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Driving vigilance estimation is an important task for traffic safety. Nowadays, electroencephalography (EEG) and electrooculography (EOG) have made some achievements in vigilance estimation, but there are still some challenges: 1) The traditional approachs with direct multimodal fusion may face the problems of information redundancy and data dimensionality mismatch; 2) Capture key discriminative features during multimodal fusion without losing specific patterns to each modality. In order to solve the above problems, this paper proposes a approach with fusion of EEG and EOG features in split bands, which not only preserves the information about brain activities in different bands of EEG, but also effectively integrates the relevant information of EOG. On this basis, we further propose a hierarchical multi-scale topological enhanced network (HMS-TENet). This network first introduces a pyramid pooling structure (PPS) to capture contextual relationships from different discriminative perspectives. And then we design a selective convolutional structure (SCS) for adaptive sense-field selection, which enables us to mine the desired discriminative information in small-size features. In addition, we design a topology self-aware attention to enhance the learning of representations of complex topological relationships among EEG channels. Finally, the output of the model can be selected for both regression and classification tasks, providing higher flexibility and adaptability. We demonstrate the robustness, generalizability, and utility of the proposed method based on intra-subject and cross-subject experiments on the SEED-VIG public dataset. Codes are available at https://github.com/tangmeng28/HMS-TENet.

Abstract Background Leaf nitrogen (N) and phosphorus (P) resorption is a fundamental adaptation strategy for plant nutrient conservation. However, the relative roles that environmental factors and plant functional traits play in regulating N and P resorption remain largely unclear, and little is known about the underlying mechanism of plant functional traits affecting nutrient resorption. Here, we measured leaf N and P resorption and 13 plant functional traits of leaf, petiole, and twig for 101 representative broad-leaved tree species in our target subtropical transitional forests. We integrated these multiple functional traits into the plant economics spectrum (PES). We further explored whether and how elevation-related environmental factors and these functional traits collectively control leaf N and P resorption. Results We found that deciduous and evergreen trees exhibited highly diversified PES strategies, tending to be acquisitive and conservative, respectively. The effects of PES, rather than of environmental factors, dominated leaf N and P resorption patterns along the elevational gradient. Specifically, the photosynthesis and nutrient recourse utilization axis positively affected N and P resorption for both deciduous and evergreen trees, whereas the structural and functional investment axis positively affected leaf N and P resorption for evergreen species only. Specific leaf area and green leaf nutrient concentrations were the most influential traits driving leaf N and P resorption. Conclusions Our study simultaneously elucidated the relative contributions of environmental factors and plant functional traits to leaf N and P resorption by including more representative tree species than previous studies, expanding our understanding beyond the relatively well-studied tropical and temperate forests. We highlight that prioritizing the fundamental role of traits related to leaf resource capture and defense contributes to the monitoring and modeling of leaf nutrient resorption. Therefore, we need to integrate PES effects on leaf nutrient resorption into the current nutrient cycling model framework to better advance our general understanding of the consequences of shifting tree species composition for nutrient cycles across diverse forests.

Abstract Accurate estimations of carbon (C), nitrogen (N), and phosphorus (P) densities in shrublands are pivotal for assessing terrestrial ecosystem carbon sequestration. Combining in‐situ investigations and machine learning facilitates large‐scale patterns mapping, however, which often overlooks underlying ecological regulations. Here we utilize data from 1,122 survey plots across China's shrublands and develop a novel knowledge‐based deep learning framework that integrates a structural equation model (SEM) to elucidate mechanisms and construct an artificial neural network (ANN) based on these causal relationships. Results show that biomass allocation to different organs follows allometric regulations and that N and P concentrations maintain a degree of stoichiometric homeostasis following biological stoichiometry theory. This insight guides the construction of our ANN, which outperforms both SEM and other prevalent machine learning methods. By leveraging ecological theories to inform model construction, our framework not only enhances prediction accuracy and explainability but also provides a methodological blueprint for ecological research.

The ecological relationships between tree growth and climate factors are important for the adaptation, growth prediction, and forest management of tree species against a background of global warming. Yet how these relationships for drought-sensitive conifer trees are changed and affected by elevation remains unclear. To investigate the effect of elevation on spruce tree growth–climate interactions, we collected a total of 1886 tree-ring cores (two cores per tree) from four spruce species, including Picea crassifolia Kom., Picea meyeri Rehd. et Wils., Picea schrenkiana Fisch. et Mey., and Picea wilsonii Mast., in 10 pure forests at a pair of high- and low-elevation alpine sites with the same slope across two aridity zones in China. We then constructed 20 stand tree-ring chronologies for the low- and high-elevation sites. Overall, the growth of spruce trees was more sensitive to drought variability at sites in the semi-arid zone whereas it was weakly limited by drought in the semi-humid zone. Further, spruce trees growing at high-elevation sites were sensitive to temperature unlike the stronger positive drought responses of those at low-elevation sites. In the latter half of the 20th century, the positive drought–growth relationships of spruce were enhanced at both high and low elevation across both aridity zones due to warming and increased drought intensity. Our dendrochronology-based findings suggest that spruce trees’ radial growth in stands at high elevation may have faced drought stress during three recent decades. Nevertheless, the low-elevation trees incurred stronger drought stress compared to the first half of the 20th century.

To prevent convulsions and falls of patients in the absence of medical staff, it is crucial to monitor their physical condition in hospital wards. However, several unresolved challenges in human joint recognition remain, such as object occlusion, human self-occlusion and complex backgrounds, resulting in difficulties in its practical application. In this paper, a multi-LiDAR system is proposed to obtain a multi-view human body point cloud. An improved V2V-Posenet model was introduced to detect the actual position of the human joint. In this system, each point cloud was spliced into a full point cloud and voxelized into the model. We also used a random voxel zero setting for data enhancement, constraining the relative length between human joints into a loss function and three-dimensional Gaussian filtering in a heat map for model learning. The improved model exhibited excellent performance in detecting human joints in hospital wards. The experimental results showed that the improved model achieved 91.6 % mean average precision, compared to 80.1 % for the original model and 77.4 % for the comparison algorithm A2J-Posenet. The speed of the improved model meets the requirements for real-time target detection.

Abstract Direct electrosynthesis of hydrogen peroxide (H2O2) via the two-electron oxygen reduction reaction presents a burgeoning alternative to the conventional energy-intensive anthraquinone process for on-site applications. Nevertheless, its adoption is currently hindered by inferior H2O2 selectivity and diminished H2O2 yield induced by consecutive H2O2 reduction or Fenton reactions. Herein, guided by theoretical calculations, we endeavor to overcome this challenge by activating a main-group Pb single-atom catalyst via a local micro-environment engineering strategy employing a sulfur and oxygen super-coordinated structure. The main-group catalyst, synthesized using a carbon dot-assisted pyrolysis technique, displays an industrial current density reaching 400 mA cm−2 and elevated accumulated H2O2 concentrations (1358 mM) with remarkable Faradaic efficiencies. Both experimental results and theoretical simulations elucidate that S and O super-coordination directs a fraction of electrons from the main-group Pb sites to the coordinated oxygen atoms, consequently optimizing the *OOH binding energy and augmenting the 2e− oxygen reduction activity. This work unveils novel avenues for mitigating the production-depletion challenge in H2O2 electrosynthesis through the rational design of main-group catalysts.

Cross-subject electroencephalogram (EEG) based seizure subtype classification is very important in precise epilepsy diagnostics. Deep learning is a promising solution, due to its ability to automatically extract latent patterns. However, it usually requires a large amount of training data, which may not always be available in clinical practice. This paper proposes Multi-Branch Mutual-Distillation (MBMD) Transformer for cross-subject EEG-based seizure subtype classification, which can be effectively trained from small labeled data. MBMD Transformer replaces all even-numbered encoder blocks of the vanilla Vision Transformer by our designed multi-branch encoder blocks. A mutual-distillation strategy is proposed to transfer knowledge between the raw EEG data and its wavelets of different frequency bands. Experiments on two public EEG datasets demonstrated that our proposed MBMD Transformer outperformed several traditional machine learning and state-of-the-art deep learning approaches. To our knowledge, this is the first work on knowledge distillation for EEG-based seizure subtype classification.

Desertification in the context of global change and intensified anthropogenic activities poses a huge challenge to the sustainable development of the Earth’s systems, including the Qinghai Lake Basin, which is located in the Tibetan Plateau. However, we know little about desertification in the Qinghai Lake Basin, which is an urgent and important issue. To that end, this study used the enhanced vegetation index (EVI) and the albedo data from MODIS satellites to explore this issue. Results based on vegetation cover (FVC) calculated from EVI indicated that desertification in the Qinghai Lake Basin had reversed over the last 20 years, and the heavily desertified areas were concentrated along the northwestern to northern basin boundaries and on the sandy eastern shore of Qinghai Lake. More interestingly, we found that the relationship between albedo and EVI showed a “V” shape instead of the traditional monotonic trapezoid, which may be related to multiple factors such as soil moisture, soil type, and spatial scale of sampling. This study unfolds the spatial and temporal distribution of desertification in the Qinghai Lake Basin quantitatively and emphasizes the threshold of the desertification process revealed in the EVI-albedo feature space, which sheds light on the monitoring of desertification in alpine areas.

In this paper, we study the micro-motion characteristics of multi-feature targets based on a double pulse coherent system under atmospheric conditions. The theoretical model for echo signal and micro-motion characteristics of a 3D target in double pulse coherent system is deduced. We discuss the influence of micro-motion characteristics, the relative size of light spot and target, target shapes, and incident direction on frequency shift. LRCS (Lidar cross-section), echo waveform, intensity and radiation energy distribution under different conditions are obtained additionally. Simulation results conclude that these parameters are of advantage to the inversion of target shape properties and motion types.

Electroencephalogram (EEG) based seizure subtype classification is very important in clinical diagnostics. Source-free domain adaptation (SFDA) uses a pre-trained source model, instead of the source data, for privacy-preserving transfer learning. SFDA is useful in seizure subtype classification, which can protect the privacy of the source patients, while reducing the amount of labeled calibration data for a new patient. This paper introduces semi-supervised transfer boosting (SS-TrBoosting), a boosting-based SFDA approach for seizure subtype classification. We further extend it to unsupervised transfer boosting (U-TrBoosting) for unsupervised SFDA, i.e., the new patient does not need any labeled EEG data. Experiments on three public seizure datasets demonstrated that SS-TrBoosting and U-TrBoosting outperformed multiple classical and state-of-the-art machine learning approaches in cross-dataset/cross-patient seizure subtype classification.

Scanless three-dimensional (3D) imaging technology has received extensive attention in recent years due to its rapid detection and system reliability. Compressed sensing imaging technology provides a new solution for the realization of scan-free 3D imaging. In this paper, a 3D imaging method based on dual-frequency laser phase ranging based on compressed sensing technology is introduced and realized. Using the combination of dual-frequency laser phase ranging and compressed sensing theory, two-dimensional range reconstruction from the time-domain light intensity signal collected by a single-point detector is performed. Aiming at the spatial sparsity of the target scene, this technology uses the compressed sensing algorithm to solve the phase information of the two-dimensional spatial distribution contained in the time domain signal so as to invert the 3D image information of the target scene and realize the effect of scanning-free 3D imaging. First, the feasibility of the system is verified by simulations, and the imaging effects of different reconstruction algorithms on different terrains are compared. Second, a non-scanning 3D imaging experimental platform is designed and built. Finally, the 3D images of multiple objects with 32 × 32 resolution are successfully reconstructed through experiments with a compression ratio of 0.25. The ranging accuracy of this system is 0.05 m. This work is promising for applications in multiple objects’ fast detections.

Summary: Current classifications of oxygen evolution catalysts are based on energy levels of the clean catalysts. It is generally asserted that a LOM-catalyst can only follow LOM chemistry in each electron transfer step and that there can be no mixing between AEM and LOM steps without an external trigger. We use ab initio theory to track the charge flow of the water-on-catalyst system and show that the position of water orbitals is pivotal in determining whether an electron transfer step is water dominated oxidation (WDO), lattice-oxygen dominated oxidation (LoDO), or metal dominated oxidation (MDO). Microscopic photo-catalytic pathways of TiO2 (110), a material whose lattice oxygen bands lie above the metal bands, show that viable OER pathways follow either all AEM steps or mixed AEM-LOM steps. The results provide a correct description of redox chemistries at the atomic level and advance our understanding of how water-splitting catalysts produce desorbed oxygen.

This paper utilizes the idea of theoretical analysis to introduce a method for echo characteristics in remote detection with the pulse LiDAR of aerial targets under atmospheric conditions. A Missiles and an aircraft are selected as simulation targets. The relation among mutual mapping of target surface elements can be directly gained by setting light source and target parameters. We discuss influences on atmospheric transport conditions, target shapes and detection conditions on echo characteristics. Atmospheric transport model is introduced as weather conditions, including sunny and cloudy days, with or without turbulence. Simulation results conclude that the outline of scanned waveform can invert the target shape. These provide a theoretical basis for improving the target detection and tracking performance.

Electroencephalogram (EEG) based seizure subtype classification is very important in clinical diagnostics. However, manual seizure subtype classification is expensive and time-consuming, whereas automatic classification usually needs a large number of labeled samples for model training. This paper proposes an EEGNet-based slim deep neural network, which relieves the labeled data requirement in EEG-based seizure subtype classification. A temporal information enhancement module with sinusoidal encoding is used to augment the first convolution layer of EEGNet. A training strategy for automatic hyper-parameter selection is also proposed. Experiments on the public TUSZ dataset and our own CHSZ dataset with infants and children demonstrated that our proposed TIE-EEGNet outperformed several traditional and deep learning models in cross-subject seizure subtype classification. Additionally, it also achieved the best performance in a challenging transfer learning scenario. Both our code and the CHSZ dataset are publicized.

Abstract Background Endophytic actinomycetes, as emerging sources of bioactive metabolites, have been paid great attention over the years. Recent reports demonstrated that endophytic streptomycetes could yield compounds with potent anticancer properties that may be developed as chemotherapeutic drugs. Results Here, a total of 15 actinomycete-like isolates were obtained from the root tissues of Lilium davidii var. unicolor (Hoog) Cotton based on their morphological appearance, mycelia coloration and diffusible pigments. The preliminary screening of antagonistic capabilities of the 15 isolates showed that isolate LRE541 displayed antimicrobial activities against all of the seven tested pathogenic microorganisms. Further in vitro cytotoxicity test of the LRE541 extract revealed that this isolate possesses potent anticancer activities with IC50 values of 0.021, 0.2904, 1.484, 4.861, 6.986, 8.106, 10.87, 12.98, and 16.94 μg/mL against cancer cell lines RKO, 7901, HepG2, CAL-27, MCF-7, K562, Hela, SW1990, and A549, respectively. LRE541 was characterized and identified as belonging to the genus Streptomyces based on the 16S rRNA gene sequence analysis. It produced extensively branched red substrate and vivid pink aerial hyphae that changed into amaranth, with elliptic spores sessile to the aerial mycelia. To further explore the mechanism underlying the decrease of cancer cell viability following the LRE541 extract treatment, cell apoptosis and cell cycle arrest assays were conducted in two cancer cell lines, RKO and 7901. The result demonstrated that LRE541 extract inhibited cell proliferation of RKO and 7901 by causing cell cycle arrest both at the S phase and inducing apoptosis in a dose-dependent manner. The chemical profile of LRE541 extract performed by the UHPLC-MS/MS analysis revealed the presence of thirty-nine antitumor compounds in the extract. Further chemical investigation of the LRE541 extract led to the discovery of one prenylated indole diketopiperazine (DKP) alkaloid, elucidated as neoechinulin A, a known antitumor agent firstly detected in Streptomyces; two anthraquinones 4-deoxy-ε-pyrromycinone (1) and epsilon-pyrromycinone (2) both displaying anticancer activities against RKO, SW1990, A549, and HepG2 with IC50 values of 14.96 ± 2.6 − 20.42 ± 4.24 μg/mL for (1); 12.9 ± 2.13, 19.3 ± 4.32, 16.8 ± 0.75, and 18.6 ± 3.03 μg/mL for (2), respectively. Conclusion Our work evaluated the anticarcinogenic potential of the endophyte, Streptomyces sp. LRE541 and obtained one prenylated indole diketopiperazine alkaloid and two anthraquinones. Neoechinulin A, as a known antitumor agent, was identified for the first time in Streptomyces. Though previously found in Streptomyces, epsilon-pyrromycinone and 4-deoxy-ε-pyrromycinone were firstly shown to possess anticancer activities. Graphical Abstract

With the development of nanomedicine, more and more nanoparticles are used in the diagnosis and treatment of leukemia. This study aimed to identify author, country, institutional, and journal collaborations and their impacts, assess the knowledge base, identify existing trends, and uncover emerging topics related to leukemia research. 1825 Articles and reviews were obtained from the WoSCC and analyzed by Citespace and Vosviewer. INTERNATIONAL JOURNAL OF NANOMEDICINE is the journal with the highest output. The contribution of FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY is also noteworthy. The three main aspects of research in Nanoparticles-leukemia-related fields included nanoparticles for the diagnosis and treatment of leukemia, related to the type and treatment of leukemia, the specific molecular mechanism, and existing problems of the application of nanoparticles in leukemia. In the future, synthesize nano-drugs that have targeted therapy and chemotherapy resistance according to the mechanism, which may be the dawn of the solution to leukemia. This study offers a comprehensive overview of the Nanoparticles-leukemia-related field using bibliometrics and visual methods for the first time, providing a valuable reference for researchers interested in Nanoparticles-leukemia.

Plantation’s nutrient cycling can regulate and affect the material cycling of ecosystems, which is the key to maintain the sustainable development of the plantation ecosystem. However, the current understanding of the nutrient cycling characteristics of the “leave-root-litter-soil” continuum of dryland plantation ecosystems is limited. Therefore, in the Longzhong Loess Plateau of China, we selected nine typical dryland plantations to carry related research, including two evergreen (Platycladus orientalis (13-years and 50-years) and Pinus tabuliformis) and four deciduous (Caragana korshinskii (13-years, 35-years and 55-years), Armeniaca sibirica, Populus hopeiensis and Tamarix chinensis) tree species, and measured C, N, P and K contents of green leaves, fine roots, leaf litter and surface soil (0–20 cm). Results showed tree species and afforestation years strongly changed C, N, P and K contents and ratios of green leaves, fine roots, leaf litter and soil components, and also significantly affected leaf N, P and K reabsorption efficiencies. The average N, P and K contents of four components and soil available nitrogen (AN), available phosphorus (AP) and available potassium (AK) contents in deciduous plantations were higher than those in evergreen plantations, resulting in the lower C:N:P:K stoichiometry of deciduous plantations than evergreen plantations. Especially in 55-years C. korshinskii plantation, its soil C, N, AN, AP and AK contents were higher than those in A. sibirica, P. hopeiensis, P. orientalis and P. tabuliformis plantations. Moreover, soil C, N, P, AN, AP and AK contents in C. korshinskii plantations increased significantly with the increase of afforestation years. Thus, C. korshinskii was more suitable for ecological restoration in drylands. Due to the P limitation in plantations, P reabsorption efficiency was higher than N reabsorption efficiency, and significantly negatively correlated with P contents of four components. And green leaves had the homeostasis to soil AP, which may be the nutrient utilization strategies for plantations to alleviate P limitation. Correlation analysis revealed that the C cycling appeared in green leave-fine root and green leave-leaf litter, the N cycling appeared in green leave-leaf litter-soil-fine root, and the P cycling and K cycling appeared in green leave-leaf litter- soil and leaf litter-fine root. These results will provide guidance for ecological restoration and plantation management in drylands.

The non-natural mineralization of CaCO3 with special structures or morphologies is generated during the migration of crude oil and is the main form of scale in alkaline/surfactant/polymer (ASP) flooding in oilfields, adversely affecting oil recovery and causing environmental pollution. To date, the mineralization of aragonite superstructures and the role of heavy alkyl-benzene sulfonate (HABS) in mineralization are still unclear. In this work, aragonite-based superstructures of CaCO3 crystals were obtained in an O/W emulsion with HABS to help deepen the understanding of the diversified growth of CaCO3 scaling in oilfields. As a result, rosette-like, bouquet-like, and dumbbell-shaped CaCO3 crystals with vaterite–aragonite, aragonite, and calcite–aragonite phases were formed with 200 mg/L HABS concentration at 45 °C for 60 min and spherical vaterite phase stabilized at a high HABS concentration (800 mg/L and 1000 mg/L). Rhombohedral calcite content experienced a fluctuation of about 40% as the HABS concentration varied. Needle-like and bundle-like aragonite precipitates were generated with increasing temperatures from 65 °C to 85 °C. Thus, HABS affects the nucleation and growth of the precipitated CaCO3 solid, leading to modifications in the structure and morphology of the crystals. The synergistic effect between HABS and temperature can regulate ion pairs with the calcium ions and block sites that are essential to the incorporation of new solutes into the crystal lattice, which leads to the heterogeneous nucleation of vaterite and aragonite on calcite, forming aragonite-based superstructures in kerosene emulsion. This work may enrich the understanding of CaCO3 mineralization in oilfields, and also provide a novel strategy for manufacturing organic–inorganic composites.

The spatial pattern of vegetation can reflect the impacts of the environment on plants and the response of plants to the environment, which can promote a deep understanding of the potential driving mechanisms of vegetation evolution and community maintenance. A sand-binding vegetation system without irrigation has been implemented in the oasis–desert transitional zone since the 1970 s, where the annual precipitation has been approximately 120 mm. While the mobile dunes have been effectively stabilized, a patchy pattern of sand-binding vegetation has been observed. However, we do not understand why the pattern of sand-binding vegetation changed from the initial uniform distribution to the current patchy pattern. In this study, low-altitude UAV remote sensing technology and imaging-based quantification techniques were used to explore the effects of biotic and abiotic factors on the spatial patterns of sand-binding vegetation over 50 years. The spatial pattern of Haloxylon ammodendron changed gradually from a uniform distribution to an aggregated distribution, and the degree of patch fragmentation of H. ammodendron at the landscape scale gradually increased with the age of the sand-binding vegetation. The artificial sand-binding vegetation composed of H. ammodendron showed discontinuous change in which the system state reached a transition point after 30 years and changed to another state after 40 years. There were no significant correlations between the landscape indices and soil water content in the shallow layers (0–10 cm, 10–50 cm), while the soil water content in the 50–100 cm layers was significantly negatively correlated with the class area, percentage of landscape, largest patch index, percentage of like adjacencies and aggregation index and was positively correlated with the normalized landscape shape index. The soil water content in the 100–200 cm layers was positively correlated with the number of patches and patch density. Competition intensity at the individual level had a more significant effect on the area-type indices, and competition intensity at the population level had a more significant effect on the clustering-type indices. Finally, we found that the soil water content in deep layers and competition are the main drivers of the H. ammodendron spatial pattern change from a uniform pattern to a patchy pattern. These findings enrich theory on the self-organization of vegetation in arid and semiarid environments and have important theoretical and practical significance for the establishment and management of artificial vegetation in arid areas.

Abstract Background Large-scale afforestation can significantly change the ground cover and soil physicochemical properties, especially the soil fertility maintenance and water conservation functions of artificial forests, which are very important in semi-arid mountain ecosystems. However, how different tree species affect soil nutrients and soil physicochemical properties after afforestation, and which is the best plantation species for improving soil fertility and water conservation functions remain largely unknown. Methods This study investigated the soil nutrient contents of three different plantations (Larix principis-rupprechtii, Picea crassifolia, Pinus tabuliformis), soils and plant-soil feedbacks, as well as the interactions between soil physicochemical properties. Results The results revealed that the leaves and litter layers strongly influenced soil nutrient availability through biogeochemical processes: P. tabuliformis had higher organic carbon, ratio of organic carbon to total nitrogen (C:N) and organic carbon to total phosphorus (C:P) in the leaves and litter layers than L. principis-rupprechtii or P. crassifolia, suggesting that higher C:N and C:P hindered litter decomposition. As a result, the L. principis-rupprechtii and P. crassifolia plantation forests significantly improved soil nutrients and clay components, compared with the P. tabuliformis plantation forest. Furthermore, the L. principis-rupprechtii and P. crassifolia plantation forests significantly improved the soil capacity, soil total porosity, and capillary porosity, decreased soil bulk density, and enhanced water storage capacity, compared with the P. tabuliformis plantation forest. The results of this study showed that, the strong link between plants and soil was tightly coupled to C:N and C:P, and there was a close correlation between soil particle size distribution and soil physicochemical properties. Conclusions Therefore, our results recommend planting the L. principis-rupprechtii and P. crassifolia as the preferred tree species to enhance the soil fertility and water conservation functions, especially in semi-arid regions mountain forest ecosystems.

A laser beam is an effective power and data carrier that offers inherent advantages in terms of the simultaneous transfer of wireless information and power, which is widely used in both the Internet of Things and the Internet of Energy. This paper proposes an adaptive high-power and high-efficiency laser-based simultaneous wireless information and power transfer system. This is achieved through the use of adjusted and modulated laser diode systems at the transmitter and multiplexed photovoltaic cells, a coupler, a filter, and a maximum power point tracking (MPPT) converter at the receiver. The interaction between the converter and the communication component is investigated theoretically and experimentally using a current-fed boost MPPT converter with the MPPT algorithm of perturbation and observation. The results indicate a maximum DC output power of 7.3 W at the receiver and a maximum MPPT converter efficiency of 84%. Additionally, at a data rate of 495 kbit/s, with a DC output power of 5.11 W, the bit error ratio is 2.62 × 10-4 for the binary amplitude shift keying modulation format, the MPPT converter efficiency is 88%, and the corresponding loss of communication is about 1% of the total transmitted power.

Wireless laser power transmission is a promising technique in the far-field wireless power supply with the advantages of high-power density, and small transmitter and receiver sizes. This article proposes a high-efficiency pulse width modulation-based wireless laser power transmission step-down system based on an 808 nm laser diode and gallium arsenide photovoltaic cells. The output voltage of the proposed system is controlled with the use of pulse width modulation of the laser diode in the transmitter without switch tubes and rectifier diodes in the receiver. The model of the proposed system is built, and characteristics of the system is analyzed based on the state-space averaging method. Additionally, the steady and dynamic operations, as well as the efficiency analyses, are investigated and evaluated experimentally. With the use of the propounded system, when the load is 3 ohms and the output voltage is 1.5 V, a converter efficiency of 96.6% is obtained that is ~10% and ~5% higher than those of continuous wireless power transmission constant voltage systems with asynchronous and synchronous buck converters, respectively.

Optical lattices (OLs) with diverse transverse patterns and optical vortex lattices (OVLs) with special phase singularities have played important roles in the fields of atomic cooling, particle manipulation, quantum entanglement, and optical communication. As a matter of consensus until now, the OL patterns are generated by coherently superimposing multiple transverse modes with a fixed phase difference through the transverse mode locking (TML) effect. There are phase singularities in the dark area of this kind of OL pattern, so it is also called OVL pattern. However, in our research, it is found that some high-order complex symmetric OL patterns can hardly be analyzed by TML model. Instead, the analysis method of incoherent superposition of mode intensity could be applied. The OL pattern obtained by this method can be regarded as in non-TML state. Therefore, in this article, we mainly study the distinct characteristics and properties of OL patterns in TML and non-TML states. Through intensity comparison, interferometry, and beat frequency spectrum, we can effectively distinguish OL pattern in TML and non-TML states, which is of significance to explore the formation of laser transverse pattern possessing OL.

In order to maintain a ski resort efficiently, regular inspections of the cableways are essential. However, there are some difficulties in discovering and observing the cable car cableways in the ski resort. This paper proposes a high-precision segmentation and extraction method based on the 3D laser point cloud data collected by airborne lidar to address these problems. In this method, first, an elevation filtering algorithm is used to remove ground points and low-height vegetation, followed by preliminary segmentation of the cableway using the spatial distribution characteristics of the point cloud. The ropeway segmentation and extraction are then completed using the least squares-principal component combination analysis method for parameter fitting. Additionally, we selected three samples of data from the National Alpine Ski Center to be used as test objects. The real value is determined by the number of point clouds manually deducted by CloudCompare. The extraction accuracy is defined as the ratio of the number of point clouds extracted by the algorithm to the number of point clouds manually extracted. While the environmental complexities of the samples differ, the algorithm proposed in this paper is capable of segmenting and extracting cableways with great accuracy, achieving a comprehensive and effective extraction accuracy rate of 90.59%, which is sufficient to meet the project’s requirements.

As an important means of curbing soil degradation, afforestation has a profound impact on regional soil properties and quality. However, it is still unclear regarding how to conduct a systematic assessment of soil properties and soil quality and the impact of vegetation characteristics and plant functional traits in leguminous plantations with different afforestation years in drylands. Therefore, we investigated the vegetation characteristics and determined the functional traits of leaves and roots and the soil physicochemical properties of Caragana korshinskii plantations with 13, 35, and 55 years. The results showed that tree height; crown diameter (CD); root dry matter content; root water content; soil clay, silt, and sand contents; bulk density (BD); soil water content; soil organic carbon (SOC); total nitrogen (TN); available nitrogen; total phosphorus (TP); available phosphorus (AP); and soil quality index (SQI) changed significantly with an increase in afforestation years. Although the specific leaf area did not show a significant variation, it had a significant negative effect on soil properties and SQI, except for soil sand and BD. Soil sand and BD decreased with the afforestation succession, but the succession pattern of soil clay, silt, SOC, TN, TP, and AP was 13 years < 35 years < 55 years, and SQI increased from 0.20 (13 years) to 0.77 (55 years). This indicated that long-term legume afforestation led to the transformation of soil texture from silty loam to silt and significantly improved the soil properties and quality in the study area.

In the present day, 3D point clouds are considered to be an important form of representing the 3D world. In computer vision, mobile robotics, and computer graphics, point cloud registration is a basic task, and it is widely used in 3D reconstruction, reverse engineering, among other applications. However, the mainstream method of point cloud registration is subject to the problems of a long registration time as well as a poor modeling effect, and these two factors cannot be balanced. To address this issue, we propose an adaptive registration mechanism based on a multi-dimensional analysis of practical application scenarios. Through the use of laser point clouds and RGB images, we are able to obtain geometric and photometric information, thus improving the data dimension. By adding target scene classification information to the RANSAC algorithm, combined with geometric matching and photometric matching, we are able to complete the adaptive estimation of the transformation matrix. We demonstrate via extensive experiments that our method achieves a state-of-the-art performance in terms of point cloud registration accuracy and time compared with other mainstream algorithms, striking a balance between expected performance and time cost.

To address the long-term statistical problem of ski-track area in the construction and operation of ski resorts, we propose a new ski-track point cloud boundary extraction method that improves the accuracy of boundary extraction and minimizes the offset of the area error. In this method, all point clouds are first projected onto the fitting plane using the random sample consensus (RANSAC) method. An improved point cloud boundary extraction algorithm is used to triangulate and extract the high-precision ski-track boundary. A discrete Green formula is then used to calculate and count the ski track’s exact area. It is demonstrated through five sets of test experiments that the error offset of the method proposed in this paper is smaller than that of other classical methods, which confirms its benefits and feasibility.

Stony soils are very widely distributed and contain abundant rock fragments (>2 mm), which impose major effects on soil properties and plant growth. However, the role of rock fragments is still often neglected, which can lead to an inadequate understanding of the interaction between plants and soil. Undisturbed soil columns were collected from three alpine grasslands on the Qilian Mountain, and the X-ray computed tomography method was applied to investigate the characteristics of rock fragments. The results showed there was significant difference in number density, volumetric content and surface area density of rock fragment among the three grasslands, and followed the order of alpine meadow > alpine steppe > alpine desert steppe. In addition, the soil organic carbon, total nitrogen, total phosphorus, available phosphorus, N-NH4+, and N-NO3− contents in fine earth all increased with increasing number density, volumetric content and surface area density but to different degrees. Furthermore, positive correlations were observed between the rock shape factor and belowground biomass (R2 = 0.531, p < 0.05), between the rock volumetric content and aboveground biomass (R2 = 0.527, p < 0.05), and between number density and Simpson’s index (R2 = 0.875, p < 0.05). Our findings suggest that within a certain range, the increase in rock fragment content is conducive to soil nutrient accumulation and soil water storage and circulation and changes plant features, which contributes to the growth of plants. In addition, rock fragments should be given more consideration when investigating the relationships between soil and vegetation and their response to climate change in future studies.

In the past few decades, industrialization has caused a large number of pollutants to be released into the atmosphere. Forest ecosystems play an important function in regulating the biogeochemistry and the circulation of metal ions pollutants. Forest ecosystems affect the absorption of pollutants and dissolution of nutrients from the atmosphere and vegetation canopy, thereby influencing the content and composition of forest floor leachate and soil solution. This study examined changes in acid anions (NO3−, SO42−, Cl−) and metal cations (K+, Ca2+, Na2+, Mg2+, Fe3+, Pb2+, Cu2+, Cd2+) in rainfall, throughfall, stemflow, and forest floor leachate for five different forests (Larix principis-rupprechtii, Picea wilsonii, Picea crassifolia, Betula platyphylla and Rhododendron communities). The results showed that the enrichment capacity of acid anions and metal cations in the vegetation canopy of the coniferous forests (L. principis-rupprechtii, P. wilsonii, P. crassifolia) was stronger than that of the broad-leaved forests (B. platyphylla and Rhododendron communities). The content of acid anions and metal cations in stemflow of coniferous forests were 3.7–5.6 times and 0–9.3 times higher than those of broad-leaved forests, respectively. Corresponding values in throughfall were 1–1.4 times and 0.3–2.4 times, respectively. The contents of NO3−, Cl−, K+, Mg2+, Fe3+, Pb2+, Cu2+, and Cd2+ in leachate filtered from the soil layers that are deepening gradually showed consistent decreasing trend for all the forest stands. In addition, NO3−, Cl−, K+, Mg2+, Fe3+, and Pb2+ were also concentrated in the topsoil, except for Cu2+ and Cd2+. Nevertheless, SO42− and Na+ were concentrated in the subsoil, whereas Ca2+ was concentrated in the upper soil layers. Soil organic carbon (SOC) and total nitrogen (TN) contents in coniferous forest stands were 20–37% and 34–63% higher than those in broad-leaved forest stands, respectively. This results also shown that the contents of OC and TN has a strong correlation with the content of partial metal cations in soil and litter, indicating that coniferous forest stands had stronger ion scavenging and adsorption capacity in soil layer and litter layer than broad-leaved forest stands. Therefore, L. principis-rupprechtii, P. wilsonii, P. crassifolia had higher air pollutant adsorption and soil pollution remediation capacities than the other two forests. Thus, we recommend planting coniferous tree species (L. principis-rupprechtii, P. wilsonii and P. crassifolia) for eco-rehabilitation and water purification to improve the ecological service function of forest ecosystems.

Abstract Background and aims Soil respiration is the second‐largest terrestrial carbon (C) flux, and soil temperature and soil moisture are the main drivers of temporal variation in soil respiration and its components. Here, we quantified the contribution of soil temperature, soil moisture, and their intersection on the variation in soil respiration and its components of the evergreen broad‐leaved forests (EBF), mixed evergreen and deciduous broad‐leaved forests (MF), deciduous broad‐leaved forests (DBF), and subalpine coniferous forests (CF) along an elevation gradient. Methods We measured soil respiration of four types of forests along the elevation gradient in Shennongjia, Hubei China based on the trenching experiments. We parameterized the relationships between soil respiration and soil temperature, soil moisture, and quantified the intersection of temperature and moisture on soil respiration and its components. Results Total soil respiration (RS), heterotrophic respiration (RH), and autotrophic respiration (RA) were significantly correlated with soil temperature in all four forests. The Q10 value of soil respiration significantly differed among the four types of forest, and the Q10 was 3.06 for EBF, 3.75 for MF, 4.05 for DBF, and 4.49 for CF, respectively. The soil temperature explained 62%–81% of the variation in respiration, while soil temperature and soil moisture together explained 91%–97% of soil respiration variation for the four types of forests. The variation from the intersection of soil temperature and moisture were 12.1%–25.0% in RS, 1.0%–7.0% in RH, and 17.1%–19.6% in RA, respectively. Conclusions Our results show that the temperature sensitivity (Q10) of soil respiration increased with elevation. The intersection between soil temperature and soil moisture had strong effects on soil respiration, especially in RH. We demonstrated that the intersection effects between soil temperature and soil moisture on soil respiration were essential to understand the response of soil respiration and its components to climate change.

Single-atom catalysts attract lots of attention, but direct transformation of bulk metal oxide into single atoms remains challenging. Here the authors report a gas-transport route to transform monolithic copper (I) oxide into copper single-atoms catalyst with a high activity for oxygen reduction.

Ivermectin, a kind of valuable derivatives of Avermectin, is distinct from Avermectin due to the saturated bond at C22C23 position. Combinatorial biosynthesis of Ivermectins based on Avermectins biosynthetic gene cluster (ave) has been achieved recently, while the establishment of an Ivermectin homogeneous component producing strain is challenging because of the limited compatibility between the native and heterologous polyketide synthase (PKS) domains. In this study, the PKS module 2 Dehydratase (DH)-Enoylreductase (ER)-Ketoreductase (KR) domain set of Meilingmycin, which is another naturally occurring homologue of Avermectin, was employed to substitute the DH-KR domains of Avermectins PKS module 2 to generate an Ivermectin biosynthetic gene cluster (ive). Ivermectins B1a and A1a were heterologously biosynthesized in a classic actinomyces host Streptomyces lividans. The Avermectin B1a high-producing strain S. avermitilis 3-115 was genetically engineered to give an artificial host cell and Ivermectin B1a single component was effectively produced with a production of 1.25 ± 0.14 g/L. Keywords: Avermectin, Ivermectin, Meilingmycin, Domain swapping, Heterologo-us biosynthesis

The growing popularity of the mini-camera is posing a serious threat to privacy and personal security. Disguised as common tools in rooms, these devices can become undetectable. Moreover, conventional active laser detection systems often fail to recognize them owing to their small lens size, weak reflectivity, and the influence of interference targets. In this paper, a method for building a laser active detection system for mini-cameras is proposed. Using a monostatic optical system and a deep learning classification algorithm, this anti-camera system can detect mini-cameras accurately in real time. This article describes the system components including its optical design, core components and image processing algorithm. The capability of the system for detecting mini-cameras and identifying interference is also experimentally demonstrated. This work successfully overcomes the limit of mini-camera detection using deep learning methods in active laser detection systems.

A dual-polarization, dual-frequency and dual-transvers-mode laser beam is generated by a dual-medium microchip laser. The dual-transvers-mode includes a linearly polarized LG01 mode and a perpendicular polarized TEM00 mode, which have different optical frequencies. How is the beat frequency of the dual-mode influenced by the thermal factors, including cooling temperature of birefringent crystal and thermal effect of gain medium, is experimentally investigated and theoretically analyzed. These studies offer an extension and better understanding of the dual-medium based dual-frequency laser, which is of important applications in coherent Lidar detection and optical communications.

Mini-cameras are one of several emerging types of cat-eye devices using small lenses with insufficient retro-reflection for traditional detection systems to identify. Based on a structural analysis of these devices, this paper provides an accurate theoretical description of the received beam profile. The simulated and experimental results have good similarity in terms of profile shapes and trends with different incident angles and defocus distances. An analysis of the detection conditions and the reflection image features described in this article can thus be applied to hidden camera detection. Mini-cameras can be detected according to these features of the received beam profiles.

At present, the mainstream laser point cloud classification algorithms are mainly based on the geometric information of the target. Nevertheless, if there is occlusion between the targets, the classification effect will be negatively affected. Compared with the above methods, a new method of ski tracks extraction using laser intensity information based on target reflection is presented in this paper. The method can complete the downsampling of the point cloud datasets of ski tracks under the condition that the information of the target edge is complete. Then, the clustering and extraction of ski tracks are effectively accomplished based on the smoothing threshold and curvature between adjacent point clouds. The experimental results show that, different from the traditional methods, the composite classification method based on the intensity information proposed in this paper can effectively extract ski tracks from the complex background. By comparing the proposed method to the Euclidean distance method, the clustering segmentation method, and the RANSAC method, the average extraction accuracy is increased by 16.9%, while the over extraction rate is reduced by 8.4% and the under extraction rate is reduced by 8.6%, allowing us to accurately extract the ski track point cloud of a ski resort.

Studying the spatio-temporal niche partitioning among closely related sympatric species is essential for understanding their stable coexistence in animal communities. However, consideration of niche partitioning across multiple ecological dimensions is still poor for many sympatric pheasant species. Here, we studied temporal activity patterns and spatial distributions of the Blue Eared Pheasant (EP, Crossoptilon auritum) and Blood Pheasant (BP, Ithaginis cruentus) in the Qilian Mountains National Nature Reserve (QMNNR), Northwestern China, using 137 camera traps from August 2017 to August 2020. Kernel density estimation was applied to analyze diel activity patterns, and the Maxent model was applied to evaluate their suitable distributions and underlying habitat preferences. Eight Galliformes species were captured in 678 detection records with 485 records of EP and 106 records of BP over a total of 39,206 camera days. Their monthly activity frequencies demonstrate temporal partitioning but their diel activity patterns do not. Furthermore, 90.78% of BP distribution (2867.99 km2) overlaps with the distribution of EP (4355.86 km2) in the QMNNR. However, BP manifests a high dependence on forest habitats and shows larger Normalized Difference Vegetation Index (NDVI) values, while EP showed obvious avoidance of forest with NDVI greater than 0.75. Hence, differentiation in monthly activity patterns and partitioning in habitat preference might facilitate their coexistence in spatiotemporal dimensions. Conservation actions should give priority to highly overlapping areas in the center and east of the QMNNR and should strengthen forest landscape connectivity, as they provide irreplaceable habitats for these threatened and endemic Galliformes.

Objective. Accumulating evidence indicates that microRNAs (miRNAs) play crucial roles in osteogenic differentiation. However, the associated mechanisms remain elusive. This paper is aimed at exploring the role of miR-129-5p in regulating bone marrow mesenchymal stem cell (BMSC) differentiation and bone regeneration in vivo and in vitro. Methods. BMSCs were transduced by miR-129-5p mimic, miR-129-5p inhibitor, and negative control lentivirus. The ability of BMSC differentiation to osteoblast was tested by alkaline phosphatase (ALP) and alizarin red staining (ARS). The expression of osteogenic genes (Runx2, Bmp2, and OCN) was examined via quantitative RT-PCR and western blot. A mouse model of calvaria defect was investigated by Micro-CT, immunohistochemistry, and histological examination. The luciferase reporter gene assay was performed to confirm the binding between Dkk3 and miR-129-5p. For the transfection experiments, lipofectamine 3000 was used to transfect pcDNA-Dkk3 into BMSCs to overexpress Dkk3. Coimmunoprecipitation and immunofluorescent localization assay were included for exploring the role of Dkk3 and β-catenin. Results. miR-129-5p was induced in BMSCs and MSC cell line C3H10T1/2 cells under osteogenic medium. Overexpression of miR-129-5p significantly promoted osteogenic differentiation of BMSCs in vitro. Moreover, BMSCs transduced with miR-129-5p mimic exhibited better bone regeneration compared with BMSCs transduced with control counterpart in vivo. Luciferase and western blot data showed that Dickkopf3 (Dkk3) is a target gene of miR-129-5p and the expression of Dkk3 was inhibited in BMSCs transduced with miR-129-5p mimic but enhanced in BMSCs transduced with miR-129-5p inhibitor. In addition, Dkk3 interacted with β-catenin directly. Conclusions. miR-129-5p promotes osteogenic differentiation of BMSCs and bone regeneration, and miR-129-5p/Dkk3 axis may be new potential targets for the treatment of bone defect and bone loss.

Carbon sinks in terrestrial ecosystems can be significantly increased by afforestation, which will slow global warming. However, it is still unclear how different plantations influence the carbon sink and how they respond to environmental factors, especially in drylands. In this study, eddy correlation method (EC) was used to measure carbon and water fluxes and environmental factors of two artificial forests (Larix principis-rupprechtii and Pinus tabulaeformis) in the dryland of Northwest China, and the responses of evapotranspiration (ET), net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (RECO) to environmental factors were also assessed. Results showed that the L. principis-rupprechtii forest ecosystem had higher water use efficiency (WUE), light use efficiency (LUE), GPP, and RECO than the P. tabulaeformis forest ecosystem. However, the proportion of net ecosystem production (NEP) to GPP in the P. tabulaeformis forest ecosystem (62.89%) was higher than that in the L. principis-rupprechtii forest ecosystem (47.49%), indicating that the P. tabulaeformis forest ecosystem had the higher carbon sequestration efficiency. In addition, the CO2 and H2O fluxes in the L. principis-rupprechtii forest ecosystem were more sensitive to environmental factors, compared with the P. tabulaeformis forest ecosystem. Further, the RECO of the L. principis-rupprechtii forest ecosystem was more sensitive to temperature changes, which implies that the L. principis-rupprechtii forest ecosystem will release more CO2 than the P. tabulaeformis forest ecosystem with a warming climate. Therefore, the P. tabulaeformis forest ecosystem may have better carbon sequestration potential. These results are important for understanding the effects of climate change on the CO2 and H2O cycles in coniferous plantation ecosystems in drylands.

The environment of ski resorts is usually complex and changeable, and there are few characteristic objects in the background, which creates many difficulties for the registration of ski-resort point cloud datasets. However, in the traditional iterative closest point (ICP) algorithm, two points need to have good initial positions, otherwise it is easy to get caught up in local optimizations in registration. Aiming at this problem, according to the topographic features of ski resorts, this paper put forward a ski-resort coarse registration method based on extraction, and matching between feature points is proposed to adjust the initial position of two point clouds. Firstly, the feature points of the common part of the point cloud datasets are extracted based on the SIFT algorithm; secondly, the Euclidean distance between the feature normal vectors is used as the pairing condition to complete the pairing between the feature points in the point cloud datasets; then, the feature point pair is purified by using the included angle of the normal vector; finally, in the process of coarse registration, the rotation matrix and translation vector between point clouds are solved by the unit quaternion method. Experiments demonstrate that the proposed coarse registration method based on the normal vector of feature points is helpful to the smooth completion of the subsequent fine registration process, avoids the phenomenon of falling into local optimization, and effectively completes the ski-resort point cloud registration.

Actinomycetes in extreme alpine habitat have attracted much attention due to their unique physiological activities and functions. However, little is known about their ecological distribution and diversity. Here, we explored the phylogenetic relationship and physiological heterogeneity of cultivable actinomycetes from near-root soils of different plant communities in the Laohu Ditch (2200 – 4200 m) and Gaize County area (5018 – 5130 m) on the Qinghai-Tibetan Plateau. A total of 128 actinomycete isolates were obtained, 16S rDNA-sequenced and examined for antimicrobial activities and organic acid, H2S, diffusible pigments, various extracellular enzymes production. Seventy three isolates of the total seventy eight isolates from the Laohu Ditch, frequently isolated from 2200 to 4200 m, were closely related to Streptomyces spp. according to the 16S rDNA sequencing, while four isolates within the genus Nocardia spp. were found at 2200, 2800, and 3800 m. In addition, one potential novel isolate with 92% sequence similarity to its nearest match Micromonospora saelicesensis from the GenBank database, was obtained at 2200 m. From the Gaize County area, fifty Streptomyces isolates varied in diversity at different sites from 5018 to 5130 m. The investigation of phenotypic properties of 128 isolates showed that 94.5, 78.9, 68, 64.8, 53, 51.6, 50, 36.7, 31.2, and 22.7% of the total isolates produced catalase, lipase 2, urease, protease, H2S, lipase 3, amylase, lipase 1, diffusible pigment and organic acid, respectively. The antimicrobial assays of the total isolates revealed that 5, 28, 19, and 2 isolates from Streptomyces spp. exhibited antimicrobial activity against Escherichia coli, Staphylococcus aureus, Candida albicans, and Pseudomonas aeruginosa, respectively. This study intends to bring helpful insights in the exploitation and utilization of alpine actinomycetes for novel bioactive compounds discovery.

Solar-pumped lasers (SPLs) allow direct solar-to-laser power conversion, and hence, provide an opportunity to harness a renewable energy source. Herein, we report significant improvements in end-side-pumped solar laser collection efficiency and beam brightness using a novel 1.5-m-diameter compound solar concentrator combining a Fresnel lens and modified parabolic mirror. A key component of this scheme is the off-axis-focused parabolic mirror. An original dual-parabolic pump cavity is another feature. To determine the dependence of the SPL performance on the distance between the focus and central axis of the modified parabolic mirror, several systems with different distances were optimized using TracePro and ASLD software. It was numerically calculated that end-side pumping a 5-mm-diameter, 22-mm-long Nd:YAG crystal rod would generate 74.6 W of continuous-wave solar laser power at a collection efficiency of 42.2 W/m2, i.e., 1.1 times greater than the previous record value. Considering the laser beam quality, a brightness figure of 0.063 W was obtained, which is higher than that of other multimode SPL designs with end-side pumping. Thus, our SPL concentrator offers the possibility of achieving a beam quality as high as that obtainable via side pumping, alongside highly efficient energy conversion, which is characteristic to end-side pumping.

In order to obtain high peak power RF intensity-modulated pulses for long-distance applications, a Q-switched Nd:YAG laser is injection seeded by a dual-frequency laser signal. The beat note frequency of the dual-frequency laser signal is adjusted to the frequency spacing of two adjacent longitudinal modes of the Q-switched laser. When the dual-frequency signal is injected into the Q-switched slave resonator, simultaneously two cavity axial modes are tuned to allow the injected wave frequencies within the axial modes selection range, the two selected slave cavity modes will oscillate due to phase-pulling effect. The Interference of the two modes results in intensity modulated pulses. The modulation frequency equals to a free spectral range of the Q-switched cavity, which is 225 MHz in our experiment. Maximum intensity-modulated pulse energy of 7 mJ and pulsewidth of 16 ns are measured. The dependence of locking bandwidth to the injected power is also studied experimentally, it is confirmed that the locking bandwidth increases with respect to the injected power of the seed signal. The high peak power RF intensity-modulated pulsed light source is a promising candidate for long-distance lidar-radar applications.

The influence of phase noise in a dual-frequency laser phase-shift range finder is theoretically and experimentally investigated. The proposed range finder is based on the use of a coherent dual-frequency laser and direct detection of the backscattered laser. The effects of laser phase noise and noise from an acousto-optic frequency shifter (AOFS) on the dual-frequency laser phase-shift range finder are analyzed. Expressions of the power spectral density and the phase noise of the dual-frequency laser beat note are deduced. In addition, we find that noise from the AOFS has a considerable impact on beat note noise conversion. The theoretical results can be used to estimate the influence of laser phase noise, noise induced by the AOFS and delay length in the dual-frequency laser range finder. An experiment involving the dual-frequency laser range finder is performed on outdoor targets at a distance of 200 m, and the phase jitter observed in the experiment is in good agreement with the model of beat note phase noise.

Long-term afforestation strongly changes the soil’s physicochemical and biological properties. However, the underlying mechanism of different tree species driving change in soil nutrients is still unclear in the long-term dryland plantations of the Loess Plateau, China. In this study, samples of surface soil (0–20 cm) and woody litter were collected from five plantations (≥50 years) of Caragana korshinskii, Armeniaca sibirica, Populus hopeiensis, Platycladus orientalis, and Pinus tabulaeformis and a natural grassland, and tested for the carbon, nitrogen, phosphorus, and potassium contents, as well as the soil sucrase (SC), urease (UE), and alkaline phosphorus (ALP) activities. We found that soil nutrients, enzyme activities, and the litter’s chemical properties obviously varied among five tree species. C. korshinskii significantly increased the soil’s TC, organic carbon (OC), total nitrogen (TN), available nitrogen (AN), and available potassium (AK) by 28.42%, 56.08%, 57.41%, 107.25%, and 10.29%, respectively, and also increased the soil’s available phosphorus (AP) by 18.56%; while P. orientalis significantly decreased soil TN (38.89%), TP (30.58%), AP (76.39%), TK (8.25%), and AK (8.33%), and also decreased soil OC (18.01%) and AN (1.09%), compared with those in grassland. The C. korshinskii plantation had higher quality litter and soil enzyme activities than the P. orientalis plantation. Moreover, 62.2% of the total variation in soil nutrients was explained by the litter’s chemical properties and soil enzyme activities, and the litter phosphorus (LP) and soil ALP had a more significant and positive impact on soil nutrients. Therefore, tree species, LP, and soil ALP were key factors driving soil nutrient succession in dryland plantations. The significantly positive nitrogen–phosphorus coupling relationship in the “litter–enzyme–soil” system revealed that the improving nitrogen level promoted the phosphorus cycle of the plantation ecosystem. Our results suggest that leguminous tree species are more suitable for dryland afforestation through the regulation of litter quality and soil enzyme activities.

Abstract Background The behavior of cranes reflects many of their survival strategies, but little has been known of the incubation strategies of cranes, in which both parents share incubation duties, in response to cold temperatures in alpine environments. The lack of information may restrict the effective conservation of the threatened Black-necked Crane (Grus nigricollis), a biparental bird nesting in high elevation wetlands. Methods We directly observed and used infrared video cameras from 2014 to 2015 to study the incubation behavior and quantitatively measured the frequency and details of egg turning behavior in the Black-necked Crane at the Yanchiwan National Nature Reserve in western Gansu Province, China. Results At lower ambient temperatures in the morning, crane parents spent more time on the nest with less recess frequency and prolonged on-bout duration, while at higher temperatures around noon, the parents had more frequent recesses from incubation and shorter periods between nest exchanges. They adjusted the amount of time incubating by varying the recess frequency and the length of on-bout duration. Mean nest attendance and egg turning frequency of females were significantly higher than those of the males. The nest attendance and on-bout duration of females showed a significantly negative relationship with those of males. The two parents responded differently to the change of temperature. Females spent more time on the nest at lower morning temperatures, while males increased their time on the nest at higher temperatures after noon. Higher incubation recess frequency and egg turning frequency were observed at noon, probably because parents spent more time foraging, taking advantage of the lower egg cooling rate. Conclusion Both Black-necked Crane parents in the alpine environment adjusted their behavior in response to the thermal requirements of eggs and the weather conditions experienced. Our findings demonstrate that parents of this species incubated in different but complementary ways and efficiently enhanced egg care in a dynamic environment, so as to maximize benefits from the warm portion of the day and the intense solar radiation while minimizing the cost of rewarming eggs and the risks of cooling eggs.

Avermectins, a group of polyketide natural products, are widely used as anthelmintics in agriculture. Metabolic engineering and combinatorial biosynthesis were extensively employed to improve Avermectins production and create novel Avermectin derivatives, including Ivermectin and Doramectin. It is labor intensive and time cost to genetically manipulate Avermectins producer Streptomyces avermitilis in vivo. Cloning and heterologous expression of Avermectins biosynthetic gene cluster will make it possible to tailor the cluster in vitro. We constructed a Bacterial Artificial Chromosome (BAC) library of S. avermitilis ATCC 31267 with inserted DNA fragments ranged from 100 to 130 Kb. Five recombinant BAC clones which carried the Avermectins biosynthetic gene cluster ave (81 Kb in size) were screened out from the library. Then, ave was hetero-expressed in S. lividans. Three Avermectin components, A2a, B1a and A1a were detected from the cell extracts of recombinant strains. It will facilitate the development of Avermectin derivatives by polyketide synthase domain swapping and provide functional element for Avermectins synthetic biology study.

We investigate the radio-frequency (RF) up-conversion and waveform generation properties of an optical fiber loop including a frequency shifter and an amplifier. By seeding the loop with a single-frequency continuous-wave laser, one can develop a wide optically carried RF comb, whose spectral extension is governed by the loop net gain. In addition, by choosing the fiber loop length and the RF shifting frequency, arbitrary waveforms can be generated. We present an analytical interference model that includes the time delay, the frequency shift, and the gain. Experiments are conducted with 1.06-μm fiber-optic components. Using a 200-MHz acousto-optic frequency shifter, we find a 19-fold up-conversion up to 3.8 GHz with a typical in-loop gain of 3. Various waveforms including bright and dark pulses, square- or triangle shaped are achieved by properly adjusting the loop length and the frequency shift. A good agreement between experimental and theoretical results is obtained. The fully fibered microwave-photonic source is applied to a laboratory Doppler velocimetry demonstration. The gain in sensitivity obtained with the up-converted signal is readily observed.

Previous studies indicate that the plant phenotypic traits eventually shape its microbiota due to the community assembly based on the functional types. If so, the distance-related variations of microbial communities are mostly only in taxonomical composition due to the different seeds pool, and there is no difference in microbial community functional structure if the location associated factors would not cause phenotypical variations in plants. We test this hypothesis by investigating the phyllospheric microbial community from five species of spruce (Picea spp.) trees that planted similarly but at three different locations. Results indicated that the geographical location affected microbial taxonomical compositions and had no effect on the community functional structure. In fact, this actually leads to a spurious difference in the microbial community. Our findings suggest that, within similar host plants, the phyllosphere microbial communities with differing taxonomical compositions might be functionally similar.