In 2023, images on the web make up 41% of transmitted data, significantly impacting the performance of web apps. Fortunately, image formats like WEBP and AVIF could offer advanced compression and faster page loading but may face performance disparities across browsers. Therefore, we conducted performance evaluations on five major browsers - Chrome, Edge, Safari, Opera, and Firefox - while comparing four image formats. The results indicate that the newer formats exhibited notable performance enhancements across all browsers, leading to shorter loading times. Compared to the compressed JPEG format, WEBP and AVIF improved the Page Load Time by 21% and 15%, respectively. However, web scraping revealed that JPEG and PNG still dominate web image choices, with WEBP at 4% as the most used new format. Through the web scraping and web performance evaluation, this research serves to (1) explore image format preferences in web applications and analyze distribution and characteristics across frequently-visited sites in 2023 and (2) assess the performance impact of distinct web image formats on application load times across popular web browsers.
The success of a web application is closely linked to its performance, which positively impacts user satisfaction and contributes to energy-saving efforts. Among the various optimization techniques, one specific subject focuses on improving the utilization of web fonts. This study investigates the impact of different font formats on client-side resource consumption, such as CPU, memory, load time, and energy. In a controlled experiment, we evaluate performance metrics using the four font formats: OTF, TTF, WOFF, and WOFF2. The results of the study show that there are significant differences between all pair-wise format comparisons regarding all performance metrics. Overall, WOFF2 performs best, except in terms of memory allocation. Through the study and examination of literature, this research contributes (1) an overview of methodologies to enhance web performance through font utilization, (2) a specific exploration of the four prevalent font formats in an experimental setup, and (3) practical recommendations for scientific professionals and practitioners.
Systems that use Machine Learning (ML) have become commonplace for companies that want to improve their products and processes. Literature suggests that Requirements Engineering (RE) can help address many problems when engineering ML-enabled systems. However, the state of empirical evidence on how RE is applied in practice in the context of ML-enabled systems is mainly dominated by isolated case studies with limited generalizability. We conducted an international survey to gather practitioner insights into the status quo and problems of RE in ML-enabled systems. We gathered 188 complete responses from 25 countries. We conducted quantitative statistical analyses on contemporary practices using bootstrapping with confidence intervals and qualitative analyses on the reported problems involving open and axial coding procedures. We found significant differences in RE practices within ML projects. For instance, (i) RE-related activities are mostly conducted by project leaders and data scientists, (ii) the prevalent requirements documentation format concerns interactive Notebooks, (iii) the main focus of non-functional requirements includes data quality, model reliability, and model explainability, and (iv) main challenges include managing customer expectations and aligning requirements with data. The qualitative analyses revealed that practitioners face problems related to lack of business domain understanding, unclear goals and requirements, low customer engagement, and communication issues. These results help to provide a better understanding of the adopted practices and of which problems exist in practical environments. We put forward the need to adapt further and disseminate RE-related practices for engineering ML-enabled systems.
This work presents a novel shared control architecture dedicated to teleoperated contact tasks. We use Learning from Demonstration as a framework to learn a task model that encodes the desired motions, forces and stiffness profiles. Then, the learnt information is used by a Virtual Fixture (VF) to guide the human operator along a nominal task trajectory that captures the task dynamics, while simultaneously adapting the remote robot impedance. Furthermore, we provide haptic guidance in a human-aware manner. To that end, we propose a control law that eliminates time dependency and depends only on the current human state, inspired by the path and flow control formulations used in the exoskeleton literature , . The proposed approach is validated in a user study where we test the guidance effect for the bilateral teleoperation of a drawing and a wiping task. The experimental results reveal a statistically significant improvement in several metrics, compared to teleoperation without guidance.
We present a method to calculate the asymptotic behavior of eigenfunctions of Schrödinger operators that also works at the threshold of the essential spectrum. It can be viewed as a higher order correction to the well-known WKB method which does need a safety distance to the essential spectrum. We illustrate its usefulness on examples of quantum particles in a potential well with a long-range repulsive term outside the well.
In this paper, we present a novel learning-based shared control framework. This framework deploys first-order Dynamical Systems (DS) as motion generators providing the desired reference motion, and a Variable Stiffness Dynamical Systems (VSDS) (Chen et al. 2021) for haptic guidance. We show how to shape several features of our controller in order to achieve authority allocation, local motion refinement, in addition to the inherent ability of the controller to automatically synchronize with the human state during joint task execution. We validate our approach in a teleoperated task scenario, where we also showcase the ability of our framework to deal with situations that require updating task knowledge due to possible changes in the task scenario, or changes in the environment. Finally, we conduct a user study to compare the performance of our VSDS controller for guidance generation to two state-of-the-art controllers in a target reaching task. The result shows that our VSDS controller has the highest successful rate of task execution among all conditions. Besides, our VSDS controller helps reduce the execution time and task load significantly, and was selected as the most favorable controller by participants.
Joule heating is one of the main energy inputs into the thermosphere-ionosphere system. Precise modeling of this process is essential for any space weather application. Existing ionosphere models tend to underestimate the actual Joule heating rate quite significantly. The Thermosphere-Ionosphere-Electrodynamics General-Circulation-Model applies an empirical scaling factor of 1.5 for compensation. We calculate vertical profiles of Joule heating rates from approximately 2220 h of measurements with the EISCAT incoherent scatter radar and the corresponding model runs. We investigate model runs with the plasma convection driven by both the Heelis and the Weimer model. The required scaling of the Joule heating profiles is determined with respect to the Kp index, the Kan-Lee merging electric field EKL, and the magnetic local time. Though the default scaling factor of 1.5 appears to be adequate on average, we find that the required scaling varies strongly with all three parameters ranging from 0.46 to ∼20 at geomagnetically disturbed and quiet times, respectively. Furthermore, the required scaling is significantly different in runs driven by the Heelis and Weimer model. Adjusting the scaling factor with respect to the Kp index, EKL, the magnetic local time, and the choice of convection model would reduce the difference between measurement and model results.
In view of the increasing number of space objects, comprehensive high‐quality space surveillance becomes ever more important. Radar is a powerful tool that, in addition to detection and tracking of objects, also enables spatially high‐resolution imaging independent of daylight and most weather conditions. Together with the technique of Inverse Synthetic Aperture Radar (ISAR), very high‐resolution and distance‐independent two‐dimensional images can be obtained. However, advanced high‐performance radar imaging of space objects is a complex and demanding task, touching many technological and signal processing issues. Therefore, besides theoretical work, the Microwaves and Radar Institute of German Aerospace Center (DLR) has developed and constructed an experimental radar system called IoSiS (Imaging of Satellites in Space) for basic research on new concepts for the acquisition of advanced high‐resolution radar image products of objects in a low earth orbit. Based on pulse radar technology, which enables precise calibration and error correction, IoSiS has imaged space objects with a spatial resolution in the centimetre range, being novel in public perception and accessible literature. The goal of this paper is therefore to communicate and illustrate comprehensively the technological steps for the construction and successful operation of advanced radar‐based space surveillance. Besides the basic description of the IoSiS system design this paper outlines primarily useful theory for ISAR imaging of objects in space, together with relevant imaging parameters and main formulae. All relevant processing steps, necessary for very high‐resolution imaging of satellites in practice, are introduced and verified by simulation results. Finally, a unique measurement result demonstrates the practicability of the introduced processing steps and error correction strategies.
Blood volume (BV) is an important clinical parameter and is usually reported per kg of body mass (BM). When fat mass is elevated, this underestimates BV/BM. One aim was to study if differences in BV/BM related to sex, age, and fitness would decrease if normalized to lean body mass (LBM). The analysis included 263 women and 319 men (age: 10–93 years, body mass index: 14–41 kg/m²) and 107 athletes who underwent assessment of BV and hemoglobin mass (Hbmass), body composition, and cardiorespiratory fitness. BV/BM was 25% lower (70.3 ± 11.3 and 80.3 ± 10.8 mL/kgBM) in women than men, respectively, whereas BV/LBM was 6% higher in women (110.9 ± 12.5 and 105.3 ± 11.2 mL/kgLBM). Hbmass/BM was 34% lower (8.9 ± 1.4 and 11.5 ± 11.2 g/kgBM) in women than in men, respectively, but only 6% lower (14.0 ± 1.5 and 14.9 ± 1.5 g/kgLBM)/LBM. Age did not affect BV. Athlete's BV/BM was 17.2% higher than non‐athletes, but decreased to only 2.5% when normalized to LBM. Of the variables analyzed, LBM was the strongest predictor for BV (R² = .72, p < .001) and Hbmass (R² = .81, p < .001). These data may only be valid for BV/Hbmass when assessed by CO re‐breathing. Hbmass/LBM could be considered a valuable clinical matrix in medical care aiming to normalize blood homeostasis.
The complexity of the human shoulder girdle enables the large mobility of the upper extremity, but also introduces instability of the glenohumeral (GH) joint. Shoulder movements are generated by coordinating large superficial and deeper stabilizing muscles spanning numerous degrees-of-freedom. How shoulder muscles are coordinated to stabilize the movement of the GH joint remains widely unknown. Musculoskeletal simulations are powerful tools to gain insights into the actions of individual muscles and particularly of those that are difficult to measure. In this study, we analyze how enforcement of GH joint stability in a musculoskeletal model affects the estimates of individual muscle activity during shoulder movements. To estimate both muscle activity and GH stability from recorded shoulder movements, we developed a Rapid Muscle Redundancy (RMR) solver to include constraints on joint reaction forces (JRFs) from a musculoskeletal model. The RMR solver yields muscle activations and joint forces by minimizing the weighted sum of squared-activations, while matching experimental motion. We implemented three new features: first, computed muscle forces include active and passive fiber contributions; second, muscle activation rates are enforced to be physiological, and third, JRFs are efficiently formulated as linear functions of activations. Muscle activity from the RMR solver without GH stability was not different from the computed muscle control (CMC) algorithm and electromyography of superficial muscles. The efficiency of the solver enabled us to test over 3600 trials sampled within the uncertainty of the experimental movements to test the differences in muscle activity with and without GH joint stability enforced. We found that enforcing GH stability significantly increases the estimated activity of the rotator cuff muscles but not of most superficial muscles. Therefore, a comparison of shoulder model muscle activity to EMG measurements of superficial muscles alone is insufficient to validate the activity of rotator cuff muscles estimated from musculoskeletal models.
Large-scale simulations often require frequent checks on global conditions that are not directly needed for the computation itself. While such health checks are not an integral part of the numerical algorithm, they serve an important role in controlling and coordinating the simulation. In distributed parallel computations their required communication may negatively impact the actual parallel computation and result in unnecessary synchronization points. We show that by using a non-blocking reduction these synchronization requirements can be loosened and the impact on the actual computation minimized. Further, it enables us to shift the communication into the background and progress it during the MPI calls that are done during the computation anyway. We demonstrate that a sufficient amount of MPI calls in between is required to allow for progress to happen. The presented approach delays the decision to be made in response to those health checks. But as it is not vital for the correct computation itself such a delay is usually tolerable and could offer a more robust scaling to large process counts.
Plain Language Summary The knowledge of the crustal structure of Mars is essential for understanding the formation and evolution of the planet. Thanks to the Very Broadband Seismometer of the InSight mission which landed on the surface of Mars (its operational life lasted almost four terrestrial years), seismic signals generated by meteoroid impacts have been recorded. Five craters have been identified by orbital imaging to be located within a circle of ∼250 km radius around the lander. For two of these meteoroid impacts, we measured surface waves for the first time, which are mostly sensitive to the crustal structure in the first kilometers below the InSight lander. Our surface wave analysis, in combination with other measurements, are compatible with a crustal model in the vicinity of the InSight lander made of four layers, with a shallow low velocity layer ∼1.2 km thick. We verified the compatibility of our results with independent observations from previous studies.
Planets with radii between that of the Earth and Neptune (hereafter referred to as ‘sub-Neptunes’) are found in close-in orbits around more than half of all Sun-like stars1,2. However, their composition, formation and evolution remain poorly understood³. The study of multiplanetary systems offers an opportunity to investigate the outcomes of planet formation and evolution while controlling for initial conditions and environment. Those in resonance (with their orbital periods related by a ratio of small integers) are particularly valuable because they imply a system architecture practically unchanged since its birth. Here we present the observations of six transiting planets around the bright nearby star HD 110067. We find that the planets follow a chain of resonant orbits. A dynamical study of the innermost planet triplet allowed the prediction and later confirmation of the orbits of the rest of the planets in the system. The six planets are found to be sub-Neptunes with radii ranging from 1.94R⊕ to 2.85R⊕. Three of the planets have measured masses, yielding low bulk densities that suggest the presence of large hydrogen-dominated atmospheres.
The article presents a new analytical equation for calculating the Nu number in a macroporous structure of channel absorbers for high- temperature solar receivers. This equation is characterized by including the processes of heat and mass transfer in the boundary layers when the flow passes through a macroporous absorber channel of complex shape. The necessity of considering the length of the thermodynamic boundary layer in a macroporous medium of channel type, when calculating the heat transfer coefficient according to the Nusselt equation, is shown. Including the proposed indicators of porosity and flow characteristics in a macroporous channel significantly increases the accuracy of calculations of the heat transfer coefficient for macroporous channel media. The lack of consideration of certain of the proposed values in the Nusselt number for macroporous media explains the discrepancies in the existing calculation relationships and experiments. The empirical coefficients for the Nusselt number are proposed and obtained by the statistical method. The new semi-empirical equation obtained for macroporous channel media is applied to macroporous absorbers of solar receivers. The obtained results will help to predict the characteristics of future macroporous absorbers much more accurately than before to make them more efficient. The obtained equation for calculating the Nusselt number for channel-like macroporous absorbers has been successfully tested for the receiver of concentrated solar power plants with different geometric structure of the absorber.
Planetary Radio Interferometry and Doppler Experiment (PRIDE) is a multi-purpose experimental technique aimed at enhancing the science return of planetary missions. The technique exploits the science payload and spacecraft service systems without requiring a dedicated onboard instrumentation or imposing on the existing instrumentation any special for PRIDE requirements. PRIDE is based on the near-field phase-referencing Very Long Baseline Interferometry (VLBI) and evaluation of the Doppler shift of the radio signal transmitted by spacecraft by observing it with multiple Earth-based radio telescopes. The methodology of PRIDE has been developed initially at the Joint Institute for VLBI ERIC (JIVE) for tracking the ESA’s Huygens Probe during its descent in the atmosphere of Titan in 2005. From that point on, the technique has been demonstrated for various planetary and other space science missions. The estimates of lateral position of the target spacecraft are done using the phase-referencing VLBI technique. Together with radial Doppler estimates, these observables can be used for a variety of applications, including improving the knowledge of the spacecraft state vector. The PRIDE measurements can be applied to a broad scope of research fields including studies of atmospheres through the use of radio occultations, the improvement of planetary and satellite ephemerides, as well as gravity field parameters and other geodetic properties of interest, and estimations of interplanetary plasma properties. This paper presents the implementation of PRIDE as a component of the ESA’s Jupiter Icy Moons Explorer (JUICE) mission.
Geolocated social media data hold a hitherto untapped potential for exploring the relationship between user mobility and their interests at a large scale. Using geolocated Twitter data from Nigeria, we provide a feasibility study that demonstrates how the linkage of (1) a trajectory analysis of Twitter users' geolocation and (2) natural language processing of Twitter users' text content can reveal information about the interests of migrants. After identifying migrants via a trajectory analysis, we train a language model to automatically detect the topics of the migrants' tweets. Biases of manual labelling are circumvented by learning community-defined topics from a Nigerian web forum. Results suggest that differences in users' mobility correlate with varying interests in several topics, most notably religion. We find that Twitter data can be a flexible source for exploring the link between users' mobility and interests in large-scale analyses of urban populations. The joint use of spatial techniques and text analysis enables migration researchers to (a) study migrant perspectives in greater detail than is possible with census data and (b) at a larger scale than is feasible with interviews. Thereby, it provides a valuable complement to interviews, surveys and censuses, and holds a large potential for further research.
Zinc‐based batteries offer good volumetric energy densities and are compatible with environmentally friendly aqueous electrolytes. Zinc‐ion batteries (ZIBs) rely on a lithium‐ion‐like Zn ²⁺ ‐shuttle, which enables higher roundtrip efficiencies and better cycle life than zinc‐air batteries. Manganese‐oxide cathodes in near‐neutral zinc sulfate electrolytes are the most prominent candidates for ZIBs. Zn ²⁺ ‐insertion, H ⁺ ‐insertion, and Mn ²⁺ ‐dissolution are proposed to contribute to the charge‐storage mechanism. During discharge and charge, two distinct phases are observed. Notably, the pH‐driven precipitation of zinc‐sulfate‐hydroxide is detected during the second discharge phase. However, a complete and consistent understanding of the two‐phase mechanism of these ZIBs is still missing. This paper presents a continuum full cell model supported by density functional theory (DFT) calculations to investigate the implications of these observations. The complex‐formation reactions of near‐neutral aqueous electrolytes are integrated into the battery model and, in combination with the DFT calculations, draw a consistent picture of the cycling mechanism. The interplay between electrolyte pH and reaction mechanisms is investigated at the manganese‐oxide cathodes and the dominant charge‐storage mechanism is identified. The model is validated with electrochemical cycling data, cyclic voltammograms, and in situ pH measurements. This allows to analyze the influence of cell design and electrolyte composition on cycling and optimize the battery performance.
Estimating global and multi-level Thermosphere Neutral Density (TND) is important for studying coupling processes within the upper atmosphere, and for applications like orbit prediction. Models are applied for predicting TND changes, however, their performance can be improved by accounting for the simplicity of model structure and the sampling limitations of model inputs. In this study, a simultaneous Calibration and Data Assimilation (C/DA) algorithm is applied to integrate freely available CHAMP, GRACE, and Swarm derived TND measurements into the NRLMSISE-00 model. The improved model, called ‘C/DA-NRLMSISE-00’, and its outputs fit to these measured TNDs, are used to produce global TND fields at arbitrary altitudes (with the same vertical coverage as the NRLMSISE-00). Seven periods, between 2003-2020 that are associated with relatively high geomagnetic activity selected to investigate these fields, within which available models represent difficulties to provide reasonable TND estimates. Independent validations are performed with along-track TNDs that were not used within the C/DA framework, as well as with the outputs of other models such as the Jacchia-Bowman 2008 and the High Accuracy Satellite Drag Model. The numerical results indicate an average 52%, 50%, 56%, 25%, 47%, 54%, and 63% improvement in the Root Mean Squared Errors of the short term TND forecasts of C/DA-NRLMSISE00 compared to the along-track TND estimates of GRACE (2003, altitude 490 km), GRACE (2004, altitude 486 km), CHAMP (2008, altitude 343 km), GOCE (2010, altitude 270 km), Swarm-B (2015, altitude 520 km), Swarm-B (2017, altitude 514 km), and Swarm-B (2020, altitude 512 km), respectively.
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