Deep-Sea Biological Detection Method Based on Lightweight YOLOv5n.

Deep-sea biological detection is essential for deep-sea resource research and conservation. However, due to the poor image quality and insufficient image samples in the complex deep-sea imaging environment, resulting in poor detection results. Furthermore, most existing detection models accomplish high precision at the expense of increased complexity, and leading cannot be well deployed in the deep-sea environment. To alleviate these problems, a detection method for deep-sea organisms based on lightweight YOLOv5n is proposed. First, a lightweight YOLOv5n is created. The proposed image enhancement method based on global and local contrast fusion (GLCF) is introduced into the input layer of YOLOv5n to address the problem of color deviation and low contrast in the image. At the same time, a Bottleneck based on the Ghost module and simAM (GS-Bottleneck) is developed to achieve a lightweight model while ensuring sure detection performance. Second, a transfer learning strategy combined with knowledge distillation (TLKD) is designed, which can reduce the dependence of the model on the amount of data and improve the generalization ability to enhance detection accuracy. Experimental results on the deep-sea biological dataset show that the proposed method achieves good detection accuracy and speed, outperforming existing methods.

Experimental Study of Deep Submersible Structure Defect Monitoring Based on Flexible Interdigital Transducer Surface Acoustic Wave Technology.

In view of the shortage of structural defect monitoring methods for deep submersibles, numerical simulation and experimental research on underwater SAW propagation based on interdigital transducers are carried out in this paper. PVDF interdigital transducer (PVDF-IDT) has shown considerable potential in the application of structural health monitoring because of its micro size, soft material characteristics, and the characteristics of long-term bonding on the surface of the tested structure. In order to realize the application of IDT on submersible or underwater structures, it is necessary to understand the influence of underwater environment on IDTs with different structures. The underwater attenuation of IDT with 2-5 mm wavelength and the underwater attenuation of Lamb (A0 mode) wave on a 4 mm thick titanium alloy plate is obtained through COMSOL software simulation. The experimental verification shows that the simulation results match with the actual situation, which proves that COMSOL software can accurately calculate the acoustic attenuation of surface waves at the solid-liquid interface. At the same time, the underwater attenuation of IDT with different structures is very different, providing important design parameters for the underwater interdigital transducer. In this paper, it is found that the Lamb wave has significant advantages over the Rayleigh wave in the health monitoring of underwater thin plate structures.

An Online Active Broad Learning Approach for Real-Time Safety Assessment of Dynamic Systems in Nonstationary Environments.

Real-time safety assessment of the complex dynamic systems in nonstationary environments is of great significance for avoiding the potential hazards. In this case, the update procedure with high assessment accuracy and training speed is crucial and meaningful in the dynamic streaming setting. Generally, the performance of most online learning approaches will be negatively affected by limited annotated samples in such a setting. Moreover, the time cost of advanced conventional methods with retaining procedures is relatively high, constraining their practicality. In this article, a novel online active broad learning approach, termed OABL, is proposed. In detail, the effectiveness of the broad learning system in the framework of online active learning is first revealed and verified. A reasonable dynamic asymmetric query strategy is then designed with a limited annotation budget to actively annotate the relatively valuable samples, which is beneficial to mitigating the negative effects of class imbalance. In this context, the advantage of the human-in-the-loop characteristic is also effectively used to control the evolution direction of the learner during the incremental update, which makes it better able to adapt to complex and nonstationary environments. Several related experiments are conducted with the realistic data of JiaoLong deep-sea manned submersible. Results show the effectiveness and practicality of the proposal compared with the existing advanced approaches.

The Mutation Analysis of the AMT Gene in a Chinese Family With Nonketotic Hyperglycinemia.

Background: Nonketotic hyperglycinemia is a metabolic disease with autosomal recessive inheritance due to the glycine cleavage system (GCS) defect leading to the accumulation of glycine that causes severe and fatal neurological symptoms in the neonatal period. Methods: Genomic DNA was extracted from the peripheral blood of the female proband and her family members. The AMT variation was detected in the patient by whole-exome sequencing (WES), and the variant was validated by Sanger sequencing. Results: The WES showed that there were novel compound heterozygous frameshift variations c.977delA (p.Glu326Glyfs*12) and c.982_983insG (p.Ala328Glyfs*22) in exon eight of the AMT gene (NM_000481.4) in the proband. Genetic analysis showed that the former was inherited from the mother, and the latter was inherited from the father. Conclusion: We report the novel compound heterozygous variation of the AMT gene in a Chinese girl with NKH by WES, which has never been reported previously. Our case expanded the AMT gene mutation spectrum, further strengthened the understanding of NKH, and deepened the genetic and clinical heterogeneity of the disease. However, the study of treatment and prognosis is still our future challenge and focus.

Detection of the Deep-Sea Plankton Community in Marine Ecosystem with Underwater Robotic Platform.

Variations in the quantity of plankton impact the entire marine ecosystem. It is of great significance to accurately assess the dynamic evolution of the plankton for monitoring the marine environment and global climate change. In this paper, a novel method is introduced for deep-sea plankton community detection in marine ecosystem using an underwater robotic platform. The videos were sampled at a distance of 1.5 m from the ocean floor, with a focal length of 1.5-2.5 m. The optical flow field is used to detect plankton community. We showed that for each of the moving plankton that do not overlap in space in two consecutive video frames, the time gradient of the spatial position of the plankton are opposite to each other in two consecutive optical flow fields. Further, the lateral and vertical gradients have the same value and orientation in two consecutive optical flow fields. Accordingly, moving plankton can be accurately detected under the complex dynamic background in the deep-sea environment. Experimental comparison with manual ground-truth fully validated the efficacy of the proposed methodology, which outperforms six state-of-the-art approaches.

Altered Gene Expression in the Testis of Infertile Patients with Nonobstructive Azoospermia.

BACKGROUND: The molecular mechanism of nonobstructive azoospermia (NOA) remains unclear. The aim of this study was to identify gene expression changes in NOA patients and to explore potential biomarkers and therapeutic targets. METHODS: The gene expression profiles of GSE45885 and GSE145467 were collected from the Gene Expression Omnibus (GEO) database, and the differences between NOA and normal spermatogenesis were analyzed. Enrichment analysis was performed to explore biological functions for common differentially expressed genes (DEGs) in GSE45885 and GSE145467. Coexpression analysis of DEGs in GSE45885 was performed, and two modules with the highest correlation with NOA were screened. Key genes were then screened from the intersection genes of the two modules and common DEGs and PPI network. The expression of key genes was validated by quantitative real-time polymerase chain reaction (qRT-PCR) experiments. Finally, through miRTarBase, miRDB, and RAID, the miRNAs were predicted to regulate key genes, respectively. RESULTS: A total of 345 common DEGs were identified and they were mainly related to spermatogenesis, insulin signaling pathway. Coexpression analysis of DEGs in GSE45885 yielded eight modules; MEblack and MEturquoise had the highest correlation with NOA. Six genes in MEturquoise and RNF141 in MEblack were identified as key genes. qRT-PCR experiments validated the differential expression of key genes between NOA and control. Furthermore, RNF141 was regulated by the largest number of miRNAs. CONCLUSION: Our findings suggest that the significant change expression of key genes may be potential markers and therapeutic targets of NOA and may have some impact on the development of NOA.

A High-Dimensional and Small-Sample Submersible Fault Detection Method Based on Feature Selection and Data Augmentation.

The fault detection of manned submersibles plays a very important role in protecting the safety of submersible equipment and personnel. However, the diving sensor data is scarce and high-dimensional, so this paper proposes a submersible fault detection method, which is made up of feature selection module based on hierarchical clustering and Autoencoder (AE), the improved Deep Convolutional Generative Adversarial Networks (DCGAN)-based data augmentation module and fault detection module using Convolutional Neural Network (CNN) with LeNet-5 structure. First, feature selection is developed to select the features that have a strong correlation with failure event. Second, data augmentation model is conducted to generate sufficient data for training the CNN model, including rough data generation and data refiners. Finally, a fault detection framework with LeNet-5 is trained and fine-tuned by synthetic data, and tested using real data. Experiment results based on sensor data from submersible hydraulic system demonstrate that our proposed method can successfully detect the fault samples. The detection accuracy of proposed method can reach 97% and our method significantly outperforms other classic detection algorithms.

Underwater Hyperspectral Imaging Technology and Its Applications for Detecting and Mapping the Seafloor: A Review.

Common methods of ocean remote sensing and seafloor surveying are mainly carried out by airborne and spaceborne hyperspectral imagers. However, the water column hinders the propagation of sunlight to deeper areas, thus limiting the scope of observation. As an emerging technology, underwater hyperspectral imaging (UHI) is an extension of hyperspectral imaging technology in air conditions, and is undergoing rapid development for applications in shallow and deep-sea environments. It is a close-range, high-resolution approach for detecting and mapping the seafloor. In this paper, we focus on the concepts of UHI technology, covering imaging systems and the correction methods of eliminating the water column's influence. The current applications of UHI, such as deep-sea mineral exploration, benthic habitat mapping, and underwater archaeology, are highlighted to show the potential of this technology. This review can provide an introduction and overview for those working in the field and offer a reference for those searching for literature on UHI technology.

Factors influencing postoperative outcomes in patients with symptomatic discoid lateral meniscus.

BACKGROUND: Due to its abnormal morphology and ultrastructure, discoid lateral meniscus (DLM) is prone to tear and degeneration, leading to clinical symptoms. Arthroscopy is the main treatment for symptomatic DLM; however, postoperative outcomes vary widely due to the effects of diverse factors. This research aims to explore the factors influencing postoperative outcomes of symptomatic DLM. METHODS: Patients with DLM who underwent arthroscopic surgery at our hospital from 9/2008 to 9/2015 were enrolled according to the inclusion and exclusion criteria. Fourteen variables, including sex, body mass index (BMI) and other variables, were chosen as factors for study. Knee function was assessed using the International Knee Documentation Committee (IKDC) score. Univariate analyses (Mann-Whitney U test or Kruskall-Wallis rank sum test) and multivariate analyses (ordinal logistic regression) were used to identify the factors that influenced postoperative outcomes. P < 0.05 was considered statistically significant. RESULTS: A total of 502 patients, including 353 females (70.3%) and 149 males (29.7%), were enrolled. The median IKDC score postoperatively (87.4; range, 41.4 ~ 97.7; IQR, 14.6) was higher than that preoperatively (57.6; range, 26.9 ~ 64.9; IQR, 9.7) (P < 0.001). Male sex was predictive of a higher IKDC score (P = 0.023, OR = 1.702). Compared with BMI ≥25 kg/m2, < 18.5 kg/m2 was associated with better IKDC score (P = 0.026, OR = 3.016). Contrasting with age of onset ≥45 years, ≤14 years (P < 0.001, OR = 20.780) and 14 ~ 25 years (P < 0.001, OR = 8.516) were associated with better IKDC score. In comparison with symptoms duration> 24 months, IKDC scores for patients with symptoms duration ≤1 month (P = 0.001, OR = 3.511), 1 ~ 6 months (P < 0.001, OR = 3.463) and 6 ~ 24 months (P < 0.001, OR = 3.254) were significantly elevated. Compared to Outerbridge grade III ~ IV, no injury (P < 0.001, OR = 6.379) and grade I (P = 0.01, OR = 4.332) were associated with higher IKDC score. CONCLUSIONS: Arthroscopic treatment of symptomatic DLM is safe and effective, but its clinical efficacy is affected by many factors. Specifically, male sex, BMI < 18.5 kg/m2, age of onset < 25 years (especially < 14 years) and symptoms duration < 24 months are conducive to good postoperative outcomes. However, combined articular cartilage injury (Outbridge grade ≥ 2) reduces postoperative effect.

Continuous nerve block versus single-shot nerve block for total knee arthroplasty: a meta-analysis from randomized controlled trials.

INTRODUCTION: This meta-analysis aims to determine whether continuous nerve block (CNB) provides better pain relief and functional recovery than single-shot nerve block (SSNB) after total knee arthroplasty (TKA). EVIDENCE ACQUISITION: Embase, PubMed, and the Cochrane Library databases were comprehensively searched. Randomized controlled trials (RCTs) with a modified Jadad Score ≥4 comparing CNB with SSNB in patients after TKA were enrolled in our meta-analysis. The primary outcomes were visual analogue scale (VAS) pain score and morphine consumption. The secondary outcomes were distance able to ambulate, complications and length of hospital stay. Review Manager 5.3 for Windows was used to analyze the extracted data. EVIDENCE SYNTHESIS: Two RCTs that compared continuous adductor canal block (ACB) with single-shot ACB, and four RCTs that compared continuous femoral nerve block (FNB) with single-shot FNB were included in our meta-analysis. There were no significant differences in VAS scores at rest for 12 hours (P=0.44), 24 hours (P=0.15) and 48 hours (P=0.16) postoperatively, VAS scores on activity for 24 hours (P=0.15) and 48 hours (P=0.23), total opioid consumption at 12 hours (P=0.20), 24 hours (P=0.25) and 48 hours (P=0.41), distance walked at 24 hours (P=0.58) and 48 hours (P=0.93), nausea and vomiting at 24 hours (P=0.18) and 48 hours (P=0.62), and length of hospital stay (P=0.71) between the CNB and SSNB groups. CONCLUSIONS: CNB and SSNB have similar effects on pain relief, complications and functional recovery in patients receiving TKA. The optimal analgesic regimen for patients after TKA needs further identification.

Lycium barbarum polysaccharides protect human trophoblast HTR8/SVneo cells from hydrogen peroxide­induced oxidative stress and apoptosis.

Pregnancy complications are associated with abnormal cytotrophoblast differentiation and invasion. Hydrogen peroxide (H2O2) is an important mediator of oxidative ischemia/reperfusion stress in the placenta. Lycium barbarum polysaccharides (LBP) have been demonstrated to counteract oxidative free radicals. The effects of LBP in trophoblast HTR8/SVneo cells injured with H2O2 were examined. A cell counting kit­8 assay was performed to detect the effect of LBP at different concentrations on the proliferative ability of H2O2 injured trophoblast cells. Flow cytometry was used to determine the levels of reactive oxygen species (ROS), mitochondria membrane potential (MMP) disruption and apoptosis. Superoxide dismutase (SOD) activity and lactate dehydrogenase (LDH) leakage into the supernatant was detected by ultraviolet spectrophotometry. Reverse transcription­quantitative polymerase chain reaction and western blot analysis were performed to detect the expression of apoptosis­associated factors, including survivin, hypoxia inducible factor 1­α (HIF1­α), Bcl­2 apoptosis regulator (Bcl­2), Bcl­2 associated X apoptosis regulator (Bax). The results revealed that LBP protected the proliferative ability of trophoblast cells injured with H2O2 in a dose­dependent manner. LBP inhibited the oxidative stress induced by H2O2, by reducing ROS and LDH levels and increasing SOD activity. Additionally, LBP decreased MMP disruption and cell apoptosis induced by H2O2, by increasing the mRNA and protein expression of survivin, HIF1­α and Bcl­2 and decreasing Bax expression. Therefore, it was concluded that LBP protected human trophoblast cells from H2O2­induced oxidative stress and cell apoptosis via regulation of apoptosis­associated factor expression. It will provide a novel strategy for the treatment of pregnancy complications.

A new species of the thorid genus Paralebbeus Bruce & Chace, 1986 (Crustacea: Decapoda: Caridea) from the deep sea of the Northwestern Pacific Ocean.

During recent dives by the Chinese manned submersible "Jiaolong", some shrimp specimens were sampled from the deep sea of the Northwestern Pacific Ocean. A new species of the caridean family Thoridae, Paralebbeus jiaolongi sp. nov., is described and illustrated in this study. The rostrum armed with only one subterminal ventral tooth can easily distinguish the new species from its congeners.

Effect of overpasses in the Biham-Middleton-Levine traffic flow model with random and parallel update rule.

The effect of overpasses in the Biham-Middleton-Levine traffic flow model with random and parallel update rules has been studied. An overpass is a site that can be occupied simultaneously by an eastbound car and a northbound one. Under periodic boundary conditions, both self-organized and random patterns are observed in the free-flowing phase of the parallel update model, while only the random pattern is observed in the random update model. We have developed mean-field analysis for the moving phase of the random update model, which agrees with the simulation results well. An intermediate phase is observed in which some cars could pass through the jamming cluster due to the existence of free paths in the random update model. Two intermediate states are observed in the parallel update model, which have been ignored in previous studies. The intermediate phases in which the jamming skeleton is only oriented along the diagonal line in both models have been analyzed, with the analyses agreeing well with the simulation results. With the increase of overpass ratio, the jamming phase and the intermediate phases disappear in succession for both models. Under open boundary conditions, the system exhibits only two phases when the ratio of overpasses is below a threshold in the random update model. When the ratio of the overpass is close to 1, three phases could be observed, similar to the totally asymmetric simple exclusion process model. The dependence of the average velocity, the density, and the flow rate on the injection probability in the moving phase has also been obtained through mean-field analysis. The results of the parallel model under open boundary conditions are similar to that of the random update model.

Phase diagrams of the Katz-Lebowitz-Spohn process on lattices with a junction.

This paper studies the Katz-Lebowitz-Spohn (KLS) process on lattices with a junction, where particles move on parallel lattice branches that combine into a single lattice at the junction. It is shown that 11 kinds of phase diagrams could be observed, depending on the two parameters ε and δ in the KLS process. We have investigated the phase diagrams as well as bulk density analytically based on flow rate conservation and the extremal current principle. Extensive Monte Carlo computer simulations are performed, and it is found that they are in excellent agreement with theoretical prediction.

Dynamical traffic light strategy in the Biham-Middleton-Levine model.

In this paper, we study dynamical traffic light strategies in the Biham-Middleton-Levine traffic flow model. The strategies use local vehicular information to control urban traffic, which take into account the interaction of vehicles traveling in different directions via considering their dynamical spatial configuration. Simulations find out two strategies, in which local information at nearby sites is used. The two strategies perform much better than the alternating strategy. Under these two strategies, vehicles can self-organize into a new intermediate state with band structure. The analytical solutions of velocity of this state have been presented, which are in good agreement with simulations.

Traffic flow in the Biham-Middleton-Levine model with random update rule.

A stochastic version of the Biham-Middleton-Levine model with random update rule is studied. It is shown that under periodic boundary condition, the system exhibits a sharp transition from moving phase to jamming phase. Under open boundary condition, the coexistence of moving phase and jamming phase can be observed. We have presented a mean-field analysis for the moving phase, which successfully takes into account the correlation and produces good agreement with simulation results.