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This article presents a study of cultural differences affecting the acceptance and design preferences of social robots. Based on a survey with 794 participants from Germany and the three Arab countries of Egypt, Jordan, and Saudi Arabia, we discuss how culture influences the preferences for certain attributes. We look at social roles, abilities and appearance, emotional awareness and interactivity of social robots, as well as the attitude toward automation. Preferences were found to differ not only across cultures, but also within countries with similar cultural backgrounds. Our findings also show a nuanced picture of the impact of previously identified culturally variable factors, such as attitudes toward traditions and innovations. While the participants’ perspectives toward traditions and innovations varied, these factors did not fully account for the cultural variations in their perceptions of social robots. In conclusion, we believe that more real-life practices emerging from the situated use of robots should be investigated. Besides focusing on the impact of broader cultural values such as those associated with religion and traditions, future studies should examine how users interact, or avoid interaction, with robots within specific contexts of use.
Non-contact anterior cruciate ligament injuries typically occur during cutting maneuvers and are associated with high peak knee abduction moments (KAM) within early stance. To screen athletes for injury risk or quantify the efficacy of prevention programs, it may be necessary to design tasks that mimic game situations. Thus, this study compared KAMs and ranking consistency of female handball players in three sport-specific fake-and-cut tasks of increasing complexity. The biomechanics of female handball players (n = 51, mean ± SD: 66.9 ± 7.8 kg, 1.74 ± 0.06 m, 19.2 ± 3.4 years) were recorded with a 3D motion capture system and force plates during three standardized fake-and-cut tasks. Task 1 was designed as a simple pre-planned cut, task 2 included catching a ball before a pre-planned cut in front of a static defender, and task 3 was designed as an unanticipated cut with three dynamic defenders involved. Inverse dynamics were used to calculate peak KAM within the first 100 ms of stance. KAM was decomposed into the frontal plane knee joint moment arm and resultant ground reaction force. RANOVAs (α ≤ 0.05) were used to reveal differences in the KAM magnitudes, moment arm, and resultant ground reaction force for the three tasks. Spearman's rank correlations were calculated to test the ranking consistency of the athletes' KAMs. There was a significant task main effect on KAM (p = 0.02; ηp2 = 0.13). The KAM in the two complex tasks was significantly higher (task 2: 1.73 Nm/kg; task 3: 1.64 Nm/kg) than the KAM in the simplest task (task 1: 1.52 Nm/kg). The ranking of the peak KAM was consistent regardless of the task complexity. Comparing tasks 1 and 2, an increase in KAM resulted from an increased frontal plane moment arm. Comparing tasks 1 and 3, higher KAM in task 3 resulted from an interplay between both moment arm and the resultant ground reaction force. In contrast to previous studies, unanticipated cutting maneuvers did not produce the highest KAMs. These findings indicate that the players have developed an automated sport-specific cutting technique that is utilized in both pre-planned and unanticipated fake-and-cut tasks.
One of the practical bottlenecks associated with commercialization of lithium-air cells is the choice of an appropriate electrolyte that provides the required combination of cell performance, cyclability and safety. With the help of a two-dimensional multiphysics model, we attempt to narrow down the electrolyte choice by providing insights into the effect of the transport properties of electrolyte, electrode saturation (flooded versus gas diffusion), and electrode thickness on a single discharge performance of a lithium-air button cell cathode for five different electrolytes including water, ionic liquid, carbonate, ether, and sulfoxide. The 2D distribution of local current density and concentrations of electrochemically active species (O2 and Li+) in the cathode is also discussed w.r.t electrode saturation. Furthermore, the efficacy of species transport in the cathode is quantified by introducing two parameters, firstly, a transport efficiency that gives local insight into the distribution of mass transfer losses, and secondly, an active electrode volume that gives global insight into the cathode volume utilization at different current densities. A detailed discussion is presented toward understanding the design-induced performance limitations in a Li-air button cell prototype.
Virtual-Reality-Anwendungen ermöglichen es Anbietern von Erfahrungsgütern durch innovative Produktpräsentationen die inhärenten Informationsasymmetrien zu reduzieren. Dadurch kann den potenziellen Kunden eine effiziente Leistungsbeurteilung ermöglicht und das Risiko einer informationsbedingten Fehlentscheidung minimiert werden. Die vorliegende Studie fokussiert sich auf die Identifikation wichtiger Determinanten, die die Nutzungsintention von Virtual-Reality-Anwendungen zur Leistungsbeurteilung von Erfahrungsgütern beeinflussen. Um das Akzeptanzverhalten von Nutzern gegenüber dieser neuartigen Technologie zu erforschen, wurde ein erweitertes Technologieakzeptanzmodell eingesetzt. Als Untersuchungsobjekt wurde eigens für die Studie eine Virtual-Reality-Anwendung entwickelt, die es den Nutzern ermöglichte, eigenständig ein virtuelles Erfahrungsgut zu erkunden. Insgesamt nahmen 569 Probanden an der Datenerhebung teil. Für die Berechnung des Strukturgleichungsmodells und die Hypothesenüberprüfung wurde eine Partial-Least-Squares-Analyse eingesetzt. Wie die Studienergebnisse verdeutlichen, führt das immersive Produkterlebnis zu einer effizienteren Informationsbeschaffung. Speziell der wahrgenommene Nutzen einer Virtual-Reality-Anwendung ist ein zentraler Prädiktor, der sowohl auf die Nutzungseinstellung als auch auf die Nutzungsintention einen starken positiven Einfluss ausübt.
Deep learning approaches are becoming increasingly important for the estimation of the Remaining Useful Life (RUL) of mechanical elements such as bearings. This paper proposes and evaluates a novel transfer learning-based approach for RUL estimations of different bearing types with small datasets and low sampling rates. The approach is based on an intermediate domain that abstracts features of the bearings based on their fault frequencies. The features are processed by convolutional layers. Finally, the RUL estimation is performed using a Long Short-Term Memory (LSTM) network. The transfer learning relies on a fixed-feature extraction. This novel deep learning approach successfully uses data of a low-frequency range, which is a precondition to use low-cost sensors. It is validated against the IEEE PHM 2012 Data Challenge, where it outperforms the winning approach. The results show its suitability for low-frequency sensor data and for efficient and effective transfer learning between different bearing types.
A strong heat load in buildings and cities during the summer is not a new phenomenon. However, prolonged heat waves and increasing urbanization are intensifying the heat island effect in our cities; hence, the heat exposure in residential buildings. The thermophysiological load in the interior and exterior environments can be reduced in the medium and long term, through urban planning and building physics measures. In the short term, an increasingly vulnerable population must be effectively informed of an impending heat wave. Building simulation models can be favorably used to evaluate indoor heat stress. This study presents a generic simulation model, developed from monitoring data in urban multi-unit residential buildings during a summer period and using statistical methods. The model determines both the average room temperature and its deviations and, thus, consists of three sub-models: cool, average, and warm building types. The simulation model is based on the same mathematical algorithm, whereas each building type is described by a specific data set, concerning its building physical parameters and user behavior, respectively. The generic building model may be used in urban climate analyses with many individual buildings distributed across the city or in heat–health warning systems, with different building and user types distributed across a region. An urban climate analysis (with weather data from a database) may evaluate local differences in urban and indoor climate, whereas heat–health warning systems (driven by a weather forecast) obtain additional information on indoor heat stress and its expected deviations.
Lithium-ion battery cells exhibit a complex and nonlinear coupling of thermal, electrochemical,and mechanical behavior. In order to increase insight into these processes, we report the development of a pseudo-three-dimensional (P3D) thermo-electro-mechanical model of a commercial lithium-ion pouch cell with graphite negative electrode and lithium nickel cobalt aluminum oxide/lithium cobalt oxide blend positive electrode. Nonlinear molar volumes of the active materials as function of lithium stoichiometry are taken from literature and implemented into the open-source software Cantera for convenient coupling to battery simulation codes. The model is parameterized and validated using electrical, thermal and thickness measurements over a wide range of C-rates from 0.05 C to 10 C. The combined experimental and simulated analyses show that thickness change during cycling is dominated by intercalation-induced swelling of graphite, while swelling of the two blend components partially cancel each other. At C-rates above 2 C, electrochemistry-induced temperature increase significantly contributes to cell swelling due to thermal expansion. The thickness changes are nonlinearly distributed over the thickness of the electrode pair due to gradients in the local lithiation, which may accelerate local degradation. Remaining discrepancies between simulation and experiment at high C-rates might be attributed to lithium plating, which is not considered in the model at present.
In this project, different calcification methods for collagen and collagen coatings were compared in terms of their applicability for 3D printing and production of collagen-coated scaffolds. For this purpose, scaffolds were printed from polycaprolactone PCL using the EnvisionTec 3D Bioplotter and then coated with collagen. Four different coating methods were then applied: hydroxyapatite (HA) powder directly in the collagen coating, incubation in 10× SBF, coating with alkaline phosphatase (ALP), and coating with poly-L-aspartic acid. The results were compared by ESEM, µCT, TEM, and EDX. HA directly in the collagen solution resulted in a pH change and thus an increase in viscosity, leading to clumping on the scaffolds. As a function of incubation time in 10× SBF as well as in ALP, HA layer thickness increased, while no coating on the collagen layer was apparently observed with poly-L-aspartic acid. Only ultrathin sections and TEM with SuperEDX detected nano crystalline HA in the collagen layer. Exclusively the incubation in poly-L-aspartic acid led to HA crystals within the collagen coating compared to all other methods where the HA layers formed in different forms only at the collagen layer.
Purpose
To summarize the mechanical loading of the spine in different activities of daily living and sports.
Methods
Since the direct measurement is not feasible in sports activities, a mathematical model was applied to quantify spinal loading of more than 600 physical tasks in more than 200 athletes from several sports disciplines. The outcome is compression and torque (normalized to body weight/mass) at L4/L5.
Results
The data demonstrate high compressive forces on the lumbar spine in sport-related activities, which are much higher than forces reported in normal daily activities and work tasks. Especially ballistic jumping and landing skills yield high estimated compression at L4/L5 of more than ten times body weight. Jumping, landing, heavy lifting and weight training in sports demonstrate compression forces significantly higher than guideline recommendations for working tasks.
Conclusion
These results may help to identify acute and long-term risks of low back pain and, thus, may guide the development of preventive interventions for low back pain or injury in athletes.
The impact of the circular economy on sustainable development: A European panel data approach
(2022)
The circular economy (CE) has attracted considerable attention because of its potential to help achieve sustainable development (SD). This paper presents a comprehensive analysis of the effect of the CE on the three dimensions of SD at the country level. We analysed the impact of each CE source of value (renewable energy, reuse, repair, recycling) and the influence of an overall factor-analysis-derived measure of the CE on the economic, environmental and social dimensions of SD. The aim was to compare the individual impacts and outcomes of the CE and its sources of value in a single study. Panel data analysis was performed using a sample of 25 European countries for the period 2010 to 2019. The findings show a major impact of the CE on achieving SD, which has positive
effects on the economy, environment and society. However, the results show that the impact of each CE value source on the three SD dimensions varies. While renewable energies and reuse reduce the impact on the environment, recycling has no effect, and repair increases GHG emissions. However, repair is the only CE source with a positive economic impact at the country level. Finally, renewable energy, repair and recycling reduce unemployment. Decision makers should conduct impact analysis to design suitable, efficient and targeted measures depending on each country's specific objectives.