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Zinc-air batteries (ZABs) and Proton exchange membrane fuel cells (PEMFCs) have attracted wide attention because of their high energy density. However, the oxygen reduction reaction (ORR) occurred at the cathode is 6 orders of magnitude lower than the oxidation reaction occurred at the anode. In recent years, atomically dispersed metal-nitrogen-carbon (M-N-C) catalyst has been widely considered as one of the most promising catalysts to replace platinum-based catalysts. However, the performance of M-N-C catalyst is much lower than that of the most advanced Pt catalysts. The key to improving the catalytic activity of M-N-C ORR catalysts is to increase the intrinsic activity of the catalyst active sites. In this paper, the active sites of atomically dispersed M-N-C ORR catalysts are introduced, and the strategies of enhancing the intrinsic activity of the active sites including heteroatom doping, construction of dual atoms sites and creation rich defects in carbon materials are systematically summarized. Finally, the opportunities and challenges of further development of atomically dispersed M-N-C catalysts are proposed. • A comprehensive overview of atomically dispersed M-N-C catalysts for ORR. • Focus on the enhancement of the intrinsic activity of the active site. • Future directions of developing advanced M-N-C catalysts for ORR are outlined. [ABSTRACT FROM AUTHOR]

The bus passenger detection algorithm is a key component of a public transportation bus management system. The detection techniques based on the convolutional neural network have been widely used in bus passenger detection. However, they require high memory and computational requirements, which hinder the deployment of bus passenger detectors in the bus system. In this paper, a lightweight bus passenger detection model based on YOLOv5 is introduced. To make the model more lightweight, the inner and outer cross‐stage bottleneck modules, called ICB and OCB, respectively, are proposed. The proposed module reduces the quantity of parameter and floating point operations and increases the detection speed. In addition, the neighbour feature attention pooling is adopted to improve detection accuracy. The performance of the lightweight model on the bus passenger dataset is empirically demonstrated. The experiment results demonstrate that the proposed model is lightweight and efficient. Compared lightweight YOLOv5n with the original algorithm, the model weight is reduced by 31% to 2.6M, and the detection speed is increased by 6% to 40FPS without an accuracy drop. [ABSTRACT FROM AUTHOR]

Objective The aim of the study is to assess the causal effects of cardiovascular risk factors on venous thromboembolism (VTE) and its subtypes including deep vein thrombosis (DVT) and pulmonary embolism (PE). Methods A summary-level Mendelian randomization (MR) analysis was performed by extracting data from public and large-scale genome-wide association studies for cardiovascular risk factors (hypertension, systolic blood pressure [SBP], diastolic blood pressure [DBP], total cholesterol, triglycerides, high-density lipoprotein [HDL], low-density lipoprotein [LDL], type 2 diabetes, fasting glucose, body mass index [BMI], smoking, alcohol, and physical activity), VTE, DVT, and PE to identify genetic instruments. Results BMI (per standard deviation [SD] increase; odds ratio [OR]: 1.39; 95% confidence interval [CI]: 1.25–1.54; p = 8.02 × 10 −10) could increase the VTE risk, whereas SBP (per SD increase; OR: 0.99; 95% CI: 0.98–0.99; p = 0.0005) could decrease the VTE risk. For DVT, BMI (per SD increase; OR: 1.48; 95% CI: 1.28–1.72; p = 1.53 × 10 −7) could increase the risk, whereas physical activity (per SD increase; OR: 0.05; 95% CI: 0.01–0.33; p = 0.0020) could decrease the risk. For PE, BMI (per SD increase; OR: 1.29; 95% CI: 1.12–1.49; p = 0.0005) could increase the risk, whereas SBP (per SD increase; OR: 0.99; 95% CI: 0.98–1.00; p = 0.0032) could decrease the risk. Suggestive evidence between smoking and higher risks of VTE and DVT was also observed. Conclusion Our study supports that BMI is a causal risk factor for VTE, DVT, and PE. SBP is a protective factor for VTE and PE. Physical activity is a protective factor for DVT. However, the effects of other cardiovascular risk factors are not identified. [ABSTRACT FROM AUTHOR]

Infrared (IR) and visible image fusion is an important data fusion and image processing technique that can accurately and comprehensively integrate the thermal radiation and texture details of source images. However, existing methods neglect the high-contrast fusion problem, leading to suboptimal fusion performance when thermal radiation target information in IR images is replaced by high-contrast information in visible images. To address this limitation, we propose a contrast-balanced framework for IR and visible image fusion. Specifically, a novel contrast balance strategy is proposed to process visible images and reduce energy while allowing for detailed compensation of overexposed areas. Moreover, a contrast-preserving guided filter is proposed to decompose the image into energy-detail layers to reduce high contrast and filter information. To effectively extract the active information in the detail layer and the brightness information in the energy layer, we proposed a new weighted energy-of-Laplacian operator and a Gaussian distribution of the image entropy scheme to fuse the detail and energy layers, respectively. The fused result was obtained by adding the detail and energy layers. Extensive experimental results demonstrate that the proposed method can effectively reduce the high contrast and highlighted target information in an image while simultaneously preserving details. In addition, the proposed method exhibited superior performance compared to the state-of-the-art methods in both qualitative and quantitative assessments. [ABSTRACT FROM AUTHOR]

Full-field optical angiography (FFOA) has considerable potential for clinical applications in the prevention and diagnosis of various diseases. However, owing to the limited depth of focus attainable using optical lenses, only information about blood flow in the plane within the depth of field can be acquired using existing FFOA imaging techniques, resulting in partially unclear images. To produce fully focused FFOA images, an FFOA image fusion method based on the nonsubsampled contourlet transform and contrast spatial frequency is proposed. Firstly, an imaging system is constructed, and the FFOA images are acquired by intensity-fluctuation modulation effect. Secondly, we decompose the source images into low-pass and bandpass images by performing nonsubsampled contourlet transform. A sparse representation-based rule is introduced to fuse the lowpass images to effectively retain the useful energy information. Meanwhile, a contrast spatial frequency rule is proposed to fuse bandpass images, which considers the neighborhood correlation and gradient relationships of pixels. Finally, the fully focused image is produced by reconstruction. The proposed method significantly expands the range of focus of optical angiography and can be effectively extended to public multi-focused datasets. Experimental results confirm that the proposed method outperformed some state-of-the-art methods in both qualitative and quantitative evaluations. [ABSTRACT FROM AUTHOR]

In this work, we present a relativistic quantum embedding formalism capable of variationally treating relativistic effects, including scalar-relativity and spin–orbit coupling. We extend density functional theory (DFT)-in-DFT projection-based quantum embedding to a relativistic two-component formalism, where the full spin magnetization vector form is retained throughout the embedding treatment. To benchmark various relativistic embedding schemes, spin–orbit splitting of the nominally t2g valence manifold of W(CO)6, exchange coupling of [(H3N)4Cr(OH)2Cr(NH3)4]4+, and the dissociation potential curve of WF6 are investigated. The relativistic embedding formalism introduced in this work is well suited for efficient modeling of open-shell systems containing late transition metal, lanthanide, and actinide molecular complexes. [ABSTRACT FROM AUTHOR]

The change in electronic state from one spin multiplicity to another, known as intersystem crossing, occurs in molecules via the relativistic phenomenon of spin-orbit coupling. Current means of estimating intersystem crossing rates rely on the perturbative evaluation of spin-orbit coupling effects. This perturbative approach, valid in lighter atoms where spin-orbit coupling is weaker, is expected to break down for heavier elements where relativistic effects become dominant. Methods which incorporate spin-orbit effects variationally, such as the exact-two-component (X2C) method, will be necessary to treat this strong-coupling regime. We present a novel procedure which produces a diabatic basis of spin-pure electronic states coupled by spin-orbit terms, generated from fully variational relativistic calculations. This method is implemented within X2C using time-dependent density-functional theory and is compared to results from a perturbative relativistic study in the weak spin-orbit coupling regime. Additional calculations on a more strongly spin-orbit-coupled [ U O 2 C l 4 ] 2 − complex further illustrate the strengths of this method. This procedure will be valuable in the estimation of intersystem crossing rates within strongly spin-coupled species. [ABSTRACT FROM AUTHOR]

The article discusses Sustainable Development Goal 15 (SDG 15), which aims to protect and restore terrestrial ecosystems, manage forests sustainably, combat desertification, and halt biodiversity loss. The article highlights that many of the indicators for SDG 15 are off track or going in reverse, indicating a lack of progress. However, the article also mentions the use of big data, such as earth observation and citizen science, to address data gaps and improve monitoring of SDG 15. The article concludes by introducing a special issue that showcases advancements in using cutting-edge technologies for evaluating SDG 15 indicators. [Extracted from the article]

Land productivity is one of the sub-indicators for measuring SDG 15.3.1. Land Productivity Dynamics (LPD) is the most popular approach for reporting this indicator at the global scale. A major limitation of existing products of LPD is the coarse spatial resolution caused by remote sensing data input, which cannot meet the requirement of fine-scale land degradation assessment. To resolve this problem, this study developed a tool (HiLPD-GEE) to calculate 30 m LPD by fusing Landsat and MODIS data based on Google Earth Engine (GEE). The tool generates high-quality fused Normalized Difference Vegetation Index (NDVI) dataset for LPD calculation through gap filling and Savitzky–Golay filtering (GF-SG) and then uses the method recommended by the European Commission Joint Research Centre (JRC) to calculate LPD. The tool can calculate 30 m LPD in any spatial range within any time window after 2013, supporting global land degradation monitoring. To demonstrate the applicability of this tool, the LPD product was produced for African Great Green Wall (GGW) countries. The analysis proves that the 30 m LPD product generated by HiLPD-GEE could reflect the land productivity change effectively and reflect more spatial details. The results also provide an important insight for the GGW initiative. [ABSTRACT FROM AUTHOR]

In modern convolutional neural networks (CNNs), the pooling layer is seen as one of the primary layers for building the CNN model, which effectively downscales the spatial size of feature maps to reduce memory consumption. Several types of pooling operations, such as average pooling, max pooling, and strided convolution, fail to capture the spatial dependence between the pooling region feature and its neighbour features. In this paper, we propose a simple but effective attention-based pooling method called Neighbour Feature Attention-Based Pooling (NFP), which integrates neighbour features of the pooling region to keep semantic continuity across multiple layers. NFP adopts attention weights encoding with neighbour features by depthwise convolution, which effectively directs local spatial pooling for learning discriminative features. Compared to other pooling methods, the proposed method generates more discriminative features directed by neighbour information of the pooling region. The experiments results show that it consistently improves the performance across various backbone architectures on image classification tasks. [ABSTRACT FROM AUTHOR]

Pre-pregnancy obesity was associated with gestational diabetes in observational studies, but whether this relationship is causal remains to be determined. To evaluate whether pre-pregnancy obesity traits causally affect gestational diabetes risk, a two-sample Mendelian randomization (MR) analysis was performed utilizing summary-level statistics from published genome-wide association studies (GWAS). Obesity-related traits included body mass index (BMI), overweight, obesity, obesity class 1, obesity class 2, obesity class 3, childhood obesity, waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR), percent liver fat, visceral adipose tissue volume, abdominal subcutaneous adipose tissue volume. Effect estimates were evaluated using the inverse-variance weighting method. Weighted median, MR-Egger, simple mode, and weighted mode were performed as sensitivity analyses. Genetically predicted pre-pregnancy BMI [odds ratio (OR) = 1.68; 95% confidence interval (CI): 1.45–1.95; P = 9.13 × 10–12], overweight (OR = 1.49; 95% CI: 1.21–1.85; P = 2.06 × 10–4), obesity (OR = 1.25; 95% CI: 1.18–1.33; P = 8.01 × 10–13), obesity class 1 (OR = 1.31; 95% CI: 1.17–1.46; P = 1.49 × 10–6), obesity class 2 (OR = 1.26; 95% CI: 1.16–1.37; P = 5.23 × 10–8), childhood obesity (OR = 1.33; 95% CI: 1.23–1.44; P = 4.06 × 10–12), and WHR (OR = 2.35; 95% CI: 1.44–3.83; P = 5.89 × 10–4) were associated with increased risk of gestational diabetes. No significant association was observed with obesity class 3, WC, HC, percent liver fat, visceral adipose tissue volume, or abdominal subcutaneous adipose tissue volume. Similar results were observed in sensitivity analyses. Therefore, genetically predicted pre-pregnancy obesity traits may increase the risk of gestational diabetes. Weight control before pregnancy may be beneficial to prevent gestational diabetes. [ABSTRACT FROM AUTHOR]

In long-tailed recognition tasks, the knowledge distillation technology is widely adopted for improving performance of deep neural networks. These methods distill the knowledge from the pretrained teacher model to the student model, which enables higher long-tailed recognition accuracy. However, the dependence on accompanying assistive models complicates the single network's training process in the need for large memory and time costs. In this work, we present Balanced Self-Distillation (BSD) to distill tail knowledge by a single network without the assistive models. Specifically, BSD distills knowledge between different distortions of the same samples to stimulate the representation learning potential of the single network and adopts a balanced class weight for shifting the distillation focus from head-to-tail classes. Comprehensive experimentation across diverse datasets, including CIFAR-10-LT, CIFAR-100-LT and TinyImageNet-LT, consistently outperforms robust baseline methods. Specifically, BSD achieves improvements of 8.13% on CIFAR-100-LT with an imbalance ratio of 100 compared to the baseline (cross entropy). Furthermore, the proposed method enables seamless integration with contemporary techniques like re-sampling, meta-learning, and cost-sensitive learning. It emerges as a versatile tool capable of effectively addressing the challenges of long-tailed scenarios. [ABSTRACT FROM AUTHOR]

Spontaneous rupture and hemorrhage of mediastinal germ cell tumors is a rare occurrence. In the current report, the case of a 20-year-old male patient who was admitted with chest tightness and dyspnea is presented. An urgent chest CT scan revealed a large tumor in the right anterior mediastinum, measuring ~12 cm in diameter, with associated intratumoral hemorrhage. An emergency thoracotomy was performed to excise the lesion, which revealed that the bleeding was caused by a ruptured tumor. Postoperative pathological findings revealed a mediastinal mixed germ cell tumor consisting of four pathological types: Embryonal carcinoma, seminoma, yolk sac tumor and immature teratoma. Postoperatively, the patient showed marked improvement in the symptoms of dyspnea. However, the follow-up outcome was poor, and the patient succumbed 2 months after surgery. To the best of our knowledge, there are no reports of rupture and hemorrhage involving >4 mixed germ cell tumors. In the present report, the experience of the treatment of the patient is summarized, and literature was reviewed to improve clinicians' awareness of the disease. [ABSTRACT FROM AUTHOR]

Data augmentation is a powerful and widely used technique to improve the generalization of convolutional neural networks. The majority of data augmentation methods emphasize transforming samples to bolster network robustness. However, these methods overlook learning the invariance between the samples augmented by different transformations, impairing the quality of learned representations and generalization of the model. In this paper, we introduce a straightforward yet highly effective method called Consistent Augmentation (CA) to compel networks to learn explicitly the invariance of transformations. Specifically, CA minimizes the bidirectional KL divergence between the predicted distributions of different variants generated from the same samples using different transformations, explicitly enforcing consistency among various semantics-preserving transformations. Implementing CA is intuitive, uncomplicated, and does not introduce additional computational costs during inference. The validation experiments performed on conventional and fine-grained classification tasks demonstrate that CA can be employed across various network architectures and consistently improve their generalization ability. Notably, convolutional neural networks benefit significantly on fine-grained classification tasks, with an improvement of 5.18% and 6.61% compared with other augmentation methods in accuracy observed for the ShuffleNetV2 model on the Stanford Dogs and CUB-200-2011 datasets. Compatibility experiments conducted on the CIFAR-100 dataset reveal that CA improves the accuracy of the Mixup and CutMix methods by 1.25% and 2.11%, respectively. These results underscore the effectiveness of our approach when employed alongside mix-based augmentation methods, further enhancing the capabilities of the model. [ABSTRACT FROM AUTHOR]

Endometrial carcinoma (EC) is a commonly diagnosed gynecological malignancy. Interleukin-6 (IL6) plays a critical role in modulating the progression of several types of tumors, including EC. However, the specific mechanism of IL6 in regulating EC progression has not been clearly elucidated. In this study, we performed a series of functional experiments to explore the potential mechanisms involved in IL6 function in the progression of EC. Here, we found that IL6 increased reactive oxygen species (ROS) generation by enhancing the NADPH oxidase (NOX) level and induced mtDNA leakage in EC cells, which further caused the activation of the downstream cGAS-STING signaling and increased production of extracellular vesicle (EV) production from EC cells. Besides, the activation of cGAS-STING signaling enhanced the expression of type I IFN and its downstream molecule PD-L1 through the TBK1-IRF3 pathway. Importantly, a high level mtDNA and PD-L1 were present in EVs derived from IL6-induced EC cells; these vesicles were shown to be able to induce T cell apoptosis. Finally, anti-PD-L1 treatment in mice showed that blockade of PD-L1 significantly reversed tumor immune escape mediated by IL6-induced EVs. Together, we provide evidence that IL6 induced mtDNA leakage to regulate the immune escape of EC cells. Our findings may provide a novel clue for the development of therapeutic targets for EC. [ABSTRACT FROM AUTHOR]

The Silica Index (SI) obtained from thermal infrared bands is an effective way for monitoring sandy desertification. Sustainable Development Goals Science Satellite 1 (SDGSAT-1) enriches the thermal infrared imagery globally with three thermal infrared bands. However, the use of SDGSAT-1 for monitoring sandy desertification remains underexplored, especially with radiance instead of emissivity. This study firstly explored the capacity of SDGSAT-1-based SI for large-scale sandy desertification monitoring and its performance was evaluated through the comparison with ASTER-based SI and related studies. Taking the Mu Us sandy land as the study area, a key technique was developed to generate the Relative Normalized Silica Index (RNSI) to remove the land surface temperature effects on multi-temporal SI. Then the annual composite RNSI was acquired by averaging all available non-growing season RNSI scenes and used to classify the sandy desertification with a simple threshold method. The results show that the relative normalization approach could effectively remove the effect of land surface temperature difference in the original SI, ensuring that the average composite RNSI has good spatial consistency. The proposed composite RNSI could effectively classify different sandy desertification lands, with an overall accuracy of 85.7%. Moreover, the RNSI has greater advantages in discriminating moderate and severe sandy desertification lands compared to commonly used NDVI. The proportions of light, moderate, severe, and extreme severe sandy desertification lands account for 21.4%, 28.7%, 29.2%, and 20.7%, respectively. Severe and extremely severe sandy desertification covers nearly half of the study area. Therefore, the protection and recovery of the Mu Us sandy land still require continued attention. Since SDGSAT-1's thermal infrared sensor has a higher spatial resolution (30 m) and wider swath (300 km), the initial findings from this study demonstrate that SDGSAT-1 has great potential for rapid monitoring of sandy desertification with high precision at a large scale. • A revised Silica Index (RNSI) was proposed for sandy desertification monitoring. • The relative normalization method improves multi-temporal SI consistency greatly. • SDGSAT-1 based RNSI has great potential in large-scale desertification monitoring. [ABSTRACT FROM AUTHOR]

In 2015, the United Nations adopted the Transforming Our World: The 2030 Agenda for Sustainable Development, in which land degradation neutrality (LDN) is one of the important targets of the Sustainable Development Goal (SDG 15.3). However, due to varies indicative symptoms of land degradation in different climatic/geographical zones and land use types, the complexity of factors affecting land degradation or improvement, and the limits of spatial and temporal scope to define land degradation, for a long time, there was lack of common accepted methodology to identify land degradation, and short of key data set to establish reference baselines, and measure progress of SDG 15.3, which hinders the realization of SDG 15.3 by 2030. As a typical representative of a data-intensive scientific paradigm, Big Earth Data provides the possibility to solve this data gap. Focusing on two important aspects of SDG 15.3 reporting, namely baseline determination and progress monitoring, this article introduces the key challenges we faced, the potential of Big Earth Data and the practices we have taken. Finally, the prospects for harnessing Big Earth Data to facilitate SDG 15.3 in the future are outlined. [ABSTRACT FROM AUTHOR]

The k0 values of 6 non-1/v nuclides (152Eu, 152mEu, 154Eu, 177Lu, 192Ir and 194Ir) were determined using the extended Høgdahl formalism at the research reactor FRM II with very high f values. Standards were irradiated in 4 channels at different local temperatures between 40 °C and 55 °C measured using temperature sensitive irreversible labels. A good agreement with the recommended values was found for 152Eu, 154Eu and 177Lu using the original g(Tn) factors by Gryntakis, however, the k0 values for 152mEu in this work were 7% higher. New k0 values were also determined using the g(Tn) factors by Van Sluijs. Differences up to 6% were found for Eu isotopes compared with the recommended values. The recommended k0 values for 192Ir and 194Ir could be confirmed using g = 1. The theoretical k0 values for 177Lu were calculated using new nuclear data. They are up to 6% less than the recommended values. The present k0 values determined in this work showed a similar trend. The influence of different g(Tn) factors on the determination of the k0 values was investigated. [ABSTRACT FROM AUTHOR]

Multimodal medical image fusion extracts useful information from different modal medical images and integrates them into one image for a comprehensive and objective lesion description. However, existing methods ignore the simultaneous retention of significant edge and energy information that reflect lesion characteristics in medical images; this affects the application value of medical image fusion in computer aided diagnosis. This paper proposes a novel medical image fusion scheme based on extended difference-of-Gaussians (XDoG) and edge-preserving. A simple yet effective energy-based scheme was developed to generate the fused energy layer, which helped preserve energy. Moreover, the averaging filter was used to generate the detail layers of source images. The fusion of detail layers was considered the combination of significant and non-significant edge information. A rule of the detail layer with a salient edge based on edge extraction operator XDoG was proposed to efficiently detect the salient structure of the significant edges, and a spatial frequency energy operator was developed to detect the gradient and energy of non-significant information. The fused result could be reconstructed by synthesizing the fused energy layer and details of significant and non-significant edges. Experiments demonstrated that the proposed approach outperforms some advanced fusion methods in terms of subjective and objective assessment. The code of this paper is available at https://github.com/JEI981214/FGF-and-XDoG-based. [ABSTRACT FROM AUTHOR]

The neutron temperature at different irradiation positions in the research reactor FRM II was measured using thermometer labels together with lutetium standards. This was the first time to measure the local temperature at the irradiation positions with this combination. The simplified Westcott formalism was used to calculate the neutron temperature using Lu and g(Tn) factors from different data sources. The results showed agreement between neutron temperature according to the Lu method and the temperature showed on the labels. They can be used as a reliable alternative to determine the neutron temperature instead of using Lu standards in the extended k0 NAA. [ABSTRACT FROM AUTHOR]

While the natural transition orbital (NTO) method has allowed electronic excitations from time‐dependent Hartree‐Fock and density functional theory to be viewed in a traditional orbital picture, the extension to multicomponent molecular orbitals such as those used in relativistic two‐component methods or generalized Hartree‐Fock (GHF) or generalized Kohn‐Sham (GKS) is less straightforward due to mixing of spin‐components and the inherent inclusion of spin‐flip transitions in time‐dependent GHF/GKS. An extension of single‐component NTOs to the two‐component framework is presented, in addition to a brief discussion of the practical aspects of visualizing two‐component complex orbitals. Unlike the single‐component analog, the method explicitly describes the spin and frequently obtains solutions with several significant orbital pairs. The method is presented using calculations on a mercury atom and a CrO2Cl2 complex. [ABSTRACT FROM AUTHOR]

In order to investigate the anti-fibrotic effect of different molecular weight (Mw) fucoidans on TGF-β1-induced mouse renal tubular epithelial cell (MTEC) mode. Oxidative degradation method was used to obtain fucoidans with different molecular weights and the reaction time, reaction temperature and the concentration of oxidants were investigated. Cell viability was detected by CCK-8, and EMT markers expression was detected by Western-bolt and Cell immunofluorescence assay. As a result, after chemical analysis of three independent batches of prepared samples, one batch of fucoidan sample (LHX 1–9) which chemical contents are similar but Mw ranging from 3.3 KDa to 49.3 KDa were selected to do further research. We found LHX1 (Mw = 3.3 KDa) and LHX 3–9 (Mw = 6.6 KDa, 8.3 KDa, 11.3 KDa, 14.9 KDa, 25.2 KDa, 35.4 KDa, 49.3 KDa) could resist the TGF-β1-induced depithelial–mesenchymal transition (EMT) by decreased expression of Fn and CTGF and maintained epithelial cell morphology in MTEC. However, the relationship between the Mw of fucoidans and their anti-EMT effect is not simply linear. Among the samples, LHX 1, 5 and 8 showed significant anti-EMT effects than others by de-regulated Fn and CTGF expression on MTEC cells. [ABSTRACT FROM AUTHOR]

Multielectron excited states have become a hot topic in many cutting-edge research fields, such as the photophysics of polyenes and in the possibility of multiexciton generation in quantum dots for the purpose of increasing solar cell efficiency. However, obtaining multielectron excited states has been a major obstacle as it is often done with multiconfigurational methods, which involve formidable computational cost for large systems. Although they are computationally much cheaper than multiconfigurational wave function based methods, linear response adiabatic time-dependent Hartree–Fock (TDHF) and density functional theory (TDDFT) are generally considered incapable of obtaining multielectron excited states. We have developed a real-time TDHF and adiabatic TDDFT approach that is beyond the perturbative regime. We show that TDHF/TDDFT is able to simultaneously excite two electrons from the ground state to the doubly excited state and that the real-time TDHF/TDDFT implicitly includes double excitation within a superposition state. We also present a multireference linear response theory to show that the real-time electron density response corresponds to a superposition of perturbative linear responses of the S0 and S2 states. As a result, the energy of the two-electron doubly excited state can be obtained with several different approaches. This is done within the adiabatic approximation of TDDFT, a realm in which the doubly excited state has been deemed missing. We report results on simple two-electron systems, including the energies and dipole moments for the two-electron excited states of H2 and HeH+. These results are compared to those obtained with the full configuration interaction method. [ABSTRACT FROM AUTHOR]

Data augmentation is widely used to improve the generalization ability of convolutional neural networks in the image domain. The conventional augmentation schemes, e.g., single augmentation (including RandAug, Mixup, and CutMix) or batch augmentation, only optimize the network from pairs of augmented images and corresponding labels, leading to a loss of discriminative representation learning. To this end, we propose contrastive augmentation (CA), to learn discriminative representation by capturing the contrastive semantics among augmented samples. Specifically, the proposed CA method explicitly regularizes the similarity of augmented sample pairs to enable the model learn contrastive semantics. Equipped with CA at the training stage, the model simultaneously learns classification representation and contrastive semantics, which makes representation discriminative and does not incur additional inference computational costs. On conventional and fine-grained classification tasks, the experimental results show that the proposed method can effectively improve the generalization capability of convolutional neural networks, including ResNet, EfficientNet, MobileNet, ShuffleNet, and VAN. The compatibility experiment shows that our contrastive augmentation can be combined with other augmentation techniques, e.g., Mixup and CutMix, to further improve the model's performance. [ABSTRACT FROM AUTHOR]

Solar fuels catalysis is a promising route to efficiently harvesting, storing, and utilizing abundant solar energy. To achieve this promise, however, molecular systems must be designed with sustainable components that can balance numerous photophysical and chemical processes. To that end, we report on the structural and photophysical characterization of a series of Cu(I)–anthraquinone-based electron donor–acceptor dyads. The dyads utilized a heteroleptic Cu(I) bis-diimine architecture with a copper(I) bis-phenanthroline chromophore donor and anthraquinone electron acceptor. We characterized the structures of the complexes using x-ray crystallography and density functional theory calculations and the photophysical properties via resonance Raman and optical transient absorption spectroscopy. The calculations and resonance Raman spectroscopy revealed that excitation of the Cu(I) metal-to-ligand charge-transfer (MLCT) transition transfers the electron to a delocalized ligand orbital. The optical transient absorption spectroscopy demonstrated that each dyad formed the oxidized copper–reduced anthraquinone charge-separated state. Unlike most Cu(I) bis-phenanthroline complexes where increasingly bulky substituents on the phenanthroline ligands lead to longer MLCT excited-state lifetimes, here, we observe a decrease in the long-lived charge-separated state lifetime with increasing steric bulk. The charge-separated state lifetimes were best explained in the context of electron-transfer theory rather than with the energy gap law, which is typical for MLCT excited states, despite the complete conjugation between the phenanthroline and anthraquinone moieties. [ABSTRACT FROM AUTHOR]

Snow interception by the forest canopy is an important control on the forest hydrological cycle in the Xiaoxing'an Mountains within the northern temperate region of China. In this study, the effects of snowfall characteristics and stand structures on the snowfall redistribution of the canopies within primary spruce‐fir Korean pine forests are analyzed at the forest stand scale. Characteristics of snowfall, through‐canopy snowfall, and stand structure are continuously measured using positioning observations. A semiempirical theoretical model is used to conduct snow interception simulations in the Xiaoxing'an Mountain region. The results indicate that the snowfall, canopy density, slope gradient, and tree height have a significant effect on the through‐canopy snowfall. The interception efficiency gradually decreases with an increase in the amount of snowfall and is particularly sensitive to the snowfall and canopy density, although it shows no significant correlation with average diameter at breast height, tree height, basal area, canopy height, canopy width, leaf area, or slope gradient. Very similar results have been observed in Canada and Switzerland, suggesting the transferability of the results between North America, Western Europe, and China. However, although model results provide a satisfactory simulation of snow interception, further studies are required to optimize the model in this region. [ABSTRACT FROM AUTHOR]

Phototherapy is a non-invasive or minimally invasive therapeutic strategy. Immunotherapy uses different immunological approaches, such as antibodies, vaccines, immunoadjuvants, and cytokines to stimulate the host immune system to fight against diseases. In cancer treatment, phototherapy not only destroys tumor cells, but also induces immunogenic tumor cell death to initiate a systemic anti-tumor immune response. When combined with immunotherapy, the effectiveness of phototherapy can be enhanced. Because of their special physical, chemical, and sometimes immunological properties, nanomaterials have also been used to enhance phototherapy. In this article, we review the recent progress in nanotechnology-based phototherapy, including nano-photothermal therapy, nano-photochemical therapy, and nano-photoimmunological therapy in cancer treatment. Specifically, we focus on the immunological responses induced by nano-phototherapies. [ABSTRACT FROM AUTHOR]

For a set H of graphs, a graph G is H -free if G does not contain any subgraph isomorphic to some graph in H . In this paper, we study the minimum H -free node deletion problem (Min H FND) and the maximum H -free node set problem (Max H FNS), which include a lot of extensively-studied problems such as the minimum k -path vertex cover problem, the dissociation number problem, and the minimum degree bounded node deletion problem. For a large class of H , PTASs are given for Min H FND and Max H FNS on disk graphs whose heterogeneity is bounded by a constant, where the heterogeneity of a disk graph is the ratio of the maximum radius to the minimum radius of disks. [ABSTRACT FROM AUTHOR]

A nitrogen K-edge x-ray absorption near-edge structure (XANES) survey is presented for tetrapyrido[3,2-a:2′,3′-c:3″,2″-h:2‴,3‴-j]phenazine (tpphz)-bridged bimetallic assemblies that couple chromophore and catalyst transition metal complexes for light driven catalysis, as well as their individual molecular constituents. We demonstrate the high N site sensitivity of the N pre-edge XANES features, which are energetically well-separated for the phenazine bridge N atoms and for the individual metal-bound N atoms of the inner coordination sphere ligands. By comparison with the time-dependent density functional theory calculated spectra, we determine the origins of these distinguishable spectral features. We find that metal coordination generates large shifts toward higher energy for the metal-bound N atoms, with increasing shift for 3d < 4d < 5d metal bonding. This is attributed to increasing ligand-to-metal σ donation that increases the effective charge of the bound N atoms and stabilizes the N 1s core electrons. In contrast, the phenazine bridge N pre-edge peak is found at a lower energy due to stabilization of the low energy electron accepting orbital localized on the phenazine motif. While no sensitivity to ground state electronic coupling between the individual molecular subunits was observed, the spectra are sensitive to structural distortions of the tpphz bridge. These results demonstrate N K-edge XANES as a local probe of electronic structure in large bridging ligand motifs, able to distinctly investigate the ligand-centered orbitals involved in metal-to-ligand and ligand-to-ligand electron transfer following light absorption. [ABSTRACT FROM AUTHOR]

Block-localized wave function is a useful method for optimizing constrained determinants. In this article, we extend the generalized block-localized wave function technique to a relativistic two-component framework. Optimization of excited state determinants for two-component wave functions presents a unique challenge because the excited state manifold is often quite dense with degenerate states. Furthermore, we test the degree to which certain symmetries result naturally from the ΔSCF optimization such as time-reversal symmetry and symmetry with respect to the total angular momentum operator on a series of atomic systems. Variational optimizations may often break the symmetry in order to lower the overall energy, just as unrestricted Hartree–Fock breaks spin symmetry. Overall, we demonstrate that time-reversal symmetry is roughly maintained when using Hartree–Fock, but less so when using Kohn–Sham density functional theory. Additionally, maintaining total angular momentum symmetry appears to be system dependent and not guaranteed. Finally, we were able to trace the breaking of total angular momentum symmetry to the relaxation of core electrons. [ABSTRACT FROM AUTHOR]

Upconversion nanoparticles capable of strongly absorbing photons in a wide spectral range are highly desired for practical applications. In this work, IR-806 dye was used to increase the light absorptivity of Nd 3+ /Yb 3+ /Er 3+ tri-doped core/shell nanoparticles and then to enhance their upconversion luminescence under ∼800 nm excitation. The IR-806 dye exhibited more efficient energy transfer to Nd 3+ ions than to Yb 3+ ions for subsequent upconversion emission due to the increased spectral overlap between the dye emission and Nd 3+ absorption. The influence of the Nd 3+ concentration in the shell and the dye/nanoparticle ratio on the dye-sensitization effect was also investigated. A maximum 28-fold overall enhancement in the emission intensity was achieved for NaYF 4 :Yb 3+ /Er 3+ @NaYF 4 :Yb 3+ /Nd 3+ core/shell nanoparticles using dye sensitization. The dye-sensitized NaYF 4 :Yb 3+ /Er 3+ @NaYF 4 :Yb 3+ /Nd 3+ core/shell nanoparticles also exhibited increased photothermal conversion capabilities and excellent temperature sensing properties, enabling their potential application in photothermal nanoheaters with real-time temperature monitoring under 808 nm single beam excitation. [ABSTRACT FROM AUTHOR]

Increasing human numbers and aspirations threaten protected areas worldwide. China faces especially strong pressure since many people live inside protected areas. It has sought to balance human needs and conservation goals within them by creating mixed zoning schemes loosely based on UNESCO's Man and the Biosphere Programme. These include strictly-protected core zones, buffer zones allowing limited human use, and experimental zones that examine different land-use options. To test the efficacy of this zoning, we employed field surveys and remote sensing to assess the penetration of agricultural and urban land into 109 national nature reserves in China for 2000 and 2010. Human disturbance was lowest in core zones and highest in experimental zones in both 2000 and 2010. Over this period, 82% of the reserves were unchanged or had decreased human disturbance. Nonetheless, overall human disturbance increased by 7%, 4%, and 5% in the core, buffer and experimental zones respectively. Almost all the increase in the core zone was in four wetland reserves, where human actions converted large areas to agriculture. Some 58% of reserves experienced some human disturbance in core zones in 2010, demonstrating a need for more effective zoning. The findings have broader implications for protected area management globally because they highlight the strengths and weaknesses of zoning for balancing human needs and species conservation. [ABSTRACT FROM AUTHOR]

The genetic diversity of malaria parasites traces the origin and spread of new variants and can be used to evaluate the effectiveness of malaria control measures. Therefore, this study aims to improve the understanding of the molecular epidemiology of Plasmodium vivax malaria at the China-Myanmar border by genotyping the PvMSP-3α and PvMSP-3β genes. Blood samples were collected from P. vivax malaria patients along the China-Myanmar border. The PvMSP-3α and PvMSP-3β genes were amplified by polymerase chain reaction (PCR) and the genetic polymorphism and haplotype of the two genes were analyzed. A total of 422 blood samples were used for this study, of which 224 were analyzed at PvMSP-3α and 126 at PvMSP-3β. Samples mainly were from young adults aged 18–45 years, although local patients were significantly younger than migrant laborers crossing the border at Tengchong (P < 0.0001). Molecular evolutionary analysis revealed that PvMSP-3α and PvMSP-3β underwent diversifying natural selection, and intragenic recombination contributed to the diversity of the isolates. Based on the length of the genes, we identified three types of PvMSP-3α [1.9–2.0 kb (Type-A), 1.4–1.5 kb (Type-B), and 1.1–1.3 kb (Type-C)] and two types of PvMSP-3β [1.7–2.2 kb (Type-A) and 1.4–1.5 kb (Type-B)]. Migrant laborers returning to China through Tengchong bore P. vivax infections displaying significantly higher genetic diversity than local residents. Both PvMSP-3 paralogs were subjected to diversifying selection in each sample population. Clustering of alleles supports ephemeral endemic differentiation of alleles, but the broader phylogeny suggests that alleles transit the globe, perhaps accelerated by movements of migrants such as those transiting Tengchong. [ABSTRACT FROM AUTHOR]

A vertex subset C of a connected graph G is called a connected k -path vertex cover ( C V C P k ) if every path on k vertices contains at least one vertex from C , and the subgraph of G induced by C is connected. This concept originated in the field of security and supervisory control. This paper studies the minimum (weight) C V C P k problem. We first show that the minimum weight C V C P k problem can be solved in time O ( n ) when the graph is a tree, and can be solved in time O ( r n ) when the graph is a uni-cyclic graph whose unique cycle has length r , where n is the number of vertices. Making use of the algorithm on trees, we present a k -approximation algorithm for the minimum (cardinality) C V C P k problem under the assumption that the graph has girth at least k . An example is given showing that performance ratio k is asymptotically tight for our algorithm. [ABSTRACT FROM AUTHOR]

The measurement of plant community structure provides an extensive understanding of its function, succession and ecological process. The detection of plant community boundary is rather a challenge despite in situ work. Recent advances in object-based image analysis (OBIA) and machine learning algorithms offer new opportunities to address this challenge. This study presents a multi-scale segmentation approach to accurately identify the boundaries of each vegetation and plant community for mapping plant community structure. Initially, a very high resolution (VHR) Worldview-2 image of a desert area is hierarchically segmented from scale parameter 2 to 500. Afterward, the peak values of the standard deviation of brightness and normalized difference vegetation index (NDVI) across the segmentation scales are detected to determine the optimal segmentation scales of homogeneous single plant and plant community boundaries. A multi-scale classification of vegetation characterization with features of multiple bands, NDVI, grey-level co-occurrence matrix (GLCM) entropy and shape index is performed to identify dryland vegetation types. Finally, the four vegetation structural features on the type, diversity, object size and shape are calculated within the plant community boundaries and composed to plant community structure categories. Comparing the results with the object fitting index (FI) of the reference data, the validation indicates that the optimal segmentations of tree, shrub and plant communities are consistent with the identified peak values. [ABSTRACT FROM AUTHOR]

Aiming for the restoration of degraded ecosystems, many ecological engineering projects have been implemented around the world. This study investigates the ecological engineering project effectiveness on vegetation restoration in the Beijing-Tianjin Sand Source Region (BTSSR) from 2000 to 2010 based on the rain use efficiency (RUE) trend in relation to the land cover. More than half of the BTSSR experienced a vegetation productivity increase from 2000 to 2010, with the increasing intensity being sensitive to the indicators chosen. A clear tendency towards smaller increasing areas was shown when using the net primary productivity (NPP, 51.30%) instead of the accumulated normalized difference vegetation index (59.30%). The short-term variation in the precipitation and intra-seasonal precipitation distribution had a great impact on the remote sensing-based vegetation productivity. However, the residual trends method (RESTREND) effectively eliminated this correlation, while incorporating the variance and skewness of the precipitation distribution increased the models′ ability to explain the vegetation productivity variation. The RUE combined with land cover dynamics was valid for the effectiveness assessment of the ecological engineering projects on vegetation restoration. Particularly, the result based on growing season accumulated normalized difference vegetation index (ΣNDVI) residuals was the most effective, showing that 47.39% of the BTSSR experienced vegetation restoration from 2000 to 2010. The effectiveness of the ecological engineering projects differed for each subarea and was proportional to the strength of ecological engineering. The water erosion region dominated by woodland showed the best restoration, followed by the wind-water erosion crisscross regions, while the wind erosion regions dominated by grassland showed the worst effect. Seriously degraded regions still cover more area in the BTSSR than restored regions. Therefore, more future effort should be put in restoring degraded land. [ABSTRACT FROM AUTHOR]

The green vegetation fraction Fg, which represents the horizontal density of live vegetation, is an important parameter for the study of global energy, carbon, hydrological, and biogeochemical cycling. A common method of calculating Fg is to create a simple linear mixing model between two NDVI endmembers: bare soil NDVI, , and full vegetation NDVI, . However, many uncertainties exist for the determination of these parameters at large scales. The present study investigates how and determination can impact Fg calculations for all of China, based on different land-cover datasets, hyperspectral data, and soil type classification maps. The results show the following: 1) The regional ChinaCover dataset, with higher accuracy and more detailed classification, is preferable for calculating Fg in China, compared with the most commonly used MOD12Q1 dataset, although it would not lead to too much difference in values. 2) The soil NDVI from Hyperion datasets shows that soils have highly variable NDVI values (0.006-0.2), and 79.36% of the area studied has a much larger NDVI value than the commonly used value of 0.05. Therefore, the dynamic values with different soil types are much better for Fg calculation than the invariant value (0.05), which would yield a significant overestimation of Fg, especially for areas with low vegetation coverage. 3) A high-quality Fg dataset for China from 2000 to 2010 was established with and parameters based on MOD13Q1 250-m NDVI data. [ABSTRACT FROM AUTHOR]

The aim of our study was to increase the detection rate of fetal cardiac malformations for congenital heart disease (CHD). The ultrasonic and microanatomical methods were combined to study the CHD cases firstly, which could provide the microsurgical anatomical basis to the prenatal ultrasonic diagnosis which was used in suspected CHD and help the sonographer to improve the quality of fetal cardiac diagnosis. We established the ultrasonic standard section of the 175 complex CHD cases and collected the fetal echocardiography image files. The induced/aborted fetuses were fixed by 4% paraformaldehyde and dissected by the ultrasonic microsurgical anatomy. This research could obtain the fetal cardiac anatomic cross-sectional images which was consistent with the ultrasonic standard section and could clearly show the internal structure of the vascular malformation that optimized the ultrasound examination individually. This method could directly display the variation of the CHD fetal heart clearly and comprehensively help us to understand the complex fetal cardiac malformation from the internal structure of the vascular malformation which was consolidated by the anatomical basis of the fetal heart. This study could improve the integrity and accuracy of the prenatal cardiac ultrasound examination tremendously. [ABSTRACT FROM AUTHOR]

Due to the presence of multi-principal elements, the multi-principal element alloys (MPEAs) are supposed to undergo competing oxidation reactions during micro-arc oxidation (MAO). In this work, Ti–Nb–Zr medium entropy alloy (MEA, MAO-Free) was MAO-treated at various applied voltage. For Ti–Nb–Zr MEA treated at 250 V (MAO-250 V), the coating microstructure was characterized by amorphous oxides of Ti, Nb and Zr from the substrate and amorphous compounds of CaO, Ca(OH) 2 , SiO 2 and CaSiO 3 from the electrolyte, which distributed homogeneously in coating matrix. Different from the microstructure of MAO-250 V group, tetragonal-ZrO 2 nano-crystals dispersed in amorphous coating matrix were noticed for that treated at 300 V (MAO-300 V). For specimen treated at 350 V (MAO-350 V), the coating matrix exhibited higher crystallinity by composing of major tetragonal-ZrO 2 and minor rutile-TiO 2 , with the presence of nano-sized amorphous regions. The pore size, porosity, surface roughness and hydrophilicity of coatings increased with the increase of applied voltage. An order of MAO-300 V > MAO-250 V > MAO-Free > MAO-350 V group was identified for the wear resistance. Moreover, the MAOed coatings exhibited comparable corrosion resistance and cyto-compatibility to MAO-Free group. Together, the results indicate that the MAO-300 V group with favorable wear resistance, corrosion resistance and cyto-compatibility is promising for biomedical applications. [ABSTRACT FROM AUTHOR]

Endowing advanced 3D photonic nanoarchitectures with dynamic controllability is currently in the spotlight of soft‐matter photonics research. Herein, a well‐defined photopatterned polymer‐stabilized blue phase (PSBP) film with 3D electrically tunable photonic bandgap is fabricated by a liquid crystalline thiol–acrylate monomers system. Remarkably, the addition of thiol monomers can effectively improve the electrical tuning performance of the PSBP film and maintain excellent thermal stability simultaneously. The proportions of acrylate and thiol monomers are proved to be a key factor on the morphology structure of the polymer network in the PSBP system. By masked UV photopolymerization, a patterned sample with a high‐quality image and reversible nonsynergistic electrochromism is obtained. With increasing electric field, the patterned region changes from initial green reflection color to a red one, while no obvious visual color change occurs for the shading region with initial blue reflection color. The distinct electrically responsive behaviors are mainly caused by the microstructural difference of polymer networks, which is engendered by the migration of polymerizable monomers during polymerization. The research disclosed herein may provide new insights into the development of patterned 3D self‐assembled liquid crystalline photonic crystal toward anticounterfeiting, displays, colorimetric sensors, labeling technology, and programming photonics. [ABSTRACT FROM AUTHOR]

A novel, promising potential cancer vaccine strategy was proposed to use a two-injection procedure for solid tumors to prompt the immune system to identify and systemically eliminate primary and metastatic cancers. The two-injection procedure consists of local photothermal application on a selected tumor intended to liberate whole cell tumor antigens, followed by a local injection of an immunoadjuvant that consists of a semi-synthetic functionalized glucosamine polymer, N-dihydro-galacto-chitosan (GC), which is intended to activate antigen presenting cells and facilitate an increased uptake of tumor antigens. This strategy is thus proposed as an in situ autologous cancer vaccine (inCVAX) that may activate antigen presenting cells and expose them to tumor antigens in situ, with the intention of inducing a systemic tumor specific T-cell response. Here, the development of inCVAX for the treatment of metastatic cancers in the past decades is systematically reviewed. The antitumor immune responses of local photothermal treatment and immunological stimulation with GC are also discussed. This treatment approach is also commonly referred to as laser immunotherapy (LIT). [ABSTRACT FROM AUTHOR]

A novel, promising potential cancer vaccine strategy was proposed to use a two-injection procedure for solid tumors to prompt the immune system to identify and systemically eliminate primary and metastatic cancers. The two-injection procedure consists of local photothermal application on a selected tumor intended to liberate whole cell tumor antigens, followed by a local injection of an immunoadjuvant that consists of a semi-synthetic functionalized glucosamine polymer, N -dihydro-galacto-chitosan (GC), which is intended to activate antigen presenting cells and facilitate an increased uptake of tumor antigens. This strategy is thus proposed as an in situ autologous cancer vaccine (inCVAX) that may activate antigen presenting cells and expose them to tumor antigens in situ , with the intention of inducing a systemic tumor specific T-cell response. Here, the development of inCVAX for the treatment of metastatic cancers in the past decades is systematically reviewed. The antitumor immune responses of local photothermal treatment and immunological stimulation with GC are also discussed. This treatment approach is also commonly referred to as laser immunotherapy (LIT). [ABSTRACT FROM AUTHOR]

The objectives of the study are to observe and analyze the causes of 237 patients' malposition peripherally inserted central catheter ( PICC) from 3012 patients in clinical practice and to further explore the methods of its prevention and remedies, which can help to improve the skills of placing tubes, to efficiently avoid and reduce the occurrence of complications, and to alleviate the pains and cost of patients. From August 2000 to March 2012, 3012 cases receiving PICC were reviewed. The locations of the tube tips were recorded by chest X ray and summarized for analysis. Malposition was observed in 237 cases (7.87%). The most frequently occurring site was in the jugular vein followed by the axillary vein. By taking different remedies, all the malpositioned PICCs were relocated in the superior vena cava or subclavian vein. In order to secure the safety usage of PICC, the strict rules of handling, the skill and experience of operator, and cooperation patients are necessary. [ABSTRACT FROM AUTHOR]

Semiconducting nanocrystals have been the subject of intense research due to the ability to modulate the electronic and magnetic properties by controlling the size of the crystal, introducing dopants, and surface modification. While relatively simple models such as a particle in a sphere can work well to describe moderately sized quantum dots, this approximation becomes less accurate for very small nanocrystals that are strongly confined. In this work, we report all-electron, relativistic ab initio electronic structure calculations for a series of ZnO quantum dots in order to study the modulation of the Rashba effect. The impact and magnitude of spin-orbit coupling and crystalline anisotropy on the fine structure of the band-edge excitonic manifold are discussed. [ABSTRACT FROM AUTHOR]

Wall attachment has great potential in a broad range of applications such as robotic grasping, transfer printing, and asteroid sampling. Herein, a new type of underactuated bionic microspines gripper is proposed to attach to an irregular, rough wall. Experimental results revealed that the gripper, profiting from its flexible structure and underactuated linkage mechanism, is capable of adapting submillimeter scale roughness to centimeter scale geometry irregularity in both normal and tangential attachment. The rigid-flexible coupling simulation analysis validated that the rough adaptation was achieved by the passive deformation of the zigzag flexible structure, while the centimeter-scale irregularity adaptation come from the underactuated design. The attachment test of a spine confirmed that a 5 mm sliding distance of the spine tip on the fine brick wall promises a saturated tangential attachment force, which can guide the stiffness design of flexible structure and parameter selection of underactuated linkage. Furthermore, the developed microspines gripper was successfully demonstrated to grasp irregular rocks, tree trunks, and granite plates. This work presents a generally applicable and dexterous passive adaption design to achieve rough wall attachment for flat and curved objects, which promotes the understanding and application of wall attachment. [ABSTRACT FROM AUTHOR]

Meta-analysis is performing statistical analysis utilizing results from multiple sources. An application of meta-analysis is inference on a common mean when independent random samples are available from different normal populations with unknown and possibly unequal variances. This is an extension of the classical Behrens–Fisher problem. Chang and Pal [Testing on the common mean of several normal distributions, Comput. Statist. Data Anal. 53 (2008), pp. 321–333] described several methods that can be used to test hypotheses concerning this common mean. They proposed four methods which are the likelihood ratio test, two tests based on the Graybill-Deal estimator of the common mean, and a parametric bootstrap test based on the maximum-likelihood estimator. This paper proposes several Bayesian procedures to test the hypotheses of interest. Simulation studies investigating the size, power, and robustness of the new tests as well as the tests in Chang and Pal [1] are performed and discussed. Some of the results are in conflict with Chang and Pal [1] and some of the Bayesian tests appear to be attractive alternatives to tests that have been proposed in the past. [ABSTRACT FROM AUTHOR]