Anthropomorphism in social robotics: empirical results on human–robot interaction in hybrid production workplaces

New forms of artificial intelligence on the one hand and the ubiquitous networking of “everything with everything” on the other hand characterize the fourth industrial revolution. This results in a changed understanding of human–machine interaction, in new models for production, in which man and machine together with virtual agents form hybrid teams. The empirical study “Socializing with robots” aims to gain insight especially into conditions of development and processes of hybrid human–machine teams. In the experiment, human–robot actions and interactions were closely observed in a virtual environment. Robots as partners differed in shape and behavior (reliable or faulty). Participants were instructed to achieve an objective that could only be achieved via close teamwork. This paper unites different aspects from core disciplines of social robotics and psychology contributing to anthropomorphization with the empirical insights of the experiment. It focuses on the psychological effects (e.g. reactions of different personality types) on anthropomorphization and mechanization, taking the inter- and transdisciplinary field of social robotics as a starting point.     

Impact of particle morphology on structure,crystallization kinetics,and properties of PCL composites with TiO<Subscript>2</Subscript>-based particles

Crystallization kinetics of polycaprolactone (PCL) filled with TiO₂-based particles (TiX) was shown to depend on the TiX particle type and concentration, which were associated with a slight polymer matrix degradation. The partially degraded, shorter, and more mobile polymer chains increased the overall crystallization rate at the initial stage of crystallization, while at the later stages, the non-nucleating TiX particles acted as a sterical hindrance, slowing down the crystallization process. The PCL/TiX composites were prepared by melt-mixing and contained 2.5 and 5 wt% of the filler. The investigated TiX particles included isometric anatase microparticles (mTiO₂) and titanate nanotubes with high-aspect ratio (TiNT). Light and electron microscopy showed very homogeneous dispersion of the mTiO₂ particles in the PCL matrix, while the TiNT formed large agglomerates. In situ polarized light microscopy displayed faster isothermal crystallization of all PCL/TiX composites, but the micrographs indicated that the TiX particles did not act as nucleation centres. Isothermal DSC experiments, evaluated in terms of Avrami theory, confirmed the PLM results and showed that the overall rate of isothermal crystallization increased in the following order: PCL <PCL/TiNT <PCL/mTiO₂. Non-isothermal DSC and rheological measurements revealed the correlation between the crystallization rate and the polymer matrix degradation—the well-dispersed mTiO₂ particles with high specific surface caused the highest PCL degradation and, consequently, the earliest start of non-isothermal crystallization as well as the fastest isothermal crystallization. Microindentation hardness measurements confirmed that the partial degradation of the polymer matrix did not have a significant impact on the mechanical performance of PCL/mTiO₂ composites.     

The effect of embedded carbon nanotubes on the morphological evolution during the carbonization of poly(acrylonitrile) nanofibers

Hybrid nanofibers with different concentrations of multi-walled carbon nanotubes (MWCNTs) in polyacrylonitrile (PAN) were fabricated using the electrospinning technique and subsequently carbonized. The morphology of the fabricated carbon nanofibers (CNFs) at different stages of the carbonization process was characterized by transmission electron microscopy and Raman spectroscopy. The polycrystalline nature of the CNFs was shown, with increasing content of ordered crystalline regions having enhanced orientation with increasing content of MWCNTs. The results indicate that embedded MWCNTs in the PAN nanofibers nucleate the growth of carbon crystals during PAN carbonization.     

A noble silver nanoflower on nitrogen doped carbon nanotube for enhanced oxygen reduction reaction

An electrodeposition-approach for the synthesis of silver nanoflowers (AgNFs) on nitrogen doped carbon nanotubes (NCNTs) for the oxygen reduction reaction (ORR) in alkaline media has been developed. The as prepared material (NCNTs-AgNFs) has been characterized by various instrumental methods. The morphological analysis shows the unique rose-like AgNFs are placed onto the NCNTs with better dispersion. The higher population of AgNFs has also been observed onto NCNTs coated glassy carbon (GC) rather than bare GC plate. The X-ray photoelectron spectroscopy shows chemical reduction and N-doping has done successfully with the restoring sp² domain in carbon network. The electrocatalytic activities have been verified using cyclic voltammetry (CV) and hydrodynamic voltammetry techniques in 0.1 M KOH electrolyte. The resulting catalyst system, NCNT-AgNFs, surpasses the performance of Pt/C, in terms of a kinetic current density, better fuel selectivity and durability. It is also noteworthy that the NCNT-AgNFs exhibits a four-electron reduction pathway for ORR with lowering H₂O₂ yield. The admirable performance of NCNT-AgNFs catalyst along with higher durability holds great potential for application in various fuel cells as cathode catalyst.     

Impaired Retromer Function in Niemann-Pick Type C Disease Is Dependent on Intracellular Cholesterol Accumulation

Niemann-Pick type C disease (NPC) is a rare inherited neurodegenerative disorder characterized by an accumulation of intracellular cholesterol within late endosomes and lysosomes due to NPC1 or NPC2 dysfunction. In this work, we tested the hypothesis that retromer impairment may be involved in the pathogenesis of NPC and may contribute to increased amyloidogenic processing of APP and enhanced BACE1-mediated proteolysis observed in NPC disease. Using NPC1-null cells, primary mouse NPC1-deficient neurons and NPC1-deficient mice (BALB/cNctr-Npc1m1N), we show that retromer function is impaired in NPC. This is manifested by altered transport of the retromer core components Vps26, Vps35 and/or retromer receptor sorLA and by retromer accumulation in neuronal processes, such as within axonal swellings. Changes in retromer distribution in NPC1 mouse brains were observed already at the presymptomatic stage (at 4-weeks of age), indicating that the retromer defect occurs early in the course of NPC disease and may contribute to downstream pathological processes. Furthermore, we show that cholesterol depletion in NPC1-null cells and in NPC1 mouse brains reverts retromer dysfunction, suggesting that retromer impairment in NPC is mechanistically dependent on cholesterol accumulation. Thus, we characterized retromer dysfunction in NPC and propose that the rescue of retromer impairment may represent a novel therapeutic approach against NPC.     

An agent-based concept for planning and control of the production of carbon fibre reinforced plastics aircraft structures with mobile production units

This article is concerned with the control of the production of aircraft primary structures made of carbon fibre reinforced plastics. To increase the parallelization of the production, a scenario that implies new design paradigms is discussed. In order to realize this parallelization, mobile production entities work concurrently at the same primary structure of the fuselage. The present article proposes a software architecture for the control of such a production system. It is proposed that components are organized hierarchically. In enhancement to previous proposals, two perspectives of hierarchy are used here: grouping by functionality and grouping by timing context. The core of the architecture is a market-based multi-agent system, where the agents may operate in multiple timing contexts. Such a design yields advantages in terms of fast integration of new functionalities and scale-up of the production system. In brief, this article introduces a top-level control architecture for parallelized production of large reliable CFRP structures in a scalable production system.     

Augmenting research cooperation in production engineering with data analytics

Understanding how members of a research team cooperate and identifying possible synergies may be crucial for organizational success. Using data-driven approaches, recommender systems may be able to find promising collaborations from publication data. Yet, the outcome of scientific endeavors (i.e. publications) are only produced sparingly in comparison to other forms of data, such as online purchases. In order to facilitate this data in augmenting research cooperation, we suggest to combine data-driven approaches such as text-mining, topic modeling and machine learning with interactive system components in an interactive visual recommendation system. The system leads to an augmented perspective on research cooperation in a network: Interactive visualization analyzes, which cooperation could be intensified due to topical overlap. This allows to reap the benefit of both worlds. First, utilizing the computational power to analyze large bodies of text and, second, utilizing the creative capacity of users to identify suitable collaborations, where machine-learning algorithms may fall short.     

Biogenic amines and their producers in Akawi white cheese

The aim of this work was to study the biogenic amine content of brine‐ripened cheeses after one year of storage and then to investigate possible contaminating micro‐organisms with decarboxylase activity. The biogenic amine production of isolates was tested in vitro. The most frequent biogenic amines were putrescine, histamine and tyramine. The biogenic amine content detected in one cheese sample was above 120 mg/kg; this can be considered toxicologically relevant. Decarboxylase activity was found for 33 contaminating micro‐organisms. Isolates belonging to Bacillus licheniformis, Debaryomyces hansenii, Staphylococcus equorum and Serratia marcescens produced significant amounts of putrescine and cadaverine.     

Characterisation and modelling of the elastic properties of poly(lactic acid) nanofibre scaffolds

The aim of this study is to predict the elastic response of poly(lactic acid) (PLA) electrospun nanofibre scaffolds through mathematical models based on homogenisation and the differential replacement method (DRM). These models principally seek to determine and analyse the effects of the internal morphology of the nanofibres on the effective Young’s modulus of polymer nanofibre scaffolds. The microstructure of the nanofibres was first characterised by SEM, XRD, DSC, AFM, and TEM techniques. From this characterisation, strong evidence of a hierarchical core–shell structure was found. With the experimental data, it was possible to design and validate better models than those currently used. In addition, the effects of the electrospinning parameters, such as take-up velocity and thermal treatment, were analysed and correlated with the morphology and the elastic properties of the nanofibres and their scaffolds. To validate the models’ results, we conducted a series of uniaxial tensile tests on the PLA nanofibre scaffolds. Using the data from the nanofibre measurements, the homogenisation approximations and the model based on the DRM predicted an effective Young’s modulus of 667 and 835 MPa, respectively. The predicted data were in excellent agreement with the experimental results (685–880 MPa). These models will be useful in understanding and evaluating the structure–property relationships of oriented nanofibre scaffolds for medical or biological applications.