Sorption-induced Static Bending of Microcantilevers Coated with Viscoelastic Material

Absorption of a chemical analyte into a polymercoating results in an expansion governed by the concentration and type of analyte that has diffused into the bulk of the coating. When the coating is attached to a microcantilever, this expansion results in bending of the device. Assuming that absorption (i.e., diffusion across the surface barrier into the bulk of the coating) is Fickian, with a rate of absorption that is proportional to the difference between the absorbed concentration and the equilibrium concentration, and the coating is elastic, the bending response of the coated device should exhibit a first-order behavior. However, for polymercoatings, complex behaviors exhibiting an overshoot that slowly decays to the steady-state value have been observed. A theoretical model of absorption-induced static bending of a microcantilever coated with a viscoelastic material is presented, starting from the general stress/strain relationship for a viscoelastic material. The model accounts for viscoelasticstress relaxation and possible coating plasticization. Calculated responses show that the model is capable of reproducing the same transient behavior exhibited in the experimental data. The theory presented can also be used for extracting viscoelasticproperties of the coating from the measured bending data

Rapid Detection of Analytes with Improved Selectivity Using Coated Microcantilever Chemical Sensors and Estimation Theory

Rapid detection of analytes with improved selectivity is achieved though the use of estimation theory to analyze the response of polymer-coated microcantilever chemical sensors. In general, chemical sensors exhibit partial selectivity and can have relatively long response times. Using estimation theory, it is possible to make short-term response predictions from past data. This makes it possible to use the transient information (response time), often unique to an analyte/coating pair, to achieve an improvement in analyte species recognition while simultaneously allowing for a reduction in the time required for identification and quantification. An extended Kalman filter is used as a recursive online approach to refine the estimate of the sensor\u27s future response. Both identification and quantification are thus possible as soon as the filter estimate achieves a high confidence level. Also, with improved selectivity, identification is possible using fewer sensors in an array

Local stellar kinematics from RAVE data - II. Radial metallicity gradient

We investigate radial metallicity gradients for a sample of dwarf stars from the RAdial Velocity Experiment (RAVE) Data Release 3 (DR3). We select a total of approximately 17 000 F-type and G-type dwarfs, using a selection of colour, log g and uncertainty in the derived space motion, and calculate for each star a probabilistic (kinematic) population assignment to a thick or thin disc using space motion and additionally another (dynamical) assignment using stellar vertical orbital eccentricity. We additionally subsample by colour, to provide samples biased toward young thin-disc and older thin-disc stars. We derive a metallicity gradient as a function of Galactocentric radial distance, i.e. d[M/H]/dRm=−0.051 ± 0.005 dex kpc−1, for the youngest sample, F-type stars with vertical orbital eccentricities ev≤ 0.04. Samples biased toward older thin-disc stars show systematically shallower abundance gradients

CCD BV and 2MASS photometric study of the open cluster NGC 1513

We present CCD BV and JHK$_{s}$ 2MASS photometric data for the open cluster NGC 1513. We observed 609 stars in the direction of the cluster up to a limiting magnitude of $V\sim19$ mag. The star count method shows that the centre of the cluster lies at $\alpha_{2000}=04^{h}09^{m}36^{s}$, $\delta_{2000}=49^{\circ}28^{'}43^{''}$ and its angular size is $r=10$ arcmin. The optical and near-infrared two-colour diagrams reveal the colour excesses in the direction of the cluster as $E(B-V)=0.68\pm0.06$, $E(J-H)=0.21\pm0.02$ and $E(J-K_{s})=0.33\pm0.04$ mag. These results are consistent with normal interstellar extinction values. Optical and near-infrared Zero Age Main-Sequences (ZAMS) provided an average distance modulus of $(m-M)_{0}=10.80\pm0.13$ mag, which can be translated into a distance of $1440\pm80$ pc. Finally, using Padova isochrones we determined the metallicity and age of the cluster as $Z=0.015\pm 0.004$ ($[M/H]=-0.10 \pm 0.10$ dex) and $\log (t/yr) = 8.40\pm0.04$, respectively.Comment: 15 pages, 12 figures and 4 tables, accepted for publication in Astrophysics & Space Scienc

Local stellar kinematics from RAVE data: III. Radial and Vertical Metallicity Gradients based on Red Clump Stars

We investigate radial and vertical metallicity gradients for a sample of red clump stars from the RAdial Velocity Experiment (RAVE) Data Release 3. We select a total of 6781 stars, using a selection of colour, surface gravity and uncertainty in the derived space motion, and calculate for each star a probabilistic (kinematic) population assignment to a thin or thick disc using space motion and additionally another (dynamical) assignment using stellar vertical orbital eccentricity. We derive almost equal metallicity gradients as a function of Galactocentric distance for the high probability thin disc stars and for stars with vertical orbital eccentricities consistent with being dynamically young, e_v<=0.07, i.e. d[M/H]/dR_m = -0.041(0.003) and d[M/H]/dR_m = -0.041(0.007) dex/kpc. Metallicity gradients as a function of distance from the Galactic plane for the same populations are steeper, i.e. d[M/H]/dz_{max} = -0.109(0.008) and d[M/H]/dz_{max} = -0.260(0.031) dex/kpc, respectively. R_m and z_{max} are the arithmetic mean of the perigalactic and apogalactic distances, and the maximum distance to the Galactic plane, respectively. Samples including more thick disc red clump giant stars show systematically shallower abundance gradients. These findings can be used to distinguish between different formation scenarios of the thick and thin discs.Comment: 27 pages, including 15 figures and 4 tables, accepted for publication in MNRA

Output feedback robust H∞ control with D-stability and variance constraints: A parametrization approach

This is the post print version of the article. The official published version can be obtained from the link below - Copyright 2005 Springer Ltd.In this paper, we study the problem of robust H∞ controller design for uncertain continuous-time systems with variance and D-stability constraints. The parameter uncertainties are allowed to be unstructured but norm-bounded. The aim of this problem is the design of an output feedback controller such that, for all admissible uncertainties, the closed-loop poles be placed within a specified disk, the H∞ norm bound constraint on the disturbance rejection attenuation be guaranteed, and the steady-state variance for each state of the closed-loop system be no more than the prescribed individual upper bound, simultaneously. A parametric design method is exploited to solve the problem addressed. Sufficient conditions for the existence of the desired controllers are derived by using the generalized inverse theory. The analytical expression of the set of desired controllers is also presented. It is shown that the obtained results can be readily extended to the dynamic output feedback case and the discrete-time case

On the moment dynamics of stochastically delayed linear control systems

In this article, the dynamics and stability of a linear system with stochastic delay and additive noise are investigated. It is assumed that the delay value is sampled periodically from a stationary distribution. A semi‐discretization technique is used to time‐discretize the system and derive the mean and second‐moment dynamics. These dynamics are used to obtain the stationary moments and the corresponding necessary and sufficient stability conditions. The application of the proposed method is illustrated through the analysis of the Hayes equation with stochastic delay and additive noise. The method is also applied to the control design of a connected automated vehicle. These examples illuminate the effects of stochastic delays on the robustness of dynamical systems

A human brainstem glioma xenograft model enabled for bioluminescence imaging

Despite the use of radiation and chemotherapy, the prognosis for children with diffuse brainstem gliomas is extremely poor. There is a need for relevant brainstem tumor models that can be used to test new therapeutic agents and delivery systems in pre-clinical studies. We report the development of a brainstem-tumor model in rats and the application of bioluminescence imaging (BLI) for monitoring tumor growth and response to therapy as part of this model. Luciferase-modified human glioblastoma cells from five different tumor cell sources (either cell lines or serially-passaged xenografts) were implanted into the pontine tegmentum of athymic rats using an implantable guide-screw system. Tumor growth was monitored by BLI and tumor volume was calculated by three-dimensional measurements from serial histopathologic sections. To evaluate if this model would allow detection of therapeutic response, rats bearing brainstem U-87 MG or GS2 glioblastoma xenografts were treated with the DNA methylating agent temozolomide (TMZ). For each of the tumor cell sources tested, BLI monitoring revealed progressive tumor growth in all animals, and symptoms caused by tumor burden were evident 26–29 days after implantation of U-87 MG, U-251 MG, GBM6, and GBM14 cells, and 37–47 days after implantation of GS2 cells. Histopathologic analysis revealed tumor growth within the pons in all rats and BLI correlated quantitatively with tumor volume. Variable infiltration was evident among the different tumors, with GS2 tumor cells exhibiting the greatest degree of infiltration. TMZ treatment groups were included for experiments involving U-87 MG and GS2 cells, and in each case TMZ delayed tumor growth, as indicated by BLI monitoring, and significantly extended survival of animal subjects. Our results demonstrate the development of a brainstem tumor model in athymic rats, in which tumor growth and response to therapy can be accurately monitored by BLI. This model is well suited for pre-clinical testing of therapeutics that are being considered for treatment of patients with brainstem tumors

Robust filtering for a class of nonlinear stochastic systems with probability constraints

This paper is concerned with the probability-constrained filtering problem for a class of time-varying nonlinear stochastic systems with estimation error variance constraint. The stochastic nonlinearity considered is quite general that is capable of describing several well-studied stochastic nonlinear systems. The second-order statistics of the noise sequence are unknown but belong to certain known convex set. The purpose of this paper is to design a filter guaranteeing a minimized upper-bound on the estimation error variance. The existence condition for the desired filter is established, in terms of the feasibility of a set of difference Riccati-like equations, which can be solved forward in time. Then, under the probability constraints, a minimax estimation problem is proposed for determining the suboptimal filter structure that minimizes the worst-case performance on the estimation error variance with respect to the uncertain second-order statistics. Finally, a numerical example is presented to show the effectiveness and applicability of the proposed method

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation