23 MHz widely wavelength-tunable L-band dissipative soliton from an all-fiber Er-doped laser

Via careful choice of Er-doped fiber length in the cavity, a widely wavelength-tunable L-band dissipative soliton all-fiber Er-doped laser incorporating a L-band optimized polarizing fiber grating device is experimentally demonstrated. The laser delivers 15.38 ps dissipative soliton pulses centered at 1597.34 nm with 3 dB bandwidth of 34.6 nm under 622 mW pump power. The pulse repetition rate is 23 MHz. After using single mode fiber at external cavity, the pulse duration is compressed to 772 fs. With nonlinear polarization rotation-based intracavity comb filter, the central wavelength of the generated dissipative soliton can be tuned from 1567 nm to 1606 nm with a spectral tuning range of 39 nm, which, to the best of our knowledge, is the widest tuning range yet reported for a dissipative soliton fiber laser working in communication band

Combination of (M)DSC and surface analysis to study the phase behaviour and drug distribution of ternary solid dispersions

Purpose: Miscibility of the different compounds that make up a solid dispersion based formulation play a crucial role in the drug release profile and physical stability of the solid dispersion as it defines the phase behaviour of the dispersion. The standard technique to obtain information on phase behaviour of a sample is (modulated) differential scanning calorimetry ((M)DSC). However, for ternary mixtures (M)DSC alone is not sufficient to characterize their phase behaviour and to gain insight into the distribution of the active pharmaceutical ingredient (API) in a two-phased polymeric matrix. Methods: MDSC was combined with complementary surface analysis techniques, specifically time-of-flight secondary ion mass spectrometry (ToF-SIMS) and atomic force microscopy (AFM). Three spray-dried model formulations with varying API/PLGA/PVP ratios were analyzed. Results: The distribution of the API in the ternary solid dispersions depended on formulation parameters. The extent of API surface coverage and therefore the distribution of the API over both polymeric phases differed significantly for the three formulations. Conclusions: Combining (M)DSC and surface analysis rendered additional insights in the composition of mixed phases in complex systems, like ternary solid dispersions

A Nonluminescent and Highly Virulent Vibrio harveyi Strain Is Associated with “Bacterial White Tail Disease” of Litopenaeus vannamei Shrimp

Recurrent outbreaks of a disease in pond-cultured juvenile and subadult Litopenaeus vannamei shrimp in several districts in China remain an important problem in recent years. The disease was characterized by “white tail” and generally accompanied by mass mortalities. Based on data from the microscopical analyses, PCR detection and 16S rRNA sequencing, a new Vibrio harveyi strain (designated as strain HLB0905) was identified as the etiologic pathogen. The bacterial isolation and challenge tests demonstrated that the HLB0905 strain was nonluminescent but highly virulent. It could cause mass mortality in affected shrimp during a short time period with a low dose of infection. Meanwhile, the histopathological and electron microscopical analysis both showed that the HLB0905 strain could cause severe fiber cell damages and striated muscle necrosis by accumulating in the tail muscle of L. vannamei shrimp, which led the affected shrimp to exhibit white or opaque lesions in the tail. The typical sign was closely similar to that caused by infectious myonecrosis (IMN), white tail disease (WTD) or penaeid white tail disease (PWTD). To differentiate from such diseases as with a sign of “white tail” but of non-bacterial origin, the present disease was named as “bacterial white tail disease (BWTD)”. Present study revealed that, just like IMN and WTD, BWTD could also cause mass mortalities in pond-cultured shrimp. These results suggested that some bacterial strains are changing themselves from secondary to primary pathogens by enhancing their virulence in current shrimp aquaculture system

Bayesian Regularization Algorithm Based Recurrent Neural Network Method and NSGA-II for the Optimal Design of the Reflector

The optical-mechanical system of a space camera is composed of several complex components, and the effects of several factors (weight, gravity, modal frequency, temperature, etc.) on its system performance need to be considered during ground tests, launch, and in-orbit operation. In order to meet the system specifications of the optical camera system, the dimensional parameters of the optical camera structure need to be optimized. There is a highly nonlinear functional relationship between the dimensional parameters of the optical machine structure and the design indexes. The traditional method takes a significant amount of time for finite element calculation and is less efficient. In order to improve the optimization efficiency, a recurrent neural network prediction model based on the Bayesian regularization algorithm is proposed in this paper, and the NSGA-II is used to globally optimize multiple prediction objectives of the prediction model. The reflector of the space camera is used as an example to predict the weight, first-order modal frequency, and gravitational mirror deformation root mean square of the reflector, and to complete the lightweight design. The results show that the prediction model established by BR-RNN-NSGA-II offers high prediction accuracy for the design indexes of the reflector, which all reach over 99.6%, and BR-RNN-NSGA-II can complete the multi-objective optimization search efficiently and accurately. This paper provides a new idea of optimization of optical machine structure, which enriches the theory of complex structure design

Bayesian Regularization Algorithm Based Recurrent Neural Network Method and NSGA-II for the Optimal Design of the Reflector

The optical-mechanical system of a space camera is composed of several complex components, and the effects of several factors (weight, gravity, modal frequency, temperature, etc.) on its system performance need to be considered during ground tests, launch, and in-orbit operation. In order to meet the system specifications of the optical camera system, the dimensional parameters of the optical camera structure need to be optimized. There is a highly nonlinear functional relationship between the dimensional parameters of the optical machine structure and the design indexes. The traditional method takes a significant amount of time for finite element calculation and is less efficient. In order to improve the optimization efficiency, a recurrent neural network prediction model based on the Bayesian regularization algorithm is proposed in this paper, and the NSGA-II is used to globally optimize multiple prediction objectives of the prediction model. The reflector of the space camera is used as an example to predict the weight, first-order modal frequency, and gravitational mirror deformation root mean square of the reflector, and to complete the lightweight design. The results show that the prediction model established by BR-RNN-NSGA-II offers high prediction accuracy for the design indexes of the reflector, which all reach over 99.6%, and BR-RNN-NSGA-II can complete the multi-objective optimization search efficiently and accurately. This paper provides a new idea of optimization of optical machine structure, which enriches the theory of complex structure design

Corrosion behavior and electrochemical corrosion of a high manganese steel in simulated marine splash zone

The corrosion behavior of a high manganese steel in simulated marine splash zone environment was studied by dry-wet cyclic corrosion experiment and electrochemical experiment. Corrosion kinetics, composition, surface morphology, cross-section morphology, element distribution, valence state, polarization curve and electrochemical impedance spectroscopy were analyzed with the aim of characterizing the characteristics of corrosion product films. The results show that in chloride-containing environment, in the initial corrosion products, Mn oxides with porous structure lead to higher corrosion rate. As corrosion extends, the formation of alloy element oxides in corrosion products changes the corrosion properties of rust layers at different stages. Mo oxides form a stable passivation film, which reduces the influence of chloride ion on corrosion. Ni oxides in the inner rust layer facilitate the transformation of goethite, and Cr oxides in the outer rust layer increase the densification of the rust layer. The stability and compactness of Fe _3 O _4 , α -FeOOH and FeCr _2 O _4 in the later corrosion products inhibit the corrosion action of manganese iron oxides and slow down the corrosion rate. With the corrosion durations, the corrosion current density of the sample with the corrosion product film first increases and then decreases, and the corrosion potential first moves negative and then shifts in a positive direction subsequently, indicating that the protective effect of the corrosion product film is gradually significant

Construction and Application of MALDI-TOF Mass Spectrometry for the Detection of Haemophilus parasuis

To construct a protein fingerprint database of Haemophilus parasuis (H. parasuis), thus improving its clinical diagnosis efficiency. A total of 15 H. parasuis standard strains were collected to establish a protein fingerprint database of H. parasuis using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS), and the effects of different culture media and culture time on the quality and identification results of the protein fingerprint were investigated. The results showed that tryptone soy agar (TSA) and tryptone soy broth (TSB) media and different incubation times had no significant effect on the characteristic peaks of the protein profiles. In addition, 18 clinical isolates were used to compare the identification results of the self-built protein fingerprint database, PCR detection, and basic database. Only one strain was identified in the original VITEK-MS system database, while the self-made protein fingerprint database of H. parasuis was 100% accurate for the detection of 18 clinical isolate strains. The protein fingerprint database of H. parasuis built by our laboratory is suitable for rapid clinical diagnosis of H. parasuis, due to its high accuracy, efficiency, and strong specificity

The Optimization Research of Diesel Cylinder Gasket Parameters Based on Hybrid Neutral Network and Improved Grey Wolf Algorithm

In order to improve reliability and fatigue life of cylinder gaskets in heavy duty diesel engine, several methods and algorithms are applied to optimize operating factors of gaskets. Finite element method is utilized to figure out and analyze the temperature fields, thermal-mechanical coupling stress fields, and deformations of gasket. After determining the maximum values of three state parameters, the orthogonal experimental design method is adopted to analyze the influence rules of five operating factors on three state parameters of the gaskets and four factors which most significantly affect these state parameters are determined. Then, the method which uses operating factors to predict state parameters is established on the application of hybrid neuron network based on partial least squares regression and deep neural network. The comparison results between the predicted values and real values verified the accuracy of the hybrid neuron network method. Based on artificial bee colony algorithm, improvement is attached to the way three kinds of grey wolves locate preys in grey wolf algorithm and the way how using different hierarchy wolfs in grey wolf algorithm to determine three weight coefficients and the location of prey is put forward with. The method using artificial bee colony algorithm to optimize the grey wolf algorithm is called ABC and GWO. The proposed HNN and the ABC and GWO method are applied to work out operating factors values which correspond to optimal state parameters of gasket, and the gaskets are optimized according to the optimal values. It has been demonstrated by finite element analysis results that maximum temperature, maximum coupling stress, and the maximum deformation decrease to 6 K, 12.57 MPa, and 0.0925 mm compared to the original values, respectively, which proves the accuracy of the algorithm and the validity of the improvement

Randomized controlled trial: Standard versus supplemental bowel preparation in patients with Bristol stool form 1 and 2.

Bristol stool form 1 and 2 is an important predictor of inadequate bowel preparation.To evaluate the efficacy of supplemental preparation in bowel cleansing quality among patients with Bristol stool form 1 and 2, as well as the feasibility of tailored bowel preparation guided by Bristol stool form scale.Patients with Bristol stool form 1 and 2 from 3 Chinese tertiary hospitals randomly received either 2 L PEG-ELP (group A) or 10 mg bisacodyl plus 2 L PEG-ELP (group B); patients with Bristol stool form 3 to 7 received 2 L PEG-ELP (group C) for bowel preparation. The primary endpoint is the rate of adequate bowel reparation for the whole colon. The adequate bowel preparation rate for separate colon segments, the polyp detection rate (PDR), tolerability, acceptability, sleeping quality and compliance were evaluated as secondary endpoints.700 patients were randomized. In per-protocol analysis, patients in group B attained significantly higher successful preparation rate than group A (88.7% vs. 61.2%, p<0.001) and similar with group C (88.7% vs. 85.0%, p = 0.316). The PDR in group B was significantly higher than group A (43.2% vs. 25.7%, p<0.001). Acceptability was much higher in group B and C.10 mg bisacodyl plus 2 L PEG-ELP can significantly improve both bowel preparation quality and PDR in patients with Bristol stool form 1 and 2. Bristol stool form scale may be an easy and efficient guide for tailored bowel preparation before colonoscopy

Discovery of N‑Substituted Oseltamivir Derivatives as Potent and Selective Inhibitors of H5N1 Influenza Neuraminidase

To discover group-1-specific neuraminidase (NA) inhibitors that are especially involved in combating the H5N1 virus, two series of oseltamivir derivatives were designed and synthesized by targeting the 150-cavity. Among these, compound <b>20l</b> was the most potent N1-selective inhibitor, with IC₅₀ values of 0.0019, 0.0038, and 0.0067 μM against NAs from three H5N1 viruses. These values are better than those of oseltamivir carboxylate. Compound <b>32</b> was another potent N1-selective inhibitor that exhibited a 12-fold increase in activity against the H274Y mutant relative to oseltamivir carboxylate. Molecular docking studies revealed that the 150-cavity was an auxiliary binding site that may contribute to the high selectivity of these compounds. The present work is a significant breakthrough in the discovery of potent group-1-specific neuraminidase inhibitors, which may be further investigated for the treatment of infection by the H5N1 virus