Photoresist-based integration of enzyme functionality into MEMS

We demonstrate the direct immobilization of glucose oxidase and lactate oxidase onto photoresists commonly used in microfabrication. The method allows for a cost-effective, facile inclusion of enzyme functionality into novel MEMS devices because it does not require any chemical or physical pre-treatment of surfaces, and it is largely compatible with existing fabrication technologies. We used fluorescence imaging and absorbance spectrometry to confirm attachment of the enzymes onto the photoresists and to determine their activity. In addition, the procedure was used to successfully integrate enzyme functionality into a photoresist-based biosensor. This further demonstrates the effectiveness of the approach, and opens a path towards other novel applications in MEMS research.     

High Dynamic Range SQUID Readout for Frequency-Domain Multiplexers

A 16-SQUID array has been designed and fabricated, which shows 0.12 μΦ ₀ Hz^−1/2 flux noise at 4.2 K. The readout amplifier based on a cryogenic silicon-germanium bipolar transistor employs short-delay negative flux feedback and reaches 7 MHz bandwith for a 1 Φ _0p-p signal. The −1 dB compression is reached approximately at 4.2 Φ _0p-p amplitude when the signal frequency is 1 MHz. In the feedback mode the flux noise is anomalously increased to 0.35 μΦ ₀ Hz^−1/2.      

BMC via on-the-fly determinization

This paper develops novel bounded model checking (BMC) techniques for asynchronous parallel systems. The aim is to increase the efficiency of BMC by exploiting the inherent concurrency in such systems. This added efficiency is gained by covering more reachable states within a given bound using two techniques. Firstly, a nonstandard execution model, step executions, where multiple actions can take place simultaneously is applied. Secondly, the number of executions the system can have is reduced by modeling the execution of the system components as if they were determinized. This determinization technique also enables the removal of the internal transitions of the components. Step executions can be further restricted to a subclass called process executions without losing any reachable states.The paper presents a translation scheme for BMC of reachability properties. The translation is from an asynchronous system where the components are modeled as labeled transition systems (LTSs) to a propositional formula. The models of the formula correspond to the step executions of the original system where each component is replaced with its determinized counterpart. The formula for step executions can be easily extended in such a way that its models correspond to the process executions of the system. The translation scheme has been implemented and some experimental comparisons performed. The results show that the bound needed to detect a violation of a reachability property is, for step and process executions, in most cases lower than in interleaving executions and that the running time of the model checker using process executions is smaller than of that using steps. Moreover, the performance compares favorably to a state-of-the-art interleaving BMC implementation in the NuSMV system.     

MORE – a multimodal observation and analysis system for social interaction research

The MORE system is designed for observation and machine-aided analysis of social interaction in real life situations, such as classroom teaching scenarios and business meetings. The system utilizes a multichannel approach to collect data whereby multiple streams of data in a number of different modalities are obtained from each situation. Typically the system collects a 360-degree video and audio feed from multiple microphones set up in the space. The system includes an advanced server backend component that is capable of performing video processing, feature extraction and archiving operations on behalf of the user. The feature extraction services form a key part of the system and rely on advanced signal analysis techniques, such as speech processing, motion activity detection and facial expression recognition in order to speed up the analysis of large data sets. The provided web interface weaves the multiple streams of information together, utilizes the extracted features as metadata on the audio and video data and lets the user dive into analyzing the recorded events. The objective of the system is to facilitate easy navigation of multimodal data and enable the analysis of the recorded situations for the purposes of, for example, behavioral studies, teacher training and business development. A further unique feature of the system is its low setup overhead and high portability as the lightest MORE setup only requires a laptop computer and the selected set of sensors on site.     

Variation and directional anisotropy of reflectance at the crown scale — Implications for tree species classification in digital aerial images

Tree species classification is still solved at insufficient reliability in airborne optical data. The variation caused by directional reflectance anisotropy hampers image-based solutions. In addition, trees show considerable within-species variation in reflectance properties. We examined these phenomena at the single-tree level, using the Leica ADS40 line sensor and XPro software, which constitute the first photogrammetric large-format multispectral system to provide target reflectance images. To analyze the influence of illumination conditions in the canopy, we developed a method in which the crown shape as well as between-tree occlusions and shading were modeled, using dense LiDAR data. The precision of the ADS40 reflectance images in well-defined surfaces was 5% as coefficient of variation when 1−4-km image data were fused. The range of reflectance anisotropy was ± 30% for trees near the solar principal plane, with differences between bands and species. Because of the anisotropy differences observed, the spectral separability of the tree species in different bands is dependent on the view-illumination geometry. The within-species variation was high; the coefficient of variation was 13−31%. The contribution of tree and stand variables to anisotropy-normalized reflectance variation was examined. The effects of the species composition of adjacent trees were substantial in NIR and this variation hampers spectral classification in mixed stands. We also studied species- and band-specific intracrown brightness patterns, and we suggest their use as high-order image features in species classification. A species classification accuracy of up to 80% was obtained using 4-km data, which showed the high potential of the ADS40.     

Greenhouse impact assessment of peat-based Fischer–Tropsch diesel life-cycle

New raw materials for transportation fuels need to be introduced, in order to fight against climate change and also to cope with increasing risks of availability and price of oil. Peat has been recognised suitable raw material option for diesel produced by gasification and Fischer–Tropsch (FT) synthesis. The energy content of Finnish peat reserves is remarkable. In this study, the greenhouse impact of peat-based FT diesel production and utilisation in Finland was assessed from the life-cycle point of view. In 100 year's time horizon the greenhouse impact of peat-based FT diesel is likely larger than the impact of fossil diesel. The impact can somewhat be lowered by producing peat from the agricultural peatland (strong greenhouse gas emissions from the decaying peatlayer are avoided) with new peat production technique, and utilising the produced biomass from the after-treatment area for diesel also. If diesel production is integrated with pulp and paper mill to achieve energy efficiency benefits and if the electricity demand can be covered by zero emission electricity, the greenhouse impact of peat-based FT diesel reduces to the level of fossil diesel when agricultural peatland is used, and is somewhat higher when forestry-drained peatland is used as raw material source.     

Preparation and Study of Pd Catalysts Supported on Activated Carbon Cloth (ACC) for Direct Synthesis of H2O2 from H2 and O2

Activated carbon cloths (ACCs) were used as supports for Pd catalysts. The catalyst preparation was carried out by the impregnation method using acidic solution of palladium dichloride (PdCl₂) as metal precursor. The effects of the oxidation state of the loaded metal, heat treatment of the catalysts in different atmosphere (H₂, air) at different temperatures and surface chemistry of the support on the catalyst characterizations and the catalytic activities were investigated. Wet oxidation of ACC was done by nitric acid in order to induce oxygen-containing surface functional groups. Surface chemistry of the support and oxidation state of the metallic phase was investigated by means of XPS, TPD, SEM, DTA and TGA tests. Direct synthesis of hydrogen peroxide from H₂ and O₂ was performed batch wise in a stainless steel autoclave. The reactions were conducted under high pressure (38 bar) at 0 °C and methanol was used as reaction medium. The direct synthesis results showed that the oxygen-containing surface functional groups increase the selectivity of the catalysts by reducing the rate of water production. Existence of the oxidized state of Pd (PdO) also makes the catalyst more selective than the corresponding zerovalent state (Pd0). PdO affected on selectivity by increasing the rate of H₂O₂ production and reducing the amount of production of water, simultaneously.     

Imputation of single-tree attributes using airborne laser scanning-based height, intensity, and alpha shape metrics

Forest inventories based on single-tree interpretation of airborne laser scanning (ALS) data often rely on an allometric estimation chain in which inaccuracies in the estimates of the diameter at breast height (DBH) propagate to other characteristics of interest such as the stem volume. Our purpose was to test nearest neighbor imputation by the k-Most Similar Neighbor (k-MSN) and the Random Forest (RF) methods for the simultaneous estimation of species, DBH, height and stem volume using ALS data. The predictors included computational alpha shape metrics and variables based on the height and intensity distributions in the ALS data. Separate data sets covering 1898 and 1249 dominant to intermediate trees in a typical Scandinavian stand structure were used for training and validation, respectively. RF proved to be a flexible method with an ability to handle 1846 predictors with no need for their reduction. Classification of Scots pine, Norway spruce and deciduous trees showed an accuracy of 78%, and the estimates of DBH, height and volume had root mean square errors of 13%, 3%, and 31%, respectively, when evaluated against the validation data. The two selection strategies implemented here reduced the number of candidate variables effectively without any substantial effect on the accuracy relative to the use of all predictors. Differences in k-MSN and RF imputations were marginal when the reduced sets of variables were used. Estimation accuracies could be maintained practically unchanged with only 12.5% of the initial reference data (237 trees), provided the distribution of the observations was similar in the reference and target data. Since we used information collected in the field for extracting the ALS point clouds for individual trees, our results represent an optimal case and should nevertheless be validated against automated tree delineation.     

Flexible view recognition for indoor navigation based on Gabor filters and support vector machines

Real-world scenes are hard to segment into (relevant) objects and (irrelevant) background. In this paper, we argue for view-based vision, which does not use segmentation, and demonstrate a practical approach for recognizing textured objects and scenes in office environments.

A small set of Gabor filters is used to preprocess texture combinations from input images. The impulse responses of the filters are transformed into feature vectors that are fed to support vector machines. Pairwise feature comparisons decide the classification of views.

We validate the approach on a robot platform using three different types of target objects and indoor scenes: people, doorways, and written signs. The general-purpose system can run in real time, and that recognition accuracies of practical utility are obtained.