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Abstract Although there is no doubt from an empirical viewpoint that reflex mechanisms can contribute to tongue motor control in humans, there is limited neurophysiological evidence to support this idea. Previous results failing to observe any tonic stretch reflex in the tongue had reduced the likelihood of a reflex contribution in tongue motor control. The current study presents experimental evidence of a human tongue reflex in response to a sudden stretch while holding a posture for speech. The latency was relatively long (50 ms), which is possibly mediated through cortical-arc. The activation peak in a speech task was greater than in a non-speech task while background activation levels were similar in both tasks, and the peak amplitude in a speech task was not modulated by the additional task to react voluntarily to the perturbation. Computer simulations with a simplified linear mass-spring-damper model showed that the recorded muscle activation response is suited for the generation of tongue movement responses that were observed in a previous study with the appropriate timing when taking into account a possible physiological delay between reflex muscle activation and the corresponding force. Our results evidenced clearly that reflex mechanisms contribute to tongue posture stabilization for speech production.

A quick correction mechanism of the tongue has been formerly experimentally observed in speech posture stabilization in response to a sudden tongue stretch perturbation. Given its relatively short latency (< 150 ms), the response could be driven by somatosensory feedback alone. The current study assessed this hypothesis by examining whether this response is induced in the absence of auditory feedback. We compared the response under two auditory conditions: with normal versus masked auditory feedback. Eleven participants were tested. They were asked to whisper the vowel /e/ for a few seconds. The tongue was stretched horizontally with step patterns of force (1 N during 1 s) using a robotic device. The articulatory positions were recorded using electromagnetic articulography simultaneously with the produced sound. The tongue perturbation was randomly and unpredictably applied in one-fifth of trials. The two auditory conditions were tested in random order. A quick compensatory response was induced in a similar way to the previous study. We found that the amplitudes of the compensatory responses were not significantly different between the two auditory conditions, either for the tongue displacement or for the produced sounds. These results suggest that the observed quick correction mechanism is primarily based on somatosensory feedback. This correction mechanism could be learned in such a way as to maintain the auditory goal on the sole basis of somatosensory feedback.

Abstract The advent of Artificial Intelligence (AI) is fostering the development of innovative methods of communication and collaboration. Integrating AI into Information and Communication Technologies (ICTs) is now ushering in an era of social progress that has the potential to empower marginalized groups. This transformation paves the way to a digital inclusion that could qualitatively empower the online presence of women, particularly in conservative and male-dominated regions. To explore this possibility, we investigated the effect of integrating conversational agents into online debates encompassing 240 Afghans discussing the fall of Kabul in August 2021. We found that the agent leads to quantitative differences in how both genders contribute to the debate by raising issues, presenting ideas, and articulating arguments. We also found increased ideation and reduced inhibition for both genders, particularly females, when interacting exclusively with other females or the agent. The enabling character of the conversational agent reveals an apparatus that could empower women and increase their agency on online platforms.

Orofacial somatosensory inputs may play a role in the link between speech perception and production. Given the fact that speech motor learning, which involves paired auditory and somatosensory inputs, results in changes to speech perceptual representations, somatosensory inputs may also be involved in learning or adaptive processes of speech perception. Here we show that repetitive pairing of somatosensory inputs and sounds, such as occurs during speech production and motor learning, can also induce a change of speech perception. We examined whether the category boundary between /ε/ and /a/ was changed as a result of perceptual training with orofacial somatosensory inputs. The experiment consisted of three phases: Baseline, Training, and Aftereffect. In all phases, a vowel identification test was used to identify the perceptual boundary between /ε/ and /a/. In the Baseline and the Aftereffect phase, an adaptive method based on the maximum-likelihood procedure was applied to detect the category boundary using a small number of trials. In the Training phase, we used the method of constant stimuli in order to expose participants to stimulus variants which covered the range between /ε/ and /a/ evenly. In this phase, to mimic the sensory input that accompanies speech production and learning in an experimental group, somatosensory stimulation was applied in the upward direction when the stimulus sound was presented. A control group (CTL) followed the same training procedure in the absence of somatosensory stimulation. When we compared category boundaries prior to and following paired auditory-somatosensory training, the boundary for participants in the experimental group reliably changed in the direction of /ε/, indicating that the participants perceived /a/ more than /ε/ as a consequence of training. In contrast, the CTL did not show any change. Although a limited number of participants were tested, the perceptual shift was reduced and almost eliminated 1 week later. Our data suggest that repetitive exposure of somatosensory inputs in a task that simulates the sensory pairing which occurs during speech production, changes perceptual system and supports the idea that somatosensory inputs play a role in speech perceptual adaptation, probably contributing to the formation of sound representations for speech perception.

Intelligent transportation systems encompass a series of technologies and applications that exchange information to improve road traffic and avoid accidents. According to statistics, some studies argue that human mistakes cause most road accidents worldwide. For this reason, it is essential to model driver behavior to improve road safety. This paper presents a Fuzzy Rule-Based System for driver classification into different profiles considering their behavior. The system’s knowledge base includes an ontology and a set of driving rules. The ontology models the main entities related to driver behavior and their relationships with the traffic environment. The driving rules help the inference system to make decisions in different situations according to traffic regulations. The classification system has been integrated on an intelligent transportation architecture. Considering the user’s driving style, the driving assistance system sends them recommendations, such as adjusting speed or choosing alternative routes, allowing them to prevent or mitigate negative transportation events, such as road crashes or traffic jams. We carry out a set of experiments in order to test the expressiveness of the ontology along with the effectiveness of the overall classification system in different simulated traffic situations. The results of the experiments show that the ontology is expressive enough to model the knowledge of the proposed traffic scenarios, with an F1 score of 0.9. In addition, the system allows proper classification of the drivers’ behavior, with an F1 score of 0.84, outperforming Random Forest and Naive Bayes classifiers. In the simulation experiments, we observe that most of the drivers who are recommended an alternative route experience an average time gain of 66.4%, showing the utility of the proposal.

Abstract Recently, wearable extra robotic limbs that aim to enhance the functionality and capability of human operators as extra arms or fingers have become an active research subject among robotics researchers. Improving the operability of the extra robotic limbs is required for the human operators, an approach for which is to induce robotic embodiment. In this paper, we focus on the update of sense of self-location which is the key aspect of embodiment and contributes to the body representation update, and we elucidate dominant factors which induce the embodiment of an extra robotic thumb (ERT). The experiments are conducted to compare the performance of the reaching task of the ERT under three separately given conditions, of which two are somatosensory feedbacks: (1) tactile and position feedback from the fingertips and (2) tactile and position feedback from the human face, and one is a non-somatosensory feedback: (3) auditory feedback. As a result, we confirmed that the somatosensory feedback from finger tips has a large contribution for the update of sense of self-location.

Musicians tend to have better auditory and motor performance than non-musicians because of their extensive musical experience. In a previous study, we established that loudness discrimination acuity is enhanced when sound is produced by a precise force generation task. In this study, we compared the enhancement effect between experienced pianists and non-musicians. Without the force generation task, loudness discrimination acuity was better in pianists than non-musicians in the condition. However, the force generation task enhanced loudness discrimination acuity similarly in both pianists and non-musicians. The reaction time was also reduced with the force control task, but only in the non-musician group. The results suggest that the enhancement of loudness discrimination acuity with the precise force generation task is independent of musical experience and is, therefore, a fundamental function in auditory-motor interaction.

Purpose – This paper aims to present a preliminary experimental result on a large-scale experiment on a cyber-physical hybrid discussion support environment in a panel discussion session in an international conference. Design/methodology/approach – In this paper, the authors propose a hybrid (cyber-physical) environment in which people can discuss online and also offline simultaneously. The authors conducted a large-scale experiment in a panel discussion session in an international conference where participants can discuss by using their online discussion support system and by physical communications as usual. Findings – The authors analyzed the obtained date from the following three viewpoints: participants’ cyber-physical attention, keywords cyber-physical linkage and cyber-physical discussion flow. These three viewpoints indicate that the methodology of the authors can be effective to support hybrid large-scale discussions. Originality/value – Online large-scale discussion has been focused as a new methodology that enable people to discuss, argue and make consensus in terms of political issues, social complex problems (like climate change), city planning and so on. In several cases, the authors found that online discussions are very effective to gather people opinions and discussions so far. Moreover, this paper proposes a hybrid (cyber-physical) environment in which people can discuss online and also offline simultaneously.

Multisensory integration (MSI) allows us to link sensory cues from multiple sources and plays a crucial role in speech development. However, it is not clear whether humans have an innate ability or whether repeated sensory input while the brain is maturing leads to efficient integration of sensory information in speech. We investigated the integration of auditory and somatosensory information in speech processing in a bimodal perceptual task in 15 young adults (age 19–30) and 14 children (age 5–6). The participants were asked to identify if the perceived target was the sound /e/ or /ø/. Half of the stimuli were presented under a unimodal condition with only auditory input. The other stimuli were presented under a bimodal condition with both auditory input and somatosensory input consisting of facial skin stretches provided by a robotic device, which mimics the articulation of the vowel /e/. The results indicate that the effect of somatosensory information on sound categorization was larger in adults than in children. This suggests that integration of auditory and somatosensory information evolves throughout the course of development.

Artificial Intelligence (AI) has been applied to solve various challenges of real-world problems in recent years. However, the emergence of new AI technologies has brought several problems, especially with regard to communication efficiency, security threats and privacy violations. Towards this end, Federated Learning (FL) has received widespread attention due to its ability to facilitate the collaborative training of local learning models without compromising the privacy of data. However, recent studies have shown that FL still consumes considerable amounts of communication resources. These communication resources are vital for updating the learning models. In addition, the privacy of data could still be compromised once sharing the parameters of the local learning models in order to update the global model. Towards this end, we propose a new approach, namely, Federated Optimisation (FedOpt) in order to promote communication efficiency and privacy preservation in FL. In order to implement FedOpt, we design a novel compression algorithm, namely, Sparse Compression Algorithm (SCA) for efficient communication, and then integrate the additively homomorphic encryption with differential privacy to prevent data from being leaked. Thus, the proposed FedOpt smoothly trade-offs communication efficiency and privacy preservation in order to adopt the learning task. The experimental results demonstrate that FedOpt outperforms the state-of-the-art FL approaches. In particular, we consider three different evaluation criteria; model accuracy, communication efficiency and computation overhead. Then, we compare the proposed FedOpt with the baseline configurations and the state-of-the-art approaches, i.e., Federated Averaging (FedAvg) and the paillier-encryption based privacy-preserving deep learning (PPDL) on all these three evaluation criteria. The experimental results show that FedOpt is able to converge within fewer training epochs and a smaller privacy budget.

Compare the WSN with other conventional network system, the changing or charging the existing battery of sensor node within WSN is a tough job. Therefore, since last decade the effort has been made to design and introduce a large number of communication protocol for WSN with given concern on the performance parameter of energy efficiency and still the key requirements within WSN domain, that how to incrementally expands the energy minimization consuming techniques of sensor battery. The other parameters include latency, fairness, throughput and delivery ratio. In this work, we propose a novel joint cooperative routing, medium access control (MAC) and physical layer protocol with traffic differentiation based QoS- aware for wireless sensor network (WSNs). This is referred to as a Joint Routing, MAC and Physical layer protocol (J-RMP). By blending the classical layered approach and combining routing, MAC and physical layer functions, the proposed J-RMP protocol achieves a solution for energy efficiency in WSNs. Convention ally, the problem of energy efficient protocol design is considered independently at respective layer of protocol stack. This paper has taken a holistic approach of finding solution by addressing the possible energy gain in Routing, MAC and Physical layer together. Firstly, it is seen that communication path with the large number of short hop substantially minimizes energy consumption. This phenomenon is used while instantaneous network information is collected with minimum overhead through the control packets for selecting next hop. Based on the updated network knowledge the next hop neighbor is chosen with reduced control overhead. Further, we describe how J-RMP protocol uses the approach for finding the constrained shortest path for forwarding packets [1], which results in load balancing in WSNs and provide mathematical analysis of node forwarding path determination within network. Finally, we compare our proposed method with existing protocols by ns-2 simulator and confirm that J-RMP outperform in some cases in term of sensitive traffics. The experimental results have proved that the traffic load has been balanced to a certain traffic, and energy efficiency has been achieved by properly adjusting the applied theory. The outcome supports the theory, and proves the effectiveness of our proposed scheme. This kind of protocol should have significant implications for various WSNs application where energy constraint is the main point of concerns.

Despite an increase in energy efficiency of WSNs research in couple of last years, still the key challenge in the design of WSNs remains to maximize the quality of service (QoS) and energy efficiency of network system. The layered strength and functionality collaboration is commonly considered as one of the most promising techniques for dealing with the given challenge to increase the duration between recharging battery and improve energy efficiency in order to prolong the sensor nodes and network lifetime. This paper presents a novel Intelligent Cross Layer QoS-aware Protocol (I-XLP) with traffic differentiation for WSNs for monitoring applications which has been done by addressing cross layered, cluster-less and application specific design. The target application is building monitoring. The novel concept behind this paper is that, by leveraging classical layered approach and blending different layer functions our proposed protocol I-XLP achieves a solution for energy efficiency and latency for the case of building monitoring applications of WSNs. This is done by combining the strong functionalities of Medium Access control (MAC), Routing and Congestion control. The proposed protocol is energy efficient and the protocol ensures lower latency for the prioritized traffic. Our proposed I-XLP is simulated by using the network simulator (ns-2). The simulation results corroborate the theoretical idea, and verify that the proposed I-XLP transmits more data with less delay and its energy consumption compared with existing protocol achieves optimum energy efficiency.

Demand Response (DR) has been extensively studied as one of the important features of smart grid. The DR strategies can be grouped into two categories, one is incentive-based DR and the other is pricing-based DR. Our work focuses on DR involving both pricing factor and incentive factor using scoring rule. In the literature, several DR mechanisms have been proposed, however, most studies have not focused on the cooperation among consumers although it is important to devise an efficient and stable DR. In this paper, we propose a cooperative demand response mechanism by using a truthful allocation mechanism with scoring rule. The brief ideas of our model are the following: the consumers will be rewarded a discount on the price to measure up how well they predict demand shift. A reward mechanism is based on a strictly proper scoring rule. This mechanism is applied between consumer agents (CA) to Cooperative Demand Response System (CDRS) and Generation Company (GENCO). The proposed mechanism is tested on real data provided by Chubu Electric Power Company and we show that this mechanism is capable of reducing peak demand.

Introduction: Unlike cardiac arrest occurring out-of-hospital, the safety and efficacy of automated external defibrillators (AED) in the hospital has not been assessed. This study examined the conditions of AED use in hospital and the prognosis of these patients. Methods and Results: We examined the condition and prognosis of 32 patients who were given AED treatment while they were in an unconscious state in the hospital, between May 2004 and January 2007. During this period, AED was used only for patients, not for visitors or hospital personnel. Ventricular fibrillation (VF) or ventricular tachycardia (VT) was observed in 7 patients, and in the other 25 the initial rhythm of the patients did not require AED. Two patients survived with the help of AED, but it did not deliver shock in two patients with VF and VT. There was no significant difference in vital prognosis due to the presence or absence of shock delivery in the VF or VT patients. Conclusion: The situation of AED use may be different whether it is used in hospital or outof-hospital. This study suggests that using AED in the hospital may have limited effect when it is used for critically ill patients.

A 50-year-old man who had suffered from old myocardial infarction presented with an episode of syncope. DC shock was required for the interruption of frequent pleomorphic ventricular tachycardia (VT). Although the treatment for heart failure decreased the frequency of VT attacks, hemodynamically unstable VT occurred several times. A 12-lead Holter electrocardiogram was used to determine the triggering premature ventricular contraction (PVC) and catheter ablation was performed by targeting this PVC. The site of origin of the triggering PVC was considered to be located between damaged cardiac muscle and intact Purkinje's fiber. No episode of PVC and VT was observed after a few days of ablation. An implantable cardioverter defibrillator was implanted but VT did not recur for more than 20 months.

We examined a patient with concealed WPW syndrome who exhibited five different electrocardiographic waveforms during tachycardia. With the intracardiac electrogram, all tachycardia were artrioventricular reciprocating tachycardia with retrograde conduction through only the accessory pathway where each artrioventricular conduction form varied: i.e., one with anterograde conduction through the fast pathway, one with anterograde conduction through the slow pathway, one with anterograde conduction through the fast pathway and slow pathway alternately, and an irregular R-R interval, one with anterograde conduction through the fast pathway and wide QRS tachycardia with the right bundle branch block type, and one with anterograde conduction through the fast pathway and wide QRS tachycardia with left bundle branch block. His bundle electrogram might be split and H, H′ was recorded at the time of sinus rhythm. Furthermore, the right and left bundle branches exhibited a different refractory period because of longitudinal dissociation in the His bundle. Therefore wide QRS tachycardia with both right and left bundle branch block might appear without complete atrioventricular block. In addition to the association between fast pathway and slow pathway, right and left bundle branch block patterns appeared.

Much research has been conducted on anomaly detection by wireless sensor networks (WSNs). The existing WSNs require specialized knowledge and skills to install the sensors in environments such as houses and buildings. Therefore, we have developed a flexible WSN based on small sensor devices that can be easily installed. The users only need to place these sensors at the locations where they want to sense and to provide some information to the server through a web page. Then, these small sensor devices automatically create wireless networks, start communicating with the central server for logging continuous data, and show anomalies by using inference based on a basic Bayesian Network. However, a serious problem is that a large amount of noise data prevents correct inferences. Therefore, in this paper, we propose a method for reducing noise data based on location sampling of real human movements. Our experimental results show that our method is effective in increasing the inference accuracy for detecting anomaly data.

Intelligent transportation systems are a set of technological solutions used to improve the performance and safety of road transportation. A crucial element for the success of these systems is the exchange of information, not only between vehicles, but also among other components in the road infrastructure through different applications. One of the most important information sources in this kind of systems is sensors. Sensors can be within vehicles or as part of the infrastructure, such as bridges, roads or traffic signs. Sensors can provide information related to weather conditions and traffic situation, which is useful to improve the driving process. To facilitate the exchange of information between the different applications that use sensor data, a common framework of knowledge is needed to allow interoperability. In this paper an ontology-driven architecture to improve the driving environment through a traffic sensor network is proposed. The system performs different tasks automatically to increase driver safety and comfort using the information provided by the sensors.

An interaction between orofacial somatosensation and the perception of speech was demonstrated in recent psychophysical studies (Ito et al. 2009; Ito and Ostry 2009). To explore further the neural mechanisms of the speech-related somatosensory-auditory interaction, we assessed to what extent multisensory evoked potentials reflect multisensory interaction during speech perception. We also examined the dynamic modulation of multisensory integration resulting from relative timing differences between the onsets of the two sensory stimuli. We recorded event-related potentials from 64 scalp sites in response to somatosensory stimulation alone, auditory stimulation alone, and combined somatosensory and auditory stimulation. In the multisensory condition, the timing of the two stimuli was either simultaneous or offset by 90 ms (lead and lag). We found evidence of multisensory interaction with the amplitude of the multisensory evoked potential reliably different than the sum of the two unisensory potentials around the first peak of multisensory response (100–200 ms). The magnitude of the evoked potential difference varied as a function of the relative timing between the stimuli in the interval from 170 to 200 ms following somatosensory stimulation. The results demonstrate clear multisensory convergence and suggest a dynamic modulation of multisensory interaction during speech.

Purpose: Orofacial somatosensory inputs play an important role in speech motor control and speech learning. Since receiving specific auditory-somatosensory inputs during speech perceptual training alters speech perception, similar perceptual training could also alter speech production. We examined whether the production performance was changed by perceptual training with orofacial somatosensory inputs. Method: We focused on the French vowels /e/ and /ø/, contrasted in their articulation by horizontal gestures. Perceptual training consisted of a vowel identification task contrasting /e/ and /ø/. Along with training, for the first group of participants, somatosensory stimulation was applied as facial skin stretch in backward direction. We recorded the target vowels uttered by the participants before and after the perceptual training and compared their F1, F2, and F3 formants. We also tested a control group with no somatosensory stimulation and another somatosensory group with a different vowel continuum (/e/-/i/) for perceptual training. Results: Perceptual training with somatosensory stimulation induced changes in F2 and F3 in the produced vowel sounds. F2 decreased consistently in the two somatosensory groups. F3 increased following the /e/-/ø/ training and decreased following the /e/-/i/ training. F2 change was significantly correlated with the perceptual shift between the first and second half of the training phase in the somatosensory group with the /e/-/ø/ training, but not with the /e/-/i/ training. The control group displayed no effect on F2 and F3, and just a tendency of F1 increase. Conclusion: The results suggest that somatosensory inputs associated to speech sound inputs can play a role in speech training and learning in both production and perception. [ABSTRACT FROM AUTHOR]

Improving fuel economy of gasoline-powered vehicles is of great importance for achieving carbon neutrality of the society. The present paper deals with a concept study of a series hybrid powertrain to reduce CO2 emissions as much as possible, considering both engine and vehicle key performances. The study utilized model-based research using 0D/1D/3D-CAE and DOE optimization techniques. The ICE simulation shows >47% break thermal efficiency under restrictions from combustion noise level and tail pipe emissions. In terms of series hybrid powertrain vehicle fuel economy, ICE power in generation for best fuel economy shall be optimized according to the given battery capacity. Also, short-term future driving power demands information may help reasonable ICE activation through the transient driving cycle. [ABSTRACT FROM AUTHOR]