Search

With the rapid development of industry, agriculture, and urbanization, various organic pollutants have accumulated in natural water, posing a potential threat to both the ecological environment and human beings, and removing organic pollutants from water is an urgent priority. Piezoelectric techniques, with the advantages of green, simple operation, and high efficiency, are highly sought after in the degradation of environmental organic pollutants. Moreover, combining piezoelectric techniques with advanced oxidation processes (AOPs), photocatalysis, or electrocatalysis can further effectively promote the efficient degradation of target pollutants. Therefore, a perspective is presented on the recent progress of piezoelectric techniques for the degradation of various organic pollutants from aqueous solutions. The classification of various piezoelectric materials, as well as modification strategies for improving piezocatalysis, are first systematically summarized. Furthermore, the latest research on piezocatalysis and its combination with other technologies, such as AOPs, photocatalysis, and electrocatalysis, in the degradation of environmental pollutants is discussed. The potential mechanisms of piezocatalysis are also analyzed in depth. Finally, the urgent challenges and future opportunities for piezoelectric techniques in the degradation of organic pollutants are provided.

Abstract Background The functional integrity of the anterior cruciate ligament (ACL) influences surgical decision-making in patients with knee osteoarthritis (KOA). This study aimed to compare the diagnostic value of radiography and magnetic resonance imaging (MRI) in determining the functional status of ACL. Methods We analyzed 306 knees retrospectively using preoperative hip-to-ankle anteroposterior standing (APS) radiographs, anteroposterior (AP) and lateral knee radiographs, AP valgus stress (VS) force radiographs, and standard orthogonal MRI. Based on the intraoperative visualization, the knees were grouped into ACL functionally-intact and ACL functionally-deficient (ACLD) groups. The diagnostic validity and reliability were calculated based on the radiograph parameters such as hip-knee-ankle angle (HKA), medial proximal tibial angle (MPTA), lateral distal femoral angle (LDFA), posterior tibial slope (PTS), sagittal tibiofemoral subluxation (STFS), coronal tibiofemoral subluxation (CTFS), joint line convergence angle (JLCA), the maximum wear point of the proximal tibia plateau (MWPPT%), and MRI parameters including ACL grades and MWPPT%. Results HKA, MPTA, PTS, STFS, JLCA, and CTFS on APS and AP radiographs, and MWPPT% on radiographs and MRI showed a significant diagnostic value (P

[Introduction] Under the background of "carbon peak and neutrality" target and "ocean power" strategy, the integration of ocean renewable energy represented by offshore wind power and ocean resources represented by marine ranch is the new direction, new situation and new opportunity for the future development and utilization of ocean resources. The article reviews and analyzes the integrated development mode and key technical problems of offshore wind power and marine pasture, in order to provide technical references to the relevant research and engineering projects in China. [Method] Taking the integration of China's marine resources development needs as the guide, the global development trend of offshore wind power and marine ranch integration was analyzed, and the current situation and shortcomings of China's wind-fishery integration development were clarified. On this basis, the integration mode, equipment design, engineering cases and key technical problems of the integration development of offshore wind power and ocean ranch were analyzed in detail. Finally, a future outlook on the integration development of offshore wind power and ocean ranch in China was discussed. [Result] Through the analysis of the integrated development mode and key technical problems of the integration of offshore wind power and marine ranch development, the bottlenecks and technical challenges are clarified, and the key breakthrough directions are pointed out, providing scientific guidance and reference basis for the comprehensive development and utilization of offshore resources in China. [Conclusion] The article illustrates the necessity and feasibility of integrating the development of offshore wind power and marine ranch, and proposes a feasible way to integrate offshore wind power and marine ranch in China.

[Introduction] Under the backdrop of "carbon peak and neutrality", coastal provinces and cities in China are gradually developing clean energy towards the ocean. The development of offshore wind farm has begun to take shape and achieved equal price of connection to power grid, and pilot projects for offshore floating photovoltaic (FPV) systems are emerging. The comprehensive development of a variety of marine resources, the intensive use of sea resources in the energy sector, and the creation of an integrated marine energy system are of great significance for coastal provinces to achieve high-quality carbon neutrality. [Method] The article summarized the current development and pilot projects of offshore FPV technology both inside and outside of China, analyzed the advantages and challenges of various offshore FPV technologies, predicted the future market size of offshore FPV in China, explored the integration development mode of offshore FPV and other offshore infrastructure, and provided the integration scenarios and economic analysis based on case studies. [Result] The offshore FPV technology is currently at the pilot stage with broad market in the future. The main technical challenge is the viability of floating structure under harsh marine environmental conditions, and the unit cost of the existing pilot projects is relatively high, however, it has enormous potential of combination with other marine facilities. [Conclusion] The integration of offshore FPV and other offshore facilities such as offshore wind power can effectively improve the utilization efficiency of energy facilities and reduce the cost of construction and operation. The complementary use of marine scenery also effectively solves the stability and security problems of a single energy supply.

Purpose This study aims to compare the mid-term radiographic, clinical results and survivorship between distal tibial tuberosity high tibial osteotomy (DTT-HTO) and conventional biplanar medial open-wedge high tibial osteotomy (cOW-HTO). Methods The weight-bearing line ratio (WBL%) and medial proximal tibial angle (MPTA) were evaluated using a standing anteroposterior view of lower extremity. The posterior tibial slope (PTS), Caton-Deschamps index (CDI), tilting angle (TT) and lateral shift ratio (LSR) were evaluated using the lateral views and Merchant views. The Knee Society (KS) knee and function score, Lysholm score, and Anterior Knee Pain Scale (Kujala score) were were used to evaluate the functional outcomes. All parameters were evaluated preoperatively and at the final follow-up. The postoperative complications and survivorship for both groups were also evaluated during the follow-up period. Results The WBL% and MPTA exhibited no significant differences between the two groups preoperatively and at the final follow-up. The postoperative CDI and TT in the cOW group decreased significantly compared with the DTT group ( p = .037 and .041, respectively). The PF grade showed a significant increase after DTT-HTO and cOW-HTO ( p = .036 and

Oedaleus decorus asiaticus (O. asiaticus), the dominant species of steppe locust, plays a crucial role in driving the dynamic changes of the grassland ecosystem. However, there are a limited number of studies on the impact of locust feeding on the relationship of the major plants in the species community. This study has employed the Shannon-Wiener index, Pianka index, and the maximum information coefficient (MIC) to assess the impact of O. asiaticus feeding on the community structure and interspecific relationships in the grasslands of Inner Mongolia. The chosen indices measured niche breadth, niche overlap, and interspecies correlation. The topological network structure between the main species was further analyzed. The results indicated that: 1) locust gnawing expands the niche width of major species and increases the niche overlap index of food-loving species; 2) the feeding of locusts reduces the overall correlation between species but increases the interspecific relatedness between food-loving species and other species. 3) the number of links in the species topological network structure is reduced due to locust gnawing.

Intelligent vehicle detection systems have the potential to improve road safety and optimize traffic management. Despite the continuous advancements in AI technology, the detection of different types of vehicles in complex traffic environments remains a persistent challenge. In this paper, an end-to-end solution is proposed. The image enhancement part proposes a super-resolution synthetic image GAN (SSIGAN) to improve detection of small, distant objects in low-resolution (LR) images. An edge enhancer (EE) and a hierarchical self-attention module (HS) are applied to address the loss of high-frequency edge information and texture details in the super-resolved images. The output super-resolution (SR) image is fed into detection part. In the detection part, we introduce a global context-aware network (GCAFormer) for accurate vehicle detection. GCAFormer utilizes a cascade transformer backbone (CT) that enables internal information interaction and generates multi-scale feature maps. This approach effectively addresses the challenge of varying vehicle scales, ensuring robust detection performance. We also built in a cross-scale aggregation feature (CSAF) module inside GCAFormer, which fuses low- and high-dimensional semantic information and provides multi-resolution feature maps as input to the detection head, so as to make the network more adaptable to complex traffic environments and realize accurate detection. In addition, we validate the effectiveness of our proposed method on a large number of datasets, reaching 89.12% mAP on the KITTI dataset, 90.62% on the IITM-hetra, 86.83% on the Pascal VOC and 93.33% on the BDD-100k. The results were compared to SOTA and demonstrated the competitive advantages of our proposed method for Vehicle Detection in complex traffic environments.

Abstract Background Surgical site infection (SSI) is a common and serious complication of elective clean orthopedic surgery that can lead to severe adverse outcomes. However, the prognostic efficacy of the current staging systems remains uncertain for patients undergoing elective aseptic orthopedic procedures. This study aimed to identify high-risk factors independently associated with SSI and develop a nomogram prediction model to accurately predict the occurrence of SSI. Methods A total of 20,960 patients underwent elective clean orthopedic surgery in our hospital between January 2020 and December 2021, of whom 39 developed SSI; we selected all 39 patients with a postoperative diagnosis of SSI and 305 patients who did not develop postoperative SSI for the final analysis. The patients were randomly divided into training and validation cohorts in a 7:3 ratio. Univariate and multivariate logistic regression analyses were conducted in the training cohort to screen for independent risk factors of SSI, and a nomogram prediction model was developed. The predictive performance of the nomogram was compared with that of the National Nosocomial Infections Surveillance (NNIS) system. Decision curve analysis (DCA) was used to assess the clinical decision-making value of the nomogram. Results The SSI incidence was 0.186%. Univariate and multivariate logistic regression analysis identified the American Society of Anesthesiology (ASA) class (odds ratio [OR] 1.564 [95% confidence interval (CI) 1.029–5.99, P = 0.046]), operative time (OR 1.003 [95% CI 1.006–1.019, P

In ecological communities, the relationships between interacting species are very complex, resulting in nonlinear or even chaotic oscillations. Human activities, such as habitat destruction and fragmentation, overexploitation of natural resources, and noise and light pollution, have been shown to influence species interactions. However, the pattern of impact of these activities on fig wasps remains unclear. In this study, we analyzed the network relationships associated with fig wasps at six different sites, including both human-disturbed habitats and primary rainforests in Xishuangbanna, tropical China. Our analysis revealed that the pollinator Ceratosolen fusciceps had complex non-linear relationships with five species of non-pollinator wasps in the primary rainforests. The connectivity and complexity of species networks were reduced in human-disturbed habitats, particularly regarding the number and strength of associations of the key pollinator, Ceratosolen fusciceps, with other non-pollinator wasps. Additionally, we separately analyzed the association networks of male and female fig wasps and found that human disturbance had a greater impact on female wasps, as evidenced by a more pronounced decrease in edges in the female network compared to the male network. The positive correlation between females and males was weakened in different populations under the influence of human interference, while it was strengthened in different sexes of the same species. Overall, human disturbances altered fig wasp numerical relationships, reducing connectivity and complexity in species networks. This impacted fig-fig wasp mutualism, especially involving Ceratosolen fusciceps and non-pollinator wasps. These findings may contribute to our understanding of the coevolution between fig-fig wasp mutualism.

[Introduction] Strategies for preventing corrosion in steel structures at offshore wind farms, derived from a comprehensive study on the environmental conditions, symptoms, and mechanisms of corrosion in such structures, as well as an analysis on various causes were proposed, aiming to ensure safe operation throughout their lifecycle. [Method] The study focused on the grid-connected offshore wind farms and investigated corrosion observed in specific marine environmental conditions for different foundation types, structural components, materials, and parts. [Result] The results show that corrosion appears in various forms and progresses at varying rates among different foundation types, structural components, and parts in specific marine environmental conditions. Electrochemical corrosion is identified as the main form of corrosion, while internal and external stresses act as potential accelerators of corrosion in steel structures. Manufacturing quality control and the implementation of protective measures directly affect the rate of corrosion development.[Conclusion] In summary, it is crucial to identify various potential risks related to manufacturing characteristics, material properties, and environmental conditions of steel structures at offshore wind farms and take appropriate refined protection measures to eliminate underlying causes. In addition, protection levels should be increased for certain critical parts.

IntroductionThe ratio of Triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C) is a crucial indicator for diabetes diagnosis.MethodsThis study utilizes the Copula function to model and fit the non-linear correlation among fasting blood glucose (Glu), glycosylated hemoglobin (HbA1C), and TG/HDL-C in patients with diabetes. The Copula function chosen for this study includes the two-dimensional Archimedes and Elliptical distribution family, as well as the multidimensional Vine Copula function, for fitting the data. The evaluation of the fitting effect is performed using the mean absolute error (MAE) and mean square error (MSE).ResultsThe results indicate that the Clayton Copula exhibits the highest effectiveness in fitting the pairwise relationship between Glu and TG/HDL-C, as well as HbA1C and TG/HDL-C, displaying the smallest fitting error. Additionally, the Vine Copula function produces a satisfactory fit for the relationship among all three indicators. Compared to linear analysis methods, the Copula function more accurately depicts the correlation among these three types of indicators.DiscussionMoreover, our findings indicate a stronger correlation in the lower tail between Glu and HbA1C, as well as TG/HDL-C, suggesting that the Copula function provides greater accuracy and applicability in depicting the relationship among these indicators. As a result, it can offer a more precise auxiliary diagnosis and serve as a valuable reference in clinical judgment.

In this article, when 2≤p≤4, we establish the Cloc0,1-regularity of weak solutions to the degenerate parabolic p-Laplacian equation ∂tu=−∑i=16Xi*(|∇Hu|p−2Xiu) on the group SU(3) granted with horizontal vector fields X1, …, X6. Compared to the Heisenberg group, Hn, we obtained the optimal range of p; that is, 2≤p≤4.

High-precision, short-term power forecasting for photovoltaic systems not only reduces unnecessary energy consumption but also provides power grid security. To this end, in this paper we propose a photovoltaic short-term power forecasting model based on the division of data of the 24 traditional Chinese solar terms and the Adaboost-GA-BP model. The 24 solar terms were condensed from the laws of meteorology, phenology, and seasonal changes to adapt to agricultural times in ancient China and have become intangible cultural heritage. This article first analyzes the numerical characteristics of meteorological factors and demonstrates their close correlation with the turning points of the 24 solar terms. Second, using Standardized Euclidean Distance and Spearman’s Correlation Coefficients to analyze data similarity between the Gregorian half-months and the 24 solar terms divisions for comparative analysis purposes, it is shown that the intragroup data under the division of the 24 solar terms have a higher similarity, leading to an average decrease of 15.68%, 40.57%, 14.68%, and 14.64% in the MAE, MSE, RMSE, and WMAPE of the predicted results, respectively. Finally, based on the data derived from the 24 solar terms, the combined algorithm was compared with the Adaboost-GA-BP model and then was verified. The genetic algorithm and Adaboost were used to optimize the BP neural network algorithm in initial value assignment and neural network structure, resulting in a 23.42%, 18.12%, and 22.28% reduction in the mean values of the MAE, RMSE, and WMAPE of the predicted results, respectively. Analysis of the results show that using the Adaboost-GA-BP model based on the 24 solar terms for short-term photovoltaic power forecasting can improve the accuracy of photovoltaic power forecasting and significantly improve the predictive performance of the model.

[Introduction] This paper adoptes the methods based on parametric study and CPT in-situ test for analysis and calculation, the preliminary analysis is carried out according to the actual construction data. By doing this, the self-weight penetration of monopiles can be better and faster predicted and the risks in monopile installation are significantly reduced. [Method] Modified the design input parameters by API recommended pile capacity theory, combined with error analysis, the predicted self-weight penetration was compared to the real data on site. [Result] The analysis results show that there is a great difference in prediction of self-weight penetration due to the different reduction strength coefficient \begin{document}$ {S}_{\mathrm{r}} $\end{document} in the process of calculating clay self-weight penetration and pile running analysis. At the same time, the selection of reduction strength coefficient is different between the self-weight penetration and pile running process. [Conclusion] Through comparative analysis, the value range of clay strength reduction coefficient \begin{document}$ {S}_{\mathrm{r}} $\end{document} of Guangdong sea area is obtained, which can provide a design reference for the following offshore pile penetration operations. It's also proved that the CPT can be used to better predict self-weight penetration and pile running phenomenon.

Osteosarcoma (OS) is a malignant tumor with an extremely poor prognosis, especially in progressive patients. Immunotherapy based on immune checkpoint inhibitors (ICIs) is considered to be a promising treatment option for OS. Due to tumor heterogeneity, only a minority of patients benefit from immunotherapy. Therefore, it is urgent to explore a model that can accurately assess the response of OS to immunotherapy. In this study, we obtained the single-cell RNA sequencing datasets of OS patients from public databases and defined 34 cell clusters by dimensional reduction and clustering analysis. PTPRC was applied to identify immune cell clusters and nonimmune cell clusters. Next, we performed clustering analysis on the immune cell clusters and obtained 25 immune cell subclusters. Immune cells were labeled with CD8A and CD8B to obtain CD8+ T cell clusters. Meanwhile, we extracted the differentially expressed genes (DEGs) of CD8+ T cell clusters and other immune cell clusters. Furthermore, we constructed a prognostic model (CD8-DEG model) based on the obtained DEGs of CD8+ T cells, and verified the excellent predictive ability of this model for the prognosis of OS. Moreover, we further investigated the value of the CD8-DEG model. The results indicated that the risk score of the CD8-DEG model was an independent risk factor for OS patients. Finally, we revealed that the risk score of the CD8-DEG model correlates with the immune profile of OS and can be used to evaluate the response of OS to immunotherapy. In conclusion, our study revealed the critical role of CD8 cells in OS. The risk score model based on CD8-DEGs can provide guidance for prognosis and immunotherapy of OS.

Water ecosystems are highly sensitive to environmental conditions, including meteorological factors, which influence dissolved oxygen (DO) concentrations, a critical indicator of water quality. However, the complex relationships between multiple meteorological factors from various sites and DO concentrations pose a significant challenge for accurate prediction. This study introduces an innovative framework for enhancing DO concentration predictions in water bodies by integrating multi-station meteorological data. We first construct a dynamic meteorological graph with station-specific factors as node features and geographic distances as edge weights. This graph is processed using a Geo-Contextual Graph Embedding Module, leveraging a Graph Convolutional Network (GCN) to distill geographical and meteorological features from multi-station data. Extracted features are encoded and then temporally merged with historical DO values to form time-series data. Finally, a Temporal Transformer module is used for future DO concentration predictions. The proposed model shows superior performance compared to traditional methods, successfully capturing the complex relationships between meteorological factors and DO levels. It provides an effective tool for environmental scientists and policymakers in water quality monitoring and management. This study suggests that the integration of graph-based learning and a Temporal Transformer in environmental modeling is a promising direction for future research.

The accurate prediction of PM2.5 concentration, a matter of paramount importance in environmental science and public health, has remained a substantial challenge. Conventional methodologies for predicting PM2.5 concentration often grapple with capturing complex dynamics and nonlinear relationships inherent in multi-station meteorological data. To address this issue, we have devised a novel deep learning model, named the Meteorological Sparse Autoencoding Transformer (MSAFormer). The MSAFormer leverages the strengths of the Transformer architecture, effectively incorporating a Meteorological Sparse Autoencoding module, a Meteorological Positional Embedding Module, and a PM2.5 Prediction Transformer Module. The Sparse Autoencoding Module serves to extract salient features from high-dimensional, multi-station meteorological data. Subsequently, the Positional Embedding Module applies a one-dimensional Convolutional Neural Network to flatten the sparse-encoded features, facilitating data processing in the subsequent Transformer module. Finally, the PM2.5 Prediction Transformer Module utilizes a self-attention mechanism to handle temporal dependencies in the input data, predicting future PM2.5 concentrations. Experimental results underscore that the MSAFormer model achieves a significant improvement in predicting PM2.5 concentrations in the Haidian district compared to traditional methods. This research offers a novel predictive tool for the field of environmental science and illustrates the potential of deep learning in the analysis of environmental meteorological data.

The purpose of this study was to explore the dynamic and intervention mechanisms of daily abusive experience affecting daily work engagement. Drawing on conservation of resources (COR) theory, we examine the effect of daily abusive supervision on daily work engagement through daily negative emotions from the resource consumption perspective, and the moderation effect of coworker support from the resource provision perspective. Using a daily diary approach and based on a sample of 73 employees for 5 consecutive days in China. The results reveal that daily abusive supervision has a significant negative effect on daily work engagement, daily negative emotions mediate this relationship, and coworker support had a cross-level moderating effect between daily abusive supervision and daily negative emotions. Our study shows ways to boost employees’ daily work engagement and especially ways buffer the negative effect of abused experience on work engagement.

ObjectiveThe present study was designed for the contrastive analysis of conservative and percutaneous kyphoplasty (PKP) on pain severity and recovery of injured vertebrae in elderly patients with acute symptomatic osteoporotic vertebral compression fracture (OVCF).MethodsA total of 60 elderly patients with acute symptomatic OVCF were divided into two groups according to different treatment protocols, with 30 patients in each group. Patients in the Con group received conservative treatment, while patients in the PKP group received percutaneous kyphoplasty treatment. Clinical evaluation included the visual analogue scale (VAS), the Dallas pain questionnaire, the vertebral body leading edge height, the Cobb angle of injured vertebrae, the MOS item short-form health survey (SF-36), the Barthel index, and the mini-mental state examination (MMSE).ResultsAt 3 days, 3 months, and 6 months post-treatment, the score of VAS and the Cobb angle of injured vertebrae in patients of the PKP group were all significantly lower than those in the Con group (P 0.05).ConclusionCompared with conservative treatment, PKP treatment of elderly patients with acute symptomatic OVCF provides rapid pain relief, restoration of damaged vertebral body height, correction of Cobb's angle, and improved quality of life.

In densely populated coastal areas with sea-level rise (SLR), protecting the shorelines against erosion due to the wave impact is crucial. Along with many engineered structures like seawalls and breakwaters, there are also green structures like constructed oyster reefs (CORs) that can not only attenuate the incident waves but also grow and maintain pace with SLR. However, there is a lack of data and understanding of the long-term wave attenuation capacity of the living shoreline structures under SLR. In this study, we used the phase-resolving Boussinesq model, FUNWAVE-TVD, to examine the hydrodynamics including wave height and wave-induced currents around the CORs in the Gandys Beach living shoreline project area in the upper Delaware Bay, United States. Waves were measured at six locations (offshore to onshore, with and without CORs) in the Gandys Beach living shoreline project area for two winter months, during which four nor’easters occurred. We selected three cases that represent prevailing wind, wave, and tide conditions to examine the fine spatial and temporal changes in wave height and current velocity by the construction of the reefs. Wave heights and wave energy spectra generated from FUNWAVE-TVD were then validated with field observations. It is found that FUNWAVE-TVD is capable of simulating waves and associated hydrodynamic processes that interact with CORs. The model results show that wave attenuation rates vary with the incident wave properties and water depth, and wave-induced circulation patterns are affected by the CORs. The wave attenuation capacity of CORs over the next 100 years was simulated with the incorporation of the oyster reef optimal growth zone. Our study found that sustainable wave attenuation capacity can only be achieved when suitable habitat for COR is provided, thus it can vertically grow with SLR. Suitable habitat includes optimal intertidal inundation duration, current velocity for larval transport and settlement, on-reef oyster survival and growth, and other environmental conditions including salinity, temperature, and nutrient availability. Furthermore, the model results suggest that it would take CORs approximately 9 years after construction to reach and maintain the maximum wave attenuation capacity in sustainable living shorelines.

Let (E,h1,∞) be a nonautonomous discrete dynamical system (briefly, N.D.D.S.) that is defined by a sequence (hj)j=1∞ of continuous maps hj:E→E over a nontrivial metric space (E,d). This paper defines and discusses some forms of ergodicity and sensitivity for the system (E,h1,∞) by upper density, lower density, density, and a sequence of positive integers. Under some conditions, if the rate of convergence at which (hj)j=1∞ converges to the limit map h is “fast enough” with respect to a sequence of positive integers with a density of one, it is shown that several sensitivity properties for the N.D.D.S. (E,h1,∞) are the same as those properties of the system (E,h). Some sufficient conditions for the N.D.D.S. (E,h1,∞) to have stronger sensitivity properties are also presented. The conditions in our results are less restrictive than those in some existing works, and the conclusions of all the theorems in this paper improve upon those of previous studies. Thus, these results are extensions of the existing ones.

Organizational environmental sustainability depends primarily on employees’ organizational citizenship behavior for the environment (OCBE), and leadership plays an important role in improving and inhibiting employees’ OCBE. The purpose of the present study is to examine the mediation process by which abusive supervision affects employees’ OCBE through a daily diary study and to explore the boundary conditions of the relationship between daily moral disengagement and daily OCBE. We collected data from 112 Chinese employees for 10 consecutive days. The results show that daily abusive supervision has a significant negative effect on daily OCBE and that daily moral disengagement plays a significant mediating role in this relationship. In addition, the negative effect of daily moral disengagement on daily OCBE could be attenuated by a psychological green climate. Our findings support our hypotheses and offer useful theoretical and practical implications for promoting OCBE.

Based on the theory of purposeful work behavior, this study proposed that the two facets of employee conscientiousness, namely duty orientation and achievement orientation, have opposite effects on pro-social rule breaking (PSRB). We also explored the moderating effect of employees’ task characteristic (job autonomy) and social characteristic (leader reward omission) on the above relationships. Using two-wave data collected from 216 employee-supervisor dyads, we found that duty orientation was positively related to PSRB, while achievement orientation was negatively related to PSRB. Further, job autonomy, by amplifying employees’ perceived meaningfulness of their higher-order implicit goals, can strengthen the positive effect of duty orientation and the negative effect of achievement orientation on PSRB. Similarly, leader reward omission could also activate the negative effect of achievement orientation and PSRB, but not significantly moderate the positive relationship between duty orientation and PSRB. By separating the distinct role of facet-specific personality, our study sheds light on the relationship between employee conscientiousness and PSRB.

Strawberry mottle virus (SMoV) is associated with strawberry decline disease, causing losses to fruit yield and quality. In this study, using a screening system that enables detection of both local and systemic plant host (RNA silencing) defense responses, we found that Pro2Glu and P28, encoded by SMoV RNA2 genome, functioned to suppress local and systemic RNA silencing triggered by single- but not double-stranded GFP RNA. Subcellular localization assay revealed that both Pro2Glu and P28 were localized to nucleus and cytoplasm. The deletion of 11 amino acid residues at the C-terminus destabilized Pro2Glu protein, and the disruption of two conserved GW motifs deprived Pro2Glu of ability to suppress RNA silencing. Additionally, SMoV Pro2Glu and P28 enhanced the accumulation of potato virus X (PVX) in Nicotiana benthamiana 22 days post-infiltration, and P28 exacerbated significantly the symptoms of PVX. Collectively, these data indicate that the genome of SMoV RNA2 encodes two suppressors of RNA silencing. This is the first identification of a stramovirus suppressor of RNA silencing.

The present paper reported a novel approach for the fabrication of a high-aspect ratio (K, Na)NbO3 (KNN) piezoelectric micropillar array via epoxy gelcasting, which involves the in situ consolidation of aqueous KNN suspensions with added hydantoin epoxy resin on a polydimethylsiloxane (PDMS) soft micromold. KNN suspensions with solid loadings of up to 45.0 vol.% have rheological behavior, which was suitable for the gelcasting process. The uniform green KNN bodies derived from the optimized suspension of 42.0 vol.% solid loading and 15.0 wt.% resin had exceptionally high mechanical strength (9.14 MPa), which was responsible for the integrity of the piezoceramic micropattern structure. The square-shaped KNN piezoelectric pillar array with lateral dimensions of up to 5 μm and an aspect ratio of up to five was successfully fabricated.

Abstract Objectives This study aimed to investigate the application of shear wave elastography (SWE) in the early damage detection through assessing the endometrial elasticity after artificial abortion. Methods A total of nulliparous women (20–30 years) who received ultrasonography in our hospital were recruited between January 2017 and December 2017. These women were divided into normal control group (NC; n = 65), after once artificial abortion group (AOAA; n = 68), after twice artificial abortion group (ATAA; n = 61), and after three times or more (range, 3–6) artificial abortion group (ATTMAA; n = 60). SWE was performed to evaluate the endometrium; Young’s modulus of the endometrium was determined and then the endometrial thickness was measured. Results Young’s modulus of the endometrium increased in the order of NC group, AOAA group, ATAA group, and ATTMAA group, and Young’s modulus increased with the increase in the number of artificial abortions (p 0.05). Conclusions SWE increases with increasing number of abortions, which may indicate the damage that is done to the endometrium earlier than measurement of the endometrial thickness do.

The natural host range for brassica yellows virus (BrYV) is generally limited to Cruciferae. However, we found that BrYV can naturally infect strawberry. The full-length genome sequences of BrYV-MB (accession No. MZ666129) and BrYV-HY (accession No. ON060762) identified in strawberry from Yantai and Beijing, China, were obtained by high-throughput sequencing (HTS) combined with the RT-PCR and RACE techniques. The complete genome sequences of BrYV-MB and BrYV-HY are 5666 nt and contain six open reading frames (ORFs). The two isolates have the highest nucleotide (nt) sequence identity of 99.0%. The infectious cDNA clone of BrYV-HY was constructed through homologous recombination and used to agroinfiltrate Nicotiana benthamiana and Arabidopsis thaliana. The inoculated leaves of N. benthamiana showed necrotic symptoms after 4 days of inoculation (dpi), and the systematic leaves of A. thaliana exhibited purple symptoms at 14 dpi. To develop a rapid and high-sensitive method for the detection of BrYV, a TaqMan real-time fluorescence quantitative RT-PCR method (TaqMan RT-qPCR) was established. Under optimum reaction conditions, the sensitivity of the detection was as low as 100 fg and approximately 100-fold more sensitive than the conventional RT-PCR, so it can be used in large-scale testing.

By using the uniform continuity of two onto maps, this paper further explores stronger forms of Kato’s chaos, sensitivity, and accessibility of Cournot maps. In particular, the sensitivity, the collective sensitivity, the accessibility, and the collective accessibility of the compositions of two reaction functions are studied. It is observed that a Cournot onto map H on a product space is sensitive (collectively sensitive, collectively accessible, accessible, or collectively Kato chaotic) if and only if the restriction of the map H2 to the MPE-set is sensitive as well. Several examples are given to show the necessity of the reaction functions being continuous onto maps.

Ecosystem modeling is a critical process for understanding complex systems at spatiotemporal scales needed to conserve, manage, and restore ecosystem services (ESs). Although mangrove wetlands are sources of ESs worth billions of dollars, there is a lack of modeling tools. This is reflected in our lack of understanding of mangroves’ functional and structural attributes. Here, we discuss the “state of the art” of mangrove models used in the planning and monitoring of R/R projects during the last 30 years. The main objectives were to characterize the most frequent modeling approach, their spatiotemporal resolution, and their current utility/application in management decisions. We identified 281 studies in six broad model categories: conceptual, agent-based (ABM), process-based (PBM), spatial, statistical, and socioeconomic/management (ScoEco). The most widely used models are spatial and statistical, followed by PBM, ScoEco, and conceptual categories, while the ABMs were the least frequently used. Yet, the application of mangrove models in R/R projects since the early 1990s has been extremely limited, especially in the mechanistic model category. We discuss several approaches to help advance model development and applications, including the targeted allocation of potential revenue from global carbon markets to R/R projects using a multi-model and integrated approach.

Developing a fluorescent probe for UO22+, which is resistant to interference from other ions such as Cu2+ and can be applied in acidic and high-water systems, has been a major challenge. In this study, a “turn-off” fluorescent probe for triamine-modified flavonoid derivatives, 2-triphenylamine-3-hydroxy-4H-chromen-4-one (abbreviated to HTPAF), was synthesized. In the solvent system of dimethyl sulfoxide:H2O (abbreviated to DMSO:H2O) (v/v = 5:95 pH = 4.5), the HTPAF solution was excited with 364 nm light and showed a strong fluorescence emission peak at 474 nm with a Stokes shift of 110 nm. After the addition of UO22+, the fluorescence at 474 nm was quenched. More importantly, there was no interference in the presence of metal ions (Pb2+, Cd2+, Cr3+, Fe3+, Co2+, Th4+, La3+, etc.), especially Cu2+ and Al3+. It is worth noting that the theoretical model for the binding of UO22+ to HTPAF was derived by more detailed density functional theory (DFT) calculations in this study, while the coordination mode was further verified using HRMS, FT-IR and 1HNMR, demonstrating a coordination ratio of 1:2. In addition, the corresponding photo-induced electron transfer (PET) fluorescence quenching mechanism was also proposed.

Oxygen vacancy manipulation and hierarchical morphology construction in oxygen-containing semiconductors have been demonstrated to be effective strategies for developing high efficiency photocatalysts. In most studies of bismuth-based photocatalysts, hierarchical morphology and crystal defects are achieved separately, so the catalysts are not able to benefit from both features. Herein, using boiling ethylene glycol as the treatment solution, we developed an etching-recrystallization method for the fabrication of 3D hierarchical defective BiOCl at ambient pressure. The target hierarchical 3D-BiOCl is composed of self-assembled BiOCl nanosheets, which exhibit a hexagonal prism-like morphology on a micron scale, while simultaneously containing numerous oxygen vacancies within the crystal structure. Consequently, the target catalyst was endowed with a higher specific surface area, greater light harvesting capability, as well as more efficient separation and transfer of photo-excited charges than pristine BiOCl. As a result, 3D-BiOCl presented an impressive photocatalytic activity for the degradation of tetracycline hydrochloride in both visible light and natural white light emitting diode (LED) irradiation. Moreover, an extraordinary recycling property was demonstrated for the target photocatalyst thanks to its hierarchical structure. This study outlines a simple and energy-efficient approach for producing high-performance hierarchically defective BiOCl, which may also open up new possibilities for the morphological and crystal structural defect regulation of other Bi-based photocatalysts.

Human milk contains numerous free low molecular weight peptides (LMWPs), which may play an important role in infant health and growth. The bioactivities of LMWPs are determined by their structures, especially the amino acid sequences. In the present study, 81 human milk samples were collected and purified by cation-exchange solid-phase extraction (SPE). Ultra-high performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS) was used for the separation and detection of free LMWPs in human milk. A total of 56 LMWPs were identified and quantified. These LMWPs were mainly derived from 3 regions of β-casein, which were the amino acid fragments of 16–40, 85–110, and 205–226. The predominant LMWPs were RETIESLSSSEESITEYK, RETIESLSSSEESITEYKQKVEKVK, ETIESLSSSEESITEYK, TQPLAPVHNPIS, and QPLAPVHNPISV with molecular weights of 2247.9573, 2860.2437, 2091.8591, 1372.7666, and 1271.7212, respectively. The results indicated that the technique based on SPE and UPLC-QTOF-MS might greatly facilitate the analysis of LMWPs in human milk.

Ti/SnO2-Sb electrode, which is one of the dimensionally stable anode (DSA) electrodes, offers high specific conductivity, excellent electrocatalytic performance, and great chemical stability. For these reasons, Ti/SnO2-Sb electrode has been extensively studied in the fields of wastewater treatment. This review covers essential research work about the advanced oxidation technology and related DSA electrodes. It gives an overview of preparation methods of SnO2 electrodes, including sol-gel method, dip-coating method, electrodeposition method, chemical vapor deposition method, thermal decomposition method, magnetron sputtering method, and hydrothermal method. To extend service life and improve electrocatalytic efficiency, the review provides comprehensive details about the modification technologies of Ti/SnO2-Sb electrode, such as doping modification, composite modification, and structural modification. In addition, the review discusses common problems in industrial applications of Ti/SnO2-Sb electrode and highlights the promising outlook of Ti/SnO2-Sb electrode.

The initiation and quality of flowering directly affect the time to market and economic benefit of cultivated strawberries, but the underlying mechanisms of these processes are largely unknown. To investigate the gene activity during the key period of floral induction in strawberries, time-course transcriptome analysis was performed on the shoot apex of the strawberry cultivar ‘Benihoppe.’ A total of 7177 differentially expressed genes (DEGs) were identified through pairwise comparisons. These DEGs were grouped into four clusters with dynamic expression patterns. By analyzing the key genes in the potential flowering pathways and the development of the leaf and flower, at least 73 DEGs that may be involved in the regulatory network of floral induction in strawberries were identified, some of which belong to the NAC, MYB, MADS, and SEB families. A variety of eight hormone signaling pathway genes that might play important roles in floral induction were analyzed. In particular, the gene encoding DELLA, a key inhibitor of the gibberellin signaling pathway, was found to be significantly differentially expressed during the floral induction. Furthermore, the differential expression of some important candidate genes, such as TFL1, SOC1, and GAI-like, was further verified by qRT-PCR. Therefore, we used this time-course transcriptome data for a preliminary exploration of the regulatory network of floral induction and to provide potential candidate genes for future studies of flowering in strawberries.

In a high-temperature gas-cooled reactor, the integrity of tristructural-isotropic-(TRISO-) coated fuel particles ensures the safety of the reactor, especially in case of an air-ingress accident. The oxidation of TRISO particles with the outer layers of silicon carbide (SiC) was performed at temperatures of 900°C–1400°C in air environment. Both the microstructure and phase composition of the SiC layers were studied. The results showed that the SiC layers had a good oxidation resistance below 1100°C. However, the amorphous silica on the SiC layers formed at 1200°C and gradually crystallized at 1400°C with the presence of microcracks. The reaction rates of the SiC layers were determined by measuring the silica thickness. It was proposed that the oxidation of the SiC layers followed the linear-parabolic law with the activation energy of 146 ± 5 kJ/mol. The rate-determining step of the oxidation was the diffusion of oxygen in silica.

The reaction diffusion system is one of the important models to describe the objective world. It is of great guiding importance for people to understand the real world by studying the Turing patterns of the reaction diffusion system changing with the system parameters. Therefore, in this paper, we study Gierer–Meinhardt model of the Depletion type which is a representative model in the reaction diffusion system. Firstly, we investigate the stability of the equilibrium and the Hopf bifurcation of the system. The result shows that equilibrium experiences a Hopf bifurcation in certain conditions and the Hopf bifurcation of this system is supercritical. Then, we analyze the system equation with the diffusion and study the impacts of diffusion coefficients on the stability of equilibrium and the limit cycle of system. Finally, we perform the numerical simulations for the obtained results which show that the Turing patterns are either spot or stripe patterns.

The requirements regarding the weight and capacity reduction of neutron shielding materials have become an urgent issue for advanced nuclear facilities and plants. An epoxy-based neutron shielding material with high-temperature stability and good neutron irradiation resistance was designed in this paper to solve the above issue. Aminophenol trifunctional epoxy resin (AFG-90H) was compounded with samarium oxide (Sm2O3) by means of an ultrasonic-assisted method and the compatibility of Sm2O3 with the AFG-90H matrix was improved by 3-aminopropyltriethoxysilane (APTES) surface modification. Fabricated Sm2O3-APTES/AFG-90H composites exhibited improved thermal stability, glass transition temperature and Young’s modulus with increased Sm2O3-APTES content. Neutronics calculation results show that the neutron permeability of 2 mm-thick 30 wt% Sm2O3-APTES/AFG-90H was 98.9% higher than that of the AFG-90H matrix under the irradiation of the thermal neutron source. The results show that the proper addition range of Sm2O3-APTES is between 20% and 25%. The Sm2O3-APTES/AFG-90H composite is a promising neutron shielding material for advanced nuclear system.

Abstract In this paper, we propose a novel image enhancement algorithm via anti-degraded model and L 1 L 2-based variational retinex (AD-L 1 L 2VR) for non-uniform illumination endoscopic images. Firstly, a haze-free endoscopic image is obtained by an anti-degraded model named dark channel prior (DCP). For getting a more accurate transmission map, it is refined by using a guided image filtering. Secondly, the haze-free endoscopic image is decomposed into detail and naturalness components by light filtering. Thirdly, a logarithmic Laplacian-based gamma correction (LLGC) is added to the naturalness component for preventing color cast and uneven lighting. Fourthly, we assume that the error between the detail component of the haze-free image and the product of associated reflectance and background illumination follows Gaussian-Laplacian distribution. So, the associated reflectance component can be obtained by using the proposed L 1 L 2-based variational retinex (L 1 L 2VR) model. Finally, the recombination of modified naturalness component and associated reflectance component become the final result. Experimental results demonstrate that the proposed algorithm reveals more details in the background regions as well as other interesting areas and can mostly prevent the color cast. It has a better performance on increasing diagnosis and reducing misdiagnosis than other existing enhancement methods.

Abstract Recently, L1 tracker has been widely applied and received great success in visual tracking. However, most L1 trackers use only the image intensity for sparse representation, which is insufficient to represent the object especially when drastic appearance changes occur. Convolutional neural network (CNN) has demonstrated remarkable capability in a wide range of computer vision fields, and features extracted from different convolutional layers have different characteristics. In this paper, we propose a novel sparse representation model with convolutional features for visual tracking. Besides, to alleviate the redundancy from high-dimensional convolutional features, a feature selection method is adopted to remove noisy and irrelevant feature maps, which can reduce computation redundancy and improve tracking accuracy. Different from traditional sparse representation based tracking methods, our model not only exploits convolutional features to improve the robustness for describing the object appearance but also uses the trivial templates to model both reconstruction errors caused by sparse representation and the eigen-subspace representation. In addition, an unified objective function is proposed and a customized APG method is developed to effectively solve the optimization problem. Numerous qualitative and quantitative evaluations demonstrate that our tracker outperforms other state-of-the-art trackers in a wide range of tracking scenarios.

Abstract In this letter, a surround suppression variational Retinex enhancement algorithm (SSVR) is proposed for non-uniform illumination images. Instead of a gradient module, a surround suppression mechanism is used to provide spatial information in order to constrain the total variation regularization strength of the illumination and reflectance. The proposed strategy preserves the boundary areas in the illumination so that halo artifacts are prevented. It also preserves textural details in the reflectance to prevent from illumination compression, which further contributes to the contrast enhancement in the resulting image. In addition, strong regularization strength is enforced to eliminate uneven intensities in the homogeneous areas. The split Bregman optimization algorithm is employed to solve the proposed model. Finally, after decomposition, a contrast gain is added to reflectance for contrast enhancement, and a Laplacian-based gamma correction is added to illumination for prevent color cast. The recombination of the modified reflectance and illumination become the final result. Experimental results demonstrate that the proposed SSVR algorithm performs better than other methods.

α-Glucosidase and lipase inhibitors play important roles in the treatment of hyperglycaemia and dyslipidemia.To identify novel naturally occurring inhibitors, a bioactivity-guided phytochemical research was performed on the pu-erh tea. One new flavanol, named (–)-epicatechin-3-O-(Z)-coumarate (1), and 16 known analogs (217) were isolated from the aqueous extract of the pu-erh tea. Their structures were determined by spectroscopic and chemical methods. Furthermore, the water extract of pu-erh tea and its fractions exhibited inhibitory activities against α-glucosidases and lipases in vitro; compound 15 showed moderate inhibitory effect against sucrase with an IC50 value of 32.5 μmol/L and significant inhibitory effect against maltase with an IC50 value of 1.3 μmol/L. Compounds 8, 10, 11 and 15 displayed moderate activity against a lipase with IC50 values of 16.0, 13.6, 19.8, and 13.3 μmol/L, respectively.

Tropical overshooting convection has a strong impact on both heat budget and moisture distribution in the upper troposphere and lower stratosphere, and it can pose a great risk to aviation safety. Cloud-top height is one of the essential concerns of overshooting convection for both the climate system and the aviation weather forecast. The main purpose of our work is to verify the application of the machine learning method, taking the random forest (RF) model as an instance, in overshooting cloud-top height retrieval from Himawari-8 data. By using collocated CloudSat observations as a reference, we utilize several infrared indicators of Himawari-8 that are commonly recognized to relate to cloud-top height, along with some temporal and geographical parameters (latitude, month, satellite zenith angle, etc.), as predictors to construct and validate the model. Analysis of variable importance shows that the brightness temperature of 6.2 um acts as the dominant predictor, followed by satellite zenith angle, brightness temperature of 13.3 um, latitude, and month. In the comparison between the RF model and the traditional single-channel interpolation method, retrievals from the RF model agree well with observation with a high correlation coefficient (0.92), small RMSE (222 m), and small MAE (164 m), while these metrics from traditional single-channel interpolation method shows lower skills (0.70, 1305 m, and 1179 m). This work presents a new sight of overshooting cloud-top height retrieval based on the machine learning method.

The quality and yields of strawberry plants are seriously affected by abiotic stress every year. NAC (NAM, ATAF, CUC) transcription factors are plant-specific, having various functions in plant development and response to stress. In our study, FaNAC2 from strawberry (Fragaria × ananassa, cultivar “Benihoppe”) was isolated and found to be a member of the ATAF sub-family, belonging to the NAC family of transcription factors. FaNAC2 was strongly expressed in the shoot apical meristem and older leaves of strawberries, and was induced by cold, high salinity, and drought stress. To investigate how FaNAC2 functions in plant responses to abiotic stress, transgenic Nicotiana benthamiana plants ectopically overexpressing FaNAC2 were generated. The transgenic plants grew better under salt and cold stress, and, during simulated drought treatment, these transgenic lines not only grew better, but also showed higher seed germination rates than wild-type plants. Gene expression analysis revealed that key genes in proline biosynthesis pathways were up-regulated in FaNAC2 overexpression lines, while its catabolic pathway genes were down-regulated and proline was accumulated more with the overexpression of FaNAC2 after stress treatments. Furthermore, the gene expression of abscisic acid biosynthesis was also promoted. Our results demonstrate that FaNAC2 plays an important positive role in response to different abiotic stresses and may be further utilized to improve the stress tolerance of strawberry plants.

Retrievals of ice cloud properties require accurate estimates of ice particle mass. Empirical mass–dimensional (m–D) relationships in the form m = a D b are widely used and usually universally applied across the complete range of particle sizes. For the first time, the dependence of a and b coefficients in m–D relationships on median mass diameter (Dmm) is studied. Using combined cloud microphysical data collected during the Olympic Mountains Experiment and coincident observations from Airborne Precipitation Radar Third Generation, Dmm-dependent (a, b) coefficients are derived and represented as surfaces of equally plausible solutions determined by some tolerance in the chi-squared difference χ 2 that minimizes the difference between observed and retrieved radar reflectivity. Robust dependences of a and b on Dmm are shown with both parameters significantly decreasing with Dmm, leading to smaller effective densities for larger Dmm ranges. A universally applied constant m–D relationship overestimates the mass of large aggregates when Dmm is between 3–6 mm and temperatures are between −15–0 °C. Multiple m–D relations should be applied for different Dmm ranges in retrievals and simulations to account for the variability of particle sizes that are responsible for the mass and thus for the variability of particle shapes and densities.

This study investigated a novel method of fusing visible (VIS) and infrared (IR) images with the major objective of obtaining higher-resolution IR images. Most existing image fusion methods focus only on visual performance and many fail to consider the thermal physical properties of the IR images, leading to spectral distortion in the fused image. In this study, we use the IR thermal physical property to correct the VIS image directly. Specifically, the Stefan-Boltzmann Law is used as a strong constraint to modulate the VIS image, such that the fused result shows a similar level of regional thermal energy as the original IR image, while preserving the high-resolution structural features from the VIS image. This method is an improvement over our previous study, which required VIS-IR multi-wavelet fusion before the same correction method was applied. The results of experiments show that applying this correction to the VIS image directly without multi-resolution analysis (MRA) processing achieves similar results, but is considerably more computationally efficient, thereby providing a new perspective on VIS and IR image fusion.

One new flavonoid named (2R,3R)-7-O-galloylplumbocatechin A (1) and three known flavonoids, (−)-5,3',4',5'-tetrahydroxyflavan-7-gallate (2), (+)-3,5,3',4',5'-penta-hydroxyflavan-7-gallate (3), and (−)-7,4'-di-O-galloyltricetiflavan (4), were isolated from Pithecellobium clypearia Benth. Their structures were elucidated based on spectroscopic analysis, including homonuclear and heteronuclear correlation NMR (HSQC and HMBC) experiments. In vitro assays, compounds 1 and 2 showed moderate inhibitory effects against influenza H1N1 virus neuraminidase (NA). Compounds 1–4 were all found to inhibit the expression of proinflammatory cytokines IL-6 or MCP-1 induced by influenza H1N1 virus in human A549 lung carcinoma cells.

Coastal Louisiana hosts 37% of the coastal wetland area in the conterminous US, including one of the deltaic coastal regions more susceptible to the synergy of human and natural impacts causing wetland loss. As a result of the construction of flood protection infrastructure, dredging of channels across wetlands for oil/gas exploration and maritime transport activities, coastal Louisiana has lost approximately 4900 km2 of wetland area since the early 1930s. Despite the economic relevance of both wetland biomass and net primary productivity (NPP) as ecosystem services, there is a lack of vegetation simulation models to forecast the trends of those functional attributes at the landscape level as hydrological restoration projects are implemented. Here, we review the availability of peer-reviewed biomass and NPP wetland data (below and aboveground) published during the period 1976−2015 for use in the development, calibration and validation of high spatial resolution (

Barrier islands are dynamic environments because of their position along the marine–estuarine interface. Geomorphology influences habitat distribution on barrier islands by regulating exposure to harsh abiotic conditions. Researchers have identified linkages between habitat and landscape position, such as elevation and distance from shore, yet these linkages have not been fully leveraged to develop predictive models. Our aim was to evaluate the performance of commonly used machine learning algorithms, including K-nearest neighbor, support vector machine, and random forest, for predicting barrier island habitats using landscape position for Dauphin Island, Alabama, USA. Landscape position predictors were extracted from topobathymetric data. Models were developed for three tidal zones: subtidal, intertidal, and supratidal/upland. We used a contemporary habitat map to identify landscape position linkages for habitats, such as beach, dune, woody vegetation, and marsh. Deterministic accuracy, fuzzy accuracy, and hindcasting were used for validation. The random forest algorithm performed best for intertidal and supratidal/upland habitats, while the K-nearest neighbor algorithm performed best for subtidal habitats. A posteriori application of expert rules based on theoretical understanding of barrier island habitats enhanced model results. For the contemporary model, deterministic overall accuracy was nearly 70%, and fuzzy overall accuracy was over 80%. For the hindcast model, deterministic overall accuracy was nearly 80%, and fuzzy overall accuracy was over 90%. We found machine learning algorithms were well-suited for predicting barrier island habitats using landscape position. Our model framework could be coupled with hydrodynamic geomorphologic models for forecasting habitats with accelerated sea-level rise, simulated storms, and restoration actions.

Replicating circular RNAs are independent plant pathogens known as viroids, or act to modulate the pathogenesis of plant and animal viruses as their satellite RNAs. The rate of discovery of these subviral pathogens was low over the past 40 years because the classical approaches are technical demanding and time-consuming. We previously described an approach for homology-independent discovery of replicating circular RNAs by analysing the total small RNA populations from samples of diseased tissues with a computational program known as progressive filtering of overlapping small RNAs (PFOR). However, PFOR written in PERL language is extremely slow and is unable to discover those subviral pathogens that do not trigger in vivo accumulation of extensively overlapping small RNAs. Moreover, PFOR is yet to identify a new viroid capable of initiating independent infection. Here we report the development of PFOR2 that adopted parallel programming in the C++ language and was 3 to 8 times faster than PFOR. A new computational program was further developed and incorporated into PFOR2 to allow the identification of circular RNAs by deep sequencing of long RNAs instead of small RNAs. PFOR2 analysis of the small RNA libraries from grapevine and apple plants led to the discovery of Grapevine latent viroid (GLVd) and Apple hammerhead viroid-like RNA (AHVd-like RNA), respectively. GLVd was proposed as a new species in the genus Apscaviroid, because it contained the typical structural elements found in this group of viroids and initiated independent infection in grapevine seedlings. AHVd-like RNA encoded a biologically active hammerhead ribozyme in both polarities, and was not specifically associated with any of the viruses found in apple plants. We propose that these computational algorithms have the potential to discover novel circular RNAs in plants, invertebrates and vertebrates regardless of whether they replicate and/or induce the in vivo accumulation of small RNAs.

A new nortriterpenoid, 19(R)-hydroxyl-wuweizidilactone H (1), and a sesquiterpene, (6R)-β-chamigrenic acid (2), together with one known nortriterpenoid, wuweizidilactone H (3), and three known hepatoprotective lignans, micrantherin A (4), gomisin M2 (5) and schizandrin (6) were isolated from the fruit of Schisandra chinensis. Their structures were elucidated by UV, IR, HRESIMS, NMR spectra and X-ray analysis. Among them, the absolute configuration of 2 was confirmed for the first time. In vitro assays, compounds 4–6 (10 μM) exhibited hepatoprotective activities (survival rate: 44%, 43% and 44%) against damage induced by N-acetyl-p-aminophenol (APAP) in human liver carcinoma (HepG2) cells.