PEDOT:PSS-Modified Cotton Conductive Thread for Mass Manufacturing of Textile-Based Electrical Wearable Sensors by Computerized Embroidery

The textile industry has advanced processes that allow computerized manufacturing of garments at large volumes with precise visual patterns. The industry, however, is not able to mass fabricate clothes with seamlessly integrated wearable sensors, using its precise methods of fabrication (such as computerized embroidery). This is due to the lack of conductive threads compatible with standard manufacturing methods used in industry. In this work, we report a low-cost poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS)-modified cotton conductive thread (PECOTEX) that is compatible with computerized embroidery. The PECOTEX was produced using a crosslinking reaction between PEDOT:PSS and cotton thread using divinyl sulfone as the crosslinker. We extensively characterized and optimized our formulations to create a mechanically robust conductive thread that can be produced in large quantities in a roll-to-roll fashion. Using PECOTEX and a domestic computerized embroidery machine, we produced a series of wearable electrical sensors including a facemask for monitoring breathing, a t-shirt for monitoring heart activity and textile-based gas sensors for monitoring ammonia as technology demonstrators. PECOTEX has the potential to enable mass manufacturing of new classes of low-cost wearable sensors integrated into everyday clothes.

“President-Protector”: A Multimodal Critical Discourse Analysis of a News Report Promoting the Personality Cult of the President of Turkmenistan G. Berdymukhamedov

The cult of personality started by the first President of Turkmenistan Saparmurat Niyazov has acquired new dimensions with the present leader of the country. The cult of personality of Gurbanguly Berdymukhamedov is actively constructed via mass media. This paper examines two short clips of a news report dedicated to the President’s birthday celebration that was broadcasted on the Turkmen national TV on 26 June 2020. The paper analyzes a set of specific mechanisms of flattery inflation used in the report and demonstrates special linguistic choices and visual patterns applied to force a specific ideology on the audience. Due to the multimodal nature of the analyzed discourse, multimodal critical discourse analysis has been implemented, additionally informed by the systemic functional linguistics and the visual semiotic analysis.

Patterns for Visual Management in Industry 4.0

The technologies of Industry 4.0 provide an opportunity to improve the effectiveness of Visual Management in manufacturing. The opportunity of improvement is twofold. From one side, Visual Management theory and practice can inspire the design of new software tools suitable for Industry 4.0; on the other side, the technology of Industry 4.0 can be used to increase the effectiveness of visual software tools. The paper first explores how the theoretical result on Visual Management can be used as a guideline to improve human-computer interaction, then a methodology is proposed for the design of visual patterns for manufacturing. Four visual patterns are presented that contribute to the solution of problems frequently encountered in discrete manufacturing industries; these patterns help to solve planning and control problems thus providing support to various management functions. Positive implications of this research concern people engagement and empowerment as well as improved problem solving, decision-making and management of manufacturing processes.

Emotional Responses to the Visual Patterns of Urban Streets: Evidence from Physiological and Subjective Indicators

Despite recent progress in the research of people’s emotional response to the environment, the built—rather than natural—environment’s emotional effects have not yet been thoroughly examined. In response to this knowledge gap, we recruited 26 participants and scrutinized their emotional response to various urban street scenes through an immersive exposure experiment using virtual reality. We utilized new physiological monitoring technologies that enable synchronized observation of the participants’ electroencephalography, electrodermal activity, and heart rate, as well as their subjective indicators. With the newly introduced measurement for the global visual patterns of the built environment, we built statistical models to examine people’s emotional response to the physical element configuration and color composition of street scenes. We found that more diverse and less fragmented scenes inspired positive emotional feelings. We also found (in)consistency among the physiological and subjective indicators, indicating a potentially interesting neural−physiological interpretation for the classic form−function dichotomy in architecture. Besides the practical implications on promoting physical environment design, this study combined objective physiology-monitoring technology and questionnaire-based research techniques to demonstrate a better approach to quantify environment−emotion relationships.

Interpretable Compositional Convolutional Neural Networks

This paper proposes a method to modify a traditional convolutional neural network (CNN) into an interpretable compositional CNN, in order to learn filters that encode meaningful visual patterns in intermediate convolutional layers. In a compositional CNN, each filter is supposed to consistently represent a specific compositional object part or image region with a clear meaning. The compositional CNN learns from image labels for classification without any annotations of parts or regions for supervision. Our method can be broadly applied to different types of CNNs. Experiments have demonstrated the effectiveness of our method. The code will be released when the paper is accepted.

Electrophysiological priming effects demonstrate independence and overlap of visual regularity representations in the extrastriate cortex

An Event Related Potential (ERP) component called the Sustained Posterior Negativity (SPN) is generated by regular visual patterns (e.g. vertical reflectional symmetry, horizontal reflectional symmetry or rotational symmetry). Behavioural studies suggest symmetry becomes increasingly salient when the exemplars update rapidly. In line with this, Experiment 1 (N = 48) found that SPN amplitude increased when three different reflectional symmetry patterns were presented sequentially. We call this effect ‘SPN priming’. We then exploited SPN priming to investigate independence of different symmetry representations. SPN priming did not survive changes in retinal location (Experiment 2, N = 48) or non-orthogonal changes in axis orientation (Experiment 3, N = 48). However, SPN priming transferred between vertical and horizontal axis orientations (Experiment 4, N = 48) and between reflectional and rotational symmetry (Experiment 5, N = 48). SPN priming is interesting in itself, and a useful new method for identifying functional boundaries of the symmetry response. We conclude that visual regularities at different retinal locations are coded independently. However, there is some overlap between different regularities presented at the same retinal location.

Zur sprachlichen und visuellen Konstruktion rechter Diskursgemeinschaften in Social Media. Von PEGIDA zur Identitären Bewegung

<p>The article examines how right-wing discourse communities are linguistically and visually constituted in social media in the context of flight, migration and Islam. The PEGIDA Facebook Corpus covering user comments (2014–2015), the PolRrA Corpus containing right-wing populist speeches (2016–2017) and the Instagram Corpus of the hashtag #identitäre (2019–2020) with postings and user comments are the data basis. Thus the corpus consists of different language-based and multimodal entities. The aim is to show how right-wing discourse communities in Germany are constituted by <em>us</em>-<em>you</em> relations, naming practices and visual patterns across time, platform and organization.</p><p> </p>