Double Filter Research Articles

Double-High-Pass-Filter-Based Electrical-Recording Front-Ends and Fluorescence-Recording Front-Ends for Monitoring Multimodal Neural Activity

This brief presents a multimodal neural activity monitoring system consisting of a double-high-pass-filter-based electrical-recording front-end and a fluorescence-recording front-end. The proposed electrical-recording circuit based on double high-pass filters is implemented by placing a narrow-band buffer in the feedback path of the low-noise and programmable-gain amplifiers so that low-frequency artifacts can be sufficiently suppressed during the electrical and fluorescence recording. The implemented system successfully measures the electrical signals and calcium ions in vivo for studying heterogeneous cell populations. For electrical recording, the front-end consumes the power of 2 $\mu \text{W}$ /channel and achieves the input-referred noise of 2.9 $\mu \text{V}_{\mathrm{ rms}}$ . The high-pass cutoff frequency can be programmed from sub-1 Hz to about 300 Hz using the function of double high-pass filtering. For fluorescence recording, the front-end consumes the power of 10.8 $\mu \text{W}$ /block and occupies the area of 0.18 mm2/block.

Bizanțul în filtrul balcanic – poezie română din a doua jumătate a secolului XX / Byzantium in Balkanic filter – Romanian poetry in the second part of twentieth century

Talking about Balkanism in Romanian contemporary poetry means to betray, to a certain extent required by degradation or alteration, some literary themes and motifs. Finding ourselves in a geographical area of cultural contaminations, the influence of other peoples in Balkans comes naturally: the nostalgia of Byzantium perfection, continuous reporting at an ideal time, abstraction of the chronology. Balkan themes and motives in poetry are identifiable from the early writings of Romanian literature, including the folklore, with Anton Pann, the Vacarescu and Conachi poets – and their ludic descriptivism – , to Ion Barbu, who strikes a metaphysical note in the Balkan motifs, and later, in the second part of twentieth century, with the species of parody. The Romanian native receptivity allowed continuous assimilations without creating an unpleasant heterogeneous feeling. This openness has contributed decisively in a formative way to bring Byzantium on a new soil in a perfect and saturated array; the perfectibility is not possible anymore, so the failure was natural, in a degraded status – Constantinople. Oriental-Byzantine gravity becomes in Oriental-Balkan tragedy or comedy, balance slid to one extreme, sometime becoming ridiculous. Contemporary poetry does not express any more a true lament, but a kind of parody (in ludic poetry) or sheer contempt (in the solemn poetry). The Balkan intelligence is not critical, but creative, with the risk of perpetuating monstrous forms, beyond good and evil. Byzantium established itself through a double filter – for the East and for the West – influencing and being influenced, in turn. Romanian poetry has the full sequence of themes and aesthetic formulae, from tragic to comic, often switching rapidly from one edge to the other, taking into account the old Thracian solemn part, then the proud Byzantium and its absorption in Constantinople – all rolling in a series of formal expressions reflected in themes and vocabulary.

Simultaneous removal of particulates and NO by the catalytic bag filter containing V2O5-MoO3/TiO2

V2O5-MoO3/TiO2 based catalytic bag filters were developed for the simultaneous removal of particulates and NO in the temperature range of 200–250 °C. Good denitrification activity, dedust efficiency as well as high adhesion strength in the temperature range of 200–250 °C was exhibited. The study of catalyst powder for coating revealed that the increased V and Mo content in catalyst can elevate the low-temperature activity, and the chosen V10Mo10 sample for coating showed the best activity with 100% NO conversion at just 180 °C. The further research on catalytic bag filter found the low ratio of PTFE, high loading and long residence time (e.g., low filtration velocity or double layer filter) may help to achieve high DeNOx efficiency. The best performance was obtained with above 80% NO conversion at 200–250 °C even in the presence of SO2/H2O and 99.9% dust collection efficiency on the condition of 500 g/m2 loading, 10% PTFE, 0.5 m/min filtration velocity and double layers of filter, which demonstrated great feasibility for industrial application.

Purpose of the housing double stage polypropylene-carbon cartridges filters usage in bath gray water treatment

Bath gray water organoleptically did not appear to be significantly contaminated liquid. However, in order to re-use them, they need proper treatment. When recirculated in a household, they cannot pose a threat to human life. Based on their appearance, it seems that the solution to the problem is the use of cartridges filter. The article presents the results of the filtration of gray water from the bath through the filtration system with a housing double stage polypropylene-carbon filter FCCA-STO and to determine the impact of individual filter layers on wastewater treatment, tests were carried out on a single polypropylene FCPS10 and carbon FCCA filtration cartridge. The aim of the study was to determine the suitability of the selected housing filter cartridges for the treatment of bathing gray water for their reuse. For the tests were used natural bathing gray water from a two-family building inhabited by seven people. Wastewater were fed to the filter with a constant flow rate of 0.1 dm3·s–1. The assessment of the work of the filters based on parameters such as: COD, BOD5, suspension, dry residue, decay and turbidity. The conducted tests have shown a slight improvement in most of the quality parameters of gray water after filtration through selected housing cartridge filters. Only for turbidity, the reduction in the value of the pollution indicator was noticeable. The cartridge filters used in tests, acted like ordinary mechanical filtration cartridges. For the considered gray water, the use of analyzed cartridge filters can only be used for their initial purification.

Dual-Regulating Feedback Optimization Control of Distributed Energy Storage System in Power Smoothing Scenariox Based on KF-MPC

Taking the photovoltaic (PV)-hybrid energy storage system (HESS) composed of the distributed PV power generation and the distributed energy storage as the research object, under the scenario of smoothing PV power fluctuation, a dual-regulating feedback optimization control strategy of the PV-HESS based on double Kalman filters (KFs) and model predictive control (MPC) is proposed. The first Kalman filter (KF1) is used to realize the effective decomposition of the PV power, the MPC is used to optimize the output and the state of charge (SOC) of the HESS, and the output of the HESS is optimized by the second Kalman filter (KF2) to realize the energy distribution between the energy storage battery and supercapacitors. The optimized output of the HESS is fed back to the KF1 to realize the closed-loop optimization of the entire PV-HESS. The effectiveness and correctness of the proposed optimization control method are verified by simulating the actual operation data of a certain PV-HESS station in China. The simulation results show that the service life of the HESS can be extended by the dual feedback regulating control, and the overall economics of the PV-HESS can be improved.

High order aberrations calculations of Wien filters using differential algebra methods

In this paper, a novel scheme based on the differential algebraic (DA) method is proposed to analyze the electron optics properties of the Wien filters. A new software package is then developed, to compute the geometrical and chromatic aberrations up to the fifth order of the Wien filters. For examples, the aberrations of single filter and the double filters are calculated. The calculated geometrical aberration coefficients are comparable with the counterpart calculated by Tang's theory. However, both theories can only match with each other in the calculation of the chromatic aberration coefficient when the dispersion ray is taken into consideration in Tang's theory.

Interannual variation in the start of vegetation growing season and its response to climate change in the Qinghai–Tibet Plateau derived from MODIS data during 2001 to 2016

In recent years, remote sensing of phenology has become a useful tool to reveal the response and feedback of vegetation dynamics to global climate change due to its multitemporal phase, wide-coverage, continuous space coverage, and long-time series. Based on the Moderate Resolution Imaging Spectroradiometer data product MOD09A1, enhanced vegetation index (EVI) was calculated, and the time series EVI of the growing season in the Qinghai–Tibet Plateau (QTP) from 2001 to 2016 was reconstructed in light of the double logistic function filter. A dynamic threshold method was used to extract the starting date of the growing season (SOG) of vegetation. The characteristics of temporal–spatial variation of SOG of vegetation in QTP were analyzed, and the irregularity of the vegetation SOG in response to climate change was explored. The results show that: (1) the vegetation SOG in QTP varied between day of year (DOY) 110 and DOY 170 between 2001 and 2016. Affected by the spatial difference of hydrothermal conditions, the vegetation SOG is gradually delayed from the southeast to the northwest in the plateau, the latest of which in the southwest of Tibet. The SOG of vegetation in the east of QTP is in advance while it is delayed in the west. (2) the SOG of vegetation has the characteristics of vertical differentiation as well, especially in the range of 3600 to 5000 m, and the delaying rate of the SOG with increasing elevation is 10.7 day / km. (3) The time lag analysis between climatic factors and the vegetation SOG in QTP indicates that the SOG has a time lag of 0 to 15 days behind the air temperature and 15 to 30 days behind precipitation. The SOG of vegetation in southern Tibet and southern Qinghai is more sensitive to air temperature changes than precipitation, whereas the vegetation SOG in southwestern Tibet and southwestern Qinghai is more sensitive to precipitation changes than air temperature changes.

An efficient gene selection method for microarray data based on LASSO and BPSO

BackgroundThe main goal of successful gene selection for microarray data is to find compact and predictive gene subsets which could improve the accuracy. Though a large pool of available methods exists, selecting the optimal gene subset for accurate classification is still very challenging for the diagnosis and treatment of cancer.ResultsTo obtain the most predictive genes subsets without filtering out critical genes, a gene selection method based on least absolute shrinkage and selection operator (LASSO) and an improved binary particle swarm optimization (BPSO) is proposed in this paper. To avoid overfitting of LASSO, the initial gene pool is divided into clusters based on their structure. LASSO is then employed to select high predictive genes and further calculate the contribution value which indicates the genes’ sensitivity to samples’ classes. With the second-level gene pool established by double filter strategy, the BPSO encoding the contribution information obtained from LASSO is improved to perform gene selection. Moreover, from the perspective of the bit change probability, a new mapping function is defined to guide the updating of the particle to select the more predictive genes in the improved BPSO.ConclusionsWith the compact gene pool obtained by double filter strategies, the improved BPSO could select the optimal gene subsets with high probability. The experimental results on several public microarray data with extreme learning machine verify the effectiveness of the proposed method compared to the relevant methods.

Assessing the Correlations between Different Traits in Copper-Sensitive and Copper-Resistant Varieties of Jute (Corchorus capsularis L.).

The current study was conducted to explore the potential for phytoremediation in different varieties of jute grown under toxic concentrations of copper (Cu). For this purpose, a Petri dish experiment was conducted under controlled conditions using four varieties of jute, i.e., HongTieGuXuan, C-3, GuBaChangaJia, and ShangHuoMa, grown in double filter paper under 50 µmol L−1 of artificially spiked copper (Cu) using CuSO4.H2O. The results of the present study revealed that jute varieties C-3 and HongTieGuXuan were able to survive under high concentrations of Cu without a significant decrease in plant height, plant fresh and dry weights, total chlorophyll content, or seed germination, while varieties GuBaChangaJia and ShangHuoMa exhibited a significant reduction in their growth and biomass. Furthermore, high concentrations of Cu in the medium resulted in lipid peroxidation. This could be due to the oxidative damage induced in the roots and leaves of the jute varieties, which might be a result of by hydrogen peroxide (H2O2) and electrolyte leakage. Reactive oxygen species (ROS) generated due to Cu toxicity can be overcome by the increasing activity of antioxidants, and it was also noted that GuBaChangaJia and ShangHuoMa exhibited high Cu stress, while C-3 and HongTieGuXuan showed some resistance to Cu toxicity. Contrastingly, Cu accumulation and uptake was higher in C-3 and HongTieGuXuan, while a little Cu was accumulated in the roots and leaves of GuBaChangaJia and ShangHuoMa. On the basis of these findings, it can be suggested that C-3 and HongTieGuXuan have the potential to cope with Cu stress and can be considered Cu-resistant varieties, while GuBaChangaJia and ShangHuoMa are considered Cu-sensitive varieties. Moreover, C-3 and HongTieGuXuan have the potential to revoke large amounts of Cu, and can be cultivated as phytoremediation tools in Cu-contaminated soil.

Detection and identification of objects on multispectral satellite images

This article considers the detection of objects on the time sequences of satellite multizone images. Optimal and quasi-optimal detection algorithms are built on the basis of a combination of non-linear double stochastic filters and pseudo-gradient procedures. The analysis of behavior of the synthesized algorithms at processing of the real satellite material under conditions of a priori uncertainty concerning parameters of deformation of the reference image is carried out.

VisConnectome: an independent and graph-theory based software for visualizing the human brain connectome

As a complex system, the topology of human's brain network has an important effect on further study of brain's structural and functional mechanism. Graph theory, a kind of sophisticated analytic strategies, is widely used for analyzing complex brain networks effectively and comparing difference of topological structure alteration in normal development and pathological condition. For the purpose of using this analysis methodology efficiently, it is necessary to develop graph-based visualization software. Thus, we developed VisConnectome, which displays analysis results of the brain network friendly and intuitively. It provides an original graphical user interface (GUI) including the tool window, tool bar and innovative double slider filter, brain region bar, runs in any Windows operating system and doesn't rely on any platform such as Matlab. When importing the user-defined script file that initializes the brain network, VisConnectome abstracts the brain network to the ball-and-stick model and render it. VisConnectome allows a series of visual operations, such as identifying nodes and connection, modifying properties of nodes and connection such as color and size with the color palette and size double slider, imaging the brain regions, filtering the brain network according to its size property in a specific domain as simplification and blending with the brain surface as a context of the brain network. Through experiment and analysis, we conclude that VisConnectome is an effective visualization software with high speed and quality, which helps researchers to visualize and compare the structural and functional brain networks flexibly.

A Visual Detection and Location Method for Soft Fabrics

The soft fabric is prone to burr, fold, enfold and blur, which poses a great challenge to the accuracy of visual edge detection and localization of the autonomous loading and unloading material system of garment robot. In order to overcome the above problems, it proposes an adaptive edge localization method based on double filtering in this paper, which can be used to guide the garment robot to achieve grasping of soft fabric automatically. Firstly, the Gauss filtering and morphological filtering are used to smooth the image, and then it calculates the canny adaptive threshold based on the edge gradient information and detect the edge, finally it locates the coordinates of edge feature extracted. The experiment results show that the method is effective accuracy greater than 96%and robust tested on the real data sets composed of soft fabric. The method has good application value for the autonomous loading and unloading operation of the garment robot and has positive significance for the construction of the intelligent garment factory.

Research on harmonic suppression ability of active power filter

The system control model of double resonance injection hybrid active power filter (DIHAPF) and mathematical model of voltage source inverter with controller was established based on the structure and operating principle of DIHAPF. The injection branch features were analyzed including the static reactive power compensation capability and dividing capability of harmonic voltages. Stability and harmonic suppression capacity of DIHAPF was analyzed simultaneously. The influence of the parallel resonant circuit resonant frequency to system performance was discussed in detail. Furthermore, the method of designing the resonant frequency of parallel resonant circuit was proposed. The simulation model of DIHAPF was established and simulated on PSIM 6.0 taking nonlinear loads as harmonic current sources. A 6kV DIHAPF experiment prototype controlled by TMS320F28335 was built. Simulation and experimental results prove the validity of the analysis in this paper.

State of charge estimation for lithium-ion batteries based on adaptive dual Kalman filter

Accurate estimation of the battery state of charge (SOC) is of great significance for enhancing its service life and safety. In this study, based on the fractional-order equivalent circuit model of lithium-ion battery, the SOC estimation methods using dual Kalman filter (DKF) and dual extended Kalman filter (DEKF) are simulated and compared, in terms of model accuracy and SOC estimation accuracy. Then, combining the advantages of the DKF and DEKF algorithms, an SOC estimation algorithm based on adaptive double Kalman filter is proposed. This algorithm uses the recursive least squares (RLS) method to update the battery model parameters online in real time, and employs the DKF algorithm to filter the SOC twice to reduce the interferences from the battery model error and the current measurement error. In the experimental studies, the measured SOC values are compared with the estimated SOC values produced by the proposed algorithm. The comparison results show that SOC estimation error of the proposed algorithm is within the range of ±0.01 under most test conditions, and it can automatically correct SOC to true value in the presence of system errors. Thus, the validity, accuracy, robustness and adaptability of the proposed algorithm under different operation conditions are verified.

Triple Notches Bandstop Microstrip Filter Based on Archimedean Spiral Electromagnetic Bandgap Structure

With the development of artificial electromagnetic structures, defective grounding structures (DGS), defective microstrip structures (DMS), and electromagnetic bandgap (EBG) have been widely used in the design of microstrip filters. In this paper, a triple notches ultra wideband bandstop microstrip filter based on Archimedean spiral electromagnetic bandgap structure (ASEBG) structure is proposed. Firstly, the equivalent circuit of ASEBG is analyzed, and L and C values are extracted by using Advanced Design System (ADS). Secondly, the correctness of the lumped parameter model is verified by comparing the High Frequency Structure Simulator (HFSS) simulation results with the measured results. Finally, the influence of ASEBG structure parameters on resonant performance is analyzed by HFSS simulation, and the filter parameters are further optimized. By coupling ASEBG structure to existing double notch microstrip filters, a triple notches ultra wideband bandstop microstrip filter is realized. This method can also be used in the design of other microstrip devices with stopband characteristics. The three bandgap center frequencies of the proposed triple notches ultra wideband bandstop microstrip filter are 3.5, 5.2, and 7.4 GHz, respectively. The corresponding maximum attenuation of the three stopbands is 33.6, 24.8, and 21.7 dB, respectively.

New NOAH modules for structure elucidation at natural isotopic abundance.

We introduce several new NOAH modules designed for NMR supersequences that allow structure elucidation of small organic molecules from a single measurement. We show that double isotope filters (ZZ-filters) increase the flexibility of module permutation within the NMR supersequences, optimising combinations exploiting 15N and 13C nuclides. The time-shared 2BOB module combined with the ZZ-HMBC module (yielding NOAH-2 BO) provides an example of extending the NMR supersequences with parallel experiments (here 2BOB) that are incompatible with sequential implementation. Finally, the PANSY-COSY module combined with the HSQC sequence (yielding NOAH-2 SC2) provides an example of incorporating multiple receiver experiments into NMR supersequences opening new avenues for designing information rich NMR experiments. The new NOAH supersequences were utilized in computer assisted structure elucidation (CASE) study accomplished using the CMCse software.

Double Bayesian Smoothing as Message Passing

Recently, a novel method for developing filtering algorithms, based on the interconnection of two Bayesian filters and called double Bayesian filtering, has been proposed. In this manuscript we show that the same conceptual approach can be exploited to devise a new smoothing method, called double Bayesian smoothing. A double Bayesian smoother combines a double Bayesian filter, employed in its forward pass, with the interconnection of two backward information filters used in its backward pass. As a specific application of our general method, a detailed derivation of double Bayesian smoothing algorithms for conditionally linear Gaussian systems is illustrated. Numerical results for two specific dynamic systems evidence that these algorithms can achieve a better complexity-accuracy tradeoff and tracking capability than other smoothing techniques recently appeared in the literature.

Quantitative Isotopomer Rates in Real-Time Metabolism of Cells Determined by NMR Methods.

Tracer-based metabolism is becoming increasingly important for studying metabolic mechanisms in cells. NMR spectroscopy offers several approaches to measure label incorporation in metabolites, including 13 C- and 1 H-detected spectra. The latter are generally more sensitive, but quantification depends on the proton-carbon 1 JCH coupling constant, which varies significantly between different metabolites. It is therefore not possible to have one experiment optimised for all metabolites, and quantification of 1 H-edited spectra such as HSQCs requires precise knowledge of coupling constants. Increasing interest in tracer-based and metabolic flux analysis requires robust analyses with reasonably small acquisition times. Herein, we compare 13 C-filtered and 13 C-edited methods for quantification and show the applicability of the methods for real-time NMR spectroscopy of cancer-cell metabolism, in which label incorporations are subject to constant flux. We find an approach using a double filter to be most suitable and sufficiently robust to reliably obtain 13 C incorporations from difference spectra. This is demonstrated for JJN3 multiple myeloma cells processing glucose over 24 h. The proposed method is equally well suited for calculating the level of label incorporation in labelled cell extracts in the context of metabolic flux analysis.

Double filter instrumental variable estimation of panel data models with weakly exogenous variables

In this article, we propose instrumental variables (IV) and generalized method of moments (GMM) estimators for panel data models with weakly exogenous variables. The model is allowed to include heterogeneous time trends besides the standard fixed effects (FE). The proposed IV and GMM estimators are obtained by applying a forward filter to the model and a backward filter to the instruments in order to remove FE, thereby called the double filter IV and GMM estimators. We derive the asymptotic properties of the proposed estimators under fixed T and large N, and large T and large N asymptotics where N and T denote the dimensions of cross section and time series, respectively. It is shown that the proposed IV estimator has the same asymptotic distribution as the bias corrected FE estimator when both N and T are large. Monte Carlo simulation results reveal that the proposed estimator performs well in finite samples and outperforms the conventional IV/GMM estimators using instruments in levels in many cases.

Application of Landsat 8 Satellite Image – NDVI Time Series for Crop Phenology Mapping: Case Study Balkh and Jawzjan Regions of Afghanistan

In this article, it was targeted to reveal the variations of NDVI which may represent the phenological stages of agricultural crops derived from Landsat 8 imagery from the start to end of growing seasons which eventually influence the final yields. An effective method was developed to map seasonal phenological variations of crops over large geographic regions using 16-day Landsat 30 m resolution NDVI time series data obtained from USGS. The Google Earth Engine (GEE) platform was used for processing the Landsat 8 data. The areas with cloud cover and cloud shadows were masked out, filled by no data and smoothing double logistic filter was fitted on the time series of the reflectance values. Phenological metrics extracted from the NDVI time series were obtained by the TIMESAT software. Seasonal data were extracted for growing seasons of the years of 2015 and 2016. The phenology maps were created for study area.