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Abstract This article introduces and formalizes a novel stochastic method that combines inverse simulation with the theory of generalized Polynomial Chaos (gPC) to solve and study inverse problems under uncertainty in energy system design applications. The method is particularly relevant to design tasks where only a deterministic forward model of a physical system is available, in which a target design quantity is an input to the model that cannot be obtained directly, but can be quantified reversely via the outputs of the model. In this scenario, the proposed method offers an analytical and direct approach to invert such system models. The method puts emphasis on user-friendliness, as it enables its users to conduct the inverse simulation under uncertainty directly in the gPC domain by redefining basic algebra operations for computations. Moreover, the method incorporates an optimization-based approach to integrate supplementary constraints on stochastic quantities. This feature enables the solution of inverse problems bounding the statistical moments of stochastic system variables. The authors exemplify the application of the proposed method with proof-of-concept tests in energy system design, specifically performing uncertainty quantification and sensitivity analysis for a Multi-Energy System (MES). The findings demonstrate the high accuracy of the method as well as clear advantages over conventional sampling-based methods when dealing with a small number of stochastic variables in a system or model. However, the case studies also highlight the current limitations of the proposed method such as slow execution speed due to the optimization-based approach and the challenges associated with, for example, the curse of dimensionality in gPC.

Abstract Many ants establish foraging routes through learning views of the visual panorama. Route models have focused primarily on attractive view use, which experienced foragers orient towards to return to known sites. However, aversive views have recently been uncovered as a key component of route learning. Here, Cataglyphis velox rapidly learned aversive views, when associated with a negative outcome, a period of captivity in vegetation, triggering increases in hesitation behavior. These memories were based on the accumulation of experiences over multiple trips with each new experience regulating forager hesitancy. Foragers were also sensitive to captivity time differences, suggesting they possess some mechanism to quantify duration. Finally, we analyzed foragers' perception of risky (i.e. variable) versus stable aversive outcomes by associating two sites along the route with distinct captivity schedules, a fixed or variable duration, with the same mean across training. Foragers exhibited fewer hesitations in response to risky outcomes compared to fixed ones, indicating they perceived risky outcomes as less severe. Results align with a logarithmic relationship between captivity duration and hesitations, suggesting that aversive stimulus perception is a logarithm of its actual value. We discuss how aversive view learning could be executed within the mushroom bodies circuitry following a prediction error rule.

The increasing popularity of virtual, augmented, and mixed reality (VR/AR/MR) applications is driving the media industry to explore the creation and delivery of new immersive experiences. One of the trends is volumetric video, which allows users to explore content unconstrained by the traditional two-dimensional window of director’s view.The ISO/IEC joint technical committee 1 subcommittee 29, better known as the Moving Pictures Experts Group (MPEG), has recently finalized a group of standards, under the umbrella of Visual Volumetric Video-based Coding (V3C). These standards aim to efficiently code, store, and transport immersive content with 6 degrees of freedom. The V3C family of standards currently consists of three documents: 1) ISO/IEC 23090-5 defines the generic concepts of volumetric video-based coding and its application to dynamic point cloud data; 2) ISO/IEC 23090-12 specifies another application that enables compression of volumetric video content captured by multiple cameras; and 3) ISO/IEC 23090-10 describes how to store and deliver V3C compressed volumetric video content. Each standard leverages the capabilities of traditional 2D video coding and delivery solutions, allowing for re-use of existing infrastructures which facilitates fast deployment of volumetric video.This article provides an overview of the generic concepts of V3C, as defined in ISO/IEC 23090-5. Furthermore, it describes V3C carriage related functionalities specified in ISO/IEC 23090-10 and offers best practices for the community with respect to storage and delivery of volumetric video.

We introduce the open-source Python software framework pycity_scheduling for the effective development, testing, and assessment of optimisation-based power scheduling algorithms for local multi-energy systems in city districts. The framework primarily targets the elaboration of coordination concepts that can efficiently solve the power dispatch problem on the city district level. Its target users are researchers in the field of smart grid applications and the deployment of operational flexibility for local energy systems. Illustrative code examples demonstrate the capabilities of the pycity_scheduling framework and its use cases. The design principles established in pycity_scheduling allows users to access, extend, and modify the Python package without any need for commercial software or licensing concerns.

In this article a gateway module to integrate legacy laboratory devices into the network of the digital laboratory in the 21st century is introduced. The device is based on ready to buy consumer hardware that is easy to get and inexpensive. Depending on the specific requirements of the desired application (bare embedded computer, RS232 serial port connector, IP65 certified casing and connectors) the needed investment ranges from about 95 € up to 200 €. The embedded computer runs an open source Linux operating system and can in principle be used to run any kind of software needed for communicating with the laboratory device. Here the open source SiLA2 standard is used for presenting the device’s functions in the network. As an example the digital integration of a magnetic stirrer is shown and can be used as a template for other applications. A method for easy remote integration of the device to ensure an easy and consistent workflow in development, testing and usage is also presented. This incorporates a method for remote installation of SiLA2 servers on the box as well as a web frontend for administration, debugging and management of those.

Rolling bearings have to meet the highest requirements in terms of guidance accuracy, energy efficiency, and dynamics. An important factor influencing these performance criteria is the cage, which has different effects on the bearing dynamics depending on the cage’s geometry and bearing load. Dynamics simulations can be used to calculate cage dynamics, which exhibit high agreement with the real cage motion, but are time-consuming and complex. In this paper, machine learning algorithms were used for the first time to predict physical cage related performance criteria in an angular contact ball bearing. The time-efficient prediction of the machine learning algorithms enables an estimation of the dynamic behavior of a cage for a given load condition of the bearing within a short time. To create a database for machine learning, a simulation study consisting of 2000 calculations was performed to calculate the dynamics of different cages in a ball bearing for several load conditions. Performance criteria for assessing the cage dynamics and frictional behavior of the bearing were derived from the calculation results. These performance criteria were predicted by machine learning algorithms considering bearing load and cage geometry. The predictions for a total of 10 target variables reached a coefficient of determination of R2≈0.94 for the randomly selected test data sets, demonstrating high accuracy of the models.

During the course of evolution, up until the agricultural revolution, environmental fluctuations forced the human species to develop a flexible metabolism in order to adapt its energy needs to various climate, seasonal and vegetation conditions. Metabolic flexibility safeguarded human survival independent of food availability. In modern times, humans switched their primal lifestyle towards a constant availability of energy-dense, yet often nutrient-deficient, foods, persistent psycho-emotional stressors and a lack of exercise. As a result, humans progressively gain metabolic disorders, such as the metabolic syndrome, type 2 diabetes, non-alcoholic fatty liver disease, certain types of cancer, cardiovascular disease and Alzheimer´s disease, wherever the sedentary lifestyle spreads in the world. For more than 2.5 million years, our capability to store fat for times of food shortage was an outstanding survival advantage. Nowadays, the same survival strategy in a completely altered surrounding is responsible for a constant accumulation of body fat. In this article, we argue that the metabolic disease epidemic is largely based on a deficit in metabolic flexibility. We hypothesize that the modern energetic inflexibility, typically displayed by symptoms of neuroglycopenia, can be reversed by re-cultivating suppressed metabolic programs, which became obsolete in an affluent environment, particularly the ability to easily switch to ketone body and fat oxidation. In a simplified model, the basic metabolic programs of humans’ primal hunter-gatherer lifestyle are opposed to the current sedentary lifestyle. Those metabolic programs, which are chronically neglected in modern surroundings, are identified and conclusions for the prevention of chronic metabolic diseases are drawn.

During the course of evolution, up until the agricultural revolution, environmental fluctuations forced the human species to develop a flexible metabolism in order to adapt its energy needs to various climate, seasonal and vegetation conditions. Metabolic flexibility safeguarded human survival independent of food availability. In modern times, humans switched their primal lifestyle towards a constant availability of energy-dense, yet often nutrient-deficient, foods, persistent psycho-emotional stressors and a lack of exercise. As a result, humans progressively gain metabolic disorders, such as the metabolic syndrome, type 2 diabetes, non-alcoholic fatty liver disease, certain types of cancer, cardiovascular disease and Alzheimer´s disease, wherever the sedentary lifestyle spreads in the world. For more than 2.5 million years, our capability to store fat for times of food shortage was an outstanding survival advantage. Nowadays, the same survival strategy in a completely altered surrounding is responsible for a constant accumulation of body fat. In this article, we argue that the metabolic epidemic is largely based on a deficit in metabolic flexibility. We hypothesize that the modern energetic inflexibility, typically displayed by symptoms of neuroglycopenia, can be reversed by re-cultivating suppressed metabolic programs, which became obsolete in an affluent environment, particularly the ability to easily switch to ketone body and fat oxidation. In a simplified model, the basic metabolic programs of humans’ primal hunter-gatherer lifestyle are opposed to the current sedentary lifestyle. Those metabolic programs, which are chronically neglected in modern surroundings, are identified and conclusions for the prevention of chronic metabolic diseases are drawn.

Even after years of research on navigation in the Red Honey Ant, Melophorus bagoti, much of its life history remains elusive. Here, we present observations on nest relocation and the reproductive and founding stages of colonies. Nest relocation is possibly aided by trail laying behaviour, which is highly unusual for solitary foraging desert ants. Reproduction occurs in synchronised mating flights, which are probably triggered by rain. Queens may engage in multiple matings, and there is circumstantial evidence that males are chemically attracted to queens. After the mating flight, the queens found new colonies independently and singly. Excavation of these founding colonies reveals first insights into their structure.