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Objectives Foaming and spraying are common application techniques for biocidal products. In the past, inhalation and dermal exposure during spraying have been investigated extensively. Currently, however, no exposure data are available for foaming, hindering a reliable risk assessment for foam applications of biocidal products. The focus of this project was the quantification of inhalation and potential dermal exposure to non-volatile active substances during the foam application of biocidal products in occupational settings. In some settings, exposure during spray application was measured for comparative purposes. Methods The inhalation and dermal exposure of operators were investigated during the application of benzalkonium chlorides and pyrethroids by foaming and spraying, considering both small- and large-scale application devices. Inhalation exposure was measured by personal air sampling; potential dermal exposure was measured using coveralls and gloves. Results Potential dermal exposure was substantially higher than inhalation exposure. Changing from spraying to foaming reduced inhalation exposure to airborne non-volatile active substances, but had no relevant effect on potential dermal exposure. However, for potential dermal exposure, considerable differences were observed between the application device categories. Conclusions To our knowledge, this study presents the first comparative exposure data for the foam and spray application of biocidal products in occupational settings with detailed contextual information. The results indicate a reduction of inhalation exposure with foam application compared to spray application. However, special attention is necessary for dermal exposure, which is not reduced by this intervention. [ABSTRACT FROM AUTHOR]

The application of biocidal products by foam is considered an alternative to droplet spraying when disinfecting surfaces or fighting infestations. Inhalation exposure to aerosols containing the biocidal substances cannot be ruled out during foaming. In contrast to droplet spraying, very little is known about aerosol source strength during foaming. In this study, the formation of inhalable aerosols was quantified according to the aerosol release fractions of the active substance. The aerosol release fraction is defined as the mass of active substance transferred into inhalable airborne particles during foaming, normalised to the total amount of active substance released through the foam nozzle. Aerosol release fractions were measured in control chamber experiments where common foaming technologies were operated according to their typical conditions of use. These investigations include foams generated mechanically by actively mixing air with a foaming liquid as well as systems that use a blowing agent for foam formation. The values of the aerosol release fraction ranged from 3.4 × 10−6 to 5.7 × 10−3 (average values). For foaming processes based on mixing air and the foaming liquid, the release fractions could be correlated to the process and foam parameters such as foam exit velocity, nozzle dimensions, and foam expansion ratio. [ABSTRACT FROM AUTHOR]

Artificially intelligent automation has not only impact on sensor technologies, but also on comprehensive multiple sensor systems for assisting situational awareness and decision-making. This is particularly true for integrated Manned-unManned-Teaming (MuM-T), for example. From a systems engineering perspective which does not exclude applications in the defence domain, three tasks need to be fulfilled: (1) Design artificially intelligent automation in a way that human beings are mentally and emotionally able to master each situation. (2) Identify technical design principles to facilitate the responsible use of AI in ethically critical applications. (3) Guarantee that human decision makers always have full superiority of information, decision-making, and options of action. Our discussion of AI-driven systems for multiple sensor data fusion results in recommendations and key results. We are addressing the algorithms needed, the data to be processed, the programming skills required, the computing devices to be used, the inevitable anthropocentric design, the reviewing of R & D efforts necessary, and the integration of different dimensions in a systems-of-systems point of view. [ABSTRACT FROM AUTHOR]

Examined the contribution of perceptual processes to cognitive ability with respect to stimulus complexity, response mode, level of encoding, and attention. Findings for 124 college students show that about 70% of common variance of perceptual processes and cognitive ability was due to attentive processes, with 30% resulting from pre-attentive processes. (SLD)

• Novel discovery approaches are based on proteolytic activation. • Antibody therapies targeting proteolytic activation. • Activatable pro-forms of antibodies or effector proteins. Proteases have crucial roles in homeostasis and disease; and protease inhibitors and recombinant proteases in enzyme replacement therapy have become key therapeutic applications of protease biology across several indications. This review briefly summarises therapeutic approaches based on protease activation and focuses on how recent insights into the spatial and temporal control of the proteolytic activation of growth factors and interleukins are leading to unique strategies for the discovery of new medicines. In particular, two emerging areas are covered: the first is based on antibody therapies that target the process of proteolytic activation of the pro-form of proteins rather than their mature form; the second covers a potentially new class of biopharmaceuticals using engineered, proteolytically activable and initially inactive pro-forms of antibodies or effector proteins to increase specificity and improve the therapeutic window. [ABSTRACT FROM AUTHOR]

In stochastic estimation problems, we aim to estimate an unknown state of interest given a set of measurements received from noisy sensory devices, such as radar, light detection and ranging, etc. A common model of the measurements’ random error is white Gaussian noise. This noise model is usually used to derive an estimator of the unknown state; accordingly, the state is described as a random variable with a Gaussian density. In some applications, the unknown state is known to take only positive values, e.g., estimating size or dimension. In such a case, the classical approaches based on Gaussian densities might fail, i.e., produce a negative value. In this article, a recursive Bayesian filter is proposed based on modeling the unknown state as Wishart distributed random matrix. This model ensures that the probability densities of the random variables are restricted to positive real values, even though the measurement’s noise is still modeled as white Gaussian noise. The feasibility of the proposed Bayesian–Wishart filter is demonstrated within the framework of extended target tracking. A target contour measurement model of a symmetric star-convex shape is presented and integrated in the proposed filter to track the target’s extent. [ABSTRACT FROM AUTHOR]

Target tracking with adaptive phased-array radars in the presence of standoff jamming presents both challenges and opportunities to the track filter designer. A measurement likelihood function is derived for this situation which accounts for the effect of both positive and negative contact information. This likelihood function is approximated as a weighted sum of Gaussian terms consisting of both positive and negative weights, accounting for the positive and negative contact information. Additionally, recent theoretical results have been reported which have derived an accurate measurement error covariance in the vicinity of the jammer when adaptive beamforming is used by the radar to null the effects of the jammer. We compare the impact of using a likelihood function that accounts for negative contact information and the corrected measurement error covariance by comparing five Kalman filter-based trackers in five different scenarios. We show that only those track filters which use both the negative contact information and the corrected measurement error covariance are effective in maintaining track on a maneuvering target as it passes through the jamming region. This approach can also be generalized to any target tracking problem where the sensor response is anisotropic.

Tracking ground targets with airborne GMTI (ground moving target indicator) sensor measurements proves to be a challenging task due to high target density, high clutter, and low visibility. The exploitation of nonstandard background information such as road maps and terrain information is therefore highly desirable for the enhancement of track quality and track continuity. The present paper presents a Bayesian approach to incorporate such information consistently. It is particularly suited to deal with winding roads and networks of roads. The target dynamics is modeled in quasi one-dimensional road coordinates and mapped onto ground coordinates using linear road segments taking road map errors into account. The case of several intersecting roads with different characteristics, such as mean curvature, slope, or visibility, is treated within an interacting multiple model (IMM) scheme. Targets can be masked both by the clutter notch of the sensor and by terrain obstacles. Both effects are modeled using a sensor-target state dependent detection probability. The iterative filter equations are formulated within a framework of Gaussian sum approximations on the one hand and a particle filter approach on the other hand. Simulation results for single targets taken from a realistic ground scenario show strongly reduced target location errors compared with the case of neglecting road-map information. By modeling the clutter notch of the GMTI sensor, early detection of stopping targets is demonstrated.

Currently, the retrieval of wind fields from synthetic aperture radar (SAR) images suffers from inadequate knowledge of the wind direction. State-of-the-art spectral analysis works fine on open seas, but is limited in spatial resolution. The method described here is based on the local gradients computed with standard image processing algorithms. It handles image features not caused by wind and can be applied to irregularly shaped regions. The new method has already been applied to many images from the European Remote sensing Satellite SARs and RADARSAT-1 ScanSAR, usually supplying reasonable wind fields. The spatial sampling most frequently used was 20 x 20 and 10 x 10 [km.sup.2]. In some cases, samplings down to 1 x 1 [km.sup.2] were tested. This paper describes the local gradients method including the filtering of nonwind generated image features and gives some application examples. Index Terms--Automatic wind direction retrieval, image filtering, image processing, numerical recipe, ocean winds, synthetic aperture radar (SAR), wind streaks.

Random matrices are widely used to estimate the extent of an elliptically contoured object. Usually, it is assumed that the measurements follow a normal distribution, with its standard deviation being proportional to the object’s extent. However, the random matrix approach can filter the center of gravity and the covariance matrix of measurements independently of the measurement model. This work considers the whole chain from data acquisition to the linear Kalman Filter with extension estimation as a reference plant. The input is the (unknown) ground truth (position and extent). The output is the filtered center of gravity and the filtered covariance matrix of the measurement distribution. A virtual measurement model emulates the behavior of the reference plant. The input of the virtual measurement model is adapted using the proposed algorithm until the output parameters of the virtual measurement model match the result of the reference plant. After the adaptation, the input to the virtual measurement model is considered an estimation for position and extent. The main contribution of this paper is the reference model concept and an adaptation algorithm to optimize the input of the virtual measurement model. [ABSTRACT FROM AUTHOR]

When comparing the transporters of three completely sequenced eukaryotic genomes -- Saccharomyces cerevisiae, Arabidopsis thaliana and Homo sapiens -- transporter types can be distinguished according to phylogeny, substrate spectrum, transport mechanism and cell specificity. The known amino acid transporters belong to five different superfamilies. Two preferentially [Na.sup.+]-coupled transporter superfamilies are not represented in the yeast and Arabidopsis genomes, whereas the other three groups, which often function as [H.sup.+]-coupled systems, have members in all investigated genomes. Additional superfamilies exist for organellar transport, including mitochondrial and plastidic carriers. When used in combination with phylogenetic analyses, functional comparison might aid our prediction of physiological functions for related but uncharacterized open reading frames.

Sugar beet (Beta vulgaris subsp. vulgaris) is the exclusive source of sugar in the form of sucrose in temperate climate zones. Sugar beet is grown there as an annual crop from spring to autumn because of the damaging effect of freezing temperatures to taproot tissue. A collection of hybrid and non-hybrid sugar beet cultivars was tested for winter survival rates and freezing tolerance. Three genotypes with either low or high winter survival rates were selected for detailed study of their response to frost. These genotypes differed in the severity of frost injury in a defined inner region in the upper part of the taproot, the so-called pith. We aimed to elucidate genotype- and tissue-dependent molecular processes during freezing and combined analyses of sugar beet anatomy and physiology with transcriptomic and metabolite profiles of leaf and taproot tissues at low temperatures. Freezing temperatures induced strong downregulation of photosynthesis in leaves, generation of reactive oxygen species (ROS), and ROS-related gene expression in taproots. Simultaneously, expression of genes involved in raffinose metabolism, as well as concentrations of raffinose and its intermediates, increased markedly in both leaf and taproot tissue at low temperatures. The accumulation of raffinose in the pith tissue correlated with freezing tolerance of the three genotypes. We discuss a protective role for raffinose and its precursors against freezing damage of sugar beet taproot tissue. [ABSTRACT FROM AUTHOR]