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Lamina cribrosa morphology is ever changing in health and disease, and its changes might cause primary optic nerve damage and secondary damage due to the decrease of blood supply and axoplasmic transport. There is no information in literature about the peculiarities of lamina cribrosa thickness in patients with diabetic optic neuropathy (DON) in vivo.The objective was to study the morphometric changes of the lamina cribrosa and changes of its scleral canal in patients with diabetes mellitus (DM) depending on the type and stage of the diabetic optic neuropathy, and to establish the clinicopathogenetic role of lamina cribrosa morphometric changes in the development of DON.Materials and methods. 575 patients (1150 eyes) with type II DM were examined. In addition to standard ophthalmologic methods optical coherent tomography (OCT) of the retina and optic nerve was performed. Lamina cribrosa thickness was measured with the help of SD OCT using LC_Thickness_programm.m and main_low_ noise_fi lters_programm.m, based on the adaptive compensation algorithm for eliminating a high-level noise in the deep layers of the optic nerve and improving the visualization of the posterior border of the lamina cribrosa, as well as for processing B-scan with a set of 3 digital fi lters: Butterworth Low-pass Filter inverion image, Wavelet Low-pass Filter Analysis Daubechies original and inversion image. The area of lamina cribrosa scleral canal was measured with the help of SD OCT using the LC_cut_position_programm.m for choosing the depth of measurement and LC_diameter_calculation_programm.m for improvement of the selected image by the main digital fi lters.Results. Analyzing the results of examination, the correlation between the type and stage of DON and scleral lamina cribrosa thickness in patients with DM was revealed. An average index of lamina cribrosa thickness in patients with DM without diabetic optic neuropathy was 1.4 times higher than that of the control group; in subclinical stage of axial DON – 1.9 times higher, in initial stage – 2.1 times higher, in severe stage of axial DON and diabetic papillopathy – 2.6 times higher, in anterior ischemic DON – 2.7 times higher, in dystrophic stage – 3.1 times higher than that of the control group (303±56 μm) (р

HighlightsThe OPC-N3, developed by Alphasense, may be useful in measuring occupational exposure in agricultural settings based on the agreement with mass concentrations measured by gravimetrical filter analysis.The AirBeam2 is better suited for environmental exposure measurements rather than occupational measurements.Particle sizing by the GRIMM Mini-WRAS 1371 and the OPC-N3 show many aerosols that agricultural workers are exposed to follow a bimodal curve and are above 0.1 µm, thereby the respirator used as personal protective equipment is effective in filtering out aerosols in this occupation.Abstract. Prolonged exposure to dust has been shown to have adverse health effects in agricultural workers, primarily with the development of respiratory diseases. Low-cost sensors may be cost-effective tools for farmers to determine when they are exposed to harmful levels of dust during their workday. The purpose of this study was to identify low-cost sensors that may be reliably used in occupational settings to help workers and employers identify respirable particle matter exposure. The study utilized two different low-cost optical particle counters (OPCs) to collect data on dust exposure, which were worn on a belt by the participant: the OPC-N3 developed by Alphasense and the AirBeam2 developed by HabitatMap. Additionally, an AirChek TOUCH air sampling pump fit with a respirable dust aluminum cyclone allowed for the collection of respirable particulate matter (PM4) to determine the true concentration of exposure. Results show that the PM4 measurements made by the OPC-N3 are similar to the gravimetrical filter measurement at concentrations of < 50 µg/m3. In addition, the data analysis suggests that the AirBeam2 may be significantly underestimating the amount of particulate matter that farmworkers are exposed to and therefore may not be suitable for occupational exposure measurements compared to the OPC-N3. Keywords: Aerosols, Agriculture, AirBeam2, Dust, Exposure, Low-cost, Occupational, Optical particle counter, OPC-N3.

Numerous contexts in macroeconomics, finance, and quality control require real-time estimation of trends, turning points, and anomalies. The real-time signal extraction problem is formulated as a multivariate linear prediction problem, the optimal solution is presented in terms of a known model, and multivariate direct filter analysis is proposed to address the more typical situation where the process’ model is unknown. It is shown how general constraints – such as level and time shift constraints – can be imposed on a concurrent filter in order to guarantee that real-time estimates have requisite properties. The methodology is applied to petroleum and construction data.

The problem of standing out a signal from an additive mixture of a harmonic signal and white Gaussian noise is considered. The analysis is based on the phenomenon of stochastic resonance (SR), which consists in amplifying a periodic signal under the influence of noise of a certain power. SR is a universal physical phenomenon that is typical of some nonlinear systems, and is came out not only in technical, but also in biological and social systems. When calculating the spectral characteristics of the output signal, Volterra series were used. The problem is solved using the transfer functions of Volterra without the initial definition of kernels. Volterra transfer functions are obtained by the harmonic input signal method. The influence of the input signal parameters, in particular the amplitude and frequency of the harmonic signal and the noise power, on the spectral power density of the output signal is studied. Optimal parameters values are determined. Criteria are formulated for using a stochastic filter to standing out a harmonic signal on the background white Gaussian noise.

Particle exposure has been linked to an increased incidence of cardiovascular disease. Furthermore, particle exposure has been shown to have a chronic inhibitory effect on lung development in young people and may result in increased respiratory problems in adults or children with respiratory-related diseases. In today’s urban environments, particle levels are mainly monitored gravimetrically; however, other factors such as particle size, shape and surface reactivity have recently been noted as highly important in relation to possible health outcomes. Here, particles from TEOM monitor filters placed in three different cities were studied. The purpose of the study was to investigate whether there are variations in particle masses, cadmium and lead contents, as well as endotoxin levels between locations and time points over the year and if this can be correlated to the particles ability to induce a pro-inflammatory response in vitro. Results showed that it is possible to detect variations at different locations and at different time points over the year and that cadmium, lead and endotoxin levels did not coincide with the increased total particle masses while endotoxin levels coincided with pro-inflammatory responses in vitro. The present study shows that filter analysis is a useful complement to gravimetric or particle-counting measurements in studies of particle-related health effects and will give useful information regarding future air quality measurements.

Assessment methods on data quality and environmental variability are lacking for microplastics (MP). Here we assess occurrence and variability of MP number concentrations in two Dutch rivers. Strict QA/QC procedures were applied to identify MP using Fourier-transform infrared (FTIR) microscopy followed by state of the art automated image analysis. For a series of randomly selected, yet ever smaller subareas of filters, we assessed how accurately MP numbers and polymer types are represented during partial filter analysis. Levels of uncertainty were acceptable when analysing 50% of a filter during chemical mapping, and when identifying at least a subset of 50 individual particles with attenuated total reflection (ATR)-FTIR. Applying these guidelines, MP number concentrations between 67 and 11532 MP m−3 were detected in Dutch riverine surface waters. Spatial differences caused MP number concentrations to vary by two orders of magnitude. Temporal differences were lower and induced a maximum variation of one order of magnitude. In total, 26 polymer types were identified, the most common were polyethylene (23%), polypropylene (19.7%) and ethylene propylene diene monomer rubber (18.3%). The highest diversity of polymer types was found for small MPs, whereas MP larger than 1 mm was scarce and almost exclusively made of polyethylene or polypropylene. Virtually all sampling locations revealed MP number concentrations that are considerably below known effect thresholds for anticipated adverse ecological effects.

Precipitation is highly variable in space and discontinuous in time, which makes it challenging for models to predict on subseasonal scales (10–30 days). We analyze multi-pentad predictions from the Beijing Climate Center Climate System Model version 1.2 (BCC_CSM1.2), which are based on hindcasts from 1997 to 2014. The analysis focus on the skill of the model to predict precipitation variability over Southeast Asia from May to September, as well as its connections with intraseasonal oscillation (ISO). The effective precipitation prediction length is about two pentads (10 days), during which the skill measured by anomaly correlation is greater than 0.1. In order to further evaluate the performance of the precipitation prediction, the diagnosis results of the skills of two related circulation fields show that the prediction skills for the circulation fields exceed that of precipitation. Moreover, the prediction skills tend to be higher when the amplitude of ISO is large, especially for a boreal summer intraseasonal oscillation. The skills associated with phases 2 and 5 are higher, but that of phase 3 is relatively lower. Even so, different initial phases reflect the same spatial characteristics, which shows higher skill of precipitation prediction in the northwest Pacific Ocean. Finally, filter analysis is used on the prediction skills of total and subseasonal anomalies. The results of the two anomaly sets are comparable during the first two lead pentads, but thereafter the skill of the total anomalies is significantly higher than that of the subseasonal anomalies. This paper should help advance research in subseasonal precipitation prediction.

The Mahu Depression is an important hydrocarbon-bearing foreland sag located at the northwestern margin of the Junggar Basin, China. On the northern slope of the depression, large coarse-grained proximal fan-delta depositional systems developed in the Lower Triassic Baikouquan Formation (T1b). Some lithologic hydrocarbon reservoirs have been found in the conglomerates of the formation since recent years. However, the rapid vertical and horizontal lithology variations make it is difficult to divide the base-level cycle of the formation using the conventional methods. Spectral analysis technologies, such as Integrated Prediction Error Filter Analysis (INPEFA), provide another effective way to overcome this difficultly. In this paper, processed by INPEFA, conventional resistivity logs are utilized to study the base-level cycle of the fan-delta depositional systems. The negative trend of the INPEFA curve indicates the base-level fall semi-cycles, adversely, positive trend suggests the rise semi-cycles. Base-level cycles of Baikouquan Formation are divided in single and correlation wells. One long-term base-level rise semi-cycle, including three medium-term base-level cycles, is identified overall the Baikouquan Formation. The medium-term base-level cycles are characterized as rise semi-cycles mainly in the fan-delta plain, symmetric cycles in the fan-delta front and fall semi-cycles mainly in the pro-fan-delta. The short-term base-level rise semi-cycles most developed in the braided channels, sub-aqueous distributary channels and sheet sands. While, the interdistributary bays and pro-fan-delta mud indicate short-term base-level fall semi-cycles. Finally, based on the method of INPEFA, sequence filling model of Baikouquan formation is established.

This study aims to determine the root of problem and alternative solutions of inaccuracy return medical record inpatient files. The research was conducted through qualitative descriptive approach in RSUD Blambangan from September until October 2017. Data was collected by document review, field observation and unstructured interview with Head of Services, Head of Nursing Services, 1 doctor, 2 head of ward, Head of Medical Record Installation, Head of Nutrition Installation and Head of Pharmacy Installation. Root of problem was analyzed with fishbone diagram, focus group discussion (FGD) method and urgency, seriousness, growth (USG) method. Priority determination solution is carried out using filter analysis method with CARL (Capability Accessibility Readiness Leverage). The results show that factor inaccuracy return inpatient medical records file because are incomplete of medical record file, absence of standard opera t i ng procedure and unavailability of monitoring and evaluation, and the increasing number of medical record form according to hospital quality standard. The root problem is not optimally main task and function of professional care giver when filling medical record. Alternative proposed solutions is socialization to professional care giver, revised standard of operational procedure, and monitoring evaluation of the completeness and timeliness of medical record file returns with innovation "ABED TANGI" .

Eleven years (by publication) years after the development and application of the control banding (CB) Nanotool for the qualitative assessment and control of engineered nanoparticles (ENP), there remains no quantitative gold standard to serve as an alternative to the qualitative assessment. Many CB models have been developed during the years subsequent to the initial development of the CB Nanotool and the literature continues to blossom with comparisons and applications of these various tools; however, these developments have hitherto been made in the absence of validating and verifying their effectiveness using existing, albeit limited, quantitative methods. This paper reviews the existing literature on the CB Nanotool to evaluate its effectiveness in a variety of settings and presents a summary of qualitative and quantitative information from its application in a broad range of ENP handling activities performed in two different research institutions. A total of 28 ENP activities were assessed using the CB Nanotool (Version 2.0). Due to the lack of guidance on a single exposure assessment methodology, a combination of real-time monitoring, filter analysis, and microscopic analysis was used to assess various quantitative metrics, including mass concentration, particle number concentration, and particle speciation. All the results indicated that the control outcomes from the CB Nanotool qualitative assessment were sufficient to prevent workers from being exposed to ENP at levels beyond established exposure limits or background levels. These data represent an independent quantitative validation of CB Nanotool risk level outcomes and give further credence to the use of the CB Nanotool to effectively control worker exposures in the absence of quantitative air monitoring results.

Introduction/purpose To refine the development of novel endovascular devices and materials, innovative experimental testing methods can assess blood flow effects, material fatigue, downstream migration, and particulation. Specifically, in vivo animal models are not ideal for assessment of downstream particulation. This study describes the development of an in vitro neurovascular model to quantify particulation risks from endovascular devices. Materials and methods A flow loop simulates neurovascular blood flow and pressures. The model is controlled by a pump and a temperature-controlled (TC) fluid reservoir (to maintain 37°C). A LabVIEW monitoring system records and displays real-time data from pressure transducers, flow meters, and thermocouples connected to the flow loop. The pump delivers 250 ml/min (tunable to physiological conditions) and generates a mean pressure of 100 mmHg to the attached vessel phantoms. Distal to the phantoms are in-line filters to capture particles above 5.0 µm (figure 1). After a simulated endovascular procedure, filters are removed for analysis. The model can characterize the short- and long-term performance of devices delivered to vessel defects, such as aneurysms. Results The device tested was a liquid embolic (PPODA-QT). Microcatheters were placed into the aneurysm phantom using endovascular surgical techniques. Fluoroscopic imaging monitored the PPODA-QT delivery. Particle assessment was conducted by filter analysis (optical and electron microscopy) and liquid sample analysis (in-line interference holography) of downstream particle size and quantity and compared to the release specification for injectable fluids (USP – table 1). Conclusions Development of novel devices for neurovascular treatments requires robust modeling to ensure both short-and long-term effectiveness without downstream migration. This venture is a synergistic collaboration between the bioengineering and neurointerventional fields, and this study is ultimately important for providing physicians with a better understanding of non-thrombus downstream effects from neurovascular devices and materials. Disclosures T. Cotter: 1; C; National Institutes of Health. 4; C; Aneuvas Technologies, Inc. 5; C; Aneuvas Technologies, Inc, Barrow Neurological Institute, Northern Arizona University. K. LoGrande: None. M. Almutairi: None. S. Aldhufairi: None. C. Settanni: None. C. Gonzalez: 1; C; National Institutes of Health. 4; C; Aneuvas Technologies, Inc. 5; C; Aneuvas Technologies, Inc, Barrow Neurological Institute. A. Ducruet: 1; C; National Institutes of Health. 4; C; Aneuvas Technologies, Inc. 5; C; Aneuvas Technologies, Inc, Barrow Neurological Institute. T. Becker: 1; C; National Institutes of Health. 4; C; Aneuvas Technologies, Inc. 5; C; Aneuvas Technologies, Inc, Barrow Neurological Institute, Northern Arizona University.

Bushen-Yizhi prescription (BSYZ) has been an effective traditional Chinese medicine (TCM) prescription in treating Alzheimer’s disease (AD) for hundreds of years. However, the underlying mechanisms have not been fully elucidated yet. In this work, a systems pharmacology approach was developed to reveal the underlying molecular mechanisms of BSYZ in treating AD. First, we obtained 329 candidate compounds of BSYZ by in silico ADME/T filter analysis and 138 AD-related targets were predicted by our in-house WEGA algorithm via mapping predicted targets into AD-related proteins. In addition, we elucidated the mechanisms of BSYZ action on AD through multiple network analysis, including compound-target network analysis and target-function network analysis. Furthermore, several modules regulated by BSYZ were incorporated into AD-related pathways to uncover the therapeutic mechanisms of this prescription in AD treatment. Finally, further verification experiments also demonstrated the therapeutic effects of BSYZ on cognitive dysfunction in APP/PS1 mice, which was possibly via regulating amyloid-β metabolism and suppressing neuronal apoptosis. In conclusion, we provide an integrative systems pharmacology approach to illustrate the underlying therapeutic mechanisms of BSYZ formula action on AD.

L'analyse à filtre partiel est une méthode utilisée pour évaluer l'exposition des tissus buccaux (mouth level exposure, MLE) des fumeurs de cigarettes aux constituants de la fumée principale. Nous avons évalué la capacité de l'analyse à filtre partiel à effectuer une comparaison de l'exposition des tissus buccaux à la nicotine et au goudron chez des populations de fumeurs et lors d'un étalonnage. A trois reprises, trois groupes de sujets ont fumé deux lots de la même marque de cigarettes hongroises avec un rendement en goudron de 1-mg ISO. Dix-huit courbes d'étalonnage furent tracées par trois opérateurs utilisant trois machines à fumer. Pour chaque lot de cigarettes, aucune différence significative de l'exposition des tissus buccaux ne fut observée ni parmi les trois groupes de fumeurs ni après répétition de la consommation au sein des groupes. L'exposition des tissus buccaux lors de la consommation du premier lot de cigarettes fut marginalement supérieure à l'exposition observée pour le deuxième lot. Aucune différence significative ne fut observée entre les pentes et les points d'intersection des courbes d'étalonnage produites à l'aide des différentes machines à fumer par les différents opérateurs. L'analyse à filtre partiel propose une approche reproductible permettant d'estimer l'exposition des tissus buccaux des fumeurs à la nicotine et au goudron dans le cadre d'études à grande échelle dans des environnements normaux de tabagisme.

This paper studies theH-index problem. We obtain a necessary and sufficient condition ofH-index larger thanγ>0. A generalized differential equation is introduced and it is proved that its solvability and the feasibility of theH-index are equivalent. We extend the deterministic cases to the stochastic models. Our results can be used to fault detection filter analysis. Finally, the effectiveness of the proposed results is illustrated by an example.

The project aim was to identify differences in the metabolomic profiles in the serum of patients with multiple sclerosis (MS), those with neuropathic pain (NP) and those with both MS and NP compared with controls and to identify potential biomarkers of each disease state. Metabolomic profiling was performed using ultra-high-performance liquid chromatography coupled to mass spectrometry and the data analysis involved parametric methods, principal component analysis, and discriminating filter analysis to determine the differences between disease and control serum samples. Sphingosine and dihydrosphingosine were identified as significant biomarkers.

Marine aerosols, that are very common in the highly populated coastal cities and communities, may contain biological constituents. Some of this biological fraction of marine aerosols, such as cyanobacteria and plankton debris, may influence human health by inflammation and allergic reactions when inhaled. In this study we identify and compare sources for endotoxins sampled on filters in an on-shore and more-inland site. Filter analysis included endotoxin content, total bacteria, gram-negative bacteria and cyanobacteria genome concentrations as well as ion content in order to identify possible sources for the endotoxins. Satellite images of chlorophyll-a levels and back trajectory analysis were used to further study the cyanobacteria blooms in the sea, close to the trajectory of the sampled air. The highest endotoxin concentrations found in the shoreline site were during winter (3.23±0.17 EU/m(3)), together with the highest cyanobacteria genome (1065.5 genome/m(3)). The elevated endotoxin concentrations were significantly correlated with cyanobacterial levels scaled to the presence of marine aerosol (r=0.90), as well as to chlorophyll-a (r=0.96). Filters sampled further inland showed lower and non-significant correlation between endotoxin and cyanobacteria (r=0.70, P value=0.19), suggesting decrease in marine-originated endotoxin, with possible contributions from other sources of gram-negative non-cyanobacteria. We conclude that marine cyanobacteria may be a dominant contributor to elevated endotoxin levels in coastal areas.

In a variational data assimilation system, background error statistics (BES) spread the influence of the observations in space and filter analysis increments through dynamic balance or statistical relationships. In a data-sparse region such as the Bay of Bengal, BES play an important role in defining the location and structure of monsoon depressions (MDs). In this study, the Indian-region-specific BES have been computed for the Weather Research and Forecasting (WRF) three-dimensional variational data assimilation system. A comparative study using single observation tests is carried out using the computed BES and global BES within the WRF system. Both sets of BES are used in the assimilation cycles and forecast runs for simulating the meteorological features associated with the MDs. Numerical experiments have been conducted to assess the relative impact of various BES in the analysis and simulations of the MDs. The results show that use of regional BES in the assimilation cycle has a positive impact on the prediction of the location, propagation, and development of rainbands associated with the MDs. The track errors of MDs are smaller when domain-specific BES are used in the assimilation cycle. Additional experiments have been conducted using data from the Interim European Centre for Medium-Range Weather Forecasts Re-Analysis (ERA-Interim) as initial and boundary conditions (IBCs) in the assimilation cycle. The results indicate that the use of domain-dependent BES and high-resolution ERA-I data as IBCs further improved the initial conditions for the model leading to better forecasts of the MDs.

Summary A day-ahead dispatch strategy for the integrated system of wind/photovoltaic/pumped-storage/gas-turbine-power/energy storage is proposed based on the multi-frequency scale power of wind/photovoltaic (PWP). First, filter analysis of the PWP is carried out according to the control target of the system to get the components of PWP under different frequency scales; thus, the power output of different compensatory plants can be scheduled. Second, an improved particle swarm optimization algorithm is utilized to parallel optimize costs of different plants and calculate the overall power output of the integrated system. Finally, based on different dispatch modes, considering system stability and the penetration ability of wind/photovoltaic, the per-unit generation cost of the integrated system is optimized and the power output is scheduled. Simulation results show that, compared with traditional optimization models and algorithms, the proposed strategy is capable of smoothing the power fluctuation caused by large-scale wind/photovoltaic integration, as well as realizing economical, efficient and environmentally friendly operation of the system. Copyright © 2014 John Wiley & Sons, Ltd.

Interest in atmospheric aerosol issues has been increasing worldwide. X-ray fluorescence (XRF) is an important atmospheric aerosol monitoring tool for inorganic component analysis, because XRF is a rapid and easy analysis method. In particular, Energy dispersive X-ray fluorescence (EDXRF) has drawn attention for aerosol analysis. However, EDXRF has difficulties that: (1) many overlapping peaks exist for aerosol filter analysis and (2) many thin-film standard samples are required when an empirical calibration method is employed. Accurate analysis method of aerosol filter samples without the need for large sets of standards by semi-quantitative analysis software RPF–SQX (Rigaku profile fitting–spectra quant X), which includes the exact profile fitting and thin-film fundamental parameter (FP) method, is described using the EDXRF spectrometer equipped with secondary targets and polarized optics.

This paper is concerned with the problem of robust finite frequency (FF) H"~ filtering for uncertain two-dimensional (2-D) discrete-time systems in the Fornasini-Marchesini local state-space (FM LSS) model with polytopic uncertain parameters. The goal of the paper is to design filters such that the FF H"~ norm of the filtering error system has a specified upper bound for all uncertainties. In light of a recently developed generalized bounded real lemma, a linear matrix inequality-based approach is proposed for robust FF H"~ filter analysis and design. It is demonstrated that the presented approach to robust FF H"~ filter design covers the latest standard H"~ filtering result. Moreover, it is shown that the existing results specialized for the Roesser model, when applied to the FM LSS model through a model transformation, are much more restrictive than the proposed results in the paper, further justifying this work.

This paper describes the first part of a project conducted to evaluate the trace element composition of atmospheric aerosol particles (PM2.5) and to determine their influence on air quality in Taif city, Saudi Arabia. PM2.5 particles were collected from two different sites (industrial and residential) in Taif during the summer of 2011. The industrial site was situated in the largest industrial area of Taif, and the residential site was situated in the city’s most crowded area. PM2.5 samples were collected on polycarbonate filters using a cyclonic collector. Each sample was collected over a 24 hour period and new samples were collected weekly. Average PM2.5 concentrations of 47 ± 15 and 46 ± 31 µg/m 3 were seen in the industrial and residential areas, respectively. An Energy Dispersive X-ray Fluorescence (EDXRF) spectrometer with a Mo secondary target was used to analyze the solid samples because of the relative simplicity of the technique for filter analysis. The use of a Mo secondary target is advantageous, because it decreases the impact of continuum radiation from the X-ray tube and increases the signal to background ratio. Quantitative X-ray Analysis Software (PyMca) was used to perform quantitative analysis of the atmospheric aerosols. The analysis resulted in detected concentrations for sixteen elements; Si, S, Cl, K, Ca, Ti, Cr, Mn, Fe, Ni, Cu, Zn, Rb, Sr, Pb and Black Carbon (BC). Using Principal Component Analysis (PCA) it was possible to distinguish between natural and anthropogenic sources. The measured concentrations of the potentially hazardous trace elements Cu, Cr, Mn, Ni and Pb were below the limits defined by international guidelines and national standards for ambient air quality. However, further long-term research will be required to validate the quantification of trace elements in particulate matter in Taif.

This paper is concerned with the H"~ filtering problem for a class of nonlinear stochastic systems subject to sensor saturation over unreliable communication channel. The investigated plant is described by a class of stochastic systems with global Lipschitz nonlinearities and random noise depending on state and external-disturbance. The characteristic of sensor saturation is handled by a decomposition approach which is more general than those in the existing work where the sensor saturation and network-induced phenomenon were considered separately. The communication links between the plant and filter are unreliable network channels, and the effects of output logarithmic quantization and data packet losses are considered together. The purpose of this work is to design a full-order filter by employing the incomplete output measurements such that the dynamics of the estimation error is guaranteed to be stochastically stable. Both filter analysis and synthesis problems are investigated, and the explicit expression of the desired filters is also provided. Finally, a numerical simulation is illustrated to show the effectiveness of the designing filtering technique.

A novel compact bandstop filter (BSF) using vertical coupled striplines is presented. Stopband rejection depth and bandwidth can be easily controlled by the coupling factor of the coupled-line section. A lossless transmission line model analysis is used for filter analysis. To validate the proposed topology, a multilayer BSF centered at 5.8 GHz with bandwidth of 75% is designed and built. Good agreement between measured and simulated results is obtained. With the assistance of vertical coupling structure and LTCC technology, the filter occupies an area of only 4.7 mm × 3.8 mm. © 2012 Wiley Periodicals, Inc. Microwave Opt Technol Lett 54:1173–1176, 2012; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.26787

A clinical study conducted in Canada compared two methods of estimating exposure to cigarette smoke in 192 volunteer subjects: 43 smokers of 4–6mg, 49 of 8–12mg and 50 of 14–15mg ISO tar yield cigarettes and 50 non-smokers. Estimates of mouth level exposure (MLE) to nicotine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), pyrene and acrolein were obtained by chemical analysis of spent cigarette filters. Estimates of smoke constituent uptake were achieved by analysis of urinary biomarkers for total nicotine equivalents (nicotine, cotinine, trans–3′-hydroxycotinine plus their glucuronide conjugates), NNK (total 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) plus glucuronide), pyrene (1-hydroxy pyrene plus glucuronide) and acrolein (3-hydroxylpropyl-mercapturic acid) plus the nicotine metabolite cotinine in plasma and saliva. The objective of our study was to confirm the correlations between measures of human exposure obtained by filter analysis and biomarkers. Significant correlations (p

Smoke yields determined by a machine-based smoking method cannot adequately predict exposures experienced by human smokers. In this work, a filter analysis technique which addresses this fundamental limitation was used to measure mouth level exposures (MLE) to tar and nicotine in 1330 smokers of 26 brand-styles of US cigarettes covering a wide range of machine-generated yields.Despite the high degree of variability observed among individual smokers, MLEs were significantly correlated with machine-derived tar and nicotine yields (r=0.423 for nicotine MLE/cigarette; r=0.493 for tar MLE/cigarette; p

In 2005, Human-Smoked (HS) tar and nicotine yields from commercial Canadian cigarettes were determined using a part filter analysis method to obtain estimates representative of human smoking behavior. In 2006, new cigarette designs were introduced to ensure compliance with the Canadian Low Ignition Propensity (LIP) regulations. It was not known how the changes in product design would affect HS yields. To assess the impact of the cigarette design modifications on HS yields, a further group of Canadian smokers was recruited for smoking the modified version of 10 products previously assessed. No differences in estimated HS tar yields were found between products following product modification. The HS nicotine yield was different for one product. In general, HS yields were higher than ISO machine yields while Canadian intense machine yields were more representative of the maximum HS yields. The same product ranking order was obtained for HS yields and the two machine yields but differences between the mean HS yields and ISO yields were smaller as the product ISO yields increased. Higher HS yields were measured when products were smoked by male smokers. The methodology used in this study showed the wide range of HS yields obtained by smokers as well as a good degree of stability in average HS yields just before and after the introduction of LIP regulations.

A forced switch to a lower ISO tar yield cigarette was used in a clinical study, conducted in Germany, that compared two methods of estimating exposure to cigarette smoke. Pre- and post-switch estimates of Mouth Level Exposure (MLE) to nicotine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), pyrene and acrolein were obtained by chemical analysis of spent cigarette filters for nicotine content. Similarly, pre- and post-switch estimates of uptake of these smoke constituents were achieved by analysis of corresponding urinary biomarkers of exposure (BoE): total nicotine equivalents; total 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL); total 1-hydroxypyrene (1-OHP), and 3-hydroxypropyl-mercapturic acid (3-HPMA), plus the nicotine metabolite cotinine, in plasma and saliva. Three hundred healthy volunteers were recruited comprising 100 smokers of each of 9–10 and 4–6 mg ISO tar yield cigarettes and 50 smokers of 1–2 mg ISO tar yield cigarettes and 50 non-smokers. Fifty smokers of each of the 9–10 and 4–6 mg ISO tar yield cigarettes took part in the switching aspects of this study whilst the remaining smokers formed non-switching control groups who smoked their usual ISO tar yield cigarette throughout the study. After 5 days, all subjects were admitted into a clinic where baseline measures of MLE and BoE were obtained. The 10 mg switching group was then switched to the 4 mg ISO tar yield cigarette and the 4 mg ISO tar yield switching group switched to the 1 mg cigarette. Subjects returned home for 12 days, continuing to smoke the supplied cigarettes before being readmitted into the clinic where samples were collected for MLE and BoE analysis. Changes in daily exposure estimates were determined on a group and individual basis for both methods. The pre- to post-switch directional changes in MLEs and their corresponding BoEs were generally consistent and the MLE/BoE relationship maintained. Switching to a lower yield cigarette generally resulted in reductions in exposure with the resultant exposure level being similar to that seen in regular smokers of the lower yield cigarette.

This article systematically studies investment regulation policies adopted after 1994 to prevent overcapacity in the Chinese iron and steel industry. Theoretical analysis shows that these policies have three major limitations: they cannot fundamentally govern overcapacity; they cannot be used by policymakers to make accurate predictions or formulate acceptable investment plans; they may disturb the market process and lead to negative policy results. Reviews of policy predictions show that there has always been a large difference between iron and steel industry policy forecasts and plans for investment regulation and market realities. A Hodrick-Prescott filter analysis of the effects of these policies on fixed-asset investment in the industry further reveals that the policies obstruct self-adjustment of fixed-asset investment in the market, leading to negative policy results. Policies of these types should be adopted with great caution.

Objective Determine human smoked (HS) cigarette yields of tar and nicotine for smokers using their own brand in their everyday environment. Method A robust, filter analysis method was used to estimate the tar and nicotine yields for 784 subjects. Seventeen brands were chosen to represent a wide range of styles: 85 and 100 mm lengths; menthol and non-menthol; 17, 23, and 25 mm circumference; with tar yields [Federal Trade Commission (FTC) method] ranging from 1 to 18 mg. Tar bands chosen corresponded to yields of 1–3 mg, 4–6 mg, 7–12 mg, and 13+ mg. Results A significant difference (p

The analysis of spent filters from human-smoked (HS) cigarettes has been used to estimate cigarette yields for over three decades. Until recently, the whole filter was used for estimation; however a part-filter method has been shown to improve the accuracy of estimated HS yields. The part-filter method uses only the mouth-end portion of the filter, downstream of the ventilation holes, for analysis. In this portion, the filtration efficiency is relatively constant irrespective of typical puff flow rates of humans and also minimizes butt length effects (e.g. nicotine condensation) on filtration efficiency. Therefore, the estimations of HS cigarette yields are more robust to human smoking conditions than previous whole-filter methods. British American Tobacco has adopted this method to obtain better understanding of how smokers actually use their products in their everyday environment. This can give information to help understand approaches to harm reduction. Since adopting this method, modifications and quality control features have been added to improve the accuracy of the estimation. This paper will describe in detail the methodology currently in use, along with sources of error, storage studies, quality control, repeatability and reproducibility.

Background Led by the American College of Surgeons Trauma Quality Improvement Program, performance improvement efforts have expanded to regional and national levels. The American College of Surgeons Trauma Quality Improvement Program recommends 5 audit filters to identify records with erroneous data, and the Georgia Committee on Trauma instituted standardized audit filter analysis in all Level I and II trauma centers in the state. Study Design Audit filter reports were performed from July 2013 to September 2014. Records were reviewed to determine whether there was erroneous data abstraction. Percent yield was defined as number of errors divided by number of charts captured. Results Twelve centers submitted complete datasets. During 15 months, 21,115 patient records were subjected to analysis. Audit filter captured 2,901 (14%) records and review yielded 549 (2.5%) records with erroneous data. Audit filter 1 had the highest number of records identified and audit filter 3 had the highest percent yield. Individual center error rates ranged from 0.4% to 5.2%. When comparing quarters 1 and 2 with quarters 4 and 5, there were 7 of 12 centers with substantial decreases in error rates. The most common missed complications were pneumonia, urinary tract infection, and acute renal failure. The most common missed comorbidities were hypertension, diabetes, and substance abuse. Conclusions In Georgia, the prevalence of erroneous data in trauma registries varies among centers, leading to heterogeneity in data quality, and suggests that targeted educational opportunities exist at the institutional level. Standardized audit filter assessment improved data quality in the majority of participating centers.