bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multi-species test and calibration of an improved transient thermal dissipation system of sap flow measurement with a single probe
Authors: Nhean Sophea , Isarangkool Na Ayutthaya Supat , Rocheteau Alain , Do Frederic C 
Published: March 2019

Abstract
Transient thermal dissipation (TTD) systems provide a simple way to measure xylem sap flow with dual or single Granier-type probe, which gives lower energy consumption and higher accuracy due to its lessor sensitivity to thermal interferences. A new system, TTD heat within 5 min (TTD5), proposed on the reduction of the heating duration. This evolution captured interest through decreased energy consumption and increased temporal resolution. Within our study, the first objective was to test and calibrate this new system with a single probe for young rubber tree – Hevea brasiliensis. The second objective was to explore the sources of variability in calibration such as species, individual cut-stems and probe–wood contact. The complementary species consisted of two diffuse-porous species (mango tree – Mangifera indica, eucalyptus tree – Eucalyptus camaldulensis) and one ring-porous species (teak tree – Tectonia grandis). Twenty-eight response curves were assessed over a large range of flux densities from 0.5 to 10 l dm−2 h−1. The incremental rise of temperature from 30 to 300 s (T300–30) after commencement of heating was sensitive to flux density over the complete range. Compared with the full signal at 300 s, the incremental signal markedly reduced the variability between response curves within species and between species. Moreover, a new index K2, defined as (T0 – Tu)/T0, normalized the responses between 0 and 1. However, the responses had a non-linear trend above 5 l dm−2 h−1. Within diffuse-porous wood type, the species did not differ in calibration, whereas the ring-porous species was markedly different. A sigmoid function provided the best fit for the diffuse-porous species. Individual stems were identified as the main source of within-species variability in calibration. The normalizing K2 index removed the influence of probe–wood contacts, controlled through drilling difference; however, there was still an effect of individual stems interacting with flux density (P = 0.019). Replications of cut-stems and response curves are necessary to assess a reliable averaged calibration. In conclusion, the applicability of the TTD5 system with a single probe has been confirmed and several sources of variability in calibration have been evaluated.
Live human–robot interactive public demonstrations with automatic emotion and personality prediction
Authors: Gunes Hatice , Celiktutan Oya , Sariyanidi Evangelos 
Published: March 2019

Communication with humans is a multi-faceted phenomenon where the emotions, personality and non-verbal behaviours, as well as the verbal behaviours, play a significant role, and human–robot interaction (HRI) technologies should respect this complexity to achieve efficient and seamless communication. In this paper, we describe the design and execution of five public demonstrations made with two HRI systems that aimed at automatically sensing and analysing human participants’ non-verbal behaviour and predicting their facial action units, facial expressions and personality in real time while they interacted with a small humanoid robot. We describe an overview of the challenges faced together with the lessons learned from those demonstrations in order to better inform the science and engineering fields to design and build better robots with more purposeful interaction capabilities.
This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction’.
Natural language generation for social robotics: opportunities and challenges
Authors: Foster Mary Ellen 
Published: March 2019

In the increasingly popular and diverse research area of social robotics, the primary goal is to develop robot agents that exhibit socially intelligent behaviour while interacting in a face-to-face context with human partners. An important aspect of face-to-face social conversation is fluent, flexible linguistic interaction; face-to-face dialogue is both the basic form of human communication and the richest and most flexible, combining unrestricted verbal expression with meaningful non-verbal acts such as gestures and facial displays, along with instantaneous, continuous collaboration between the speaker and the listener. In practice, however, most developers of social robots tend not to use the full possibilities of the unrestricted verbal expression afforded by face-to-face conversation; instead, they generally tend to employ relatively simplistic processes for choosing the words for their robots to say. This contrasts with the work carried out Natural Language Generation (NLG), the field of computational linguistics devoted to the automated production of high-quality linguistic content; while this research area is also an active one, in general most effort in NLG is focused on producing high-quality written text. This article summarizes the state of the art in the two individual research areas of social robotics and natural language generation. It then discusses the reasons why so few current social robots make use of more sophisticated generation techniques. Finally, an approach is proposed to bringing some aspects of NLG into social robotics, concentrating on techniques and tools that are most appropriate to the needs of socially interactive robots.
This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction’.
Social behaviour as an emergent property of embodied curiosity: a robotics perspective
Authors: Gordon Goren 
Published: March 2019

Social interaction is an extremely complex yet vital component in daily life. We present a bottom-up approach for the emergence of social behaviours from the interaction of the curiosity drive, i.e. the intrinsic motivation to learn as much as possible, and the embedding environment of an agent. Implementing artificial curiosity algorithms in robots that explore human-like environments results in the emergence of a hierarchical structure of learning and behaviour. This structure resembles the sequential emergence of behavioural patterns in human babies, culminating in social behaviours, such as face detection, tracking and attention-grabbing facial expressions. These results suggest that an embodied curiosity drive may be the progenitor of many social behaviours if satiated by a social environment.This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction’.
Predictive learning: its key role in early cognitive development
Authors: Nagai Yukie 
Published: March 2019

What is a fundamental ability for cognitive development? Although many researchers have been addressing this question, no shared understanding has been acquired yet. We propose that predictive learning of sensorimotor signals plays a key role in early cognitive development. The human brain is known to represent sensorimotor signals in a predictive manner, i.e. it attempts to minimize prediction error between incoming sensory signals and top–down prediction. We extend this view and suggest that two mechanisms for minimizing prediction error lead to the development of cognitive abilities during early infancy. The first mechanism is to update an immature predictor. The predictor must be trained through sensorimotor experiences because it does not inherently have prediction ability. The second mechanism is to execute an action anticipated by the predictor. Interacting with other individuals often increases prediction error, which can be minimized by executing one's own action corresponding to others’ action. Our experiments using robotic systems replicated developmental dynamics observed in infants. The capabilities of self–other cognition and goal-directed action were acquired based on the first mechanism, whereas imitation and prosocial behaviours emerged based on the second mechanism. Our theory further provides a potential mechanism for autism spectrum condition. Atypical tolerance for prediction error is hypothesized to be a cause of perceptual and social difficulties.This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction’.
Fusing autonomy and sociality via embodied emergence and development of behaviour and cognition from fetal period
Authors: Kuniyoshi Yasuo 
Published: March 2019

Human-centred AI/Robotics are quickly becoming important. Their core claim is that AI systems or robots must be designed and work for the benefits of humans with no harm or uneasiness. It essentially requires the realization of autonomy, sociality and their fusion at all levels of system organization, even beyond programming or pre-training. The biologically inspired core principle of such a system is described as the emergence and development of embodied behaviour and cognition. The importance of embodiment, emergence and continuous autonomous development is explained in the context of developmental robotics and dynamical systems view of human development. We present a hypothetical early developmental scenario that fills in the very beginning part of the comprehensive scenarios proposed in developmental robotics. Then our model and experiments on emergent embodied behaviour are presented. They consist of chaotic maps embedded in sensory–motor loops and coupled via embodiment. Behaviours that are consistent with embodiment and adaptive to environmental structure emerge within a few seconds without any external reward or learning. Next, our model and experiments on human fetal development are presented. A precise musculo-skeletal fetal body model is placed in a uterus model. Driven by spinal nonlinear oscillator circuits coupled together via embodiment, somatosensory signals are evoked and learned by a model of the cerebral cortex with 2.6 million neurons and 5.3 billion synapses. The model acquired cortical representations of self–body and multi-modal sensory integration. This work is important because it models very early autonomous development in realistic detailed human embodiment. Finally, discussions toward human-like cognition are presented including other important factors such as motivation, emotion, internal organs and genetic factors.This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction’.
Brain activity during reciprocal social interaction investigated using conversational robots as control condition
Authors: Rauchbauer Birgit , Nazarian Bruno , Bourhis Morgane , Ochs Magalie , Prévot Laurent , Chaminade Thierry 
Published: March 2019

We present a novel functional magnetic resonance imaging paradigm for second-person neuroscience. The paradigm compares a human social interaction (human–human interaction, HHI) to an interaction with a conversational robot (human–robot interaction, HRI). The social interaction consists of 1 min blocks of live bidirectional discussion between the scanned participant and the human or robot agent. A final sample of 21 participants is included in the corpus comprising physiological (blood oxygen level-dependent, respiration and peripheral blood flow) and behavioural (recorded speech from all interlocutors, eye tracking from the scanned participant, face recording of the human and robot agents) data. Here, we present the first analysis of this corpus, contrasting neural activity between HHI and HRI. We hypothesized that independently of differences in behaviour between interactions with the human and robot agent, neural markers of mentalizing (temporoparietal junction (TPJ) and medial prefrontal cortex) and social motivation (hypothalamus and amygdala) would only be active in HHI. Results confirmed significantly increased response associated with HHI in the TPJ, hypothalamus and amygdala, but not in the medial prefrontal cortex. Future analysis of this corpus will include fine-grained characterization of verbal and non-verbal behaviours recorded during the interaction to investigate their neural correlates.
This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction'.
A neurocognitive investigation of the impact of socializing with a robot on empathy for pain
Authors: Cross Emily S. , Riddoch Katie A. , Pratts Jaydan , Titone Simon , Chaudhury Bishakha , Hortensius Ruud 
Published: March 2019

To what extent can humans form social relationships with robots? In the present study, we combined functional neuroimaging with a robot socializing intervention to probe the flexibility of empathy, a core component of social relationships, towards robots. Twenty-six individuals underwent identical fMRI sessions before and after being issued a social robot to take home and interact with over the course of a week. While undergoing fMRI, participants observed videos of a human actor or a robot experiencing pain or pleasure in response to electrical stimulation. Repetition suppression of activity in the pain network, a collection of brain regions associated with empathy and emotional responding, was measured to test whether socializing with a social robot leads to greater overlap in neural mechanisms when observing human and robotic agents experiencing pain or pleasure. In contrast to our hypothesis, functional region-of-interest analyses revealed no change in neural overlap for agents after the socializing intervention. Similarly, no increase in activation when observing a robot experiencing pain emerged post-socializing. Whole-brain analysis showed that, before the socializing intervention, superior parietal and early visual regions are sensitive to novel agents, while after socializing, medial temporal regions show agent sensitivity. A region of the inferior parietal lobule was sensitive to novel emotions, but only during the pre-socializing scan session. Together, these findings suggest that a short socialization intervention with a social robot does not lead to discernible differences in empathy towards the robot, as measured by behavioural or brain responses. We discuss the extent to which long-term socialization with robots might shape social cognitive processes and ultimately our relationships with these machines.
This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction’.
Brain stimulation to left prefrontal cortex modulates attentional orienting to gaze cues
Authors: Wiese Eva , Abubshait Abdulaziz , Azarian Bobby , Blumberg Eric J. 
Published: March 2019

In social interactions, we rely on non-verbal cues like gaze direction to understand the behaviour of others. How we react to these cues is determined by the degree to which we believe that they originate from an entity with a mind capable of having internal states and showing intentional behaviour, a process calledmind perception. While prior work has established a set of neural regions linked to mind perception, research has just begun to examine how mind perception affects social-cognitive mechanisms like gaze processing on a neuronal level. In the current experiment, participants performed a social attention task (i.e. attentional orienting to gaze cues) with either a human or a robot agent (i.e. manipulation of mind perception) while transcranial direct current stimulation (tDCS) was applied to prefrontal and temporo-parietal brain areas. The results show that temporo-parietal stimulation did not modulate mechanisms of social attention, neither in response to the human nor in response to the robot agent, whereas prefrontal stimulation enhanced attentional orienting in response to human gaze cues and attenuated attentional orienting in response to robot gaze cues. The findings suggest that mind perception modulates low-level mechanisms of social cognition via prefrontal structures, and that a certain degree of mind perception is essential in order for prefrontal stimulation to affect mechanisms of social attention.This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction’.
Immediate and deferred epigenomic signature of neuronal activation
Authors: Fernandez-Albert Jordi , Lipinski Michal , Lopez-Cascales María T. , Rowley M. Jordan , Martin-Gonzalez Ana M. , del Blanco Beatriz , Corces Victor G. , Barco Angel 
Published: March 2019

SummaryActivity-driven transcription plays an important role in many brain processes, including those underlying memory and epilepsy. Here, we combine the genetic tagging of neuronal nuclei and ribosomes with various sequencing-based techniques to investigate the transcriptional and chromatin changes occurring at hippocampal excitatory neurons upon synchronous activation during status epilepticus and sparse activation during novel context exploration. The transcriptional burst, which affects both nucleus-resident non-coding RNAs and numerous protein-coding genes involved in neuroplasticity, is associated with a dramatic increase in chromatin accessibility of activity-regulated genes and enhancers,de novobinding of activity-regulated transcription factors, augmented promoter-enhancer interactions, and the formation of gene loops that bring together the TSS and TTS of strongly induced genes to sustain the fast re-loading of RNAPII complexes. Remarkably, some chromatin occupancy changes and interactions remain long after neuronal activation and may underlie the changes in neuronal responsiveness and circuit connectivity observed in these neuroplasticity paradigms.
Synergetic effect of non-complementary 5’ AT-rich sequences on the development of a multiplex TaqMan real-time PCR for specific and robust detection of Clavibacter michiganensis and C. michiganensis subsp. nebraskensis
Authors: Larrea-Sarmiento Adriana , Alvarez Anne M. , Stack James P. , Arif Mohammad 
Published: March 2019

AbstractClavibacter is an agriculturally important genus comprising a single species, Clavibacter michiganensis, and multiple subspecies, including, C. michiganensis subsp. nebraskensis which causes Goss’s wilt/blight of corn and accounts for high yield losses - listed among the five most significant diseases of corn in the United States of America. Our research objective was to develop a robust and rapid multiplex TaqMan real-time PCR (qPCR) to detect C. michiganensis in general and C. michiganensis subsp. nebraskensis with enhanced reliability and accuracy by adding non-complementary AT sequences to the 5’ end of the forward and reverse primers. Comparative genomic analyses were performed to identify unique and conserved gene regions for primer and probe design. The unique genomic regions, ABC transporter ATP-binding protein CDS/ABC-transporter permease and MFS transporter were determined for specific detection of C. michiganensis and C. m. subsp. nebraskensis, respectively. The AT-rich sequences at the 5’ position of the primers enhanced the reaction efficiency and sensitivity of rapid qPCR cycling; the reliability, accuracy and high efficiency of the developed assay was confirmed after testing with 59 strains from inclusivity and exclusivity panels – no false positives or false negatives were detected. The assays were also validated through naturally and artificially infected corn plant samples; all samples were detected for C. michiganensis and C. m. subsp. nebraskensis with 100% accuracy. The assay with 5’ AT-rich sequences detected up to 10- and 100-fg of C. michiganensis and C. michiganensis subsp. nebraskensis genome targets, respectively. No adverse effect was observed when sensitivity assays were spiked with host genomic DNA. Addition of 5’ AT rich sequences enhanced the qPCR reaction efficiency from 0.82 (M = -3.83) and 0.91 (M = -3.54) to 1.04 (with optimum slope value; M = -3.23) for both C. michiganensis and C. michiganensis subsp. nebraskensis, respectively; a increase of 10-fold sensitivity was also obtained with C. michiganensis primer set. The methodology proposed here can be used to optimize the reaction efficiency and to harmonize the diagnostic protocols which have prodigious applications in routine diagnostics, biosecurity and microbial forensics.
CUX1 and IκBζ mediate the synergistic inflammatory response to TNF and IL-17A in stromal fibroblasts
Authors: Slowikowski Kamil , Nguyen Hung N. , Noss Erika H. , Simmons Daimon P. , Mizoguchi Fumitaka , Watts Gerald F.M. , Gurish Michael F. , Brenner Michael B. , Raychaudhuri Soumya 
Published: March 2019

SummaryThe role of stromal fibroblasts in chronic inflammation is unfolding. In rheumatoid arthritis (RA), leukocyte-derived cytokines tumor necrosis factor (TNF) and IL-17A work together, activating fibroblasts to become a dominant source of the hallmark cytokine IL-6. However, IL-17A alone has minimal effect on fibroblasts. To identify key mediators of the synergistic response to TNF and IL-17A in human synovial fibroblasts, we performed time series, dose response, and gene silencing transcriptomics experiments. Here we show that in combination with TNF, IL-17A selectively induces a specific set of genes mediated by factors including CUX1 and IκBζ. In the promoters of CXCL1, CXCL2, and CXCL3, we found a putative CUX1-NF-κB binding motif not found elsewhere in the genome. CUX1 and NF-κB p65 mediate transcription of these genes independent of LIFR, STAT3, STAT4, and ELF3. Transcription of NFKBIZ, encoding the atypical IκB factor IκBζ, is IL-17A dose-dependent, and IκBζ only mediates the transcriptional response to TNF and IL-17A, but not to TNF alone. In fibroblasts, IL-17A response depends on CUX1 and IκBζ to engage the NF-κB complex to produce chemoattractants for neutrophil and monocyte recruitment.
Convergent loss of an EDS1/PAD4 signalling pathway in several plant lineages predicts new components of plant immunity and drought response
Authors: Baggs EL , Thanki AS , O’Grady R , Schudoma C , Haerty W , Krasileva KV 
Published: March 2019

AbstractPlant innate immunity relies on NLR receptors that recognize pathogen derived molecules and activate downstream signalling pathways. We analyzed the variation in copy number of NLR genes across flowering plants, and identified a number of species with a low number of NLRs relative to sister species. Two distinct lineages, one monocot (Lentibulariaceae) and one dicot (Alismatales) encapsulate four species with particularly few NLR genes. In these lineages, loss of NLRs coincided with loss of the well-known downstream immune signalling complex (EDS1-PAD4). When we expanded our analysis across the whole proteomes, we were able to identify other characterized immune genes absent only in Lentibulariaceae and Alismatales. Additionally, we identified a small subset of genes with unknown function convergently lost in all four species. We predicted that some of these genes may have a role in plant immunity. Gene expression analyses confirmed that a group of these genes was differentially expressed under pathogen infection. Another subset of these genes was differentially expressed upon drought providing further evidence of a link between the drought and plant immunity.