Achieving complete electrooxidation of ethanol by single atomic Rh decoration of Pt nanocubes.

SignificanceDirect ethanol fuel cells are attracting growing attention as portable power sources due to their advantages such as higher mass-energy density than hydrogen and less toxicity than methanol. However, it is challenging to achieve the complete electrooxidation to generate 12 electrons per ethanol, resulting in a low fuel utilization efficiency. This manuscript reports the complete ethanol electrooxidation by engineering efficient catalysts via single-atom modification. The combined electrochemical measurements, in situ characterization, and density functional theory calculations unravel synergistic effects of single Rh atoms and Pt nanocubes and identify reaction pathways leading to the selective C-C bond cleavage to oxidize ethanol to CO2. This study provides a unique single-atom approach to tune the activity and selectivity toward complicated electrocatalytic reactions.

An Amiable Design of Cobalt Single Atoms as the Active Sites for Oxygen Evolution Reaction in Desalinated Seawater.

Green fuel from water splitting is hardcore for future generations, and the limited source of fresh water (<1%) is a bottleneck. Seawater cannot be used directly as a feedstock in current electrolyzer techniques. Until now single atom catalysts were reported by many synthetic strategies using notorious chemicals and harsh conditions. A cobalt single-atom (CoSA) intruding cobalt oxide ultrasmall nanoparticle (Co3 O4 USNP)-intercalated porous carbon (PC) (CoSA-Co3 O4 @PC) electrocatalyst was synthesized from the waste orange peel as a single feedstock (solvent/template). The extended X-ray absorption fine structure spectroscopy (EXAFS) and theoretical fitting reveal a clear picture of the coordination environment of the CoSA sites (CoSA-Co3 O4 and CoSA-N4 in PC). To impede the direct seawater corrosion and chlorine evolution the seawater has been desalinated (Dseawater) with minimal cost and the obtained PC is used as an adsorbent in this process. CoSA-Co3 O4 @PC shows high oxygen evolution reaction (OER) activity in transitional metal impurity-free (TMIF) 1 M KOH and alkaline Dseawater. CoSA-Co3 O4 @PC exhibits mass activity that is 15 times higher than the commercial RuO2 . Theoretical interpretations suggest that the optimized CoSA sites in Co3 O4 USNPs reduce the energy barrier for alkaline water dissociation and simultaneously trigger an excellent OER followed by an adsorbate evolution mechanism (AEM).

Electrochemically Activatable Liquid Organic Hydrogen Carriers and Their Applications.

Hydrogen has been chosen as an environmentally benign energy source to replace fossil-fuel-based energy systems. Since hydrogen is difficult to store and transport in its gaseous phase, thermochemical liquid organic hydrogen carriers (LOHCs) have been developed as one of the alternative technologies. However, the high temperature and pressure requirements of thermochemical LOHC systems result in huge energy waste and impracticality. This Perspective proposes electrochemical (EC)-LOHCs capable of more efficient, safer, and lower temperature and pressure hydrogen storage/utilization. To enable this technology, several EC-LOHC candidates such as isopropanol, phenolic compounds, and organic acids are described, and the latest research trends and design concepts of related homo/hetero-based electrocatalysts are discussed. In addition, we propose efficient fuel-cell-based systems that implement electrochemical (de)hydrogenation of EC-LOHCs and present prospects for relevant technologies.

Smartphone Authentication System Using Personal Gaits and a Deep Learning Model.

In a society centered on hyper-connectivity, information sharing is crucial, but it must be ensured that each piece of information is viewed only by legitimate users; for this purpose, the medium that connects information and users must be able to identify illegal users. In this paper, we propose a smartphone authentication system based on human gait, breaking away from the traditional authentication method of using the smartphone as the medium. After learning human gait features with a convolutional neural network deep learning model, it is mounted on a smartphone to determine whether the user is a legitimate user by walking for 1.8 s while carrying the smartphone. The accuracy, precision, recall, and F1-score were measured as evaluation indicators of the proposed model. These measures all achieved an average of at least 90%. The analysis results show that the proposed system has high reliability. Therefore, this study demonstrates the possibility of using human gait as a new user authentication method. In addition, compared to our previous studies, the gait data collection time for user authentication of the proposed model was reduced from 7 to 1.8 s. This reduction signifies an approximately four-fold performance enhancement through the implementation of filtering techniques and confirms that gait data collected over a short period of time can be used for user authentication.

Template-Directed Rapid Synthesis of Pd-Based Ultrathin Porous Intermetallic Nanosheets for Efficient Oxygen Reduction.

Atomically ordered intermetallic nanoparticles exhibit improved catalytic activity and durability relative to random alloy counterparts. However, conventional methods with time-consuming and high-temperature syntheses only have rudimentary capability in controlling the structure of intermetallic nanoparticles, hindering advances of intermetallic nanocatalysts. We report a template-directed strategy for rapid synthesis of Pd-based (PdM, M=Pb, Sn and Cd) ultrathin porous intermetallic nanosheets (UPINs) with tunable sizes. This strategy uses preformed seeds, which act as the template to control the deposition of foreign atoms and the subsequent interatomic diffusion. Using the oxygen reduction reaction (ORR) as a model reaction, the as-synthesized Pd3 Pb UPINs exhibit superior activity, durability, and methanol tolerance. The favored geometrical structure and interatomic interaction between Pd and Pb in Pd3 Pb UPINs are concluded to account for the enhanced ORR performance.

Seomae mugwort and jaceosidin attenuate osteoarthritic cartilage damage by blocking IκB degradation in mice.

Seomae mugwort, a Korean native variety of Artemisia argyi, exhibits physiological effects against various diseases. However, its effects on osteoarthritis (OA) are unclear. In this study, a Seomae mugwort extract prevented cartilage destruction in an OA mouse model. In vitro and ex vivo analyses revealed that the extract suppressed MMP3, MMP13, ADAMTS4 and ADAMTS5 expression induced by IL-1ß, IL-6 and TNF-α and inhibited the loss of extracellular sulphated proteoglycans. In vivo analysis revealed that oral administration of the extract suppressed DMM-induced cartilage destruction. We identified jaceosidin in Seomae mugwort and showed that this compound decreased MMP3, MMP13, ADAMTS4 and ADAMTS5 expression levels, similar to the action of the Seomae mugwort extract in cultured chondrocytes. Interestingly, jaceosidin and eupatilin combined had similar effects to Seomae mugwort in the DMM-induced OA model. Induction of IκB degradation by IL-1ß was blocked by the extract and jaceosidin, whereas JNK phosphorylation was only suppressed by the extract. These results suggest that the Seomae mugwort extract and jaceosidin can attenuate cartilage destruction by suppressing MMPs, ADAMTS4/5 and the nuclear factor-κB signalling pathway by blocking IκB degradation. Thus, the findings support the potential application of Seomae mugwort, and particularly jaceosidin, as natural therapeutics for OA.

Boosting Activity and Selectivity of CO2 Electroreduction by Pre-Hydridizing Pd Nanocubes.

The electrochemical CO2 reduction reaction (CO2 RR) to syngas represents a promising solution to mitigate CO2 emissions and manufacture value-added chemicals. Palladium (Pd) has been identified as a potential candidate for syngas production via CO2 RR due to its transformation to Pd hydride under CO2 RR conditions, however, the pre-hydridized effect on the catalytic properties of Pd-based electrocatalysts has not been investigated. Herein, pre-hydridized Pd nanocubes (PdH0.40 ) supported on carbon black (PdH0.40 NCs/C) are directly prepared from a chemical reduction method. Compared with Pd nanocubes (Pd NCs/C), PdH0.40 NCs/C presented an enhanced CO2 RR performance due to its less cathodic phase transformation revealed by the in situ X-ray absorption spectroscopy. Density functional theory calculations revealed different binding energies of key reaction intermediates on PdH0.40 NCs/C and Pd NCs/C. Study of the size effect further suggests that NCs of smaller sizes show higher activity due to their more abundant active sites (edge and corner sites) for CO2 RR. The pre-hydridization and reduced NC size together lead to significantly improved activity and selectivity of CO2 RR.

Can Ensemble Deep Learning Identify People by Their Gait Using Data Collected from Multi-Modal Sensors in Their Insole?

Gait is a characteristic that has been utilized for identifying individuals. As human gait information is now able to be captured by several types of devices, many studies have proposed biometric identification methods using gait information. As research continues, the performance of this technology in terms of identification accuracy has been improved by gathering information from multi-modal sensors. However, in past studies, gait information was collected using ancillary devices while the identification accuracy was not high enough for biometric identification. In this study, we propose a deep learning-based biometric model to identify people by their gait information collected through a wearable device, namely an insole. The identification accuracy of the proposed model when utilizing multi-modal sensing is over 99%.

Cirsium japonicum var. maackii and apigenin block Hif-2α-induced osteoarthritic cartilage destruction.

Although Hif-2α is a master regulator of catabolic factor expression in osteoarthritis development, Hif-2α inhibitors remain undeveloped. The aim of this study was to determine whether Cirsium japonicum var. maackii (CJM) extract and one of its constituents, apigenin, could attenuate the Hif-2α-induced cartilage destruction implicated in osteoarthritis progression. In vitro and in vivo studies demonstrated that CJM reduced the IL-1ß-, IL-6, IL-17- and TNF-α-induced up-regulation of MMP3, MMP13, ADAMTS4, ADAMTS5 and COX-2 and blocked osteoarthritis development in a destabilization of the medial meniscus mouse model. Activation of Hif-2α, which directly up-regulates MMP3, MMP13, ADAMTS4, IL-6 and COX-2 expression, is inhibited by CJM extract. Although cirsimarin, cirsimaritin and apigenin are components of CJM and can reduce inflammation, only apigenin effectively reduced Hif-2α expression and inhibited Hif-2α-induced MMP3, MMP13, ADAMTS4, IL-6 and COX-2 expression in articular chondrocytes. IL-1ß induction of JNK phosphorylation and IκB degradation, representing a critical pathway for Hif-2α expression, was completely blocked by apigenin in a concentration-dependent manner. Collectively, these effects indicate that CJM and one of its most potent constituents, apigenin, can lead to the development of therapeutic agents for blocking osteoarthritis development as novel Hif-2α inhibitors.

Theoretical and Experimental Understanding of Hydrogen Evolution Reaction Kinetics in Alkaline Electrolytes with Pt-Based Core-Shell Nanocrystals.

The free energy of H adsorption (ΔGH) on a metallic catalyst has been taken as a descriptor to predict the hydrogen evolution reaction (HER) kinetics but has not been well applied in alkaline media. To assess this, we prepare Pd@Pt and PdH@Pt core-shell octahedra enclosed by Pt(111) facets as model catalysts for controlling the ΔGH affected by the ligand, the strain, and their ensemble effects. The Pt shell thickness is adjusted from 1 to 5 atomic layers by varying the amount of Pt precursor added during synthesis. In an alkaline electrolyte, the HER activity of core-shell models is improved either by the construction of core-shell structures or by the increased number of Pt shells. These experimental results are in good agreement with the ΔGH values calculated by the first-principles density functional theory with a complex surface strained core-shell slab model. However, enhanced HER activities of Pd@Pt and PdH@Pt core-shell nanocrystals over the Pt catalyst are inconsistent with the thermodynamic ΔGH scaling relationship only but can be explained by the work function and apparent ΔGH models that predict the interfacial electric field for the HER.

Ultrathin-Polyaniline-Coated Pt-Ni Alloy Nanooctahedra for the Electrochemical Methanol Oxidation Reaction.

Controlling the morphology and composition of nanocatalysts constructed from metals and conductive polymers has attracted attention owing to their great potential for the development of high-efficiency catalysts for various catalytic applications. Herein, a facile synthetic approach for ultrathin-polyaniline-coated Pt-Ni nanooctahedra (Pt-Ni@PANI hybrids) with controllable PANI shell thicknesses is presented. Pt-Ni nanooctahedra/C catalysts enclosed by PANI shells with thicknesses from 0.6 to 2.4 nm were obtained by fine control over the amount of aniline. The various Pt-Ni@PANI hybrids exhibited electrocatalytic activity toward the methanol oxidation reaction that is highly dependent on the thickness of the PANI shell. Pt-Ni@PANI hybrids with the thinnest PANI shells (0.6 nm) showed markedly improved electrocatalytic performance for the methanol oxidation reaction compared with Pt-Ni@PANI hybrids with thicker PANI shells, Pt-Ni nanooctahedra/C, and commercial Pt/C due to synergistic benefits of ultrathin PANI shells and Pt-Ni alloy.

Classification of Gait Type Based on Deep Learning Using Various Sensors with Smart Insole.

In this paper, we proposed a gait type classification method based on deep learning using a smart insole with various sensor arrays. We measured gait data using a pressure sensor array, an acceleration sensor array, and a gyro sensor array built into a smart insole. Features of gait pattern were then extracted using a deep convolution neural network (DCNN). In order to accomplish this, measurement data of continuous gait cycle were divided into unit steps. Pre-processing of data were then performed to remove noise followed by data normalization. A feature map was then extracted by constructing an independent DCNN for data obtained from each sensor array. Each of the feature maps was then combined to form a fully connected network for gait type classification. Experimental results for seven types of gait (walking, fast walking, running, stair climbing, stair descending, hill climbing, and hill descending) showed that the proposed method provided a high classification rate of more than 90%.

User Identification from Gait Analysis Using Multi-Modal Sensors in Smart Insole.

Recent studies indicate that individuals can be identified by their gait pattern. A number of sensors including vision, acceleration, and pressure have been used to capture humans' gait patterns, and a number of methods have been developed to recognize individuals from their gait pattern data. This study proposes a novel method of identifying individuals using null-space linear discriminant analysis on humans' gait pattern data. The gait pattern data consists of time series pressure and acceleration data measured from multi-modal sensors in a smart insole used while walking. We compare the identification accuracies from three sensing modalities, which are acceleration, pressure, and both in combination. Experimental results show that the proposed multi-modal features identify 14 participants with high accuracy over 95% from their gait pattern data of walking.

Dendrite-Embedded Platinum-Nickel Multiframes as Highly Active and Durable Electrocatalyst toward the Oxygen Reduction Reaction.

Pt-based nanoframe catalysts have been explored extensively due to their superior activity toward the oxygen reduction reaction (ORR). Herein, we report the synthesis of Pt-Ni multiframes, which exhibit the unique structure of tightly fused multiple nanoframes and reinforced by an embedded dendrite. Rapid reduction and deposition of Ni atoms on Pt-Ni nanodendrites induce the alloying/dealloying of Pt and Ni in the overall nanostructures. After chemical etching of Ni, the newly formed dendrite-embedded Pt-Ni multiframes show an electrochemically active surface area (ECSA) of 73.4 m2 gPt-1 and a mass ORR activity of 1.51 A mgPt-1 at 0.93 V, which is 30-fold higher than that of the state-of-the-art Pt/C catalyst. We suggest that high ECSA and ORR performances of dendrite-embedded Pt-Ni multiframes/C can be attributed to the porous nanostructure and numerous active sites exposed on surface grain boundaries and high-indexed facets.

Face Recognition in SSPP Problem Using Face Relighting Based on Coupled Bilinear Model.

There have been decades of research on face recognition, and the performance of many state-of-the-art face recognition algorithms under well-conditioned environments has become saturated. Accordingly, recent research efforts have focused on difficult but practical challenges. One such issue is the single sample per person (SSPP) problem, i.e., the case where only one training image of each person. While this problem is challenging because it is difficult to establish the within-class variation, working toward its solution is very practical because often only a few images of a person are available. To address the SSPP problem, we propose an efficient coupled bilinear model that generates virtual images under various illuminations using a single input image. The proposed model is inspired by the knowledge that the illuminance of an image is not sensitive to the poor quality of a subspace-based model, and it has a strong correlation to the image itself. Accordingly, a coupled bilinear model was constructed that retrieves the illuminance information from an input image. This information is then combined with the input image to estimate the texture information, from which we can generate virtual illumination conditions. The proposed method can instantly generate numerous virtual images of good quality, and these images can then be utilized to train the feature space for resolving SSPP problems. Experimental results show that the proposed method outperforms the existing algorithms.

Structural Evolution of Sub-10 nm Octahedral Platinum-Nickel Bimetallic Nanocrystals.

Octahedral Pt alloy nanocrystals (NCs) have shown excellent activities as electrocatalysts toward oxygen reduction reaction (ORR). As the activity and stability of NCs are highly dependent on their structure and the elemental distribution, it is of great importance to understand the formation mechanism of octahedral NCs and to rationally synthesize shape-controlled alloy catalysts with optimized ORR activity and stability. However, the factors controlling the structural and compositional evolution during the synthesis have not been well understood yet. Here, we systematically investigated the structure and composition evolution pathways of Pt-Ni octahedra synthesized with the assistance of W(CO)6 and revealed a unique core-shell structure consisting of a Pt core and a Pt-Ni alloy shell. Below 140 °C, sphere-like pure Pt NCs with the diameter of 3-4 nm first nucleated, followed by the isotropic growth of Pt-Ni alloy on the seeds at temperatures between 170 and 230 °C forming Pt@Pt-Ni core-shell octahedra with {111} facets. Owing to its unique structure, the Pt@Pt-Ni octahedra show an unparalleled stability during potential cycling, that is, no activity drop after 10 000 cycles between 0.6 and 1.0 V. This work proposes the Pt@Pt-Ni octahedra as a high profile electrocatalyst for ORR and reveals the structural and composition evolution pathways of Pt-based bimetallic NCs.

Minimum Interference Channel Assignment Algorithm for Multicast in a Wireless Mesh Network.

Wireless mesh networks (WMNs) have been considered as one of the key technologies for the configuration of wireless machines since they emerged. In a WMN, wireless routers provide multi-hop wireless connectivity between hosts in the network and also allow them to access the Internet via gateway devices. Wireless routers are typically equipped with multiple radios operating on different channels to increase network throughput. Multicast is a form of communication that delivers data from a source to a set of destinations simultaneously. It is used in a number of applications, such as distributed games, distance education, and video conferencing. In this study, we address a channel assignment problem for multicast in multi-radio multi-channel WMNs. In a multi-radio multi-channel WMN, two nearby nodes will interfere with each other and cause a throughput decrease when they transmit on the same channel. Thus, an important goal for multicast channel assignment is to reduce the interference among networked devices. We have developed a minimum interference channel assignment (MICA) algorithm for multicast that accurately models the interference relationship between pairs of multicast tree nodes using the concept of the interference factor and assigns channels to tree nodes to minimize interference within the multicast tree. Simulation results show that MICA achieves higher throughput and lower end-to-end packet delay compared with an existing channel assignment algorithm named multi-channel multicast (MCM). In addition, MICA achieves much lower throughput variation among the destination nodes than MCM.

Ultrathin Free-Standing Ternary-Alloy Nanosheets.

A synthesis strategy for the preparation of ultrathin free-standing ternary-alloy nanosheets is reported. Ultrathin Pd-Pt-Ag nanosheets with a thickness of approximately 3 nm were successfully prepared by co-reduction of the metal precursors in an appropriate molar ratio in the presence of CO. Both the presence of CO and the interplay between the constituent metals provide fine control over the anisotropic two-dimensional growth of the ternary-alloy nanostructure. The prepared Pd-Pt-Ag nanosheets were superior catalysts of ethanol electrooxidation owing to their specific structural and compositional characteristics. This approach will pave the way for the design of multicomponent 2D nanomaterials with unprecedented functions.

Impact of an electronic consultant system on hypersensitivity reactions to iodinated radiocontrast media: an observational study.

OBJECTIVE: To evaluate the impact of an electronic consultation support system on the incidence of hypersensitivity reactions to iodinated radiocontrast media (RCM). MATERIALS AND METHODS: A retrospective observational study was conducted before and after the introduction of the consultation support system. The 1-year study period was divided into two 6-month periods: before and after 1 December 2012 (baseline and intervention periods, respectively), which was when our consultation support system was introduced. Data from examinations were collected retrospectively from the hospital information centre and problem reporting sheets in the radiology department. The primary outcome was the incidence of RCM reactions before and after the introduction of the consultation support system. Generalised estimating equations were used to account for the correlation between the same patients measured on multiple occasions. RESULTS: There were 317/20,179 (1.6%) and 186/19,873 (0.9%) hypersensitivity reactions during the baseline and intervention periods, respectively. The consultation support system significantly decreased the odds of the occurrence of a RCM reaction (OR=0.59, 95% CI 0.49 to 0.71, p<0.001) compared with baseline. There was also a twofold increase in the premedication rate after initiation of the consultation support system (OR=2.05, 95% CI 1.16 to 3.65 p=0.01). However, there was no significant difference in the recurrence rate between the periods (OR=0.97, 95% CI 0.58 to 1.65, p<0.93). CONCLUSIONS: The introduction of the consultation support system reduced the incidence of hypersensitivity reactions to RCM and increased the use of premedication in patients with known hypersensitivity to RCM.

Atomic layer-by-layer deposition of Pt on Pd nanocubes for catalysts with enhanced activity and durability toward oxygen reduction.

An effective strategy for reducing the Pt content while retaining the activity of a Pt-based catalyst is to deposit the Pt atoms as ultrathin skins of only a few atomic layers thick on nanoscale substrates made of another metal. During deposition, however, the Pt atoms often take an island growth mode because of a strong bonding between Pt atoms. Here we report a versatile route to the conformal deposition of Pt as uniform, ultrathin shells on Pd nanocubes in a solution phase. The introduction of the Pt precursor at a relatively slow rate and high temperature allowed the deposited Pt atoms to spread across the entire surface of a Pd nanocube to generate a uniform shell. The thickness of the Pt shell could be controlled from one to six atomic layers by varying the amount of Pt precursor added into the system. Compared to a commercial Pt/C catalyst, the Pd@PtnL (n = 1-6) core-shell nanocubes showed enhancements in specific activity and durability toward the oxygen reduction reaction (ORR). Density functional theory (DFT) calculations on model (100) surfaces suggest that the enhancement in specific activity can be attributed to the weakening of OH binding through ligand and strain effects, which, in turn, increases the rate of OH hydrogenation. A volcano-type relationship between the ORR specific activity and the number of Pt atomic layers was derived, in good agreement with the experimental results. Both theoretical and experimental studies indicate that the ORR specific activity was maximized for the catalysts based on Pd@Pt2-3L nanocubes. Because of the reduction in Pt content used and the enhancement in specific activity, the Pd@Pt1L nanocubes showed a Pt mass activity with almost three-fold enhancement relative to the Pt/C catalyst.