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With the problem of nuclear leakage being concerned by more and more industries, the research of coastal ecological environment monitoring has become more and more important. Therefore, it is necessary to study the current unsystematic coastal ecological environment monitoring and protection system. Aiming at the accuracy of feature fusion and representation of single short environment information, this paper compares the classification effects of the three fusion methods on four classifiers: logistic regression, SVM, random forest, and naive Bayes, to verify the effectiveness of LDA and DS model fusion and determine the consistency vector representation method of short environment information data. This paper collects and analyzes the coastal data in recent years using multisource information fusion decision-making. In this paper, DS (Dempster Shafer) evidence algorithm is used to collect the data of coastal salinization degree and air relative humidity, and then, the DS feature matching model is introduced to fuse the whole index system. The method in the article completes the standardized and standardized processing of monitoring data digital conversion, quality control, and data classification, forms interrelated four-dimensional spatiotemporal data, and establishes a distributed, object-oriented, Internet-oriented dynamic management real-time and delayed database. Finally, this paper carries out tree decision processing on the coastal ecological environment monitoring data of multisource information fusion, to achieve the extraction and intuitive analysis of special data, and puts forward targeted protection strategies for the coastal ecological environment according to the data results of the DS algorithm. The research shows that the number of indicators in multisource information fusion in this paper is 16, a total of 3251 data, 2866 meaningful information, and 1869 data including ecological cycle. These data are the results of the collection of multi-information data. Based on the multilevel nature of the existing marine environment three-dimensional monitoring system, the study established a comprehensive resource-guaranteed framework and divided it into four levels according to the level of the marine monitoring system: country, sea area, locality, and data access point. In specific analysis, the guarantee resources involved in each level are introduced. On the basis of in-depth analysis of the requirements of the marine environment three-dimensional monitoring system operation guarantee and the guarantee resource structure, the marine environment three-dimensional monitoring operation comprehensive guarantee system is described from the internal structure and the external connection. The DS algorithm extracts the status information resources of various marine environment three-dimensional monitoring systems, through the interaction of various subsystems, realizes the operation and maintenance of the monitoring system, and provides various technical supports such as system evaluation and failure analysis. After multisource information fusion and decision-making, it is obtained that the index equilibrium module in the DS algorithm in this paper is 0.52, the sensitivity is 0.68, and the independence is 0.42. Among them, the range of sensitivity is the largest. In the simulation results, the eco-economic coefficient can be increased from 12% to 36%. Therefore, using the method of multisource information fusion for quantitative index analysis can provide data support for coastal ecological environment detection, to establish a more perfect protection system.

Post-marketing surveillance of antineoplastic agents is performed to evaluate the efficacy and safety in patients aiming at expanding drug indications and discovering potential adverse events. The real-world data is fraught with missing values. Literature addressing different strategies for dealing with missing data in such a situation is scarce. Using machine learning (ML) algorithms for predicting therapeutic outcomes of PD-1/PD-L1 Inhibitors has attracted attention. However, training a predictive model usually requires imaging or biomarker information, which is rarely available in the post-marketing surveillance data. To address these challenges, we propose an ML-aided framework to predict the outcomes of Anti-PD-1 therapy for gynecological malignancy on a dataset with 117 patient samples, treated by Camrelizumab (with 50 patient samples), Sintilimab (44), and Toripalimab (23). Four therapeutic outcomes, including Response Evaluation Criteria in Solid Tumours (RECIST), organ adverse effect (AE), general AE, and death, are predicted. The proposed framework feeds the dataset into a learning pipeline consisting of imputation, feature engineering, model training, ensemble learning, and model selection to generate the final predictive model. We conduct experiments to justify several critical design choices, such as the specific feature engineering strategies and the SMOTE over-sampling technique. The final model for each learning task is selected from a large pool of model candidates based on a joint consideration of accuracy and F1. Moreover, we conduct thorough and visualized model analysis and gain a deeper understanding of model behavior and feature importance. The results, analysis, and findings demonstrate the superiority of the proposed learning-aided framework.

Based on the coherence theory for non-stationary optical fields, we introduce a new class of partially coherent pulse sources with multi-cosine-Gaussian correlated Schell-model (MCGCSM) and derive the analytic expression for the temporally mutual coherence function (TMCF) of an MCGCSM pulse beam when it propagates through dispersive media. The temporally average intensity (TAI) and the temporal degree of coherence (TDOC) of the MCGCSM pulse beams spreading in dispersive media are investigated numerically, respectively. Our results show that over propagation distance, the evolution of pulse beams is from the primary single beam into multiple subpulses or form flat-topped TAI distributions by controlling source parameters. Moreover, when the chirp coefficient s

An ultra-high sensitivity photonic crystal fiber mid-infrared refractive index (RI) sensor based on surface plasmon resonance is proposed, whose properties are investigated by the finite element method. Gold can be utilized to create excitation between the fundamental mode and surface plasmon polaritons mode. The simulation results indicate that, at the wavelength of 1.7–4.0 μm, the proposed sensor could detect a RI in the range of 1.00–1.31, a maximum sensitivity of 37 000 nm RIU−1, and an optimal resolution of 2.70 × 10−6 RIU is achieved. The result of curve fitting is 0.98185. The proposed mid-infrared RI sensor plays an important role in organic chemistry detection, medical detection, and related fields.

A novel concave-shaped photonic crystal fiber sensor with double loss peaks based on surface plasmon resonance is proposed, whose properties are investigated by the finite element method. Gold can be utilized to generate excitation between the core mode and surface plasmon polariton mode. The simulation results indicate that in the wavelength range of 1.2 to 2.2 μm, the proposed sensor could detect the refractive index (RI) in the range of 1.18–1.30, the wavelength sensitivity of the primary loss peak could reach up to 18 000 nm/RIU and the corresponding resolution is 5.56 × 10−6 RIU in the RI range from 1.26 to 1.27. In addition, the double loss peaks could improve the detection accuracy, and the trough wavelength variation range is small, indicating that the proposed sensor is relatively stable, which improves the practicability of the sensor. This work could have a wide application value in the detection of medical testing, biomolecules, and organic chemistry.

In recent years, "big data (BD)" has become a realistic background that we cannot ignore, and it is closely related to all aspects of people's survival and life. The combination of ideological and political education (IAPE) and BD in colleges and universities has provided a brand new opportunity for the cultural development of IAPE in our country, and it has also brought numerous challenges. Therefore, how colleges and universities innovate in the development of IAPE and culture in the context of the era of BD has become a new topic worthy of our study. The purpose of this article is to study the cultural development of IAPE in the context of BD. This paper analyzes the practical problems of IAPE in universities, can find the specific entry point for BD to serve IAPE in universities, and discover the integration direction and trend of IAPE innovation and BD in universities. Based on the working concept of collaboration, sharing, openness, and equality of IAPE in colleges and universities under the background of BD, this paper proposes specific practical strategies for the reform of IAPE in colleges and universities, namely, exploring the emotional resonance based on data and the construction of personalized education mode and the conduct of implicit education. Based on the questionnaire analysis of the effectiveness of college students (CS)' IAPE from the perspective of BD, this article elaborates on the opportunities and challenges that BD brings to the development of CS' IAPE and culture. The survey research shows that when investigating whether teachers will prepare lessons in advance, only 31.95% of teachers often prepare lessons. This shows that teachers have not studied the new teaching model in depth, and educational resources have not kept up with current political content in time, so that students Don't like to listen to classes.

DNA methylation markers in the peripheral blood are able to be applied to treat epithelial cancer. Nevertheless, the diagnostic potential value of it for ovarian cancer (OV) has not been studied. The study aimed to explore the difference of DNA methylation in peripheral blood between OV patients and healthy women. Firstly, the whole blood of DNA methylation data was provided by the Gene Expression Omnibus (GEO) database. The linear model was applied to the identification of significantly differentially expressed methylated CpG sites (differentially methylation sites [DMP]), and the further screen of co-expression CpG sites (Co-DMP). A total of 2812 DMPs were identified, and weighted gene co-expression network analysis helped to obtain seven co-expression modules. Among them, the yellow module was the most related to OV. Co-DMPs (167) in the yellow module were mainly distributed near the transcription start sites. However, most of them were not in the CpG island. Least absolute shrinkage and selection operator (LASSO) regression analysis was applied to the identification of stable OV-related blood biomarkers that six Co-DMPs (cg00134539, cg00226923, cg25268718, cg25697314, cg25839227, cg26574610) with the highest frequency were found as potential biomarkers. Finally, the diagnostic classifier was established using the support vector machine (SVM) with the accuracy rate of 87.1% and 74.5% in training data set and validation data set, respectively. To sum up, a new feature was provided here for the diagnosis of OV, which is helpful for the diagnosis and individualized treatments of early OV.

Background Ovarian cancer (OC) is the gynecologic cancer with the highest mortality. Circular RNAs (circRNAs) play a vital role in the development and progression of cancer. This study aimed to explore the potential role of circ_0015756 in OC and its molecular mechanism. Methods The levels of circ_0015756, microRNA-942-5p (miR-942-5p) and Cullin 4B (CUL4B) were determined by quantitative real-time PCR (qRT-PCR) or Western blot assay. Cell proliferation, apoptosis, migration and invasion were assessed by Cell Counting Kit-8 (CCK-8), colony formation assay, flow cytometry and transwell assay. The levels of proliferation-related and metastasis-related proteins were measured by Western blot assay. The relationship between miR-942-5p and circ_0015756 or CUL4B was verified by dual-luciferase reporter assay, RNA immunoprecipitation assay and RNA pull-down assay. Xenograft assay was used to analyze tumor growth in vivo. Results Circ_0015756 and CUL4B levels were increased, while miR-942-5p level was decreased in OC tissues and cells. Depletion of circ_0015756 suppressed proliferation, migration and invasion and promoted apoptosis in OC cells. Down-regulation of circ_0015756 hindered OC cell progression via modulating miR-942-5p. Also, up-regulation of miR-942-5p impeded OC cell development by targeting CUL4B. Mechanistically, circ_0015756 up-regulated CUL4B via sponging miR-942-5p. Moreover, circ_0015756 silencing inhibited tumor growth in vivo. Conclusion Knockdown of circ_0015756 suppressed OC progression via regulating miR-942-5p/CUL4B axis, suggesting that circ_0015756 might be a potential therapeutic target for ovarian cancer.

The propagation model of orbital angular momentum (OAM) modes carried by the perfect vortex (pv) beam through anisotropic oceanic turbulence links is established and the factors influencing the OAM propagation are discussed. The findings show that the self-focusing property of pv beams is beneficial to the propagation of OAM modes: a smaller topological charge, a smaller initial radius, and an optimized half-ring width can alleviate degrading effects of turbulence on the pv beam. Additionally, the pv beam with a longer wavelength is more resistant to turbulent interference. The oceanic conditions with a higher dissipation rate of kinetic energy per unit mass of seawater, larger values of anisotropy and inner-scale factor, a smaller temperature–salinity contribution ratio, or a lower mean-squared temperature dissipation rate can improve the signal mode detection probability. The results are expected to further optimize the design of OAM-based underwater wireless communication systems.

We establish the propagation model of orbital angular momentum (OAM) modes carried by hollow vortex Gaussian (hvG) beams propagating in anisotropic atmospheric turbulence. Effects of light source parameters and atmospheric conditions on the OAM mode propagation performance are investigated in detail. The findings indicate the hvG beam with a smaller OAM quantum number, a larger beam order, or a longer source wavelength has more robust resistance to atmospheric turbulence interference. The waist width of the light source has different influences on the OAM mode propagation at different propagation distances. Atmospheric turbulences with larger values of anisotropy, inner-scale factor, non-Kolmogorov power spectrum index, and altitude are favorable for the OAM mode propagation. These research results are conducive to optimizing the design of light sources and space wireless communication systems with hvG beams.

More efficient biomarkers are needed to facilitate the early detection of hepatocellular carcinoma (HCC). We aimed to identify candidate biomarkers for HCC detection by proteomic analysis. First, we performed a global proteomic analysis of 10 paired HCC and non-tumor tissues. Then, we validated the top-ranked proteins by targeted proteomic analyses in another tissue cohort. At last, we used enzyme-linked immunosorbent assays to validate the candidate biomarkers in multiple serum cohorts including HCC cases (HCCs), cirrhosis cases (LCs), and normal controls (NCs). We identified and validated 33 up-regulated proteins in HCC tissues. Among them, eight secretory or membrane proteins were further evaluated in serum, revealing that aldo–keto reductase family 1 member B10 (AKR1B10) and cathepsin A (CTSA) can distinguish HCCs from LCs and NCs. The area under the curves (AUCs) were 0.891 and 0.894 for AKR1B10 and CTSA, respectively, greater than that of alpha-fetoprotein (AFP; 0.831). Notably, combining the three proteins reached an AUC of 0.969, which outperformed AFP alone (P

N6-Methyladenosine (m6A) represents the most prevalent internal modification in mammalian mRNAs. Emerging evidences suggest that m6A modification is profoundly implicated in many biological processes, including cancer development. However, limited knowledge is available about the functional importance of m6A in lung cancer. In this study, by data mining The Cancer Genome Atlas (TCGA) database, we first identified fat mass- and obesity-associated protein (FTO) as a prognostic factor for lung squamous cell carcinoma (LUSC). Then we showed that FTO, but not other m6A modification genes including METTL3, METTL14 and ALKBH5, was the major dysregulated factor responsible for aberrant m6A modification in LUSC. Loss-of-function studies suggested that FTO knockdown effectively inhibited cell proliferation and invasion, while promoted cell apoptosis of L78 and NCI-H520 cells. Furthermore, overexpression of FTO, but not its mutant form, facilitated the malignant phenotypes of CHLH-1 cells. Mechanistically, FTO enhanced MZF1 expression by reducing m6A levels and mRNA stability in MZF1 mRNA transcript, leading to oncogenic functions. Taken together, our study demonstrates the functional importance of FTO in the tumor progression of LUSC and provides a potential therapeutic target for LUSC treatment.

This study evaluated the efficacy of rAd-p53 (Gendicine®) followed by chemotherapy for the treatment of uterine sarcoma. Twelve cases of uterine sarcoma treated at Shengjing Hospital were retrospectively analyzed. Among the 12 patients, one had primary cancer, and 11 had recurrent cancer. For the recurrent cases, the interval between the first operation and diagnosis of recurrence, or progression-free survival time 1 (PFS1), was 1–18 months (median 3 months). All patients were treated with local application of rAd-p53 followed by chemotherapy (local injection of bleomycin and i.v. infusion of cisplatin, epirubicin, and isocyclophosphamide). Efficacy was evaluated, and the rates of complete remission (CR) and partial remission (PR) were calculated. During follow-up, PFS time 2 (PFS2) after the baseline period and overall survival (OS) time after the baseline period of rAd-p53 treatment data were obtained. The treatment resulted in one CR, seven PR, three with stable disease (SD), and one with progressive d...

This study aimed to evaluate the impact of cancer-related mortality on life expectancy in Feicheng City.We extracted the death records and population data of Feicheng City from 2013 to 2018 through the Feicheng Center for Disease Control and Prevention. The mortality, premature mortality, cause-eliminated life expectancy, potential years of life lost (PYLL), average potential years of life lost (APYLL), annual change percentage (APC), and other indicators of cancer were calculated. The age-standardized rates were calculated using the sixth national census (2010).From 2013 to 2018, the mortality rate of cancer in Feicheng City was 221.55/100,000, and the standardized mortality rate was 166.37/100,000. The standardized mortality rate increased from 2013 to 2014 and then decreased annually. The premature mortality of cancer was 8.98% and showed a downward trend (APC = -2.47%, t = -3.10, P = .04). From 2013 to 2018, the average life expectancy of residents in Feicheng City was 78.63 years. Eliminating the impact of cancer, life expectancy could increase by 3.72 years. The rate of life loss caused by cancer in men was higher than that in women. The total life loss caused by cancer deaths was 126,870.50 person-years, the potential life loss rate was 22.51‰, and the average potential life loss was 13.30 years. The standardized potential years of life lost rate showed a downward trend (APC = -2.96%, t = -3.72, P = .02), and APYLL decreased by 1.98% annually (t = -5.44, P = .01). The top 5 malignant tumors in APYLL were leukemia, breast cancer, brain tumor, liver cancer, and ovarian cancer.Lung cancer, esophageal cancer, female breast cancer, and childhood leukemia have a great impact on the life expectancy of residents in Feicheng City. Effective measures need to be taken to reduce the disease burden of malignant tumors.

The spectral reflectivity of the visible light bands of a non-self-illuminating object is one of the root causes of the colour formation of an object, and its uniqueness can be used to distinguish objects. Under low illumination conditions, the ability of the visible light image sensor to capture the colour of an object is greatly reduced. However, the object still has near-infrared radiation. The near-infrared radiation of the object collected by the near-infrared image sensor is combined with the visible light information of the object to improve the colour quality of the acquired object. Since the spectral reflectivity information of an object requires professional equipment to collect, it is inconvenient to use. Aim to more convenient use of spectral information data for colour restoration under low illumination conditions. In this paper, a plant’s spectral reflectivity database in visible and near-infrared bands was proposed. Firstly, 50 plants samples such as ginkgo were collected from 400 nm to 1000 nm spectral reflectivity data by a full-bands hyperspectral sorter and processed by Minimum Noise Fraction (MNF). Secondly, according to the requirements of this database, the business process, function modules and architecture of the database are designed in detail. Finally, according to the design, use C# and SQL Server to establish the database. The establishment of this database provides some data support for colour restoration and other applications.

Background In vitro hemolysis is still the most common source of pre-analytical nonconformities. This study aimed to investigate the hemolytic effects on commonly used biochemical tests as well as to determine the hemolysis index (HI) thresholds on Siemens Advia 2400 chemistry analyzer. Methods Peripheral blood samples were collected from forty healthy volunteers. Hemolysis was achieved using syringes. Five hemolysis levels were produced including the no hemolysis group, slight hemolysis group, mild hemolysis group, moderate hemolysis group, and heavy hemolysis group. We then used the bias from baseline (no hemolysis) and HI to construct regression functions. The HI corresponding to the bias limits was considered as HI thresholds. We chose the total allowable error (TAE) as the bias limit. Results Of the twenty-eight analytes, ten analytes had clinical significance. Creatine kinase-MB, creatine kinase, potassium, aspartate aminotransferase, and hydroxybutyrate dehydrogenase were all positively affected; the corresponding HI threshold was 45.2, 99.96, 4.07, 10.16, and 7.94, respectively. Lactate dehydrogenase was also positively interfered, but we failed to calculate the HI threshold. Total bile acid, uric acid, and sodium were all negatively affected, and the HI threshold was 42.23, 500 and 501.8, respectively. Glucose was also negatively interfered, but it failed to achieve the HI threshold. Conclusions When the HI value was higher than its threshold, the corresponding analyte was considered inappropriate for reporting. The implementation of the assay-specific HI thresholds could provide an accurate method to identify analytes interfered by hemolysis, which would improve clinical interpretations and further boost laboratory quality by reducing errors associated with hemolysis.

Momordicoside G is a bioactive component from Momordica charantia, this study explores the contributions of macrophages to the effects of momordicoside G on lung injury and carcinoma lesion. In vitro, when administered at the dose that has no effect on cell viability in M2-like macrophages, momordicoside G decreased ROS and promoted autophagy and thus induced apoptosis in M1-like macrophages with the morphological changes. In the urethane-induced lung carcinogenic model, prior to lung carcinoma lesions, urethane induced obvious lung injury accompanied by the increased macrophage infiltration. The lung carcinoma lesions were positively correlated with lung tissue injury and macrophage infiltration in alveolar cavities in the control group, these macrophages showed mainly a M1-like (iNOS+/CD68+) phenotype. ELISA showed that the levels of IL-6 and IL-12 were increased and the levels of IL-10 and TGF-β1 were reduced in the control group. After momordicoside G treatment, lung tissue injury and carcinoma lesions were ameliorated with the decreased M1-like macrophages and the increased M2-like (arginase+/CD68+) macrophages, whereas macrophage depletion by liposome-encapsulated clodronate (LEC) decreased significantly lung tissue injury and carcinoma lesions and also attenuated the protective efficacy of momordicoside G. The M2 macrophage dependent efficacy of momordicoside G was confirmed in a LPS-induced lung injury model in which epithelial closure was promoted by the transfer of M2-like macrophages and delayed by the transfer of M1-like macrophages. To acquire further insight into the underlying molecular mechanisms by which momordicoside G regulates M1 macrophages, we conduct a comprehensive bioinformatics analysis of momordicoside G relevant targets and pathways involved in M1 macrophage phenotype. This study suggests a function of momordicoside G, whereby it selectively suppresses M1 macrophages to stimulate M2-associated lung injury repair and prevent inflammation-associated lung carcinoma lesions.

According to the partially coherent theory for non-stationary optical fields, we introduce a novel model of partially coherent pulse sources, of which the TDOC is limited by Fractional Multi-Gaussian correlated Schell-model (FMGCSM) function. The analytical formula for the temporally mutual coherence function (TMCF) of a FMGCSM pulse beam on propagation in the presence of dispersive media is derived. The average intensity and the temporal degree of coherence (TDOC) of the FMGCSM pulse beam spreading through dispersive media are illustrated numerically. It can be seen that the pulse beam will form strongly sharp pulse intensity pattern when it propagates into far field. Moreover, the FMGCSM pulse beam propagating in dispersive media with chirp coefficient of s 0 will exhibit self-focusing effect and the focal position is controllable via the change of the source parameters. The far-field properties of the pulse beam may be useful for pulse laser shaping and material surface processing.

Obesity is a risk factor for cancer and cancer-related mortality, however, its role in lung cancer progression remains controversial. This study aimed to assess whether high-fat diet (HFD)-induced obesity promotes lung cancer progression and whether the promotion can be decreased by Kanglaite injection (KLTI). In vivo, HFD-induced overweight or obesity increases the lung carcinoma incidence and multiplicity in a urethane-induced lung carcinogenic model and cancer-related mortality in a LLC allograft model by increasing oxidative stress and cellular signaling molecules including JAK, STAT3, Akt, mTOR, NF-κB and cyclin D1. These changes resulted in increases in vascular disruption and the lung water content, thereby promoting lung epithelial proliferation and the epithelial-mesenchymal transition (EMT) during carcinogenesis. Chronic KLTI treatment substantially prevented the weight gain resulting from HFD consumption, thereby reversing the metabolic dysfunction-related physiological changes and reducing susceptibility to lung carcinogenesis. In vitro, KLTI significantly suppressed the proliferation and induced apoptosis and differentiation in 3T3-L1 preadipocyte cells and attenuated endothelial cell permeability in HUVECs. Our study indicates that there is a potential relationship between obesity and lung cancer. This is the first study to show that obesity can directly accelerate carcinogen-induced lung cancer progression and that KLTI can decrease the lung cancer-promoting effect of HFD-induced obesity.

Both gingerol and capsaicin are agonists of TRPV1, which can negatively control tumor progression. This study observed the long-term effects of oral administration of 6-gingerol alone or in combination with capsaicin for 20 weeks in a urethane-induced lung carcinogenic model. We showed that lung carcinoma incidence and multiplicity were 70% and 21.2 ± 3.6, respectively, in the control versus 100% and 35.6 ± 5.2 in the capsaicin group (P < 0.01) and 50% and 10.8 ± 3.1 in the 6-gingerol group (P < 0.01). The combination of 6-gingerol and capsaicin reversed the cancer-promoting effect of capsaicin (carcinoma incidence of 100% versus 20% and multiplicity of 35.6 ± 5.2 versus 4.7 ± 2.3; P < 0.001). The cancer-promoting effect of capsaicin was due to increased epidermal growth-factor receptor (EGFR) level by decreased transient receptor potential vanilloid type-1 (TRPV1) level (P < 0.01) . The capsaicin-decreased EGFR level subsequently reduced levels of nuclear factor-κB (NF-κB) and cyclin D1 that favored enhanced lung epithelial proliferation and epithelial-mesenchymal transition (EMT) during lung carcinogenesis (P < 0.01). In contrast, 6-gingerol promoted TRPV1 level and drastically decreased the levels of EGFR, NF-κB, and cyclin D1 that favored reduced lung epithelial proliferation and EMT (P < 0.01). This study provides valuable information for the long-term consumption of chili-pepper-rich diets to decrease the risk of cancer development.

We present a novel method for generating tangentially and radially polarized laser radiations by using two pairs of positive and negative axicons. Tangentially and radially polarized diode-pumped Nd:YAG hollow lasers were demonstrated respectively. At an incident pump power of 17.8 W, the output power of tangentially and radially polarized laser beam is 6.9 W and 8.6 W, respectively. Polarization purity of tangentially and radially polarized laser beam is 99.2% and 98.7%, respectively. The experimental results reveal that tangentially and radially polarized laser beams with high polarization purity can be generated by resonator cavity consisting of only axicons. To the best of our knowledge, this is the first time that the cylindrical vector laser beam was realized only by axicons.

We present a tunable three-level Nd:YAG laser using a birefringent filter (BF) based on the 4F3/2–4I9/2 transition, generally used for a 946 nm emission. Three-level Nd:YAG laser was performed at three different laser wavelengths of 869 (pure-three-level), 875 (pure-three-level), and 878 nm (quasi-three-level). Within three wavelengths, the 875 and 878 nm were demonstrated for what is believed to be the first time. The highest output power of 1.21 W was achieved at 869 nm with a slope efficiency of 9.9%. Moreover, a continuous-wave (CW) simultaneous dual-wavelength Nd:YAG laser at 875 and 878 nm was also demonstrated for the first time.

In this paper, a novel terahertz modulator using the phase transition characteristics of vanadium dioxide to achieve both band-pass and band-stop filter states is proposed. The regular hexagonal split-ring is used as a unit structure, and the center frequency can be changed by changing the size of the regular hexagon. The simulation results show that any frequency between 0.1~1THz can be used as its center frequency. In the case of 140 um regular hexagon cell, the band-pass filter state shows that the -3dB bandwidth reaches to 100 GHz, and the band-stop filter state shows that the -20dB bandwidth reaches to 75 GHz. Furthermore, a mirror-type regular hexagonal structure is designed as unit cell, which can improve the modulator performance in both states.

Visible and near-infrared spectral reflectances of surface vegetation are basic data for applications in remote sensing classification, multispectral imaging and color reproduction. Leaves are the objects of this study. Firstly, The 400-700 nm visible light spectral reflectance and 700−1000 nm near infrared spectral reflectance data of 12 kinds of trees such as camphor tree, ginkgo tree and peach tree (etc.) are measured by visible and near-infrared portable hyperspectral cameras. The spectral reflectance data is obtained by denoising the using the Minimum Noise Fraction (MNF). Secondly, the Principal Component Analysis (PCA) is used as a method of processing spectral reflectance in the visible and near infrared bands. At last, the correlation analysis is used for spectral reflectance in the visible and near-infrared bands. The obtained data and results provide a theoretical basis for the subsequent establishment of a spectral reflectance data base of surface vegetation spectroscopy and multispectral imaging.

Image registration has always been the hot topic in image research field, and the mutual information registration method has become a commonly used method in image registration because of its high precision and good robustness. Unfortunately, it has a problem for infrared and visible image registration. Lots of rich background detail information is usually provided by the visible light band, while the infrared image can locate an object (heat source) with a higher temperature, and often can't obtain the background information. The large difference in the background information of the two images not only interferes with the accuracy of the registration algorithm but also brings a lot of computation. In this paper, a method of fuzzy c-means clustering is used to separate foreground and background which reduces the background information interference for registration, based on the feature that the infrared image and the visible image have a high uniformity in the target area and a large difference in the background area. Then, the mutual information of the foreground image marked by clustering algorithm is calculated as the similarity measure to achieve the purpose of registration. Finally, the algorithm is tested by the infrared and visible images acquired actually. The results show that the two image’s registration is perfectly implemented and verify the effectiveness of this method.

A novel enhancement algorithm is presented to solve the problem of over exposure in bright areas of Low illumination image enhancement algorithm. In this paper, a model is proposed which can make the bright region gain compressed, and a complementary map can be generated which contains the bright region information. And a segmentation method is proposed to detect the bright region of the low illumination image. Meanwhile, in order to avoid colour distortion, a brightness transfer fusion strategy is used to the bright area of low illumination images. Experiments have shown that the new algorithm has higher average gradient, higher information entropy and close structural similarity to the original algorithm. So it can get better performance in dealing with the bright region of low illumination images both in subjective and objective.

6-Gingerol (6-G) is the main bioactive component in Ginger (Zingiber officinale Roscoe). The aim of this study was to explore the contribution of macrophage polarization in 6-G-associated anti-cancer effects. In a urethane-induced lung carcinogenic model, lung carcinogenesis was positively correlated with macrophage (F4/80+) infiltration in lung interstitial in the control group. Furthermore, higher numbers of arginase+/F4/80+ M2 cells than iNOS+/F4/80+ M1 cells were observed in interstitial macrophages. Moreover, macrophage depletion by liposome-encapsulated clodronate (LEC) could significantly prevent lung carcinogenesis, whereas pexidartinib promoted lung carcinogenesis. After 6-G treatment, lung carcinogenesis was ameliorated with increased M1 macrophages and decreased M2 macrophages in the lung interstitial. ELISA showed that the levels of IFN-γ and IL-12 increased and the levels of IL-10 and TGF-β1 decreased in the alveolar cavity compared to those in the control group. Unexpectedly, the carcinogenesis-preventing efficacy of 6-G was promoted in LEC-treated mice, but completely aborted in pexidartinib-treated mice. In the in vitro experiment, 6-G reset the IL-4-induced arginase+ M2 cells toward iNOS+ M1 cells and exhibited reduced levels of arginase 1 and ROS and elevated levels of L-arginine and NO. LEC and nor-NOHA selectively suppressed M2 macrophages but had a negligible effect on M1 macrophages, whereas pexidartinib decreased both M2 and M1 macrophages. The iNOS+ macrophage-promoting efficacy of 6-G was increased by LEC, but was completely eliminated by pretreatment with pexidartinib or nor-NOHA. M2 macrophage-resetting efficacy of 6-G was confirmed in a Lewis lung cancer allograft model. This study indicated a reprogramming effect of 6-G as an arginase inhibitor on tumor supporting macrophages.