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Background Scientists have been facing numerous challenges in the development of an effective therapeutic strategy for the treatment of COVID-19 pneumonia. Several studies have suggested that improving patient immunity and reducing lung injury induced by SARS-CoV-2 may be effective for treating patients with COVID-19. Methods A pilot trial of nebulization therapy with exosomes of mesenchymal stem cells (MSCs) was performed on seven patients with COVID-19 pneumonia. Exosomes secreted from MSCs were collected and purified using multiple ultrafiltration steps. All patients were treated with nebulization of MSC-derived exosomes, and primary safety and efficacy outcomes were evaluated. Results Our clinical study demonstrated that nebulization of MSC-derived exosomes is a novel method that might be utilized in the treatment of COVID-19 pneumonia. Nebulization of MSC-derived exosomes did not induce acute allergic or secondary allergic reactions but did promote the absorption of pulmonary lesions and reduce the duration of hospitalization for mild cases of COVID-19 pneumonia. Conclusions Nebulization of MSC-derived exosomes is a safe, effective, and simple method, and their application at the beginning of treatment may be more beneficial. Trial Registration Chinese Clinical Trial Registry, ChiCTR2000030261. Registered on 26 February 2020. Graphical Abstract

Short-term load forecasting with high accuracy is essential to power systems. Because power loads involve high volatility and uncertainty, it is challenging to accurately perform short-term load forecasting (STLF). To solve this problem, this paper proposes a decomposition-based approximate entropy cooperation long short-term memory (DB-AEC-LSTM) model for STLF. In DB-AEC-LSTM, a complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method is first introduced to generate the multiple electric load time series into many cooperation sub-series and decrease the reconstruction errors. Then, an Approximate Entropy Cooperation ensemble Long Short-term Memory Model is developed by using approximate entropy (ApEn) to construct an effective cooperative relationship between different time sub-series groups, greatly improving the predictive accuracy. By rationally combined the effective technologies ApEn, CEEMDAN, and AEC-LSTM, the proposed DB-AEC-LSTM can obtain competitive predictive performance in STLF. Several short-term load forecasting datasets are performed to check the predictive performance of DB-AEC-LSTM. Experimental results show that DB-AEC-LSTM has better predictive accuracy and satisfactory robustness compared with state-of-the-art and conventional predictive models.

Short‐term load forecasting is essential to power systems management. However, most existing forecasting methods fail to fully consider how to rationally integrate the intrinsic time‐related dimensions of electric load data and the decomposition methods into machine learning models so that their prediction accuracy and robustness still have much room for improvement. To solve this problem, this paper proposes a decomposition‐based multi‐time dimension long short‐term memory (DB‐MTD‐LSTM) model for short‐term electric load forecasting (STELF). In DB‐MTD‐LSTM, empirical mode decomposition with adaptive noise (CEEMDAN) is first introduced to smooth non‐linear non‐stationary electric load data and constrain the modal aliasing or noise of decomposed electric load data in the traditional decomposed method. A joint relevant time dimensions method (JRTDM) is then developed using autocorrelation analysis to rationally extract the temporal characteristics of decomposed data in multiple time dimensions. An improved LSTM called MTD‐LSTM is developed by combining JRTDM with LSTM, which can effectively apply multi‐dimensional time characteristics of the decomposed load to improve the predictive accuracy and robustness. Several datasets from Australia and China are performed to check the predictive performance of DB‐MTD‐LSTM. Experimental results verify that DB‐MTD‐LSTM has better predictive accuracy and satisfactory robustness compared with state‐of‐the‐art and conventional predictive models.

To explore the application rules and effects of "Four Elements, One Peptide, and Two Transplantations" in the bundle treatment of the patients with coronavirus disease 2019 (COVID-19), so as to provide a scientific evidence for effective treatment and prevention of severe type.A retrospective comparative study method was used to analyze the clinical data of COVID-19 patients admitted to Wuxi Fifth People's Hospital from January 2020 to March 2022, including demographic information, underlying diseases, clinical classification, length of hospital stay, treatment cost, clinical symptoms, laboratory tests and other key indicators, and evaluate the application rules and effect of "Four Elements, One Peptide, and Two Transplantations" in the bundle treatment of the patients with COVID-19.The L-type new coronavirus strain was predominant in 2020, the Delta variant in 2021, and the Omicron variant in 2022. The proportion of mild cases was highest in 2022, with the highest proportion of65 years old patients developing severe and critical. Among the 150 patients, the proportion of interferon use (100.0%) was the highest in the bundle treatment regimen of "Four Elements, One Peptide, and Two Transplantation". The combined use of vitamin C, interferon and thymopeptide was highest in 2022. More than 75.0% of the age65 years old group had underlying diseases, which was also the age group with the highest proportion of "Four Elements, One Peptide, and Two transplantations". Compared with mild cases, the age, length of hospital stay, and hospitalization cost of patients with COVID-19 increased significantly with severity. Mild, ordinary, severe, and critically ill patients all had low lymphocyte counts, with 40.0% of severe patients having the lowest lymphocyte counts within 3 days of admission. The lymphocyte count of critically ill patients was reduced or continuously reduced after admission, and the use of the "Four Elements, One Peptide, and Two transplantations" method to regulate immunity can effectively save the lives of critically ill patients. Of all cases of COVID-19 infection, 51.3% were asymptomatic, followed by respiratory symptoms (48.7%) and lung lesions (38.0%). Patients with renal dysfunction received this bundle therapy was highest, followed abnormal coagulation and abnormal liver function. This bundle therapy promoted a significant increase in CD4Advanced age with underlying diseases is a risk factor for severe disease of COVID-19, the "Four Elements, One Peptide, and Two transplantations" bundle fine treatment of COVID-19 can improve the proportion of lymphocyte composition and organ function, which can control the occurrence and development of severe diseases. In addition to the proportion of CD4

To improve the accuracy of ultra-short-term wind speed prediction, a hybrid generative adversarial network model (HGANN) is proposed in this paper. Firstly, to reduce the noise of the wind sequence, the raw wind data are decomposed using complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN). Then the decomposed modalities are entered into the HGANN network for prediction. HGANN is a continuous game between the generator and the discriminator, which in turn allows the generator to learn the distribution of the wind data and make predictions about it. Notably, we developed the optimized broad learning system (OBLS) as a generator for the HGANN network, which can improve the generalization ability and error convergence of HGANN. In addition, improved particle swarm optimization (IPSO) was used to optimize the hyperparameters of OBLS. To validate the performance of the HGANN model, experiments were conducted using wind sequences from different regions and at different times. The experimental results show that our model outperforms other cutting-edge benchmark models in single-step and multi-step forecasts. This demonstrates not only the accuracy and robustness of the proposed model but also the applicability of our model to more general environments for wind speed prediction.

Since December 2019, there has been a global outbreak of COVID-19. As of the end of July 2020, more than 600,000 deaths had been reported globally. The purpose of this paper is to further explore the application of non-invasive ventilation in severe COVID-19 patients.A retrospective study was conducted to included 57 confirmed COVID-19 patients, among which 36 cases were severe. According to different oxygen inhalation methods, they were divided into non-invasive ventilator assisted ventilation group with 21 cases (group A) and 15 cases of nasal catheter oxygen inhalation group (group B). The data of respiration (RR), heart rate (HR), partial arterial pressure of oxygen (PaO2), partial arterial pressure of carbon dioxide (PaCO2), and oxygenation index (OI) before the treatment of noninvasive ventilator assisted ventilation or nasal catheter oxygen treatment at 24, 48, and 72 hours of treatment of the 2 groups were collected and analyzed to determine whether the above indicators were statistically different in each time period.After 24 hours of treatment with noninvasive ventilator assisted ventilation in group A, RR gradually decreased, PaO2 and OI were significantly higher than before treatment, while after 24 hours of treatment, PaO2, RR, HR and other indexes in group B showed no significant improvement, and OI increased gradually after 48 hours of treatment, with statistically significant difference compared with that before treatment.Early adoption of non-invasive ventilation can effectively improve the hypoxic state of patients with severe COVID-19. The combination of underlying diseases will not prolong the use of non-invasive ventilation.

With the development of femtosecond (fs) laser technology, an fs laser pulse with 10s of Joule, even 100s of Joule energy is available and the focused laser intensity can be expected to induce the pure Coulomb explosion of the cluster with a much larger average radius than before. Meanwhile, the production of gas cluster with an average radius of upto 10s of nanometer has been possible. In this case, it is necessary to reinvestigate the feasibility of 109 n/shot neutron yield for the practical application in the intense fs laser-driven nuclear fusion. In this work, the neutron yield from the explosions of the D2 clusters of 6–20 nm average radius at the 0.5–100 J pulse energy and the CD4 clusters was investigated theoretically. It is found that the optimum neutron yield of 109 n/shot can be obtained at the laser energy and the cluster radius currently available. However, a clustered-gas jet with a large cross-section is demanded to match the proper plasma diameter.

Photovoltaic (PV) systems are becoming increasingly significant because they can convert solar energy into electricity. The conversion efficiency is related to the PV models’ parameters, so it is crucial to identify parameters of PV models. Recently, various heuristic methods have been proposed to identify the parameters, but they cannot provide sufficient accurate and reliable performance. To address this problem, this paper proposes a spiral-based chaos chicken swarm optimization algorithm (SCCSO) including three strategies: i) the information-sharing strategy provides the latest information of the roosters for searching global optimal solution, beneficial to improve the exploitation ability; ii) the spiral motion strategy can enable hens and chicks to move towards their corresponding targets with a spiral trajectory, improving the exploration ability; iii) a self-adaptive-based chaotic disturbance mechanism is introduced around the global optimal solution to generate a promising solution for the worst chick at each iteration, thereby improving the convergence speed of the chicken flock. Besides, SCCSO is used for identifying different PV models such as the single diode, the double diode, and PV module models. Comprehensive analysis and experimental results show that SCCSO provides better robustness and accuracy than other advanced heuristic methods.

To analyze the immunotherapy and clinical characteristics of coronavirus disease 2019 (COVID-19) patients, and focus on exploring the effects of immunotherapy and mesenchymal stem cells (MSC) transplantation in the critically ill patients' treatment.Fity-five COVID-19 patients were admitted to the Fifth People's Hospital of Wuxi from January 23rd to March 31st, 2020 as the research object. The demographic characteristics of the cases and the methods of immunotherapy were analyzed, focusing on the immunized indicators, positivity of pathogens and clinical indicators of critically ill COVID-19 patient, and the effects of immunotherapy and stem cell transplantation were evaluated.Aged, male and people with comorbidities were the main risk factors in the development of severe and critical COVID-19. All of confirmed COVID-19 cases (n = 55) had been treated with interferon-α (IFN-α), of which 81.8% (n = 45, mild and ordinary) of the patients were recovered, 14.6% (n = 8) of the patients were converted to severe, 3.6% (n = 2) of the patients were converted to critical, and some severe patients were treated with gamma globulin and albumin as adjuvant treatment. Critically ill patients were not only treated with IFN-α, gamma globulin and albumin, but also treated with convalescent plasma and MSC transplantation. Due to pulmonary hemorrhage and persistently low blood oxygen saturation, terminal lung transplantation therapy was implemented. The total number of lymphocytes, CD4In addition to IFN, gamma globulin, antiserum and MSC transplantation therapy can help clear the virus and reduce inflammation. Although MSC transplantation fail to completely change the immunecompromised state of critically ill patients, it controlled the progression of inflammation in the liver and kidneys.

Background: Scientists have been facing numerous challenges in the development of an effective therapeutic strategy for the treatment of COVID-19 pneumonia. Several studies have suggested that improving patient immunity and reducing lung injury induced by SARS-CoV-2 may be effective for treating patients with COVID-19.Methods: A pilot trial of nebulization therapy with exosomes of mesenchymal stem cells (MSCs) was performed on seven patients with COVID-19 pneumonia. Exosomes secreted from MSCs were collected and purified using multiple ultrafiltration steps. All patients were treated with nebulization of MSC-derived exosomes, and primary safety and efficacy outcomes were evaluated.Results: Our clinical study demonstrated that nebulization of MSC-derived exosomes is a novel method that might be utilized in the treatment of COVID-19 pneumonia. Nebulization of MSC-derived exosomes did not induce acute allergic or secondary allergic reactions but did promote the absorption of pulmonary lesions and reduce the time of hospitalization for mild cases of COVID-19 pneumonia.Conclusions: Nebulization of MSC-derived exosomes is a safe, effective, and simple method, and their application at the beginning of treatment may be more beneficial.Trial registration: Chinese Clinical Trial Registry, ChiCTR2000030261. Registered on 26 February 2020 – Retrospective registered, http://www.chictr.org.cn

Since the first infected case of Coronavirus Disease 2019 (COVID-19) was reported in Wuhan, China in December 2019, the virus has spread swiftly, inflicting upon millions of people around the globe. The objective of the study is to investigate and analyze the clinical characteristics and outcomes of patients infected with COVID-19 in Wuxi, China.Cross-sectional study.The Fifth People's Hospital of Wuxi, China.A total of 48 COVID-19 patients were enrolled in the study from 23 January 2020 to 8 March 2020, and the clinical data of these subjects were collected.Epidemiological, clinical, laboratory, and radiologic characteristics, as well as treatment and outcome data, were collected and analyzed.Of these 48 patients with confirmed COVID-19, 3 were mild cases (6.3%), 44 were moderate cases (91.7%), 1 was severe case (2.1%). The median age of the subjects was 45 years (interquartile range [IQR], 24-59; range, 5-75 years). Twenty-five of the patients (52.1%) were male and 23 (47.9%) were female. Twenty-eight cases (58.3%) returned to Wuxi, Jiangsu Province. Thirty-four (70.8%) cases were infected due to clustering epidemic and 29 cases (85.3%) were attributable to family-clustering epidemic. No obvious clinical symptoms were observed in the cohort of patients, except for 3 mild cases. The most common symptoms include fever (41 [85.4%]), cough (28 [58.3%]), asthenia (13 [27.1%]), expectoration (11 [22.9%]), diarrhea (10 [20.8%]), and dyspnea (5 [10.4%]). Seventeen (35.4%) patients had lower lymphocyte values than baseline, 31 patients (64.6%) had higher d-dimers to exceed the normal range. The distribution of high-resolution computed tomography (HRCT)-positive lesions were as follows: left lung in 5 cases (10.4%), right lung in 9 cases (18.8%), and bilateral lungs in 31 cases (64.6%). In terms of density of lesions: 28 cases (58.3%) showed ground glass shadows in the lung, 7 cases (14.6%) showed solid density shadows, and 10 cases (20.8%) showed mixed density shadows. Extrapulmonary manifestations found that mediastinal lymph nodes were enlarged in 2 cases (4.2%) and that pleural effusion was present in 1 case (2.1%). All patients underwent treatment in quarantine. Forty-five (93.8%) patients received antiviral treatments, 22 (45.8%) patients received antibacterial treatments, 6 (12.5%) patients received glucocorticoid treatments, 2 (4.2%) patients received high flow oxygen inhalation treatments, and 6 (12.5%) patients received noninvasive ventilation treatments. As of 8 March 2020, all 48 patients included in this study were cured. The average time of hospitalization of the 48 patients was 18 ±â€Š6 (mean ±â€ŠSD) days, the average time of the lesion resorption was 11 ±â€Š4 days, and the average time taken to achieve negativity in the result of nucleic acid examination was (10 ±â€Š4) days.The epidemiological characteristics of 48 COVID-19 patients in Wuxi were mainly imported cases and clustered cases. The clinical manifestations of these patients were mainly fever and cough. Laboratory results showed that the lymphocytopenia and increased d-dimer are positively correlated with disease severity. Pulmonary imaging showed unilateral or bilateral ground glass infiltration. Most of the patients entered clinical recovery stage within 15 days after hospitalization.

Background: Scientist have been facing numerous challenges in the development of an effective therapeutic strategy for the treatment of COVID-19 pneumonia. Several studies have suggested that improving patient immunity and reducing lung injury induced by COVID -19 could be effective in treating the patients with COVID-19. Methods: A pilot trial of nebulization therapy for COVID-19 pneumonia with exosomes of MSCs was performed on seven patients with COVID-19 infected pneumonia. Exosomes were collected and purified from secretion of MSCs using multiple ultrafiltration. All patients was treated with nebulization of MSC-derived exosomes. The primary safety and efficacy outcome were observed.Results: Our clinical study demonstrated that nebulization mesenchymal stem cell (MSCs)-derived exosomes is a novel method that could be utilized in the treatment of COVID-19 pneumonia. Nebulization of MSC-derived exosomes did not induce acute allergic and secondary allergic reactions. It could promote the absorption of pulmonary lesions, and reduce the time of hospitalization for minor cases of COVID-19 pneumonia.Conclusions: Nebulization of MSC-derived exosomes is a safe, effective, and simple method. Nebulization of MSC-derived exosomes from the beginning of the treatment could be more beneficial to the patients. Trial registration: Chinese Clinical Trial Registry, ChiCTR2000030261. Registered on 26 February 2020.

ObjectiveWe aimed to investigate clinical features and management of 55 COVID-19 patients in Wuxi, especially severe COVID-19.MethodsEpidemiological, demographic, clinical, laboratory, imaging, treatment, and outcome data of patients were collected. Follow-up lasted until April 6, 2020.ResultsAll 55 patients included 47 (85.5%) non-severe patients and 8 (14.5%) severe patients. Common comorbidities were hypertension and diabetes. Common symptoms were fever, cough and sputum. Lymphopenia was a common laboratory finding, and ground-glass opacity was a common chest CT feature. All patients received antiviral therapy of α-interferon inhalation and lopinavir-ritonavir tablets. Common complications included acute liver injury and respiratory failure. All patients were discharged. No death was occurred and no medical staff got infected. Patients with severe COVID-19 showed significantly older age, decreased lymphocytes, increased C reactive protein, and higher frequency of bilateral lung infiltration compared to non-severe patients. Significantly more treatments including antibiotic therapy and mechanical ventilation, longer hospitalization stay and higher cost were shown on severe patients.ConclusionsOur study suggested that patients with severe COVID-19 may be more likely to have an older age, present with lymphopenia and bilateral lung infiltration, receive multiple treatments and stay longer in hospital.

The main objective of the current study was to investigate the chemical composition of the essential oil of Artemisia asiatica together with investigating the antibacterial effects it exerts on several common respiratory infection causing bacteria including Haemophilus influenzae. Its mechanism of action was studied using various state-of-the-art assays like scanning electron microscopy, DNA, RNA and protein leakage assays, growth curve assays etc. The essential oil was extracted from the leaves of A. asiatica by supercritical CO2 fluid extraction technology. Chemical composition of essential oils was analyzed by gas chromatography-mass-spectrometry (GC-MS). The antibacterial activity was evaluated against 6 bacteria by the paper disc diffusion method. The minimum inhibitory concentration (MIC) and minimum bactericide concentration (MBC) values of the essential oil were estimated by agar dilution method. The antibacterial mechanism was evaluated by growth curve, the integrity of cell membrane and scanning electronmicroscope (SEM). Gas chromatographic analysis of the A. asiatica essential oil led to the identification of 16 chemical constituents accounting for 97.2% of the total oil composition. The major components were found to be Piperitone, (z)-davanone, p-cymene and 1, 8-cineole. The essential oil showed maximum growth inhibition against Haemophilus influenzae with a zone of inhibition of 24.5 mm and MIC/MBC values of 1.9/4.5 mg/mL respectively. Bacteria treated with the essential oil led to a rapid decrease in the number of viable cells. On adding the essential oil of A. asiatica to the bacterial culture, the constituents of the bacterial cell got released into the medium and this cell constituent release increased with increasing doses of the essential oil. SEM showed that the bacterial cells treated with the essential oil showed damaged cell wall, deformed cell morphology and shrunken cells., Highlights • Antibacterial activity of Artemisia asiatica essential oil evaluated. • The antibacterial mechanism evaluated by scanning electron microscope. • 16 chemical constituents were identified in the essential oil. • Essential oil caused damage to the bacterial cell membrane. • The essential oil was found to be most potent against Haemophilus influenzae.

Differential interferometric synthetic aperture radar (D-InSAR) is an effective technique for geological disaster prevention. In this study, an early landslide detection method based on the D-InSAR technique is proposed. First, SAR data are used to monitor landslide deformation in the Wudongde hydropower reservoir. Then, the ground surface deformation is derived by using the D-InSAR technique, which includes both soil and non-soil deformations. To remove the non-soil deformation, the vertical deformation filter method and slope deformation filter method for extracting soil deformations are established, and the error of D-InSAR results is analyzed. By using two methods, Permanent Scatterers InSAR and Corner Reflectors InSAR, the errors caused by the atmospheric delay are estimated quantitatively. Additionally, the relationship between the landslide deformation and the temporal-spatial change of the SAR data is analyzed, and used to identify landslides. Finally, through the proposed early landslide detection method, the Jinpingzi landslide in the Wudongde area is investigated to validate the proposed method, and the other unknown landslides in this area are also detected, which demonstrates the feasibility of the proposed method. The outcome of this study provides a workable technique for early detection of landslides in valley reservoir areas.

To discuss the problems in perioperative nursing care for patients with postoperative infectious endophthalmitis.The medical records of 34 patients (35 eyes) presenting with infectious endophthalmitis at Zhongshan Ophthalmic Center, Sun Yat-sen University between April 2002 and December 2013 were collected to analyze preoperative and postoperative nursing care for endophthalmitis after ocular surgery.Thirty-four patients (35 eyes) developed complications of infectious endophthalmitis after surgery. Thirty-three cases were successfully cured and only one patient (1 eye) was untreated due to Pseudomonas aeruginosa infection.Perioperative nursing care plays a pivotal role in preventing and controlling the incidence and development of postoperative infectious endophthalmitis.

To investigate the effect of preoperative psychological intervention on alleviating negative emotions in patients undergoing emergent ocular trauma surgery.A total of 100 patients undergoing emergent ocular trauma surgery were selected using convenience sampling and randomly divided into control (n = 49) and experimental (n = 51) groups. Patients in the control group received conventional nursing and their counterparts in the observation group were treated with individualized psychological interventions including psychological support, relaxation training, and humanistic care based on conventional nursing care. Self-rating anxiety scale (SAS), self-rating depression scale (SDS), and fear visual analog scale (FVAS) scores were statistically compared between the two groups.The scores of SAS, SDS, and FAVS were significantly lower in the experimental group than in the control group (all P0.001).Comprehensive psychological intervention effectively eliminates negative emotions in patients undergoing emergent ocular trauma surgery and accelerates their physical and mental recovery.

ZnSe nanoparticles were synthesized through a vapor-phase reaction of zinc and selenium and deposited as random aggregates on a water-cooled copper collector. X-ray diffraction (XRD) and transmission electron microscopy (TEM) demonstrate that the as-grown nanoparticles are polycrystalline ZnSe nanoparticles. Their diameters can be controlled through the deposition temperature. Raman spectra of nanoparticles with different diameter-size distribution and bulk material were measured at various excitation laser power with 632.8 and 532 nm laser. The phonon confinement mode was considered, and three-phonon process were used to explain the Raman spectra variation. The temperature effect of Raman scattering on microcrystalline was more obvious when excited with 532 nm laser than 632.8 nm laser, and small-size particles show a stronger temperature effect than large-size particles.

Decoupling of multiple coupled photonic crystal waveguides (M-CPCWs) is investigated based on the self-imaging principle. We choose the three-, four-, and eight-CPCWs as typical structures to discuss the general characteristics of the M-CPCWs. It is found that around the frequency where the multiple guided modes are almost degenerate, the power transfer in the M-CPCWs is eliminated for any entrance. The frequency region for decoupling is insensitive to the number of coupled waveguides with the extinction ratios higher than -15 dB. The decoupling of the M-CPCWs exhibit many advantages and may have practical applications in photonic integrated circuits.

Landslide monitoring is one of the most important methods in landslide prevention. Landslide early identifying that based on D-InSAR technique is one of the effective means in landslide monitoring in ravine reservoir area. On the basis of D-InSAR technique analysis in ravine reservoir, how to eliminate the error and find the real moving area caused by rock and soil is the key problem. Considering the fact, an experiment region in reservoir of Wudongde hydropower station, Jinsha River has been studied. Based on D-InSAR analysis method and the characteristics of radar data, an analysis method of the SAR data trusted zone, the detectable landsliding displacement and error estimation has been established, extracting the effective range in the result of SAR data analysis.

The time evolution of residual entanglement in a three-qubit system embedded in a photonic crystal is investigated by using a modified conjugate gradient method. In the isotropic photonic crystal the phenomena of entanglement ``sudden death'' and entanglement ``sudden birth'' are found due to the decoherence induced by the environment and its memory effect. Compared with the environment of an isotropic photonic crystal, entanglement has a longer lifetime in the anisotropic photonic crystal if the transition frequency is near the band edge. However, once the entanglement disappears, at a finite time in the anisotropic photonic crystal, it cannot revive, which means the phenomenon of entanglement sudden birth cannot happen in the anisotropic photonic crystal. The tripartite entanglement decays faster than bipartite entanglement in both types of photonic crystal, which indicates that multipartite entanglement is more fragile than bipartite entanglement in resisting quantum noise.

GIS ( Geographic Information System)-baded three-dimension limit equilibrium model is used to analyze the stebility of potential landslide body in this article; The result of the improved unidirectional flow analysis is applied to confirm the then surge hazards when the landslide happens, in the upper reaches of reservoir. Then the influence range of the surge hazard can be visualized in GIS. The result of the study could provide the risk assessment of the potential landslide with an effective and reliable decision-support.

Landslide disaster has happened frequently in our country. Monitoring and early warning are the main means to effectively reduce the harm of landslide disaster. Different from the traditional method of monitoring, differential interferometry synthetic aperture radar (D-InSAR) measuring technique has the advantage of detecting and penetrating earth surface in all weather conditions and in all time, obtaining continuous and large-area deformation information. Taking the Jinpingzi Landslide of Jinshajiang valley as the research object. The monitoring technique of three orbits difference, the basic method of D-InSAR, is used to obtain surface deformation value. Research results show that the deformation value of Landslide boundaries is larger than the surrounding area, and the D-InSAR technology is a feasible approach for monitoring landslide.

We propose and simulate a new kind of compact polarizing beam splitter (PBS) based on a photonic crystal ring resonator (PCRR) with complete photonic bandgaps. The two polarized states are separated far enough by resonant and nonresonant coupling between the waveguide modes and the microring modes. Some defect holes are utilized to control the beam propagation. The simulated results obtained by the finite-difference time-domain method show that high transmission (over 95%) is obtained and the polarization separation is realized with a length as short as 3.1 microm. The design of the proposed PBS can be flexible, thanks to the advantages of PCRRs.