Fractional release factors of long-lived halogenated organic compounds in the tropical stratosphere

Fractional release factors (FRFs) of organic trace gases are time-independent quantities that influence the calculation of Global Warming Potentials and Ozone Depletion Potentials. We present the first set of vertically resolved FRFs for 15 long-lived halocarbons in the tropical stratosphere up to 34 km altitude. They were calculated from measurements on air samples collected on board balloons and a high altitude aircraft. We compare the derived dependencies of FRFs on the mean stratospheric transit times (the so-called mean ages of air) with similarly derived FRFs originating from measurements at higher latitudes and find significant differences. Moreover a comparison with averaged FRFs currently used by the World Meteorological Organisation revealed the limitations of these measures due to their observed vertical and latitudinal variability. The presented data set could be used to improve future ozone level and climate projections

A hybrid model for day-ahead electricity price forecasting: Combining fundamental and stochastic modelling

The accurate prediction of short-term electricity prices is vital for effective trading strategies, power plant scheduling, profit maximisation and efficient system operation. However, uncertainties in supply and demand make such predictions challenging. We propose a hybrid model that combines a techno-economic energy system model with stochastic models to address this challenge. The techno-economic model in our hybrid approach provides a deep understanding of the market. It captures the underlying factors and their impacts on electricity prices, which is impossible with statistical models alone. The statistical models incorporate non-techno-economic aspects, such as the expectations and speculative behaviour of market participants, through the interpretation of prices. The hybrid model generates both conventional point predictions and probabilistic forecasts, providing a comprehensive understanding of the market landscape. Probabilistic forecasts are particularly valuable because they account for market uncertainty, facilitating informed decision-making and risk management. Our model delivers state-of-the-art results, helping market participants to make informed decisions and operate their systems more efficiently

Accuracy of a magnetic resonance imaging‐based 3D printed stereotactic brain biopsy device in dogs

Background: Brain biopsy of intracranial lesions is often necessary to determine specific therapy. The cost of the currently used stereotactic rigid frame and optical tracking systems for brain biopsy in dogs is often prohibitive or accuracy is not sufficient for all types of lesion. Objectives: To evaluate the application accuracy of an inexpensive magnetic resonance imaging‐based personalized, 3D printed brain biopsy device. Animals: Twenty‐two dog heads from cadavers were separated into 2 groups according to body weight (20 kg). Methods: Experimental study. Two target points in each cadaver head were used (target point 1: caudate nucleus, target point 2: piriform lobe). Comparison between groups was performed using the independent Student's t test or the nonparametric Mann‐Whitney U Test. Results: The total median target point deviation was 0.83 mm (range 0.09‐2.76 mm). The separate median target point deviations for target points 1 and 2 in all dogs were 0.57 mm (range: 0.09‐1.25 mm) and 0.85 mm (range: 0.14‐2.76 mm), respectively. Conclusion and Clinical Importance: This magnetic resonance imaging‐based 3D printed stereotactic brain biopsy device achieved an application accuracy that was better than the accuracy of most brain biopsy systems that are currently used in veterinary medicine. The device can be applied to every size and shape of skull and allows precise positioning of brain biopsy needles in dogs

Density of neutral interstellar hydrogen at the termination shock from Ulysses pickup ion observations

By reevaluating a 13-month stretch of Ulysses SWICS H pickup ion measurements near 5 AU close to the ecliptic right after the previous solar minimum, this paper presents a determination of the neutral interstellar H density at the solar wind termination shock and implications for the density and ionization degree of hydrogen in the LIC. The density of neutral interstellar hydrogen at the termination shock was determined from the local pickup ion production rate as obtained close to the cut-off in the distribution function at aphelion of Ulysses. As shown in an analytical treatment for the upwind axis and through kinetic modeling of the pickup ion production rate at the observer location, with variations in the ionization rate, radiation pressure, and the modeling of the particle behavior, this analysis turns out to be very robust against uncertainties in these parameters and the modeling. Analysis using current heliospheric parameters yields the H density at the termination shock equal to $0.087\pm0.022$ cm$^{-3}$, including observational and modeling uncertainties.Comment: Re-edited version, density revised downward due to data re-processing, accepted by A&

Observations of interstellar helium pickup ions in the inner heliosphere

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98161/1/jgra50227.pd

Industrial DevOps

The visions and ideas of Industry 4.0 require a profound interconnection of machines, plants, and IT systems in industrial production environments. This significantly increases the importance of software, which is coincidentally one of the main obstacles to the introduction of Industry 4.0. Lack of experience and knowledge, high investment and maintenance costs, as well as uncertainty about future developments cause many small and medium-sized enterprises hesitating to adopt Industry 4.0 solutions. We propose Industrial DevOps as an approach to introduce methods and culture of DevOps into industrial production environments. The fundamental concept of this approach is a continuous process of operation, observation, and development of the entire production environment. This way, all stakeholders, systems, and data can thus be integrated via incremental steps and adjustments can be made quickly. Furthermore, we present the Titan software platform accompanied by a role model for integrating production environments with Industrial DevOps. In two initial industrial application scenarios, we address the challenges of energy management and predictive maintenance with the methods, organizational structures, and tools of Industrial DevOps.Comment: 10 page

Predictive Attentional Bias Modification Induces Stimulus-Evoked Attentional Bias for Threat

Attention Bias Modification (ABM) aims to modulate attentional biases, but questions remain about its efficacy and there may be new variants yet to explore. The current study tested effects of a novel version of ABM, predictive ABM (predABM), using visually neutral cues predicting the locations of future threatening and neutral stimuli that had a chance of appearing after a delay. Such effects could also help understand anticipatory attentional biases measured using cued Visual Probe Tasks. 102 participants completed the experiment online. We tested whether training Towards Threat versus Away from Threat contingencies on the predABM would cause subsequent attentional biases towards versus away from threat versus neutral stimuli, respectively. Participants were randomly assigned and compared on attentional bias measured via a post-training Dot-Probe task. A significant difference was found between the attentional bias in the Towards Threat versus Away from Threat group. The training contingencies induced effects on bias in the expected direction, although the bias in each group separately did not reach significance. Stronger effects may require multiple training sessions. Nevertheless, the primary test confirmed the hypothesis, showing that the predABM is a potentially interesting variant of ABM. Theoretically, the results show that automatization may involve the process of selecting the outcome of a cognitive response, rather than a simple stimulus-response association. Training based on contingencies involving predicted stimuli affect subsequent attentional measures and could be of interest in future clinical studies