A Ukrainian soldier has described the moment a passenger train was targeted by Russian drones, killing five people. When a carriage on the train was hit in northeastern Ukraine, passengers threw themselves on the floor in panic and the military officer told them to get out immediately. Without his instruction, issued moments before the carriage burst into flames, many more passengers could have died. The officer, whose army call-sign is Omar, is part of Ukraine's 93rd brigade. He was among the passengers travelling on a route from Chop, on the border with Slovakia, to Barvinkove, the last stop before the front line in eastern Ukraine.

In cross-cultural recipe adaptation, the goal is not only to ensure cultural appropriateness and retain the original dish's essence, but also to provide diverse options for various dietary needs and preferences. Retrieval Augmented Generation (RAG) is a promising approach, combining the retrieval of real recipes from the target cuisine for cultural adaptability with large language models (LLMs) for relevance. However, it remains unclear whether RAG can generate diverse adaptation results. Our analysis shows that RAG tends to overly rely on a limited portion of the context across generations, failing to produce diverse outputs even when provided with varied contextual inputs. This reveals a key limitation of RAG in creative tasks with multiple valid answers: it fails to leverage contextual diversity for generating varied responses. To address this issue, we propose CARRIAGE, a plug-and-play RAG framework for cross-cultural recipe adaptation that enhances diversity in both retrieval and context organization. To our knowledge, this is the first RAG framework that explicitly aims to generate highly diverse outputs to accommodate multiple user preferences. Our experiments show that CARRIAGE achieves Pareto efficiency in terms of diversity and quality of recipe adaptation compared to closed-book LLMs.

In this work, we fabricated and studied two designs for omnidirectional vision sensors for swarm robotics, based on catadioptric systems consisting of a mirror with rotational symmetry, eight discrete infrared photodiodes and a single LED, in order to provide localization and navigation abilities for mobile robotic agents. We considered two arrangements for the photodiodes: one in which they point upward into the mirror, and one in which they point outward, perpendicular to the mirror. To determine which design offers a better field of view on the plane, as well as detection of distance and orientation between two agents, we developed a test rail with three degrees of freedom to experimentally and systematically measure the signal registered by the photodiodes of a given sensor (in a single readout) from the light emitted by another as functions of the distance and orientation. Afterwards, we processed and analyzed the experimental data to develop mathematical models for the mean response of a photodiode in each design. Finally, by numerically inverting the models, we compared the two designs in terms of their accuracy. Our results show that the design with the photodiodes pointing upward resolves better the distance, while the other resolves better the orientation of the emitting agent, both providing an omnidirectional field of view. Keywords: computer vision, catadioptric sensors, swarm robotics 1. Introduction Localization is a key factor in the implementation of navigation and motion control in mobile autonomous robotic systems. Several methods can be implemented for this purpose.

Handling large amounts of data has become a key for developing automated driving systems. Especially for developing highly automated driving functions, working with images has become increasingly challenging due to the sheer size of the required data. Such data has to satisfy different requirements to be usable in machine learning-based approaches. Thus, engineers need to fully understand their large image data sets for the development and test of machine learning algorithms. However, current approaches lack automatability, are not generic and are limited in their expressiveness. Hence, this paper aims to analyze a state-of-the-art text and image embedding neural network and guides through the application in the automotive domain. This approach enables the search for similar images and the search based on a human understandable text-based description. Our experiments show the automatability and generalizability of our proposed method for handling large data sets in the automotive domain.

Microorganisms such as algae and bacteria move in a viscous environment with extremely low Reynolds ($Re$), where the viscous drag dominates the inertial forces. They have adapted to this environment by developing specialized features such as whole-body deformations and flexible structures such as flagella (with various shapes, sizes, and numbers) that break the symmetry during the motion. In this study, we hypothesize that the changes in the flexibility of the flagella during a cycle of movement impact locomotion dynamics of flagellated locomotion. To test our hypothesis, we developed an autonomous, self-propelled robot with four flexible, multi-segmented flagella actuated together by a single DC motor. The stiffness of the flagella during the locomotion is controlled via a cable-driven mechanism attached to the center of the robot. Experimental assessments of the robot's swimming demonstrate that increasing the flexibility of the flagella during recovery stroke and reducing the flexibility during power stroke improves the swimming performance of the robot. Our results give insight into how these microorganisms manipulate their biological features to propel themselves in low viscous media and are of great interest to biomedical and research applications.

The Modular Automated Crop Array Online System (MACARONS) is an extensible, scalable, open hardware system for plant transport in automated horticulture systems such as vertical farms. It is specified to move trays of plants up to 1060mm x 630mm and 12.5kg at a rate of 100mm/s along the guide rails and 41.7mm/s up the lifts, such as between stations for monitoring and actuating plants. The cost for the construction of one grow unit of MACARONS is 144.96USD which equates to 128.85USD/m2 of grow area. The designs are released and meets the requirements of CERN-OSH-W, which includes step-by-step graphical build instructions and can be built by a typical technical person in one day at a cost of 1535.50USD. Integrated tests are included in the build instructions are used to validate against the specifications, and we report on a successful build. Through a simple analysis, we demonstrate that MACARONS can operate at a rate sufficient to automate tray loading/unloading, to reduce labour costs in a vertical farm.

The field of transportation and logistics has witnessed fundamental transformations in the last decade, due to the convergence of seemingly unrelated technologies. The fast pace of innovations has been particularly striking for an industry that had been relatively stagnant for a long time. Taxi services were born in England where a public coach service for hire was first documented in 1605. The Hackney Carriage Act, which legalized horse-drawn carriages for hire, was passed in Parliament in 1635, and a similar service was started in Paris in 1637. Public transit was invented by Blaise Pascal in 1662 through a service known as the "carriage," which was quite popular and operated for 15 years.

When a survey in 2015 revealed that more than half of Guangzhou's female commuters had experienced some form of sexual harassment ("inappropriate touching") on public transport, a handful of Chinese cities began reserving subway cars for female commuters. But the designated carriages, which were sometimes labelled in pink Chinese characters with floral adornments, did little to deter men from squeezing aboard. "When everyone is rushing to work, no one cares whether it is a female-only car or not," one commuter complained on weibo. Indeed, many men have either blatantly ignored the restrictions or were oblivious to women-only subway carriages. Enforcement has lacked teeth – in part because the metro system is so overcrowded.

With the rise of self-driving technologies, there is great speculation as to how this new world of autonomous transportation will impact the economy and society. Critics claim that industries will suffer, millions of people will lose their jobs, and society will overall be worse off. Optimists predict that along with new technologies will come new industries and new jobs, and with the benefits of self-driving cars, there will be a ripple of benefits into other aspects of life. Before exploring these different possibilities of what the future may be, let's take a journey to the past. Here we find civilizations at war, and one of the earliest forms of transportation: the chariot.

It's 7.40am on Monday morning and Stiofan Sexton is about to do something he has never done before – and he doesn't even know it. Waiting on the platform at Sydney's Chatswood station, he is one of the first thousand passengers on the new fully driverless Metro Northwest in its first weekday rush-hour test. He used to take a slow bus up to work in North Ryde. Now he steps on to a carriage that goes up to 100km/h, along a 66km track, with service every four minutes, all run by a single computer. Asked by Guardian Australia how he feels about the fully automated train, he says he did not realise it was.