Working everywhere and every time? – Chances and risks in crowdworking and crowdsourcing work design

Schulte J, Schlicher K, Maier GW. Working everywhere and every time? – Chances and risks in crowdworking and crowdsourcing work design. Gruppe. Interaktion. Organisation. Zeitschrift für Angewandte Organisationspsychologie (GIO). 2020;51(1):59-69.This article of the journal Gruppe. Interaktion. Organisation (GIO) deals with the question how work and organizational psychology can contribute to a better understanding of work design in crowdwork. Over the last decade, crowdsourcing (CS) has gained much momentum and attention, yet people who use CS as an additional or exclusive source of income are experiencing less consideration overall. Therefore, we define the term crowdwork (CW), and delimit it from related concepts, e.g., CS and gig economy. We then address how work and organizational psychology theory can contribute to the research of CW, with a focus on work design, and where new approaches are necessary. We give an overview of current research in this field, and derive suggestions and recommendations for both further research approaches and also practical application of work design in CW

Involvement of rat posterior prelimbic and cingulate area 2 in vocalization control

Microstimulation mapping identified vocalization areas in primate anterior cingulate cortex. Rat anterior cingulate and medial prefrontal areas have also been intensely investigated, but we do not know, how these cortical areas contribute to vocalizations and no systematic mapping of stimulation‐evoked vocalizations has been performed. To address this question, we mapped microstimulation‐evoked (ultrasonic) vocalizations in rat cingulate and medial prefrontal cortex. The incidence of evoked vocalizations differed markedly between frontal cortical areas. Vocalizations were most often evoked in posterior prelimbic cortex and cingulate area 2, whereas vocalizations were rarely evoked in dorsal areas (vibrissa motor cortex, secondary motor cortex and cingulate area 1) and anterior areas (anterior prelimbic, medial‐/ventral‐orbital cortex). Vocalizations were observed at intermediate frequencies in ventro‐medial areas (infralimbic and dorsopeduncular cortex). Various complete, naturally occurring calls could be elicited. In prelimbic cortex superficial layer microstimulation evoked mainly fear calls with low efficacy, whereas deep layer microstimulation evoked mainly 50 kHz calls with high efficacy. Vocalization stimulation thresholds were substantial (70–500 μA, the maximum tested; on average ~400 μA) and latencies were long (median 175 ms). Posterior prelimbic cortex projected to numerous targets and innervated brainstem vocalization centers such as the intermediate reticular formation and the nucleus retroambiguus disynaptically via the periaqueductal gray. Anatomical position, stimulation effects and projection targets of posterior prelimbic cortex were similar to that of monkey anterior cingulate vocalization cortex. Our data suggest that posterior prelimbic cortex is more closely involved in control of vocalization initiation than in specifying acoustic details of vocalizations.Peer Reviewe

The role of cognitive control in prosocial behavior – Investigating the neural foundations of retribution and forgiveness

Forgiveness is a highly relevant ability for a satisfied life with long-lasting relationships. It is hypothesized that cognitive control enables forgiveness through the inhibition of baser revenge seeking feelings. For investigating the exact underlying mechanisms, a set of four studies was run. In order to study the ability to forgive, the participants first played an ultimatum game, in which they learned that some opponents are fair and some are unfair. Following this implicit learning experience the roles were changed and in a subsequent dictator game the participants had to split up money between themselves and the opponents of the previous game. Regarding the previously unfair opponents they had to decide if they wanted to forgive (with allocating a fair amount of money) or to take revenge (with allocating an unfair amount of money). This paradigm sequence was combined in a first study with inhibitory theta-burst stimulation of the right dorsolateral prefrontal cortex (DLPFC), resulting in the causal conclusion that cognitive control is needed for forgiveness processes as after the stimulation the participants were significantly more revenge seeking. In another study, participants with high and low cognitive control were compared. Participants with low cognitive control were significantly more revenge seeking, whereas, participants with high cognitive control were less revenge seeking. Concluding from the results of a regression analysis this difference was (partly) caused by different emotional foundations of the behavior, with sympathy as a relevant factor in the high cognitive control group and revenge in the low cognitive control group. In a third study the gaming paradigms (ultimatum game and dictator game) were used in combination with activating theta-burst stimulation of the right DLPFC in a highly impulsive group which is known to be more revenge seeking than the average. With higher activation in the right DLPFC it was not possible to increase the forgiveness behavior towards the unfair opponents. Surprisingly, the activating neuromodulation increased the generosity towards fair opponents. In an additional study with a different paradigm the ability of emotion regulation (which is assumed to be a key player in forgiveness processes) in participants with low vs. high cognitive control was measured. It was shown that participants with low cognitive control failed, especially in implicit emotion regulation which is essential for daily life forgiveness processes. Based on these results a forgiveness model is proposed. According to this model the probability to forgive a wrongdoer is influenced by cultural/cognitive response tendencies and state/trait emotional tendencies. Cognitive control especially, but also the experienced emotions play a crucial role in forgiveness processes according to this model

Morbidity Measures Predicting Mortality in Inpatients:A Systematic Review

OBJECTIVES: Morbidity is an important risk factor for mortality and a variety of morbidity measures have been developed to predict patients' health outcomes. The objective of this systematic review was to compare the capacity of morbidity measures in predicting mortality among inpatients admitted to internal medicine, geriatric, or all hospital wards. DESIGN: A systematic literature search was conducted from inception to March 6, 2019 using 4 databases: Medline, Embase, Cochrane, and CINAHL. Articles were included if morbidity measures were used to predict mortality (registration CRD42019126674). SETTING AND PARTICIPANTS: Inpatients with a mean or median age ≥65 years. MEASUREMENTS: Morbidity measures predicting mortality. RESULTS: Of the 12,800 articles retrieved from the databases, a total of 34 articles were included reporting on inpatients admitted to internal medicine, geriatric, or all hospital wards. The Charlson Comorbidity Index (CCI) was reported most frequently and a higher CCI score was associated with greater mortality risk, primarily at longer follow-up periods. Articles comparing morbidity measures revealed that the Geriatric Index of Comorbidity was better predicting mortality risk than the CCI, Cumulative Illness Rating Scale, Index of Coexistent Disease, and disease count. CONCLUSIONS AND IMPLICATIONS: Higher morbidity measure scores are better in predicting mortality at longer follow-up period. The Geriatric Index of Comorbidity was best in predicting mortality and should be used more often in clinical practice to assist clinical decision making

Deep OCT Angiography Image Generation for Motion Artifact Suppression

Eye movements, blinking and other motion during the acquisition of optical coherence tomography (OCT) can lead to artifacts, when processed to OCT angiography (OCTA) images. Affected scans emerge as high intensity (white) or missing (black) regions, resulting in lost information. The aim of this research is to fill these gaps using a deep generative model for OCT to OCTA image translation relying on a single intact OCT scan. Therefore, a U-Net is trained to extract the angiographic information from OCT patches. At inference, a detection algorithm finds outlier OCTA scans based on their surroundings, which are then replaced by the trained network. We show that generative models can augment the missing scans. The augmented volumes could then be used for 3-D segmentation or increase the diagnostic value.Comment: Accepted at BVM 202

Nonclassical Recrystallization

Applications in the fields of materials science and nanotechnology increasingly demand monodisperse nanoparticles in size and shape. Up to now, no general purification procedure exists to thoroughly narrow the size and shape distributions of nanoparticles. Here, we show by analytical ultracentrifugation (AUC) as an absolute and quantitative high-resolution method that multiple recrystallizations of nanocrystals to mesocrystals is a very efficient tool to generate nanocrystals with an excellent and so-far unsurpassed size-distribution (PDIc=1.0001) and shape. Similar to the crystallization of molecular building blocks, nonclassical recrystallization removes “colloidal” impurities (i.e., nanoparticles, which are different in shape and size from the majority) by assembling them into a mesocrystal. In the case of nanocrystals, this assembly can be size- and shape-selective, since mesocrystals show both long-range packing ordering and preferable crystallographic orientation of nanocrystals. Besides the generation of highly monodisperse nanoparticles, these findings provide highly relevant insights into the crystallization of mesocrystals. © 2020 The Authors. Published by Wiley-VCH Gmb

Towards Deep End-of-Turn Prediction for Situated Spoken Dialogue Systems

Maier A, Hough J, Schlangen D. Towards Deep End-of-Turn Prediction for Situated Spoken Dialogue Systems. In: Proceedings of INTERSPEECH 2017. Stockholm, Sweden; 2017

Protocol for the Reconstructing Consciousness and Cognition (ReCCognition) Study

Important scientific and clinical questions persist about general anesthesia despite the ubiquitous clinical use of anesthetic drugs in humans since their discovery. For example, it is not known how the brain reconstitutes consciousness and cognition after the profound functional perturbation of the anesthetized state, nor has a specific pattern of functional recovery been characterized. To date, there has been a lack of detailed investigation into rates of recovery and the potential orderly return of attention, sensorimotor function, memory, reasoning and logic, abstract thinking, and processing speed. Moreover, whether such neurobehavioral functions display an invariant sequence of return across individuals is similarly unknown. To address these questions, we designed a study of healthy volunteers undergoing general anesthesia with electroencephalography and serial testing of cognitive functions (NCT01911195). The aims of this study are to characterize the temporal patterns of neurobehavioral recovery over the first several hours following termination of a deep inhaled isoflurane general anesthetic and to identify common patterns of cognitive function recovery. Additionally, we will conduct spectral analysis and reconstruct functional networks from electroencephalographic data to identify any neural correlates (e.g., connectivity patterns, graph-theoretical variables) of cognitive recovery after the perturbation of general anesthesia. To accomplish these objectives, we will enroll a total of 60 consenting adults aged 20–40 across the three participating sites. Half of the study subjects will receive general anesthesia slowly titrated to loss of consciousness (LOC) with an intravenous infusion of propofol and thereafter be maintained for 3 h with 1.3 age adjusted minimum alveolar concentration of isoflurane, while the other half of subjects serves as awake controls to gauge effects of repeated neurobehavioral testing, spontaneous fatigue and endogenous rest-activity patterns

Anti Stokes Thermometry of Plasmonic Nanoparticle Arrays

Metallic nanoparticles possess strong photothermal responses, especially when illuminated as ensembles due to collective effects. However, accurately quantifying the temperature increase remains a significant challenge, impeding progress in several applications. Anti Stokes thermometry offers a promising solution by enabling direct and non-invasive temperature measurements of the metal without the need for labeling or prior calibration. While Anti Stokes thermometry is successfully applied to individual nanoparticles, its potential to study light-to-heat conversion with plasmonic ensembles remains unexplored. In this study, the theoretical framework and the conditions that must be fulfilled for applying Anti Stokes thermometry to ensembles of nanoparticles are discussed. Then, this technique is implemented to measure the light-induced heating of square arrays of Au nanodisks. The obtained temperature measurements are validated using wavefront microscopy, demonstrating excellent agreement between the two thermometry methods. These results showcase the extension of Anti Stokes thermometry to plasmonic ensembles, highlighting its potential for implementation in the diverse photothermal applications involving these systems