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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.

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.

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.

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 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 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.

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

In order to analyze the expression profiles of a large number of genes in the tissues (or cells) of interest, and to identify the genes preferentially expressed in the tissues, we have developed a large-scale gene expression analysis system. It is based on the hybridization of the mRNAs from the tissues with a high-density cDNA filter followed by the quantitative measurement of the amount of the hybridized mRNA on each cDNA spot. By employing a high-performance bioimaging analyzer, the system allowed us to compare the expression profiles of thousands of genes (cDNAs) simultaneously with a sensitivity comparable to conventional Northern blotting analysis. By this system (called high-density cDNA filter analysis or HDCFA), the expression profiles of 2505 cloned human brain cDNAs (genes) were monitored. Through the comparison of the expression profiles of these cDNAs in the adult brain, fetal brain and adult liver, about one half of these brain cDNAs (1239 clones) were identified as the candidates which were expressed preferentially in the brain. Among these, 408 and 288 clones were found to be preferentially expressed in the adult and fetal brain, respectively. The results have shown that the system may be widely applicable for analysis of the gene expression profiles of various tissues on a large scale

At ITN, analysis of air particulate matter has been made since 1999, stimulated by a contract for air quality monitoring of an urban waste incinerator. Samples are analysed by Instrumental Neutron Activation Analysis (INAA) and Proton Induced X-ray Emission (PIXE). Heavy metals and other elements are determined. The procedures for filter analysis have recently been changed, leading to the present comparison between the old and the new procedures. For INAA, in this new procedure we look for the 336.2 keV gamma line of 115m In in addition to the gamma-ray line of 527.9 keV used for the detection of 115 Cd. Cd evaluations obtained by both gamma lines are compared and detection limits for Cd are presented. Preliminary results for Cd, As, Ni, and Hg are shown for a region in the north of Lisbon.

Inexpensive fibreglass mesh window screens were used as spacers between colony blot filters to increase the number of bacterial isolates that could be tested by DNA colony hybridization. Sixty filters with up to 48 isolates per filter were tested at one time. This modified technique reduced the amount of radiolabelled probe and other materials needed for simultaneous analysis of up to 2880 test isolates.