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AD is a common and well established industrial drying process. As idealised in Fig. 8.1, a typical drying curve of a foodstuff can be subdivided into three periods. After an initial phase (IP), a steady state is reached in which the drying rate (evaporated water over time) is constant. Therefore, this period is called "constant rate period" (CRP). In this period the product surface is still wet and the passing airflow transfers the heat for water evaporation to the surface. Simultaneously, the air is collecting the water vapour and is transporting it away from the product surface out of the dryer. This is a simultaneous heat and mass transfer. To keep the surface wet, enough water has to flow from the inside of the food to its surface. In the constant rate period this water flow is mainly capillary-driven and the surface temperature of the product is theoretically constant. As the water evaporation consumes energy, the surface temperature is typically significantly lower than the air temperature. The temperature profile in Fig. 8.1 A is adopted from a hot air drying process of carrot slices and it shows that this constant temperature period is not necessarily exactly reflected in real data. The factors that determine and limit the drying rate in the CRP are: the state of the air (temperature and relative humidity) as well as air velocity. By changing any of these parameters the drying process may be accelerated (or delayed) considerably.

With the new generation of satellite technologies, the archives of remote sensing (RS) images are growing very fast. To make the intrinsic information of each RS image easily accessible, visual question answering (VQA) has been introduced in RS. VQA allows a user to formulate a free-form question concerning the content of RS images to extract generic information. It has been shown that the fusion of the input modalities (i.e., image and text) is crucial for the performance of VQA systems. Most of the current fusion approaches use modalityspecific representations in their fusion modules instead of joint representation learning. However, to discover the underlying relation between both the image and question modality, the model is required to learn the joint representation instead of simply combining (e.g., concatenating, adding, or multiplying) the modality-specific representations. We propose a multi-modal transformer-based architecture to overcome this issue. Our proposed architecture consists of three main modules: i) the feature extraction module for extracting the modality-specific features; ii) the fusion module, which leverages a user-defined number of multi-modal transformer layers of the VisualBERT model (VB); and iii) the classification module to obtain the answer. In contrast to recently proposed transformer-based models in RS VQA, the presented architecture (called VBFusion) is not limited to specific questions, e.g., questions concerning pre-defined objects. Experimental results obtained on the RSVQAxBEN and RSVQA-LR datasets (which are made up of RGB bands of Sentinel-2 images) demonstrate the effectiveness of VBFusion for VQA tasks in RS. To analyze the importance of using other spectral bands for the description of the complex content of RS images in the framework of VQA, we extend the RSVQAxBEN dataset to include all the spectral bands of Sentinel-2 images with 10m and 20m spatial resolution. Experimental results show the importance of utilizing these bands to characterize the land-use land-cover classes present in the images in the framework of VQA. The code of the proposed method is publicly available at https://git.tu-berlin.de/rsim/multimodal-fusion-transformer-for-vqa-in-rs.

: Serial combination drying processes are currently studied as alternatives to conventional drying processes. Compared to freeze-drying (FD), serial combination drying appears to be faster and less expensive, while providing better product quality than hot-air drying (HAD) and microwave-vacuum drying (MVD) as previously demonstrated for carrots. Using the example of carrots, it has also been shown that the drying front moves radially outwards over the course of FD. This unexpected behaviour was suggested to originate from the carrots´ heterogeneous structure. It was hypothesized that apple pieces behave differently. Here, this hypothesis was proven by using micro-computed tomography (micro-CT) measurements of partly freeze-dried apple pieces. In order to improve the drying process of apple pieces, several single and combination drying processes were carried out. Processes were evaluated by using drying time and sample quality as relevant parameters. Sample quality was determined by analyzing the 3Dstructure, rehydration behaviour, colour and ingredient retention. Results showed that single MVD is a well suitable drying technique for apple pieces, producing dried products of equal quality to FD. Different from carrots, serial combinations are not necessary to improve the quality of dried apple pieces. Nonetheless, especially a combination of HAD and MVD was useful to obtain specific structures such as puffed pores that did not result from single MVD.