive for blending modification of Polyvinylidene Fluoride (PVDF) membrane in this study. The addition of APS changed the macroscopic and micro-structure of membrane, as the small scaly aggregates appeared and hydrophilicity increased slightly. Comparing with blank membrane, the specific surface area of PVDF membrane was reduced from 19.98 m 2 /g to 7.95 m 2 /g, and the total adsorption average pore size of membrane was increased from 89.82 nm to 253.58 nm when 0.7% of APS was added. During the short term filtration, the pure water flux of blank membrane was reduced by 61% and 81% after the first and second testing cycle, respectively. As a comparison, it was only reduced by 39% and 60% for 0.7% APS modified membrane. The effluent turbidity values of those modified membranes were all lower than that of blank membrane. During the long term operation in MBR, the filtration time of 0.7% APS modified membrane lasted for 21 days including 2 operational cycles. Comparing with modified membrane, the filtration time of blank membrane only lasted for 19 days, which included 3 times of membrane cleaning.

The dolomite reservoirs in the Paleogene Shahejie Formation in the Bozhong area of the Bohai Bay Basin contain a large amount of dolomite cement. Petrologic and mineralogic studies have shown that the dolomite cements can be divided into three types according to their occurrence: coating dolomite (CD), pore-lining dolomite (LD), and pore-filling dolomite (FD). The laser microsampling technique was used to analyze the C and O isotopes in the carbonate minerals. This method is an effective way to produce CO2 gas from a particular carbonate structure in a thin section, and it has a spatial resolution of 20&ndash, 50 &micro, m and an optimal precision of approximately &plusmn, 0.22&sigma, for &delta, 13C and &delta, 18O in carbonate standard materials. The carbon and oxygen isotopic compositions and the oxygen isotopic geothermometer results showed that the dolomitization fluid is mainly low temperature fluid, the lake basin environment is relatively closed, and the salinity index Z value is greater than 120, which indicates the invasion of seawater. CD and early-stage LD crystals were mainly very fine crystals with faint cathodoluminescence, which indicates the early formation of diagenesis. The high temperatures of late-stage LD and FD measured by oxygen isotope thermometers indicates that they formed at a deeper depth. The dolomite cements in the study area may have formed in two stages: seepage-reflux dolomitization during the penecontemporaneous period and burial dolomitization.

The pH value of oil acidized wastewater is relatively low (pH = 6.1), which seriously affects the flocculation of polyacrylamide (PAM). NaOH was used to adjust the pH value, but the maximum was only 7.5. The regulation was limited as the Ca2+ in aqueous phase up to 1,350 mg L−1 consumed OH−. A novel formulation of Na2CO3 + PAM was proposed to form CaCO3 floc core to facilitate PAM coagulation. When the concentration was above 400 mg L−1, the PAM precipitation tended to be maximum, followed by NaOH adjustment of pH to 8.0 that could enhance PAM flocculation successively. The sewage sludge (SS) remained and residue oil reduced to 25 mg L−1 and 34mg L−1 respectively. The analysis of the species and composition of fatty acids indicated that the coagulation-flocculation selectively effected the sedimentation of saturated fatty acids (SAT). This provides a new idea for recovery of high value-added residual oil. The optimal additive of Na2CO3 is expected as promising coagulant aid to improve the PAM coagulation-flocculation of oil acidized wastewater.

Influenza viruses continue to present global threats to human health. Antigenic drift and shift, genetic reassortment, and cross-species transmission generate new strains with differences in epidemiology and clinical severity. We compared the temporal transcriptional responses of human dendritic cells (DC) to infection with two pandemic (A/Brevig Mission/1/1918, A/California/4/2009) and two seasonal (A/New Caledonia/20/1999, A/Texas/36/1991) H1N1 influenza viruses. Strain-specific response differences included stronger activation of NF-κB following infection with A/New Caledonia/20/1999 and a unique cluster of genes expressed following infection with A/Brevig Mission/1/1918. A common antiviral program showing strain-specific timing was identified in the early DC response and found to correspond with reported transcript changes in blood during symptomatic human influenza virus infection. Comparison of the global responses to the seasonal and pandemic strains showed that a dramatic divergence occurred after 4 h, with only the seasonal strains inducing widespread mRNA loss. IMPORTANCE Continuously evolving influenza viruses present a global threat to human health; however, these host responses display strain-dependent differences that are incompletely understood. Thus, we conducted a detailed comparative study assessing the immune responses of human DC to infection with two pandemic and two seasonal H1N1 influenza strains. We identified in the immune response to viral infection both common and strain-specific features. Among the stain-specific elements were a time shift of the interferon-stimulated gene response, selective induction of NF-κB signaling by one of the seasonal strains, and massive RNA degradation as early as 4 h postinfection by the seasonal, but not the pandemic, viruses. These findings illuminate new aspects of the distinct differences in the immune responses to pandemic and seasonal influenza viruses.

To elucidate gene expression pathways underlying age-associated impairment in influenza vaccine response, we screened young (age 21-30) and older (age ≥65) adults receiving influenza vaccine in two consecutive seasons and identified those with strong or absent response to vaccine, including a subset of older adults meeting criteria for frailty. PBMCs obtained prior to vaccination (Day 0) and at day 2 or 4, day 7 and day 28 post-vaccine were subjected to gene expression microarray analysis. We defined a response signature and also detected induction of a type I interferon response at day 2 and a plasma cell signature at day 7 post-vaccine in young responders. The response signature was dysregulated in older adults, with the plasma cell signature induced at day 2, and was never induced in frail subjects (who were all non-responders). We also identified a mitochondrial signature in young vaccine responders containing genes mediating mitochondrial biogenesis and oxidative phosphorylation that was consistent in two different vaccine seasons and verified by analyses of mitochondrial content and protein expression. These results represent the first genome-wide transcriptional profiling analysis of age-associated dynamics following influenza vaccination, and implicate changes in mitochondrial biogenesis and function as a critical factor in human vaccine responsiveness.

Annual influenza vaccinations are currently recommended for all individuals 6 months and older. Antibodies induced by vaccination are an important mechanism of protection against infection. Despite the overall public health success of influenza vaccination, many individuals fail to induce a substantial antibody response. Systems-level immune profiling studies have discerned associations between transcriptional and cell subset signatures with the success of antibody responses. However, existing signatures have relied on small cohorts and have not been validated in large independent studies. We leveraged multiple influenza vaccination cohorts spanning distinct geographical locations and seasons from the Human Immunology Project Consortium (HIPC) and the Center for Human Immunology (CHI) to identify baseline (i.e., before vaccination) predictive transcriptional signatures of influenza vaccination responses. Our multicohort analysis of HIPC data identified nine genes (RAB24, GRB2, DPP3, ACTB, MVP, DPP7, ARPC4, PLEKHB2, and ARRB1) and three gene modules that were significantly associated with the magnitude of the antibody response, and these associations were validated in the independent CHI cohort. These signatures were specific to young individuals, suggesting that distinct mechanisms underlie the lower vaccine response in older individuals. We found an inverse correlation between the effect size of signatures in young and older individuals. Although the presence of an inflammatory gene signature, for example, was associated with better antibody responses in young individuals, it was associated with worse responses in older individuals. These results point to the prospect of predicting antibody responses before vaccination and provide insights into the biological mechanisms underlying successful vaccination responses.

New designs of infinite impulse response (IIR) wideband digital integrators of second-, third- and forth-order are presented in this paper. These new integrators are designed by a recently proposed magnitude constrained minimax phase-error method. In these designs, the maximum phase response error is minimized under some constraints that the maximum relative magnitude response error is below a prescribed level. Simulation results show that our proposed wideband IIR digital integrators have much smaller maximum phase response error and maximum relative magnitude error than existing wideband IIR digital integrators in the literature.