Destabilized Passivation Layer on Magnesium-Based Intermetallics as Potential Anode Active Materials for Magnesium Ion Batteries

Passivation of magnesium metal anode is one of the critical challenges for the development of magnesium batteries. Here we investigated the passivation process of an intermetallic anode: Mg3Bi2 synthesized by solid-state and thin film process. The Mg3Bi2 composite electrode shows excellent reversibility in magnesium bis(trifluoromethansulfonylamide) dissolved in acetonitrile, while Mg3Sb2, which has same crystal structure and similar chemical properties, is electrochemically inactive. We also fabricated the Mg3Bi2 thin film electrodes, which show reversibility with low overpotential not only in the acetonitrile solution but also glyme-based solutions. Surface layer corresponding to the decomposed TFSA anion is slightly suppressed in the case of the Mg3Bi2 thin film electrode, compared with Mg metal. Comparative study of hydrolysis process of the Mg3Bi2 and the Mg3Sb2 suggests that the both intermetallic anodes are not completely passivated. The bond valence sum mapping of the Mg3Bi2 indicates that the fast Mg2+ diffusion pathway between 2d tetrahedral sites is formed. The electrochemical properties of the Mg3Bi2 anode is mainly due to the less passivation surface with the fast Mg2+ diffusion pathways

Time- and Learner-Dependent Hidden Markov Model for Writing Process Analysis Using Keystroke Log Data

Teaching writing strategies based on writing processes has attracted wide attention as a method for developing writing skills. The writing process can be generally defined as a sequence of subtasks, such as planning, formulation, and revision. Therefore, instructor feedback is often given based on sequence patterns of those subtasks. For such feedback, instructors need to analyze sequence patterns for all learners, which becomes problematic as the number of learners increases. To resolve this problem, this study proposes a new machine-learning method that estimates sequence patterns from keystroke log data. Specifically, we propose an extension of the Gaussian hidden Markov model that incorporates parameters representing temporal change in a subtask appearance distribution for each learner. Furthermore, we propose a collapsed Gibbs sampling algorithm as the parameter estimation method for the proposed model. We demonstrate effectiveness of the proposed model by applying it to actual keystroke log datasets

Predictors of exercise-induced pulmonary hypertension in patients with asymptomatic degenerative mitral regurgitation: mechanistic insights from 2D speckle-tracking echocardiography

Presence of exercise-induced pulmonary hypertension (EIPH) in asymptomatic degenerative mitral regurgitation (DMR) determines prognosis. This study aimed to elucidate the mechanism and predictors of EIPH in asymptomatic DMR. Ninety-one consecutive asymptomatic patients with DMR who underwent exercise stress echocardiography were prospectively included. We obtained various conventional echocardiographic parameters at rest and during peak exercise, as well as left atrial (LA) function at rest using 2-dimensional speckle-tracking analysis. The 25 patients (33.3%) with EIPH were significantly older and had a greater ratio of mitral peak velocity of early filling to early diastolic mitral annular velocity during peak exercise than those without EIPH. LA strain (LAS)-s and LAS-e, indices of LA reservoir and conduit function, respectively, were significantly lower in those with EIPH than in those without EIPH. Multivariate analysis indicated that LAS-s was the only resting echocardiographic parameter that independently predicted EIPH, with a cut-off value of 26.9%. Furthermore, Kaplan-Meier curve analysis showed that symptom-free survival was markedly lower among those with reduced LAS-s. In conclusion, decreased LA reservoir function contributes to EIPH, and LAS-s at rest is a useful indicator for predicting EIPH in asymptomatic patients with DMR

Differences in the Optimal Motion of Android Robots for the Ease of Communications Among Individuals With Autism Spectrum Disorders

Android robots are employed in various fields. Many individuals with autism spectrum disorders (ASD) have the motivation and aptitude for using such robots. Interactions with these robots are structured to resemble social situations in which certain social behaviors can occur and to simulate daily life. Considering that individuals with ASD have strong likes and dislikes, ensuring not only the optimal appearance but also the optimal motion of robots is important to achieve smooth interaction and to draw out the potential of robotic interventions. We investigated whether individuals with ASD found it easier to talk to an android robot with little motion (i.e., only opening and closing its mouth during speech) or an android robot with much motion (i.e., in addition to opening and closing its mouth during speech, moving its eyes from side to side and up and down, blinking, deeply breathing, and turning or moving its head or body at random). This was a crossover study in which a total of 25 participants with ASD experienced mock interviews conducted by an android robot with much spontaneous facial and bodily motion and an android robot with little motion. We compared demographic data between participants who answered that the android robot with much motion was easier to talk to than android robot with little motion and those who answered the opposite. In addition, we investigated how each type of demographic data was related to participants\u27 feeling of comfort in an interview setting with an android robot. Fourteen participants indicated that the android robot with little motion was easier to talk to than the robot with much motion, whereas 11 participants answered the opposite. There were significant differences between these two groups in the sensory sensitivity score, which reflects the tendency to show a low neurological threshold. In addition, we found correlations between the sensation seeking score, which reflects the tendency to show a high neurological threshold, and self-report ratings of comfort in each condition. These results provide preliminary support for the importance of setting the motion of an android robot considering the sensory traits of ASD

Bioinspired approaches for toughening of fibre reinforced polymer composites

In Nature, there are a large range of tough, strong, lightweight and multifunctional structures that can be an inspiration to better performingmaterials. Thiswork presents a review of structures found in Nature, frombiological ceramics and ceramics composites, biological polymers and polymers composites, biological cellular materials, biological elastomers to functional biological materials, and their main tougheningmechanisms, envisaging potential mimicking approaches that can be applied in advanced continuous fibre reinforced polymer (FRP) composite structures. For this, themost common engineering compositemanufacturing processes and current composite damage mitigation approaches are analysed. This aims at establishing the constraints of biomimetic approaches development as these bioinspired structures are to be manufactured by composite technologies. Combining both Nature approaches and engineering composites developments is a route for the design and manufacturing of high mechanical performance and multifunctional composite structures, therefore new bioinspired solutions are proposed.This research was funded by the project “IAMAT—Introduction of advanced materials technologies into new product development for the mobility industries”, with reference MITP-TB/PFM/0005/2013, under the MIT-Portugal program and in the scope of projects with references UIDB/05256/2020 and UIDP/05256/2020, exclusively financed by FCT - Fundação para a Ciência e Tecnologia

Improved Cycling Performance of Intermetallic Anode by Minimized SEI Layer Formation

Electrochemical properties of bismuth composite electrode are investigated as potential negative electrode for lithium ion batteries. The electrode shows severe capacity decay typically observed in the case of alloy-based materials, using a conventional carbonate-based electrolyte solution. The electrode maintained only 10% of the theoretical capacity after 25 cycles of lithiation/delithiation process. The electrode shows poor coulombic efficiency of 98% of reversible capacity, even after 50 cycles. The bismuth electrode cycled in the LiBH4 electrolyte maintained relatively large bismuth particles compared with the electrode cycled in the carbonate-based electrolyte. In situ FTIR study proved the carbonate-based electrolyte forms passivation layer <0.7 V vs. Li, while the LiBH4 electrolyte does not passivate the electrode surface