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Climate and landscape structure are widely recognized as the primary drivers of soil erosion; however, the spatiotemporal variability of their effects remains insufficiently understood, limiting our comprehension of the dynamic processes of soil erosion. To address this gap, this study analyzed soil erosion trends on the Loess Plateau from 2000 to 2018. extreme Gradient Boosting was used to identify key climatic and landscape structural factors, while a geographically and temporally weighted regression model was applied to assess the spatiotemporal variability of these influences. The results indicate a decreasing trend in soil erosion from 2000 to 2008, followed by a sharp increase from 2008 to 2018. Grassland edge density emerged as the most important factor, followed closely by grassland percentage and annual precipitation. Temporally, the positive effect of annual precipitation has been intensifying since 2010, contributing to increased erosion, while landscape structural factors progressively enhanced their hydrological regulatory roles, reflecting dynamic interactions with climate. Spatially, the direction of climatic influences remained generally stable, consistently promoting erosion, although by 2018, the effects of average annual temperature and annual sunshine duration reversed to suppress erosion in specific areas. In contrast, landscape structural influences exhibited greater spatial variability, often fluctuating or reversing depending on topography, human activity, and land use. This variability applied specifically and differentially to each metric of fragmentation and diversity, highlighting the critical importance of trade-offs in landscape management. The findings emphasize the complexity and dynamics of soil erosion in response to climate and landscape structure, suggesting implications for the development of spatially targeted soil erosion control strategies that accommodate the phases of temporal variation., (Copyright © 2024. Published by Elsevier B.V.)

Aims: A new model of computational fluid dynamics (CFD)-based algorithm for coronary CT angiography (CCTA)-derived fractional flow reserve (FFR) (CT-FFR) analysis by expanding the coronary tree to smaller-diameter lumen (0.8 mm) using Newton-Krylov-Schwarz (NKS) method to solve the three-dimensional time-dependent incompressible Navier-Stokes equations has been developed; however, the diagnostic performance of this new method has not been sufficiently investigated. The aim of this study was to determine the diagnostic performance of a novel CT-FFR technique by expanding the coronary tree in the CFD domain., Methods and Results: Six centres enrolled 338 symptomatic patients with suspected or known coronary artery disease (CAD) who prospectively underwent CCTA and FFR. Stenosis assessment in CCTA and CT-FFR analysis were performed in independent core laboratories. Haemodynamically significant stenosis was defined by a CT-FFR and FFR ≤ 0.80, and anatomically obstructive CAD was defined as a CCTA with stenosis ≥ 50%. Diagnostic performance of CT-FFR was evaluated against invasive FFR using receiver operating characteristic (ROC) curve analysis. The correlation between CT-FFR and invasive FFR was analysed using the Spearman correlation coefficient and Bland-Altman analysis. Intra-observer and inter-observer agreements were evaluated utilizing the intraclass correlation coefficient (ICC). In this study, 338 patients with 422 targeted vessels were investigated, revealing haemodynamically significant stenosis in 31.1% (105/338) of patients and anatomically obstructive stenosis in 54.1% of patients. On a per-vessel basis, the area under the ROC curve for CT-FFR was 0.94 vs. 0.76 for CCTA ( P < 0.001). Per-vessel accuracy, sensitivity, specificity, positive predictive value, and negative predictive value were 89.8%, 89.3%, 90.0%, 79.0%, and 99.2%, respectively, for CT-FFR and were 68.4%, 82.8%, 62.3%, 48.1%, and 89.6%, respectively, for CCTA stenosis. CT-FFR and FFR were well correlated ( r = 0.775, P < 0.001) with a Bland-Altman bias of 0.0011, and limits of agreement from -0.1509 to 0.1531 ( P = 0.770). The ICCs with CT-FFR for intro- and inter-observer agreements were 0.919 (95% CI: 0.866-0.952) and 0.909 (95% CI: 0.851-0.945), respectively. The average computation time for CT-FFR analysis was maintained at 11.7 min., Conclusion: This novel CT-FFR model with the inclusion of smaller lumen provides high diagnostic accuracy in detecting haemodynamically significant CAD. Furthermore, the integration of the NKS method ensures that the computation time remains within an acceptable range for potential clinical applications in the future., Competing Interests: Conflict of interest: M.Z. has received research grants from National Natural Science Foundation of China and Shanghai Municipal Key Clinical Specialty, and serves as a consultant for United Imaging. J.G. has received research grants from National Key Research and Development Program of China and Shanghai Clinical Research Center for Interventional Medicine and China Cardiovascular Health Alliance-Access Research Fund. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (© The Author(s) 2024. Published by Oxford University Press on behalf of the European Society of Cardiology.)

Global climate change has necessitated the implementation of green infrastructure that is resilient in a manner of sustainable development. The current understanding of green infrastructure resilience is hindered by the divergence of generic properties and performance in adapting to uncertain disturbances. This study develops an operational methodology that integrates structural and functional properties of green infrastructure, and their connections to shape the general resilience. A further empirical study is conducted in the context of Shenzhen City, where the effectiveness of resilient connections is correlated with the distribution of waterlogging. We demonstrate that green infrastructure present different levels of resilience in terms of its structural composition and functional performance. The Shenzhen city shows a high capacity to maintain soil retention stability, but a feeble capacity regarding water yield and gross primary productivity. The resilient connections of green infrastructure are highly centralized, with a few pivotal nodes performing a high degree of connectivity. It shows that a total of 52.2% of resilient lines are identified as belonging to the fourth level but linking the majority of the nodes. Enhancing the general resilience of green infrastructure could facilitate its adaptation to specific disturbances such as waterlogging. When correlated the resilient connections of green infrastructure with the distribution of waterlogging, a distance of 1.6 km from the waterlogging points is significantly identified where the residuals of the entropy index display the lowest variance. As the distance increases, the composite entropy index initially decreases and then increases. We suggest that the alignment of generic properties and specified performance of green infrastructure is essential in the pursuit of sustainable development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

AutoDock Vina and its derivatives have established themselves as a prevailing pipeline for virtual screening in contemporary drug discovery. Our Vina-GPU method leverages the parallel computing power of GPUs to accelerate AutoDock Vina, and Vina-GPU 2.0 further enhances the speed of AutoDock Vina and its derivatives. Given the prevalence of large virtual screens in modern drug discovery, the improvement of speed and accuracy in virtual screening has become a longstanding challenge. In this study, we propose Vina-GPU 2.1, aimed at enhancing the docking speed and precision of AutoDock Vina and its derivatives through the integration of novel algorithms to facilitate improved docking and virtual screening outcomes. Building upon the foundations laid by Vina-GPU 2.0, we introduce a novel algorithm, namely Reduced Iteration and Low Complexity BFGS (RILC-BFGS), designed to expedite the most time-consuming operation. Additionally, we implement grid cache optimization to further enhance the docking speed. Furthermore, we employ optimal strategies to individually optimize the structures of ligands, receptors, and binding pockets, thereby enhancing the docking precision. To assess the performance of Vina-GPU 2.1, we conduct extensive virtual screening experiments on three prominent targets, utilizing two fundamental compound libraries and seven docking tools. Our results demonstrate that Vina-GPU 2.1 achieves an average 4.97-fold acceleration in docking speed and an average 342% improvement in EF1% compared to Vina-GPU 2.0. The source code and tools for Vina-GPU 2.1 are freely available accompanied by comprehensive instructions and illustrative examples.

Inorganic metal sulfides have received extensive investigation as anode materials in lithium-ion batteries (LIBs). However, applications of crystalline organic hybrid metal sulfides as anode materials in LIBs are quite rare. In addition, combining the nanoparticles of crystalline organic hybrid metal sulfides with conductive materials is expected to enhance the electrochemical lithium storage performance. Nevertheless, due to the difficulty of harvesting the nanoparticles of crystalline organic hybrid metal sulfides, this approach has never been tried to date. Herein, nanoparticles of a crystalline organic hybrid cadmium antimony sulfide (1,4-DABH 2 )Cd 2 Sb 2 S 6 (DCAS) were prepared by a top-down method, including the procedures of solvothermal synthesis, ball milling, and ultrasonic pulverization. Thereafter, the nanoparticles of DCAS with sizes of ∼500 nm were intercalated into graphene oxide nanosheets through a freeze-drying treatment and a DCAS@GO composite was obtained. Compared with the reported Sb 2 S 3 - and CdS-based composites, the DCAS@GO composite exhibited superior electrochemical Li + ion storage performance, including a high capacity of 1075.6 mAh g -1 at 100 mA g -1 and exceptional rate tolerances (646.8 mAh g -1 at 5000 mA g -1 ). In addition, DCAS@GO can provide a high capacity of 705.6 mAh g -1 after 500 cycles at 1000 mA g -1 . Our research offers a viable approach for preparing the nanoparticles of crystalline organic hybrid metal sulfides and proves that intercalating organic hybrid metal sulfide nanoparticles into GO nanosheets can efficiently boost the electrochemical Li + ion storage performance.

Ultra-High Toughness Cementitious Composite (UHTCC) represents a composite material meticulously engineered on the foundation of micromechanical principles. The multi-crack cracking and strain-hardening characteristics of UHTCC enable it to be applied to orthotropic steel decks to control the crack width. Different from most studies which only focus on hybrid fiber or fatigue characteristics, this paper studies the influence of hybrid fiber content on static mechanical properties, flexural toughness, and flexural fatigue characteristics of UHTCC under different stress levels. The compressive and flexural strength, bending toughness, and fatigue damage of UHTCC under different fiber ratios were compared, and the fatigue properties of hybrid fiber UHTCC were verified. The results reveal that hybrid fiber exerts a more pronounced effect on toughness, augmenting the maximum folding ratio by 23.7%. Single-doped steel fiber UHTCC exhibits a characteristic strain-softening phenomenon attributable to inadequate fiber content, whereas the bending toughness index of hybrid fiber UHTCC surpasses that of SF1.5P0 by 18.6%. Under low-stress conditions, UHTCC demonstrates a nearly threefold increase in bending fatigue life with a mere 1% steel fiber content, while the influence of polyvinyl alcohol (PVA) fiber on fatigue life is more significant: with an increase of only 1/5 volume content, the fatigue life increased by 29.8%, reaching a maximum increase of 43.2% at 1/4 volume content. Furthermore, the fatigue damage accumulation curve of UHTCC follows a three-stage inverted S-shaped trajectory. The inclusion of PVA fiber facilitates early initiation of stable cracking during the fatigue failure process, thereby advancing the entire strain stability development stage and mitigating external load forces through the proliferation of micro-cracks. Consequently, compared to SF1P0, the ε 0 of SF1P5 experiences a significant increase, reaching 143.43%.

As a new type of backfill material, Self-compacting solidified soil (SCSS) takes the abandoned slurry of cast-in-place piles after dewatering and reduction as the main raw material, which brings a problem of coordinating the working performance with the mechanical property under the condition of high mobility. In this paper, hydroxypropyl methyl cellulose (HPMC) and metakaolin were introduced as additives to solve this problem. First, the workability and mechanical properties of SCSS were regulated and optimized by means of the water seepage rate test, the flowability test, and the unconfined compressive strength test. Second, this study also used X-ray diffraction (XRD) and scanning electron microscopy (SEM) to investigate the effects of HPMC and metakaolin on the physical phase and microstructure of SCSS. In this way, the results showed that there was a significant impact on the flowability of SCSS, that is, when the dosage reached 0.3%, the water seepage rate of SCSS was reduced to less than 1%, and the compressive strength at 7 days reached its peak. At the same time, HPMC weakened the strength growth of SCSS in the age period of 7 days to 14 days. However, the addition of metakaolin promoted its compressive strength. XRD analysis showed that the additives had no significant effects on the physical phases. And, from the SEM results, it can be seen that although the water-retaining effect of HPMC makes hydration of cement more exhaustive, more ettringite (AFt) can be observed in the microstructure. In addition, it can be observed that the addition of metakaolin can generate more hydrated calcium silicate (C-S-H) due to the strong surface energy possessed by metakaolin. As a result of the above factors, SCSS filled the voids between particles and improved the interface structure between particles, thus enhanced the compressive strength.

Motivation: Deep graph learning (DGL) has been widely employed in the realm of ligand-based virtual screening. Within this field, a key hurdle is the existence of activity cliffs (ACs), where minor chemical alterations can lead to significant changes in bioactivity. In response, several DGL models have been developed to enhance ligand bioactivity prediction in the presence of ACs. Yet, there remains a largely unexplored opportunity within ACs for optimizing ligand bioactivity, making it an area ripe for further investigation., Results: We present a novel approach to simultaneously predict and optimize ligand bioactivities through DGL and ACs (OLB-AC). OLB-AC possesses the capability to optimize ligand molecules located near ACs, providing a direct reference for optimizing ligand bioactivities with the matching of original ligands. To accomplish this, a novel attentive graph reconstruction neural network and ligand optimization scheme are proposed. Attentive graph reconstruction neural network reconstructs original ligands and optimizes them through adversarial representations derived from their bioactivity prediction process. Experimental results on nine drug targets reveal that out of the 667 molecules generated through OLB-AC optimization on datasets comprising 974 low-activity, noninhibitor, or highly toxic ligands, 49 are recognized as known highly active, inhibitor, or nontoxic ligands beyond the datasets' scope. The 27 out of 49 matched molecular pairs generated by OLB-AC reveal novel transformations not present in their training sets. The adversarial representations employed for ligand optimization originate from the gradients of bioactivity predictions. Therefore, we also assess OLB-AC's prediction accuracy across 33 different bioactivity datasets. Results show that OLB-AC achieves the best Pearson correlation coefficient (r2) on 27/33 datasets, with an average improvement of 7.2%-22.9% against the state-of-the-art bioactivity prediction methods., Availability and Implementation: The code and dataset developed in this work are available at github.com/Yueming-Yin/OLB-AC., (© The Author(s) 2024. Published by Oxford University Press.)

Very high-resolution remote sensing images hold promising applications in ground observation tasks, paving the way for highly competitive solutions using image processing techniques for land cover classification. To address the challenges faced by convolutional neural network (CNNs) in exploring contextual information in remote sensing image land cover classification and the limitations of vision transformer (ViT) series in effectively capturing local details and spatial information, we propose a local feature acquisition and global context understanding network (LFAGCU). Specifically, we design a multidimensional and multichannel convolutional module to construct a local feature extractor aimed at capturing local information and spatial relationships within images. Simultaneously, we introduce a global feature learning module that utilizes multiple sets of multi-head attention mechanisms for modeling global semantic information, abstracting the overall feature representation of remote sensing images. Validation, comparative analyses, and ablation experiments conducted on three different scales of publicly available datasets demonstrate the effectiveness and generalization capability of the LFAGCU method. Results show its effectiveness in locating category attribute information related to remote sensing areas and its exceptional generalization capability. Code is available at https://github.com/lzp-lkd/LFAGCU ., (© 2024. The Author(s).)

The continuous advancement in the field of flexible and wearable electronics has led to increased research interest in safe, low-cost, and flexible zinc-ion batteries, particularly with a focus on flexible electrolytes. In this study, we present a leather gel electrolyte (LGE) that offers robust mechanical properties and an excellent electrochemical performance. LGE exhibits an ionic conductivity of 1.36 × 10 -2 S cm -1 and achieves a capacity of 303.7 mAh g -1 in flexible zinc-manganese dioxide batteries. Even after 1000 cycles, the capacity retention remains above 90%, demonstrating outstanding performance in protecting the zinc anode. Furthermore, such a flexible battery shows good resistance to damage due to the strong mechanical strength originating from leather. Notably, LGE utilizes green and sustainable leather as a raw material, making it a promising option for sustainable flexible devices.

A Prussian blue analogue was synthesized using biomass leather waste as a precursor by doping with Co 2+ ions. This material, demonstrates good performance in both the oxygen reduction reaction and oxygen evolution reaction, and exhibits excellent charge-discharge performance and stability in zinc-air batteries.

With the extensive industrialization and urbanization taking place in China during the recent decades, land use throughout the country has experienced profound changes influenced not only by the demand for population growth and living standard improvement but also by the constraints of series of land use policies. However, whether the conflict between the expansion of settlement land (SL) and the loss of cultivated land (CL) have been resolved at the national scale or transferred between the local regions remains unclear. Based on yearly ESA CCI land use and land cover products from 1992 to 2020, the long-term trends of quantity and spatial pattern of SL expansion and CL change in China from national and local views were investigated using trend statistic methods, and finally a comprehensive zoning framework was proposed to recognize the trade-off and synergies relationships between SL expansion and CL change. There are a continuous expansion of SL with global linear trends showing three breakpoints in 2000, 2005, and 2012, and a fluctuation decline of CL presented with four breakpoints in 1997, 2002, 2006, and 2013. Aggregation and dispersion tendencies with linear characteristics of SL expansion and CL change were found with breakpoints in 2001, 2008, 2012, and 2016 and breakpoints in 2001 and 2010, respectively. A spotty spatial pattern of SL was shown spatially coincident with urban agglomerations in China while the planar continuous characteristic was found for CL. Local counties were classified into five tradeoff and synergies zones (TSZs), where general synergies (G-S) and decoupling (D) of SL expansion and CL change were rare cases and the different change in quantity and trend of SL expansion and CL change in local counties was concealed by the national trend. A few scattered counties were belonging to G-S and D TSZs, while most of the counties in the central-east and western China were in General-Tradeoff (G-T) and Superior-Tradeoff (S-T) TSZs. Counties in south and north China with higher percentages of CL were more prevalent in Superior-Synergy (S-S) TSZ. Our findings explicated the complex relationships between SL expansion and CL change of China at the national scale and in local counties, which pointed out the differences of unified land use management activities across scales and could provide insights for future policy-making and management measures of land use to both ensure the national food security and promote regional sustainable development more synchronously., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Site specific biotinylation of AviTagged recombinant proteins using BirA enzyme is a widely used protein labeling technology. However, due to the incomplete biotinylation reactions and the lack of a purification method specific for the biotinylated proteins, it is challenging to purify the biotinylated sample when mixed with the non-biotinylated byproduct. Here, we have developed a monoclonal antibody that specifically recognizes the non-biotinylated AviTag but not the biotinylated sequence. After a ten-minute incubation with the resin that is conjugated with the antibody, the non-biotinylated AviTagged protein is trapped on the resin while the fully biotinylated material freely passes through. Therefore, our AviTrap (anti-AviTag antibody conjugated resin) provides an efficient solution for enriching biotinylated AviTagged proteins via a simple one-step purification., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Lu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Lane detection under extreme conditions presents a highly challenging task that requires capturing each crucial pixel to predict the complex topology of lane lines and differentiate the various lane types. Existing methods predominantly rely on deep feature extraction networks with substantial parameters or the fusion of multiple prediction modules, resulting in large model sizes, embedding difficulties, and slow detection speeds. This article proposes a Proportional Feature Pyramid Network (P-FPN) through fusing the weights into the FPN for lane detection. For obtaining a more accurately detecting result, the cross refinement block is introduced in the P-FPN network. The cross refinement block takes the feature maps and anchors as inputs and gradually refines the anchors from high to low level feature maps. In our method, the high-level features are explored to predict lanes coarsely while local-detailed features are leveraged to improve localization accuracy. Extensive experiments on two widely used lane detection datasets, The Chinese Urban Scene Benchmark for Lane Detection (CULane) and the TuSimple Lane Detection Challenge (TuSimple) datasets, demonstrate that the proposed method achieves competitive results compared with several state-of-the-art approaches., Competing Interests: The authors declare there are no competing interests., (©2024 Hui et al.)

Background: Accumulating studies demonstrated that resistance of colon cancer (CC) to 5-fluorouracil (5-FU) contributes to adverse prognosis. We investigated how Kruppel-like factor 4 (KLF4) affected 5-FU resistance and autophagy in CC cells., Methods: KLF4 expression and its downstream target gene RAB26 in CC tissues was analyzed by bioinformatics analysis, and the effect of abnormal KLF4 expression on prognoses of CC patients was predicted. Luciferase reporter assay detected the targeted relationship between KLF4 and RAB26. The viability and apoptosis of CC cells were analyzed by CCK-8 and flow cytometry. The formation of intracellular autophagosomes was detected by confocal laser scanning microscopy and immunofluorescence staining. The mRNA and protein levels were assayed by qRT-PCR and western blot. A xenograft animal model was constructed to verify the function of KLF4. Rescue assay was employed to verify whether KLF4/RAB26 could affect 5-FU resistance in CC cells through autophagy., Results: KLF4 and RAB26 were lowly expressed in CC. KLF4 correlated with patients' survival. KLF4 was down-regulated in 5-FU resistant CC cells. KLF4 overexpression suppressed the proliferation and 5-FU resistance of CC cells, and inhibited LC3 II/I expression and autophagosome formation. Autophagy activator Rapamycin or sh-RAB26 treatment reversed the impact of KLF4 overexpression on 5-FU resistance. In vivo assay verified that KLF4 inhibited 5-FU resistance in CC cells. Rescue experiments revealed that KLF4 targeted RAB26 to inhibit CC cell autophagy, resulting in decreasing the resistance to 5-FU., Conclusion: KLF4 strengthened the sensitivity of CC cells to 5-FU by targeting RAB26 to restrain autophagy pathway.

Unravelling the evolution of landscape patterns is essential to understand regional socio-ecological processes and to solve conflicts between environment protection and human development. However, the role of landscape transition in regional landscape pattern evolution remains unclear. Taking 325 county-level areas in the middle reaches of the Yangtze River (MRYR) as an example, this study explored the spatiotemporal associations between landscape quantity and pattern from the 1970s to 2020. Employing the methods of landscape metrics and trend and correlation analysis, associations between landscape transition and landscape pattern were found. The main results were as follows: (1) From the 1970s to 2020, urban land nearly doubled from 0.93 to 1.89 million km 2 . Arable land and forest showed the largest quantity reductions of 0.88 million km 2 and 0.28 million km 2 , respectively. Other landscapes showed both decreasing and increasing trends with a spatial overlap among counties. (2) Transition in landscape quantity drives the change in landscape patches, thus affecting the landscape pattern in counties. The percentage of landscape area at the class level (CPLAND) showed relative changes in the quantities of landscape categories in each observation year, but their extreme outliers presented larger changes. (3) Diverse correlation coefficients in terms of magnitude and direction suggested that the transition from natural landscape to human-influenced landscape and the reverse processes occurred. Aggregation and diversity metrics showed spatial interaction with similar distances and the perimeter-area fractal dimension (PAFRAC) showed spatial autocorrelation at local scale. Optimal bandwidths among arable land, forest, and urban land (129.2 km) revealed direct spatial interactions and causal relationships, as did waters and unused land (66.7 km). The findings explained the evolution of landscape patterns and highlighted key areas where various landscape changes occurred, and can provide scientific support for policy-making in regional landscape transition governance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

High-entropy oxides (HEOs) can be well suited for lithium-ion battery anodes because of their multi-principal synergistic effect and good stability. The appropriate selection and combination of elements play a crucial role in designing conversion-type anode materials with outstanding electrochemical performance. In this study, we have successfully built a single-phase spinel-structured HEO material of (Mn 0.23 Fe 0.23 Co 0.22 Cr 0.19 Zn 0.13 ) 3 O 4 (HEO-MFCCZ). When the HEO-MFCCZ materials transform into a coexisting state of amorphous and nanocrystalline structures during the cycling process, the inert Zn element can initiate a pegging effect, causing enhanced stability. The transition also introduces many defect sites, effectively reducing the potential barrier for ion transport and accelerating ion transport. The increased electronic and ionic conductivities and pseudocapacitive contribution significantly enhance the rate performance. As a result, a unique and practical approach is provided for developing anode materials for lithium-ion batteries.

Simulated Annealing (SA) algorithm is not effective with large optimization problems for its slow convergence. Hence, several parallel Simulated Annealing (pSA) methods have been proposed, where the increase of searching threads can boost the speed of convergence. Although satisfactory solutions can be obtained by these methods, there is no rigorous mathematical analyses on their effectiveness. Thus, this article introduces a probabilistic model, on which a theorem about the effectiveness of multiple initial states parallel SA (MISPSA) has been proven. The theorem also demonstrates that the increasing parallelism in pSA algorithm with the reducing of search depth in each thread could obtain almost the same probability of finding the global optimal solution. We validated our theorem on AutoDock Vina, a widely used molecular docking tool with high accuracy and docking speed. AutoDock Vina uses a pSA strategy to find optimal molecular conformations. Under the premise that the total searching workload (i.e., thread number * iteration depth of each thread) remains unchanged, the docking accuracy from an aggressively parallelized SA searching method is almost the same or even better than those from the default exhaustiveness (parallelism degree) configuration of AutoDock Vina. Taking complex '1hnn' as an example,with the increase (125x) in the number of initial states (from 8 to 1000) and the decrease in the search depth for each thread (from 15540 to 124, or 1/125 of the original search depth), the mean energy is -7.80 and -7.94, while the mean RMSD is 3.4 and 3.14, respectively. The result also implies that a considerable speedup (in this case 125x in theory) can be obtained by a highly parallelized SA algorithm implementation.

Background: Evading immune surveillance is a hallmark for the development of multiple cancer types. Whether immune evasion contributes to the pathogenesis of high-grade prostate cancer (HGPCa) remains an area of active inquiry., Methods: Through single-cell RNA sequencing and multicolor flow cytometry of freshly isolated prostatectomy specimens and matched peripheral blood, we aimed to characterize the tumor immune microenvironment (TME) of localized prostate cancer (PCa), including HGPCa and low-grade prostate cancer (LGPCa)., Results: HGPCa are highly infiltrated by exhausted CD8 + T cells, myeloid cells, and regulatory T cells (TRegs). These HGPCa-infiltrating CD8 + T cells expressed high levels of exhaustion markers including TIM3, TOX, TCF7, PD-1, CTLA4, TIGIT, and CXCL13. By contrast, a high ratio of activated CD8 +  effector T cells relative to TRegs and myeloid cells infiltrate the TME of LGPCa. HGPCa CD8 +  tumor-infiltrating lymphocytes (TILs) expressed more androgen receptor and prostate-specific membran antigen yet less prostate-specific antigen than the LGPCa CD8 +  TILs. The PCa TME was infiltrated by macrophages but these did not clearly cluster by M1 and M2 markers., Conclusions: Our study reveals a suppressive TME with high levels of CD8 + T cell exhaustion in localized PCa, a finding enriched in HGPCa relative to LGPCa. These studies suggest a possible link between the clinical-pathologic risk of PCa and the associated TME. Our results have implications for our understanding of the immunologic mechanisms of PCa pathogenesis and the implementation of immunotherapy for localized PCa., (© 2023 Wiley Periodicals LLC.)

Modern drug discovery typically faces large virtual screens from huge compound databases where multiple docking tools are involved for meeting various real scenes or improving the precision of virtual screens. Among these tools, AutoDock Vina and its numerous derivatives are the most popular and have become the standard pipeline for molecular docking in modern drug discovery. Our recent Vina-GPU method realized 14-fold acceleration against AutoDock Vina on a piece of NVIDIA RTX 3090 GPU in one virtual screening case. Further speedup of AutoDock Vina and its derivatives with graphics processing units (GPUs) is beneficial to systematically push their popularization in large-scale virtual screens due to their high benefit-cost ratio and easy operation for users. Thus, we proposed the Vina-GPU 2.0 method to further accelerate AutoDock Vina and the most common derivatives with new docking algorithms (QuickVina 2 and QuickVina-W) with GPUs. Caused by the discrepancy in their docking algorithms, our Vina-GPU 2.0 adopts different GPU acceleration strategies. In virtual screening for two hot protein kinase targets, RIPK1 and RIPK3, from the DrugBank database, our Vina-GPU 2.0 reaches an average of 65.6-fold, 1.4-fold, and 3.6-fold docking acceleration against the original AutoDock Vina, QuickVina 2, and QuickVina-W while ensuring their comparable docking accuracy. In addition, we develop a friendly and installation-free graphical user interface tool for their convenient usage. The codes and tools of Vina-GPU 2.0 are freely available at https://github.com/DeltaGroupNJUPT/Vina-GPU-2.0, coupled with explicit instructions and examples.

The Chinese central government has been running an intensive exchange program called the Mainland China-Hong Kong Ten Thousand Student Exchange Program since 2012 to support local Hong Kong university students' visits to mainland China, with the aim of promoting exchange and regional cooperation between Hong Kong and mainland China. However, little is known about local Hong Kong university students' views on regional cooperation and whether the program is effective in changing their views. Using a randomized experimental design, we find that most students hold positive views on regional cooperation between Hong Kong and mainland China, but a considerable percentage of students oppose integration with mainland China. We also find that the program is effective in positively changing students' views on certain aspects of regional cooperation related to the free trade zones and the Hong Kong-Zhuhai-Macau Bridge, but is not significantly effective on other aspects of regional cooperation. This study provides the first causal quantitative evidence regarding the impact of the mainland China-Hong Kong exchange program on local university students' views regarding regional cooperation. The findings help inform the public about the prospect of regional cooperation and offer policy implications on youth exchange between mainland China and Hong Kong., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Liu, Li, Zhang, Song, Li and Wu.)

Rapid urbanization has changed the urban spatial form, which directly leads to the emergence of urban informal settlements, and the impact on ecological environment is manifested as the obvious deterioration of urban thermal environment. The thermal environment of informal settlements, which are called urban villages in China, is seriously deteriorated. In the process of urban renewal, we should pay attention to the thermal environment effect of urban villages and promote the sustainable development of cities. However, at present there are few studies on the differences of thermal comfort among urban settlements. Taking Shenzhen as an example city, this paper distinguished several scopes such as urban villages, formal settlements and non-urban areas, then analyzed the pattern characteristics of urban thermal comfort by using the Modified Temperature and Humidity Index (MTHI), and finally explored the spatial relationship between thermal comfort and various environmental factors through spatial regression models. The results show that (1) thermal comfort has significant spatial autocorrelation and the thermal environment centers are clustered in built-up areas of Shenzhen city. The overall MTHI of urban villages is relatively the highest, and the dominant thermal comfort level in summer is sultry and hot. (2) According to the Spatial Error Model, the green space coverage represented by NDVI has the strongest mitigation effect on urban thermal comfort, and the building density has an obvious aggravating effect on the muggy environment. Both of them have more obvious effects on the thermal comfort of informal settlements. (3) The current thermal environment of urban settlements cannot be ignored, especially in urban villages. In the process of urban renewal, heat dissipation should be considered emphatically. Increasing urban green area and decreasing building density will help to improve urban thermal environment. The study can provide suggestions for urban renewal from the perspective of improving thermal environment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier B.V.)

Since the Coronavirus Disease 2019 (COVID-19) outbreak, unconventional cell line development (CLD) strategies have been taken to enable development of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-neutralizing antibodies at expedited speed. We previously reported a novel chemistry, manufacturing, and control (CMC) workflow and demonstrated a much-shortened timeline of 3-6 months from DNA to investigational new drug (IND) application. Hereafter, we have incorporated this CMC strategy for many SARS-CoV-2-neutralizing antibody programs at WuXi Biologics. In this paper, we summarize the accelerated development of a total of seven antibody programs, some of which have received emergency use authorization  approval in less than 2 years. Stable pools generated under good manufacturing practice (GMP) conditions consistently exhibited similar productivity and product quality at different scales and batches, enabling rapid initiation of phase I clinical trials. Clones with comparable product quality as parental pools were subsequently screened and selected for late-stage development and manufacturing. Moreover, a preliminary stability study plan was devised to greatly reduce the time required for final clone determination and next-generation sequencing-based viral testing was implemented to support rapid conditional release of the master cell bank for GMP production. The successful execution of these COVID-19 programs relies on our robust, fit for purpose, and continuously improving CLD platform. The speed achieved for pandemic-related biologics development may innovate typical biologics development timelines and become a new standard in the industry., (© 2022 Wiley Periodicals LLC.)

Background: Prolonged postoperative ileus (PPOI) is a major complication in patients undergoing colorectal resection. The aim of this study was to analyze the risk factors contributing to PPOI, and to develop an effective nomogram to determine the risks of this population., Methods: A total of 1,254 patients with colorectal cancer who underwent radical colorectal resection at Fujian Cancer Hospital from March 2016 to August 2021 were enrolled as a training cohort in this study. Univariate analysis and multivariate logistic regressions were performed to determine the correlation between PPOI and clinicopathological characteristics. A nomogram predicting the incidence of PPOI was constructed. The cohort of 153 patients from Fujian Provincial Hospital were enrolled as a validation cohort. Internal and external validations were used to evaluate the prediction ability by area under the receiver operating characteristic curve (AUC) and a calibration plot., Results: In the training cohort, 128 patients (10.2%) had PPOI after colorectal resection. The independent predictive factors of PPOI were identified, and included gender, age, surgical approach and intraoperative fluid overload. The AUC of nomogram were 0.779 (95% CI: 0.736-0.822) and 0.791 (95%CI: 0.677-0.905) in the training and validation cohort, respectively. The two cohorts of calibration plots showed a good consistency between nomogram prediction and actual observation., Conclusions: A highly accurate nomogram was developed and validated in this study, which can be used to provide individual prediction of PPOI in patients after colorectal resection, and this predictive power can potentially assist surgeons to make the optimal treatment decisions., (© 2022. The Author(s).)

The reduction of carbon dioxide (CO 2 ) emissions and sustainable development in low-carbon ways are of great significance to urban agglomerations. However, few studies are exploring the relationship between CO 2 emissions and socioeconomic development at city levels from the perspective of clusters of regions. Based on the open data of inventory for anthropogenic CO 2 emissions, nighttime light data, and population dataset as a proxy for the socioeconomic development levels of urban agglomerations, we used Mann-Kendall trend test, Tapio decoupling analysis, and spatial autocorrelation analysis to explore the spatiotemporal association of CO 2 emissions and the impact of socioeconomic development on emissions in the nineteen urban agglomerations in China. Findings showed that the growth of CO 2 emissions in China was primarily concentrated in urban agglomerations. The CO 2 emissions in eastern coastal and northern urban agglomerations were much higher than those in other areas, while the emissions in western urban agglomerations were the lowest. The periodic characteristics of CO 2 emissions were consistent with China's five-year development plan. Urban agglomerations in the early stage from 2000 to 2002 or with developed and stable industrial structures tended to achieve decoupling. High-high (HH) clusters of socioeconomic development with CO 2 emissions were mainly distributed in urban agglomerations of the Beijing-Tianjin-Hebei region (BTH), the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), Yangtze River Delta (YRD), Huhhot-Baotou-Ordos-Yulin (HBOY), Shandong Peninsula (SP), and Central Shanxi (CS). Most of the clusters except those in HBOY shrunk from 2000 to 2010 and remained relatively stable from 2010 to 2019. These urban agglomerations should promote synergistic emission reduction. High-low (HL) clusters mostly appeared in central cities with a high socioeconomic level and surrounding cities with low CO 2 emissions s, i.e., in urban agglomerations of Chengdu-Chongqing region (CC), the Beibu Gulf (BG), and Lanzhou-Xining (LX). These urban agglomerations with prominent polarization phenomena should adhere to regional overall coordination and thus minimize total regional costs of CO 2 emission reduction. The results could provide references for the synergistic reduction of CO 2 emissions and the coordinated development in urban agglomerations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier Ltd.)

Topological order is a new quantum phase that is beyond Landau's symmetry-breaking paradigm. Its defining features include robust degenerate ground states, long-range entanglement and anyons. It was known that R and F matrices, which characterize the fusion-braiding properties of anyons, can be used to uniquely identify topological order. In this article, we explore an essential question: how can the R and F matrices be experimentally measured? We show that the braidings, i.e. the R matrices, can be completely determined by the half braidings of boundary excitations due to the boundary-bulk duality and the anyon condensation. The F matrices can also be measured by comparing the quantum states involving the fusion of three anyons in two different orders. Thus we provide a model-independent experimental protocol to uniquely identify topological order. By using quantum simulations based on a toric code model with boundaries encoded in three- and four-qubit systems and state-of-the-art technology, we obtain the first experimental measurement of R and F matrices by means of an NMR quantum computer at room temperature., (© The Author(s) 2022. Published by Oxford University Press on behalf of China Science Publishing & Media Ltd.)

The Guangdong-Hong Kong-Macao Greater Bay Area urban agglomeration is an urban agglomeration with some of the most intensive urbanization since 1980s. A large amount of cultivated land, forest land, water bodies and other land types in the region has been occupied by construction land, resulting in fragmented ecological landscapes and biodiversity in the region and causing many other ecological problems. Based on this, this paper takes the Guangdong-Hong Kong-Macao Greater Bay Area as a case study, constructs an ecological network of the dispersion scale of five species from 1990 to 2020 based on a morphological spatial pattern analysis (MSPA) method, identifies the ecological groups in the network and uses the core node-based community evolution path tracking algorithm to analyze the ecological groups in order to explore the changes of ecological network connectivity at different scales in the region and to reveal the overall and local characteristics and changes of the migratory space of terrestrial mammals with different dispersion capabilities. The research results show that: (1) From 1990 to 2020, the area of construction land in the Guangdong-Hong Kong-Macao Greater Bay Area increased sharply, with good connectivity in the northwest, southwest and eastern regions and poor connectivity in the central region. (2) There are obvious differences between the overall and local changes in the connectivity trends of multi-scale regional ecological networks. On the whole, the overall ecological connectivity of the ecological network at each scale showed a gradual upward trend, and the overall connectivity index IIC and the possible connectivity index PC gradually increased with the increase of the maximum dispersal distance of species. From the perspective of local patches, the larger the species dispersion scale, the larger the value of the revised betweenness centrality index and the patch possible connectivity index. (3) The distribution of ecological groups at different species dispersion scales is different, and the smaller the dispersal scale of the species, the greater the distribution of ecological groups. Small-scale species are limited by the maximum dispersal distance, and the range of their ecological groups is generally small. Small-scale (3 km), mesoscale (10 km) and large-scale (30 km) core nodes of ecological groups show a gradual increase trend, and the overall connectivity of ecological groups has improved. However, the core nodes of the extra-large-scale (60 km) and ultra-large-scale (100 km) ecological groups show a trend of decreasing fluctuations, and the overall connectivity within the ecological group has declined. This study is helpful to clarify the structural characteristics of regional ecological space and provide a theoretical basis for regional ecological planning.

Materials with interactions between the topology and magnetism are triggering increasing interest. We constructed a two-dimensional (2D) van der Waals heterostructure germanene/Mn 2 S 2 , where the germanene is a quantum spin Hall insulator and Mn 2 S 2 provides antiferromagnetic (AFM) interactions. In this structure, a 2D AFM nodal-line semimetal (NLSM) phase is expected without the spin-orbit coupling (SOC), which is of a high density of states around the Fermi level. The band touching rings originate from the intersection between different spin components of p orbitals of germanene. This result provides a possible 2D realization of NLSMs, which are usually realized in three-dimensional systems. When the SOC is present, a quantum anomalous Hall (QAH) state emerges with the annihilation of the band-touching rings. The nontrivial topology is determined by calculating the Chern number and Wannier charge centers. This provides an alternative platform to realize QAH states. These results could also provide the possibility of further understanding the topological states in NLSM and electronic applications., (© 2022 IOP Publishing Ltd.)

In transition metal dichalcogenides (TMDs), Ising superconductivity with an antisymmetric spin texture on the Fermi surface has attracted wide interest due to the exotic pairing and topological properties. However, it is not clear whether the Q valley with a giant spin splitting is involved in the superconductivity of heavily doped semiconducting 2H-TMDs. Here by taking advantage of a high-quality monolayer WS 2 on hexagonal boron nitride flakes, we report an ionic-gating induced superconducting dome with a record high critical temperature of ∼6 K, accompanied by an emergent nonlinear Hall effect. The nonlinearity indicates the development of an additional high-mobility channel, which (corroborated by first principle calculations) can be ascribed to the population of Q valleys. Thus, multivalley population at K and Q is suggested to be a prerequisite for developing superconductivity. The involvement of Q valleys also provides insights to the spin textured Fermi surface of Ising superconductivity in the large family of transition metal dichalcogenides.

Background: Clinical studies of type 2 (T2) cytokine-related neutralizing antibodies in asthma have identified a substantial subset of patients with low levels of T2 inflammation who do not benefit from T2 cytokine neutralizing antibody treatment. Non-T2 mechanisms are poorly understood in asthma but represent a redefined unmet medical need., Objective: We sought to gain a better understanding of genetic contributions to T2-low asthma., Methods: We utilized an unbiased genome-wide association study of patients with moderate to severe asthma stratified by T2 serum biomarker periostin. We also performed additional expression and biological analysis for the top genetic hits., Results: We identified a novel protective single nucleotide polymorphism at chr19q13.41, which is selectively associated with T2-low asthma and establishes Kallikrein-related peptidase 5 (KLK5) as the causal gene mediating this association. Heterozygous carriers of the single nucleotide polymorphisms have reduced KLK5 expression. KLK5 is secreted by human bronchial epithelial cells and elevated in asthma bronchial alveolar lavage. T2 cytokines IL-4 and IL-13 downregulate KLK5 in human bronchial epithelial cells. KLK5, dependent on its catalytic function, induces epithelial chemokine/cytokine expression. Finally, overexpression of KLK5 in airway or lack of an endogenous KLK5 inhibitor, SPINK5, leads to spontaneous airway neutrophilic inflammation., Conclusion: Our data identify KLK5 to be the causal gene at a novel locus at chr19q13.41 associated with T2-low asthma., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Long-term intensive open-pit mining can have huge impacts on ecosystems and the services they provide, affecting the integrity of ecosystem structures, functions and process and thus the "ecological security" of a whole mining region. The indirect and direct impacts of mining are spatially and temporally complex and therefore ecological security patterns need to be considered. However, to date there has been little research focusing on ecological security patterns in mining regions. This study aims to model and map ecological security and restoration priorities in an intensive open-cut coal mining region accounting for spatio-temporal changes of multiple ecosystem services. Four ecosystem services including habitat quality, carbon sequestration, water yield, and sediment retention were assessed and mapped in 1990, 2000, 2010, and 2020. Next ecological security patterns and restoration priorities were modelled and characterized using the Self-Organizing Feature Map to identify ecological sources, and circuit theory in Linkage Mapper to characterize connectivity and flows. The results showed that habitat quality, carbon sequestration, and water yield services were most affected by vegetation cover changes due to mining exploitation, while sediment retention was influenced by multiple natural factors, especially topography. Ecological sources, corridors, pinch-points and barriers showed various changing trends due to mined and built-up land expansion over time. Ecological source area declined from 1355.08km 2 in 2000 to 584.92 km 2 in 2020, while the number of corridors increased from 17 in 2000 to 25 in 2010 and then decreased to 21 in 2020. Although restoration has been conducted on some mine sites, regional-scale restoration needs greater consideration. This study provides decision-makers and stakeholders with a method for assessing regional-scale ecological security and restoration in a holistic and systematic way moving beyond a single mine, which is critical for balancing ecological security protection with minerals production in intensive mining regions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Most of the news headline generation models that use the sequence-to-sequence model or recurrent network have two shortcomings: the lack of parallel ability of the model and easily repeated generation of words. It is difficult to select the important words in news and reproduce these expressions, resulting in the headline that inaccurately summarizes the news. In this work, we propose a TD-NHG model, which stands for news headline generation based on an improved decoder from the transformer. The TD-NHG uses masked multi-head self-attention to learn the feature information of different representation subspaces of news texts and uses decoding selection strategy of top-k, top-p, and punishment mechanisms (repetition-penalty) in the decoding stage. We conducted a comparative experiment on the LCSTS dataset and CSTS dataset. Rouge-1, Rouge-2, and Rouge-L on the LCSTS dataset and CSTS dataset are 31.28/38.73, 12.68/24.97, and 28.31/37.47, respectively. The experimental results demonstrate that the proposed method can improve the accuracy and diversity of news headlines., (© 2022. The Author(s).)

In this paper, a top-down method is used to partially hydrolyze leather to achieve a leather-based gel electrolyte, and successfully develop a leather-based all-in-one configured flexible supercapacitor. The hierarchical structure of collagen fibers effectively solves the interface problem of flexible supercapacitors, and at the same time endows the gel electrolyte with degradability and reproducibility.

There are many new or potential drug targets in G protein-coupled receptors (GPCRs) without sufficient ligand associations, and it is essential and urgent to implement drug discovery targeting these GPCRs. Precise modeling and representing ligand bioactivities are essential for screening and optimizing these GPCR targeted drugs, yet insufficient samples made it difficult to achieve. Transfer learning intends to solve this by introducing rich information from related source domains with sufficient ligand training samples. In addition, ligand molecules naturally constitute a graph structure, which can be utilized by molecular graph convolutional networks to form an end-to-end multiple-level representation learning. This study proposed a novel method, TL-MGCN, using transfer learning with molecular graph convolutional networks to precisely model and represent bioactivities of ligands targeting GPCRs without sufficient data. The study tested TL-MGCN on a series of 54 representative target domain datasets which cover most human subfamilies, and 44 out of them have less than 600 ligand associations. TL-MGCN obtained an average improvement of 28.74%, 17.28%, 10.05%, 77.83%, 43.65% and 14.65% on correlation coefficient (r 2 ) and 11.90%, 7.43%, 14.86%, 41.46%, 31.02% and 22.94% on root-mean-square error (RMSE) compared with the WDL-RF, transfer learning version of WDL-RF (TR-WDL-RF), attentive FP, GIN, Weave and MPNN predictors, respectively. Users have free access to the web server of TL-MGCN, along with the source codes and datasets, at http://www.noveldelta.com/TL&#95;MGCN for academic purposes., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Ligand molecules naturally constitute a graph structure. Recently, many excellent deep graph learning (DGL) methods have been proposed and used to model ligand bioactivities, which is critical for the virtual screening of drug hits from compound databases in interest. However, pharmacists can find that these well-trained DGL models usually are hard to achieve satisfying performance in real scenarios for virtual screening of drug candidates. The main challenges involve that the datasets for training models were small-sized and biased, and the inner active cliff cases would worsen model performance. These challenges would cause predictors to overfit the training data and have poor generalization in real virtual screening scenarios. Thus, we proposed a novel algorithm named adversarial feature subspace enhancement (AFSE). AFSE dynamically generates abundant representations in new feature subspace via bi-directional adversarial learning, and then minimizes the maximum loss of molecular divergence and bioactivity to ensure local smoothness of model outputs and significantly enhance the generalization of DGL models in predicting ligand bioactivities. Benchmark tests were implemented on seven state-of-the-art open-source DGL models with the potential of modeling ligand bioactivities, and precisely evaluated by multiple criteria. The results indicate that, on almost all 33 GPCRs datasets and seven DGL models, AFSE greatly improved their enhancement factor (top-10%, 20% and 30%), which is the most important evaluation in virtual screening of hits from compound databases, while ensuring the superior performance on RMSE and $r^2$. The web server of AFSE is freely available at http://noveldelta.com/AFSE for academic purposes., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

AutoDock Vina is one of the most popular molecular docking tools. In the latest benchmark CASF-2016 for comparative assessment of scoring functions, AutoDock Vina won the best docking power among all the docking tools. Modern drug discovery is facing a common scenario of large virtual screening of drug hits from huge compound databases. Due to the seriality characteristic of the AutoDock Vina algorithm, there is no successful report on its parallel acceleration with GPUs. Current acceleration of AutoDock Vina typically relies on the stack of computing power as well as the allocation of resource and tasks, such as the VirtualFlow platform. The vast resource expenditure and the high access threshold of users will greatly limit the popularity of AutoDock Vina and the flexibility of its usage in modern drug discovery. In this work, we proposed a new method, Vina-GPU, for accelerating AutoDock Vina with GPUs, which is greatly needed for reducing the investment for large virtual screens and also for wider application in large-scale virtual screening on personal computers, station servers or cloud computing, etc. Our proposed method is based on a modified Monte Carlo using simulating annealing AI algorithm. It greatly raises the number of initial random conformations and reduces the search depth of each thread. Moreover, a classic optimizer named BFGS is adopted to optimize the ligand conformations during the docking progress, before a heterogeneous OpenCL implementation was developed to realize its parallel acceleration leveraging thousands of GPU cores. Large benchmark tests show that Vina-GPU reaches an average of 21-fold and a maximum of 50-fold docking acceleration against the original AutoDock Vina while ensuring their comparable docking accuracy, indicating its potential for pushing the popularization of AutoDock Vina in large virtual screens.

Research on urban thermal environments based on thermal comfort can help formulate effective measures to improve urban thermal and human settlement environments, which is of great significance for improving urban quality, urban climate change adaptation, and sustainable development. Taking 344 municipal administrative districts in China as study areas, the Universal Thermal Climate Index (UTCI) of each city in the last 20 years was calculated to evaluate thermal comfort. We then analyzed the thermal comfort and spatiotemporal heterogeneity of each city during a typical heat wave. Finally, the driving forces of the potential socioeconomic, natural, and landscape factors influencing thermal comfort were analyzed using geographic detectors. The results show that the thermal comfort index had similar spatial patterns and differentiation characteristics in different years, and the interannual variation was not obvious. Cities in the typical heat wave period were mainly distributed in East and Northwest China. The driving factor in the contribution rate of the same index in different years was basically the same and was not affected by the change in years, and the highest contribution rate was the natural factor.

Atmospheric pollution studies have linked diminished human activity during the COVID-19 pandemic to improve air quality. This study was conducted during January to March (2019-2021) in 332 cities in China to examine the association between population migration and air quality, and examined the role of three city attributes (pollution level, city scale, and lockdown status) in this effect. This study assessed six air pollutants, namely CO, NO 2 , O 3 , PM 10 , PM 2.5 , and SO 2 , and measured meteorological data, with-in city migration (WCM) index, and inter-city migration (ICM) index. A linear mixed-effects model with an autoregressive distributed lag model was fitted to estimate the effect of the percent change in migration on air pollution, adjusting for potential confounding factors. In summary, lower migration was associated with decreased air pollution (other than O 3 ). Pollution change in susceptibility is more likely to occur in NO 2 decrease and O 3 increase, but unsusceptibility is more likely to occur in CO and SO 2 , to city attributes from low migration. Cities that are less air polluted and population-dense may benefit more from decreasing PM 10 and PM 2.5 . The associations between population migration and air pollution were stronger in cities with stringent traffic restrictions than in cities with no lockdowns. Based on city attributes, an insignificant difference was observed between the effects of ICM and WCM on air pollution. Findings from this study may gain knowledge about the potential interaction between migration and city attributes, which may help decision-makers adopt air-quality policies with city-specific targets and paths to pursue similar air quality improvements for public health but at a much lower economic cost than lockdowns., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 Turkish National Committee for Air Pollution Research and Control. Production and hosting by Elsevier B.V. All rights reserved.)

Exploring the spatial and temporal distribution characteristics of air quality has become an important topic for the harmonious development of human and nature. Based on the hourly data of CO, O 3 , NO 2 , SO 2 , PM 2.5 and PM 10 of 1427 air quality monitoring stations in China in 2016, this paper calculated the annual mean and annual standard deviation of six air quality indicators at each station to obtain 12 variables. Self-Organizing Maps (SOM) and K-means clustering algorithms were carried out based on MATLAB and SPSS Statistics, respectively. Kriging interpolation was used to get the clustering distribution of air quality and fluctuation in China, and Principal Component Analysis (PCA) was used to analyze the main factors affecting the clustering results. The results show that: (1) Most areas in China are low-value regions, while the high-value region is the smallest and more concentrated. Air quality in northern China is worse, and the annual fluctuations of the indicators are more dramatic. (2) Compared with AQI, AQFI has a strong indication significance for the comprehensive situation of air quality and its fluctuation. (3) The spatial distribution of SOM clustering results is more discriminative, while K-means clustering results have a large proportion of low-mean regions. (4) PM 2.5 , PM 10 and CO are the main pollutants affecting air quality and fluctuation, followed by SO 2 , NO 2 and O 3 .

It remains unknown whether exposure to ambient air pollution can be a mediator linking socioeconomic indicator to health outcome. The present study aims to examine the mediation effect of PM 2.5 air pollution on the association between urban-rural division and the incidence (mortality) rate of male lung cancer. We performed a nationwide analysis in 353 counties (districts) of China between 2006 and 2015. A structural equation model was developed to determine the mediation effect of exposure to PM 2.5 . We also tested whether the findings of the mediation effect of exposure to PM 2.5 are sensitive to the controls of smoking factors and additional air pollutant, and PM 2.5 exposures with different lag structures. According to the results, we found that exposure to PM 2.5 significantly mediated the association between urban-rural division and the incidence rate of male lung cancer. Specifically, there were significant associations between urban-rural division, exposure to PM 2.5 , and the incidence rate of male lung cancer, with PM 2.5 exposure accounting for 29.80% of total urban-rural difference in incidence rates of male lung cancer. A similar pattern of results was observed for the mortality rate of male lung cancer. That is, there was a significant mediation effect by PM 2.5 on the association of the mortality rate with urban-rural division. The findings of exposure to PM 2.5 as a mediator were robust in the three sensitivity analyses. In conclusion, urban-rural difference in exposures to PM 2.5 may be a potential factor that contributes to urban-rural disparity in male lung cancer diseases in China. The findings inform that air pollution management and control may be effective measures to alleviate the great difference in male lung cancer diseases between urban and rural areas in China., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Background: Many studies have reported the effects of PM 2.5 and PM 10 on human health, however, it remains unclear whether particular matter with finer particle size has a greater effect., Objectives: This work aims to examine the varying associations of the incidence rate of female lung cancer with PM 1 , PM 2.5 and PM 10 in 436 Chinese cancer registries between 2014 and 2016., Methods: The effects of PM 1 , PM 2.5 and PM 10 were estimated through three regression models, respectively. Mode l only included particular matter, while Model 2 and Model 3 further controlled for time and location factors, and socioeconomic covariates, respectively. Moreover, two sensitivity analyses were performed to investigate the robustness of three particular matte effects. Then, we examined the modifying role of urban-rural division on the effects of PM 1 , PM 2.5 and PM 10 , respectively., Results: The change in the incidence rate of female lung cancer relative to its mean was 5.98% (95% CI: 3.40, 8.56%) for PM 1 , which was larger than the values of PM 2.5 and PM 10 at 3.75% (95% CI: 2.33, 5.17%) and 1.57% (95% CI: 0.73, 2.41%), respectively. The effects of three particular matters were not sensitive in the two sensitivity analyses. Moreover, urban-rural division positively modified the associations of the incidence rate of female lung cancer with PM 1 , PM 2.5 and PM 10 ., Conclusions: The effect on the incidence rate of female lung cancer was greater for PM 1 , followed by PM 2.5 and PM 10 . There were positive modifying roles of urban-rural division on the effects of three particular matters. The finding supports the argument that finer particular matters are more harmful to human health, and also highlights the great significance to develop guidelines for PM 1 control and prevention in Chinese setting., (© 2022. The Author(s).)

Previous Studies, such as the evaluation of the supply of and demand for regional medical resources and carrying capacity assessments, require further development. This paper aims to evaluate the carrying capacity and spatial distribution of medical resources in Shenzhen from the perspective of supply and demand, and to conduct a time-series variation of the coupling coordination degree from 1986 to 2019. The two-step floating catchment area method was employed to quantify the carrying capacity and coupling coordination degree method and spatial autocorrelation analysis were applied to analyze spatial distribution between supply and demand. The results were as follows. (1) The carrying capacity index in more than 50% of the districts was classified as low-grade. The percentage of regions with good grades was 8.27%. The regions with a high carrying capacity were distributed in the central and southeastern areas. (2) The coupling coordination continued to rise, increasing from 0.03397 in 1986 to 0.33627 in 2019. (3) The level of supply and demand for medical resources in Shenzhen increased from 1986 to 2019, and the highest degree of compatibility between the supply and the population size was largely concentrated in the western and eastern regions. This research can provide a theoretical reference for Shenzhen to rationally plan medical resources and improve the carrying capacity of medical resources.

Previous studies on the supply and demand of ecosystem services (ES) mainly focused on inter-annual changes, and no studies have explored the impact of demographic change on the ES supply and demand on fine-grained time scales. Thus, taking Shenzhen as an example, the status of ES supply and demand, as well as diurnal population changes and their impacts on cultural services were analyzed at different time periods using mobile phone signaling data, ecological supply-demand ratio (ESDR), Geo-Informatic Tupu, InVEST model and buffer zone. The results showed that the population declines successively on workdays, weekends and holidays, and that the daytime population is greater than the nighttime. Water yield services can basically meet the demand in terms of quantity and spatial distribution, however, carbon sequestration and cultural services showed the opposite results. The main type of ESDR changes in cultural services are the mutual conversion of deficit and balance, and these are concentrated in areas with high forest coverage and small populations, but frequent population changes. In addition, when the fixed population is too large, the use of time-varying population data will conceal the impact of demographic changes on ES supply and demand, and other data are needed for auxiliary analysis. Overall, this study provides a new research perspective for the ES supply and demand and can provide a theoretical basis for refined sustainable urban management., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Controlling the morphology of the metal-organic framework (MOF) for nanosheets is beneficial for understanding their crystal growth kinetics and useful for extending these MOF nanosheets to advanced applications, in particular for gas separation and device integration. However, synthesizing MOF nanosheets with uniform thickness or desirable size still remains challenging. Herein, we provide a crystal dissolution-growth strategy for fabricating dispersible porphyrin MOF nanosheets with lateral dimensions and nanometer thickness. A morphological transition (bulk crystals-nanosheets-bulk crystals) in Zn-TCPP was observed when controlling the crystal growth kinetics by adjusting the reaction parameters (temperature and acidity). These findings encouraged the synthesis of other types of nanosheets (Cu-TCPP, Zn-TCPP (Pd), and Cu-BDC nanosheets). Zn-TCPP (Pd) nanosheets were applied in field-effect transistors and exhibited photoresponse characteristics. This work demonstrates a new strategy for obtaining MOF nanosheets and casts a new light upon fabricating two-dimensional inorganic-organic hybrid materials with controlled thickness.

Background: Contrast-induced acute kidney injury (CI-AKI) is a common complication after exposure to contrast media. Renal ischaemia occurs in the initial stage of CI-AKI, however, there are very few effective measures to improve renal perfusion., Methods: A total of 114 patients with an estimated glomerular filtration rate (eGFR) of 60-89 ml/min/1.73m 2 were randomly assigned to two groups: enhanced external counterpulsation (EECP) group (N = 57) and control group (N = 57). Two hours after contrast exposure, EECP group received EECP treatment for 1 h while no intervention was performed control group. The primary outcome was the incidence of serum cystatin C concentration to 10% above the baseline concentration at 24 h after contrast administration. The secondary outcomes were the incidence of CI-AKI (defined as an increase in serum creatinine concentration to ≥0.5 mg/dl or by 25% compare to the baseline after contrast exposure), contrast clearance and adverse clinical events., Results: The primary outcome was observed in 26 patients (6 EECP and 20 control; 11% vs. 35%; P = 0.002). CI-AKI occurred in four patients (0 EECP and 4 control; 0% vs. 7%; P = 0.042). The clearance rate of iopromide in the initial 3 h was significantly different between EECP and control group (59.92 ± 8.84 vs 46.80 ± 9.26 ml/min/1.73 m 2 ; P < 0.001). No adverse clinical events were observed in this study., Conclusions: This study demonstrates that EECP increases the contrast clearance and may have an effect in reducing the risk of CI-AKI. The study has been registered in Chinese Clinical Trial Registry (ChiCTR 2,000,039,190)., (Copyright © 2021. Published by Elsevier Inc.)

With the development of flexible devices, the demand for wearable power sources has increased and gradually become imperative. Zinc-air batteries (ZABs) have attracted lots of research interest due to their high theoretical energy density and excellent safety properties, which can meet the wearable energy supply requirements. Here, the flexibility of energy storage devices is discussed first, followed by the chemistries and development of flexible ZABs. The design of flexible electrodes, the properties of solid-state electrolytes (SSEs), and the construction of deformable structures are discussed in depth. The researchers working on flexible energy storage devices will benefit from the work., (© 2021 The Authors. Advanced Science published by Wiley-VCH GmbH.)

With the rapid development of Internet of Things (IoT) technology, IoT terminal nodes are facing many challenges in data storage, distribution, and data management. In particular, in the IoT terminal nodes considering access cost, the corresponding data distribution and storage are professional, complex, and miscellaneous. Based on the abovementioned current situation, this article innovatively proposes a complex sensor data placement algorithm based on the cloud storage distribution of IoT terminal nodes. Under this algorithm, the accurate division of IoT data I/O methods is realized through reasonable configuration. Through the adaptive sensing algorithm, while fully considering the access cost of the algorithm, the performance of the IoT data storage system is further optimized. In the corresponding terminal node load balancing problem, this article innovatively proposes the terminal node data sorting and distribution algorithm through the node data. The sorting and distribution algorithm realizes the precise segmentation of the IoT data to be processed, thereby realizing the improvement of data reading and processing speed. Based on the proposed algorithm, this article designs a load balancing cloud storage data distribution optimization system of IoT terminal nodes considering access cost and carries out experimental verification in a real environment. The experimental results show that the data pattern division accuracy corresponding to the proposed distribution strategy is improved to 97.13% and the corresponding data access efficiency is improved to 98.3%, compared with the traditional distribution strategy. Therefore, the data distribution strategy proposed in this article has obvious performance advantages and further promotion value., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2022 Jiansheng Wu et al.)

The electrocatalytic nitrogen reduction reaction (NRR) is known as a promising mean of nitrogen fixation to mitigate the energy crisis and facilitate fertilizer production under mild circumstances. For electrocatalytic reactions, the design of efficient catalysts is conducive to reducing activation energy and accelerating lethargic dynamics. Among them, hollow structural materials possess cavities in their structures, which can slack off the escape rate of N 2 and reaction intermediates, prolong the residence time of N 2 , enrich the reaction intermediates' concentration, and shorten electron transportation path, thereby further enhancing their NRR activity. Here, the basic synthetic strategies of hollow structural materials are introduced first. Then, the recent breakthroughs in hollow structural materials as NRR catalysts are reviewed from the perspective of intrinsic, mesoscopic, and microscopic regulations, aiming to discuss how structures affect and improve the catalytic performance. Finally, the future research directions of hollow structural materials as NRR catalysts are discussed. This review is expected to provide an outlook for optimizing hollow structural NRR catalysts., (© 2021 The Authors. Advanced Science published by Wiley-VCH GmbH.)

The establishment of the road green belt (RGB) is an effective means to reduce particle matter (PM 2.5 ) emissions from road traffic. This study tested the ability of 23 common tree species in Shenzhen to reduce PM 2.5 concentrations using field investigations and wind tunnel tests. The association between leaf microstructure and individual reduction ability was also analyzed. Finally, the impact of three RGB configurations (i.e., arbor, shrub, arbor + shrub) on road PM 2.5 dispersion and deposition was simulated using the ENVI-met three-dimensional aerodynamic model, based on which an optimal RGB configuration was proposed. There were three key findings of the tests. First, the wind speed was the main factor affecting the PM 2.5 concentration (54.2%), followed by vehicle flow (27.7%), temperature (14.2%), and time factor (7.6%). Second, the range of dry deposition velocity (V d ) was 0.04-6.4 m/s, and the dominant dust-retaining plant species were the evergreen trees, Ficus microcarpa and Ficus altissima, and the evergreen shrubs, Codiaeum variegatum and Fagraea ceilanica. A higher proportion of grooves or larger stomata would increase the probability that the blade would capture PM 2.5 . Third, the shrub RGB demonstrated the best performance in terms of pollutant dispersion; its PM 2.5 concentration at the respiratory height (RH, 1.5 m) on the pedestrian crossing was 15-20% lower than the other RGB configurations. In terms of pollutant deposition, the arbor + shrub composite RGB was two-fold better than the other RGB configurations. Moreover, it was more advantageous to plant shrub RGBs in street canyons to achieve a balance between the lowest concentration and the largest deposition of PM 2.5 pollutants. The findings of this study will facilitate the RGB configurations with good dust retention ability., (Copyright © 2021 The Author(s). Published by Elsevier Ltd.. All rights reserved.)