Contemporary advanced driver assistance system (ADAS) features for semi-autonomous vehicles include braking assistance during collision avoidance. Although precollision detection typically relies on ...sensing systems to enable production vehicles to perceive oncoming road obstacles, the physiological state of the driver is not measured to predict emergency braking. On the other hand, previous driving simulation experiments have demonstrated the ability of regularized linear discriminant analysis (RLDA) to predict precollision braking using brain signals from multiple electroencephalogram (EEG) electrodes. In contrast, the current study used EEG data from these previous experiments to determine the quality of support vector machine (SVM) predictions as a first step toward realizing a brain-computer interface (BCI) for emergency braking. Power spectral density (PSD) features were extracted from the EEG of one electrode to train and evaluate an SVM. Through a novel data ablation analysis, the optimal number of PSD components was determined to optimize model classification quality measured by the area under the curve (AUC). A comparison of the proposed model to the previous RLDA and other machine learning (ML) methods indicated that the SVM had a superior AUC. Thus, the proposed model is a candidate for assisting ADASs with precollision detection. Moreover, since the proposed model only utilized one electrode, our study potentially contributes to the facilitation of BCIs for autonomous vehicles.
A chemical reaction network (CRN) is composed of reactions that can be seen as interactions among entities called species, which exist within the system. Endowed with kinetics, CRN has a ...corresponding set of ordinary differential equations (ODEs). In chemical reaction network theory, we are interested with connections between the structure of the CRN and qualitative properties of the corresponding ODEs. One of the results in decomposition theory of CRNs is that the intersection of the sets of positive steady states of the subsystems is equal to the set of positive steady states of the whole system, if the decomposition is independent. Hence, computational approach using independent decompositions can be used as an efficient tool in studying large systems. In this work, we provide a necessary and sufficient condition for the existence of a nontrivial independent decomposition of a CRN, which leads to a novel step-by-step method to obtain such decomposition, if it exists. We also illustrate these results using real-life examples. In particular, we show that a CRN of a popular model of anaerobic yeast fermentation pathway has a nontrivial independent decomposition, while a particular biological system, which is a metabolic network with one positive feedforward and a negative feedback has none. Finally, we analyze properties of positive steady states of reaction networks of specific influenza virus models.
As automobiles become increasingly autonomous, there is growing interest in personalized automation based on human behavior. However, there is an increasing need for behavioral data from vehicle ...occupants that could be acquired through physiological sensors. Hence, the motivation of this review is to provide information to develop practical physiological sensors to assess behavior, while maintaining the acceptance, privacy, and safety of vehicle occupants. In order to improve driver and passenger experiences and build trust between autonomous vehicles and humans, the current review considers a number of studies addressing driving tasks based on sensors that monitor vehicle occupant behavior. By including applications to emergency and non-emergency driving scenarios, a survey of literature is conducted on physiological sensing for personalization of semi-autonomous driving. Given the limited availability of sensor technology that is specifically designed to monitor behavior in automobiles, the survey is provided as a resource to further physiological sensor development for automotive applications.
Pathogenic H7N9 avian influenza viruses continue to represent a public health concern, and several candidate vaccines are currently being developed. It is vital to assess if protective antibodies are ...induced following vaccination and to characterize the diversity of epitopes targeted. Here we characterized the binding and functional properties of twelve H7-reactive human antibodies induced by a candidate A/Anhui/1/2013 (H7N9) vaccine. Both neutralizing and non-neutralizing antibodies protected mice in vivo during passive transfer challenge experiments. Mapping the H7 hemagglutinin antigenic sites by generating escape mutant variants against the neutralizing antibodies identified unique epitopes on the head and stalk domains. Further, the broadly cross-reactive non-neutralizing antibodies generated in this study were protective through Fc-mediated effector cell recruitment. These findings reveal important properties of vaccine-induced antibodies and provide a better understanding of the human monoclonal antibody response to influenza in the context of vaccines.
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•Generation and characterization of human monoclonal antibodies after H7N9 vaccination•Neutralizing and non-neutralizing protective antibodies are induced by H7N9 vaccine•Neutralizing antibodies target known and novel epitopes on the hemagglutinin protein•Non-neutralizing antibodies mediate protection through Fc-FcγR interactions
Henry Dunand et al. characterize the antibodies induced following H7N9 influenza vaccination and identify three categories of H7-reactive protective antibodies. These antibodies target various epitopes on the HA head and stalk domains. Cross-reactive non-neutralizing antibodies recruit effector cells through Fc-FcγR interactions to mediate protection.
Neuroectodermal disease involves abnormalities that arise from the ectodermal origin, such as the nervous system, eyeball, retina, and skin. Due to the rarity of the disease, it is often ...underdiagnosed or misdiagnosed. In this study, the researcher presents two cases of pediatric patients with no fetomaternal complications who presented with focal seizures as their initial complaint. During the examination, varying skin color pigmentation and an abnormal neurophysical examination were observed. Cranial imaging showed hemimegalencephaly and voltage asymmetry on EEG. Skin biopsy was performed on both cases, which revealed basketweave orthokeratosis. The combination of a triad of intractable epilepsy, developmental delay, and cutaneous lesion prompted the consideration of a neuroectodermal disease. The study shows two cases of hypomelanosis of Ito and nevus syndrome, both of which may be due to mTOR and RAS pathways, respectively.
Disabilities of the upper limb, such as hemiplegia or upper limb amputation, can limit automobile drivers to steering with one healthy arm. For the benefit of these drivers, recent studies have ...developed prototype interfaces that realized surface electromyography (sEMG)-controlled steering assistance with path-following accuracy that has been validated with driving simulations. In contrast, the current study expands the application of sEMG-controlled steering assistance by validating the Myo armband, a mass-produced sEMG-based interface, with respect to the path-following accuracy of a commercially available automobile. It was hypothesized that one-handed remote steering with the Myo armband would be comparable or superior to the conventional operation of the automobile steering wheel. Although results of low-speed field testing indicate that the Myo armband had lower path-following accuracy than the steering wheel during a 90° turn and wide U-turn at twice the minimum turning radius, the Myo armband had superior path-following accuracy for a narrow U-turn at the minimum turning radius and a 45° turn. Given its overall comparability to the steering wheel, the Myo armband could be feasibly applied in future automobile studies.
In order to guarantee the continuous operation of electric power systems (EPS), a proper planning of these networks in steady and transient state must be performed. This paper presents an N−1 ...multi-contingency AC optimal power flow (OPF) that embeds, in the same mathematical optimization model, a set of transient stability constraints (TSC) that guarantee rotor angle and angular velocity variation within technical limits, at given N−1 contingencies. Furthermore, the proposed model considers the operation of volt/var controllers, such as shunt elements and OLTC transformers, to further improve the operation of the EPS, under given levels of demand and generation. Taking advantage of the classical first-order transient stability model of synchronous machines and the implicit trapezoidal integration rule, the proposed model can be formulated as a stand-alone mixed-integer nonlinear programming (MINLP) model. Then, through well-established linearization techniques, the initially proposed MINLP model is transformed into a new mixed-integer linear programming (MILP) model, which can be implemented via algebraic programming languages, such as AMPL, and solved using convex optimization solvers, such as CPLEX. Three systems with dissimilar number of synchronous machines and nodes have been used for tests (i.e., the 9-Bus/3-Generator Western System Coordinating Council (WSCC) system, the 39-Bus/10-Generator New England system and the 68-Bus/16-Generator IEEE system). The efficiency of the proposed linearization techniques and the stability requirements of the solutions have been validated using an exact AC power flow and the transient stability analysis program PSAT-Matlab. Results show the ability of the proposed MILP model to provide stable operating points under N−1 contingencies, at minimum production cost.
Canadian multilingualism and multiculturalism are on the rise. Yet, monolingual language instruction remains the standard: students are often discouraged from using their additional languages and ...teaching materials still lack a plurilingual lens. To further inform the practice of plurilingual pedagogies, this paper reports on results of a convergent mixed methods study that investigated the plurilingual learning strategies of 20 adult English as an additional language (EAL) student tutors and tutees in a Francophone college in Montreal. The study asked (1) What plurilingual strategies do EAL tutors and tutees use to teach and learn English from each other? (2) What are their perceptions of the affordances and challenges of these plurilingual strategies? Data from an observation grid, fieldnotes, and semi-structured interviews were analyzed deductively and inductively, and merged for convergence analysis. Results show that (1) participants regularly engaged in plurilingual practices including translation, translanguaging, and crosslinguistic comparisons during the tutoring sessions. Further, (2) participants perceived plurilingual strategies as useful for supporting English language development, fostering positive learning experience and conceptual links; however, they noted challenges pertaining to the monolingual posture of EAL instruction, to English oral production, and to the feasibility of plurilingual pedagogies. Implications for EAL education in multilingual contexts like Canada are discussed.
Haptic-shared steering (HSS) systems have been reported to enhance vehicle safety and reduce the workload for drivers. However, few studies have focused on modeling the lateral vehicle control ...behaviors of distracted drivers for HSS. The current study models this type of behavior in a series of high-fidelity driving simulator experiments with 18 participants. Two experimental conditions for a double lane change task are tested: HGT-Constant (haptic guidance torque with a constant gain) and HGT-Adaptive (haptic guidance torque with an adaptive gain). A gated recurrent unit (GRU) network is used to model lateral control behavior during driving. The effectiveness of the GRU network-based lateral control model of distracted drivers is benchmarked using a state-of-the-art long short-term memory network, a back propagation network, an extreme learning machine, and a traditional two-point visual model with neuromuscular dynamics. Experimental results indicate that the GRU network has the highest accuracy in terms of root mean square error, mean absolute error, mean absolute percentage error, and determination coefficient. In addition, a simulation model of the driver-vehicle-road closed-loop system demonstrates that the proposed model predicts driver behavior with acceptable lateral position error.
Driver distraction is a well-known cause for traffic collisions worldwide. Studies have indicated that shared steering control, which actively provides haptic guidance torque on the steering wheel, ...effectively improves the performance of distracted drivers. Recently, adaptive shared steering control based on the forearm muscle activity of the driver has been developed, although its effect on distracted driver behavior remains unclear. To this end, a high-fidelity driving simulator experiment was conducted involving 18 participants performing double lane change tasks. The experimental conditions comprised two driver states: attentive and distracted. Under each condition, evaluations were performed on three types of haptic guidance: none (manual), fixed authority, and adaptive authority based on feedback from the forearm surface electromyography of the driver. Evaluation results indicated that, for both attentive and distracted drivers, haptic guidance with adaptive authority yielded lower driver workload and reduced lane departure risk than manual driving and fixed authority. Moreover, there was a tendency for distracted drivers to reduce grip strength on the steering wheel to follow the haptic guidance with fixed authority, resulting in a relatively shorter double lane change duration.
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