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This study presents a detailed review on the ultrathin catalyst layer (UTCL) design strategy for high-performance proton exchange membrane fuel cell (PEMFC). Specifically, the motivation towards the further reduced Pt loadings by applying the UTCL electrode design is firstly introduced from both the historical and mechanism deductions. Then, the recent developments on the UTCL designs belonging to different classifications are summarized with their respective merits. In particular, the critical issues remained on these ultra-thin, low Pt-loaded electrodes are proposed with alternative solutions. Finally, the whole review is concluded with the perspectives on the possible future directions settling the remaining challenges.

The possibility of utilizing quantum effects to enhance the performance of quantum heat engines has been an active topic of research, but how to enhance the performance by optimizing the engine parameters needs to be further studied. In this study, the temperature difference and dissipation modes affecting the performance of a three-level quantum heat engine were analyzed using an orthogonal test. The results indicated that the dissipation mode dominated the performance of the quantum heat engine. The quantum heat engine performs best when there is only resonance and no detuning; however, when detuning exists, a lower resonance can improve the efficiency by reducing energy losses. Regarding the temperature difference, the best performance was achieved at a medium temperature difference owing to the decreasing heat leakage. Finally, the “quantum friction” caused by the detuning could make the maximal efficiency lower than the Carnot efficiency.

Plastic pollution is a global concern and an issue in environmental governance. Based on the updated "Plastic Prohibition/Restriction Order" issued recently in China, the present study systematically reviewed the implementation effectiveness of the "Plastic Prohibition/Restriction Order" since 2007. Furthermore, we summarized plastics in China and plastic waste management progress policies. Additionally, three deficiencies of the updated "Plastic Prohibition/Restriction Order" were discussed:policy formulation, implementation, and supervision. Some positive recommendations were provided based on the available reports, such as integrating plastic pollution into national basic laws and regulation systems, building a network platform for public attendance, and coordinating the publicity of the "Plastic prohibition/Restriction Order" with the public interest. Besides these measurements, some points about plastic waste management in the future were also highlighted, such as the "blind area" in small retail stores, the rational sharing of environmental protection responsibility, new materials and processes, and recycling and disposal systems for plastic wastes. Most importantly, the present study could provide ideas for policy-makers to address plastic pollution at its sources.

Summary Interfacial engineering has been commonly used as an effective strategy to enhance device performance and stability of perovskite solar cells (PSCs). However, most of the materials used for interface engineering are based on organics, which may have concerns for the device's long-term stability. Therefore, we developed robust fluoro-terminated TiO2 nanosheets (F-TiO2 NSs) to work as interlayers between perovskite and electron-transporting layers in inverted PSCs. The flat NS morphology of F-TiO2 NSs enables close contact with perovskite with abundant surface fluoro groups, which can interact with undercoordinated lead and MA/FA ions to prevent the formation of cation vacancies and alleviate surface defects. As a result, a remarkable power conversion efficiency (PCE) of 22.86% can be achieved. The operational stability of devices with F-TiO2 NSs interlayers is also enhanced, which can maintain over 90% of their initial PCEs after being monitored at the maximum power point (MPP) for 1,000 h under day/night cycles.

The rapid development of synthesis and fabrication techniques has opened up a research upsurge in two-dimensional (2D) material heterostructures, which have received extensive attention due to their superior physical and chemical properties. Currently, thermoelectric energy conversion is an effective means to deal with the energy crisis and increasingly serious environmental pollution. Therefore, an in-depth understanding of thermoelectric transport properties in 2D heterostructures is crucial for the development of micro-nano energy devices. In this review, the recent progress of 2D heterostructures for thermoelectric applications is summarized in detail. Firstly, we systematically introduce diverse theoretical simulations and experimental measurements of the thermoelectric properties of 2D heterostructures. Then, the thermoelectric applications and performance regulation of several common 2D materials, as well as in-plane heterostructures and van der Waals heterostructures, are also discussed. Finally, the challenges of improving the thermoelectric performance of 2D heterostructures materials are summarized, and related prospects are described.

PurposeThe calculation of buildings’ carbon footprint (CFP) is an important basis for formulating energy-saving and emission-reduction plans for building. As an important building type, there is currently no model that considers the time factor to accurately calculate the CFP of hospital building throughout their life cycle. This paper aims to establish a CFP calculation model that covers the life cycle of hospital building and considers time factor.Design/methodology/approachOn the basis of field and literature research, the basic framework is built using dynamic life cycle assessment (DLCA), and the gray prediction model is used to predict the future value. Finally, a CFP model covering the whole life cycle has been constructed and applied to a hospital building in China.FindingsThe results applied to the case show that the CO2 emission in the operation stage of the hospital building is much higher than that in other stages, and the total CO2 emission in the dynamic and static analysis operation stage accounts for 83.66% and 79.03%, respectively; the difference of annual average emission of CO2 reached 28.33%. The research results show that DLCA is more accurate than traditional static life cycle assessment (LCA) when measuring long-term objects such as carbon emissions in the whole life cycle of hospital building.Originality/valueThis research established a carbon emission calculation model that covers the life cycle of hospital building and considered time factor, which enriches the research on carbon emission of hospital building, a special and extensive public building, and dynamically quantifies the resource consumption of hospital building in the life cycle. This paper provided a certain reference for the green design, energy saving, emission reduction and efficient use of hospital building, obviously, the limitation is that this model is only applicable to hospital building.

To accurately count densely stacked rebars belongs to semantic segmentation in image. Various methods have been proposed to segment the objects in single image. However, widely and densely stacking scene such as warehouse or vehicle stacking of rebars is always faced. For these scenes, clear image of end faces of rebars cannot be obtained through a single camera. Generally, multiple cameras are often used to take clear images to count rebars. One strategy is to stitch multiple images into a single image at pixel level first, and then count rebars in this stitched image. Various methods have been proposed to stitch images, but it is extremely difficult to stitch two images at pixel level accurately for parallax distortion or partially hidden. A topological stitching strategy is proposed in this paper to count the rebars in whole scene. In the method, rebars in each image are identified and counted first, and then the identification and counting results in the adjacent images are stitched so as to esitmate the total number of rebars. The perfomance of the method is evaluated on real datasets, and the counting accuracy exceeds 99%. Experiments show that the proposed method is effective on widely and densely stacked rebars identification.

This article aims at the evaluation and improvement of the development of higher education. First of all, according to the theory and hypothesis, the comprehensive evaluation index system of higher education development level is established. The TOPSIS and the combination weighting method based on goal programming are used to measure the scores of higher education development levels of 19 major countries in the world in the recent 20 years, and the horizontal and vertical comparative analysis is carried out. Then, according to the practical feasibility, Turkey is selected as the target country to propose a higher education development and improvement policy by 2030, and the causal effect of our proposed policy is estimated using the synthetic control method. This study can provide a reference for other countries in the world to improve their higher education level.

The impact of policy uncertainty on China’s economic activity has received considerable attention. To appraise the role of economic policy uncertainty (EPU) in China’s economic downturns, we estimate the predictive distribution of China’s GDP growth as a function of EPU from 1996Q1 to 2020Q2, using quantile regression and fitted skew-t distribution. We find that the entire predicted distribution of GDP growth conditional on the EPU index evolves over time beyond the central tendency. The EPU index alters the predicted distribution’s higher moments, amplifies the growth tail risk, and improves the model’s forecast performance; this could serve as a basis for preemptive action. Our results are robust across other alternative output and EPU variables.

Highly active catalysts with promising water retention are favorable for proton exchange membrane fuel cells (PEMFCs) operating under low-humidity/high-temperature conditions. When PEMFCs operate under low-humidity/high-temperature conditions, performance attenuation rapidly occurs owing to reduced proton conductivity of dehydrated membrane electrode assemblies. Herein, we load platinum onto a perovskite-carbon joint substrate (BaZr

Cancer researchers often seek user-friendly interactive tools for validation, exploration, analysis, and visualization of molecular profiles in cancer patient samples. To aid researchers working on both low-and high-grade gliomas, we developed Glioma-BioDP, a web tool for exploration and visualization of RNA and protein expression profiles of interest in these tumor types. Glioma-BioDP is an extended version of our earlier published tool GBM-BioDP. In this version we have included expression data from both the low-and high-grade glioma patient samples from The Cancer Genome Atlas and enabled querying by mRNA, microRNA, and protein level expression data from Illumina HiSeq and RPPA platforms respectively. Glioma-BioDP enables users to explore the association of genes, proteins, and miRNA expression with molecular and/or histological subtypes of gliomas, surgical resection status and survival. The prognostic significance and visualization of the selected expression profiles can be explored using interactive utilities provided. This tool also enables potential validation and generation of new hypotheses of novel therapies impacting gliomas that aid in personalization of treatment for optimum outcomes.AvailabilityGlioma-BioDP web tool with user manual is available from: https://glioma-biodp.nci.nih.gov Contact: uma@mail.nih.gov

Polyhydroxyalkanoates (PHAs) have been reported with agricultural and medical applications in virtue of their biodegradable and biocompatible properties. Here, we systematically engineered three modules for the enhanced biosynthesis of medium-chain-length polyhydroxyalkanoate (mcl-PHA) in Pseudomonas chlororaphis HT66. The phzE, fadA, and fadB genes were deleted to block the native phenazine pathway and weaken the fatty acid β-oxidation pathway. Additionally, a PHA depolymerase gene phaZ was knocked out to prevent the degradation of mcl-PHA. Three genes involved in the mcl-PHA biosynthesis pathway were co-overexpressed to increase carbon flux. The engineered strain HT4Δ::C1C2J exhibited an 18.2 g/L cell dry weight with 84.9 wt % of mcl-PHA in a shake-flask culture, and the 3-hydroxydodecanoate (3HDD) monomer was increased to 71.6 mol %. Thermophysical and mechanical properties of mcl-PHA were improved with an enriched ratio of 3HDD. This study demonstrated a rational metabolic engineering approach to enhance the production of mcl-PHA with the enriched dominant monomer and improved material properties.

Quantum many-body systems in which time-reversal symmetry is broken give rise to a wealth of exotic phases, and thus constitute one of the frontiers of modern condensed matter physics. Quantum simulation allows us to better understand many-body systems with huge Hilbert space, where classical simulation is usually inefficient. With superconducting quantum circuit as a platform for quantum simulation, we realize synthetic Abelian gauge fields by using microwave drive and tunable coupling in loop configurations to break the time-reversal symmetry of the system. Based on high-precision manipulation and readout of circuit-QED architecture, we demonstrate the chiral ground spin current of a time-reversal symmetry broken system with nontrivial interactions. Our work is a significant attempt to simulate quantum many-body systems with time-reversal symmetry breaking in multi-qubit superconducting processors.

Understanding the mechanisms of biological invasion is critical to biodiversity protection. Previous studies have produced inconsistent relationships between native species richness and invasibility, referred to as the invasion paradox. Although facilitative interactions among species have been proposed to explain the non-negative diversity–invasibility relationship, little is known about the facilitation of plant-associated microbes in invasions. We established a two-year field biodiversity experiment with a native plant species richness gradient (1, 2, 4, or 8 species) and analyzed the effects of community structure and network complexity of leaf bacteria on invasion success. Our results indicated a positive relationship between invasibility and network complexity of leaf bacteria of the invader. Consistent with previous studies, we also found that native plant species richness increased the leaf bacterial diversity and network complexity. Moreover, the results of the leaf bacteria community assembly of the invader suggested that the complex bacteria community resulted from higher native diversity rather than higher invader biomass. We concluded that increased leaf bacterial network complexity along the native plant diversity gradient likely facilitated plant invasion. Our findings provided evidence of a potential mechanism by which microbes may affect the plant community invasibility, hopefully helping to explain the non-negative relationship between native diversity and invasibility.

Natural phenazines are a class of multifunctional secondary metabolites of bacteria that play an important role in the biocontrol of plant pathogens. In this paper, a novel bioactive phenazine derivative was isolated from Streptomyces lomondensis S015 through silica gel chromatography and preparative high-performance liquid chromatography (HPLC). The structure was identified as 1-carboxyl-6-formyl-4,7,9-trihydroxy-phenazine (CFTHP) by NMR spectroscopy in combination with ultraperformance liquid chromatography & mass spectrometry (UPLC-MS). CFTHP could inhibit Pythium ultimum, Rhizoctonia solani, Septoria steviae, and Fusarium oxysporum f. sp. niveum with minimal inhibitory concentration (MIC) values of 16, 32, 16, and 16 μg/mL, respectively. A global regulatory gene phoP could positively regulate CFTHP biosynthesis since its production was 3.0-fold enhanced by phoP overexpression and inhibited by phoP deletion in Streptomyces lomondensis S015. These studies illustrated the potential of CFTHP as a promising biopesticide and provided a reference for phenazine production improvement.

Herein, an original and divergent synthetic method for fluorinated 2-benzylated indoles and 2,2′-bis(indolyl)methanes has been established for the first time via Rh(III)-catalyzed C–H/C–F activation of arenes employing 3,3-difluoro-2-exo-methylidene indolines as novel cross-coupling partners. This redox-neutral protocol exhibited a broad substrate scope (30 examples, up to 97% yield) and high functional-group compatibility. Gram-scale and mechanistic studies were also performed.

Background: Huangqi Guizhi Wuwu decoction (HQGZWW) exhibits good effects when administered to treat multiple sclerosis (MS) and its animal model, experimental autoimmune encephalomyelitis (EAE). Understanding the precise mechanism of this decoction is thus important. Based on the findings of our previous study, the aim of the present study was to understand the role of antigen-specific CD8+ T-cells on the pathogenesis of MS/EAE when HQGZWW is administered as treatment. Methods: Myelin oligodendrocyte glycoprotein (MOG) 35-55-induced mice were administered distilled water, prednisone, and high dose or low dose HQGZWW. After purified CD4+ and CD8+ T-cells were stimulated with the MOG35-55 peptide, proliferation and cytokine secretion assays were performed. To establish the adoptive transfer EAE model, naive mice were injected with MOG35-55 -CD8+ or CD4+ T-cells. Results: Significant improvements in EAE score and pathology were observed in the high dose HQGZWW and prednisone groups. Compared to the low dose HQGZWW and distilled water groups, lower antigen-specific responses, lower levels of interferon-gamma, and higher levels of interleukin (IL)-4 and IL-10 from CD8+ and CD4+ T cells were observed in the high dose HQGZWW and prednisone groups. Finally, the EAE score was observed to be similar between the high dose HQGZWW group and prednisone group; however, this finding was not observed in the low dose HQGZWW group. Conclusion: Our findings suggest that high dose HQGZWW has similar effects on cell proliferation, cytokine secretion, and EAE score to prednisone, while low dose HQGZWW does not have such effect. The protective role of HQGZWW against EAE might thus depend on the Th2 cytokine secretion profile induced by either MOG35-55 specific CD8+ or CD4+ T-cells.

Herein, highly efficient electrochemiluminescence (ECL) of novel Au–Ag bimetallic nanocluster @CNTs–TiO2 nanocomposites (Au–Ag NCs@CNTs–TiO2 NPs) with a unique “pearl necklace” structure was achieved. An ECL immunosensor was fabricated for simple, label-free and ultra-sensitive detection of cancer embryo antigen (CEA). The functionalized CNTs–TiO2 was used as a light-emitting carrier of Au–Ag NCs, TiO2 NPs were used as the co-reaction accelerator and dissolved O2 as the intrinsic co-reactant for the in situ generation of the strong oxidizing intermediate radical OH˙. OH˙ significantly influenced the ECL properties of metal NCs. Carbon nanotubes (CNTs) acted as conductors, enabling faster electron transfer and more effective energy transmission in the Au–Ag NCs@CNTs–TiO2 NP nanostructure. Compared with the ECL of pure Ag NCs, the ECL of Au–Ag NCs on the TiO2 NP surface was significantly enhanced due to the synergistic effect of bimetallic NCs. The experimental results showed that Au–Ag NCs@CNTs–TiO2 NPs achieved excellent ECL performance, and decreased the detection limit of the immunosensor for measuring CEA to 0.03 pg mL−1 in the absence of any additional signal amplification assay. The proposed ECL immunosensor is expected to be promising for applications in diagnostics and bioanalysis using other biomolecules.

Currently, the most popular image feature learning method is deep neural network, which can automatically extract efficient features through feature learning for tasks such as classification and recognition without human involvement. However, the deep neural network image feature extraction method currently faces many challenges. Its effectiveness relies heavily on large data, and it is usually regarded as a black box model with poor interpretability. Aiming at the above challenges, a more interpretable and scalable feature learning method, multi-grained fusion image feature learning with fuzzy rule system, is proposed in the paper. The method is based on Takagi-Sugeno-Kang fuzzy system (TSK-FS) with fuzzy rule inference. This method extracts image features through rule-based TSK-FS, so the feature learning process can be explained by rules. Then, multi-granularity scanning also further enhances its feature learning ability. Extensive experiments have been conducted on image datasets of different scales, and the results show the proposed method is effective on image datasets.

An efficient oxygen reduction reaction (ORR) can be achieved by accelerating the movement of electrons, ions, reactants, and products. Here, we prepared core–shell nanohybrids with Fe0.8Zn0.2 nanop...

Objective: Polycystic ovary syndrome (PCOS), a common endocrine-metabolic dysfunction in reproductive-aged women, may be involved in compromised pregnancy and offspring outcomes. This study aimed to investigate whether maternal PCOS affects fetal growth, fetal development, and placental features. Methods: This retrospective case-control study included 60 pregnant women with PCOS (PCOS group) and 120 healthy pregnant women without PCOS (control group). Fetal magnetic resonance imaging (MRI) was performed followed by an ultrasound examination and indications for imaging, including known or suspected fetal pathology, history of fetal abnormality in previous pregnancy or in a family member, and concern for placenta accreta. Fetal MRI images were analyzed for head circumference (HC), abdomen circumference (AC), lung-to-liver signal intensity ratio (LLSIR, a prenatal marker of fetal lung maturity), lengths of liver and kidney diameters in fetuses, and placental relative signal intensity on T2-weighted single-shot fast spin echo (SSFSE) imaging (rSI(SSFSE)), and placental relative apparent diffusion coefficient value (rADC). Data on height and weight of offspring were collected through telephone follow-up. Results: Compared to the control group, the PCOS group showed the following characteristics: (1) smaller biparietal diameter and femur length in fetuses (P=0.026 and P=0.005, respectively), (2) smaller HC in fetuses (evident after 32 weeks; P=0.044), (3) lower LLSIR and smaller dorsoventral length of liver in fetuses (evident before 32 weeks; P=0.005 and P=0.019, respectively), and (4) smaller placental thickness (evident before 32 weeks; P=0.017). No significant differences in placental rSI(SSFSE) or rADC were observed between the groups (all P>0.05). No significant differences in height and weight of offspring during childhood existed between the groups (all P>0.05). Conclusions: There exist alterations of fetal growth, fetal development, and placental features from women with PCOS.

Two-dimensional materials with intrinsic long-range ordered magnetic moments have drawn a lot of attention. However, for practical applications, whether or not the magnetism is stable in their nanostructures has not been revealed. Here, based on the recently proposed magnetic penta-hexa-graphene, we study the electronic and magnetic properties of its nanoribbons (named PHGNRs). The results show that the PHGNRs have intrinsic robust magnetic moments that are different from zigzag graphene nanoribbons, where the magnetic moments caused by the edge effect are vulnerable. Moreover, the magnetic ground states, namely, ferromagnetic (FM) or antiferromagnetic (AFM), can be transformed by changing the width of PHGNRs. Most interestingly, under the FM ground state, the spin-polarized electronic properties reveal that the zigzag PHGNRs transform from spin-gapless semiconductors (SGSs) to half-metals, as the width of nanoribbons increases, while all the armchair PHGNRs are magnetic semiconductors. Furthermore, by considering different edge effects caused by the residual carbon atoms on the edges, the PHGNRs can further derive different types of SGSs, as well as half-metals. Our work suggests that the PHGNRs possessing intrinsic robust magnetic moments have potential applications in the field of spintronic devices.