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Abstract Selenium, a crucial antioxidant in the body, has been linked to all-cause and cause-specific mortality. However, the relationship between selenium and mortality in the general population remains unclear. A total of 5449 participants in the National Health and Nutrition Examination Survey (NHANES) (2003–2004, 2011–2016) were analyzed to track participant mortality until December 31, 2019. The COX proportional hazard model, Kaplan‒Meier survival analysis and restricted cubic spline regression analysis were used to investigate the associations. Subgroup analysis was conducted on the basis of age (≤ 60, > 60), sex (male, female), and smoking status (nonsmoker, former smoker, and current smoker). The second quartile was associated with lower all-cause mortality and noncardiovascular mortality (HR and 95% CI 0.61,0.45–0.83;0.59,0.42–0.83, respectively). The third quartile was associated with lower cardiovascular-related mortality (HR and 95% CI 0.49, 0.32–0.76). Elevated serum selenium concentrations were associated with lower all-cause mortality, noncardiovascular mortality (range ≤ 129.82 μg/L), and cardiovascular mortality (range ≤ 129.08 μg/L). Subgroup analysis revealed a positive correlation between the serum selenium concentration (range ≥ 129.82 μg/L) and all-cause mortality among the subgroup of current smokers (p

Abstract Single-cell transcriptomics has emerged as a powerful tool for understanding how different cells contribute to disease progression by identifying cell types that change across diseases or conditions. However, detecting changing cell types is challenging due to individual-to-individual and cohort-to-cohort variability and naive approaches based on current computational tools lead to false positive findings. To address this, we propose a computational tool, scDist, based on a mixed-effects model that provides a statistically rigorous and computationally efficient approach for detecting transcriptomic differences. By accurately recapitulating known immune cell relationships and mitigating false positives induced by individual and cohort variation, we demonstrate that scDist outperforms current methods in both simulated and real datasets, even with limited sample sizes. Through the analysis of COVID-19 and immunotherapy datasets, scDist uncovers transcriptomic perturbations in dendritic cells, plasmacytoid dendritic cells, and FCER1G+NK cells, that provide new insights into disease mechanisms and treatment responses. As single-cell datasets continue to expand, our faster and statistically rigorous method offers a robust and versatile tool for a wide range of research and clinical applications, enabling the investigation of cellular perturbations with implications for human health and disease.

Abstract Cancer immunotherapy has demonstrated significant efficacy in various tumors, but its effectiveness in treating Hepatocellular Carcinoma (HCC) remains limited. Therefore, there is an urgent need to identify a new immunotherapy target and develop corresponding intervention strategies. Bioinformatics analysis has revealed that growth differentiation factor 15 (GDF15) is highly expressed in HCC and is closely related to poor prognosis of HCC patients. The previous study revealed that GDF15 can promote immunosuppression in the tumor microenvironment. Therefore, knocking out GDF15 through gene editing could potentially reverse the suppressive tumor immune microenvironment permanently. To deliver the CRISPR/Cas9 system specifically to HCC, nanocapsules (SNC) coated with HCC targeting peptides (SP94) on their surface is utilized. These nanocapsules incorporate disulfide bonds (SNCSS) that release their contents in the tumor microenvironment characterized by high levels of glutathione (GSH). In vivo, the SNCSS target HCC cells, exert a marked inhibitory effect on HCC progression, and promote HCC immunotherapy. Mechanistically, CyTOF analysis showed favorable changes in the immune microenvironment of HCC, immunocytes with killer function increased and immunocytes with inhibitive function decreased. These findings highlight the potential of the CRISPR‐Cas9 gene editing system in modulating the immune microenvironment and improving the effectiveness of existing immunotherapy approaches for HCC.

To address the performance degradation of cross-domain object detection under various illumination conditions and adverse weather scenarios, this paper introduces a novel method a called Step-wise Domain Adaptation DEtection TRansformer (SDA-DETR). Our approach decomposes the adaptation process into three sequential steps, progressively transferring knowledge from a labeled dataset to an unlabeled one using the DETR (DEtection TRansformer) architecture. Each step precisely reduces domain discrepancy, thereby facilitating effective transfer learning. In the initial step, a target-like domain is constructed as an auxiliary to the source domain to reduce the domain gap at the image level. Then, we adaptively align the source domain and target domain features at both global and local levels. To further mitigate model bias towards the source domain, we develop a token-masked autoencoder (t-MAE) to enhance target domain features at the semantic level. Comprehensive experiments demonstrate that the SDA-DETR outperforms several popular cross-domain object detection methods on three challenging public driving datasets.

Abstract Chemotherapy-induced cardiac damage remains a leading cause of death amongst cancer survivors. Anthracycline-induced cardiotoxicity is mediated by severe mitochondrial injury, but little is known about the mechanisms by which cardiomyocytes adaptively respond to the injury. We observed the translocation of selected mitochondrial tricarboxylic acid (TCA) cycle dehydrogenases to the nucleus as an adaptive stress response to anthracycline-cardiotoxicity in human induced pluripotent stem cell-derived cardiomyocytes and in vivo. The expression of nuclear-targeted mitochondrial dehydrogenases shifts the nuclear metabolic milieu to maintain their function both in vitro and in vivo. This protective effect is mediated by two parallel pathways: metabolite-induced chromatin accessibility and AMP-kinase (AMPK) signaling. The extent of chemotherapy-induced cardiac damage thus reflects a balance between mitochondrial injury and the protective response initiated by the nuclear pool of mitochondrial dehydrogenases. Our study identifies nuclear translocation of mitochondrial dehydrogenases as an endogenous adaptive mechanism that can be leveraged to attenuate cardiomyocyte injury.

Abstract A potential therapeutic target to curb obesity and diabetes is thermogenic beige adipocytes. However, beige adipocytes quickly transition into white adipocytes upon removing stimuli. Here, we define the critical role of cyclin dependent kinase inhibitor 2A (Cdkn2a) as a molecular pedal for the beige-to-white transition. Beige adipocytes lacking Cdkn2a exhibit prolonged lifespan, and male mice confer long-term metabolic protection from diet-induced obesity, along with enhanced energy expenditure and improved glucose tolerance. Mechanistically, Cdkn2a promotes the expression and activity of beclin 1 (BECN1) by directly binding to its mRNA and its negative regulator BCL2 like 1 (BCL2L1), activating autophagy and accelerating the beige-to-white transition. Reactivating autophagy by pharmacological or genetic methods abolishes beige adipocyte maintenance induced by Cdkn2a ablation. Furthermore, hyperactive BECN1 alone accelerates the beige-to-white transition in mice and human. Notably, both Cdkn2a and Becn1 exhibit striking positive correlations with adiposity. Hence, blocking Cdkn2a-mediated BECN1 activity holds therapeutic potential to sustain beige adipocytes in treating obesity and related metabolic diseases.

Network platforms have ushered in a novel propagation model for feminist discourses. The emergence of oriental feminism in society has led to gender-based public opinions surrounding public events becoming a trending topic on Chinese social media. This study uses the 2022 Tangshan restaurant attack as a case study, an incident that sparked widespread discussions across China in 2022. The research gathered 366,602 network communication nodes within a week and examined the communication networks of three types of content nodes (information, opinion, and appeasement) using the complex network modeling method. The findings revealed that all three types of information communication networks exhibit an apparent scale-free characteristic, and the "key minority" of nodes significantly affects information communication. Information-type and appeasement-type Weibo display notable similarities in the quantity and degree distribution of nodes within the communication networks and in the information decay rate. Moreover, authoritative information issuers have become the primary catalyst for information propagation. Conversely, opinion-type Weibo has the widest communication network diameter and features a high degree of participation, multilevel propagation, and a slow decay rate. This indicates that the interaction between opinion leaders and netizens has enhanced the depth and breadth of information diffusion for opinion-type Weibo.

Abstract Flexible perovskite solar cells (f‐PSCs) as a promising power source have grabbed surging attention from academia and industry specialists by integrating with different wearable and portable electronics. With the development of low‐temperature solution preparation technology and the application of different engineering strategies, the power conversion efficiency of f‐PSCs has approached 24%. Due to the inherent properties and application scenarios of f‐PSCs, the study of strain in these devices is recognized as one of the key factors in obtaining ideal devices and promoting commercialization. The strains mainly from the change of bond and lattice volume can promote phase transformation, induce decomposition of perovskite film, decrease mechanical stability, etc. However, the effect of strain on the performance of f‐PSCs has not been systematically summarized yet. Herein, the sources of strain, evaluation methods, impacts on f‐PSCs, and the engineering strategies to modulate strain are summarized. Furthermore, the problems and future challenges in this regard are raised, and solutions and outlooks are offered. This review is dedicated to summarizing and enhancing the research into the strain of f‐PSCs to provide some new insights that can further improve the optoelectronic performance and stability of flexible devices.

Abstract The development of algorithms for remote sensing of water quality (RSWQ) requires a large amount of in situ data to account for the bio-geo-optical diversity of inland and coastal waters. The GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments (GLORIA) includes 7,572 curated hyperspectral remote sensing reflectance measurements at 1 nm intervals within the 350 to 900 nm wavelength range. In addition, at least one co-located water quality measurement of chlorophyll a, total suspended solids, absorption by dissolved substances, and Secchi depth, is provided. The data were contributed by researchers affiliated with 59 institutions worldwide and come from 450 different water bodies, making GLORIA the de-facto state of knowledge of in situ coastal and inland aquatic optical diversity. Each measurement is documented with comprehensive methodological details, allowing users to evaluate fitness-for-purpose, and providing a reference for practitioners planning similar measurements. We provide open and free access to this dataset with the goal of enabling scientific and technological advancement towards operational regional and global RSWQ monitoring.

Modification of RNA with N6-methyladenosine can regulate RNA metabolism. Here they developed scm6A-seq to profile the methylome and transcriptome in single cells, and reveal the functions of m6A modification during oocyte maturation and early embryo development.

Abstract Road damage detection is an important task to ensure road safety and realize the timely repair of road damage. The previous manual detection methods are low in efficiency and high in cost. To solve this problem, an improved YOLOv5 road damage detection algorithm, MN-YOLOv5, was proposed. We optimized the YOLOv5s model and chose a new backbone feature extraction network MobileNetV3 to replace the basic network of YOLOv5, which greatly reduced the number of parameters and GFLOPs of the model, and reduced the size of the model. At the same time, the coordinate attention lightweight attention module is introduced to help the network locate the target more accurately and improve the target detection accuracy. The KMeans clustering algorithm is used to filter the prior frame to make it more suitable for the dataset and to improve the detection accuracy. To improve the generalization ability of the model, a label smoothing algorithm is introduced. In addition, the structure reparameterization method is used to accelerate model reasoning. The experimental results show that the improved YOLOv5 model proposed in this paper can effectively identify pavement cracks. Compared with the original model, the mAP increased by 2.5%, the F1 score increased by 2.6%, and the model volume was smaller than that of YOLOv5. 1.62 times, the parameter was reduced by 1.66 times, and the GFLOPs were reduced by 1.69 times. This method can provide a reference for the automatic detection method of pavement cracks.

Abstract The rapid degradation of magnesium (Mg) alloy implants erodes mechanical performance and interfacial bioactivity, thereby limiting their clinical utility. Surface modification is among the solutions to improve corrosion resistance and bioefficacy of Mg alloys. Novel composite coatings that incorporate nanostructures create new opportunities for their expanded use. Particle size dominance and impermeability may increase corrosion resistance and thereby prolong implant service time. Nanoparticles with specific biological effects may be released into the peri‐implant microenvironment during the degradation of coatings to promote healing. Composite nanocoatings provide nanoscale surfaces to promote cell adhesion and proliferation. Nanoparticles may activate cellular signaling pathways, while those with porous or core–shell structures may carry antibacterial or immunomodulatory drugs. Composite nanocoatings may promote vascular reendothelialization and osteogenesis, attenuate inflammation, and inhibit bacterial growth, thus increasing their applicability in complex clinical microenvironments such as those of atherosclerosis and open fractures. This review combines the physicochemical properties and biological efficiency of Mg‐based alloy biomedical implants to summarize the advantages of composite nanocoatings, analyzes their mechanisms of action, and proposes design and construction strategies, with the purpose of providing a reference for promoting the clinical application of Mg alloy implants and to further the design of nanocoatings.

Quantifying the ecological carrying capacity has emerged as a crucial factor for maintaining ecosystem stability for sustainable development in vulnerable eco-regions. Here, we propose a new framework for ecological carrying capacity quantification suitable for vulnerable eco-regions. We applied this framework to calculate the ecological carrying capacity of Inner Mongolia from 1987-2015 and used a geographical detector to identify the driving factors behind spatial heterogeneity. Our results revealed the following. (1) The above-ground net primary production (ANPP) required to support the ecosystem service of soil conservation (ANPPSC) decreased from northeast to southwest, whereas the distribution pattern of ANPP required to support the ecosystem service of sand fixation (ANPPSF) exhibited a contrary trend. The average annual ANPP required to support the ecosystem service of natural regeneration (ANPPNR) in Inner Mongolia from 1987 to 2015 was 101.27 gCm-2year-1, revealing a similar spatial distribution with ANPP. (2) The total ecological carrying capacity of Inner Mongolian grassland was 78.52 million sheep unit hm-2. The regions with insufficient provisioning service capability accounted for 4.18% of the total area, primarily concentrated in the east and northwest. (3) The average optimal livestock number for grasslands in Inner Mongolia was 1.59 sheep unit hm-2 from 1987-2015, ranging from 0.77 to 1.69 sheep unit hm-2 across different zones. The average ecological carrying capacity of the cold temperate humid, medium-temperate arid, and warm temperate semi-humid regions was less than 1.08 sheep unit m-2, suggesting a need to prohibit grazing in these areas. (4) The primary influencing factors affecting ecological carrying capacity distribution were normalized difference vegetation index (NDVI), precipitation, and soil type. The framework developed herein can help identify sustainable development potential from the ecosystem service perspective and effectively contribute to decision-making in grassland ecosystem management.

While understanding the long-term slip rate of active normal faults is essential for the comprehensive assessment of seismic activity, it is difficult due to the absence of age control in the erosional bedrock region. The preserved sequence of wave-cut platforms in granite allows exploration of the long-term slip rate in the footwall of some normal faults. We investigated wave-cut platforms in the southern Pearl River Delta (PRD), a coastal delta transected by the seismically active Littoral Fault Zone (LFZ) in the northern South China Sea, to derive slip rates and their impacts on the seismic hazard potential. We mapped a flight of four wave-cut platforms (T1–T4), dated the T2 and T4 platforms by 10Be cosmogenic nuclide dating, and used the absolute age to correlate the un-dated platform to global sea-level highstands. Our results allocate the ages of 128 ka, 197 ka, and 239 ka to the upper three wave-cut platforms and yield temporally various uplift rates ranging from 0.30 to 0.38 mm/a during 239–128 ka to 0.09 mm/a since 128 ka. A decrease in the uplift rate, which coincided with a decreased subsidence rate within the PRD in previous work, implied a weakened differential uplift onshore of the LFZ system. Our findings infer that the transgression event occurred as early as marine isotope stage (MIS) 7 in the PRD, consistent with the view that Pleistocene sedimentation began in MIS 5 or earlier in the PRD.

The giant triton snail (Charonia tritonis) is widely distributed in tropical coral reefs in the Indo-West Pacific. Its distribution areas in China include the Penghu Islands, Hengchun Peninsula, and Xisha Islands. In this study, we use Multivariate Analysis of Variance (MANOVA) to compare the live weight and shell length between different shell colors of C. tritonis. In addition, we conducted sequence analysis of the mitochondrial cytochrome oxidase (COI) gene to assess the affinity of C. tritonis with two different shell colors based on the sample we obtained. Then, we constructed phylogenetic trees using the maximum likelihood (ML) and Bayesian Inference methods, and constructed haplotype network diagrams. In addition, we performed Tajima’s D and Fu’s neutrality tests. The results show that The Partial mitochondrial COI sequences of 28 C. tritonis were all 603 base pairs in length, and seven haplotypes were detected from the samples, besides, the gene flow was calculated to be 11.78, the genetic differentiation coefficient was 0.02078. Our results indicated that the population size of C. tritonis remained relatively stable. Besides, the genetic and size differentiation between the two different shell colors was small, and individuals of C. tritonis with different shell colors belong to the same genetic clade. In fact, the two morphotypes could not be distinguished by both genetic and morphometric data. The mitochondrial COI gene fragments of the two different shell colors were sequenced and analyzed to accumulate information about the population genetics of C. tritonis and to provide a scientific basis for the conservation of its species resources.The giant triton snail (Charonia tritonis) is widely distributed in tropical coral reefs in the Indo-West Pacific. Its distribution areas in China include the Penghu Islands, Hengchun Peninsula, and Xisha Islands. In this study, we use Multivariate Analysis of Variance (MANOVA) to compare the live weight and shell length between different shell colors of C. tritonis. In addition, we conducted sequence analysis of the mitochondrial cytochrome oxidase (COI) gene to assess the affinity of C. tritonis with two different shell colors based on the sample we obtained. Then, we constructed phylogenetic trees using the maximum likelihood (ML) and Bayesian Inference methods, and constructed haplotype network diagrams. In addition, we performed Tajima’s D and Fu’s neutrality tests. The results show that The Partial mitochondrial COI sequences of 28 C. tritonis were all 603 base pairs in length, and seven haplotypes were detected from the samples, besides, the gene flow was calculated to be 11.78, the genetic differentiation coefficient was 0.02078. Our results indicated that the population size of C. tritonis remained relatively stable. Besides, the genetic and size differentiation between the two different shell colors was small, and individuals of C. tritonis with different shell colors belong to the same genetic clade. In fact, the two morphotypes could not be distinguished by both genetic and morphometric data. The mitochondrial COI gene fragments of the two different shell colors were sequenced and analyzed to accumulate information about the population genetics of C. tritonis and to provide a scientific basis for the conservation of its species resources.

Abstract Deep learning networks have been successfully applied to transfer functions so that the models can be adapted from the source domain to different target domains. This study uses multiple convolutional neural networks to decode the electroencephalogram (EEG) of stroke patients to design effective motor imagery (MI) brain-computer interface (BCI) system. This study has introduced ‘fine-tune’ to transfer model parameters and reduced training time. The performance of the proposed framework is evaluated by the abilities of the models for two-class MI recognition. The results show that the best framework is the combination of the EEGNet and ‘fine-tune’ transferred model. The average classification accuracy of the proposed model for 11 subjects is 66.36%, and the algorithm complexity is much lower than other models.These good performance indicate that the EEGNet model has great potential for MI stroke rehabilitation based on BCI system. It also successfully demonstrated the efficiency of transfer learning for improving the performance of EEG-based stroke rehabilitation for the BCI system.

The working mechanism of several low-cost electrocatalyst materials is still arguable. Here the authors show a model Fe,Mn/N-C catalyst where the oxygen reduction preferentially takes place on Fe(III) sites with the intermediate spin state (t2g4 eg1) caused by the adjacent Mn-N moieties.

Time- and precision-critical applications, such as autonomous driving, have extremely rigorous standards for continuous high-precision positioning. The importance of precise point positioning (PPP) technology for self-navigation equipment is self-evident by delivering decimeter-/centimeter-level absolute position accuracy in a global coordinate framework. Nevertheless, the prolonged initialization period renders PPP almost too difficult to be widely used for time-critical applications in real transportation scenarios, for example, in city canyons and overpasses. We proposed a method to accomplish continuous decimeter-level positioning by leveraging triple-frequency GNSS observations with an Inertial Navigation System (INS) aiding in urban environments. In the proposed method, the inertial measurements and the original tri-frequency pseudorange and carrier phase measurements are tightly fused in an extended Kalman filter to obtain the optimal state estimate. Afterwards, with precise extra-wide-lane (EWL) and wide-lane (WL) Uncalibrated Phase Delay (UPD) products, the EWL and WL ambiguities can be resolved sequentially to implement instantaneous decimeter-level positioning. Exploiting the short-term high-precision characteristic of the INS, the continuity of the PPP solution can be ameliorated noticeably, and the ability of decimeter-level positioning can be maintained effortlessly throughout the navigation process. With land vehicle data collected, several experiments are undertaken to comprehensively assess the capability of the proposed system in urban scenarios, taking the solution obtained by a commercial post-processing software as the reference. The single-epoch decimeter-level position estimation can be captured instantaneously for WL ambiguity-fixed PPP solutions. Furthermore, for WL ambiguity-fixed PPP/INS-integrated solutions, the position estimation is better than 0.2 m for horizontal components and improved by 40–90% compared with that of the WL ambiguity-fixed PPP solutions. More importantly, the availability rate of positioning accuracy is better than 0.3 m in the horizontal direction and 0.5 m in the up direction reaching 93.91%, whereas it is only 53.78% for WL ambiguity-fixed PPP solutions. Overall, the WL ambiguity-fixed PPP/INS-integrated solutions have the favorable performance to maintain continuous decimeter-level positioning for self-navigation equipment, even if full GNSS outages are encountered.

Abstract High dosage of expensive Pt to catalyze the sluggish oxygen reduction reaction (ORR) on the cathode severely impedes the commercialization of proton exchange membrane fuel cells. Therefore, it is urgent to cut down the Pt catalyst by efficiently improving the ORR activity while maintaining high durability. Herein, magic concave Pt–Zn nanocubes with high‐index faceted Pt skin (Pt78Zn22) are proposed for high‐efficiency catalysis toward proton exchange membrane fuel cells. These unique structural features endow the Pt‐skin Pt78Zn22/KB with a mass activity of 1.18 mA μgPt–1 and a specific activity of 3.64 mA cm–2 for the ORR at 0.9 V (vs RHE). Meanwhile, the H2–O2 fuel cell assembled by this catalyst delivers an ultrahigh peak power density of ≈1449 mW cm–2. Both experiments and theoretical calculations show that the electronic structure of the surface is adjusted, thereby shortening the length of the Pt–Pt bond and reducing the adsorption energy of OH*/O* on the Pt surface. This work demonstrates the synergistic effect of the oxidation‐resistant metal Zn and the construction of Pt‐rich surface engineering. Also, it guides the future development of catalysts for their practical applications in energy conversion technologies and beyond.

Abstract Understanding the relationship between the electronic state of active sites and N2 reduction reaction (NRR) performance is essential to explore efficient electrocatalysts. Herein, atomically dispersed Fe and Mo sites are designed and achieved in the form of well‐defined FeN4 and MoN4 coordination in polyphthalocyanine (PPc) organic framework to investigate the influence of the spin state of FeN4 on NRR behavior. The neighboring MoN4 can regulate the spin state of Fe center in FeN4 from high‐spin (dxy2dyz1dxz1dz21dx2−y21) to medium‐spin (dxy2dyz2dxz1dz21), where the empty d orbitals and separate d electron favor the overlap of Fe 3d with the N 2p orbitals, more effectively activating N≡N triple bond. Theoretical modeling suggests that the NRR preferably takes place on FeN4 instead of MoN4, and the transition of Fe spin state significantly lowers the energy barrier of the potential determining step, which is conducive to the first hydrogenation of N2. As a result, FeMoPPc with medium‐spin FeN4 exhibits 2.0 and 9.0 times higher Faradaic efficiency and 2.0 and 17.2 times higher NH3 yields for NRR than FePPc with high‐spin FeN4 and MoPPc with MoN4, respectively. These new insights may open up opportunities for exploiting efficient NRR electrocatalysts by atomically regulating the spin state of metal centers.

The Landsat series has marked the history of Earth observation by performing the longest continuous imaging program from space. The recent Landsat-9 carrying Operational Land Imager 2 (OLI-2) captures a higher dynamic range than sensors aboard Landsat-8 or Sentinel-2 (14-bit vs. 12-bit) that can potentially push forward the frontiers of aquatic remote sensing. This potential stems from the enhanced radiometric resolution of OLI-2, providing higher sensitivity over water bodies that are usually low-reflective. This study performs an initial assessment on retrieving water quality parameters from Landsat-9 imagery based on both physics-based and machine learning modeling. The concentration of chlorophyll-a (Chl-a) and total suspended matter (TSM) are retrieved based on physics-based inversion in four Italian lakes encompassing oligo to eutrophic conditions. A neural network-based regression model is also employed to derive Chl-a concentration in San Francisco Bay. We perform a consistency analysis between the constituents derived from Landsat-9 and near-simultaneous Sentinel-2 imagery. The Chl-a and TSM retrievals are validated using in situ matchups. The results indicate relatively high consistency among the water quality products derived from Landsat-9 and Sentinel-2. However, the Landsat-9 constituent maps show less grainy noise, and the matchup validation indicates relatively higher accuracies obtained from Landsat-9 (e.g., TSM R2 of 0.89) compared to Sentinel-2 (R2 = 0.71). The improved constituent retrieval from Landsat-9 can be attributed to the higher signal-to-noise (SNR) enabled by the wider dynamic range of OLI-2. We performed an image-based SNR estimation that confirms this assumption.

Although defensins have been isolated from a variety of metazoan, their role in cellular immunity has not been answered. In the study, we found that the hemocytes of the Manila clams Ruditapes philippinarum release defensin (designated as Rpdef3) in response to Vibrio parahaemolyticus challenge. The antimicrobial Rpdef3 was proved to be involved in the extracellular traps (ETs) that hemocytes released in response to Vibrio challenge. Scanning electron microscopy observation proved the patterns how ETs eliminate invading bacteria. Furthermore, Rpdef3 involved in ETs had broad-spectrum antimicrobial effect on both Gram-negative bacteria and Gram-positive bacteria. ELISA assay revealed that Rpdef3 could bind lipopolysaccharides and peptidoglycan in a dose-dependent manner. As concerned to the antibacterial mechanisms, Rpdef3 can cause bacterial membrane permeabilization, leading to cell death. As a result, Rpdef3 might contribute to the trap and the elimination of invading Vibrio in clam ETs. Taken together, our study suggest that the formation of ETs is a defense mechanism triggered by bacterial stimulation, coupled with antibacterial defensin.

This study aims to explore the freight demand network spatial patterns in six provinces of central China from the perspective of the spread of the epidemic and the freight imbalance and breakout. To achieve this purpose, the big data of "cart search" demand information provided by small and medium freight enterprises on the freight information platform are analyzed. 343,690 pieces of freight demand big data on the freight information platform and Python, ArcGIS, UCINET, and Gephi software are used. The results show that: (1) The choke-point of unbalanced freight demand network is Wuhan, and the secondary choke-points are Hefei and Zhengzhou. (2) In southern China, a chain reaction circle of freight imbalance is formed with Wuhan, Hefei, and Nanchang as the centers. In northern China, a chain reaction circle of freight imbalance is formed with Zhengzhou and Taiyuan as the centers. (3) The freight demand of the six provinces in central China exhibits typical characteristics of long tail distribution with large span and unbalanced distribution. (4) The import and export of freight in different cities vary greatly, and the distribution is unbalanced. This study indicates the imbalance difference, chain reaction, keys and hidden troubles posed by the freight demand network. From the perspectives of freight transfer breakout, freight balance breakout, freight strength breakout, and breakout of freight periphery cities, we propose solutions to breakouts in the freight market in six provinces of central China in the post-epidemic era.

Dissolved organic matter (DOM) plays a key role in forest carbon biogeochemistry by linking soil organic carbon (SOC) sequestration and water fluxes, which is further shaped by elevated atmospheric nitrogen (N) deposition. Although enhanced SOC sequestration was evidenced in tropical forests due to rising N deposition, it remains unclear how long-term N inputs affect soil DOM composition, which regulates SOC sequestration capability due to its mobility and biological instability. Here, the quantity, optical properties, and molecular-level characteristics of soil DOM based on a simulative N deposition experiment with four N addition levels (0, 5, 10, and 15 g m ^−2 yr ^−1 ) were studied in a primary tropical forest in south China. Results showed that 18 year N additions significantly altered soil DOM composition, with an increasing trend in soil dissolved organic carbon content. Medium- (10 g m ^−2 yr ^−1 ) and high-N addition (15 g m ^−2 yr ^−1 ) markedly elevated DOM average molecular weight by 12% and aromaticity, with specific ultraviolet absorbance at 254 nm increasing by 17%, modified aromatic index by 35%, and condensed aromatics by 67%. Medium- and high-N addition also increased recalcitrant DOM components but decreased other DOM components, with increasing percentages of lignin-like, tannin-like, and carboxylic-rich alicyclic molecule-like compounds, and decreasing percentage of more bioavailable contributions with H/C ratio >1.5. Importantly, significant correlations of the SOC content of the heavy fraction with optical properties and with recalcitrant DOM components were observed. These findings suggest that long-term N additions may alter soil DOM composition in a way to benefit soil OC storage in the primary tropical forests. It merits focusing on the mechanisms to association of soil DOM dynamics with SOC sequestration.

Different methods are available for retrieving chlorophyll-a (Chl-a) in inland waters from optical imagery, but there is still a need for an inter-comparison among the products. Such analysis can provide insights into the method selection, integration of products, and algorithm development. This work aims at inter-comparison and consistency analyses among the Chl-a products derived from publicly available methods consisting of Case-2 Regional/Coast Colour (C2RCC), Water Color Simulator (WASI), and OC3 (3-band Ocean Color algorithm). C2RCC and WASI are physics-based processors enabling the retrieval of not only Chl-a but also total suspended matter (TSM) and colored dissolved organic matter (CDOM), whereas OC3 is a broadly used semi-empirical approach for Chl-a estimation. To pursue the inter-comparison analysis, we demonstrate the application of Sentinel-2 imagery in the context of multitemporal retrieval of constituents in some Italian lakes. The analysis is performed for different bio-optical conditions including subalpine lakes in Northern Italy (Garda, Idro, and Ledro) and a turbid lake in Central Italy (Lake Trasimeno). The Chl-a retrievals are assessed versus in situ matchups that indicate the better performance of WASI. Moreover, relative consistency analyses are performed among the products (Chl-a, TSM, and CDOM) derived from different methods. In the subalpine lakes, the results indicate a high consistency between C2RCC and WASI when aCDOM(440) < 0.5 m−1, whereas the retrieval of constituents, particularly Chl-a, is problematic based on C2RCC for high-CDOM cases. In the turbid Lake Trasimeno, the extreme neural network of C2RCC provided more consistent products with WASI than the normal network. OC3 overestimates the Chl-a concentration. The flexibility of WASI in the parametrization of inversion allows for the adaptation of the method for different optical conditions. The implementation of WASI requires more experience, and processing is time demanding for large lakes. This study elaborates on the pros and cons of each method, providing guidelines and criteria on their use.

In smartphone indoor positioning, owing to the strong complementarity between pedestrian dead reckoning (PDR) and WiFi, a hybrid fusion scheme of them is drawing more and more attention. However, the outlier of WiFi will easily degrade the performance of the scheme, to remove them, many researches have been proposed such as: improving the WiFi individually or enhancing the scheme. Nevertheless, due to the inherent received signal strength (RSS) variation, there still exist some unremoved outliers. To solve this problem, this paper proposes the first outlier detection and removal strategy with the aid of Machine Learning (ML), so called WiFi-AGNES (Agglomerative Nesting), based on the extracted positioning characteristics of WiFi when the pedestrian is static. Then, the paper proposes the second outlier detection and removal strategy, so called WiFi-Chain, based on the extracted positioning characteristics of WiFi, PDR, and their complementary characteristics when the pedestrian is walking. Finally, a hybrid fusion scheme is proposed, which integrates the two proposed strategies, WiFi, PDR with an inertial-navigation-system-based (INS-based) attitude heading reference system (AHRS) via Extended Kalman Filter (EKF), and an Unscented Kalman Filter (UKF). The experiment results show that the two proposed strategies are effective and robust. With WiFi-AGNES, the minimum percentage of the maximum error (MaxE) is reduced by 66.5%; with WiFi-Chain, the MaxE of WiFi is less than 4.3 m; further the proposed scheme achieves the best performance, where the root mean square error (RMSE) is 1.43 m. Moreover, since characteristics are universal, the proposed scheme integrated the two characteristic-based strategies also possesses strong robustness.

A micro-Doppler signature (m-DS) based on the rotation of drone blades is an effective way to detect and identify small drones. Deep-learning-based recognition algorithms can achieve higher recognition performance, but they needs a large amount of sample data to train models. In addition to the hovering state, the signal samples of small unmanned aerial vehicles (UAVs) should also include flight dynamics, such as vertical, pitch, forward and backward, roll, lateral, and yaw. However, it is difficult to collect all dynamic UAV signal samples under actual flight conditions, and these dynamic flight characteristics will lead to the deviation of the original features, thus affecting the performance of the recognizer. In this paper, we propose a small UAV m-DS recognition algorithm based on dynamic feature enhancement. We extract the combined principal component analysis and discrete wavelet transform (PCA-DWT) time–frequency characteristics and texture features of the UAV’s micro-Doppler signal and use a dynamic attribute-guided augmentation (DAGA) algorithm to expand the feature domain for model training to achieve an adaptive, accurate, and efficient multiclass recognition model in complex environments. After the training model is stable, the average recognition accuracy rate can reach 98% during dynamic flight.

This paper studies the measurement requirements of spectral resolution and radiometric sensitivity to enable the quantitative determination of water constituents and benthic parameters for the majority of optically deep and optically shallow waters on Earth. The spectral and radiometric variability is investigated by simulating remote sensing reflectance (Rrs) spectra of optically deep water for twelve inland water scenarios representing typical and extreme concentration ranges of phytoplankton, colored dissolved organic matter and non-algal particles. For optically shallow waters, Rrs changes induced by variable water depth are simulated for fourteen bottom substrate types, from lakes to coastal waters and coral reefs. The required radiometric sensitivity is derived for the conditions that the spectral shape of Rrs should be resolvable with a quantization of 100 levels and that measurable reflection differences at at least one wavelength must occur at concentration changes in water constituents of 10% and depth differences of 20 cm. These simulations are also used to derive the optimal spectral resolution and the most sensitive wavelengths. Finally, the Rrs spectra and their changes are converted to radiances and radiance differences in order to derive sensor (noise-equivalent radiance) and measurement requirements (signal-to-noise ratio) at the water surface and at the top of the atmosphere for a range of solar zenith angles.

The recent PlanetScope constellation (130+ satellites currently in orbit) has shifted the high spatial resolution imaging into a new era by capturing the Earth’s landmass including inland waters on a daily basis. However, studies on the aquatic-oriented applications of PlanetScope imagery are very sparse, and extensive research is still required to unlock the potentials of this new source of data. As a first fully physics-based investigation, we aim to assess the feasibility of retrieving bathymetric and water quality information from the PlanetScope imagery. The analyses are performed based on Water Color Simulator (WASI) processor in the context of a multitemporal analysis. The WASI-based radiative transfer inversion is adapted to process the PlanetScope imagery dealing with the low spectral resolution and atmospheric artifacts. The bathymetry and total suspended matter (TSM) are mapped in the relatively complex environment of Venice lagoon during two benchmark events: The coronavirus disease 2019 (COVID-19) lockdown and an extreme flood occurred in November 2019. The retrievals of TSM imply a remarkable reduction of the turbidity during the lockdown, due to the COVID-19 pandemic and capture the high values of TSM during the flood condition. The results suggest that sizable atmospheric and sun-glint artifacts should be mitigated through the physics-based inversion using the surface reflectance products of PlanetScope imagery. The physics-based inversion demonstrated high potentials in retrieving both bathymetry and TSM using the PlanetScope imagery.

In recent years, the development of new constellations including Galileo, BeiDou Navigation Satellite System (BDS) and Quasi-Zenith Satellite System (QZSS) have undergone dramatic changes. Since January 2018, about 30 satellites of the new constellations have been launched and most of the new satellites have been included in the precise orbit and clock products provided by the Multi Global Navigation Satellite System (Multi-GNSS) Experiment (MGEX). Meanwhile, critical issues including antenna parameters, yaw-attitude models and solar radiation pressure models have been continuously refined for these new constellations and updated into precise MGEX orbit determination and precise clock estimation solutions. In this context, MGEX products since 2018 are herein assessed by orbit and clock comparisons among individual analysis centers (ACs), satellite laser ranging (SLR) validation and precise point positioning (PPP) solutions. Orbit comparisons showed 3D agreements of 3–5 cm for Galileo, 8–9 cm for BDS-2 inclined geosynchronous orbit (IGSO), 12–18 cm for BDS-2 medium earth orbit (MEO) satellites, 24 cm for BDS-3 MEO and 11–16 cm for QZSS IGSO satellites. SLR validations demonstrated an orbit accuracy of about 3–4 cm for Galileo and BDS-2 MEO, 5–6 cm for BDS-2 IGSO, 4–6 cm for BDS-3 MEO and 5–10 cm for QZSS IGSO satellites. Clock products from different ACs generally had a consistency of 0.1–0.3 ns for Galileo, 0.2–0.5 ns for BDS IGSO/MEO and 0.2–0.4 ns for QZSS satellites. The positioning errors of kinematic PPP in Galileo-only mode were about 17–19 mm in the north, 13–16 mm in the east and 74–81 mm in the up direction, respectively. As for BDS-only PPP, positioning accuracies of about 14, 14 and 49 mm could be achieved in kinematic mode with products from Wuhan University applied.

The genetic control of dormancy is poorly understood in most plant species, but dormancy is a prominent feature for the potato industry. We used the microtuber system, in which tubers were produced in vitro and stored at 20°C, to perform quantitative trait locus (QTL) analysis for dormancy and gibberellic acid (GA3) content in an F1 population consisting of 178 genotypes derived from an interspecific cross between Solanum chacoense acc. PI 320285 (long dormancy) and Solanum phureja acc. DM1-3 516 R44 (short dormancy). In this analysis, 163 markers were used to construct a genetic map with a total length of 591.8 cM. Through QTL analysis, we identified 22 markers closely linked to the timing of dormancy release and GA3 content. The male parent alleles were closely related with long dormancy, with the most significant effect on chromosome I, which accounted for 9.4% of phenotypic variation. The dormancy and GA3 QTLs localized to the same position in the genome, confirming that same genomic region controls GA3 content at different developmental stages or in dormant and sprouting tubers. The identified QTLs may be useful for future breeding strategies and studies of dormancy in potato.

Remote sensing and field spectroscopy of natural waters is typically performed under clear skies, low wind speeds and low solar zenith angles. Such measurements can also be made, in principle, under clouds and mixed skies using airborne or in-situ measurements; however, variable illumination conditions pose a challenge to data analysis. In the present case study, we evaluated the inversion of hyperspectral in-situ measurements for water constituent retrieval acquired under variable cloud cover. First, we studied the retrieval of Chlorophyll-a (Chl-a) concentration and colored dissolved organic matter (CDOM) absorption from in-water irradiance measurements. Then, we evaluated the errors in the retrievals of the concentration of total suspended matter (TSM), Chl-a and the absorption coefficient of CDOM from above-water reflectance measurements due to highly variable reflections at the water surface. In order to approximate cloud reflections, we extended a recent three-component surface reflectance model for cloudless atmospheres by a constant offset and compared different surface reflectance correction procedures. Our findings suggest that in-water irradiance measurements may be used for the analysis of absorbing compounds even under highly variable weather conditions. The extended surface reflectance model proved to contribute to the analysis of above-water reflectance measurements with respect to Chl-a and TSM. Results indicate the potential of this approach for all-weather monitoring.

Salicylic acid (SA) is an elicitor to induce the biosynthesis of secondary metabolites in plant cells. Hydrogen peroxide (H2O2) plays an important role as a key signaling molecule in response to various stimuli and is involved in the accumulation of secondary metabolites. However, the relationship between them is unclear and their synergetic functions on accumulation of secondary metabolites are unknown. In this paper, the roles of SA and H2O2 in rosmarinic acid (RA) production in Salvia miltiorrhiza cell cultures were investigated. The results showed that SA significantly enhanced H2O2 production, phenylalanine ammonia-lyase (PAL) activity, and RA accumulation. Exogenous H2O2 could also promote PAL activity and enhance RA production. If H2O2 production was inhibited by NADPH oxidase inhibitor (IMD) or scavenged by quencher (DMTU), RA accumulation would be blocked. These results indicated that H2O2 is secondary messenger for signal transduction, which can be induced by SA, significantly and promotes RA accumulation.

In order to screen the Catalpa plant with high antioxidant activity and confirm the corresponding active fractions from Catalpa ovata G. Don, C. fargesii Bur., and C. bungei C. A. Mey., total flavonoid contents and antioxidant activities of the extracts/fractions of Catalpa plant leaves were determined. The determined total flavonoid content and antioxidant activity were used as assessment criteria. Those compounds with antioxidant activity were isolated with silica gel column chromatography and ODS column chromatography. Our results showed that the total flavonoid content in C. bungei C. A. Mey. (30.07 mg/g·DW) was the highest, followed by those in C. fargesii Bur. (25.55 mg/g·DW) and C. ovata G. Don (24.96 mg/g·DW). According to the determination results of total flavonoid content and antioxidant activity in 3 clones of leaves of C. bungei C. A. Mey., the total flavonoid content and antioxidant activity in crude extracts from C. bungei C. A. Mey. 6 (CA6) leaves were the highest. Moreover, the results showed that the total flavonoid content and antioxidant activities of ethyl acetate (EA) fraction in ethanol crude extracts in CA6 leaves were the highest, followed by n-butanol, petroleum ether (PE), and water fractions. Two flavonoid compounds with antioxidant activity were firstly isolated based on EA fraction. The two compounds were luteolin (1) and apigenin (2), respectively.

Past research has shown that position in a social hierarchy modulates one's social attention, as in the gaze cueing effect. While studies have manipulated the social status of others with whom the participants interact, we believe that a sense of one's own social power is also a crucial factor affecting gaze following. In two experiments, we primed the social power of participants, using different approaches, to investigate the participants' performance in a subsequent gaze cueing task. The results of Experiment 1 showed a stronger gaze cueing effect among participants who were primed with low social power, compared to those primed with high social power. Our predicted gender difference (i.e., women showing a stronger gaze cueing effect than men) was confirmed and this effect was found to be dominated by the lower social power condition. Experiment 2 manipulated the level of danger in the context and replicated the joint impact of gender and one's perceived social power on gaze cueing effect, especially in the low danger context, in comparison to the high danger context. These findings demonstrate that one's perceived social power has a concerted effect on social attention evoked by gaze, along with other factors such as gender and characteristics of the environment, and suggest the importance of further research on the complex relationship between an individual's position in the social hierarchy and social attention.

Satellite remote sensing may assist in meeting the needs of lake monitoring. In this study, we aim to evaluate the potential of Sentinel-2 to assess and monitor water constituents and bottom characteristics of lakes at spatio-temporal synoptic scales. In a field campaign at Lake Starnberg, Germany, we collected validation data concurrently to a Sentinel-2A (S2-A) overpass. We compared the results of three different atmospheric corrections, i.e., Sen2Cor, ACOLITE and MIP, with in situ reflectance measurements, whereof MIP performed best (r = 0.987, RMSE = 0.002 sr−1). Using the bio-optical modelling tool WASI-2D, we retrieved absorption by coloured dissolved organic matter (aCDOM(440)), backscattering and concentration of suspended particulate matter (SPM) in optically deep water; water depths, bottom substrates and aCDOM(440) were modelled in optically shallow water. In deep water, SPM and aCDOM(440) showed reasonable spatial patterns. Comparisons with in situ data (mean: 0.43 m−1) showed an underestimation of S2-A derived aCDOM(440) (mean: 0.14 m−1); S2-A backscattering of SPM was slightly higher than backscattering from in situ data (mean: 0.027 m−1 vs. 0.019 m−1). Chlorophyll-a concentrations (~1 mg·m−3) of the lake were too low for a retrieval. In shallow water, retrieved water depths exhibited a high correlation with echo sounding data (r = 0.95, residual standard deviation = 0.12 m) up to 2.5 m (Secchi disk depth: 4.2 m), though water depths were slightly underestimated (RMSE = 0.56 m). In deeper water, Sentinel-2A bands were incapable of allowing a WASI-2D based separation of macrophytes and sediment which led to erroneous water depths. Overall, the results encourage further research on lakes with varying optical properties and trophic states with Sentinel-2A.