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In this paper, we present a novel methodology we call MDS-ViTNet (Multi Decoder Saliency by Vision Transformer Network) for enhancing visual saliency prediction or eye-tracking. This approach holds significant potential for diverse fields, including marketing, medicine, robotics, and retail. We propose a network architecture that leverages the Vision Transformer, moving beyond the conventional ImageNet backbone. The framework adopts an encoder-decoder structure, with the encoder utilizing a Swin transformer to efficiently embed most important features. This process involves a Transfer Learning method, wherein layers from the Vision Transformer are converted by the Encoder Transformer and seamlessly integrated into a CNN Decoder. This methodology ensures minimal information loss from the original input image. The decoder employs a multi-decoding technique, utilizing dual decoders to generate two distinct attention maps. These maps are subsequently combined into a singular output via an additional CNN model. Our trained model MDS-ViTNet achieves state-of-the-art results across several benchmarks. Committed to fostering further collaboration, we intend to make our code, models, and datasets accessible to the public.

This article describes the 2023 IEEE Low-Power Computer Vision Challenge (LPCVC). Since 2015, LPCVC has been an international competition devoted to tackling the challenge of computer vision (CV) on edge devices. Most CV researchers focus on improving accuracy, at the expense of ever-growing sizes of machine models. LPCVC balances accuracy with resource requirements. Winners must achieve high accuracy with short execution time when their CV solutions run on an embedded device, such as Raspberry PI or Nvidia Jetson Nano. The vision problem for 2023 LPCVC is segmentation of images acquired by Unmanned Aerial Vehicles (UAVs, also called drones) after disasters. The 2023 LPCVC attracted 60 international teams that submitted 676 solutions during the submission window of one month. This article explains the setup of the competition and highlights the winners' methods that improve accuracy and shorten execution time., Comment: LPCVC 2023, website: https://lpcv.ai/

Using the notion of inclination of two subspaces $L$ and $M$ of Hilbert space $\mathcal{H}$, we prove the theorem on the extension of linear continuous functionals defined on the subspace $L$ to $\mathcal{H}$ so that the extended functionals vanish on the subspace $M$. We apply this theorem to study the question of decomposition of the electromagnetic field in resonator with ideally conducting walls into potential and vortex components and derive the Korn-type inequality for vortex fields., Comment: 12 pages

A new concept of a multi-valued associative memory is introduced, generalizing a similar one in fuzzy neural networks. We expand the results on fuzzy associative memory with thresholds, to the case of a multi-valued one: we introduce the novel concept of such a network without numbers, investigate its properties, and give a learning algorithm in the multi-valued case. We discovered conditions under which it is possible to store given pairs of network variable patterns in such a multi-valued associative memory. In the multi-valued neural network, all variables are not numbers, but elements or subsets of a lattice, i.e., they are all only partially-ordered. Lattice operations are used to build the network output by inputs. In this paper, the lattice is assumed to be Brouwer and determines the implication used, together with other lattice operations, to determine the neural network output. We gave the example of the network use to classify aircraft/spacecraft trajectories., Comment: This is a version with correct Theorem 3 (Theorem 2 in published variant)

Carefully designed micro and nanocarriers can provide significant advantages over conventional macroscopic counterparts in biomedical applications. The set of requirements including a high loading capacity, triggered release mechanisms, biocompatibility, and biodegradability should be considered for the successful delivery realization. Porous calcium carbonate (CaCO3) is one of the most promising platforms, which can encompass all the beforehand mentioned requirements. Here, we study both the particles formation and biological applicability of CaCO3. In particular, anisotropic differently shaped CaCO3 particles were synthesized using green sustainable approach based on co-precipitation of calcium chloride and sodium carbonate/bicarbonate at different ratios in the presence of organic additives. The impact of salts concentrations, reaction time, as well as organic additives was systematically researched to achieve controllable and reliable design of CaCO3 particles. It has been demonstrated that the crystallinity (vaterite or calcite phase) of particles depends on the initial salts concentrations. The loading capacity of prepared CaCO3 particles is determined by their surface properties such as specific surface area, pore size and zeta-potential. Differently shaped CaCO3 particles (spheroids, ellipsoids, toroids) were used to evaluate their uptake efficiency on the example of C6 glioma cells. The results show that the ellipsoidal particles possess a higher probability for internalization by cancer cells. All tested particles were also found to have a good biocompatibility. The capability to design physicochemical properties of CaCO3 particles has a significant impact on drug delivery applications, since the particles geometry substantially affects cell behavior (internalization, toxicity) and allows outperforming standard spherical counterparts.

The Facility for Antiproton and Ion Research (FAIR) in Darmstadt, Germany, provides unique possibilities for a new generation of hadron-, nuclear- and atomic physics experiments. The future antiProton ANnihilations at DArmstadt (PANDA or $\overline{\rm P}$ANDA) experiment at FAIR will offer a broad physics programme, covering different aspects of the strong interaction. Understanding the latter in the non-perturbative regime remains one of the greatest challenges in contemporary physics. The antiproton-nucleon interaction studied with PANDA provides crucial tests in this area. Furthermore, the high-intensity, low-energy domain of PANDA allows for searches for physics beyond the Standard Model, e.g. through high precision symmetry tests. This paper takes into account a staged approach for the detector setup and for the delivered luminosity from the accelerator. The available detector setup at the time of the delivery of the first antiproton beams in the HESR storage ring is referred to as the \textit{Phase One} setup. The physics programme that is achievable during Phase One is outlined in this paper., Comment: 35 pages, 15 figures