Small unmanned aerial vehicle (UAV) based remote sensing is a rapidly evolving technology. Novel sensors and methods are entering the market, offering completely new possibilities to carry out remote sensing tasks. Three-dimensional (3D) hyperspectral remote sensing is a novel and powerful technology that has recently become available to small UAVs. This study investigated the performance of UAV-based photogrammetry and hyperspectral imaging in individual tree detection and tree species classification in boreal forests. Eleven test sites with 4151 reference trees representing various tree species and developmental stages were collected in June 2014 using a UAV remote sensing system equipped with a frame format hyperspectral camera and an RGB camera in highly variable weather conditions. Dense point clouds were measured photogrammetrically by automatic image matching using high resolution RGB images with a 5 cm point interval. Spectral features were obtained from the hyperspectral image blocks, the large radiometric variation of which was compensated for by using a novel approach based on radiometric block adjustment with the support of in-flight irradiance observations. Spectral and 3D point cloud features were used in the classification experiment with various classifiers. The best results were obtained with Random Forest and Multilayer Perceptron (MLP) which both gave 95% overall accuracies and an F-score of 0.93. Accuracy of individual tree identification from the photogrammetric point clouds varied between 40% and 95%, depending on the characteristics of the area. Challenges in reference measurements might also have reduced these numbers. Results were promising, indicating that hyperspectral 3D remote sensing was operational from a UAV platform even in very difficult conditions. These novel methods are expected to provide a powerful tool for automating various environmental close-range remote sensing tasks in the very near future.

IL-4, primarily produced by T cells, mast cells, and basophiles, is a cytokine which has pleiotropic effects on the immune system. IL-4 induces T cells to differentiate to Th2 cells and activated B lymphocytes to proliferate and to synthesize IgE and IgG1. IL-4 is particularly important for the development and perpetuation of asthma and allergy. Stat6 is the protein activated by signal transduction through the IL-4R, and studies with knockout mice demonstrate that Stat6 is critical for a number of IL-4-mediated functions including Th2 development and production of IgE. In the present study, novel IL-4- and Stat6-regulated genes were discovered by using Stat6−/− mice and Affymetrix oligonucleotide arrays. Genes regulated by IL-4 were identified by comparing the gene expression profile of the wild-type T cells induced to polarize to the Th2 direction (CD3/CD28 activation + IL-4) to gene expression profile of the cells induced to proliferate (CD3/CD28 activation alone). Stat6-regulated genes were identified by comparing the cells isolated from the wild-type and Stat6−/− mice; in this experiment the cells were induced to differentiate to the Th2 direction (CD3/CD28 activation + IL-4). Our study demonstrates that a number a novel genes are regulated by IL-4 through Stat6-dependent and -independent pathways. Moreover, elucidation of kinetics of gene expression at early stages of cell differentiation reveals several genes regulated rapidly during the process, suggesting their importance for the differentiation process.

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Background: Lately, terrestrial point clouds have drawn attention as a new data source for in situ forest investigations. So far, terrestrial laser scanning (TLS) has the highest data quality among all terrestrial point cloud data in terms of geometric accuracy and level of detail (IEEE Transact Geosci Remote Sens 53: 5117-5132, 2015). The TLS point clouds processed by automated algorithms can provide certain individual tree parameters at close to required accuracy in practical applications. However, all terrestrial point clouds face a general challenge, which is the occlusions of upper tree crowns. An emerging technology called unmanned-aerial-vehicle (UAV) -borne laser scanning (ULS) potentially combines the strengths of above and under canopy surveys.Results: The performance of ULS are evaluated in 22 sample plots of various forest stand conditions in a boreal forest. The forest parameter estimates are benchmarked through a comparison with state-of-the-art terrestrial mechanisms from both static terrestrial and mobile laser scanning. The results show that in easy forest stand conditions, the performance of ULS point cloud is comparable with the terrestrial solutions. Conclusions: This study gives the first strict evaluation of ULS in situ observations in varied forest conditions. The study also acts as a benchmarking of available active remote sensing techniques for forest in situ mensuration. The results indicate that the current off-the-shelf ULS has an excellent tree height/tops measurement performance. Although the geometrical accuracy of the ULS data, especially at the stem parts, does not yet reach the level of other terrestrial point clouds, the unbeatable high mobility and fast data acquisition make the ULS a very attractive option in forest investigations.

Th1 and Th2 cells arise from a common precursor cell in response to triggering through the TCR and cytokine receptors for IL-12 or IL-4. This leads to activation of complex signaling pathways, which are not known in detail. Disturbances in the balance between type 1 and type 2 responses can lead to certain immune-mediated diseases. Thus, it is important to understand how Th1 and Th2 cells are generated. To clarify the mechanisms as to how IL-12 and IL-4 induce Th1 and Th2 differentiation and how TGF-β can inhibit this process, we have used oligonucleotide arrays to examine the early polarization of Th1 and Th2 cells in the presence and absence of TGF-β. In addition to genes previously implicated in the process, we have identified 20 genes with various known and unknown functions not previously associated with Th1/2 polarization. We have also further determined which genes are targets of IL-12, IL-4, and TGF-β regulation in the cells induced to polarize to Th1 and Th2 directions. Interestingly, a subset of the genes was coregulated by IL-12 or IL-4 and TGF-β. Among these genes are candidates that may modulate the balance between Th1 and Th2 responses.

Background: Missing values frequently pose problems in gene expression microarray experiments as they can hinder downstream analysis of the datasets. While several missing value imputation approaches are available to the microarray users and new ones are constantly being developed, there is no general consensus on how to choose between the different methods since their performance seems to vary drastically depending on the dataset being used.

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Drone-based remote sensing has evolved rapidly in recent years. Miniaturized hyperspectral imaging sensors are becoming more common as they provide more abundant information of the object compared to traditional cameras. Reflectance is a physically defined object property and therefore often preferred output of the remote sensing data capture to be used in the further processes. Absolute calibration of the sensor provides a possibility for physical modelling of the imaging process and enables efficient procedures for reflectance correction. Our objective is to develop a method for direct reflectance measurements for drone-based remote sensing. It is based on an imaging spectrometer and irradiance spectrometer. This approach is highly attractive for many practical applications as it does not require in situ reflectance panels for converting the sensor radiance to ground reflectance factors. We performed SI-traceable spectral and radiance calibration of a tuneable Fabry-Pérot Interferometer -based (FPI) hyperspectral camera at the National Physical Laboratory NPL (Teddington, UK). The camera represents novel technology by collecting 2D format hyperspectral image cubes using time sequential spectral scanning principle. The radiance accuracy of different channels varied between ±4% when evaluated using independent test data, and linearity of the camera response was on average 0.9994. The spectral response calibration showed side peaks on several channels that were due to the multiple orders of interference of the FPI. The drone-based direct reflectance measurement system showed promising results with imagery collected over Wytham Forest (Oxford, UK).