Scan2Drawing: Use of Deep Learning for As-Built Model Landscape Architecture

This paper presents an innovative and fully automatic solution of generating as-built computer-aided design (CAD) drawings for landscape architecture (LA) with three dimensional (3D) reality data scanned via drone, camera, and LiDAR. To start with the full pipeline, 2D feature images of ortho-image and elevation-map are converted from the reality data. A deep learning-based light convolutional encoder–decoder was developed, and compared with U-Net (a binary segmentation model), for image pixelwise segmentation to realize automatic site surface classification, object detection, and ground control point identification. Then, the proposed elevation clustering and segmentation algorithms can automatically extract contours for each instance from each surface or object category. Experimental results showed that the developed light model achieved comparable results with U-Net in landing pad segmentation with average intersection over union (IoU) of 0.900 versus 0.969. With the proposed data augmentation strategy, the light model had a testing pixel accuracy of 0.9764 and mean IoU of 0.8922 in the six-class segmentation testing task. Additionally, for surfaces with continuous elevation changes (i.e., ground), the developed algorithm created contours only have an average elevation difference of 1.68 cm compared to dense point clouds using drones and image-based reality data. For objects with discrete elevation changes (i.e., stair treads), the generated contours accurately represent objects’ elevations with zero difference using light detection and ranging (LiDAR) data. The contribution of this research is to develop algorithms that automatically transfer the scanned LA scenes to contours with real-world coordinates to create as-built computer-aided design (CAD) drawings, which can further assist building information modeling (BIM) model creation and inspect the scanned LA scenes with augmented reality. The optimized parameters for the developed algorithms are analyzed and recommended for future applications

Recombinant amelogenin peptide TRAP promoting remineralization of early enamel caries: An in vitro study

Objective: To explore the regulatory effect of recombinant amelogenin peptide TRAP on the remineralization of early enamel carious lesions.Methods: Forty-eight bovine enamel blocks that prepared initial lesions in vitro were split at random into four groups for immersion treatment for 12 days: 1) remineralizing medium; 2) studied peptide 1 (consisting of the N- and C-termini of porcine amelogenin) + remineralizing medium; 3) studied peptide 2 (TRAP) + remineralizing medium; 4) fluoride + remineralizing medium. After demineralization and remineralization immersion, each specimen’s mean mineral loss and lesion depth were measured using micro-computed tomography (micro-CT). The changes in lesion depth (∆LD) and mineral gain (∆Z) were computed following remineralization. The enamel samples were then cut into sections and examined with polarized light microscopy (PLM). The cross-section morphology was observed by scanning electron microscopy (SEM). The crystal phase was analyzed by an X-ray micro-diffractometer (XRD). The calcium-binding properties were determined using isothermal titration calorimetry (ITC).Results: Micro-CT analysis revealed a significant reduction in mineral loss in the four groups following the remineralization treatment (p < 0.05). The treatment with fluoride resulted in the greatest ∆Z and ∆LD, whereas the treatment with a remineralizing medium showed the least ∆Z and ∆LD among all groups. The ∆Z and ∆LD of the studied peptide 1 and studied peptide 2 groups were greater than those of the remineralizing medium group. However, there was no significant difference between the studied peptide 1 and studied peptide 2 groups (p > 0.05). All of the samples that the PLM analyzed had a thickening of the surface layer. A negative birefringent band changed in the lesion’s body. The SEM displayed that minerals were formed in all four groups of samples. The XRD results indicated that the products of remineralization of the studied peptide were hydroxyapatite crystals (HA). ITC showed that there were two binding modes between the calcium and peptide TRAP.Conclusion: This study confirmed the potential of the recombinant amelogenin peptide TRAP as a key functional motif of amelogenin protein for enamel remineralization and provided a promising biomaterial for remineralization in initial enamel carious lesion treatment

Prediction of Enterprise Free Cash Flow Based on a Backpropagation Neural Network Model of the Improved Genetic Algorithm

Enterprises with good long-term free cash flow data often have better prospects than enterprises with good net profit but unstable free cash flow for a long time, and free cash flow prediction is an important part of evaluating the enterprise value of an enterprise. By determining the fitness function, algorithm formula, population, and Backpropagation (BP) neural network design, a BP neural network model based on the improved genetic algorithm is proposed to predict the free cash flow of enterprises. Taking the free cash flow data of G Company from 1 January 2019 to 30 June 2019 as an example, after evaluating the most neurons and the best population, analyzing the relative errors and comparing the average relative errors of different prediction models, the results show that the model has better prediction accuracy. Cash flow forecasting can effectively improve decision making on productions and operations and the investment financing of enterprises, and has important practical significance for studying enterprise fund management

Resilient and sustainable production of peanut (Arachis hypogaea) in phosphorus-limited environment by using exogenous gamma-aminobutyric acid to sustain photosynthesis

Globally, many low to medium yielding peanut fields have the potential for further yield improvement. Low phosphorus (P) limitation is one of the significant factors curtailing Arachis hypogaea productivity in many regions. In order to demonstrate the effects of gamma-aminobutyric acid (GABA) on peanuts growing under P deficiency, we used a pot-based experiment to examine the effects of exogenous GABA on alleviating P deficiency-induced physiological changes and growth inhibition in peanuts. The key physiological parameters examined were foliar gas exchange, photochemical efficiency, proton motive force, reactive oxygen species (ROS), and adenosine triphosphate (ATP) synthase activity of peanuts under cultivation with low P (LP, 0.5 mM P) and control conditions. During low P, the cyclic electron flow (CEF) maintained the high proton gradient (∆pH) induced by low ATP synthetic activity. Applying GABA during low P conditions stimulated CEF and reduced the concomitant ROS generation and thereby protecting the foliar photosystem II (PSII) from photoinhibition. Specifically, GABA enhanced the rate of electronic transmission of PSII (ETRII) by pausing the photoprotection mechanisms including non-photochemical quenching (NPQ) and ∆pH regulation. Thus, GABA was shown to be effective in restoring peanut growth when encountering P deficiency. Exogenous GABA alleviated two symptoms (increased root-shoot ratio and photoinhibition) of P-deficient peanuts. This is possibly the first report of using exogenous GABA to restore photosynthesis and growth under low P availability. Therefore, foliar applications of GABA could be a simple, safe and effective approach to overcome low yield imposed by limited P resources (low P in soils or P-fertilizers are unavailable) for sustainable peanut cultivation and especially in low to medium yielding fields

HPLC Profile of Longan (cv. Shixia) Pericarp-Sourced Phenolics and Their Antioxidant and Cytotoxic Effects

Longan (Dimocarpus longan Lour.) pericarp, the main by-product of aril and pulp processing, is abundant in phenolic compounds and worthy of further utilization. The present work firstly reported HPLC analysis and in vitro antioxidant evaluation of longan (cv. Shixia) pericarp-derived phenolics (LPPs), the purified longan pericarp extract (LPE), as well as their cytotoxic effect on lung cancer cell line, A549. The results indicated that the purified LPE had significant amounts of phenolics, with content of 57.8 ± 0.6 mg of gallic acid equivalents per gram of dry longan pericarp (mg GAE·g−1 DLP), which consisted of six phenolic compounds (A⁻F), including protocatechuic acid (A), isoscopoletin (B), quercetin (C), ellagic acid (D), corilagin (E), and proanthocyanidins C1 (F). Antioxidant assays showed that LPPs (10 μM) and LPE (1.0 mg·mL−1) had certain antioxidant activities, in which corilagin (E) possessed the best DPPH radical scavenging rate 71.8 ± 0.5% and •OH inhibition rate 75.9 ± 0.3%, and protocatechuic acid (A) exhibited the strongest Fe2+ chelating ability 36.4 ± 0.7%. In vitro cytotoxic tests suggested that LPPs had different effect on A549 cell line, in which corilagin (E) exhibited potent cytotoxicity with an IC50 value of 28.8 ± 1.2 μM. These findings were further confirmed by cell staining experiments

Time-Series Monitoring of Transgenic Maize Seedlings Phenotyping Exhibiting Glyphosate Tolerance

Glyphosate is a widely used nonselective herbicide. Probing the glyphosate tolerance mechanism is necessary for the screening and development of resistant cultivars. In this study, a hyperspectral image was used to develop a more robust leaf chlorophyll content (LCC) prediction model based on different datasets to finally analyze the response of LCC to glyphosate-stress. Chlorophyll a fluorescence (ChlF) was used to dynamically monitor the photosynthetic physiological response of transgenic glyphosate-resistant and wild glyphosate-sensitive maize seedlings and applying chemometrics methods to extract time-series features to screen resistant cultivars. Six days after glyphosate treatment, glyphosate-sensitive seedlings exhibited significant changes in leaf reflection and photosynthetic activity. By updating source domain and transfer component analysis, LCC prediction model performance was improved effectively (the coefficient of determination value increased from 0.65 to 0.84). Based on the predicted LCC and ChlF data, glyphosate-sensitive plants are too fragile to protect themselves from glyphosate stress, while glyphosate-resistant plants were able to maintain normal photosynthetic physiological activity. JIP-test parameters, φE0, VJ, ψE0, and M0, were used to indicate the degree of plant damage caused by glyphosate. This study constructed a transferable model for LCC monitoring to finally evaluate glyphosate tolerance in a time-series manner and verified the feasibility of ChlF in screening glyphosate-resistant cultivars

Fuzzy Adaptive PID Control for Multi- range Hydro- mechanical Continuously Variable Transmission in Tractor

In order to realize the control for multi- range hydro- mechanical continuously variable transmission（ HMCVT） in tractor,the fuzzy adaptive PID control for multi- range HMCVT in tractor is studied.The transmission system dynamics model of tractor and fuzzy adaptive PID control model are established based on Matlab / Simulink platform. According to the actual deviation of the actual vehicle speed and the target vehicle,the fuzzy control method is adopted to automatically adjust the PID control parameters,so as to achieve the purpose of control. The fuzzy adaptive PID control simulation on the tractor dynamics model and comparison with the PID control simulation. The results show that the stronger adaptive ability and robustness of fuzzy adaptive PID control of tractor

Calculation Method and Application of Inter-Regional and Inter-Provincial Market Trading Space for Promoting the Consumption of Clean Energy

Inter-provincial market trading is putting up with to implement the national energy strategy, increasing clean energy consuming and optimization energy allocation in large-scale. To promote energy consumption, the inter-province power transmission channel’ potential needs to be full excavate to deal with clean energy fluctuation, improving trading frequency and reduce transaction period. This article puts up with an inter-province power market trading space calculation method to calculate the available power transmission ability of inter-provincial transmission channel, discovering transmission channel and releasing transaction space. Besides, for certain transmission channel or supply-demand province’s electricity requirements, the calculation method can explore the trading market space, organizing clean energy evacuation to improve transmission channel utilization and safety checking pass rates, reducing blocking

Automatic Concrete Sidewalk Deficiency Detection and Mapping with Deep Learning

Vertical displacement is a common concrete slab sidewalk deficiency, which may cause trip hazards and reduce wheelchair accessibility. This paper presents an automatic approach for trip hazard detection and mapping based on deep learning. A low-cost mobile LiDAR scanner was used to obtain full-width as-is conditions of sidewalks, after which a method was developed to convert the scanned 3D point clouds into 2D RGB orthoimages and elevation images. Then, a deep learning-based model was developed for pixelwise segmentation of concrete slab joints. Algorithms were developed to extract different types of joints of straight and curved sidewalks from the segmented images. Vertical displacement was evaluated by measuring elevation differences of adjacent concrete slab edges parallel to the boundaries of joints, based on which potential trip hazards were identified. In the end, the detected trip hazards and normal sidewalk joints were geo-visualized with specific information on Web GIS. Experiments demonstrated the proposed approach performed well for segmenting joints from images, with a highest segmentation IoU (Intersection over Union) of 0.88, and achieved similar results compared with manual assessment for detecting and mapping trip hazards but with a higher efficiency. The developed approach is cost- and time-effective, which is expected to enhance sidewalk assessment and improve sidewalk safety for the general public