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According to Ethan Mollick, artificial intelligence (AI) is the most recent general purpose technology (GPT), the “once-in-a-generation technologies, like steam power or the internet, that touch every industry and every aspect of life” (2024, p. xv). Unlike the slowly unfolding transformations caused by these earlier GPTs, the changes sparked by AI seem to evolve daily. This rapid pace creates a s

Microhabitat choice has been proposed as a mechanism contributing to the maintenance of colour polymorphism in marine gastropods, based on observed associations between shell colour and microhabitat in certain species (e.g. Littorina saxatilis). To examine this hypothesis, different colour morphs of L. saxatilis were studied following a mark-recapture experimental design to assess whether this spe

Context. Stellar radial migration has predominantly been examined in isolated disc galaxies where non-axisymmetric structures drive the process. By contrast, while tidal interactions are known for having an influence, their contribution remains comparatively under explored. The Large Magellanic Cloud (LMC), the nearest disc galaxy to the Milky Way (MW) and currently interacting with the Small Mage

An autonomous service robot should be able to interact with its environment safely and robustly without requiring human assistance. Unstructured environments are challenging for robots since the exact prediction of outcomes is not always possible. Even when the robot behaviors are well-designed, the unpredictable nature of the physical robot-object interaction may lead to failures in object manipu

Sensor degradation poses a significant challenge in autonomous driving. During heavy rainfall, interference from raindrops can adversely affect the quality of LiDAR point clouds, resulting in, for instance, inaccurate point measurements. This, in turn, can potentially lead to safety concerns if autonomous driving systems are not weather-aware, i.e., if they are unable to discern such changes. In t

Robots are more capable of achieving manipulation tasks for everyday activities than before. However, the safety of manipulation skills that robots employ is still an open problem. Considering all possible failures during skill learning increases the complexity of the process and restrains learning an optimal policy. Nonetheless, safety-focused modularity in the acquisition of skills has not been

In this work, we present a simple yet effective framework to address the domain translation problem between different sensor modalities with unique data formats. By relying only on the semantics of the scene, our modular generative framework can, for the first time, synthesize a panoramic color image from a given full 3D LiDAR point cloud.The framework starts with semantic segmentation of the poin

A cell’s ability to sense and respond to the mechanical properties of the extracellular matrix (ECM) is essential for maintaining tissue homeostasis, and its disruption contributes to diseases such as fibrosis, cardiovascular disorders, and cancer. Effective mechanical coupling between the plasma membrane, the underlying filamentous actin (F-actin) cytoskeleton, and integrin-based adhesion complex

Effective environmental policies for the tropics depend on accurate, representative scientific data. However, there is strong evidence from particular disciplines and regions that existing research is patchily distributed. Here, we show that poor representation of sampling and citation in some biomes and across key environmental gradients from all disciplines for the entire tropics may lead to fla

Background: The aim was to evaluate whether an artificial intelligence (AI)-based tool for the automated quantification of the total metabolic tumour volume (tMTV) in patients with Hodgkin lymphoma (HL) could support nuclear medicine specialists in lesion segmentation and thereby enhance inter-observer agreement. Methods: Forty-eight consecutive patients who underwent staging with [18F]FDG PET/CT

In this paper, we present a new approach for facial anonymization in images and videos, abbreviated as FIVA. Our proposed method is able to maintain the same face anonymization consistently over frames with our suggested identity-tracking and guarantees a strong difference from the original face. FIVA allows for 0 true positives for a false acceptance rate of 0.001. Our work considers the importan

The testing and safety cases of assisted and automated driving (AAD) functions require considerations for nonideal environmental conditions, such as adverse and extreme weather. In these extreme conditions, perception sensors (e.g., camera, LiDAR, and RADAR), which build the situational awareness of the vehicle, might produce noisy and degraded data. Therefore, it is key to consider: 1) how to rel

The compression of deep learning models is of fundamental importance in deploying such models to edge devices. The selection of compression parameters can be automated to meet changes in the hardware platform and application. This article introduces a Multi-Objective Hardware-Aware Quantization (MOHAQ) method, which considers hardware performance and inference error as objectives for mixed-precisi

Smart cities and communities (SCC) constitute a new paradigm in urban development. SCC ideate a data-centered society aimed at improving efficiency by automating and optimizing activities and utilities. Information and communication technology along with Internet of Things enables data collection and with the help of artificial intelligence (AI) situation awareness can be obtained to feed the SCC

We present a novel deep neural network architecture for representing robot experiences in an episodic-like memory that facilitates encoding, recalling, and predicting action experiences. Our proposed unsupervised deep episodic memory model as follows: First, encodes observed actions in a latent vector space and, based on this latent encoding, second, infers most similar episodes previously experie

Recognition of human manipulation actions together with the analysis and execution by a robot is an important issue. Also, perception of spatial relationships between objects is central to understanding the meaning of manipulation actions. Here we would like to merge these two notions and analyze manipulation actions using symbolic spatial relations between objects in the scene. Specifically, we d

Understanding continuous human actions is a non-trivial but important problem in computer vision. Although there exists a large corpus of work in the recognition of action sequences, most approaches suffer from problems relating to vast variations in motions, action combinations, and scene contexts. In this paper, we introduce a novel method for semantic segmentation and recognition of long and co