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Large language models (LLMs) have shown significant potential in guiding embodied agents to execute language instructions across a range of tasks, including robotic manipulation and navigation. However, existing methods are primarily designed for static environments and do not leverage the agent's own experiences to refine its initial plans. Given that real-world environments are inherently stochastic, initial plans based solely on LLMs' general knowledge may fail to achieve their objectives, unlike in static scenarios. To address this limitation, this study introduces the Experience-and-Emotion Map (E2Map), which integrates not only LLM knowledge but also the agent's real-world experiences, drawing inspiration from human emotional responses. The proposed methodology enables one-shot behavior adjustments by updating the E2Map based on the agent's experiences. Our evaluation in stochastic navigation environments, including both simulations and real-world scenarios, demonstrates that the proposed method significantly enhances performance in stochastic environments compared to existing LLM-based approaches. Code and supplementary materials are available at https://e2map.github.io/., Comment: 19 pages, 28 figures. Project page: https://e2map.github.io

Single-stranded RNA viruses co-assemble their capsid with the genome and variations in capsid structures can have significant functional relevance. In particular, viruses need to respond to a dehydrating environment to prevent genomic degradation and remain active upon rehydration. Theoretical work has predicted low-energy buckling transitions in icosahedral capsids which could protect the virus from further dehydration. However, there has been no direct experimental evidence, nor molecular mechanism, for such behaviour. Here we observe this transition using X-ray single particle imaging of MS2 bacteriophages after aerosolization. Using a combination of machine learning tools, we classify hundreds of thousands of single particle diffraction patterns to learn the structural landscape of the capsid morphology as a function of time spent in the aerosol phase. We found a previously unreported compact conformation as well as intermediate structures which suggest an incoherent buckling transition which does not preserve icosahedral symmetry. Finally, we propose a mechanism of this buckling, where a single 19-residue loop is destabilised, leading to the large observed morphology change. Our results provide experimental evidence for a mechanism by which viral capsids protect themselves from dehydration. In the process, these findings also demonstrate the power of single particle X-ray imaging and machine learning methods in studying biomolecular structural dynamics., Comment: 10 pages, 4 figures plus 9 pages supplementary information

In his ground-breaking work, K. Kato constructed the Euler system of Beilinson--Kato's zeta elements and proved spectacular results on the Iwasawa main conjecture for elliptic curves and the classical and $p$-adic Birch and Swinnerton-Dyer conjectures by using these elements. The goal of this expository lecture note is to explain how Kato's Euler systems fit into the framework of the arithmetic of elliptic curves and their Iwasawa theory, and we hope that this approach eventually helps the reader to read Kato's original paper more easily and with less pain., Comment: This is the refereed version. It is written for the proceedings of the ICTS program "Elliptic curves and the special values of $L$-functions". Several typos are corrected and the exposition is improved. Comments very welcome

We explicitly construct the rank one primitive Stark (equivalently, Kolyvagin) system extending a constant multiple of Flach's zeta elements for semi-stable elliptic curves. As its arithmetic applications, we obtain the equivalence between a specific behavior of the Stark system and the minimal modularity lifting theorem, and we also discuss the cyclicity of the adjoint Selmer groups. This Stark system construction yields a more refined interpretation of the collection of Flach's zeta elements than the "geometric Euler system" approach due to Flach, Wiles, Mazur, and Weston., Comment: The comparison with other recent work is given, as per the request. Comments are very welcome

In this short note, we study the anticyclotomic analogue of the "weak" main conjecture of Mazur-Tate on Fitting ideals of Selmer groups for elliptic curves with supersingular reduction., Comment: to appear in Bertolini's 60th birthday conference proceedings

Staying in the intensive care unit (ICU) is often traumatic, leading to post-intensive care syndrome (PICS), which encompasses physical, psychological, and cognitive impairments. Currently, there are limited interventions available for PICS. Studies indicate that exposure to visual art may help address the psychological aspects of PICS and be more effective if it is personalized. We develop Machine Learning-based Visual Art Recommendation Systems (VA RecSys) to enable personalized therapeutic visual art experiences for post-ICU patients. We investigate four state-of-the-art VA RecSys engines, evaluating the relevance of their recommendations for therapeutic purposes compared to expert-curated recommendations. We conduct an expert pilot test and a large-scale user study (n=150) to assess the appropriateness and effectiveness of these recommendations. Our results suggest all recommendations enhance temporal affective states. Visual and multimodal VA RecSys engines compare favourably with expert-curated recommendations, indicating their potential to support the delivery of personalized art therapy for PICS prevention and treatment., Comment: Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems (CHI 24)

X-ray Multi-Projection Imaging (XMPI) is an emerging technology that allows for the acquisition of millions of 3D images per second in samples opaque to visible light. This breakthrough capability enables volumetric observation of fast stochastic phenomena, which were inaccessible due to the lack of a volumetric X-ray imaging probe with kHz to MHz repetition rate. These include phenomena of industrial and societal relevance such as fractures in solids, propagation of shock waves, laser-based 3D printing, or even fast processes in the biological domain. Indeed, the speed of traditional tomography is limited by the shear forces caused by rotation, to a maximum of 1000 Hz in state-of-the-art tomography. Moreover, the shear forces can disturb the phenomena in observation, in particular with soft samples or sensitive phenomena such as fluid dynamics. XMPI is based on splitting an X-ray beam to generate multiple simultaneous views of the sample, therefore eliminating the need for rotation. The achievable performances depend on the characteristics of the X-ray source, the detection system, and the X-ray optics used to generate the multiple views. The increase in power density of the X-ray sources around the world now enables 3D imaging with sampling speeds in the kilohertz range at synchrotrons and megahertz range at X-ray Free-Electron Lasers (XFELs). Fast detection systems are already available, and 2D MHz imaging was already demonstrated at synchrotron and XFEL. In this work, we explore the properties of X-ray splitter optics and XMPI schemes that are compatible with synchrotron insertion devices and XFEL X-ray beams. We describe two possible schemes designed to permit large samples and complex sample environments. Then, we present experimental proof of the feasibility of MHz-rate XMPI at the European XFEL., Comment: 47 pages, 17 figures

We propose a scheme called MuNES for single mapping and trajectory planning including elevators and stairs. Optimized multifloor trajectories are important for optimal interfloor movements of robots. However, given two or more options of moving between floors, it is difficult to select the best trajectory because there are no suitable indoor multifloor maps in the existing methods. To solve this problem, MuNES creates a single multifloor map including elevators and stairs by estimating altitude changes based on pressure data. In addition, the proposed method performs floor-based loop detection for faster and more accurate loop closure. The single multifloor map is then voxelized leaving only the parts needed for trajectory planning. An optimal and realistic multifloor trajectory is generated by exploring the voxels using an A* algorithm based on the proposed cost function, which affects realistic factors. We tested this algorithm using data acquired from around a campus and note that a single accurate multifloor map could be created. Furthermore, optimal and realistic multifloor trajectory could be found by selecting the means of motion between floors between elevators and stairs according to factors such as the starting point, ending point, and elevator waiting time. The code and data used in this work are available at https://github.com/donghwijung/MuNES.

In cultured meat (CM) products the paramount significance lies in the fundamental attributes like texture and sensory of the processed end product. To cater to the tactile and gustatory preferences of real meat, the product needs to be designed to incorporate its texture and sensory attributes. Presently CM products are mainly grounded products like sausage, nugget, frankfurter, burger patty, surimi, and steak with less sophistication and need to mimic real meat to grapple with the traditional meat market. The existence of fibrous microstructure in connective and muscle tissues has attracted considerable interest in the realm of tissue engineering. Scaffolding plays an important role in CM production by aiding cell adhesion, growth, differentiation, and alignment. A wide array of scaffolding technologies has been developed for implementation in the realm of biomedical research. In recent years researchers also focus on edible scaffolding to ease the process of CM. However, it is imperative to implement cutting edge technologies like 3D scaffolds, 3D printing, electrospun nanofibers in order to advance the creation of sustainable and edible scaffolding methods in CM production, with the ultimate goal of replicating the sensory and nutritional attributes to mimic real meat cut. This review discusses recent advances in scaffolding techniques and biomaterials related to structured CM production and required advances to create muscle fiber structures to mimic real meat. Keywords: Cultured meat, Scaffolding, Biomaterials, Edible scaffolding, Electrospinning, 3D bioprinting, real meat.

Robotic agents trained using reinforcement learning have the problem of taking unreliable actions in an out-of-distribution (OOD) state. Agents can easily become OOD in real-world environments because it is almost impossible for them to visit and learn the entire state space during training. Unfortunately, unreliable actions do not ensure that agents perform their original tasks successfully. Therefore, agents should be able to recognize whether they are in OOD states and learn how to return to the learned state distribution rather than continue to take unreliable actions. In this study, we propose a novel method for retraining agents to recover from OOD situations in a self-supervised manner when they fall into OOD states. Our in-depth experimental results demonstrate that our method substantially improves the agent's ability to recover from OOD situations in terms of sample efficiency and restoration of the performance for the original tasks. Moreover, we show that our method can retrain the agent to recover from OOD situations even when in-distribution states are difficult to visit through exploration., Comment: 9 pages, 5 figures. Proceedings of the 32nd International Joint Conference on Artificial Intelligence, 2023