Addressing Challenges in Port Depth Analysis: Integrating Machine Learning and Spatial Information for Accurate Remote Sensing of Turbid Waters.

Bathymetry estimation is essential for various applications in port management, navigation safety, marine engineering, and environmental monitoring. Satellite remote sensing data can rapidly acquire the bathymetry of the target shallow waters, and researchers have developed various models to invert the water depth from the satellite data. Geographically weighted regression (GWR) is a common method for satellite-based bathymetry estimation. However, in sediment-laden water environments, especially ports, the suspended materials significantly affect the performance of GWR for depth inversion. This study proposes a novel approach that integrates GWR with Random Forest (RF) techniques, using longitude, latitude, and multispectral remote sensing reflectance as input variables. This approach effectively addresses the challenge of estimating bathymetry in turbid waters by considering the strong correlation between water depth and geographical location. The proposed method not only overcomes the limitations of turbid waters but also improves the accuracy of depth inversion results in such complex aquatic settings. This breakthrough in modeling has significant implications for turbid waters, enhancing port management, navigational safety, and environmental monitoring in sediment-laden maritime zones.

Research on Bathymetric Inversion Capability of Different Multispectral Remote Sensing Images in Seaports.

In recent years, remote sensing has become an indispensable supplementary method for determining water depth in the seaports. At present, many scholars use multi-spectral satellite data to invert the water depth of the seaports, but how to select the appropriate satellite data in the seaports area is worth exploring. In this article, the differences in the retrieving ability between domestic and foreign multispectral images are compared, through building the random forest model and the band ratio model, which use different multispectral images to conduct retrieving water depth in Nanshan Port in conjunction with the WBMS multi-beam sounding system. The band ratio model and random forest model are chosen for water depth exploration, remote sensing images use GF-6, GF-2, Sentinel-2B, and Landsat 8 OLI data, which are all popular and easily accessible. The final experiment results from the constant adjustment of the model parameter show that the domestic series of GF-6 images performed the best in this experiment. The Root Mean Square Error (RMSE) and Mean Relative Error (MRE) of the random forest model are only 1.202 and 0.187, respectively. Simultaneously, it is discovered that the 'Red Edge' band of GF-6 is also very helpful in improving the accuracy of water depth inversion, which is rarely mentioned in previous studies. To some extent, the preceding studies demonstrate that it is possible to investigate water depth using common multispectral remote sensing images. In the case of some bathymetry inversion models or in some waters, the aforementioned study demonstrates that it is possible to examine the water depth using domestic remote sensing images that are superior to foreign multispectral images in terms of bathymetry inversion ability.

Text Sentiment Classification Based on BERT Embedding and Sliced Multi-Head Self-Attention Bi-GRU.

In the task of text sentiment analysis, the main problem that we face is that the traditional word vectors represent lack of polysemy, the Recurrent Neural Network cannot be trained in parallel, and the classification accuracy is not high. We propose a sentiment classification model based on the proposed Sliced Bidirectional Gated Recurrent Unit (Sliced Bi-GRU), Multi-head Self-Attention mechanism, and Bidirectional Encoder Representations from Transformers embedding. First, the word vector representation obtained by the BERT pre-trained language model is used as the embedding layer of the neural network. Then the input sequence is sliced into subsequences of equal length. And the Bi-sequence Gated Recurrent Unit is applied to extract the subsequent feature information. The relationship between words is learned sequentially via the Multi-head Self-attention mechanism. Finally, the emotional tendency of the text is output by the Softmax function. Experiments show that the classification accuracy of this model on the Yelp 2015 dataset and the Amazon dataset is 74.37% and 62.57%, respectively. And the training speed of the model is better than most existing models, which verifies the effectiveness of the model.

Satellite-derived bathymetry based on machine learning models and an updated quasi-analytical algorithm approach.

Retrieving the water depth by satellite is a rapid and effective method for obtaining underwater terrain. In the optical shallow waters, the bottom signal has a great impact on the radiation from the water which related to water depth. In the optical shallow waters, the spatial distribution characteristic of water quality parameters derived by the updated quasi analysis algorithm (UQAA) is highly correlated with the bottom brightness. Because the bottom reflection signal is strongly correlated with the spatial distribution of water depth, the derived water quality parameters may helpful and applicable for optical remote sensing based satellite derived bathymetry. Therefore, the influence on bathymetry retrieval of the UQAA IOPs is worth discussing. In this article, different machine learning algorithms using a UQAA were tested and remote sensing reflectance at water depth in situ points and their detection accuracy were evaluated by using Worldwiew-2 multispectral remote sensing images and laser measurement data. A backpropagation (BP) neural network, extreme value learning machine (ELM), random forest (RF), Adaboost, and support vector regression (SVR) machine models were utilized to compute the water depth retrieval of Ganquan Island in the South China Sea. According to the obtained results, bathymetry using the UQAA and remote sensing reflectance is better than that computed using only remote sensing reflectance, in which the overall improvements in the root mean square error (RMSE) were 1 cm to 5 cm and the overall improvement in the mean relative error (MRE) was 1% to 5%. The results showed that the results of the UQAA could be used as a main water depth estimation eigenvalue to increase water depth estimation accuracy.

Promoter Methylation-Regulated miR-145-5p Inhibits Laryngeal Squamous Cell Carcinoma Progression by Targeting FSCN1.

Laryngeal squamous cell carcinoma (LSCC) is a common form of head and neck cancer with poor prognosis. However, the mechanism underlying the pathogenesis of LSCC remains unclear. Here, we demonstrated increased expression of fascin actin-bundling protein 1 (FSCN1) and decreased expression of microRNA-145-5p (miR-145-5p) in a clinical cohort of LSCC. Luciferase assay revealed that miR-145-5p is a negative regulator of FSCN1. Importantly, low miR-145-5p expression was correlated with TNM (tumor, node, metastasis) status and metastasis. Moreover, cases with low miR-145-5p/high FSCN1 expression showed poor prognosis, and these characteristics together served as independent prognostic indicators of survival. Gain- and loss-of-function studies showed that miR-145-5p overexpression or FSCN1 knockdown inhibited LSCC migration, invasion, and growth by suppressing the epithelial-mesenchymal transition along with inducing cell-cycle arrest and apoptosis. Additionally, hypermethylation of the miR-145-5p promoter suggested that repression of miR-145-5p arises through epigenetic inactivation. LSCC tumor growth in vivo could be inhibited by using miR-145-5p agomir or FSCN1 small interfering RNA (siRNA), which highlights the potential for clinical translation. Collectively, our findings indicate that miR-145-5p plays critical roles in inhibiting the progression of LSCC by suppressing FSCN1. Both miR-145-5p and FSCN1 are important potential prognostic markers and therapeutic targets for LSCC.

Dysregulation of DNA methylation and expression of imprinted genes in mouse placentas of fetal growth restriction induced by maternal cadmium exposure.

Cadmium (Cd) is one of the most toxic environmental pollutants that cause fetal malformation and growth restriction. However, the molecular mechanisms underlying maternal Cd toxicity on fetal growth remain largely unknown. Specifically, the expression profiles and the regulation mechanisms of the imprinted genes, have been poorly characterized in the etiology of Cd-induced fetal growth restriction (FGR). In the present study, 13 imprinted genes associated with the fetal growth and placenta development were selected and their expression patterns were examined in the Cd-exposed placentas. Quantitative real-time PCR and western blot results showed that the maternally expressed gene, Cyclin dependent kinase inhibitor 1c (Cdkn1c), and paternally expressed gene, Paternally expressed gene 10 (Peg10), were significantly upregulated and downregulated respectively in the Cd-exposed placentas when compared to the normal ones respectively. Moreover, data from bisulfate PCR demonstrated the changes of the methylation levels of the promoter regions of Cdkn1c and Peg10 in the Cd-exposed placentas. In addition, the expression profile of Cdkn1c was correlated with the methylation levels of site 2 (-837--692) but not site 1 (-389--185) of its promoter region. Therefore, our results suggest that changes of the DNA methylation levels of the promoter regions and the expression patterns of Cdkn1c and Peg10 may be involved in the etiology of Cd-induced fetal growth restriction.

[Clinical effects of different therapeutic regimens for Helicobacter pylori infection in children].

OBJECTIVE: To investigate the clinical effects of sequential therapy, triple therapy, sequential therapy combined with Lactobacillus, and triple therapy combined with Lactobacillus in the eradication of Helicobacter pylori (H.pylori) infection in children. METHODS: A total of 416 children with H.pylori infection were randomly assigned to sequential group (102 children), triple group (100 children), sequential-Lactobacillus group (109 children), and triple-Lactobacillus group (105 children). The clinical outcome, H.pylori eradication rate, cost-effect ratio, and incidence of adverse events were compared between the four groups. RESULTS: The sequential-Lactobacillus and triple-Lactobacillus groups had significantly better clinical outcomes than the sequential group and the triple group (P<0.05). The sequential-Lactobacillus group had the highest marked response rate, followed by the triple-Lactobacillus group. The triple group had the lowest marked response rate. The sequential-Lactobacillus group also had the highest H.pylori eradication rate, followed by the triple-Lactobacillus group. The triple group had the lowest H.pylori eradication rate (P<0.05). The sequential group had the lowest cost-effect ratio, followed by the sequential-Lactobacillus group. The triple group had the highest cost-effect ratio (P<0.01). The sequential-Lactobacillus group had the lowest incidence rate of adverse events, followed by the triple-Lactobacillus group. The triple group had the highest incidence rate. CONCLUSIONS: Sequential therapy combined with Lactobacillus seems to be the best regimen for the eradication of H.pylori infection in children.

Epigenetic regulation of placental glucose transporters mediates maternal cadmium-induced fetal growth restriction.

Cadmium (Cd) is one of the most toxic environmental pollutants that cause fetal malformation and growth restriction. However, the molecular mechanisms underlying maternal Cd toxicity on fetal growth remain largely unknown. Specifically, the role of placental nutrient transporters, including glucose transporters (GLUTs), has been poorly characterized in the etiology of Cd-induced fetal growth restriction (FGR). In the present study, we established a murine model of FGR induced by maternal Cd exposure, and examined the toxic effects of Cd on placental GLUTs. Our results showed that GLUT3 is significantly downregulated in Cd-exposed mouse placentas when compared to the normal ones. Data from bisulfite PCR demonstrated the hypermethylation of the promoter region of GLUT3. However, methylation levels remained unchanged in two major repetitive elements (LINE-1 and IAP) in Cd-exposed placentas. Moreover, DNA methyltransferase (DNMT) 3B and DNMT3L were significantly upregulated in Cd-exposed placentas, and there were no expression changes of DNMT1 and DNMT3A. Collectively, our results suggest that changes in DNMT3B and DNMT3L expressions and site-specific DNA methylation may be involved in the etiology of Cd-induced fetal growth restriction through downregulation of GLUT3.

[Emergency repair of skin and soft tissue defects of lower limbs with island fasciocutaneous flap supplied by superficial sural artery].

OBJECTIVE: To find a better method of emergency repair of skin and soft tissue defects in the lower leg, ankle and foot. METHODS: The distally based superficial sural artery flap was designed on the posterior aspect of the leg. From February 2000 to December 2003, 18 patients with skin and soft tissue detects of the lower leg, ankle and foot were treated with island fasciocutaneous flap supplied by superficial sural artery by emergency. The size of the flap ranged form 4 cm x 5 cm to 11 cm x 12 cm. RESULTS: The flaps survived totally in 16 cases and necrosed partially in 2 cases. After 1-2 year postoperative follow-up, the results were satisfactory except that in 2 flaps. CONCLUSION: The island fasciocutaneous flap supplied by superficial sural artery may provide a useful method for emergency repair of soft tissue defect of the lower limbs.