Miracle-dz/UniFAR-FTUs huggingface dataset:
Synthesizing Natural and Believable Emotional Expressions

puting experiments focused primarily on recognizing simpler emotions such as anger, fear, joy, and surprise. Today, affective computing algorithms and applica­ tions within devices has progressed in the capacity to understand a wider array of emotions, but there are still challenges to adequately synthesize the range of complex emotions. In this chapter, we cover some of the historical context of emo­ tional expression within affective computing, key questions, states of emotions, applications, and techniques related to emotional expression. The focus of this chapter is to identify how affective computing techniques have been and can be used to develop computational agents that are believable to humans. Here we offer progress and challenges for the future of computer systems that synthesize natural and believable emotional expressions. For the purposes of this chapter, natural and believable instantiate a sense of human-like ability to express emotions. As with humans, affective computing sys­ tems evolve in their ability to represent expressive nuances; the challenge is to manage the interplay between learning how to recognize emotional expressions and then develop techniques to recreate these emotions in a believable form. To this end, one of the major challenges is to facilitate computational learning that can communicate intentions via emotions to humans. The analogy of human and computer carries further in that if a human received limited input, the scope of emotion recognition and expression will be limited to a specific context and may not be able to accurately recognize emotions stemming from cultural, racial, and other biases [Tanaka et al. 2010, Xu et al. 2020], including only experiencing and Synthesizing Natural and Believable Emotional Expressions
Machine learning based intrusion detection as a service: task assignment and capacity allocation in a multi-tier architecture

Intrusion Detection Systems (IDS) play an important role for detecting network intrusions. Because the intrusions have many variants and zero days, traditional signature- and anomaly-based IDS often fail to detect it. Machine learning (ML), on the other hand, has better capabilities for detecting variants. In this paper, we adopt ML-based IDS which consists of three in-sequence tasks: pre-processing, binary detection, and multi-class detection. We proposed ten different task assignments, which map these three tasks into a three-tier network for distributed IDS. We evaluated these with queueing theory to determine which tasks assignments are more appropriate for particular service providers. With simulated annealing, we allocated the total capacity appropriately to each tier. Our results suggest that the service provider can decide on the task assignments that best suit their needs. Only edge or a combination of edge and cloud could be utilized due to their shorter delay and greater operational simplicity. Utilizing only the fog or a combination of fog and edge remains the most private, which allows tenants to not have to share their raw private data with other parties and save more bandwidth. A combination of fog and cloud is easier to manage while still addressing privacy concerns, but the delay was 40% slower than the fog and edge combination. Our results also indicate that more than 85% of the total capacity is allocated and spread across nodes in the lowest tier for pre-processing to reduce delays.
Reinforcement Learning and Affective Computing

prises an agent and an environment that the agent does not control. The agent has a goal in the environment. It wants something. The agent has the ability to take actions in the environment. After taking an action it can perceive how the action has changed its relationship to the environment (state change) and it also may receive a signal that indicates that it has made progress toward its goal (a reward signal). The agent learns to modify its behavior to maximize the reward signal. In reinforcement learning, the agent learns dynamically from its environment. Unlike supervised learning methods, reinforcement learning does not require labeled training sets that are often both unavailable and difficult to develop for affective data, making these methods extremely attractive for affective computing. Beyond this, however, because the reinforcement learning problem is modeled after the way human and animals learn, and based in psychology, it provides an excel­ lent framework for modeling affect and building next-generation intelligences that more closely resemble human intelligence. Emotion plays a role in both learning and reasoning for humans and extending the reinforcement learning framework to incorporate a model of emotion is of interest to both machine learning and affective modeling researchers [Moerland et al. 2018]. Emotion can be seen as a key enabler of reinforcement learning in the real world. It contributes to goal formation (wanting things), it provides the capacity to interpret signals from the environment as reward (pleasure and pain) and it helps us viscerally value being in certain states. Emotion has been found to be critical to Reinforcement Learning and Affective Computing
Researching for GIS annotation: The design of a conversational annotation interface

Using maps has become a daily activity for virtually everyone. However, in terms of interactive maps are limited. Rich interaction, such as issuing a complex query: “Which route has more greenery for my evening run? ” is currently impossible to process for most Geographic Information Systems (GIS). To enable such rich interaction, data in GIS needs to be extended with high-level semantic annotations. Such annotations, due to their intrinsic semantic nature, can currently only be supplied by humans, who might moreover also need to have some expert knowledge about GIS in order to produce useful annotations. Given the cognitive resources required, the number of annotations to be made, and the tediousness of the task, there is a need to design systems that can support experts in completing such annotation tasks. We report on a study comparing two alternative systems for performing GIS annotations, a Conversational User Interface (CUI), designed for the purpose of this study, and a Web interface with NN GIS, which reflects the current state-of-the-art used by experts. We find that CUIs can indeed help to improve the accuracy and efficiency of the annotations. We conclude the paper with some tentative design principles for annotation systems coupled to complex user interfaces.
A new pulmonary disease diagnosis system based on EfficientNet and transfer learning: pulmonary disease diagnosis based on EfficientNet and TL

Pulmonary epidemic diseases are one of the main causes of human death. Pulmonary epidemic diseases are usually highly contagious because they can be transmitted by droplets. In this study, we mainly focus on two types of common pulmonary epidemic diseases: COVID-19 and tuberculosis. COVID-19 has spread all around the globe since December 2019. The widespread COVID-19 caused the lockdown of the cities and economic losses. On the other hand, tuberculosis is among the ten highest human killers. Accurate and rapid diagnosis of pulmonary epidemic diseases is the primary step in clinical treatment. Therefore, we propose to leverage deep learning models to identify pulmonary epidemic diseases based on chest computed tomography (CT) images. We select the EfficientNet as the backbone model and employ a transfer learning method to train the model on our chest CT dataset. Experimental results reveal that our method can achieve promising classification performance, which is comparable to state-of-the-art approaches.
I wanted to honour your journal, and you spat in my face: emotive (im)politeness and face in the English and Russian blind peer review

Abstract This study explores the degree to which politeness and emotive considerations are respected across two different academic traditions and linguistic settings; in Russian and English blind peer reviews. It analyses 120 authentic reviews (70 Russian and 50 British English) with the negative verdicts: “Reject” and “To be resubmitted after substantial revisions” using a pragmatic, contextual and contrastive methodology. Drawing on (im)politeness theory, intercultural pragmatics and cultural studies, we explore the construction of alternative meanings in reviewers’ messages, and theorize that consideration for the face requirements of the reviewee may account for the lingua-cultural choices of the reviewer. We explore structural, linguistic, communicative and stylistic differences in English and Russian reviews. The results show that despite reviewers’ individual styles there are some culture-specific traits in the styles of reviews. Emotive politeness, we have suggested, appears to be (pre)determined by the sociocultural context and is more typical of English communication than Russian. We account for the differences in terms of sociocultural context, value differences and the use of different mechanisms of politeness. Our results confirm that politeness is not only social, but is also a psychological phenomenon based on empathy, whose manifestations may vary across cultures.
Title 1 Worldwide analysis of reef surveys sorts coral taxa by ( adaptive ) 2 response to heat stress 3 4

18 Coral reefs around the world are under threat due to widespread decline of hard corals caused by 19 anomalous heat waves. Different coral taxa are known to have different sensitivities to heat. 20 However, little is known about how long-term effects of heat exposure differ between coral taxa, 21 nor in particular how such effects might drive adaptive processes. Here, we combined worldwide 22 reef survey data with remotely sensed thermal anomalies to evaluate how local rates of taxa23 specific coral cover were associated with heat stress. We found a negative association between 24 coral cover and heat stress: weaker for massive and encrusting Poritidae, for meandroid Favidae 25 and Mussidae; and stronger for branching, tabular and corymbose Acroporidae. Additionally, we 26 found that coral cover decline driven by recent heat stress (measured as the year before a survey) 27 was mitigated by long-term past heat (measured since 1985) in branching, tabular and corymbose 28 Acroporidae and Pocilloporidae, but not in Poritidae, Favidae and Mussidae. This mitigation of coral 29 decline was not observed under the effect of short-term past heat (measured during the two 30 previous years), suggesting that these presumptive adaptive processes are the result of evolutionary 31 adaptation, rather than of physiological acclimatization. We finally queried the Coral Trait Database 32 to characterize morphological, physiological and reproductive traits of different taxa showing 33 similar heat-responses. Further genomics studies should confirm the evolutionary origin of such 34 divergent adaptive responses to heat stress. 35 36 37
Editorial: Active Vision and Perception in Human-Robot Collaboration

Department of Psychology, Università degli Studi di Milano-Bicocca, Milan, Italy, 2 School of Computer Science and Electronic Engineering, University of Essex, Colchester, United Kingdom, Department of Psychology, University of Essex, Colchester, United Kingdom, Department of Electronic Systems, Aalborg University, Aalborg, Denmark, Department of Mathematics and Computer Science, University of Catania, Catania, Italy
The Impact of an Audience on the Appeal of Virtual Reality

Virtual reality in a public place is enticing for some yet daunting for others. Social Impact theory proposes that performing in front of larger (vs. smaller) audiences is typically seen as more anxiety provoking and less desirable. Having peers perform with you can offset this, however. Our goal was to test whether Social Impact theory extends to the context of trying virtual reality in a busy public setting, and whether any such effects are influenced by extroversion and trait anxiety. In Experiment 1, we ran an online study with 100 participants and found that images of people trying virtual reality in front of others were indeed rated as more anxiety provoking than images with no audiences. Images with (vs. without) audiences were also rated as scenarios in which people would be less willing to try virtual reality. There was no impact of extroversion levels on people’s reported Willingness to Try; however extroverted individuals were less affected by audience size compared to introverts in terms of how anxiety-provoking they considered the scenario. Experiment 1 also found that the presence of a monitor showing one’s virtual reality “performance” made Extroverts keener to try the experience, yet Introverts less keen. Experiment 2 tested whether the main findings of the first study extended to a real-world scenario. 69 participants observed 0–3 individuals trying a virtual-reality experience in the foyer of a busy library and were then questioned on expected anxiety levels and Willingness to Try. Whilst anxiety levels were again influenced by the audience size (number of people in the foyer at the start of each test), there was no impact of audience size on Willingness to Try virtual reality. Note that relative inattention of the audience on those trying VR in Experiment 2 (compared to Experiment 1), as well as a small sample size, may have made it hard to detect effects here. Extroverts were again less anxious about trying VR in-front of others compared to introverts. These findings offer some ways to make public space virtual reality experiences more accessible, whilst suggesting future steps to properly assess some exploratory findings presented here.
Exogenous Application of Gallic Acid Induces the Direct Defense of Tea Plant Against Ectropis obliqua Caterpillars

Gallic acid (GA), an important polyphenolic compound in the plant, is a well-known antioxidant, antihyperglycemic, and anti-lipid peroxidative agent. Recently, GA treatment exhibited ameliorative effects on plants in response to some abiotic stresses. However, the elicitation effect of GA on plant defense against herbivorous insects has not yet been reported. In this study, we found that the exogenous application of GA induced the direct defense of tea plant (Camellia sinensis) against tea geometrid (Ectropis obliqua) larvae, through activating jasmonic acid (JA) signaling and phenylpropanoid pathways. These signaling cascades resulted in the efficient induction of several defensive compounds. Among them, astragalin, naringenin, and epigallocatechin-3-gallate were the three of the most active anti-feeding compounds. However, the exogenous GA treatment did not affect the preference of E. obliqua female moths and larval parasitoid Apanteles sp. Our study suggests that GA may serve as an elicitor that triggers a direct defense response against tea geometrid larvae in tea plants. This study will help to deepen the understanding of the interaction between plants and phytophagous insects and also provide theoretical and technical guidance for the development of plant defense elicitors.
Astrocytes and Inflammatory T Helper Cells: A Dangerous Liaison in Multiple Sclerosis

Multiple Sclerosis (MS) is a neurodegenerative autoimmune disorder of the central nervous system (CNS) characterized by the recruitment of self-reactive T lymphocytes, mainly inflammatory T helper (Th) cell subsets. Once recruited within the CNS, inflammatory Th cells produce several inflammatory cytokines and chemokines that activate resident glial cells, thus contributing to the breakdown of blood-brain barrier (BBB), demyelination and axonal loss. Astrocytes are recognized as key players of MS immunopathology, which respond to Th cell-defining cytokines by acquiring a reactive phenotype that amplify neuroinflammation into the CNS and contribute to MS progression. In this review, we summarize current knowledge of the astrocytic changes and behaviour in both MS and experimental autoimmune encephalomyelitis (EAE), and the contribution of pathogenic Th1, Th17 and Th1-like Th17 cell subsets, and CD8+ T cells to the morphological and functional modifications occurring in astrocytes and their pathological outcomes.
Using the Isolated Rat Placenta to Assess Fetoplacental Hemodynamics

Placental health is critical to fetal growth and maternal health during gestation. However, investigating placental flow in an ex-vivo isolated system where inflow is independently controlled has yet to be developed in the rat. Here, we describe a novel technique, isolated perfused placenta technique that allows for analysis of placental pressure outflow pressure, placental flow in rats at gestational day 20. Using this method, we successfully perfused placentas from dams and were able to observe increases in outflow pressure and flow as the inflow pressure to the placenta was increased in a step wise fashion. This method will help to advance the functional analysis of placental flow and therefore placental resistance and efficiency.
A Case Study to Establish a Basis for Evaluating Geographic Origin Claims of Timber From the Solomon Islands Using Stable Isotope Ratio Analysis

Global demand for low-cost forest products is leading manufacturers and traders to source timber and wood products from vulnerable nations and delicate ecosystems. One small island nation, the Solomon Islands, is seeing exploitation of natural resources accelerating to such a point that its natural forests may be exhausted by 2036. The main causes of natural forest loss on the archipelago are unsustainable or illegal logging practices. Various laws in consumer countries require that members of industry ensure that only legally sourced timber is placed onto their respective national markets. Those that break these laws or fail to act in a way that is compliant may be subject to harsh penalties. This study aims to establish scientific data to evaluate claims that timber has originated from the Solomon Islands. This will enable Operators to carry out due diligence analysis and permit members of Law Enforcement to conduct forensic investigations. Eighty timber core samples comprising 13 different genera of tropical trees were obtained from mature trees in two sites in the Solomon Islands (Guadalcanal and Kolombangara islands) during the period August 2019 to November 2019 using a Pickering Punch sampling device. Homogenised core samples were subject to δ18O, δ2H, δ13C, and δ34S stable isotope analysis using elemental analysis-isotope ratio mass spectrometry. Additional stable isotope data from relevant taxa and geographic origins (elevation, geographic co-ordinates) were also included in this research as an initial assessment of differences in stable isotope ratios between countries. Results show that significant differences are evident in the stable isotope ratios of the sampled taxa within the Solomon Islands (Guadalcanal and Kolombangara Islands) and between other countries. These data can be used as a basis of evaluation to evaluate origin claims of timber or wood products from the Solomon Islands, particularly Kolombangara Island. Furthermore, in the right context, these data can also be used to establish whether timber or wood products declared to be from origins other than the Solomon Islands have stable isotope ratios that are consistent with data from the Solomon Islands. If not, this would suggest foreign timber/forest products are from elsewhere and are being passed-off as originating from the Solomon Islands.
The Effects of a Single Transcranial Direct Current Stimulation Session on Impulsivity and Risk Among a Sample of Adult Recreational Cannabis Users

Individuals with substance use disorders exhibit risk-taking behaviors, potentially leading to negative consequences and difficulty maintaining recovery. Non-invasive brain stimulation techniques such as transcranial direct current stimulation (tDCS) have yielded mixed effects on risk-taking among healthy controls. Given the importance of risk-taking behaviors among substance-using samples, this study aimed to examine the effects of tDCS on risk-taking among a sample of adults using cannabis. Using a double-blind design, 27 cannabis users [M(SD) age = 32.48 (1.99), 41% female] were randomized, receiving one session of active or sham tDCS over the bilateral dorsolateral prefrontal cortex (dlPFC). Stimulation parameters closely followed prior studies with anodal right dlPFC and cathodal left dlPFC stimulation. Risk-taking—assessed via a modified Cambridge Gambling Task—was measured before and during tDCS. Delay and probability discounting tasks were assessed before and after stimulation. No significant effects of stimulation on risk-taking behavior were found. However, participants chose the less risky option ∼86% of the trials before stimulation which potentially contributed to ceiling effects. These results contradict one prior study showing increased risk-taking among cannabis users following tDCS. There was a significant increase in delay discounting of a $1000 delayed reward during stimulation for the sham group only, but no significant effects for probability discounting. The current study adds to conflicting and inconclusive literature on tDCS and cognition among substance-using samples. In conclusion, results suggest the ineffectiveness of single session dlPFC tDCS using an established stimulation protocol on risk-taking, although ceiling effects at baseline may have also prevented behavior change following tDCS.
Evaluation of Laser Confocal Raman Spectroscopy as a Non-Invasive Method for Detecting Sperm DNA Contents

Research Question Is Raman spectroscopy an efficient and accurate method to detect sperm chromosome balance state by DNA content differences? Design Semen samples were provided by diploid healthy men, and the analysis parameters met the current World Health Organization standards. The DNA content was assessed by analysis of the corresponding spectra obtained from a laser confocal Raman spectroscope. The sperm sex chromosome information was obtained by fluorescence in situ hybridization (FISH). Comparative analysis was performed between FISH results and Raman spectral analysis results. Results Different parts of the sperm head showed different spectral signal intensities, which indicated that there were different chemical components. Standard principal component analysis (PCA) can preliminarily classify sperm with different DNA contents into two groups. Further analysis showed that there were significant differences in the 785 DNA backbone peaks and 714–1,162 cm−1 DNA skeleton regions among sperm with different DNA contents. The peak and regional peak of the DNA skeleton of X sperm were significantly higher than those of Y sperm (X vs. Y, p < 0.05). The above sperm types were confirmed by FISH. ROC curve analysis shows that there is a correlation between the Raman spectrum data and FISH results. Conclusion Raman spectroscopy can identify X and Y sperms by analyzing the DNA content difference. However, the accuracy of the detection still needs to be improved. Nevertheless, Raman spectroscopy has a potential application value in the field of sperm aneuploidy detection and may even be used as a non-invasive predictor of sperm aneuploid state in preimplantation genetic testing (PGT-A).