Do Social Bots Dream of Electric Sheep? A Categorisation of Social Media Bot Accounts

So-called 'social bots' have garnered a lot of attention lately. Previous research showed that they attempted to influence political events such as the Brexit referendum and the US presidential elections. It remains, however, somewhat unclear what exactly can be understood by the term 'social bot'. This paper addresses the need to better understand the intentions of bots on social media and to develop a shared understanding of how 'social' bots differ from other types of bots. We thus describe a systematic review of publications that researched bot accounts on social media. Based on the results of this literature review, we propose a scheme for categorising bot accounts on social media sites. Our scheme groups bot accounts by two dimensions - Imitation of human behaviour and Intent.Comment: Accepted for publication in the Proceedings of the Australasian Conference on Information Systems, 201

Decision-Making in a Social Multi-Armed Bandit Task: Behavior, Electrophysiology and Pupillometry

Understanding, predicting, and learning from other people's actions are fundamental human social-cognitive skills. Little is known about how and when we consider other's actions and outcomes when making our own decisions. We developed a novel task to study social influence in decision-making: the social multi-armed bandit task. This task assesses how people learn policies for optimal choices based on their own outcomes and another player's (observed) outcomes. The majority of participants integrated information gained through observation of their partner similarly as information gained through their own actions. This lead to a suboptimal decision-making strategy. Interestingly, event-related potentials time-locked to stimulus onset qualitatively similar but the amplitudes are attenuated in the solo compared to the dyadic version. This might indicate that arousal and attention after receiving a reward are sustained when a second agent is present but not when playing alone.Comment: Accepted for publication in The 41st Annual Meeting of the Cognitive Science Society (CogSci 2019

Overlay Accuracy Limitations of Soft Stamp UV Nanoimprint Lithography and Circumvention Strategies for Device Applications

In this work multilevel pattering capabilities of Substrate Conformal Imprint Lithography (SCIL) have been explored. A mix & match approach combining the high throughput of nanoimprint lithography with the excellent overlay accuracy of electron beam lithography (EBL) has been exploited to fabricate nanoscale devices. An EBL system has also been utilized as a benchmarking tool to measure both stamp distortions and alignment precision of this mix & match approach. By aligning the EBL system to 20 mm x 20 mm and 8 mm x 8 mm cells to compensate pattern distortions of order of $3 \mu m$ over 6 inch wafer area, overlay accuracy better than $1.2 \mu m$ has been demonstrated. This result can partially be attributed to the flexible SCIL stamp which compensates deformations caused by the presence of particles which would otherwise significantly reduce the alignment precision

Macrophage-derived Lipocalin-2 contributes to ischemic resistance mechanisms by protecting from renal injury

Renal ischemia-reperfusion injury triggers an inflammatory response associated to infiltrating macrophages which determines the further outcome of disease. Brown Norway rats are known to show endogenous resistance to ischemia-induced renal damage. By contrast, Sprague Dawley rats exhibit a higher susceptibility to ischemic injury. In order to ascertain cytoprotective mechanisms, we focused on the implication of lipocalin-2 protein in main resistance mechanisms in renal ischemia/reperfusion injury by using adoptive macrophage administration, genetically modified ex vivo either to overexpress or to knockdown lipocalin-2. In vitro experiments with bone marrow-derived macrophages both from Brown Norway rats and from Sprague Dawley rats under hypoxic conditions showed endogenous differences regarding cytokine and lipocalin-2 expression profile in the two strains. Most interestingly, we observed that macrophages of the resistant strain express significantly more lipocalin-2. In vivo studies showed that tubular epithelial cell apoptosis and renal injury significantly increased and reparative markers decreased in Brown Norway rats after injection of lipocalin-2-knockdown macrophages, while the administration of lipocalin-2-overexpressing cells significantly decreased Sprague Dawley susceptibility. These data point to a crucial role of macrophage-derived lipocalin-2 in endogenous cytoprotective mechanisms. We conclude that expression of lipocalin-2 in tissue-infiltrating macrophages is pivotal for kidney-intrinsic cytoprotective pathways during ischemia reperfusion injury.The authors would like to thank M Ángeles Muñoz for her excellent technical support. This work was supported by grants from FIS PI12/00720 from Instituto de Salud Carlos III cofunded by FEDER funds/European Regional Development Fund (ERDF)-a way to buid Europe- and SENEFRO (awarded to AS) and SAF 2012-39947-02 (awarded to GH). MJ was supported by a grant from Fritz Thyssen Stiftung (Az.10.12.2.156) and a grant from University of Frankfurt (Focus Line B) and AS is supported by Miguel Servet II contracting system (CPII 14/00026).Peer Reviewe

Maternal Immune Activation Causes Behavioral Impairments and Altered Cerebellar Cytokine and Synaptic Protein Expression

Emerging epidemiology studies indicate that maternal immune activation (MIA) resulting from inflammatory stimuli such as viral or bacterial infections during pregnancy serves as a risk factor for multiple neurodevelopmental disorders including autism spectrum disorders and schizophrenia. Although alterations in the cortex and hippocampus of MIA offspring have been described, less evidence exists on the impact on the cerebellum. Here, we report altered expression of cytokines and chemokines in the cerebellum of MIA offspring, including increase in the neuroinflammatory cytokine TNFα and its receptor TNFR1. We also report reduced expression of the synaptic organizing proteins cerebellin-1 and GluRδ2. These synaptic protein alterations are associated with a deficit in the ability of cerebellar neurons to form synapses and an increased number of dendritic spines that are not in contact with a presynaptic terminal. These impairments are likely contributing to the behavioral deficits in the MIA exposed offspring

Organization of Valence-Encoding and Projection-Defined Neurons in the Basolateral Amygdala

The basolateral amygdala (BLA) mediates associative learning for both fear and reward. Accumulating evidence supports the notion that different BLA projections distinctly alter motivated behavior, including projections to the nucleus accumbens (NAc), medial aspect of the central amygdala (CeM), and ventral hippocampus (vHPC). Although there is consensus regarding the existence of distinct subsets of BLA neurons encoding positive or negative valence, controversy remains regarding the anatomical arrangement of these populations. First, we map the location of more than 1,000 neurons distributed across the BLA and recorded during a Pavlovian discrimination task. Next, we determine the location of projection-defined neurons labeled with retrograde tracers and use CLARITY to reveal the axonal path in 3-dimensional space. Finally, we examine the local influence of each projection-defined populations within the BLA. Understanding the functional and topographical organization of circuits underlying valence assignment could reveal fundamental principles about emotional processing. Basolateral amygdala (BLA) neurons distinctly encode cues predicting rewards or punishments, but how does form give rise to function? Beyeler et al. overlay anatomical projection target, location of neurons in a 3D map, and encoding properties during cue discrimination. The influence on local networks differs across projection-defined BLA populations. Keywords: reward; aversion; topography; tracing; connectivity; network; channelrhodopsin; phototagging; photoexcitation; photoinhitionNational Institute of Mental Health (U.S.) (Grant R01-MH102441)National Institute of Diabetes and Digestive and Kidney Diseases (U.S.) (Award DP2-DK-102256

50 Years of Test (Un)fairness: Lessons for Machine Learning

Quantitative definitions of what is unfair and what is fair have been introduced in multiple disciplines for well over 50 years, including in education, hiring, and machine learning. We trace how the notion of fairness has been defined within the testing communities of education and hiring over the past half century, exploring the cultural and social context in which different fairness definitions have emerged. In some cases, earlier definitions of fairness are similar or identical to definitions of fairness in current machine learning research, and foreshadow current formal work. In other cases, insights into what fairness means and how to measure it have largely gone overlooked. We compare past and current notions of fairness along several dimensions, including the fairness criteria, the focus of the criteria (e.g., a test, a model, or its use), the relationship of fairness to individuals, groups, and subgroups, and the mathematical method for measuring fairness (e.g., classification, regression). This work points the way towards future research and measurement of (un)fairness that builds from our modern understanding of fairness while incorporating insights from the past.Comment: FAT* '19: Conference on Fairness, Accountability, and Transparency (FAT* '19), January 29--31, 2019, Atlanta, GA, US