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Layered sodium-ion cathode material P2-Na0.85Li0.17Ni0.21Mn0.64O2 was investigated using operandoXASto characterize structural changes occurring in the material during electrochemical sodiation/desodiation. Based on XANES data, the primary mode of charge compensation in this material is due to Ni2-3/4+ redox activity, while the Mn remains in the +4 oxidation state, thereby providing stability to this material during extended cycling. Investigation of the initial state of the compound by high resolution synchrotron XRD and 6Li MAS NMR revealed a significant amount of structural disorder due to integration of a small amount of monoclinic layered Li phase within the overall hexagonal layered Na-structure, which manifests as Li-induced stacking faults. High quality EXAFS data could be obtained using our cell construction and revealed the local structural evolution around the redox active Ni centers. [ABSTRACT FROM AUTHOR]

The status of ambient temperature sodium ion batteries is reviewed in light of recent developments in anode, electrolyte and cathode materials. These devices, although early in their stage of development, are promising for large-scale grid storage applications due to the abundance and very low cost of sodium-containing precursors used to make the components. The engineering knowledge developed recently for highly successful Li ion batteries can be leveraged to ensure rapid progress in this area, although different electrode materials and electrolytes will be required for dual intercalation systems based on sodium. In particular, new anode materials need to be identified, since the graphite anode, commonly used in lithium systems, does not intercalate sodium to any appreciable extent. A wider array of choices is available for cathodes, including high performance layered transition metal oxides and polyanionic compounds. Recent developments in electrodes are encouraging, but a great deal of research is necessary, particularly in new electrolytes, and the understanding of the SEI films. The engineering modeling calculations of Na-ion battery energy density indicate that 210 Wh kg−1 in gravimetric energy is possible for Na-ion batteries compared to existing Li-ion technology if a cathode capacity of 200 mAh g−1 and a 500 mAh g−1 anode can be discovered with an average cell potential of 3.3 V. [ABSTRACT FROM AUTHOR]

Abstract: Na-ion batteries were tested with layered Na(Ni1/3Fe1/3Mn1/3)O2 cathodes and carbon anodes in a sodium-salt containing organic ester carbonate electrolyte. Layered single phase Na(Ni1/3Fe1/3Mn1/3)O2 was synthesized from solid-state reaction using a (Ni1/3Fe1/3Mn1/3)C2O4 oxalate precursor and Na2CO3 fired at 850°C with slow-cooling. The Na-ion NayC/Na1−y(Ni1/3Fe1/3Mn1/3)O2 cell had an average voltage of ~2.75V, modest capacity of 100mAhg−1 for 150cycles (1.5–4.0V), and a capacity of 94mAhg−1 at a 1°C rate. X-ray diffraction (XRD) data of extracted cycled electrodes were used to characterize material stability and phases formed upon cycling. It was found that Na1−y(Ni1/3Fe1/3Mn1/3)O2 (0≤y≤0.46) maintains a layered structure with good crystallinity over 150cycles. These results bode well for the development and optimization of rechargeable Na-ion batteries. [Copyright &y& Elsevier]

Abstract: Highly nanocrystalline LiFePO4 was synthesized by a solvothermal process in a polyol medium namely, diethylene glycol (DEG) without any heat-treatment as a post procedure. The synchrotron powder XRD pattern of the LiFePO4 was indexed well to a pure orthorhombic system of olivine structure (space group: Pnma) with no undesirable impurities and refined fit parameters were obtained by the Rietveld refinement method using the FULLPROF program. XPS analysis revealed the divalent state of iron (Fe(II)) in the prepared sample thereby further confirming the formation of a pure olivine phase. The synthesized LiFePO4 nanocrystals exhibited well dispersed plate morphologies with average length, width and thickness of 250, 200 and 20nm, respectively. Nanoplate LiFePO4 indicated initial discharge capacity of 138mAh/g and exhibited stable capacity retention until 50 electrochemical cycles. It also appeared to reveal considerably better rate performance at enhanced C-rates because of the contribution from nano-dimensional particles when compared to that of LiFePO4 synthesized by solid state method. [Copyright &y& Elsevier]

Abstract: A series of 0.4Li2MnO3·0.6LiMO2 (M=Ni1/3Co1/3Mn1/3 and Ni1/3Cr1/3Mn1/3) cathode materials are prepared by a co-precipitation method with subsequent quenching. Crystal structures of samples are investigated by X-ray diffraction and electron diffraction, which show a co-existence of rhombohedral and monoclinic structures indicating nanocomposite characteristics of the sample of 0.4Li2MnO3·0.6Li Ni1/3Cr1/3Mn1/3O2. The average particle size distributions of the powders are analyzed to be an order 400 and 100nm. The 0.4Li2MnO3·0.6LiMO2 (M=Ni1/3Co1/3Mn1/3 and Ni1/3Cr1/3Mn1/3) electrodes, which consist of a well balanced partial phases of rhombohedral and monoclinic can deliver a high reversible capacity of 220–230mAh/g during an extended cycling. [Copyright &y& Elsevier]

LiFePO4 nanocrystals were synthesized in various polyol media without any further post-heat treatment. The LiFePO4 samples synthesized using three different polyol media namely, diethylene glycol (DEG), triethylene glycol (TEG), and tetraethylene glycol (TTEG), exhibited plate and rod-shaped structures with average sizes of 50–500 nm. The X-ray diffraction (XRD) patterns were indexed on the basis of an olivine structure (space group: Pnma). The samples prepared in DEG, TEG, and TTEG polyol media showed reversible capacities of 123, 155, and 166 mAh/g, respectively, at current density of 0.1 mA/cm2 with no capacity fading and exhibited excellent capacity retention up to the 50th cycle. In particular, the samples showed excellent performances at high rates of 30 and 60 C with high capacity retention. It is assumed that the nanometer size materials (~50 nm) possessing a highly crystalline nature may generate improved performance at high rate current densities. [ABSTRACT FROM AUTHOR]

As society has developed, fishing villages that have relied solely on traditional fishing have found themselves on the verge of extinction. Therefore, efforts are being made to transform fishing villages into areas with various functions including recreation, tourism, and education. In this regard, the main purpose of this study is to analyze the relative importance and priorities of the multi-criteria decision-making (MCDM) process used in the revitalization of fishing village tourism. To this end, the A'WOT (AHP/SWOT) hybrid approach, developed in combination with the SWOT (Strengths, Weaknesses, Opportunities, Threats) analysis and the AHP (Analytic Hierarchy Process) method, was used to determine the significant factors. The results of the study demonstrated that the 'opportunities' and 'strengths' areas are relatively important when it comes to the priority of sustainable development. We also identified the high importance in terms of global weight of both 'Increased demand for leisure, rest and ecotourism' and 'Possession of natural resources of diverse and distinctive fishing villages by sea and region' as sustainable ways to revitalize fishing communities. This study demonstrates that with appropriate data and an applicable systematic process, the A'WOT approach can adequately show where intervention is most needed. The study shows that the application of tourism in the current context has the potential to approach the issue of fishing village tourism. Furthermore, this study is meaningful in that it quantifies the importance of fishing village tourism attributes by using a systematic approach, and it concludes with suggesting where the emphasis should be placed on policy and strategy. [ABSTRACT FROM AUTHOR]

As robots become increasingly common in human-populated environments, they must be perceived as social beings and behave socially. People try to preserve their own space during social interactions with others, and this space depends on a variety of factors, such as individual characteristics or their age. In real-world social spaces, there are many different types of people, and robots need to be more sensitive, especially when interacting with vulnerable subjects such as children. However, the current navigation methods do not consider these differences and apply the same avoidance strategies to everyone. Thus, we propose a new navigation framework that considers different social types and defines appropriate personal spaces for each, allowing robots to respect them. To this end, the robot needs to classify people in a real environment into social types and define the personal space for each type as a Gaussian asymmetric function to respect them. The proposed framework is validated through simulations and real-world experiments, demonstrating that the robot can improve the quality of interactions with people by providing each individual with an adaptive personal space. The proposed costmap layer is available on GitHub. [ABSTRACT FROM AUTHOR]

Robot navigation has transitioned from avoiding static obstacles to adopting socially aware navigation strategies for coexisting with humans. Consequently, socially aware navigation in dynamic, human-centric environments has gained prominence in the field of robotics. One of the methods for socially aware navigation, the reinforcement learning technique, has fostered its advancement. However, defining appropriate reward functions, particularly in congested environments, holds a significant challenge. These reward functions, crucial for guiding robot actions, necessitate intricate human-crafted design due to their complex nature and inability to be set automatically. The multitude of manually designed reward functions contains issues such as hyperparameter redundancy, imbalance, and inadequate representation of unique object characteristics. To address these challenges, we introduce a transformable Gaussian reward function (TGRF). The TGRF possesses two main features. First, it reduces the burden of tuning by utilizing a small number of hyperparameters that function independently. Second, it enables the application of various reward functions through its transformability. Consequently, it exhibits high performance and accelerated learning rates within the deep reinforcement learning (DRL) framework. We also validated the performance of TGRF through simulations and experiments. [ABSTRACT FROM AUTHOR]

Institutions exhibit substantial heterogeneity in trading behavior. Although many studies consider their investment horizon or portfolio concentration in isolation, we propose a two-way investor classification that jointly accounts for both characteristics. Our conceptual framework provides an intuitive account of each institutional investor group's trading and the ensuing impact on market price dynamics, offering fresh insights into seemingly mixed findings in the literature. Our results indicate that a short investment horizon and a high portfolio concentration are both proxies for an informational advantage. We also reveal substantial heterogeneity in the behavior of concentrated versus diversified institutions with similar investment horizons. • Existing studies on institutional investors consider their investment horizon or portfolio concentration in isolation, with diverse and often mixed empirical findings. • We propose a simple two-way institutional investor classification that jointly accounts for investment horizon and portfolio concentration. • Our classification yields a more intuitive account of institutional trading behavior and its ensuing implications on stock prices. • Short investment horizon and high portfolio concentration both appear to be proxies for the institutions' informational advantage. • We further reveal substantial differences in trading behavior among institutions sharing similar investment horizons but differing in their respective portfolio concentrations. [ABSTRACT FROM AUTHOR]

This study examined how demographic information, chronological age, older adults' physical and mental health, and basic psychological needs affected travel intention. The survey samples were collected from 577 adults, all over 60 years of age. A hierarchical multiple regression analysis was used to test the proposed hypotheses. First, demographic information with chronological age was used for primary analysis. The outcome indicated that chronological age was negatively associated with travel intention while all other demographic variables were not. Secondly, when physical and mental health condition variables were added, physical health positively affected travel intention while chronological age still negatively affected travel intention. Thirdly, psychological needs (autonomy, competence, relatedness) for travel were included in the final analysis. The outcome showed that all psychological needs variables had a significant impact on travel intention for those with a physical health condition. However, chronological age was not a significant factor in travel intention during this analysis. This study shows that chronological age is not always an important factor that affects older adults' travel intention when other health and psychological variables are considered. This study provides some practical implications and tips for travel industry managers who are targeting the aging population. [ABSTRACT FROM AUTHOR]

In this paper, we present a knee exoskeleton. Due to the complicated structure of the knee, an exoskeleton can limit the wearer's movement (e.g., when completely sitting down). To prevent this, the proposed exoskeleton is designed to move the ankle part prismatically, so the movement of the wearer is not limited. In addition, the developed exoskeleton could be worn on only one leg, but in this case, it is difficult to detect the intention because the relative relationship information of the two legs is unknown. For this purpose, the length between the knee center of rotation and the ankle (LBKA) was measured and used for intention detection. Using a physical sensor—an encoder and an LBKA sensor, the success rate of intention detection was 82.1%. By additionally using an electromyogram (EMG) sensor, the success rate of intention detection was increased to 92%, and the intention detection was also 27.1 ms faster on average. [ABSTRACT FROM AUTHOR]

In this study, we developed a single leg knee joint assistance robot. Commonly used exoskeletons have a left-right pair, but when only one leg of the wearer is uncomfortable, it is effective to wear the exoskeleton on only the uncomfortable leg. The designed exoskeleton uses a lightweight material and uses a wire-driven actuator, which reduces the weight of the driving section that is attached on the knee directly. Therefore, proposed exoskeleton reduces the force of inertia that the wearer experiences. In addition, the lower frame length of the exoskeleton can be changed to align with the complex movement of the knee. Furthermore, the length between the knee center of rotation and the ankle (LBKA) is measured by using this structure, and the LBKA values are used as the data for intention detection. These value helps to detect the intention because it changes faster than a motor encoder value. A neural network was trained using the motor encoder values, and LBKA values. Neural network detects the intention of three motions (stair ascending, stair descending, and walking), Training results showed that intention detection was good in various environments. [ABSTRACT FROM AUTHOR]

This study presents a defect passivation approach using coumarin dye (7-diethylaminobenzopyran-2-one) as a multi-functional passivating agent of perovskite films to boost power conversion efficiency (PCE) and operating stability of PSCs. The coumarin dye could offer strong interaction with under-coordinated Pb2+ and vacant I − in [PbI 6 ] octahedral frameworks due to multiple functional groups, which could serve as potential Lewis bases or hydrogen bonding sites, as well as highly conjugated aromaticity. The incorporation of coumarin dye contributes to improved film morphology of perovskite films, leading to compact and uniform grains without compromising crystallinity. Correspondingly, enhanced carrier extraction/transport and suppressed trap-assisted recombination are promoted in the perovskite films modified with coumarin dye. As a result, the coumarin dye incorporation improved the photovoltaic performance delivering a PCE of 20.85 % in planar p-i-n PSCs. The optimized device also recorded excellent indoor photovoltaic performance (PCE = 30.35 %) under dim-light condition. Furthermore, the devices passivated with coumarin dye also maintained >90 % of their initial PCEs after exposed under continuous indoor lighting irradiation (1000 lux) in ambient atmosphere for 2000 h, exhibiting impressive reliability and practical applicability. • A passivation strategy of defective trap-sites of perovskite films by coumarin dye is demonstrated. • High-quality perovskite films are prepared by defect passivation by coumarin dye. • High-efficiency perovskite solar cells are demonstrated by incorporation coumarin dye into the perovskite films. [ABSTRACT FROM AUTHOR]

To achieve endemic phases, repeated vaccinations are necessary. However, individuals may grapple with whether to get vaccinated due to potential side effects. When an individual is already immune due to previous infections or vaccinations, the perceived risk from vaccination is often less than the risk of infection. Yet, repeated rounds of vaccination can lead to avoidance, impeding the establishment of endemic phases. We explore this phenomenon using an individual-based Monte Carlo simulation, validating our findings with game theory. The Nash equilibrium encapsulates individuals' non-cooperative behavior, while the system's optimal value represents the societal benefits of altruistic cooperation. We define the difference between these as the price of anarchy. Our simulations reveal that the price of anarchy must fall below a threshold of 12.47 for endemic phases to be achieved in a steady state. This suggests that for a basic reproduction number of 10, a consistent vaccination rate greater than 89% is required. These findings offer new insights into vaccination-related decision-making and can inform effective strategies to tackle infectious diseases. [ABSTRACT FROM AUTHOR]

As the demand for service robots increases, a mobile manipulator robot which can perform various tasks in a dynamic environment attracts great attention. There are some controllers that control mobile platform and manipulator arm simultaneously for efficient performance, but most of them are difficult to apply universally since they are based on only one mobile manipulator model. This lack of versatility can be a big problem because most mobile manipulator robots are made by connecting a mobile platform and manipulator from different companies. To overcome this problem, this paper proposes a simultaneous controller which can be applied not only to one model but also to various types of mobile manipulator robots. The proposed controller has three main characteristics, which are as follows: (1) establishing a pose that motion planning can be carried out in any position, avoiding obstacles and stopping in a stable manner at the target coordinates, (2) preventing the robot from collision with surrounding obstacles while driving, (3) defining a safety area where the manipulator does not hit the obstacles while driving and executing the manipulation accordingly. Our controller is fully compatible with Robot Operating System (ROS) and has been used successfully with three different types of mobile manipulator robots. In addition, we conduct motion planning experiments on five targets, each in two simulation worlds, and two motion planning scenarios using real robots in real-world environments. The result shows a significant improvement in time compared to existing control methods in various types of mobile manipulator and demonstrates that the controller works successfully in the real environment. The proposed controller is available on GitHub. [ABSTRACT FROM AUTHOR]

On-skin stretchable electronic devices that can acquire electrophysiological signals for controllable human-machine interactions are of considerable importance in wearable robotics applications. The straightforward, large-area fabrication of structurally stretchable electronic sensors processed by ultrafast laser ablation techniques provides great insights into low-cost wearable stretchable sensors. In this article, a patch-based large-area frame-type stretchable sensor array system that covers a large portion (∼20 cm wide) of the human arm—processed by a simple, ultrafast (<4 min), user-accessible, mask-independent laser ablation technique—is demonstrated with resolutions down to 50 μm and 100% yield. The Ecoflex_PDMS-PEIE patch—an enabling material of soft (low modulus, ∼50 kPa), reversible adhesion to the skin (∼3.3 kPa), high permeability for water loss (∼8 gm-2h-1), and high stretchability (>100%)—allows the sensor to conformally attach to the skin for long-term usage. The patch-based sensor exhibited robust electromechanical properties under significant mechanical loadings for 10 000 cycles, a promising characteristic for product commercialization. Moreover, the results suggest that the proposed method is suitable for the fabrication of diverse materials for stretchable electronic applications. We verified the application of electromyography signals with human motion determination to control the movements of the robotic hand. [ABSTRACT FROM AUTHOR]

Abstract: For an effective and efficient visual recognition system, the region-of-interest extraction of users is one of most important image processing duties. Generally, the position of the pupil in an eyeball is directly related to the user''s interest in an input visual image. However, when using a monocular eye tracking system, it is not easy to discern an accurate position of the region-of-interest of the user in a three-dimensional space. In this paper, an eye tracking system based on binocular gaze detection is presented. The proposed system is designed as a wearable device with three mini-cameras and two hot-mirrors for users to see through. The two eye monitoring system acquires the pupil images of both eyes through the hot-mirrors illuminated by infrared LEDs; the front-view camera acquires the image visible to the user. The experiment results show that the proposed system improves upon the region-of-interest localization error of the users in both the horizontal and vertical directions for the front-view images acquired by the user. Through the proposed system, it became possible to accurately extract the user''s region-of-interest, and so can be used to improve the image processing speed through focused information processing for the region-of-interest and narrow the selective information acquisition needed for users. [Copyright &y& Elsevier]

In spectroscopic experiments, data acquisition in multi-dimensional phase space may require long acquisition time, owing to the large phase space volume to be covered. In such a case, the limited time available for data acquisition can be a serious constraint for experiments in which multidimensional spectral data are acquired. Here, taking angle-resolved photoemission spectroscopy (ARPES) as an example, we demonstrate a denoising method that utilizes deep learning as an intelligent way to overcome the constraint. With readily available ARPES data and random generation of training datasets, we successfully trained the denoising neural network without overfitting. The denoising neural network can remove the noise in the data while preserving its intrinsic information. We show that the denoising neural network allows us to perform a similar level of second-derivative and line shape analysis on data taken with two orders of magnitude less acquisition time. The importance of our method lies in its applicability to any multidimensional spectral data that are susceptible to statistical noise. [ABSTRACT FROM AUTHOR]