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Soil biodiversity and the structure of soil animal communities are important foundations for forest ecosystem functions. Forest gap formation is an important forest management practice used to transform monocultures into mixed forests. However, whether and how gap size and age affect soil biodiversity and modify nematode communities remains limited. We manipulated gap size (100, 200, and 400 m2) in Pinus massoniana plantations and studied the communities of soil nematodes, bacteria, fungi, and understory plants two and four years after gap formation. Compared to the no-gap treatment, soil nematode abundance across forest gaps increased by a factor of 1.40, which was largely attributed to the increase in herbivorous nematodes as the abundance and diversity of understory plants increased. The increased abundance of soil nematodes in forest gaps was also associated with increased soil pH presumably related to reduced input of pine needles. Furthermore, the abundance (−5.3 %) and diversity (−25.1 %) of soil nematodes decreased with gap age, presumably because of increased soil temperature and decreased soil moisture in the four- compared to the two-year-old gaps. In contrast to nematodes, the abundance and diversity of soil bacteria (21.8 % and 7.1 %) and fungi (10.5 % and 10.0 %) increased significantly with gap age. Overall, forest gaps increased the diversity of understory plants and soil biota, and changed the community and functional group structure of soil nematodes. These results provide guidelines for fostering soil biodiversity and maintaining soil functioning when transforming coniferous forests into mixed forests.

The combined cadmium (Cd) and acid rain pollution poses a significant threat to the global ecological environment. Previous studies on the combined adverse effects have predominantly focused on the aboveground plant physiological responses, with limited reports on the microbial response in the rhizosphere soil. This study employed Populus beijingensis seedlings and potting experiments to simulate the impacts of combined mild acid rain (pH=4.5, MA) or highly strong acid rain (pH=3.0, HA), and soil Cd pollution on the composition and diversity of microbial communities, as well as the physiochemical properties in the rhizosphere soil. The results showed that Cd decreased the content of inorganic nitrogen, resulting in an overall decrease of 49.10 % and 46.67 % in ammonium nitrogen and nitrate nitrogen, respectively. Conversely, acid rain was found to elevate the content of total potassium and soil organic carbon by 4.68 %-6.18 % and 8.64–19.16 %, respectively. Additionally, simulated acid rain was observed to decrease the pH level by 0.29–0.35, while Cd increased the pH level by 0.11. Moreover, Cd alone reduced the rhizosphere bacterial diversity, however, when combined with acid rain, regardless of its intensity, Cd was observed to increase the diversity. Fungal diversity was not influenced by the acid rain, but Cd increased fungal diversity to some extend under HA as observed in bacterial diversity. In addition, composition of the rhizosphere bacterial community was primarily influenced by the inorganic nitrogen components, while the fungal community was driven mainly by soil pH. Furthermore, “Metabolism” was emerged as the most significant bacterial function, which was markedly affected by the combined pollution, while Cd pollution led to a shift from symbiotroph to other trophic types for fungi. These findings suggest that simulated acid rain has a mitigating effect on the diversity of rhizosphere bacteria affected by Cd pollution, and also alters the trophic type of these microorganisms. This can be attributed to the acid rain-induced direct acidic environment, as well as the indirect changes in the availability or sources of carbon, nitrogen, or potassium.

A full factorial experiment was conducted to analyze the main and interaction effects on the physical and mechanical properties of Cupressus funebris Endl. wood subjected to vacuum heat modification. The response variables evaluated were mass loss rate (ML, %), moisture resistance (MR, %), and modulus of rupture in bending (MOR, MPa). The results reveal significant variations in the effects of modification time, holding temperature, and vacuum pressure as independent factors, along with varying degrees of interaction effects among them. Simplifying the analysis model, a regression equation was derived to describe the relationship between the response variable (mass loss rate) and the factors: The model achieved an R-squared value of 96.0% and an R-squared (predicted) value of 73.7%, indicating good overall predictive performance. Optimal process parameters for mid-temperature vacuum heat modification of cypress were determined based on the mass loss rate and modulus of rupture (MOR), resulting in a modification temperature of 120 °C, holding time of 5 h, and a pressure intensity of 0.1. The reliability of the full factorial experiment was further confirmed through orthogonal testing.

The linkage, coordination, and complementary cooperation of energy supply can improve the efficiency of transportation and utilization. At present, the level of new energy consumption needs to be improved, the coordination of the source network load storage link is insufficient, and the insufficient complementarity of various types of power sources in the power system. This article fully explores the differences and complementarities of various types of wind-solar-hydro-thermal-storage power sources, a hierarchical environmental and economic dispatch model for the power system has been established. Among them, the upper level model takes the flexible consumption of new energy as the optimization goal, the middle level model uses a combination of hydropower station and energy storage to minimizes the fluctuation variance and peak-to-valley difference of the net load curve, the lower level model aims to achieve optimal environmental and economic benefits of the power system, comprehensively considers the coal consumption cost, startup and shutdown cost, energy storage operation cost, and pollutant emissions of thermal power units, determines the startup and shutdown mode and output power of thermal power units. Finally, an improved IEEE 6-machine 30-node system is used as an example for simulation analysis, the results show that after applying the proposed hierarchical environmental and economic dispatch strategy of the power system, the fluctuation variance and the peak-to-valley difference of the net load curve have been reduced by 46.3% and 31.5%, respectively, and the environmental and economic benefits of the system is improved by 5.1% compared with the traditional economic dispatch strategy. It can meet the requirements of energy system cleaning and decarbonization while improving the operation economy, which verifies the effectiveness of the proposed environmental economic dispatch model.

An accurate prediction of peak discharge in watersheds is critical not only for water resource management, but also for understanding the complex relationships of hydrological processes. In this study, a modified peak discharge formula based on the Chemicals, Runoff, and Erosion from Agricultural Management Systems (CREAMS) model was developed by introducing rainfall intensity and soil moisture factors. The reliability of the proposed method was tested with data from 1464 storm events in 41 watersheds and was applied to 256 storm events in five remaining typical watersheds using the optimized parameters. The results indicate that the proposed method is highly accurate in terms of model efficiency, as determined by Nash–Sutcliffe efficiencies (NSEs) of 88.60%, 74.04%, and 90.12% during the calibration, validation, and application cases, respectively. Furthermore, it performed better than the original and modified CREAMS methods. Subsequently, using the parameters derived from the initial 41 watersheds and the runoff estimated using the modified Soil Conservation Service curve number (SCS–CN) method, the proposed method was used to predict the peak discharge from the last five typical watersheds. Large NSE (63.88–80.83%) and low root mean square error (RMSE) values (0.31–35.93 m3s-1) were obtained for the five watersheds. Overall, the proposed peak discharge model, combined with the modified SCS-CN method, may accurately predict event-based peak discharge and runoff for general applications under various hydrological and geomorphic conditions in the Loess Plateau region.

High-resolution satellite videos realize the short-dated gaze observation of the designated area on the ground, and its emergence has improved the temporal resolution of remote sensing data to the second level. Single object tracking (SOT) task in satellite video has attracted considerable attention. However, it faces challenges such as complex background, poor object feature representation, and lack of publicly available datasets. To cope with these challenges, a ThickSiam framework consisting of a Thickened Residual Block Siamese Network (TRBS-Net) for extracting robust semantic features to obtain the initial tracking results and a Remoulded Kalman Filter (RKF) module for simultaneously correcting the trajectory and size of the targets is designed in this work. The results of TRBS-Net and RKF modules are combined by an N-frame-convergence mechanism to achieve accurate tracking results. Ablation experiments are implemented on our annotated dataset to evaluate the performance of the proposed ThickSiam framework and other 19 state-of-the-art trackers. The comparison results show that our ThickSiam tracker obtains a precision value of 0.991 and a success value of 0.755 while running at 56.849 FPS implemented on one NVIDIA GTX1070Ti GPU.

To address the challenge of wind turbines meeting primary frequency regulation requirements, incorporating energy storage devices to handle most of the frequency regulation tasks would result in increased operational costs. When a wind turbine rotor accelerates, it deviates from the maximum power tracking point (MPPT), leading to reduced output while retaining significant rotational kinetic energy. Based on this characteristic, a primary frequency regulation strategy is proposed that coordinates the rotor kinetic energy of a double-fed induction generator (DFIG) with supercapacitors (SCs). Supercapacitors provide power support during low-frequency conditions, while accelerating the wind turbine rotor reduces output during high-frequency conditions. Additionally, continuous attention is given to subsequent frequency changes. In case of short-term, low-frequency conditions, stored kinetic energy is released for power support, establishing a mechanism for wind turbine kinetic energy recovery and release. This mechanism reduces charging and discharging requirements for supercapacitors, extends their service life, and considers both wind turbine frequency regulation requirements and economy. Finally, using MATLAB 2020/Simulink platform allows for the verification of the effectiveness and rationality of this proposed method.

Abstract The fourth paradigm of science has achieved great success in material discovery and it highlights the sharing and interoperability of data. However, most material data are scattered among various research institutions, and a big data transmission will consume significant bandwidth and tremendous time. At the meanwhile, some data owners prefer to protect the data and keep their initiative in the cooperation. This dilemma gradually leads to the “data island” problem, especially in material science. To attack the problem and make full use of the material data, we propose a new strategy of neural network training based on multi-source databases. In the whole training process, only model parameters are exchanged and no any external access or connection to the local databases. We demonstrate its validity by training a model characterizing material structure and its corresponding formation energy, based on two and four local databases, respectively. The results show that the obtained model accuracy trained by this method is almost the same to that obtained from a single database combining all the local ones. Moreover, different communication frequencies between the client and server are also studied to improve the model training efficiency, and an optimal frequency is recommended.

The grate bars are a critical and easily consumable component of the sintering machine, and the control of their corrosion is of great importance to reduce their consumption. This investigation focused on revealing the physicochemical profile of the failure sintering grate bar and the potential corrosion mechanism. The results showed that the superficial area of the failure grate bar consisted of the adhesive layer, corrosion layer, and metal layer from outside to inside. The adhesion layer is characterised by a loose structure, consisting of higher contents of alkali chloride salts and sulphate, which were the typical corrosive substances. The main components of the corrosion layer were Fe2O3 and Cr2O3; the metal layer structure was dense, which remained the original composition of the grate bar. Based on the characteristics of sintering flue gas, the potential corrosion mechanism was summarised into three main types: (a) high-temperature oxidation, due to the periodic exposure of the grate bars to the high-temperature sintering flue; (b) chlorine corrosion, due to the existence of HCl, alkali (heavy) metal chloride salts (KCl, NaCl, PbCl2) in sintering flue gas, which formed the adhesive layer of grate bars; (c) sulphate corrosion, due to the existence of high SO2 contents and sulphate in the flue gas. The research findings are important to guide the development of grate bar corrosion control technologies.

Objectives: Epithelial-mesenchymal transition (EMT) of renal tubular epithelial cells (RTECs) is a pathogenic factor for renal interstitial fibrosis (RIF). Interleukin-33 (IL-33) is related to the occurrence and development of RIF, but the underlying mechanism remains unclear. Here, we investigated whether IL-33 mediates the EMT of RTECs by activating the NF-κB/Twist1 signalling pathway. Methods: In vivo, the RIF animal model induced by unilateral ureteral obstruction (UUO) was established. The effects of exogenous IL-33 and anti-IL-33 antibodies were evaluated. In vitro, the EMT of RTECs was induced by IL-33. The inhibition of the nuclear factor kappa-B (NF-κB) by the pyrrolidine dithiocarbamate (PDTC) and the knockdown of the suppression of tumorigenicity 2 (ST2) by small interference RNA were used to observe whether IL-33 mediates the EMT of RTECs through the NF-κB/Twist1 signaling pathway. Results: In vivo, exogenous IL-33 significantly aggravated UUO-induced pathological damage and collagen deposition, down-regulated E-cadherin expression, and up-regulated α-smooth muscle actin and Vimentin expressions. Moreover, exogenous IL-33 increased the levels of phospho-IκB-α (p-IκB-α) and phospho-NF-κB p65 (p-NF-κB p65), NF-κB p65 nuclear translocation, and Twist1 nuclear expression. However, these effects were reversed by the anti-IL-33 antibody. In vitro , the increases in the levels of p-IκB-α, p-NF-κB p65, NF-κB p65 nuclear translocation, and Twist1 nuclear expression induced by IL-33 were inhibited by the knockdown of PDTC or ST2. IL-33-mediated EMT of RTECs was also significantly reversed. However, NF-κB inhibitor PDTC had no significant effect on ST2 expression. Conclusions: The IL-33/ST2 axis may up-regulate the expression of Twist1 through the NF-κB signalling pathway, thereby inducing the EMT of RTECs and leading to RIF.

Abstract In this paper, the control problem of multi‐robot systems under temporal logic tasks with limited time and logic constraints is studied, where each robot is required to reach the specified region in a given time and avoid collision all the time. Since the cooperative collision avoidance task of one robot depends on other robots' behaviors, the satisfaction of all the tasks may be conflicting. In this work, a distributed model predictive control (DMPC) strategy is proposed for conflicting temporal logic tasks. First, signal temporal logic (STL) is adopted to formally describe the temporal logic tasks. Based on robust semantics of STL formulas, a reference trajectory for the satisfaction degree of the task is designed to determine the short‐term task in the optimization horizon. In the DMPC optimization problem, the compatibility constraints are introduced to redesign the collision avoidance constraints, such that the collision avoidance tasks can be fulfilled using neighbouring robots' predicted information of the last time instant. Then, the terminal constraint is designed by the short‐term motion task which enforces each robot to move towards the goal region within the specified time interval. For conflicting tasks, a slack parameter is introduced in the terminal set to relax the motion task of each robot. The recursive feasibility of the DMPC algorithm is guaranteed, and the relaxed temporal logic tasks are fulfilled. In the proposed method, the discrete events including limited time and logic requirements are incorporated into the DMPC optimization problem, such that the motion task can be satisfied as much as possible and safety requirements are fulfilled. The effectiveness of the algorithm is illustrated by simulation and experiment results.

The second most prevalent neurodegenerative ailment, Parkinson’s disease (PD), is characterized by both motor and non-motor symptoms. Levodopa is the backbone of treatment for PD at the moment. However, levodopa-induced side effects, such as dyskinesia, are commonly seen in PD patients. Recently, several antibiotics were found to present neuroprotective properties against neurodegenerative and neuro-inflammatory processes, which might be developed to effective therapies against PD. In this study, we aimed to identify if levodopa treatment could influence the gut bacterial antibiotic resistance in PD rat. Fecal samples were collected from healthy rats and 6-OHDA induced PD rats treated with different doses of levodopa, metagenomic sequencing data showed that levodopa resulted in gut bacteria composition change, the biomarkers of gut bacteria analyzed by LEfSe changed as well. More interestingly, compared with levodopa (5 mg/kg)-treated or no levodopa-treated PD rats, levodopa (10 mg/kg) caused a significant decrease in the abundance of tetW and vanTG genes in intestinal bacteria, which were related to tetracycline and vancomycin resistance, while the abundance of AAC6-lb-Suzhou gene increased apparently, which was related to aminoglycosides resistance, even though the total quantity of Antibiotic Resistance Gene (ARG) and Antibiotic Resistance Ontology (ARO) among all groups did not significantly differ. Consequently, our results imply that the combination of levodopa and antibiotics, such as tetracycline and vancomycin, in the treatment of PD may decrease the amount of corresponding antibiotic resistance genes in gut bacteria, which would give a theoretical basis for treating PD with levodopa combined with tetracycline and vancomycin in the future.

Background. Non-small cell lung cancer (NSCLC) is the most prevalent malignant tumor of the lung cancer, for which the molecular mechanisms remain unknown. In this study, we identified novel biomarkers associated with the pathogenesis of NSCLC aiming to provide new diagnostic and therapeutic approaches for NSCLC by bioinformatics analysis. Methods. From the Gene Expression Omnibus database, GSE118370 and GSE10072 microarray datasets were obtained. Identifying the differentially expressed genes (DEGs) between lung adenocarcinoma and normal samples was done. By using bioinformatics tools, a protein-protein interaction (PPI) network was constructed, modules were analyzed, and enrichment analyses were performed. The expression and prognostic values of 14 hub genes were validated by the GEPIA database, and the correlation between hub genes and survival in lung adenocarcinoma was assessed by UALCAN, cBioPortal, String and Cytoscape, and Timer tools. Results. We found three genes (PIK3R1, SPP1, and PECAM1) that have a clear correlation with OS in the lung adenocarcinoma patient. It has been found that lung adenocarcinoma exhibits high expression of SPP1 and that this has been associated with poor prognosis, while low expression of PECAM1 and PIK3R1 is associated with poor prognosis P

Understanding fine root morphology is crucial to uncover water and nutrient acquisition and transposition of fine roots. However, there is still a lack of knowledge regarding how the soil environment affects the fine root morphology of various root orders in the stable forest ecosystem. Therefore, this experiment assessed the response strategies of fine root morphology (first- to fifth -order fine roots) in four different soil environments. The results showed that fine root morphology was related to soil environment, and there were significant differences in specific root length (SRL), specific surface area (SRA), diameter (D), and root tissue density (RTD) of first- and second -order fine roots. Soil total nitrogen (TN), alkaline nitrogen (AN) and available phosphorus (AP) were positively correlated with SRL and SRA and negatively correlated with D and RTD. Soil moisture (SW) was positively correlated with the D and RTD of first- and second-order fine roots and negatively correlated with the SRL and SRA. Soil temperature (ST), organic carbon (OC), soil bulk density (SBD) and soil porosity (SP) were not significantly correlated with the D, SRL, SRA, and RTD of the first- and second -order fine roots. AN was positively correlated with SRL and SRA and negatively correlated with both D and RTD in the first- and second -order fine roots, and the correlation coefficient was very significant. Therefore, we finally concluded that soil AN was the most critical factor affecting root D, SRL, SRA and RTD of fine roots, and mainly affected the morphology of first- and second -order fine roots. In conclusion, our research provides support for understanding the relationship between fine root morphology and soil environment, and indicates that soil nutrient gradient forms good root morphology at intraspecific scale.

The natural regeneration of seedlings is a key factor for forest succession. Nevertheless, studies explaining the mechanism of growth and biomass allocation in regenerated seedlings after disturbance are lacking. Therefore, we measured the growth, biomass accumulation, and biomass allocation in current-age seedlings of Pinus massoniana after selective logging (logging of competitive trees, LCT; logging of inferior trees, LIT; and unlogged control, CK), and established structural equation models (SEMs) among the spatial structure characteristic indexes of the stand, environmental factors, and biomass allocation in different organs. As compared to the CK, the mingling index (M), uniform angle index (W), opening degree (O), soil organic carbon (SOC), available nitrogen (SAN), available phosphorus (SAP), available potassium (SAK), and bulk density (SBD) significantly increased (p < 0.05), while the competition index (CI) and neighborhood comparison (U) significantly decreased after logging (p < 0.05). After the LCT, seedling branch biomass improved, with an increase in the ground-diameter, crown-root ratio, and seedling quality index. More biomass was allocated to foliage and roots by an increase in the height and height-diameter ratio under the LIT. In the CK, increasing stem biomass helped the seedlings absorb and utilize more light. The Pearson correlation coefficient showed that biomass allocation to organs was independent, and seedlings adopted the strategies of heterogeneous adaptation and growth, thereby resulting in the separation of the allocation patterns among the organs. As per the redundancy analysis (RDA), CI was the main factor in biomass allocation. Environmental factors had direct effects on biomass allocation to organs, while the stand spatial structure characteristic indexes had indirect effects on biomass allocation based on SEMs. In summary, the LCT had significant, albeit indirect, effects on SOC, SAN, and SBD by reducing the CI for the regeneration and growth of seedlings in the stand, which was of great significance to the sustainable development of the forest stand of P. massoniana.

Abstract Background Stem CO2 efflux (E S) plays a critical role in the carbon budget of forest ecosystems. Thinning is a core practice for sustainable management of plantations. It is therefore necessary and urgent to study the effect and mechanism of thinning intensity (TI) on E S. Methods In this study, five TIs were applied in Larix principis-rupprechtii Mayr 21-, 25-, and 41-year-old stands in North China in 2010. Portable infrared gas analyzer (Li-8100 A) was used to measure E S and its association with environmental factors at monthly intervals from May to October in 2013 to 2015. In addition, nutrients, wood structure and nonstructural carbon (NSC) data were measured in August 2016. Results The results show that E S increased with increasing TI. The maximum E S values occurred at a TI of 35 % (3.29, 4.57 and 2.98 µmol∙m-2∙s-1) and were 1.54-, 1.94- and 2.89-fold greater than the minimum E S value in the CK stands (2.14, 2.35 and 1.03 µmol∙m-2∙s-1) in July for the 21-, 25- and 41-year-old forests, respectively. The E S of the trees in low-density stands was more sensitive to temperature than that of the trees in high-density stands. Soluble sugars (SS) and temperature are the main factors affecting E S. When the stand density is low enough as 41-year-old L. principis-rupprechtii forests with TI 35 %, bark thickness (BT) and humidity should be considered in addition to air temperature (T a), wood temperature (T w), sapwood width (SW), nitrogen concentration (N) and SS in the evaluation of E S. If a change in stand density is ignored, the CO2 released from individual 21-, 25- and 41-year-old trees could be underestimated by 168.89 %, 101.94 % and 200.49 %, respectively. CO2 release was estimated based on the stem equation in combination with the factors influencing E S for reference. Conclusions We suggest that it is not sufficient to conventional models which quantify E S only by temperature and that incorporating the associated drivers (e.g. density, SS, SW and N) based on stand density into conventional models can improve the accuracy of E S estimates.

Weeping cypress is an endemic tree species that is widely planted in China, and the simple stand structure and fragile ecosystem of its plantation are common issues. Exploring the effect of different gap sizes on the soil bacterial community structure of weeping cypress plantations can provide a theoretical basis for the near-natural management of forest plantations. We, therefore, constructed three kinds of forest gaps with different sizes in weeping cypress plantations, namely, small (50–100 m2), medium (100–200 m2), and large gaps (400–667 m2), for identifying the key factors that affect soil bacterial communities following the construction of forest gaps. The results suggested that the herb layer was more sensitive than the shrub layer, while the Simpson, Shannon, and richness indices of the herb layer in plots with gaps were significantly higher than those of designated sampling plots without any gaps (CK). The presence of large gaps significantly increased the understory plant diversity and the Shannon and Simpson indices of the soil bacterial alpha diversity. There were obvious changes in the community composition of soil bacteria following the construction of forest gaps. The dominant bacterial phyla, orders, and functions were similar across the plots with different gap sizes. Of the indicator bacterial species, the abundance of the nitrogen-fixing bacteria, Lysobacter_ yangpyeongensis, and Ensifer_meliloti, was significantly different across plots with different gap sizes and accounted for a large proportion of the bacterial population of plots with medium and large gaps. The understory plant diversity was mostly related to the soil bacterial community than to other soil factors. The results of structural equation modeling indicated that the understory plant diversity was the most important environmental factor in driving the composition and diversity of bacterial communities. The construction of forest gaps significantly improved the understory plant diversity, physicochemical properties of the soil, and bacterial diversity in weeping cypress plantations, and the results of the comprehensive evaluation were in the order: large gaps > small gaps > medium gaps > CK. Our results suggested that large gaps are beneficial for the diversity of above-ground plant communities and underground soil bacterial communities.

Fine root anatomy plays an important role in understanding the relationship between fine root function and soil environment. However, in different soil environments, the variation of fine root anatomical structure in different root sequences is not well studied. We measured the soil conditions and anatomical structure characteristics (root diameter, cortical tissue, vascular tissue and xylem) of fine roots of Cupressus funebris in four experimental sites, and analyzed each level of fine roots separately. We link these data to understand the relationship between fine root anatomy and soil conditions. We found that the anatomical structure of fine roots is closely related to soil environmental factors. The fine roots of lower root order are mainly affected by soil nutrients. Among them, the cortical tissue of first-order fine roots was positively correlated with potassium and phosphorus, but negatively correlated with nitrogen, while second- and third-order fine roots was positively correlated with soil total potassium and negatively correlated with nitrogen and phosphorus. For the fine roots of high root order, the cortical tissue disappeared, and the secondary vascular tissue was mainly affected by soil moisture. In addition, we also found that the division of fine root functional groups is not fixed. On the one hand, the function of third-order fine roots will slip. For example, the decrease of soil moisture will promote the transformation of third-order fine roots into transport roots, and the reduction of nitrogen will promote the transformation of third-order fine roots into absorption roots to fix nitrogen. This transformation strategy can effectively prevent the restriction of soil nutrients on plant growth. On the other hand, with the change of habitat, the first- and second-order fine roots are still the absorbing root, and the fourth- and fifth-order fine roots are still the transport root, but the efficiency of absorption and transport will be affected. In conclusion, our findings emphasize the fine roots in different soil environment to show high levels of plasticity, shows that fine root anatomical structure changes may make plants, and reveals that the fine is just order of reaction and its mechanism in the soil environment.

Non-point source pollution caused by surface runoff has been a popular hydrological and environmental safety issue and has attracted extensive attention from global scholars. To identify the optimal vegetation coverage of Festuca arundinacea grassland for controlling soil erosion and purifying surface runoff, bare land was chosen as the control in this experiment. Simulated rainfall experiments were carried out with three levels of coverage (low coverage, moderate coverage and full coverage) under four slope conditions (flat slope, gentle slope, medium slope, and steep slope) and at four rainfall intensities (moderate rainfall, heavy rainfall, rainstorm and heavy rainstorm). The comprehensive evaluation results suggested that the capacity of Festuca arundinacea grassland for reducing the surface runoff, sediment yield, suspended solids (SS), total nitrogen (TN), total phosphorus (TP) and chemical oxygen demand (COD) decreased with increasing rainfall intensity and slope but increased with increasing vegetation coverage. Structural equation model (SEM) results suggested that there were positive relationships between the vegetation coverage and purification capacity index and negative correlations between the rainfall intensity and slope and the purification capacity index. The response surface analysis results suggested that the optimal vegetation coverage should be higher than 84% and that the slope should be smaller than 10° for controlling soil erosion and avoiding pollution via diffusion with surface runoff in Festuca arundinacea grassland. This study proposes recommendations for the vegetation configuration pattern in the development and management of runoff purification systems.

In recent years, remote sensing techniques such as satellite and drone-based imaging have been used to monitor Pine Wilt Disease (PWD), a widespread forest disease that causes the death of pine species. Researchers have explored the use of remote sensing imagery and deep learning algorithms to improve the accuracy of PWD detection at the single-tree level. This study introduces a novel framework for PWD detection that combines high-resolution RGB drone imagery with free-access Sentinel-2 satellite multi-spectral imagery. The proposed approach includes an PWD-infected tree detection model named YOLOv5-PWD and an effective data augmentation method. To evaluate the proposed framework, we collected data and created a dataset in Xianning City, China, consisting of object detection samples of infected trees at middle and late stages of PWD. Experimental results indicate that the YOLOv5-PWD detection model achieved 1.2% higher mAP compared to the original YOLOv5 model and a further improvement of 1.9% mAP was observed after applying our dataset augmentation method, which demonstrates the effectiveness and potential of the proposed framework for PWD detection.

Thanks to the development of the technologies in the wireless communications and Internet of Things (IoT), the adoption of mobile devices is growing rapidly. Accordingly, the number of multimedia applications like face recognition and augmented reality generated from various mobile devices is growing at an unprecedented rate. The processing of these multimedia applications needs a lot of computation resources and has to be processed as quickly as possible. However, as these mobile devices have limited computation resources, the undesirable response delay will occur. By offloading the multimedia applications to the edge cloud close to the access point (AP) or the cellular base station (BS), mobile edge computing (MEC) is considered as a prospective approach to improve the quality of service (QoS) and enhance the computing capacity of mobile devices. Multimedia applications offloading in a MEC system are studied in this paper. The objective of the studied problem is to minimize the execution delay of multimedia applications of all mobile devices by allocating both the communication resource and the computing resource in the edge servers. An optimization problem is formulated and an efficient multimedia applications offloading scheme is proposed to get the solution. Simulation results are conducted to verify the proposed application offloading method, which show that there is a significant execution delay reduction.

The decline in forest ecological function caused by pure forest plantations planted in the Yangtze River basin is becoming increasingly serious. To investigate this problem, we selected the local low-efficiency weeping cypress plantations for forest gap transformation. Three forest gap sizes, specifically large, medium, and small gaps, were established, and the effects of gap sizes on soil bacterial community structure and diversity in winter and summer were studied compared to no gaps (CK; control). Compared to CK, forest gaps had a significant effect on soil organic carbon (SOC) and soil total nitrogen (TN), and the highest values of SOC and soil TN under two seasons occurred in large forest gaps. The interactions of forest gap sizes and seasons had significant effects on pH, SOC, TN, and alpha diversity indices, including Simpson, Chao1, and ACE indices. Compared to winter, forest gaps significantly increased the soil bacterial community diversity indices in summer. Forest gap sizes significantly affected the composition of the bacterial community, but the composition of the dominant bacteria at the phyla and genera levels was similar. Linear discriminant effect size (LEfSe) analysis showed that there were 32 indicator bacterial species in two seasons. Co-occurrence network analysis revealed that the relationship of the soil bacterial community at the phyla level was complex, and there was a significant positive correlation among bacterial species. Soil bulk density (BD) and soil moisture (SM) significantly affected the soil bacterial alpha diversity indices. The composition of the dominant bacteria at the phyla level was significantly affected by soil microbial carbon (MBC), whereas the composition of dominant bacteria at the genera level was affected by soil hydrolysable nitrogen (AN) and the carbon/nitrogen (C/N) ratio. In this study, compared to the other forest gaps, large forest gaps were more conducive to the accumulation of soil nutrients, thus improving the structure of the soil bacterial community. Importantly, changes in the soil bacterial community structure due to gap formation may have profound effects on soil biogeochemical processes in weeping cypress forest plantations.

The root system architecture (RSA), being a key characteristic of the root economic spectrum, describes the spatial arrangement and positioning of roots that determines the plant's exploration of water and nutrients in the soil. Still, it remains poorly understood how the RSA of woody plants responds to the demand for water and nutrients in different soil environments and how the uptake of these resources is optimized. Here we selected single-species plantations of Cupressus funebris and determined their topological index (TI), revised topological index (qa and qb), root link length (RLL), root branching rate (Rb and Ri:Ri+1), and in situ soil physicochemical properties to assess which root foraging strategies adopt in different soil environments among Guang'an City (GA), Suining City (SN), Mianyang City (MY), and Deyang City (DY) in China. We also tested the potential effects of different nutrients upon RSA according to its plastic phenotype. Principal component analysis (PCA) showed that levels of soil nutrients were the highest at DY, followed by MY and SN, and lower at GA. A dichotomous branching pattern was observed for GA, SN, and MY, but a herringbone branching pattern for DY. The RLL was ranked as GA, > SN, > MY > DY. The Rb of GA, SN, and MY was significantly lower than that of DY (p < 0.05). Among the different city regions, values of R1/R2 were the largest in different regions and those of R4/R5 the smallest. The cross-sectional area of the root system did not differ between any two connected branch orders. The TI, qa, and RLL were significantly and negatively correlated with soil's water content, porosity, total nitrogen, total potassium, available nitrogen, and available phosphorus (p < 0.05), whereas they all had significant, positive relationships with soil temperature (p < 0.05). The Rb was significantly and positively correlated with total potassium in soil (p < 0.05). Redundancy analysis showed that total potassium was the main factor driving variation in RSA. Our results emphasize that the RSA is capable of corresponding plastic alterations by changing its number of internal or external links and the root link length of fine roots vis-à-vis a heterogeneous environment, thereby optimizing the rates of water capture and space utilization.

Abstract Background Salt stress is one of the main abiotic stresses that limits rice production worldwide. Rice salt tolerance at the bud burst stage directly affects the seedling survival rate and the final yield in the direct seeding cultivation model. However, the reports on quantitative trait locus (QTL) mapping and map-based cloning for salt tolerance at the bud burst stage are limited. Results Here, an F2:3 population derived from a cross between IR36 (salt-sensitive) and Weiguo (salt-tolerant) was used to identify salt-tolerant QTL interval at the bud burst stage using a whole-genome sequencing-based QTL-seq containing 40 extreme salt-tolerant and 40 extreme salt-sensitive individuals. A major QTL, qRSL7, related to relative shoot length (RSL) was detected on chromosome 7 using ΔSNP index algorithms and Euclidean Distance (ED) algorithms. According to single nucleotide polymorphisms (SNPs) between the parents, 25 Kompetitive allele-specific PCR (KASP) markers were developed near qRSL7, and regional QTL mapping was performed using 199 individuals from the F2:3 population. We then confirmed and narrowed down qRSL7 to a 222 kb genome interval. Additionally, RNA sequencing (RNA-seq) was performed for IR36 and Weiguo at 36 h after salt stress and control condition at the bud burst stage, and 5 differentially expressed genes (DEGs) were detected in the candidate region. The qRT-PCR results showed the same expression patterns as the RNA-seq data. Furthermore, sequence analysis revealed a 1 bp Indel difference in Os07g0569700 (OsSAP16) between IR36 and Weiguo. OsSAP16 encodes a stress-associated protein whose expression is increased under drought stress. Conclusion These results indicate that OsSAP16 was the candidate gene of qRSL7. The results is useful for gene cloning of qRSL7 and for improving the salt tolerance of rice varieties by marker assisted selection (MAS).

Abstract Background Salinity-alkalinity stress is one of the major factors limiting rice production. Damage caused by alkaline salt stress is more severe than that caused by neutral salt stress. Alkali tolerance at the bud stage in rice directly affects seedling survival and final yield when using the direct seeding cultivation model. However, genetic resources (QTLs and genes) for rice breeders to improve alkali tolerance are limited. In this study, we combined linkage mapping and a genome-wide association study (GWAS) to analyze the genetic structure of this trait in japonica rice at the bud stage. Results A population of 184 recombinant inbred lines (RILs) was utilized to map quantitative trait loci (QTLs) for the root length under control condition (RL), alkaline stress (ARL) and relative root length (RRL) at the bud stage. A major QTL related to alkali tolerance at the rice bud stage, qAT11, was detected on chromosome 11. Interestingly, a GWAS identified a lead SNP (Chr_21,999,659) in qAT11 that was significantly associated with alkaline tolerance. After filtering by linkage disequilibrium (LD), haplotype analysis, quantitative real-time PCR, we obtained three candidate genes (LOC_Os11g37300, LOC_Os11g37320 and LOC_Os11g37390). In addition, we performed phenotype verification on the CRISPR/Cas9 mutant of LOC_Os11g37390. Conclusion Based on these results, LOC_Os11g37300, LOC_Os11g37320 and LOC_Os11g37390 were the candidate genes contributing to alkaline tolerance in japonica rice. This study provides resources for breeding aimed at improving rice responses to alkalinity stress.

With the rapid developing of Internet of Things (IoT) technologies, various kinds of IoT devices are connected over the Internet. Consequently, how to meet the requirements of executing IoT applications is becoming a critical issue. Offloading the IoT applications to the public cloud is an efficient approach to enhance the computing capabilities of these IoT devices. However, as there is a long distance from the IoT devices to the remote public cloud, transmission delay will be caused. Mobile edge computing (MEC) provides an effective solution to this issue since IoT devices are near to the servers of the MEC systems. Pricing and load balancing are two important factors for cloud service provision. Pricing is of paramount importance for cloud service provision, and load balancing is fully considered when cloud users select an edge cloud service provider (ESP) as it has a direct relation with the quality of cloud service. In multi-cloud systems, a cloud service broker (CSB) reserves cloud resources from multiple CSPs to provision cloud services to users. While existing work has put a lot of attention on IoT applications offloading to the MEC, many of them only considered one edge cloud scenario, ignoring the multi-MEC scenario. In this article, we investigate service pricing and selection for IoT applications offloading in a multi-MEC system with multiple ESPs. Specifically, we take load balancing into account. The studied problem is formulated as a Stackelberg game, where CSB first sets service price and load balancing strategies for the cloud services trying to get its maximized revenue. Then, IoT users make their decisions on which ESP they select service. By applying the backward induction approach, the optimal solutions are derived. The proposed scheme is verified through simulation results.

Traditional recognition methods for face local features have a low recognition rate, so the recognition method for face local features based on the fuzzy algorithm and intelligent data analysis was designed. Firstly, the wavelet denoising method was used to reduce the noise of face images, and adaptive template matching was performed on the obtained images. Then, the face information was encoded, and the face features were identified to locate the face features. On this basis, the principal components of the face were analyzed to obtain the global features of the face. Finally, through the candidate set of facial local feature recognition, the extraction of face local features, and the fusion of face local features, the recognition of local face features were realized. The experimental results show that the average recognition rate of this method is 88.84% in a noise environment and 97.3% in noise-free environment. It can accurately recognize the face local features, can meet the needs of recognition of the face local features, and has certain practical application significance.

We aimed to investigate the extent to which the initial state generated by unexpected loads, such as explosions and impacts on the remaining structure, affects the dynamic response of the structure. The study used the orthogonal test method to obtain orthogonal table L25 (53) by combining five levels of each of the three factors of column removal time and initial velocity, and the initial displacement of the remaining structure under three failure scenarios of the corner, side, and internal columns at the ground floor of the reinforced concrete frame structure. The degree of influence of different factors on the structural dynamic response, and the result of the unifactorial impact of initial velocity and initial displacement of the remaining structure on the structural dynamic response in the case of failure of the bottom side columns, were obtained by the polar difference method. The results show that the analysis using the orthogonal test polar difference method revealed that the initial displacement has a more significant influence on the dynamic response of the structure, forming the main influencing factor. At the same time, the failure time and initial velocity have a smaller influence on the dynamic response of the structure as secondary influencing factors. In the case of unifactorial influence, the initial upward displacement and initial upward velocity are detrimental to the structure, leading to progressive collapse. In contrast, the initial downward velocity and initial downward displacement are favorable.

Grapholita molesta (Busck) (Lepidoptera: Tortricidae), Oriental fruit moth (OFM), attacks fruits and shoots of the economically important trees in Rosaceae. Amygdalin is a cyanogenic glucoside of rosaceous plants that may be related to the seasonal patterns of infestation in many pests. The amygdalin concentration of fruits and shoots of peach, pear, and apple varies over the growing season. However, the relationship between the amygdalin concentration and G. molesta performance has not been reported. Here, we measured the performance (feeding, growth, development, and fecundity) of G. molesta larvae (as subsequent adults) reared on artificial diets with six amygdalin concentrations (0, 3, 6, 12, 24, and 48 mg/g), and we then calculated the population parameters. We found that these different concentrations of amygdalin affected the developmental time and fecundity, except for the proportion of larvae feeding on the diet and the survival rates of larvae and pupae. When compared with the control diet without amygdalin, diets with 3 or 6 mg/g (low and moderate concentrations) of amygdalin shortened developmental times and increased the number of eggs laid by females; however, a diet with 12 mg/g (moderate concentration) of amygdalin only increased the number of eggs laid by females and did not affect the larval and pupal developmental rate. A diet with 48 mg/g (high concentration) of amygdalin prolonged developmental times and reduced the number of eggs laid by females when compared with the control diet without amygdalin. Furthermore, the intrinsic rate of increase (rm) for insects reared on diets with 3 or 6 mg/g (low and moderate concentrations) of amygdalin versus the control diet without amygdalin showed a slightly improved population growth. However, this increase in the rm value did not persist over ten successive generations of rearing on the same diet. We concluded that the diet with 6 mg of amygdalin per g of diet can enhance the performance and population growth of G. molesta, but the effects of amygdalin are concentration-dependent.

As one means of close-to-nature management, forest gaps have an important impact on the ecological service function of plantations. To improve the current situation of P. massoniana plantations, three different sizes of forest gaps (large gaps, medium gaps and small gaps) were established to observe whether gap setting can improve the soil fertility and plant diversity of forest plantations. The results showed that compared with the control, the soil organic matter content of different soil layers increased significantly in the medium forest gap and large forest gap. The content of soil organic matter in the surface layer of the middle gap had the largest increase (80.64%). Compared with the control, the content of soil-available potassium between different soil layers decreased significantly by 15.93% to 25.80%. The soil hydrolysable nitrogen reached its maximum under the medium gap. Soil moisture showed significant changes among different gap treatments, different soil layers and their interaction, decreasing significantly in large gaps and small gaps but increasing significantly in medium gaps. The soil bulk density decreased significantly compared with the control, and the surface soil reached the minimum in the medium gap. There were different plant species in forest gaps of different sizes, and shrub layer plants were more sensitive to gap size differences than herb layer plants. The plant diversity indices of the shrub layer increased significantly and showed a maximum under the medium gap. The plant diversity of the herb layer showed the opposite trend, and the Shannon-Wiener index, Simpson index and Pielou index were significantly lower than those of the control. RDA showed that different gap treatments had significant effects on the distribution of plants under the forest. Soil available potassium, soil moisture and soil bulk density affected the distribution and diversity of plants under the forest, serving as the limiting factors of plant growth. In forest management, if we strictly consider the improvement of plant diversity and soil physicochemical properties, these results suggest that a medium gap should be established in a plantation for natural restoration.

Rice (Oryza sativa L.) is an important crop in China. Although it is known that its yield is restricted by nitrogen (N) supply, the response of the root system to N supply specifically has not been systematically explored. This study aimed to investigate the effect of N uptake on grain yield to clarify the relationships between root morphophysiological traits and N uptake, and to understand relation between phytohormones and root morphophysiological traits. Two N-efficient absorption cultivars (NEAs) and two N-inefficient absorption cultivars (NIAs) were grown in the field, and three N conditions, deficient N (60 kg ha–1), intermediate N (180 kg ha–1), and sufficient N (240 kg ha–1), were applied during the growing season. The results showed higher dry matter and grain yield in NEAs than in NIAs, which was mainly attributed to increased N uptake in the mid- and late growth stages under all N conditions. And NEAs have different root regulation methods to obtain higher N accumulation and yield under different N supply conditions. Under lower N conditions, compared with NIAs, NEAs shown greater total root length, root oxidation activity, and root active absorbing surface area and smaller root diameter owing to higher indole-3-acetic acid and cytokinin content and lower 1-aminocyclopropane-1-carboxylic acid content in the early growth stages to respond to low N stress faster, laying a morphophysiological basis for its high N-uptake capacity in the mid- and late growth stages. Under higher N conditions, NEAs had higher root oxidation activity and root active absorbing surface area for N uptake and yield formation owing to higher abscisic acid and cytokinin content in the mid- and late growth stages, which improved the seed setting rate, thereby increasing the rice grain yield. These results suggest that NEAs can optimize the morphophysiological characteristics of roots through phytohormone regulation to adapt to different nutrient conditions, thereby promoting N accumulation and yield formation in rice.

Background Soil and understory vegetation are vital components of forest ecosystems. Identifying the interaction of plantation management to vegetation and soil is crucial for developing sustainable plantation ecosystem management strategies. As one of the main measures of close-to-nature management of forest plantation, few studies have paid attention to the effect of crop tree management on the soil properties and understory vegetation. Methods A 36-year-old Pinus massoniana plantation in Huaying city, Sichuan Province was taken as the research object to analyse the changes in undergrowth plant diversity and soil physicochemical properties under three different crop tree densities (100, 150, and 200 N/ha). Results Our results showed that the contents of available phosphorus, organic matter and hydrolysable nitrogen in the topsoil increased significantly after crop tree management, while content of available potassium decreased. The composition of shrub and herb layer was richer, and the dominant species were obviously replaced after crop tree management. The Shannon–Wiener index and Richness index of shrub layer, and the diversity of herb layer increased significantly after crop tree management. Herb layer diversity indexes and Richness index of shrub layer were closely related to soil organic matter, available phosphorus, hydrolysable nitrogen, available potassium, soil moisture and bulk density. As the main limiting factors for plant growth, nitrogen, phosphorus and potassium were closely related to plant diversity and to the distribution of the dominant species. At the initial stage of crop tree management, each treatment significantly improved the soil physicochemical properties and plant diversity of Pinus massoniana plantation, and the comprehensive evaluation was 200 N/ha >100 N/ha >150 N/ha >CK. Compared with other treatments, 200 N/ha had the best effect on improving the undergrowth environment of the Pinus massoniana plantation in the initial stage of crop tree management.

With offloading the tasks that mobile users (MUs) running in their mobile devices (MDs) to the data centers of remote public clouds, mobile cloud computing (MCC) can greatly improve the computing capacity and prolong the battery life of MDs. However, the data centers of remote public cloud are generally far from the MUs, thus long delay will be caused due to the transmission from the base station to the public clouds over the Internet. Mobile edge computing (MEC) is recognized as a promising technique to augment the computation capabilities of MDs and shorten the transmission delay. Nevertheless, compared with the traditional MCC and MEC generally has a limited number of cloud resources. Therefore, making a choice on offloading task to the MCC or MEC is a challenging issue for each MU. In this paper, we investigate service selection in a mobile cloud architecture, in which MUs select cloud services from two cloud service providers (CSPs), i.e., public cloud service provider (PSP) and an edge cloud service provider (ESP). We use M/M/$\infty $ queue and M/M/1 queue to model PSP and ESP, respectively. We analyze the interaction of the two CSPs and MUs by adopting Stackelberg game, in which PSP and ESP set the prices first, and then the MUs decide to select cloud services based on performances and prices. In particular, we study the relationship between PSP and ESP in the simultaneous-play game (SPG) scenario, in which they compete to set prices of their cloud services simultaneously. Our numerical results show that MUs prefer to select service from the edge cloud if the number of tasks they run is small. In another hand, more tasks will be offloaded to the remote public cloud if the number of tasks they run becomes large.

People often have different opinions toward the same topic, posing challenges for traditional sentiment analysis systems that rely on statistical models estimated with population-level data. Personalization is a solution to the problem, but it suffers from data scarcity issue, as the labeled date for a specific user is usually only available in a small quantity. In this paper, we exploit the theory of social homophily to overcome this difficulty by assuming that social neighbors are likely to express similar opinions with respect to the same topic or document. We present a personalized sentiment analysis system that leverages the social relation information to balance between personalization and overfitting. Our approach is based on network lasso that automatically clusters socially proximate users together, so that users in the same group share the same personalized model. We develop a distributed optimization algorithm that makes our system scale to large networks as well. The experiments on Yelp review datasets show that our approach consistently outperforms competitive methods.

Aiming at the Low voltage ride through capability of doubly-fed wind farm when it is merged into a weak grid, this paper researches the theory of rotor excitation control and proposed an additional control model of DFIG grid-connected rotor flux based on structure decentralization theory. In this model, the Low voltage ride through capability of the doubly-fed wind farm is enhanced by designing the d-axis and q-axis adaptive terminal sliding mode controllers for the synchronous rotating coordinate system. Simulation results show that the proposed control model not only can better realize the rapid regulation of reactive power of doubly-fed wind farms, but also improve the ability of the system to resist grid voltage fluctuations, and improve the transient stability of power systems. It has certain theoretical significance and practical application value.

Aiming at the problem of high voltage disconnection when doubly-fed wind farms are merged into weak power grids, this paper researches the theory of rotor excitation control and proposed an additional control model of DFIG grid-connected rotor flux based on structure decentralization theory. In this model, the high voltage ride-through capability for grid-connected wind farms is enhanced by designing the d-axis and q-axis adaptive terminal sliding mode controllers of the synchronous rotating coordinate system. Using the simulation software of MATLAB/Simulink, this paper established a simulation model of wind farm high voltage ride through composed of 2MW doubly fed wind turbines and carried out the off-line simulation of the whole process of high voltage traversing. Real-time simulation experiment of high voltage ride-through was also conducted on a self-developed real-time simulation platform for grid-connected doubly-fed wind farms. Real-time simulation results prove the accuracy of theoretical and offline simulation analysis and the feasibility of control strategy.

Point-of-Interest (POI) recommendation has been an important research topic in data mining and the popularity of location-based social networks (LBSNs) has significantly contributed to POI recommendation. The existing POI recommendation models mostly adopt various explicit social relationships under geographical space. The implicit relationships among users under a certain geographical region are rarely taken into account, though they have major influence on user behaviors. Due to the above limitations, we were motivated to introduce an innovative Deep Potential Geo-Social Relationship mining model for POI Recommendation (DPGSR-PR). The proposed DPGSR-PR performs the personalization of geographical features, towards the determination of user check-in behaviors and choices in specific domains, which is achieved by estimating and considering kernel density. Moreover, user preferences and personalized geo-social influence are incorporated into a geo-social recommendation framework under a holistic view. Specifically, the deep potential geo-social relationships include the explicit-implicit user geo-social relationships between users (EIU-GSR) and the implicit common check-in POI-based geo-social relationships (ICP-GSR). The estimation of Kernel density and the two-hop random walk approach are employed in an effort to mine the EIU-GSR. The ICP-GSR is discovered by specifically determining and considering the Jaccard similarity coefficient and kernel density estimation. Due to the fact that the role of both EIU-GSR and ICP-GSR as regularization terms is quite significant, we used their combined impact to obtain a unique recommendation model that employs matrix factorization. The proposed DPGSR-PR was tested on two datasets, which has proven that DPGSR-PR outperforms other well-established models.

Thinning can significantly promote forest productivity and ecological function. Rhizosphere fungi play an indispensable role in regulating nutrient cycling between plants and the environment, and their community composition can positively respond to anthropogenic disturbance. However, the initial effects of thinning on rhizosphere fungal community assembly have seldom been reported. In this research, we studied the alterations in the rhizosphere fungal communities of 29-year-old Pinus massoniana in East Sichuan 2 years after three different thinning intensity treatments. In addition, the responses of fungal community and functional group composition to alterations in understory vegetation and soil physiochemical properties were analyzed. Three thinning intensities were set, which were 0 (CK), 25% (LIT), and 50% (HIT), respectively. The results suggested that the richness index and Shannon index of understory vegetation increased significantly with increasing thinning intensity. The alpha diversity indices of rhizosphere fungal community and soil physiochemical properties did not show significant differences among the three treatments. The relative abundances of 17 fungal indicator species varied regularly with increasing thinning intensity, and most of them belong to Hypocreales and Eurotiales, indicating that these two orders were potential indicators for different thinning treatments. Rhizosphere fungal community assembly was determined by deterministic process, and it was driven by the diversity of understory vegetation in the initial stage of thinning. The Simpson index and Pielou index of herbs were useful measures of the main environmental factors driving the differentiation of fungal functional group composition. Based on network analysis, thinning resulted in distinct co-occurrence patterns of rhizosphere fungal functional groups. This research elucidates the initial role of thinning in rhizosphere fungal community assembly of P. massoniana and has practical significance for the functional restoration and protection of local forest ecosystem.

Due to the advancements of information technologies and the Internet of Things (IoT), the number of distributed sensors and IoT devices in the social IoT (SIoT) systems is proliferating. This has led to various multimedia applications, face recognition and augmented reality (AR). These applications are computation-intensive and delay-sensitive and have become popular in our daily life. However, IoT devices are well-known for their constrained computational resources, which hinders the execution of these applications. Mobile edge computing (MEC) has appeared and been deemed a prospective paradigm to solve this issue. Migrating the applications of IoT devices to be executed in the edge cloud can not only provide computational resources to process these applications but also lower the transmission latency between the IoT devices and the edge cloud. In this paper, computation resource allocation and multimedia applications offloading in MEC-assisted SIoT systems are investigated. We aim to optimize the resource allocation and application offloading by jointly minimizing the execution latency of multimedia applications and the consumed energy of IoT devices. The studied problem is a formulation of the total computation overhead minimization problem by optimizing the computational resources in the edge servers. Besides, as the technology of dynamic voltage scaling (DVS) can offer more flexibility for the MEC system design, we incorporate it into the application offloading. Since the studied problem is a mixed-integer nonlinear programming (MINP) problem, an efficient method is proposed to address it. By comparing with the baseline schemes, the theoretic analysis and simulation results demonstrate that the proposed multimedia applications offloading method can improve the performances of MEC-assisted SIoT systems for the most part.

Heavy metal exposure is a serious environmental stress in plants. However, plants have evolved several strategies to improve their heavy metal tolerance. Heavy metal-associated proteins (HMPs) participate in heavy metal detoxification. Here, we identified 46 and 55 HMPs in rice and Arabidopsis, respectively, and named them OsHMP 1–46 and AtHMP 1–55 according to their chromosomal locations. The HMPs from both plants were divided into six clades based on the characteristics of their heavy metal-associated domains (HMA). The HMP gene structures and motifs varied greatly among the different classifications. The HMPs had high collinearity and were segmentally duplicated. A cis-element analysis revealed that the HMPs may be regulated by different transcription factors. An expression profile analysis disclosed that only eight OsHMPs were constitutive in rice tissues. Of these, the expression of OsHMP37 was far higher than that of the other seven genes while OsHMP28 was expressed exclusively in the roots. For Arabidopsis, nine AtHMPs presented with very high transcript levels in all organs. Most of the selected OsHMPs were differentially expressed in various tissues under different heavy metal stresses. Only OsHMP09, OsHMP18, and OsHMP22 showed higher expression levels in all tissues under different heavy metal stresses. In contrast, most of the selected AtHMPs had nearly constant expression levels in different tissues under various heavy metal stresses. The AtHMP20, AtHMP23, AtHMP25, AtHMP31, AtHMP35, AtHMP46 expression levels under different heavy metal stresses were higher in the leaves and roots. The foregoing discoveries elucidated HMP evolution in monocotyledonous and dicotyledonous plants and may helpful functionally characterize HMPs in the future.

This laboratory study investigated whether the larval-pupal parasitoid Oomyzus sokolowskii females adjust their brood size and sex ratio in response to body size and stage of Plutella xylostella larval hosts, as well as to their own body size and the order of oviposition. These factors were analyzed using multiple regression with simultaneous entry of them and their two-way interactions. Parasitoids brood size tended to increase with host body size at parasitism when the 4th instar larval host was attacked, but did not change when the 2nd and 3rd instar larvae were attacked. Parasitoids did not vary in brood size according to their body size, but decreased with their bouts of oviposition on a linear trend from 10 offspring adults emerged per host in the first bout of oviposition down to eight in the third. Parasitoid offspring sex ratio did not change with host instar, host body weight, wasp body size, and oviposition bout. Proportions of male offspring per brood were from 11% to 13% from attacking the 2nd to 4th instar larvae and from 13% to 16% across three successive bouts of oviposition, with a large variation for smaller host larvae and wasps. When fewer than 12 offspring were emerged from a host, one male was most frequently produced; when more than 12 offspring were emerged, two or more males were produced. Our study suggests that O. sokolowskii females may optimize their clutch size in response to body size of mature P. xylostella larvae, and their sex allocation in response to clutch size.

The Internet of Things (IoT) is emerging as a new communication paradigm and has attracted a significant amount of attention from both academic and engineering communities. In this paper, we consider an IoT market where three roles exist: Wireless Sensor Networks (WSNs), two service providers (SPs) and end users. The WSNs are responsible for sensing and providing data to the two SPs. Based on the sensed data from WSNs, the two SPs compete to provide services to the end users. We model the relationship between the two SPs and end users as a two-stage Stackelberg game, where the two SPs set the prices for their services firstly, and then the end users decide which SP to choose. Specifically, we consider two price-competition scenarios of the two SPs, which are engaged in two games, one is a noncooperative strategic game (NSG) where the two SPs set the prices for services simultaneously, the other is a Stackelberg game (SG) where SP1 who sets the price first is the leader and SP2 who sets the price after is the follower. Each user decides whether and which SP to purchase services from based on prices and service rates. An equilibrium is achieved in each of the two scenarios. Numerical results are conducted to verify our theoretical analysis.