Porous Carbon Foam with Carbon Nanotubes as Cathode for Li-CO2 Batteries.

With the extensive use of fossil fuels, the ever-increasing greenhouse gas of mainly carbon dioxide emissions will result in global climate change. It is of utmost importance to reduce carbon dioxide emissions and its utilization. Li-CO2 batteries can convert carbon dioxide into electrochemical energy. However, developing efficient catalysts for the decomposition of Li2 CO3 as the discharge product represents a challenge in Li-CO2 batteries. Herein, we demonstrate a carbon foam composite with growing carbon nanotube by using cobalt as the catalyst, showing the ability to enhance the decomposition rate of Li2 CO3 , and thus improve the electrochemical performance of Li-CO2 batteries. Benefiting from its abundant pore structure and catalytic sites, the as-assembled Li-CO2 battery exhibits a desirable overpotential of 1.67 V after 50 cycles. Moreover, the overpotentials are 1.05 and 2.38 V at current densities of 0.02 and 0.20 mA cm-2 , respectively. These results provide a new avenue for the development of efficient catalysts for Li-CO2 batteries.

High-performance formaldehyde gas-sensors based on three dimensional center-hollow ZnO.

Three dimensional (3D) center-hollow ZnO architectures assembled by nanoparticles have been successfully fabricated on a large scale via a template-free method using an oil bath. The samples were characterized by X-ray diffraction, scanning electron microscopy, transmission electron microscopy, Brunauer-Emmett-Teller specific surface area, surface photocurrent and UV-Vis diffuse reflectance spectroscopy. The photoelectric gas-sensing results demonstrated that the 3D porous, center-hollow ZnO structures exhibited excellent sensitivity and good selectivity to formaldehyde under 365 nm light irradiation at room temperature. The gas response to 1 ppm formaldehyde can reach 70%, which is superior to the results reported in the literature, indicating that the 3D center-hollow ZnO architectures are ideal candidate materials for photoelectric gas sensors. The underlying mechanisms responsible for the high sensitivity and selectivity to formaldehyde are discussed, which provide a new pathway for designing novel VOC sensors. Moreover, the facile method presented in this paper has the advantage of low-cost and high-yield, which is suitable for the practical production processes.

Self-assembled dendrimer polyamide nanofilms with enhanced effective pore area for ion separation.

Membrane technology using well-defined pore structure can achieve high ion purity and recovery. However, fine-tuning the inner pore structure of the separation nanofilm to be uniform and enhance the effective pore area is still challenging. Here, we report dendrimers with different peripheral groups that preferentially self-assemble in aqueous-phase amine solution to facilitate the formation of polyamide nanofilms with a well-defined effective pore range and uniform pore structure. The high permeabilities are maintained by forming asymmetric hollow nanostripe nanofilms, and their well-designed ion effective separation pore ranges show an enhancement, rationalized by molecular simulation. The self-assembled dendrimer polyamide membrane provides Cl-/SO42- selectivity more than 17 times that of its pristine polyamide counterparts, increasing from 167.9 to 2883.0. Furthermore, the designed membranes achieve higher Li purity and Li recovery compared to current state-of-the-art membranes. Such an approach provides a scalable strategy to fine-tune subnanometre structures in ion separation nanofilms.

Epoch-Evolving Gaussian Process Guided Learning for Classification.

The conventional mini-batch gradient descent algorithms are usually trapped in the local batch-level distribution information, resulting in the ``zig-zag'' effect in the learning process. To characterize the correlation information between the batch-level distribution and the global data distribution, we propose a novel learning scheme called epoch-evolving Gaussian process guided learning (GPGL) to encode the global data distribution information in a non-parametric way. Upon a set of class-aware anchor samples, our GP model is built to estimate the class distribution for each sample in mini-batch through label propagation from the anchor samples to the batch samples. The class distribution, also named the context label, is provided as a complement for the ground-truth one-hot label. Such a class distribution structure has a smooth property and usually carries a rich body of contextual information that is capable of speeding up the convergence process. With the guidance of the context label and ground-truth label, the GPGL scheme provides a more efficient optimization through updating the model parameters with a triangle consistency loss. Furthermore, our GPGL scheme can be generalized and naturally applied to the current deep models, outperforming the state-of-the-art optimization methods on six benchmark datasets.

The Impact of Qigong and Tai Chi Exercise on Drug Addiction: A Systematic Review and Meta-Analysis.

Background: Previous preliminary studies have found that qigong exercises produced significant effects in healthy people and in various clinical populations. The purpose of this study was to systematically review the effects of qigong and tai chi exercise on individuals with drug addiction. Methods: A systematic search of seven English databases and three Chinese databases was conducted to identify randomized controlled trials (RCTs) and non-randomized comparative studies (NRS) assessing the effects of qigong and tai chi on drug addiction. Study quality was assessed using the Checklist for the Evaluation of Non-Pharmaceutical Trial Reports (CLEAR-NPT). Results: Two RCTs and nine NRS studies were included in this study, including a total of 1072 patients with drug addiction (age range, 27-43 years). The results showed that qigong and tai chi exercise had a significant overall effect on depression (SMD = -0.353, 95%CI [-0.548, -0.159]), anxiety (SMD = -0.541, 95%CI [-0.818, -0.264]), quality of life (SMD = 0.673, 95%CI [0.438, 0.907]), and sleep quality (SMD = -0.373, 95%CI [-0.631, -0.116]). The subgroup analysis found that qigong outperformed tai chi on the improving depression, anxiety, and sleep quality. Conclusion: Existing studies suggest that qigong and tai chi are effective at improving depression, anxiety, and quality of life in drug users; however, the evidence from rigorous randomized controlled group trials is lacking.

Multitask Identity-Aware Image Steganography via Minimax Optimization.

High-capacity image steganography, aimed at concealing a secret image in a cover image, is a technique to preserve sensitive data, e.g., faces and fingerprints. Previous methods focus on the security during transmission and subsequently run a risk of privacy leakage after the restoration of secret images at the receiving end. To address this issue, we propose a framework, called Multitask Identity-Aware Image Steganography (MIAIS), to achieve direct recognition on container images without restoring secret images. The key issue of the direct recognition is to preserve identity information of secret images into container images and make container images look similar to cover images at the same time. Thus, we introduce a simple content loss to preserve the identity information, and design a minimax optimization to deal with the contradictory aspects. We demonstrate that the robustness results can be transferred across different cover datasets. In order to be flexible for the secret image restoration in some cases, we incorporate an optional restoration network into our method, providing a multitask framework. The experiments under the multitask scenario show the effectiveness of our framework compared with other visual information hiding methods and state-of-the-art high-capacity image steganography methods. The code is available at https://github.com/jiabaocui/MIAIS.

The Effects of Tai Chi and Qigong Exercise on Psychological Status in Adolescents: A Systematic Review and Meta-Analysis.

Background: The purpose of this study was to systematically review the effectiveness of Tai Chi and Qigong exercise on adolescents' symptoms of depression and anxiety, and psychological status based on clinical evidences, and to calculate the pooled results using meta-analysis. Methods: A systematic search using seven English and three Chinese databases was initiated to identify randomized controlled trials (RCT) and non-randomized comparison studies (NRS) assessing the effect of Tai Chi and Qigong exercise on psychological status among adolescents. Standardized mean differences (SMD) and their 95% confidence intervals (CI) were used to determine the pooled effect of the intervention. Study quality was evaluated using a Checklist to Evaluate a Report of a Non-pharmacological Trial (CLEAR-NPT) designed for non-pharmacological trials. Results: Four RCTs and six NRS were identified, including 1,244 adolescents. The results suggested a potential beneficial effect of Tai chi and Qigong exercise on reducing anxiety (SMD = 0.386, 95 CI% [0.233, 0.538]) and depression (SMD = 1.937 [95 CI%, 1.392-2.546]) symptoms, and reducing cortisol level (SMD = 0.621 [95 CI%, 0.18-1.062]) in adolescents. Conversely, non-significant effects were found for stress, mood, and self-esteem. Conclusions: The findings of this review suggest Qigong appears to be an effective therapeutic modality to improve psychological well-being in adolescents. Hope future studies will have rigorously designed, well-controlled randomized trials with large sample sizes in order to confirm these findings.

Efficient Style-Corpus Constrained Learning for Photorealistic Style Transfer.

Photorealistic style transfer is a challenging task, which demands the stylized image remains real. Existing methods are still suffering from unrealistic artifacts and heavy computational cost. In this paper, we propose a novel Style-Corpus Constrained Learning (SCCL) scheme to address these issues. The style-corpus with the style-specific and style-agnostic characteristics simultaneously is proposed to constrain the stylized image with the style consistency among different samples, which improves photorealism of stylization output. By using adversarial distillation learning strategy, a simple fast-to-execute network is trained to substitute previous complex feature transforms models, which reduces the computational cost significantly. Experiments demonstrate that our method produces rich-detailed photorealistic images, with 13 ~ 50 times faster than the state-of-the-art method (WCT2).

Asymmetric polyamide nanofilms with highly ordered nanovoids for water purification.

Tailor-made structure and morphology are critical to the highly permeable and selective polyamide membranes used for water purification. Here we report an asymmetric polyamide nanofilm having a two-layer structure, in which the lower is a spherical polyamide dendrimer porous layer, and the upper is a polyamide dense layer with highly ordered nanovoids structure. The dendrimer porous layer was covalently assembled in situ on the surface of the polysulfone (PSF) support by a diazotization-coupling reaction, and then the asymmetric polyamide nanofilm with highly ordered hollow nanostrips structure was formed by interfacial polymerization (IP) thereon. Tuning the number of the spherical dendrimer porous layers and IP time enabled control of the nanostrips morphology in the polyamide nanofilm. The asymmetric polyamide membrane exhibits a water flux of 3.7-4.3 times that of the traditional monolayer polyamide membrane, showing an improved divalent salt rejection rate (more than 99%), which thus surpasses the upper bound line of the permeability-selectivity performance of the existing various structural polyamide membranes. We estimate that this work might inspire the preparation of highly permeable and selective reverse osmosis (RO), organic solvent nanofiltration (OSNF) and pervaporation (PV) membranes.

The effect of tai chi and Qigong exercise on depression and anxiety of individuals with substance use disorders: a systematic review and meta-analysis.

BACKGROUND: Previous studies have acknowledged Tai Chi and Qigong exercise could be potential effective treatments for reducing depression and anxiety in both healthy and clinical populations. However, there is a scarcity of systematic reviews summarizing the clinical evidence conducted among individuals with substance use disorders. This study tries to fill up this gap. METHODS: A systematic search using Medline, EMbase, PsychINFO, Eric, SPORTDiscus, CINAHL, the Cochrane Central Register of Controlled Trials (CENTRAL), the Chinese National Knowledge Infrastructure (CNKI), Wanfang, and the Chinese Scientific Journal (VIP) databases was initiated to identify randomized controlled trials (RCTs) and non-randomized comparison studies (NRS) assessing the effect of Tai Chi and Qigong versus various comparison groups on depression and anxiety related outcomes. Study quality was evaluated using a Checklist to Evaluate a Report of a Nonpharmacological Trial (CLEAR-NPT) designed for nonpharmacological trial. RESULTS: One RCT and six NRS with a total of 772 participants were identified. Some of them were meta-analyzed to examine the pooled effects based on different types of intervention and controls. The results of meta-analyses suggested the effect of Tai Chi was comparable to treatment as usual (TAU) on depression (standardized mean difference (SMD) = - 0.17[- 0.52, 0.17]). Qigong exercise appears to result in improvement on anxiety compared to that of medication (SMD = -1.12[- 1.47, - 0.78]), and no treatment control (SMD = -0.52[- 0.77, - 0.27]). CONCLUSION: The findings suggest potentially beneficial effect of Qigong exercise on symptoms of anxiety among individuals with drug abuse. Considering the small number and overall methodological weakness of included studies and lack of RCTs, results should be interpreted with caution and future rigorously designed RCTs are warranted to provide more reliable evidence.

Dao Yin (a.k.a. Qigong): Origin, Development, Potential Mechanisms, and Clinical Applications.

Dao Yin is a form of exercise combining physical movements, mental focus, and breathing originated in ancient China. In this review, we introduce the history in the development and the scope of Dao Yin, the relationship between Dao Yin with Taoist culture and Qigong, and the potential mechanisms of how Dao Yin promotes health and alleviate illnesses. Empirical research studies using Dao Yin for treatment of lumbar spondylosis, peripheral musculoskeletal diseases, cervical spondylosis, heart diseases, central nervous system disorders, immunological dysfunction, and psychological disorders are detailed.

Prussian blue coupling with zinc oxide as a protective layer: an efficient cathode for high-rate sodium-ion batteries.

Prussian blue coupled with zinc oxide has been synthesized via a facial heat treatment process. As a cathode for sodium ion batteries, the PB coupled with ZnO delivers an excellent rate performance, retaining 86.2 mA h g-1 at 10 A g-1 and a high reversible capacity of 89.9 mA h g-1 at 0.2 A g-1 after 500 cycles.

High-Performance Photoelectronic Sensor Using Mesostructured ZnO Nanowires.

Semiconductor photoelectrodes that simultaneously possess rapid charge transport and high surface area are highly desirable for efficient charge generation and collection in photoelectrochemical devices. Herein, we report mesostructured ZnO nanowires (NWs) that not only demonstrate a surface area as high as 50.7 m2/g, comparable to that of conventional nanoparticles (NPs), but also exhibit a 100 times faster electron transport rate than that in NP films. Moreover, using the comparison between NWs and NPs as an exploratory platform, we show that the synergistic effect between rapid charge transport and high surface area leads to a high performance photoelectronic formaldehyde sensor that exhibits a detection limit of as low as 5 ppb and a response of 1223% (at 10 ppm), which are, respectively, over 100 times lower and 20 times higher than those of conventional NPs-based device. Our work establishes a foundational pathway toward a better photoelectronic system by materials design.