Conversational Agents (CAs) are becoming part of our everyday lives. About 10% of users display aggressive behavior toward CAs, such as swearing at them when they produce errors. We conducted two online experiments to understand user aggression towards CAs better. In the first experiment, 175 participants used either a humanlike CA or a non-humanlike CA. Both CAs worked without errors, and we observed no increased frustration or user aggression. The second experiment (with 201 participants) was the focus of this study; in it, both CAs produce a series of errors. The results show that frustration with errors drives aggression, and users with higher impulsivity are more likely to become aggressive when frustrated. The results also suggest that there are three pathways by which perceived humanness influences users’ aggression towards CAs. First, perceived humanness directly increases the frustration with the CA when it produces errors. Second, perceived humanness increases service satisfaction, which in turn reduces frustration. Third, perceived humanness influences the nature of aggression when users become frustrated (i.e., users are less likely to use highly offensive words with a more humanlike CA). Our research contributes to our theoretical understanding of the role of anthropomorphism in the interaction with machines, showing that designing a CA to be more humanlike is a double-edged sword—both increasing and decreasing the frustration that leads to aggression—and also a means to reduce the most severe aggression.
This paper offers a systematic literature review of real-time detection and classification of Power Quality Disturbances (PQDs). A particular focus is given to voltage sags and notches, as voltage sags cause huge economic losses while research on voltage notches is still very incipient. A systematic method based on scientometrics, text similarity and the analytic hierarchy process is proposed to structure the review and select the most relevant literature. A bibliometric analysis is then performed on the bibliographic data of the literature to identify relevant statistics such as the evolution of publications over time, top publishing countries, and the distribution by relevant topics. A set of articles is subsequently selected to be critically analyzed. The critical review is structured in steps for real-time detection and classification of PQDs, namely, input data preparation, preprocessing, transformation, feature extraction, feature selection, detection, classification, and characterization. Aspects associated with the type of disturbance(s) addressed in the literature are also explored throughout the review, including the perspectives of those studies aimed at multiple PQDs, or specifically focused on voltage sags or voltage notches. The real-time performance of the reviewed tools is also examined. Finally, unsolved issues are discussed, and prospects are highlighted.
Sandwich packings represent new separation column internals, with a potential to intensify mass transfer. They comprise two conventional structured packings with different specific geometrical surface areas. In this work, the complex fluid dynamics in sandwich packings is modeled using a novel approach based on a one-dimensional, steady momentum balance of the liquid and gas phases. The interactions between the three present phases (gas, liquid, and solid) are considered by closures incorporated into the momentum balance. The formulation of these closures is derived from two fluid-dynamic analogies for the film and froth flow patterns. The adjustable parameters in the closures are regressed for the film flow using dry pressure drop measurements and liquid hold-up data in trickle flow conditions. For the froth flow, the tuning parameters are fitted to overall pressure drop measurements and local liquid hold-up data acquired from ultra-fast X-ray tomography (UFXCT). The model predicts liquid hold-up and pressure drop data with an average relative deviation of 16.4 % and 19 %, respectively. Compared to previous fluid dynamic models for sandwich packings, the number of adjustable parameters could be reduced while maintaining comparable accuracy.
Compressible Constrained Layer Damping (CCLD) is a novel semi-active damping solution for vibration mitigation. The constrained damping layer consists of a compressible damping material with the thickness that can be adjusted in operando using fluid actuation. The actuation deformations, referred to as “evanescent morphing”, change both the damping material properties and the amount of vibration-induced shear deformation, enabling a tuning of the overall structural dynamic behavior according to the excitation parameters. The CCLD can be applied to the entire surface of the vibrating structure or as patch only partially, without causing a significant increase of mass. This work demonstrates the potential of the damping measure using different damping materials. These materials were investigated and characterized at varying compression levels. The hereby obtained results were implemented in a numerical model that is discussed and validated. Experiments carried out on a single-curved shell structure with a partial CCLD patch coverage were carried out and served as the source of validation data.
In the randomized CeTeG/NOA-09 trial, lomustine/temozolomide (CCNU/TMZ) was superior to TMZ therapy regarding overall survival (OS) in MGMT promotor-methylated glioblastoma. Progression-free survival (PFS) and pseudoprogression rates (about 10%) were similar in both arms. Further evaluating this discrepancy, we analyzed patterns of postprogression survival (PPS) and MRI features at first progression according to modified RANO criteria (mRANO). We classified the patients of the CeTeG/NOA-09 trial according to long vs. short PPS employing a cut-off of 18 months and compared baseline characteristics and survival times. In patients with available MRIs and confirmed progression, the increase in T1-enhancing, FLAIR hyperintense lesion volume and the change in ADC mean value of contrast-enhancing tumor upon progression were determined. Patients with long PPS in the CCNU/TMZ arm had a particularly short PFS (5.6 months). PFS in this subgroup was shorter than in the long PPS subgroup of the TMZ arm (11.1 months, p = 0.01). At mRANO-defined progression, patients of the CCNU/TMZ long PPS subgroup had a significantly higher increase of mean ADC values (p = 0.015) and a tendency to a stronger volumetric increase in T1-enhancement (p = 0.22) as compared to long PPS patients of the TMZ arm. The combination of survival and MRI analyses identified a subgroup of CCNU/TMZ-treated patients with features that sets them apart from other patients in the trial: short first PFS despite long PPS and significant increase in mean ADC values upon mRANO-defined progression. The observed pattern is compatible with the features commonly observed in pseudoprogression suggesting mRANO-undetected pseudoprogressions in the CCNU/TMZ arm of CeTeG/NOA-09.
Data‐driven methods yield advantages in computational homogenization approaches due to the ability to capture complex material behaviour without the necessity to assume specific constitutive models. Neural network–based constitutive descriptions are one of the most widely used data‐driven approaches in the context of computational mechanics. The accuracy of this method strongly depends on the available data. Additionally, when considering inelastic materials, whose constitutive responses depend on the loading history, the accuracy and robustness of the approximation are influenced by the training algorithm. The applied recurrent neural networks exhibit reduced robustness in the presence of errors in the input. When capturing the history dependency using previously predicted material responses, occurrences of prediction errors accumulate over several time steps. An approach for achieving enhanced robustness of the predictions is based on extending the initial training dataset by iteratively generating adversarial examples, subjected to perturbations, based on the current prediction errors. In this contribution, a continuous self‐adversarial training approach yielding robust recurrent neural network constitutive descriptions for inelastic materials is presented. Compared to the iterative method it is based on, it exhibits significantly improved training efficiency. In order to demonstrate the capabilities of the proposed methods, numerical examples with datasets obtained by numerical material tests on representative volume elements are carried out. Validation of the results is performed using both test load cases from the numerical dataset, as well as application as a constitutive model in the finite element method.
The handover and commissioning of buildings are highly collaborative tasks since multiple sub-systems, designed by numerous experts from different disciplines will become operational. This means, the commissioning process is the final proof of concept for architects and engineers’ design efforts. Additionally, construction companies must verify that all materials used are certified according to national standards. Finally, certified inspectors must approve the operational capability of critical systems and document each approval step using so-called operational certificates. This paper describes a novel, AI-guided approach, which will assist main contractors, investors and building owners in compiling, storing and managing all related product models, certificates and data sources for real-time monitoring (e.g. sensors) in a federated ‘distributed Digital Twin Information Model’ (dDT-IM). Furthermore, the paper explains why the availability of a complete, consistent, and comprehensive dDT-IM is an essential pre-requisite for the successful execution of collaborative, intelligent building operation.
This paper presents an approach to control smart home objects using Brain-Computer Interface (BCI) technology. The proposed system enables more efficient, accurate, and personalized control of smart home devices by integrating BCI signals with a scaled prototype representing a smart home environment. EEG (Electroencephalography) is chosen as a technique to record and measures the electrical activity of the brain using sensors placed on the scalp. BCI is still in early development, but it has been proven to be able to be used for object control. The brain signals require utilizing of supervised Machine learning algorithm to train the classifier on understanding specific mental commands that can be mapped to the needed actuator, and to change its status. The digital twin will work as a medium to reroute control commands from brain signals to the real asset. The paper discusses the solution architecture, and the integration of BCI headset with scaled prototyped smart home, and presents the results of a pilot study evaluating the control performance of the proposed approach. These findings shall help people with disabilities control their smart-home environments. Challenges have been identified as well as the further potential of resolving these with other technologies such as Digital Twins.
Construction robots aim to automate manual construction processes and to relieve construction workers from physically difficult and monotonous tasks. The field of construction robotics is currently very dynamic, which is reflected in a large number of different systems and prototypes that have been developed in recent years. There are often large differences between the individual robotic systems in terms of economic efficiency, practicality and conformity with applicable standards and laws. The objective of this paper is to identify suitable use cases for the development and deployment of construction robots, to analyze the current state of the art and to clarify the legal framework under which the deployment of highly automated and autonomous systems on construction sites is possible. Based on an analysis and evaluation of industry-specific work processes that are carried out in the construction and expansion of buildings, use cases with a particularly high automation potential are selected. The evaluation of the processes takes into account various aspects, including the complexity of the processes, the potential hazards caused by them and the cost-effectiveness of automation. Furthermore, an overview of technological readiness level as well as the level of automation of current robotic systems is given. Finally, applicable standards, regulations and laws are presented and the conditions under which construction robotics systems can be used on construction sites are explained.
New technologies and digital solutions are currently rapidly entering the construction machinery sector. These include (partial) automation solutions for machines and the implementation of the first autonomous construction machines, which no longer require machine operators. The first of these can help relieve the personnel shortage in the future, but qualified skilled workers will still be needed to operate the construction machines. The qualification requirements will increase massively due to the increasing complexity of machine technology and the use of new technologies. Efficient and, above all, safe handling of the new machines and construction processes will be achieved not only by integrating new technologies, functions and machine types into the training and qualification content, but also by adapting the content of these training and qualification programs to ensure a high level of acceptance among operators. This publication deals with the changes that operators are facing as a result of the digitalization of their occupation and analyzes the resulting challenges for the training and further education of machine operators on the basis of an exemplary activity.
The protozoan Toxoplasma gondii (T. gondii) is a zoonotic disease agent causing systemic infection in warm-blooded intermediate hosts including humans. During the acute infection, the parasite infects host cells and multiplies intracellularly in the asexual tachyzoite stage. In this stage of the life cycle, invasion, multiplication, and egress are the most critical events in parasite replication. T. gondii features diverse cell organelles to support these processes, including the apicoplast, an endosymbiont-derived vestigial plastid originating from an alga ancestor. Previous studies have highlighted that phytohormones can modify the calcium-mediated secretion, e.g., of adhesins involved in parasite movement and cell invasion processes. The present study aimed to elucidate the influence of different plant hormones on the replication of asexual tachyzoites in a human foreskin fibroblast (HFF) host cell culture. T. gondii replication was measured by the determination of T. gondii DNA copies via qPCR. Three selected phytohormones, namely abscisic acid (ABA), gibberellic acid (GIBB), and kinetin (KIN) as representatives of different plant hormone groups were tested. Moreover, the influence of typical cell culture media components on the phytohormone effects was assessed. Our results indicate that ABA is able to induce a significant increase of T. gondii DNA copies in a typical supplemented cell culture medium when applied in concentrations of 20 ng/μl or 2 ng/μl, respectively. In contrast, depending on the culture medium composition, GIBB may potentially serve as T. gondii growth inhibitor and may be further investigated as a potential treatment for toxoplasmosis.
Background Juvenile dermatomyositis (jDM) is the most common idiopathic inflammatory myopathy of childhood. Amyopathic or hypomyopathic courses have been described. Case presentation We present the case of a 4-year-old patient with MDA5 antibody positive jDM and interstitial lung disease. In our patient, typical symptoms of jDM with classical skin lesions, arthritis, proximal muscle weakness, and ulcerative calcifications were observed. Due to the severity of the disease and the pulmonary changes, therapy with the Janus kinase (JAK) inhibitor ruxolitinib was added to the therapy with corticosteroids, intravenous immunoglobulins (IVIG) and hydroxychloroquine leading to a fast and sustained remission. Conclusion While there is growing evidence that JAK inhibition is a promising therapeutic option in jDM our case report shows that this approach may also be effective in MDA5-positive jDM with high risk features.
Medical students are a vulnerable group for harmful health behaviours due to academic stress. Increased screen time is associated with adverse health behaviour, particularly delayed bedtime, shorter sleep duration and poorer sleep quality. This possible relationship has not yet been examined among medical students in Europe. Medical students at the Technical University of Dresden were invited to participate in an online questionnaire based cross-sectional study. To analyse correlations between screen time and sleep parameters, correlation coefficients, linear regression and mixed-model analysis were calculated. 415 students (average age 24 years, 70% female) were included in the analysis. The students reported an average of 7 h screen time per day and 7.25 h sleep duration per night. Approximately 23% (n = 97) reported sleeping less than 7 h per night and 25% (n = 105) reported fairly to very poor sleep quality. Students who reported more screen time for leisure went to bed significantly later (r = 0.213, p < 0.001). Students who spent more screen time for study/work tended to sleep shorter (r = − 0.108, p < 0.015). There was no significant association between screen time and sleep quality (p = 0.103). The results show a need for educational interventions to promote healthy sleep behaviour and to limit screen time.
A novel approach for fabricating copper‐coated alumina microparticles utilizing a pectin‐based coating subsequently followed by electroless deposition is reported. The biopolymer pectin is modified with phosphate groups covalently binding to the particle surface, while the polymer itself promotes the formation of metal centers on the surface due to the high affinity to metal cations. The sugar‐based (galactose, xylose, and glucose) electroless plating process in combination with an organic‐based treatment ensures a homogeneous metal coating method. As a benefit, precious metal activation of alumina particles and hazardous reducing agents typically employed are not required, creating a low‐cost and sustainable process. Metal plated micro particles show a uniform and homogeneous coating rendering them as ideal additives for application in metal matrix composites. These ceramic metal composites can be used in a wide range of applications where high‐strength metal components are needed.
The variation of transport behaviour in a mesoscopic Fe60Al40 wire, initially possessing the ordered B2-phase structure, has been observed while inducing a phase transition to the disordered A2 structure. Gradual disordering was achieved using a highly focused beam of Ne+-ions. Both electrical resistance and anomalous Hall effect were measured in parallel with the local ion irradiation. Both the normal and Hall resistivity show a peak as a function of fluence. Moreover, the relationship between Hall resistivity and normal resistivity reconfirms the presence of two distinct regimes in the transition. Furthermore, field-dependence and temperature-dependence measurements were used to identify that it is necessary to consider the effect of scattering from magnetic clusters to understand these different regimes in transport properties.
Purpose of Review The goal of this paper was to explore the different ways the COVID-19 pandemic has affected violence against children (VAC). Recent Findings Recent research of peer-reviewed articles using operational or survey data revealed the pandemic’s impact in terms of institutional responses, risk and mediating factors, changes in VAC dynamics, and a likely increase in child marriage. Summary Findings include a decrease in institutional responses, activities, and prevention case openings; an increased incidence of interparental intimate partner violence (IPV) witnessing cases, hospital admissions for suspected Abusive Head Trauma (AHT), other pediatric injuries, and sexual violence; a change in family conflict dynamics; and an estimated increase in child marriages. It also revealed mediating factors between the relationship of the pandemic and VAC (such as parental stress and mental health symptoms), as well as risk factors observed by service providers, which include the risk of mental health symptoms of both parents and children. Post-pandemic VAC research can be improved by utilizing operational or survey data in a meaningful way to be able to derive sound intervention approaches to diminish the pandemic’s impact on VAC and child marriage. We also propose for researchers to integrate child marriage into the definition of VAC.
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