Spatiotemporal disturbances and attribution analysis of mangrove in southern China from 1986 to 2020 based on time-series Landsat imagery.

As one of the most productive ecosystems in the world, mangrove has a critical role to play in both the natural ecosystem and the human economic and social society. However, two thirds of the world's mangrove have been irreversibly damaged over the past 100 years, as a result of ongoing human activities and climate change. In this paper, adopting Landsat for the past 36 years as the data source, the detection of spatiotemporal changes of mangrove in southern China was carried out based on the Google Earth Engine (GEE) cloud platform using the LandTrendr algorithm. In addition, the attribution of mangrove disturbances was analyzed by a random forest algorithm. The results indicated the area of mangrove recovery (5174.64 hm2) was much larger than the area of mangrove disturbances (1625.40 hm2) over the 35-year period in the study area. The disturbances of mangrove in southern China were dominated by low and low-to-medium-level disturbances, with an area of 1009.89 hm2, accounting for 57.50 % of the total disturbances. The mangrove recovery was also dominated by low and low-to-medium-level recovery, with an area of 3239.19 hm2, accounting for 62.61 % of the total recovery area. Both human and natural factors interacted and influenced each other, together causing spatiotemporal disturbances of mangrove in southern China during 1986-2020. The mangrove disturbances in the Phase I (1986-2000) and Phase III (2011-2020) were characterized by human-induced (50.74 % and 58.86 %), such as construction of roads and aquaculture ponds. The mangrove disturbances in the Phase II (2001-2010) were dominated by natural factors (55.73 %), such as tides, flooding, and species invasions. It was also observed that the area of mangrove recovery in southern China increased dramatically from 1986 to 2020 due to the promulgation and implementation of the Chinese government's policy on mangrove protection, as well as increased human awareness of mangrove wetland protection.

Cutting-Force Modeling Study on Vibration-Assisted Micro-Milling of Bone Materials.

This study aims to enhance surgical safety and facilitate patient recovery through the investigation of vibration-assisted micro-milling technology for bone-material removal. The primary objective is to reduce cutting force and improve surface quality. Initially, a predictive model is developed to estimate the cutting force during two-dimensional (2D) vibration-assisted micro-milling of bone material. This model takes into account the anisotropic structural characteristics of bone material and the kinematics of the milling tool. Subsequently, an experimental platform is established to validate the accuracy of the cutting-force model for bone material. Micro-milling experiments are conducted on bone materials, with variations in cutting direction, amplitude, and frequency, to assess their impact on cutting force. The experimental results demonstrate that selecting appropriate machining parameters can effectively minimize cutting force in 2D vibration-assisted micro-milling of bone materials. The insights gained from this study provide valuable guidance for determining cutting parameters in vibration-assisted micro-milling of bone materials.

A reinterpretation of the gap fraction of tree crowns from the perspectives of computer graphics and porous media theory.

The gap fraction (GF) of vegetative canopies is an important property related to the contained bulk of reproductive elements and woody facets within the tree crown volume. This work was developed from the perspectives of porous media theory and computer graphics techniques, considering the vegetative elements in the canopy as a solid matrix and treating the gaps between them as pores to guide volume-based GFvol calculations. Woody components and individual leaves were extracted from terrestrial laser scanning data. The concept of equivalent leaf thickness describing the degrees of leaf curling and drooping was proposed to construct hexagonal prisms properly enclosing the scanned points of each leaf, and cylinder models were adopted to fit each branch segment, enabling the calculation of the equivalent leaf and branch volumes within the crown. Finally, the volume-based GFvol of the tree crown following the definition of the void fraction in porous media theory was calculated as one minus the ratio of the total plant leaf and branch volume to the canopy volume. This approach was tested on five tree species and a forest plot with variable canopy architecture, yielding an estimated maximum volume-based GFvol of 0.985 for a small crepe myrtle and a minimal volume-based GFvol of 0.953 for a sakura tree. The 3D morphology of each compositional element in the tree canopy was geometrically defined and the canopy was considered a porous structure to conduct GFvol calculations based on multidisciplinary theory.

Shortwave Radiation Calculation for Forest Plots Using Airborne LiDAR Data and Computer Graphics.

Forested environments feature a highly complex radiation regime, and solar radiation is hindered from penetrating into the forest by the 3D canopy structure; hence, canopy shortwave radiation varies spatiotemporally, seasonally, and meteorologically, making the radiant flux challenging to both measure and model. Here, we developed a synergetic method using airborne LiDAR data and computer graphics to model the forest canopy and calculate the radiant fluxes of three forest plots (conifer, broadleaf, and mixed). Directional incident solar beams were emitted according to the solar altitude and azimuth angles, and the forest canopy surface was decomposed into triangular elements. A ray tracing algorithm was utilized to simulate the propagation of reflected and transmitted beams within the forest canopy. Our method accurately modeled the solar radiant fluxes and demonstrated good agreement (R 2 ≥ 0.82) with the plot-scale results of hemispherical photo-based HPEval software and pyranometer measurements. The maximum incident radiant flux appeared in the conifer plot at noon on June 15 due to the largest solar altitude angle (81.21°) and dense clustering of tree crowns; the conifer plot also received the maximum reflected radiant flux (10.91-324.65 kW) due to the higher reflectance of coniferous trees and the better absorption of reflected solar beams. However, the broadleaf plot received more transmitted radiant flux (37.7-226.71 kW) for the trees in the shaded area due to the larger transmittance of broadleaf species. Our method can directly simulate the detailed plot-scale distribution of canopy radiation and is valuable for researching light-dependent biophysiological processes.

Individual Tree Crown Segmentation and Crown Width Extraction From a Heightmap Derived From Aerial Laser Scanning Data Using a Deep Learning Framework.

Deriving individual tree crown (ITC) information from light detection and ranging (LiDAR) data is of great significance to forest resource assessment and smart management. After proof-of-concept studies, advanced deep learning methods have been shown to have high efficiency and accuracy in remote sensing data analysis and geoscience problem solving. This study proposes a novel concept for synergetic use of the YOLO-v4 deep learning network based on heightmaps directly generated from airborne LiDAR data for ITC segmentation and a computer graphics algorithm for refinement of the segmentation results involving overlapping tree crowns. This concept overcomes the limitations experienced by existing ITC segmentation methods that use aerial photographs to obtain texture and crown appearance information and commonly encounter interference due to heterogeneous solar illumination intensities or interlacing branches and leaves. Three generative adversarial networks (WGAN, CycleGAN, and SinGAN) were employed to generate synthetic images. These images were coupled with manually labeled training samples to train the network. Three forest plots, namely, a tree nursery, forest landscape and mixed tree plantation, were used to verify the effectiveness of our approach. The results showed that the overall recall of our method for detecting ITCs in the three forest plot types reached 83.6%, with an overall precision of 81.4%. Compared with reference field measurement data, the coefficient of determination R 2 was ≥ 79.93% for tree crown width estimation, and the accuracy of our deep learning method was not influenced by the values of key parameters, yielding 3.9% greater accuracy than the traditional watershed method. The results demonstrate an enhancement of tree crown segmentation in the form of a heightmap for different forest plot types using the concept of deep learning, and our method bypasses the visual complications arising from aerial images featuring diverse textures and unordered scanned points with irregular geometrical properties.

Wave-thermal effect of a temperature-tunable terahertz absorber.

Heat-sensitive materials have great applications in sensor, detector, and tunable photoelectric devices. However, the wave-thermal effect of the heat-sensitive material is rarely been investigated in the THz range. Here, we propose the incorporation of heat-sensitive material (strontium titanate (STO)) within a THz absorber. The simulated results show that the absorptance and frequency can be dynamically controlled by the temperature of STO. Because the absorbed THz waves are finally converted into heat, then we research the theoretical mechanism of heat generation. Theoretical analysis shows that there are two reasons for the temperature rise: surface plasmon polariton (SPP) and ohmic loss of gold patch; Electromagnetic energy consumption inside the loss materials. To verify the theory, finally, we use COMSOL Multiphysics to research the nanosecond wave-thermal effect. The transient temperature of the wave-thermal effect is calculated quantitatively. The quantitative prediction of temperature variation can provide good guidance for thermal regulation and wave-thermally tunable THz devices.

Mosquito population dynamics during the construction of Three Gorges Dam in Yangtze River, China.

BACKGROUND: Mosquitoes are responsible for spreading many diseases and their populations are susceptible to environmental changes. The ecosystems in the Three Gorges Region were probably altered because of changes to the environment during the construction of the Three Gorges Dam (TGD), the world's largest hydroelectric dam by generating capacity. METHODS: We selected three sites at which to monitor the mosquitoes from 1997 to 2009. We captured adult mosquitoes with battery-powered aspirators fortnightly between May and September of each year in dwellings and sheds. We identified the mosquito species, and examined changes in the species density during the TGD construction. We monitored changes in the species and density of mosquitoes in this area for 13 years during the TGD construction and collected information that could be used to support the control and prevention of mosquito-borne infections. RESULTS: We found that the mosquito species composition around the residential areas remained the same, and the density changed gradually during the TGD construction. The changes in the populations tended to be consistent over the years, and the densities were highest in July, and were between 3 and 5 times greater in the sheds than in the dwellings. CONCLUSIONS: The mosquito species and populations remained stable during the construction of the TGD. The mosquito density may have increased as the reservoir filled, and may have decreased during the clean-up work. Clean-up work may be an effective way to control mosquitoes and prevent mosquito-borne diseases.

Levels of heavy metals and trace elements in umbilical cord blood and the risk of adverse pregnancy outcomes: a population-based study.

To better understand the relationship between prenatal exposure to heavy metals and trace elements and the risk of adverse pregnancy outcomes, we investigated the status of heavy metals and trace elements level in a Chinese population by collecting umbilical cord blood. Umbilical cord blood heavy metals and trace elements concentrations were determined by inductively coupled plasma-mass spectrometry. No differences with statistical significance in the median arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), manganese (Mn), nickel (Ni), lead (Pb), strontium (Sr), thallium (Tl), vanadium (V), and zinc (Zn) concentrations were observed between the adverse pregnancy outcome group and the reference group. Titanium (Ti) and antimony (Sb) were found at higher levels with statistical significance in the cord blood samples with adverse pregnancy group when compared to the ones in the reference group. The association between Ti levels and the risk of adverse pregnancy outcomes remained significant after adjusting for potential confounding factors, including newborn weight. These results indicated that environmental exposure to Ti may increase the risk of adverse pregnancy outcomes in Chinese women without occupational exposure.

[Process strategy for ethanol production from lignocellulose feedstock under extremely low water usage and high solids loading conditions].

The massive water and steam are consumed in the production of cellulose ethanol, which correspondingly results in the significant increase of energy cost, waster water discharge and production cost as well. In this study, the process strategy under extremely low water usage and high solids loading of corn stover was investigated experimentally and computationally. The novel pretreatment technology with zero waste water discharge was developed; in which a unique biodetoxification method using a kerosene fungus strain Amorphotheca resinae ZN1 to degrade the lignocellulose derived inhibitors was applied. With high solids loading of pretreated corn stover, high ethanol titer was achieved in the simultaneous saccharification and fermentation process, and the scale-up principles were studied. Furthermore, the flowsheet simulation of the whole process was carried out with the Aspen plus based physical database, and the integrated process developed was tested in the biorefinery mini-plant. Finally, the core technologies were applied in the cellulose ethanol demonstration plant, which paved a way for the establishment of an energy saving and environment friendly technology of lignocellulose biotransformation with industry application potential.

The quality of randomized controlled trials on DanShen in the treatment of ischemic vascular disease.

BACKGROUND AND OBJECTIVES: Many randomized controlled trials (RCTs) were conducted to evaluate the efficacy of DanShen (Salvia miltiorrhizae, an herbal medicine) on ischemic vascular diseases (IVD). However, there has been no systematic evaluation of the quality of DanShen RCTs so far. The aims of this study were (1) to assess the quality of DanShen RCTs on IVD published in mainland China from 1998 to 2007 and (2) to explore the factors correlating with the quality. DESIGN: A number of Chinese databases were searched, and most of DanShen RCTs on IVD were collected. According to CONSORT for TCM (Consolidated Standards for Reporting of Trials for Traditional Chinese Medicine) and the Jadad scale, the quality assessment and data abstraction were performed independently by two reviewers. One-way analysis of variance and Pearson correlation analysis were applied to explore the association between basic characteristic and the quality of the RCTs. RESULTS: One hundred and fifty (150) DanShen RCTs were identified finally. The mean (standard deviation) score of 150 DanShen RCTs assessed by CONSORT for TCM was 23.87 (3.68), and 1.94 (0.82) by the Jadad scale, respectively. Only 6.7% (10/150) of RCTs were identified with high quality (Jadad score > or =4). Authors' affiliation, publication journal, sample size, and follow-up time were correlated with the quality of DanShen RCTs. CONCLUSIONS: The quality of DanShen RCTs in mainland China has not been improved significantly over recent years, and the overall quality of DanShen RCTs is still poor.