Clustering user preferences for personalized teleoperation control schemes via trajectory similarity analysis

Successful operation of a teleoperated robot depends on a well-designed control scheme to translate human motion into robot motion; however, a single control scheme may not be suitable for all users. On the other hand, individual personalization of control schemes may be infeasible for designers to produce. In this paper, we present a method by which users may be classified into groups with mutually compatible control scheme preferences. Users are asked to demonstrate freehand motions to control a simulated robot in a virtual reality environment. Hand pose data is captured and compared with other users using SLAM trajectory similarity analysis techniques. The resulting pairwise trajectory error metrics are used to cluster participants based on their control motions, without foreknowledge of the number or types of control scheme preferences that may exist. The clusters identified for two different robots shows that a small number of clusters form stably for each case, each with its own control scheme paradigm. Survey data from participants validates that the clusters identified through this method correspond to the participants' control scheme rationales, and also identify nuances in participant control scheme descriptions that may not be obvious to designers relying only on participant explanations of their preferences.

The integrated stress response in metabolic adaptation

The integrated stress response (ISR) refers to signaling pathways initiated by stress-activated eIF2α kinases. Distinct eIF2α kinases respond to different stress signals, including amino acid deprivation and mitochondrial stress. Such stress-induced eIF2α phosphorylation attenuates general mRNA translation and, at the same time, stimulates the preferential translation of specific downstream factors to orchestrate an adaptive gene expression program. In recent years, there have been significant new advances in our understanding of ISR during metabolic stress adaptation. Here, I discuss those advances, reviewing among others the ISR activation mechanisms in response to amino acid deprivation and mitochondrial stress. In addition, I review how ISR regulates the amino acid metabolic pathways and how changes in the ISR impact the physiology and pathology of various disease models.

sEMG-Based Robust Recognition of Grasping Postures with a Machine Learning Approach for Low-Cost Hand Control

The design and control of artificial hands remains a challenge in engineering. Popular prostheses are bio-mechanically simple with restricted manipulation capabilities, as advanced devices are pricy or abandoned due to their difficult communication with the hand. For social robots, the interpretation of human intention is key for their integration in daily life. This can be achieved with machine learning (ML) algorithms, which are barely used for grasping posture recognition. This work proposes an ML approach to recognize nine hand postures, representing 90% of the activities of daily living in real time using an sEMG human-robot interface (HRI). Data from 20 subjects wearing a Myo armband (8 sEMG signals) were gathered from the NinaPro DS5 and from experimental tests with the YCB Object Set, and they were used jointly in the development of a simple multi-layer perceptron in MATLAB, with a global percentage success of 73% using only two features. GPU-based implementations were run to select the best architecture, with generalization capabilities, robustness-versus-electrode shift, low memory expense, and real-time performance. This architecture enables the implementation of grasping posture recognition in low-cost devices, aimed at the development of affordable functional prostheses and HRI for social robots.

Real-time emotion generation in human-robot dialogue using large language models

Affective behaviors enable social robots to not only establish better connections with humans but also serve as a tool for the robots to express their internal states. It has been well established that emotions are important to signal understanding in Human-Robot Interaction (HRI). This work aims to harness the power of Large Language Models (LLM) and proposes an approach to control the affective behavior of robots. By interpreting emotion appraisal as an Emotion Recognition in Conversation (ERC) tasks, we used GPT-3.5 to predict the emotion of a robot's turn in real-time, using the dialogue history of the ongoing conversation. The robot signaled the predicted emotion using facial expressions. The model was evaluated in a within-subjects user study (N = 47) where the model-driven emotion generation was compared against conditions where the robot did not display any emotions and where it displayed incongruent emotions. The participants interacted with the robot by playing a card sorting game that was specifically designed to evoke emotions. The results indicated that the emotions were reliably generated by the LLM and the participants were able to perceive the robot's emotions. It was found that the robot expressing congruent model-driven facial emotion expressions were perceived to be significantly more human-like, emotionally appropriate, and elicit a more positive impression. Participants also scored significantly better in the card sorting game when the robot displayed congruent facial expressions. From a technical perspective, the study shows that LLMs can be used to control the affective behavior of robots reliably in real-time. Additionally, our results could be used in devising novel human-robot interactions, making robots more effective in roles where emotional interaction is important, such as therapy, companionship, or customer service.

Scaffolding the human partner by contrastive guidance in an explanatory human-robot dialogue

Explanation has been identified as an important capability for AI-based systems, but research on systematic strategies for achieving understanding in interaction with such systems is still sparse. Negation is a linguistic strategy that is often used in explanations. It creates a contrast space between the affirmed and the negated item that enriches explaining processes with additional contextual information. While negation in human speech has been shown to lead to higher processing costs and worse task performance in terms of recall or action execution when used in isolation, it can decrease processing costs when used in context. So far, it has not been considered as a guiding strategy for explanations in human-robot interaction. We conducted an empirical study to investigate the use of negation as a guiding strategy in explanatory human-robot dialogue, in which a virtual robot explains tasks and possible actions to a human explainee to solve them in terms of gestures on a touchscreen. Our results show that negation vs. affirmation 1) increases processing costs measured as reaction time and 2) increases several aspects of task performance. While there was no significant effect of negation on the number of initially correctly executed gestures, we found a significantly lower number of attempts-measured as breaks in the finger movement data before the correct gesture was carried out-when being instructed through a negation. We further found that the gestures significantly resembled the presented prototype gesture more following an instruction with a negation as opposed to an affirmation. Also, the participants rated the benefit of contrastive vs. affirmative explanations significantly higher. Repeating the instructions decreased the effects of negation, yielding similar processing costs and task performance measures for negation and affirmation after several iterations. We discuss our results with respect to possible effects of negation on linguistic processing of explanations and limitations of our study.

Staging Paro: The care of making robot(s) care

Paro, a baby seal robot, is arguably the best-known care robot worldwide. Its clinical effects on people with special needs have been studied for more than twenty years by multidisciplinary teams. However, there are very few studies of Paro 'in the wild', inserted in the routines and pressures of a care home, which is supposed to be Paro's natural environment. Based on fieldwork in a French public nursing home, this article relocates Paro's psychosocial effects - asserted by its corporate and academic advocates to stem from the robot's software and user-friendly design - in the situated practice of care deployed by the nursing staff. Although it is commonly assumed that the robot can interact autonomously, thanks to its AI, it took considerable efforts to enable 'patient-robot' interactions, and interactions were always mediated by care staff. The supervision of the interaction between Paro and its user(s) by at least one care worker, prescribed by its sales representative to prevent the seal robot from being harmed or monopolized by a resident, thus framed the very course and meaning of the interaction, through an entanglement of verbal and tactile guidance. Staging Paro often meant awakening and maintaining interest from confused or passive users, and playing with its ontological flexibility to meet the preferences of its elderly interlocutors.

Cellular Stress: Modulator of Regulated Cell Death

Cellular stress response activates a complex program of an adaptive response called integrated stress response (ISR) that can allow a cell to survive in the presence of stressors. ISR reprograms gene expression to increase the transcription and translation of stress response genes while repressing the translation of most proteins to reduce the metabolic burden. In some cases, ISR activation can lead to the assembly of a cytoplasmic membraneless compartment called stress granules (SGs). ISR and SGs can inhibit apoptosis, pyroptosis, and necroptosis, suggesting that they guard against uncontrolled regulated cell death (RCD) to promote organismal homeostasis. However, ISR and SGs also allow cancer cells to survive in stressful environments, including hypoxia and during chemotherapy. Therefore, there is a great need to understand the molecular mechanism of the crosstalk between ISR and RCD. This is an active area of research and is expected to be relevant to a range of human diseases. In this review, we provided an overview of the interplay between different cellular stress responses and RCD pathways and their modulation in health and disease.

HRI and Personality Perception: Comparison of the Personality Evaluation of a Teleoperated Humanoid Robot and Human Interlocutor

This paper deals with the personality perception of a humanoid robot when talking to it in a natural manner, using the wizard of Oz. An experiment involving 20 subjects was performed, to compare two heteroevaluation characteristics: identity perception of human vs. humanoid, and identity perception differences when interacting with a human directly or with the same human through the robot mediation. The experiment was organized in three interactions: with a woman, with a man, and with a humanoid robot. The evaluation uses the OCEAN inventory. The results show that the subjects create for the teleoperated robot an identity of its own, which differs from the one attributed to the teleoperator. The robot was generally perceived as having less interest in art, lacking more imagination or ingenuity, being less open-minded than the human controlling it. The perception of emotional stability is greater: the absence of the human envelope allows a person to appear more stable. We identified two statistical groups in the robot evaluation, depending on the consideration of the robotic technology by the subjects: their perception of the robot conscientiousness, extroversion and agreeableness varies according to the subjects, unlike the personality of the teleoperator.

Do We Collaborate With What We Design?

The use of terms like "collaboration" and "co-workers" to describe interactions between human beings and certain artificial intelligence (AI) systems has gained significant traction in recent years. Yet, it remains an open question whether such anthropomorphic metaphors provide either a fertile or even a purely innocuous lens through which to conceptualize designed commercial products. Rather, a respect for human dignity and the principle of transparency may require us to draw a sharp distinction between real and faux peers. At the heart of the concept of collaboration lies the assumption that the collaborating parties are (or behave as if they are) of similar status: two agents capable of comparable forms of intentional action, moral agency, or moral responsibility. In application to current AI systems, this not only seems to fail ontologically but also from a socio-political perspective. AI in the workplace is primarily an extension of capital, not of labor, and the AI "co-workers" of most individuals will likely be owned and operated by their employer. In this paper, we critically assess both the accuracy and desirability of using the term "collaboration" to describe interactions between humans and AI systems. We begin by proposing an alternative ontology of human-machine interaction, one which features not two equivalently autonomous agents, but rather one machine that exists in a relationship of heteronomy to one or more human agents. In this sense, while the machine may have a significant degree of independence concerning the means by which it achieves its ends, the ends themselves are always chosen by at least one human agent, whose interests may differ from those of the individuals interacting with the machine. We finally consider the motivations and risks inherent to the continued use of the term "collaboration," exploring its strained relation to the concept of transparency, and consequences for the future of work.

Enhancing Human-Robot Collaboration through a Multi-Module Interaction Framework with Sensor Fusion: Object Recognition, Verbal Communication, User of Interest Detection, Gesture and Gaze Recognition

With the increasing presence of robots in our daily lives, it is crucial to design interaction interfaces that are natural, easy to use and meaningful for robotic tasks. This is important not only to enhance the user experience but also to increase the task reliability by providing supplementary information. Motivated by this, we propose a multi-modal framework consisting of multiple independent modules. These modules take advantage of multiple sensors (e.g., image, sound, depth) and can be used separately or in combination for effective human-robot collaborative interaction. We identified and implemented four key components of an effective human robot collaborative setting, which included determining object location and pose, extracting intricate information from verbal instructions, resolving user(s) of interest (UOI), and gesture recognition and gaze estimation to facilitate the natural and intuitive interactions. The system uses a feature-detector-descriptor approach for object recognition and a homography-based technique for planar pose estimation and a deep multi-task learning model to extract intricate task parameters from verbal communication. The user of interest (UOI) is detected by estimating the facing state and active speakers. The framework also includes gesture detection and gaze estimation modules, which are combined with a verbal instruction component to form structured commands for robotic entities. Experiments were conducted to assess the performance of these interaction interfaces, and the results demonstrated the effectiveness of the approach.

A mitochondrial iron-responsive pathway regulated by DELE1

The heme-regulated kinase HRI is activated under heme/iron deficient conditions; however, the underlying molecular mechanism is incompletely understood. Here, we show that iron-deficiency-induced HRI activation requires the mitochondrial protein DELE1. Notably, mitochondrial import of DELE1 and its subsequent protein stability are regulated by iron availability. Under steady-state conditions, DELE1 is degraded by the mitochondrial matrix-resident protease LONP1 soon after mitochondrial import. Upon iron chelation, DELE1 import is arrested, thereby stabilizing DELE1 on the mitochondrial surface to activate the HRI-mediated integrated stress response (ISR). Ablation of this DELE1-HRI-ISR pathway in an erythroid cell model enhances cell death under iron-limited conditions, suggesting a cell-protective role for this pathway in iron-demanding cell lineages. Our findings highlight mitochondrial import regulation of DELE1 as the core component of a previously unrecognized mitochondrial iron responsive pathway that elicits stress signaling following perturbation of iron homeostasis.

The Prohibitin-Binding Compound Fluorizoline Activates the Integrated Stress Response through the eIF2α Kinase HRI

Fluorizoline is a synthetic molecule that induces apoptosis, by selectively targeting prohibitins (PHBs), through induction of the BH3-only protein NOXA. This induction is transcriptionally regulated by the integrated stress response (ISR)-related transcription factors ATF3 and ATF4. Here, we evaluate the role of the four eIF2α kinases, to decipher which is responsible for the mechanism of ISR activation triggered by fluorizoline in HeLa and HAP1 cells. First, we demonstrated the involvement of the eIF2α kinases using ISR inhibitor (ISRIB) and by simultaneous downregulation of all four eIF2α kinases, as both approaches were able to increase cell resistance to fluorizoline-induced apoptosis. Furthermore, we confirmed that fluorizoline treatment results in endoplasmic reticulum (ER) stress, as evidenced by PERK activation. Despite PERK activation, this kinase was not directly involved in the ISR activation by fluorizoline. In this regard, we found that the eIF2α kinases are capable of compensating for each other's loss of function. Importantly, we demonstrated that the mitochondrial-stress-related eIF2α kinase HRI mediates ISR activation after fluorizoline treatment.

Risk Assessment of Pesticide Residues by GC-MSMS and UPLC-MSMS in Edible Vegetables

In recent years, there has been a significant increase related to pesticide residues in foods, which may increase the risks to the consumer of these foods with the different quality and concentrations of pesticide residues. Pesticides are used for controlling pests that reduce yields. On the other hand, it has become a major public health concern due to its toxic properties. Thus, the objective of the current study employed the application of Quick Easy Cheap Effective Rugged Safe (QuEChERS) method, in combination with gas and liquid chromatography-tandem mass spectrometric detection (GCMSMS, LCMSMS) in order to determine 137 pesticide residues (63 insecticides, 41 acaricides, 40 herbicide, 55 fungicide, nematicide, growth regulator, Chitin synthesis inhibitors, and Juvenile hormone mimics), in 801 vegetables such as 139 tomatoes, 185 peppers, 217 squash, 94 eggplants, and 166 cucumbers from different locations in Hail and Riyadh cities. The results showed that the majority of pesticide residues were detected for each of the following pesticides: acetaimpride, metalaxyl, imidaclopride, bifenthrin, pyridaben, difenoconazole, and azoxystrobien, which were repeated in the samples studied 39, 21, 11, 10, 8, 7, and 5, respectively. In addition, results observed that the tomato was the most contaminated with pesticide residues; it was contaminated with 19 compounds and was followed by pepper, cucumber, and squash, and the last commodity in the contaminated ranking was eggplant. The highest calculated estimated daily intakes (EDIs) were recorded for tomatoes which were estimated between 0.013 to 0.516 mg/kg of body weight per day (bw/day) while the lowest EDIs value was between 0.000002 to 0.0005 mg/kg of bw/day for cucumber. Results indicated that the EDIs values were lower than the acceptable daily intake (ADI) values. Results observed that the most of pesticide residues exposure in food consumption in Saudi Arabia were lower than ADIs. In addition, the highest value for health risk index (HRI) was recorded with Ethion residue in tomato, but in sweet pepper, the highest value for HRI was 127.5 in the form of fipronil residue. On the other hand, results found that the highest values of HRI were 1.54, 1.61, and 0.047 for difenoconazole, bifenthrin, and pyridaben residues in squash, eggplant, and cucumber.

Human-Like Movements of Industrial Robots Positively Impact Observer Perception

The number of industrial robots and collaborative robots on manufacturing shopfloors has been rapidly increasing over the past decades. However, research on industrial robot perception and attributions toward them is scarce as related work has predominantly explored the effect of robot appearance, movement patterns, or human-likeness of humanoid robots. The current research specifically examines attributions and perceptions of industrial robots-specifically, articulated collaborative robots-and how the type of movements of such robots impact human perception and preference. We developed and empirically tested a novel model of robot movement behavior and demonstrate how altering the movement behavior of a robotic arm leads to differing attributions of the robot's human-likeness. These findings have important implications for emerging research on the impact of robot movement on worker perception, preferences, and behavior in industrial settings.

Standardization of MRI Screening and Reporting in Individuals With Elevated Risk of Pancreatic Ductal Adenocarcinoma: Consensus Statement of the PRECEDE Consortium

Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive malignancies, with a dismal survival rate. Screening the general population for early detection of PDAC is not recommended, but because early detection improves survival, high-risk individuals, defined as those meeting criteria based on a family history of PDAC and/or the presence of known pathogenic germline variant genes with PDAC risk, are recommended to undergo screening with MRI and/or endoscopic ultrasound at regular intervals. The Pancreatic Cancer Early Detection (PRECEDE) Consortium was formed in 2018 and is composed of gastroenterologists, geneticists, pancreatic surgeons, radiologists, statisticians, and researchers from 40 sites in North America, Europe, and Asia. The overarching goal of the PRECEDE Consortium is to facilitate earlier diagnosis of PDAC for high-risk individuals to increase survival of the disease. A standardized MRI protocol and reporting template are needed to enhance the quality of screening examinations, improve consistency of clinical management, and facilitate multiinstitutional research. We present a consensus statement to standardize MRI screening and reporting for individuals with elevated risk of pancreatic cancer.

Social Robotics and Dementia: Results from the eWare Project in Supporting Older People and Their Informal Caregivers

The aim of this paper is to describe the results collected with the Italian study conducted within eWare project, aimed at supporting the autonomy and health of the older people affected by dementia and their informal caregivers, through the use of an innovative system based on a social robot and a sensorized environmental infrastructure. Nine dyads of older participants with their caregivers were enrolled in testing the system for 6 months. The results show a positive impact of the system in supporting the achievement of personal goals of the participants, as well as in supporting the quality of life of the informal caregivers. Nevertheless, the impact of the system in reducing the caregivers' burden needs to be deeply investigated. This research highlights the potential of the eWare system but modifications will have to be made, especially on the interactivity capabilities, in order to meet the peculiar needs and wishes of older people with dementia and to favor the long-term use of the system.

Sublethal cytochrome c release generates drug-tolerant persister cells

Drug-tolerant persister cells (persisters) evade apoptosis upon targeted and conventional cancer therapies and represent a major non-genetic barrier to effective cancer treatment. Here, we show that cells that survive treatment with pro-apoptotic BH3 mimetics display a persister phenotype that includes colonization and metastasis in vivo and increased sensitivity toward ferroptosis by GPX4 inhibition. We found that sublethal mitochondrial outer membrane permeabilization (MOMP) and holocytochrome c release are key requirements for the generation of the persister phenotype. The generation of persisters is independent of apoptosome formation and caspase activation, but instead, cytosolic cytochrome c induces the activation of heme-regulated inhibitor (HRI) kinase and engagement of the integrated stress response (ISR) with the consequent synthesis of ATF4, all of which are required for the persister phenotype. Our results reveal that sublethal cytochrome c release couples sublethal MOMP to caspase-independent initiation of an ATF4-dependent, drug-tolerant persister phenotype.

Neuron-specific translational control shift ensures proteostatic resilience during ER stress

Proteostasis is essential for cellular survival and particularly important for highly specialised post‐mitotic cells such as neurons. Transient reduction in protein synthesis by protein kinase R‐like endoplasmic reticulum (ER) kinase (PERK)‐mediated phosphorylation of eukaryotic translation initiation factor 2α (p‐eIF2α) is a major proteostatic survival response during ER stress. Paradoxically, neurons are remarkably tolerant to PERK dysfunction, which suggests the existence of cell type‐specific mechanisms that secure proteostatic stress resilience. Here, we demonstrate that PERK‐deficient neurons, unlike other cell types, fully retain the capacity to control translation during ER stress. We observe rescaling of the ATF4 response, while the reduction in protein synthesis is fully retained. We identify two molecular pathways that jointly drive translational control in PERK‐deficient neurons. Haem‐regulated inhibitor (HRI) mediates p‐eIF2α and the ATF4 response and is complemented by the tRNA cleaving RNase angiogenin (ANG) to reduce protein synthesis. Overall, our study elucidates an intricate back‐up mechanism to ascertain translational control during ER stress in neurons that provides a mechanistic explanation for the thus far unresolved observation of neuronal resilience to proteostatic stress.

Can Robotic AI Systems Be Virtuous and Why Does This Matter?

The growing use of social robots in times of isolation refocuses ethical concerns for Human–Robot Interaction and its implications for social, emotional, and moral life. In this article we raise a virtue-ethics-based concern regarding deployment of social robots relying on deep learning AI and ask whether they may be endowed with ethical virtue, enabling us to speak of “virtuous robotic AI systems”. In answering this question, we argue that AI systems cannot genuinely be virtuous but can only behave in a virtuous way. To that end, we start from the philosophical understanding of the nature of virtue in the Aristotelian virtue ethics tradition, which we take to imply the ability to perform (1) the right actions (2) with the right feelings and (3) in the right way. We discuss each of the three requirements and conclude that AI is unable to satisfy any of them. Furthermore, we relate our claims to current research in machine ethics, technology ethics, and Human–Robot Interaction, discussing various implications, such as the possibility to develop Autonomous Artificial Moral Agents in a virtue ethics framework.

Heme-regulated inhibitor: an overlooked eIF2α kinase in cancer investigations

Heme-regulated inhibitor (HRI) kinase is a serine-threonine kinase, controlling the initiation of protein synthesis via phosphorylating α subunit of eIF2 on serine 51 residue, mainly in response to heme deprivation in erythroid cells. However, recent studies showed that HRI is also activated by several diverse signals, causing dysregulations in intracellular homeostatic mechanisms in non-erythroid cells. For instance, it was reported that the decrease in protein synthesis upon the 26S proteasomal inhibition by MG132 or bortezomib is mediated by increased eIF2α phosphorylation in an HRI-dependent manner in mouse embryonic fibroblast cells. The increase in eIF2α phosphorylation level through the activation of HRI upon 26S proteasomal inhibition is believed to protect cells against the buildup of misfolded and ubiquitinated proteins, having the potential to trigger the apoptotic response. In contrast, prolonged and sustained HRI-mediated eIF2α phosphorylation can induce cell death, which may involve ATF4 and CHOP expression. Altogether, these studies suggest that HRI-mediated eIF2α phosphorylation may be cytoprotective or cytotoxic depending on the cells, type, and duration of pharmacological agents used. It is thus hypothesized that both HRI activators, inducing eIF2α phosphorylation or HRI inhibitors causing disturbances in eIF2α phosphorylation, may be effective as novel strategies in cancer treatment if the balance in eIF2α phosphorylation is shifted in favor of autophagic or apoptotic response in cancer cells. It is here aimed to review the role of HRI in various biological mechanisms as well as the therapeutic potentials of recently developed HRI activators and inhibitors, targeting eIF2α phosphorylation in cancer cells.

Wild mushrooms from Ilgaz Mountain National Park (Western Black Sea, Turkey): element concentrations and their health risk assessment

The purpose of this study was to determine Fe, Cd, Cr, Se, P, Cu, Mn, Zn, Al, Ca, Mg, and K contents of some edible (Chlorophyllum rhacodes, Clavariadelphus truncatus, Clitocybe nebularis, Hydnum repandum, Hygrophorus pudorinus, Infundibulicybe gibba, Lactarius deliciosus, L. piperatus, L. salmonicolor, Macrolepiota mastoidea, Russula grata, Suillus granulatus, and Tricholoma imbricatum), inedible (Amanita pantherina, Geastrum triplex, Gloeophyllum sepiarium, Hypholoma fasciculare, Phellinus vorax, Pholiota limonella, Russula anthracina, and Tapinella atrotomentosa), and poisonous mushroom species (Amanita pantherina and Hypholoma fasciculare) collected from Ilgaz Mountain National Park (Western Black Sea, Turkey). The element contents of the mushrooms were determined to be 18.0-1239.1, 0.2-4.6, 0.1-3.4, 0.2-3.2, 1.0-8.9, 3.3-59.9, 3.7-220.4, 21.3-154.1, 6.4-754.3, 15.8-17,473.0, 413.0-5943.0, and 2803.0-24,490.0 mg·kg^-1, respectively. In addition to metal contents, the daily intakes of metal (DIM) and Health Risk Index (HRI) values of edible mushrooms were also calculated. Both DIM and HRI values of mushroom species except L. salmanicolor, M. mastoidea, and R. grata were within the legal limits. However, it was determined that the Fe content of L. salmanicolor and M. mastoidea and Cd content of R. grata were above the legal limits.

Environmental cadmium impairs blood-testis barrier via activating HRI-responsive mitochondrial stress in mice

Cadmium (Cd) is a well-known testicular toxicant. Blood-testis barrier (BTB), a vital part of testes, which has been reported to be damaged upon Cd exposure. However, the detailed mechanism about Cd-mediated disruption of BTB remains unclear. This study aims to investigate the role of Heme-Regulated Inhibitor (HRI)-responsive mitochondrial stress in Cd-mediated disruption of BTB. Male mice are intraperitoneally injected (i.p.) with melatonin (Mel, a cellular stress antagonist, 5.0 mg/kg) before Cd treatment (i.p., 2.0 mg/kg) for 8 h, and then treated with Cd for 0-48 h. Mouse Sertoli cells are pretreated with Mel (10 μM) for 1 h, and then treated with Cd (10 μM) for 0-24 h. We find that Cd damages the BTB and reduces the Occludin protein, a crucial BTB-related protein via activating p38/matrix metalloproteinase-2 (p38/MMP2) pathway and Integrated Stress Response (ISR). Further experiments reveal that the Heme-Regulated Inhibitor (HRI)-responsive mitochondrial stress is triggered in Cd-treated Sertoli cells. Most importantly, Cd-activated p38 signaling and ISR are regulated by HRI-responsive mitochondrial stress in Sertoli cells. Unexpectedly, we find that melatonin rescues the Cd-mediated disruption of BTB through blocking HRI-responsive mitochondrial stress in testes. Overall, these data indicate that environmental cadmium exposure impairs the BTB through activating HRI-responsive mitochondrial stress in Sertoli cells.

Addressing joint action challenges in HRI: Insights from psychology and philosophy

The vast expansion of research in human-robot interactions (HRI) these last decades has been accompanied by the design of increasingly skilled robots for engaging in joint actions with humans. However, these advances have encountered significant challenges to ensure fluent interactions and sustain human motivation through the different steps of joint action. After exploring current literature on joint action in HRI, leading to a more precise definition of these challenges, the present article proposes some perspectives borrowed from psychology and philosophy showing the key role of communication in human interactions. From mutual recognition between individuals to the expression of commitment and social expectations, we argue that communicative cues can facilitate coordination, prediction, and motivation in the context of joint action. The description of several notions thus suggests that some communicative capacities can be implemented in the context of joint action for HRI, leading to an integrated perspective of robotic communication.

Empathizing and Sympathizing With Robots: Implications for Moral Standing

This paper discusses the ethical nature of empathetic and sympathetic engagement with social robots, ultimately arguing that an entity which is engaged with through empathy or sympathy is engaged with as an “experiencing Other” and is as such due at least “minimal” moral consideration. Additionally, it is argued that extant HRI research often fails to recognize the complexity of empathy and sympathy, such that the two concepts are frequently treated as synonymous. The arguments for these claims occur in two steps. First, it is argued that there are at least three understandings of empathy, such that particular care is needed when researching “empathy” in human-robot interactions. The phenomenological approach to empathy—perhaps the least utilized of the three discussed understandings—is the approach with the most direct implications for moral standing. Furthermore, because “empathy” and “sympathy” are often conflated, a novel account of sympathy which makes clear the difference between the two concepts is presented, and the importance for these distinctions is argued for. In the second step, the phenomenological insights presented before regarding the nature of empathy are applied to the problem of robot moral standing to argue that empathetic and sympathetic engagement with an entity constitute an ethical engagement with it. The paper concludes by offering several potential research questions that result from the phenomenological analysis of empathy in human-robot interactions.

LEADOR: A Method for End-To-End Participatory Design of Autonomous Social Robots

Participatory design (PD) has been used to good success in human-robot interaction (HRI) but typically remains limited to the early phases of development, with subsequent robot behaviours then being hardcoded by engineers or utilised in Wizard-of-Oz (WoZ) systems that rarely achieve autonomy. In this article, we present LEADOR (Led-by-Experts Automation and Design Of Robots), an end-to-end PD methodology for domain expert co-design, automation, and evaluation of social robot behaviour. This method starts with typical PD, working with the domain expert(s) to co-design the interaction specifications and state and action space of the robot. It then replaces the traditional offline programming or WoZ phase by an in situ and online teaching phase where the domain expert can live-program or teach the robot how to behave whilst being embedded in the interaction context. We point out that this live teaching phase can be best achieved by adding a learning component to a WoZ setup, which captures implicit knowledge of experts, as they intuitively respond to the dynamics of the situation. The robot then progressively learns an appropriate, expert-approved policy, ultimately leading to full autonomy, even in sensitive and/or ill-defined environments. However, LEADOR is agnostic to the exact technical approach used to facilitate this learning process. The extensive inclusion of the domain expert(s) in robot design represents established responsible innovation practice, lending credibility to the system both during the teaching phase and when operating autonomously. The combination of this expert inclusion with the focus on in situ development also means that LEADOR supports a mutual shaping approach to social robotics. We draw on two previously published, foundational works from which this (generalisable) methodology has been derived to demonstrate the feasibility and worth of this approach, provide concrete examples in its application, and identify limitations and opportunities when applying this framework in new environments.

Evaluation of pasture allowance of manganese for ruminants

The aim of this study was to access the Mn contamination in soil, forages, and animals. Heavy metal pollution is a matter of prime significance in natural environment. Through food chain, toxicity of heavy metals and their bioaccumulation potential are transferred into humans. Higher concentrations of metallic compounds are toxic to living organisms but these are essential to maintain body metabolism. Intake of food crops polluted with heavy metals is chief food chain channel for human exposure. Animals are exposed to heavy metal stress by the intake of richly contaminated food crops; those are chief part of food chain. Samples of soil, plant, animal blood, hair, and feces were collected to find contamination through wet digestion process in lab and metal analysis. Different forages were collected to study Mn content that was our major concern in this study. The present findings also emphasized on the assessment of bio-concentration factor (BCF). Other significant indices of mobility and pollution of metal were also calculated, i.e. pollution load index (PLI), daily intake of metal (DIM), health risk index (HRI), and enrichment factor (EF). The experimentation result showed different concentrations of metal in different seasons. The Mn concentration in forages was 20.01-28.29 mg/kg and in soil was 5.27-8.90 mg/kg. Soil samples showed higher level of (PLI) Pollution load index. Bio-concentration of MN was 2.59-4.21 mg/kg. It can be concluded that regular monitoring of the metal is essential to evaluate the contamination status. Mn contents were in the safe limits in soil and plants; however, its toxic level was observed in animals.

Integrated use of inverse and biotic ligand modelling for lake water quality resilience estimation: A case of Ramsar wetland, (Deepor Beel), Assam, India

The present study evaluates the vulnerability of the lake system (Deepor Beel) due to the combined exposure of toxic metals, major ions and mineral dissociation. The hydro-chemistry of the Deepor Beel lake reveals the dominance of carbonate weathering with strong evidences of ion-exchange reaction occurring throughout the monsoon season of 2014 and 2015. Through an integrated application of multivariate analysis, the occurrence of albite weathering was confirmed, although as an isolated incidence only, along-with substantial evidence of waste water intrusion from fertilizer industries. The moderate cation exchange capacity (CEC) of the soil, indicates the presence of illite, chlorite and kaolinite which provides a strong buffering action in terms of phosphorous and nutrient retention. However, occurrences of chemical waste in the form of bleaching powder (Ca(OCl)₂) are causing acidification of lake soil, which will trigger the release of phosphorous and may enhance the eutrophication level in near future. Through the simulations of Biotic Ligand (BL) model on ceriodaphnia dubia, it is being revealed, that the free availability of Ca²⁺ in the lake water, provides a higher adsorptive competition for labile metal species especially for Cu and Zn. Additionally, the risk among children from drinking lake water, has increased by three to seven times in a duration of just one year. The present study is a pioneering work, which has evaluated the vulnerability of Deepor Beel lake by adopting a sequential assessment strategy of lake internal as well as external ecology. Our proposed methodology can be a used as a scientific basis for future assessment of the lake health.

Transfer of heavy metals from soils to curly mustard (Brassica juncea (L.) Czern.) grown in an agricultural farm in Brunei Darussalam

Determination of heavy metal concentrations in vegetables and agricultural soils is crucial because high levels of heavy metals could affect soil quality, crop production and safe consumption of crops. A field study was conducted to determine the heavy metal concentrations and their transfer from agricultural soils to different parts (leaf, stem, and root) of Brassica juncea (L.) Czern. In addition, potential health risks of contamination in the vegetables grown in the field were evaluated. Acid digestion method USEPA 3050B in combination with ICP-OES were used to analyze heavy metal (Al, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn) contents in both pre- and post-harvest soils and vegetable samples. Results showed that none of the heavy metals in soils had concentrations above the maximum safety limits based on the WHO, USEPA and CCME guidelines. Calculated metal transfer factor (MTF >1) showed B. juncea accumulated Cd, Co, Ni, Pb and Zn in leaves, stems and roots, but Cu and Mn, as well as Cr were only accumulated in stems and roots, respectively. There were variations in heavy metal contents between the different parts of B. juncea, but only Cd and Pb contents were above the maximum allowable limit recommended by FAO/WHO. PCA analysis was able to identify 4 major components corresponding to 38.38%, 28.98%, 14.39% and 10.67% of the total variance and PC1 was clearly associated to leaves of B. juncea. Based on the MTF values, only Cd was found to have a value of HRI >1 compared to the other heavy metals, implying potential health risk associated with long-term ingestion of the vegetable.

Bridging the gap between emotion and joint action

Our daily human life is filled with a myriad of joint action moments, be it children playing, adults working together (i.e., team sports), or strangers navigating through a crowd. Joint action brings individuals (and embodiment of their emotions) together, in space and in time. Yet little is known about how individual emotions propagate through embodied presence in a group, and how joint action changes individual emotion. In fact, the multi-agent component is largely missing from neuroscience-based approaches to emotion, and reversely joint action research has not found a way yet to include emotion as one of the key parameters to model socio-motor interaction. In this review, we first identify the gap and then stockpile evidence showing strong entanglement between emotion and acting together from various branches of sciences. We propose an integrative approach to bridge the gap, highlight five research avenues to do so in behavioral neuroscience and digital sciences, and address some of the key challenges in the area faced by modern societies.

Ultrasound Stratification of Hepatic Steatosis Using Hepatorenal Index

Hepatorenal index (HRI) has been shown to be an effective, noninvasive ultrasound tool to screen patients for those with or without >5% hepatic steatosis. Objective: The aim of this study was to further refine this HRI tool in order to stratify patients according to their degree of liver steatosis and give direction as to which patients should undergo random liver biopsy. Methods: We conducted a retrospective review of 267 consecutive patients from 2015 to 2017 who had abdominal ultrasounds and a subsequent random liver biopsy within one month. The HRI was calculated and compared with the percent steatosis as assessed by histology. Results: An HRI of ≤1.17 corresponds with >95% positive predictive value of ≤5% steatosis. Between HRI values 1.18 and 1.39, performance of steatosis prediction is mixed. However, for values <1.37 there is an increased likelihood of steatosis ≤5% and likewise the opposite for values >1.37. An HRI of ≥1.4 corresponds with >95% positive predictive value of ≥10% steatosis. Conclusion: HRI is an accurate noninvasive tool to quantify degree of steatosis and guide who should undergo random liver biopsy, potentially significantly reducing the total number of necessary liver biopsies.

Remote HRI: a Methodology for Maintaining COVID-19 Physical Distancing and Human Interaction Requirements in HRI Studies

Observing how humans and robots interact is an integral part of understanding how they can effectively coexist. This ability to undertake these observations was taken for granted before the COVID-19 pandemic restricted the possibilities of performing HRI study-based interactions. We explore the problem of how HRI research can occur in a setting where physical separation is the most reliable way of preventing disease transmission. We present the results of an exploratory experiment that suggests Remote-HRI (R-HRI) studies may be a viable alternative to traditional face-to-face HRI studies. An R-HRI study minimizes or eliminates in-person interaction between the experimenter and the participant and implements a new protocol for interacting with the robot to minimize physical contact. Our results showed that participants interacting with the robot remotely experienced a higher cognitive workload, which may be due to minor cultural and technical factors. Importantly, however, we also found that whether participants interacted with the robot in-person (but socially distanced) or remotely over a network, their experience, perception of, and attitude towards the robot were unaffected.

ADA-SR: Activity detection and analysis using security robots for reliable workplace safety

BACKGROUND

Human-Robot Interaction (HRI) has become a prominent solution to improve the robustness of real-time service provisioning through assisted functions for day-to-day activities. The application of the robotic system in security services helps to improve the precision of event detection and environmental monitoring with ease.

OBJECTIVES

This paper discusses activity detection and analysis (ADA) using security robots in workplaces. The application scenario of this method relies on processing image and sensor data for event and activity detection. The events that are detected are classified for its abnormality based on the analysis performed using the sensor and image data operated using a convolution neural network. This method aims to improve the accuracy of detection by mitigating the deviations that are classified in different levels of the convolution process.

RESULTS

The differences are identified based on independent data correlation and information processing. The performance of the proposed method is verified for the three human activities, such as standing, walking, and running, as detected using the images and sensor dataset.

CONCLUSION

The results are compared with the existing method for metrics accuracy, classification time, and recall.

First Step toward Gestural Recognition in Harsh Environments

We are witnessing a rise in the use of ground and aerial robots in first response missions. These robots provide novel opportunities to support first responders and lower the risk to people’s lives. As these robots become increasingly autonomous, researchers are seeking ways to enable natural communication strategies between robots and first responders, such as using gestural interaction. First response work often takes place in harsh environments, which hold unique challenges for gesture sensing and recognition, including in low-visibility environments, making the gestural interaction non-trivial. As such, an adequate choice of sensors and algorithms needs to be made to support gestural recognition in harsh environments. In this work, we compare the performances of three common types of remote sensors, namely RGB, depth, and thermal cameras, using various algorithms, in simulated harsh environments. Our results show 90 to 96% recognition accuracy (respectively with or without smoke) with the use of protective equipment. This work provides future researchers with clear data points to support them in their choice of sensors and algorithms for gestural interaction with robots in harsh environments.

Hiding in Plain Sight: Formation and Function of Stress Granules During Microbial Infection of Mammalian Cells

Stress granule (SG) formation is a host cell response to stress-induced translational repression. SGs assemble with RNA-binding proteins and translationally silent mRNA. SGs have been demonstrated to be both inhibitory to viruses, as well as being subverted for viral roles. In contrast, the function of SGs during non-viral microbial infections remains largely unexplored. A handful of microbial infections have been shown to result in host SG assembly. Nevertheless, a large body of evidence suggests SG formation in hosts is a widespread response to microbial infection. Diverse stresses caused by microbes and their products can activate the integrated stress response in order to inhibit translation initiation through phosphorylation of the eukaryotic translation initiation factor 2α (eIF2α). This translational response in other contexts results in SG assembly, suggesting that SG assembly can be a general phenomenon during microbial infection. This review explores evidence for host SG formation in response to bacterial, fungal, and protozoan infection and potential functions of SGs in the host and for adaptations of the pathogen.

Babyface: Performance and Installation Art Exploring the Feminine Ideal in Gendered Machines

Representations of gender in new technologies like the Siri, Pepper, and Sophia robotic assistants, as well as the commodification of features associated with gender on platforms like Instagram, inspire questions about how and whether robotic tools can have gender and what it means to people if they do. One possible response to this is through artistic creation of dance performance. This paper reports on one such project where, along the route to this inquiry, creation of machine augmentation – of both the performer and audience member – was necessary to communicate the artistic ideas grappled with therein. Thus, this article describes the presentation of Babyface, a machine-augmented, participatory contemporary dance performance. This work is a reaction to feminized tropes in popular media and modern technology, and establishes a parallel between the ways that women and machines are talked about, treated, and – in the case of machines – designed to look and behave. This paper extends prior reports on the creation of this piece and its accompanying devices to describe extensions with audience member participation, and reflect on the responses of these audience members. These fabricated elements alongside the actions of the performer and a soundscape that quotes statements made by real “female” robots create an otherwordly, sad cyborg character that causes viewers to question their assumptions about and pressures on the feminine ideal.

The eIF2α kinase HRI triggers the autophagic clearance of cytosolic protein aggregates

Large cytosolic protein aggregates are removed by two main cellular processes, autophagy and the ubiquitin-proteasome system, and defective clearance of these protein aggregates results in proteotoxicity and cell death. Recently, we found that the eIF2α kinase heme-regulated inhibitory (HRI) induced a cytosolic unfolded protein response to prevent aggregation of innate immune signalosomes, but whether HRI acts as a general sensor of proteotoxicity in the cytosol remains unclear. Here we show that HRI controls autophagy to clear cytosolic protein aggregates when the ubiquitin-proteasome system is inhibited. We further report that silencing the expression of HRI resulted in decreased levels of BAG3 and HSPB8, two proteins involved in chaperone-assisted selective autophagy, suggesting that HRI may control proteostasis in the cytosol at least in part through chaperone-assisted selective autophagy. Moreover, knocking down the expression of HRI resulted in cytotoxic accumulation of overexpressed α-synuclein, a protein known to aggregate in Parkinson's disease, dementia with Lewy bodies, and multiple system atrophy. In agreement with these data, protein aggregate accumulation and microglia activation were observed in the spinal cord white matter of 7-month-old Hri-/- mice as compared with Hri+/+ littermates. Moreover, aged Hri-/- mice showed accumulation of misfolded α-synuclein in the lateral collateral pathway, a region of the sacral spinal cord horn that receives visceral sensory afferents from the bladder and distal colon, a pathological feature common to α-synucleinopathies in humans. Together, these results suggest that HRI contributes to a general cytosolic unfolded protein response that could be leveraged to bolster the clearance of cytotoxic protein aggregates.

Mind Meets Machine: Towards a Cognitive Science of Human-Machine Interactions

As robots advance from the pages and screens of science fiction into our homes, hospitals, and schools, they are poised to take on increasingly social roles. Consequently, the need to understand the mechanisms supporting human-machine interactions is becoming increasingly pressing. We introduce a framework for studying the cognitive and brain mechanisms that support human-machine interactions, leveraging advances made in cognitive neuroscience to link different levels of description with relevant theory and methods. We highlight unique features that make this endeavour particularly challenging (and rewarding) for brain and behavioural scientists. Overall, the framework offers a way to study the cognitive science of human-machine interactions that respects the diversity of social machines, individuals' expectations and experiences, and the structure and function of multiple cognitive and brain systems.

Pathogenesis and promising therapeutics of Alzheimer disease through eIF2α pathway and correspondent kinases

Eukaryotic initiation factor 2 (eIF2α) pathway is overactivated in Alzheimer disease and is probably associated with synaptic and memory deficiencies. EIF2α protein is principally in charge of the regulation of protein synthesis in eukaryotic cells. Four kinases responsible for eIF2α phosphorylation at ser-51 are: General control non-derepressible-2 kinase (GCN2), double-stranded RNA-activated protein kinase (PKR), PKR-like endoplasmic reticulum kinase (PERK), and heme-regulated inhibitor kinase (HRI) are the four kinases. They lead to reduced levels of general translation and paradoxical increase of stress-responsive mRNAs expression including the B-secretase (BACE1) and the transcriptional modulator activating transcription factor 4 (ATF4), which in turn accelerates the beta-amyloidogenesis, tau phosphorylation, proapoptotic pathway induction and autophagy elements formation leading to the main pathological hallmarks of AD. Findings suggest that genetic or pharmacological inhibition of correspondent kinases can restore memory and prevent neurodegeneration. This implies that inhibition of eIF2α phosphorylation through respondent kinases is indeed a feasible prospect of clinical application. This review discusses recent therapeutic approaches targeting eIF2α pathway and provides an overview of the links between correspondent kinases overactivation with neurodegeneration in AD.

Psychological Effects of the Allocation Process in Human-Robot Interaction - A Model for Research on ad hoc Task Allocation

Task allocation is immensely important when it comes to designing human–robot interaction (HRI), but although it is the shaping part of the interaction, it is merely regarded as a process with its own effects on human thinking and behavior. This study aims at linking research from different fields like psychological theory, HRI and allocation optimization to create a new process model of ad hoc task allocation in human–robot interaction. It addresses the process characteristics and psychological outcomes of a real-time allocation process that integrates the worker. To achieve this, we structured the process into steps and identified relevant psychological constructs associated with them. The model is a first step toward ergonomic research on the self-organized allocation of tasks in HRI, but may also be an inspiration for practitioners designing HRI systems. To create successful work in HRI, designing the technology is an important foundation, but a participative, thought-out process for allotting tasks could be the key to adequate autonomy, work satisfaction and successful cooperation.

Coordination Dynamics: A Foundation for Understanding Social Behavior

Humans' interactions with each other or with socially competent machines exhibit lawful coordination patterns at multiple levels of description. According to Coordination Dynamics, such laws specify the flow of coordination states produced by functional synergies of elements (e.g., cells, body parts, brain areas, people…) that are temporarily organized as single, coherent units. These coordinative structures or synergies may be mathematically characterized as informationally coupled self-organizing dynamical systems (Coordination Dynamics). In this paper, we start from a simple foundation, an elemental model system for social interactions, whose behavior has been captured in the Haken-Kelso-Bunz (HKB) model. We follow a tried and tested scientific method that tightly interweaves experimental neurobehavioral studies and mathematical models. We use this method to further develop a body of empirical research that advances the theory toward more generalized forms. In concordance with this interdisciplinary spirit, the present paper is written both as an overview of relevant advances and as an introduction to its mathematical underpinnings. We demonstrate HKB's evolution in the context of social coordination along several directions, with its applicability growing to increasingly complex scenarios. In particular, we show that accommodating for symmetry breaking in intrinsic dynamics and coupling, multiscale generalization and adaptation are principal evolutions. We conclude that a general framework for social coordination dynamics is on the horizon, in which models support experiments with hypothesis generation and mechanistic insights.

Compact Gearboxes for Modern Robotics: A Review

On the eve of Human-Robot-Interaction (HRI) becoming customary in our lives, the performance of HRI robotic devices remains strongly conditioned by their gearboxes. In most industrial robots, two relatively unconventional transmission technologies-Harmonic Drives© and Cycloid Drives-are usually found, which are not so broadly used in other industries. Understanding the origin of this singularity provides valuable insights in the search for suitable, future robotic transmission technologies. In this paper we propose an assessment framework strongly conditioned by HRI applications, and we use it to review the performance of conventional and emerging robotic gearbox technologies, for which the design criterion is strongly shifted toward aspects like weight and efficiency. The framework proposes to use virtual power as a suitable way to assess the inherent limitations of a gearbox technologies to achieve high efficiencies. This paper complements the existing research dealing with the complex interaction between gearbox technologies and the actuators, with a new gearbox-centered perspective particularly focused on HRI applications.

Gaze Control of a Robotic Head for Realistic Interaction With Humans

When there is an interaction between a robot and a person, gaze control is very important for face-to-face communication. However, when a robot interacts with several people, neurorobotics plays an important role to determine the person to look at and those to pay attention to among the others. There are several factors which can influence the decision: who is speaking, who he/she is speaking to, where people are looking, if the user wants to attract attention, etc. This article presents a novel method to decide who to pay attention to when a robot interacts with several people. The proposed method is based on a competitive network that receives different stimuli (look, speak, pose, hoard conversation, habituation, etc.) that compete with each other to decide who to pay attention to. The dynamic nature of this neural network allows a smooth transition in the focus of attention to a significant change in stimuli. A conversation is created between different participants, replicating human behavior in the robot. The method deals with the problem of several interlocutors appearing and disappearing from the visual field of the robot. A robotic head has been designed and built and a virtual agent projected on the robot's face display has been integrated with the gaze control. Different experiments have been carried out with that robotic head integrated into a ROS architecture model. The work presents the analysis of the method, how the system has been integrated with the robotic head and the experiments and results obtained.

In the Wild HRI Scenario: Influence of Regulatory Focus Theory

Research related to regulatory focus theory has shown that the way in which a message is conveyed can increase the effectiveness of the message. While different research fields have used this theory, in human-robot interaction (HRI), no real attention has been given to this theory. In this paper, we investigate it in an in the wild scenario. More specifically, we are interested in how individuals react when a robot suddenly appears at their office doors. Will they interact with it or will they ignore it? We report the results from our experimental study in which the robot approaches 42 individuals. Twenty-nine of them interacted with the robot, while the others either ignored it or avoided any interaction with it. The robot displayed two types of behavior (i.e., promotion or prevention). Our results show that individuals that interacted with a robot that matched their regulatory focus type interacted with it significantly longer than individuals that did not experience regulatory fit. Other qualitative results are also reported, together with some reactions from the participants.

Shall I Trust You? From Child-Robot Interaction to Trusting Relationships

Studying trust in the context of human-robot interaction is of great importance given the increasing relevance and presence of robotic agents in the social sphere, including educational and clinical. We investigated the acquisition, loss, and restoration of trust when preschool and school-age children played with either a human or a humanoid robot in vivo. The relationship between trust and the representation of the quality of attachment relationships, Theory of Mind, and executive function skills was also investigated. Additionally, to outline children's beliefs about the mental competencies of the robot, we further evaluated the attribution of mental states to the interactive agent. In general, no substantial differences were found in children's trust in the play partner as a function of agency (human or robot). Nevertheless, 3-year-olds showed a trend toward trusting the human more than the robot, as opposed to 7-year-olds, who displayed the reverse pattern. These findings align with results showing that, for 3- and 7-year-olds, the cognitive ability to switch was significantly associated with trust restoration in the human and the robot, respectively. Additionally, supporting previous findings, we found a dichotomy between attributions of mental states to the human and robot and children's behavior: while attributing to the robot significantly lower mental states than the human, in the Trusting Game, children behaved in a similar way when they related to the human and the robot. Altogether, the results of this study highlight that similar psychological mechanisms are at play when children are to establish a novel trustful relationship with a human and robot partner. Furthermore, the findings shed light on the interplay - during development - between children's quality of attachment relationships and the development of a Theory of Mind, which act differently on trust dynamics as a function of the children's age as well as the interactive partner's nature (human vs. robot).

Impacts of weather, work rate, hydration, and clothing in heat-related illness in California farmworkers

BACKGROUND

The primary aim of this study was to investigate the effects of work rate, hydration status, and clothing on core body temperature (CBT) on California farmworkers.

METHODS

Two hundred and eighty-seven farmworkers were recruited in Summer 2015, with 259 participants having sufficient data for analysis. We collected CBT, ambient temperature, work rate, body weight loss, and clothing worn by each participant throughout the work day and demographic data from a questionnaire.

RESULTS

Multiple regression with CBT as the outcome was used to determine the adjusted associations between CBT, environmental heat load, and worker characteristics. The multivariate regression model showed statistically significant associations of CBT with work rate (β = .006, 95% CI [0.004, 0.009]) and wet-bulb globe temperature (β = .03, 95% CI [0.017, 0.05]).

CONCLUSION

Results suggest that among our population workload is the primary modifiable risk factor for heat-related illness. As expected, the ambient temperature was also associated with higher risk.

Optimization of Real-Time EEG Artifact Removal and Emotion Estimation for Human-Robot Interaction Applications

Affective human-robot interaction requires lightweight software and cheap wearable devices that could further this field. However, the estimation of emotions in real-time poses a problem that has not yet been optimized. An optimization is proposed for the emotion estimation methodology including artifact removal, feature extraction, feature smoothing, and brain pattern classification. The challenge of filtering artifacts and extracting features, while reducing processing time and maintaining high accuracy results, is attempted in this work. First, two different approaches for real-time electro-oculographic artifact removal techniques are tested and compared in terms of loss of information and processing time. Second, an emotion estimation methodology is proposed based on a set of stable and meaningful features, a carefully chosen set of electrodes, and the smoothing of the feature space. The methodology has proved to perform on real-time constraints while maintaining high accuracy on emotion estimation on the SEED database, both under subject dependent and subject independent paradigms, to test the methodology on a discrete emotional model with three affective states.

Social Conformity Effects on Trust in Simulation-Based Human-Robot Interaction

OBJECTIVE

We investigated the co-acting influences of communication and social conformity on trust in human-robot interaction.

BACKGROUND

Previous work has investigated aspects of the robot, the human, and the environment as influential factors in the human-robot relationship. Little work has examined the conjoint effects of social conformity and communication on this relationship. As social conformity and communication have been shown to affect human-human trust, there are a priori reasons to believe that they will play an influential role in human-robot trust also.

METHOD

The experiment examined the influences of social conformity and robot communication on trust. A 2 × 2 (communication × social group) design was implemented with each variable having two levels (communication, no communication; positive social group, negative social group).

RESULTS

We created a communication manipulation which we then demonstrated to mediate the trust level between human and robot. However, this influence on trust was overcome by social information in which the subsequent trust level, attributed to the robot, was dominated by expressed social group attitudes to that robot.

CONCLUSION

The results confirm the importance of human social assessments over direct robot communication in setting human-robot trust levels. When social opinions are expressed, observers appear to conform to the trust displayed by the group than relying on their own judgment.

APPLICATION

In human-robot teams, the perceptions of the group may exert a greater impact than even robot communication. This may be especially important when new human members are introduced into such teams.

Trust in socially assistive robots: Considerations for use in rehabilitation

Incorporation of social robots into rehabilitation calls for understanding what factors affect user motivation and success of the interaction. Trust between the user and the robot has been identified as important in human-robot interaction and in human-human interactions in therapy. Trust has been studied in the context of automation technology, (e.g., autonomous cars), but not in the context of social robots for rehabilitation. In this narrative review, we address the unique patient-clinician-robot triad, and argue that this context calls for specific design features in order to foster trust with the users. We review pertinent methods for measuring trust, and studies demonstrating that culture, prior experience and propensity-to-trust affect to what extent users trust robots. We suggest design guidelines for fostering trust and methods for measuring trust in human-robot interactions in rehabilitation. We stress the need to create measures of trust that are accessible to people who suffer from speech or cognitive impairments. This review is pertinent to researchers, roboticists, and clinicians interested in designing and using social robots for rehabilitation.

HRI of Epinephelus coioides is a critical factor in the grouper immune response to RGNNV infection

Phosphorylation of eukaryotic initiation factor 2 alpha subunit (eIF2α) occurs under a variety of conditions, including viral infection. Heme-regulated inhibitor (HRI) is an eIF2α kinase that modifies this phosphorylation. In this study, a HRI homologue (EcHRI) from the orange-spotted grouper (Epinephelus coioides) was cloned and its roles during fish viral infection were characterized. EcHRI encodes a 664-amino acid polypeptide that shares a high degree of similarity with HRIs from other species. Quantitative real-time polymerase chain reaction analysis indicated that EcHRI was distributed in all examined tissues. Expression of EcHRI in the spleen of E. coioides was up-regulated when challenged with the synthetic analog of double-stranded RNA (dsRNA) of polyinosine-polycytidylic acid (poly I:C). EcHRI was significantly increased in red-spotted grouper nervous necrosis virus (RGNNV) infected cells. EcHRI was abundantly distributed in the nucleus of grouper spleen (GS) cells. Overexpression of EcHRI inhibited the expression of red-spotted grouper nervous necrosis virus (RGNNV) genes in GS cells. Furthermore, our results showed that EcHRI overexpression significantly increased the expression of interferon (IFN)-related cytokines and enhanced activation of IFN-β, interferon-sensitive response element (ISRE), and nuclear factor κB (NF-κB). Taken together, these results suggest that EcHRI is involved in the fish immune response to virus challenge.

A Bio-inspired Motivational Decision Making System for Social Robots Based on the Perception of the User

Nowadays, many robotic applications require robots making their own decisions and adapting to different conditions and users. This work presents a biologically inspired decision making system, based on drives, motivations, wellbeing, and self-learning, that governs the behavior of the robot considering both internal and external circumstances. In this paper we state the biological foundations that drove the design of the system, as well as how it has been implemented in a real robot. Following a homeostatic approach, the ultimate goal of the robot is to keep its wellbeing as high as possible. In order to achieve this goal, our decision making system uses learning mechanisms to assess the best action to execute at any moment. Considering that the proposed system has been implemented in a real social robot, human-robot interaction is of paramount importance and the learned behaviors of the robot are oriented to foster the interactions with the user. The operation of the system is shown in a scenario where the robot Mini plays games with a user. In this context, we have included a robust user detection mechanism tailored for short distance interactions. After the learning phase, the robot has learned how to lead the user to interact with it in a natural way.