Hydrogen sulfide and metal-enriched atmosphere for a Jupiter-mass exoplanet.

As the closest transiting hot Jupiter to Earth, HD 189733b has been the benchmark planet for atmospheric characterization 1,2,3. It has also been the anchor point for much of our theoretical understanding of exoplanet atmospheres from composition 4, chemistry 5,6, aerosols 7 to atmospheric dynamics 8, escape 9 and modeling techniques 10,11. Prior studies of HD 189733b have detected carbon and oxygen-bearing molecules H2O and CO 12,13 in the atmosphere. The presence of CO2 and CH4 has been claimed 14,15 but later disputed 12,16,17. The inferred metallicity based on these measurements, a key parameter in tracing planet formation locations 18, varies from depletion 19,20 to enhancement 21,22, hindered by limited wavelength coverage and precision of the observations. Here we report detections of H2O (13.4 sigma), CO2 (11.2 sigma), CO (5 sigma), and H2S (4.5 sigma) in the transmission spectrum (2.4-5 micron) of HD 189733b. With an equilibrium temperature of ~ 1200K, H2O, CO, and H2S are the main reservoirs for oxygen, carbon, and sulfur. Based on the measured abundances of these three major volatile elements, we infer an atmospheric metallicity of 3-5 times stellar. The upper limit on the methane abundance at 5 sigma is 0.1 ppm which indicates a low carbon-to-oxygen ratio (<0.2), suggesting formation through the accretion of water-rich icy planetesimals. The low oxygen-to-sulfur and carbon-to-sulfur ratios also support the planetesimal accretion formation pathway 23.

A reflective, metal-rich atmosphere for GJ 1214b from its JWST phase curve.

There are no planets intermediate in size between Earth and Neptune in our Solar System, yet these objects are found around a substantial fraction of other stars1. Population statistics show that close-in planets in this size range bifurcate into two classes on the basis of their radii2,3. It is proposed that the group with larger radii (referred to as 'sub-Neptunes') is distinguished by having hydrogen-dominated atmospheres that are a few percent of the total mass of the planets4. GJ 1214b is an archetype sub-Neptune that has been observed extensively using transmission spectroscopy to test this hypothesis5-14. However, the measured spectra are featureless, and thus inconclusive, due to the presence of high-altitude aerosols in the planet's atmosphere. Here we report a spectroscopic thermal phase curve of GJ 1214b obtained with the James Webb Space Telescope (JWST) in the mid-infrared. The dayside and nightside spectra (average brightness temperatures of 553 ± 9 and 437 ± 19 K, respectively) each show more than 3σ evidence of absorption features, with H2O as the most likely cause in both. The measured global thermal emission implies that GJ 1214b's Bond albedo is 0.51 ± 0.06. Comparison between the spectroscopic phase curve data and three-dimensional models of GJ 1214b reveal a planet with a high metallicity atmosphere blanketed by a thick and highly reflective layer of clouds or haze.

High-sensitivity optical fiber probe for simultaneous measurement of chloride ions and temperature.

A fiber optic probe for the simultaneous measurement of chloride ions and temperature is presented. The Ag/alginate composite film is used as the reflective surface of the Fabry-Perot interferometer (FPI) and is a sensitive film for the adsorption of chloride ions. The experimental results show that the Fabry-Perot (FP) response sensitivity is approximately 1.4689 nm/µM as the chloride ion concentration changes from 1 to 9 µM, but the fiber Bragg grating (FBG) is insensitive to chloride ions. When the temperature is changed from 35°C to 80°C, the response sensitivities of the FP and the FBG are about 0.7 and 0.01115 nm/°C, respectively.

Parallel array signal processing technology for spatial phase distortion correction in heterodyne detection.

The spatial phase distortion caused by a rough target causes a decoherence effect which, in turn, produces system sensitivity degradation. The decoherence phenomenon is the primary problem that restricts the application of active optical heterodyne detection, e.g., synthetic aperture radar and long-range coherent laser detection and ranging. By establishing a one-to-one correspondence between the combination of array signals and the system signal-to-noise ratio (SNR), a scheme for spatial phase distortion correction based on the intelligent optimization algorithm is proposed in this paper. The calculation of phase adjustments for each array signal is transformed into an optimization problem for the combination of array signals, experiments are conducted using rough target heterodyne images, and the parallel genetic algorithm (PGA) is used to calculate the phase adjustment of each array element. The results show that the spatial random phase distortion is corrected effectively without prior knowledge, and the PGA achieves an excellent computational performance which, along the efficiency of the proposed technology, has wide-scale implications for the application of active heterodyne detection and optical coherent communication.

All-fiber LP01-LP11 ultra-broadband mode converters based on T-superimposed long period gratings in PCF.

In order to cover the bandwidth of optical fiber communication, a LP01-LP11 ultra-broadband mode converter based on triple superimposed long period grating in PCF is proposed and demonstrated. The transmission spectra of the D-SLPG with gratings pitches and the T-SLPG were simulated and analyzed. The simulation results on the D-SLPG indicate that the 3 dB bandwidth of the D-SLPG is more than 1.5 times than the 3 dB bandwidth of the independent LPG and the 3 dB bandwidth of T-SLPG approaches 2.6 times as much as the independent LPG. In the experiment, the mode converter based on PCF-T-SLPG covers the wavelength of S + C + L with 3 dB bandwidth of 121 nm from 1498 nm to 1619 nm. In addition, the mode converter based on PCF-T-SLPG can accomplish ultra-broadband transmission in any wavelength by adjusting the period of gratings.

Highly sensitive temperature sensing probes based on liquid cladding elliptical micro/nanofibers.

A highly sensitive temperature probe based on a liquid cladding elliptical micro/nanofiber is proposed, which exploits a fiber loop mirror with an output port probe for remote and highly-sensitive measurements based on evanescent field coupling. The thermo-optical effective liquid cladding avoids the influence of other environmental parameters (except for temperature), while protecting the micro/nanofibers from external disturbance and contamination. This renders the sensing probe only sensitive to temperature changes, making it suitable for real-world temperature measurements. An isopropanol cladding elliptical microfiber with a diameter of 3.4 µm demonstrated a sensitivity of -16.38 nm/°C for a remote temperature measurement.

[Refractive Index Insensitive Temperature Sensor Based on Cascading Single Mode Fiber with Few Mode Fiber].

A refractive index insensitive temperature sensor is proposed base on cascading single mode fiber with few mode fiber(FMF). During the sensor preparation, the splicing current is set to 100 mA, and a section of FMF is no core-offset splicing between two single-mode fibers. Therefore, it can motivate the transmission mode preferably and form optical fiber Mach-Zehnder interferometer. The mode phase difference in FMF will be changed according to the outside environment. It will cause interference fringe shift. The parameter to be measured can be achieved by detecting the amount shift of interference spectrum. The FMF can transmit four modes with LP01, LP11, LP21, LP02. The transmission spectrum is also analyzed, which shows that they have two modes of LP01 and LP11 in sensor with the length of 81.5 mm. In the refractive index and temperature sensing experiment, the cascading FMF sensor with the length of 81.5 mm is used. The results show that the transmission spectrum of sensor appears obvious blue shift as temperature is increasing, the temperature sensitivity can be up to -85.9 pm·â„ƒ-1 within the range of 27.6~93.8 ℃ with good linearity. The refractive index sensitivity is 3.697 34 nm·RIU-1 within the range of 1.347 1~1.443 9. There is no obvious shift phenomenon in the transmission spectrum with the feature of refractive index insensitive. Therefore, compared with the traditional cladding mode and multimode interferometric fiber-optic sensor, the proposed sensor based on FMF is easier to control and analyze transmission mode has the advantages of simple structure, easy process and high sensitivity. It can avoid cross-sensitivity between temperature and refractive index measurement. Thus, it can be used for temperature detection of power system, biomedicine, aerospace and other fields.

Refractive index insensitive temperature sensor based on specialty triple-clad fiber.

A refractive index (RI) insensitive temperature sensor based on specialty triple-clad fiber (STCF) is proposed. Based on coupling mode theory, the STCF can be equivalent to a rod waveguide and two tube waveguides. Then the cladding mode resonance characteristic of STCF is analyzed by calculating different mode dispersion curves, which indicates that it works only on the mode resonance from core to the fluorine-doped silica cladding, and finally a resonance wavelength can be obtained. Two straightforward experiments are performed to prove its sensing properties. Experimental results show that it has sensitivities of 72.17 pm/°C at temperature range from 35°C~95°C with characteristics of insensitive to external RI in the range from 1.3450 to 1.4607. Thus, this proposed sensor can be used for solution temperature monitoring in real time.

[The nitrate and temperature impact analysis in the detection of COD by UV spectrum].

Configured standard solution of chemical oxygen demand with potassium hydrogen phthalate was used as experimental subjects, collected ultraviolet absorption spectra of the standard solution in the range of 1,800 mg x L(-1), were collected, and PLS (partial least squares) algorithm was used to establish the correction model of different spectral region, the results showed that. The model in the spectral region of 265-310 nm had the highest correlation and smallest error; In order to eliminate the impact of nitrates and temperature on the detection of the COD , studied the changes of the UV absorption spectrum with different concentrations of sodium standard solution and different temperature. The results showed that absorption of nitrate in 208-238 nm was apparent, and the model for spectral region of 265-310 nm was free from the influence of nitrate; In the full range of spectrum, temperature rising leads to an increase in absorbance, thus the temperature compensation model was established for the different spectral region through predictive analysis.

[The turbidity and pH impact analysis of low concentration water chemical oxygen demand ultraviolet absorption detection].

Configuration standard solution in the concentration range of 1 - 25 mg x L(-1) of potassium hydrogen phthalate was used as experimental subject, Ultraviolet absorption spectra was collected, the COD quantitative analysis model was established by partial least squares with different pretreatment methods and the turbidity of the compensation effect analysis was given. The results show the model uses smoothing first derivative pretreatment method, internal cross validation RMSECV root mean square value of 0.122 27, principal component number 4, the square of the prediction model correlation coefficient is 0.999 8, and the relative prediction error is in the range of 0.03%-1.7%; for 0-100 NTU's turbidity solution, the relative standard deviation RSD is 2.3% after compensation; with pH in the range of 3-10, influence can be ignored.

Antiepileptic drug concentration detection based on Raman spectroscopy and an improved snake optimization-convolutional neural network algorithm.

A method for measurement of antiepileptic drug concentrations based on Raman spectroscopy and an optimization algorithm for mathematical models are proposed and investigated. This study uses Raman spectroscopy to measure mixed antiepileptic drugs, and an Improved Snake Optimization (ISO)-Convolutional Neural Network (CNN) algorithm is proposed. Raman spectroscopy is widely used in the identification of pharmaceutical ingredients due to its sharp peaks, no pre-treatment of samples and non-destructive detection. To analyze the spectral data precisely, a machine learning method is used in this paper. The ISO algorithm is an improved intelligent swarm algorithm in which the method of generating random solutions is improved, which can ensure that a comprehensive local search of the model is performed, the global search capability is maintained at a later stage, and the convergence speed is accelerated. In this study, 360 groups of oxcarbazepine, carbamazepine, and lamotrigine drug mixtures are measured using Raman spectroscopy, and the raw spectral data after pre-processing are trained and evaluated using ISO-CNN algorithms, and the results are compared and analyzed with those obtained from other algorithms such as the Northern Goshawk Optimization algorithm, Chameleon Swarm Algorithm, and White Shark Optimizer algorithm. The results show that the best ISO-CNN algorithm training is achieved for oxcarbazepine, with a determination coefficient and root mean square error of 0.99378 and 0.0295 for the validation set, and 0.99627 and 0.0278 for the test set. The overall results suggest that Raman spectroscopy combined with machine learning algorithms can be a potential tool for drug concentration prediction.

A detection method of typical toxic mixed red tide algae in Qinhuangdao based on three-dimensional fluorescence spectroscopy.

Red tides occur every year in the Qinhuangdao sea area of China, including a variety of toxic algae and non-toxic algae. Toxic red tide algae have caused great damage to the marine aquaculture industry in China and seriously endangered human health, but most of non-toxic algae are important bait for marine plankton. Therefore, it is very important to identify the type of mixed red tide algae in Qinhuangdao sea area. In this paper, three-dimensional fluorescence spectroscopy and chemometrics were applied to the identification of typical toxic mixed red tide algae in Qinhuangdao. Firstly, the three-dimensional fluorescence spectrum data of typical mixed red tide algae in Qinhuangdao sea area were measured by f-7000 fluorescence spectrometer, and the contour map of algae samples was obtained. Secondly, the contour spectrum analysis is carried out to find the excitation wavelength of the peak position of the three-dimensional fluorescence spectrum and form the new three-dimensional fluorescence spectrum data selected by the feature interval. Then, the new three-dimensional fluorescence spectrum data are extracted by principal component analysis (PCA). Finally, the feature extraction data and the data without feature extraction are used as the input of the genetic optimization support vector machine (GA-SVM) and particle swarm optimization support vector machine (PSO-SVM) classification models, respectively, to obtain the classification model of mixed red tide algae, and the two feature extraction analysis methods and two classification algorithms are compared. The results show that the classification accuracy of the test set using the principal component feature extraction and GA-SVM classification method is 92.97 %, when the excitation wavelengths are 420 nm, 440 nm, 480 nm, 500 nm and 580 nm, and the emission wavelengths are 650-750 nm. Therefore, it is feasible and effective to apply the three-dimensional fluorescence spectrum characteristics and genetic optimization support vector machine classification method to the identification of toxic mixed red tide algae in Qinhuangdao sea area.

[Research on and application of hybrid optimization algorithm in Brillouin scattering spectrum parameter extraction problem].

This paper presents a novel algorithm which blends optimize particle swarm optimization (PSO) algorithm and Levenberg-Marquardt (LM) algorithm according to the probability. This novel algorithm can be used for Pseudo-Voigt type of Brillouin scattering spectrum to improve the degree of fitting and precision of shift extraction. This algorithm uses PSO algorithm as the main frame. First, PSO algorithm is used in global search, after a certain number of optimization every time there generates a random probability rand (0, 1). If rand (0, 1) is less than or equal to the predetermined probability P, the optimal solution obtained by PSO algorithm will be used as the initial value of LM algorithm. Then LM algorithm is used in local depth search and the solution of LM algorithm is used to replace the previous PSO algorithm for optimal solutions. Again the PSO algorithm is used for global search. If rand (0, 1) was greater than P, PSO algorithm is still used in search, waiting the next optimization to generate random probability rand (0, 1) to judge. Two kinds of algorithms are alternatively used to obtain ideal global optimal solution. Simulation analysis and experimental results show that the new algorithm overcomes the shortcomings of single algorithm and improves the degree of fitting and precision of frequency shift extraction in Brillouin scattering spectrum, and fully prove that the new method is practical and feasible.

Identification of ichthyotoxic red tide algae based on three-dimensional fluorescence spectra and particle swarm optimization support vector machine.

Acccurate identification whether red tide has ithyotoxicity is very significant for microalgae monitoring. In order to realize the rapid and non-destructive detection of ichthyotoxic red tide algae, a detection method combining three-dimensional (3D) fluorescence spectrum and particle swarm optimization support vector machine (PSO-SVM) was developed to monitor the ichthyotoxic red tide algae with cell concentrations from 104 cells/mL to 106 cells/mL. The contour maps contracted form three-dimensional fluorescence spectra of six common species of ichthyotoxic algae and eight common species of non-ichthyotoxic algae,which are analyzed to select the optimal emission and excitation wavelength span. The new feature data are acquired by using the emission spectrum data at 480 nm and 510 nm excitation wavelengths. The new feature data are used as the input of particle swarm optimization support vector machine to establish the optimal classification model of ichthyotoxic algae, which achieves an classification accuracy of 100% for the test set. The optimal classification model is successfully applied to identify the ichthyotoxicity of different algae including Heterosigma akashiwo, Chattonella marina, Phaeocystis globosa, Prorocentrum donghaiense, Karenia dunnii, Isoscelina galbana, Isosceles globosa and Skeletonema costatum.

[Determination of chemical oxygen demand in water using near infrared transmission and UV absorbance method].

Chemical oxygen demand (COD) is a synthetical indicator which represents the degree of organic pollution in water. The near-infrared (NIR) transmission and the UV absorbance method based on photoelectric detection technology and spectroscopy analysis have some advantages such as high precision, speed, non-contact, no secondary pollution etc compared to conventional wet chemical method. The NIR transmission spectra and UV absorbance spectra of standard solution configured with phthalate hydrogen potassium were collected respectively by MPA FTIR spectrometer (Bruker Optics Inc.) made in Germany and AvaSpec-2048-2 UV spectrometer (Avantes Inc.) made in Netherlands. After different pretreatment to the spectra, COD quantitative analysis model was established using partial least squares regression (PLS) and linear regression. The statistical analysis of COD quantitative model was implemented, and the result showed that UV absorbance method had a higher relevance but lower forecast accuracy and precision than NIR transmission method.

[Immune protection of tegument protein rSj29 against Schistosoma japonicum in mice].

OBJECTIVE: To clone, express and characterize a tegument protein gene of Schistosoma japonicum (Sj29) , and investigate the immune protection of the recombinant protein against S. japonicum in mice. METHODS: The gene coding for Sj29 protein was amplified by PCR, and the sequence was analyzed by bioinformatics tools. Partial fragment of Sj29 gene was subcloned into the prokaryotic expression vector pET28c(+). The recombinant plasmid was transformed into E. coli BL21 (DE3) and induced the recombinant with IPTG. The recombinant protein (rSj29) was purified by His-binding-resin affinity chromatography and characterized by Western blotting. Three groups each with 10 BALB/c mice were immunized subcutaneously three times (two weeks interval) respectively with 100 microl recombinant rSj29 (0.1 mg/ml) , adjuvant or PBS. At the 15th day after the final inoculation, each mouse was challenged by 40 +/- 2 cercariae of S. japonicum. At the 53rd day after infection, the mice were sacrificed to obtain the number of adult worms, number of eggs in liver and feces. Serum samples were collected at pre-immunization and certain time after immunization, and were analyzed for IgG by ELISA. The localization of rSj29 in worms of different developmental stages was demonstrated by immunofluorescent technique. mRNA expression level of Sj29 gene in worms of different developmental stages and three groups after infection was detected by quantitative real-time PCR. RESULTS: A 576 bp Sj29 gene fragment was obtained. The recombinant protein rSj29 with Mr 22,900 was expressed in the form of inclusion body. The recombinant rSj29 can be recognized by sera of mice immunized with rSj29 and sera of infected mice. The number of adult worms (15.4 +/- 5.9), number of hepatic eggs (40,143.3 +/- 2,995.9) and number of fecal eggs (3,803.9 +/- 110.9) in recombinant protein group were significantly higher than those of PBS control group (20 +/- 3.4, 49,318.1 +/- 6,648.3, 5,238.1 +/- 303.5, respectively) (P < 0.05) . There was a high level of specific IgG against rSj29 (maximum dilution 1:32000) in recombinant protein group. Immunohistochemical analysis showed the Sj29 protein expressed on the surface of different stages of S. japonicum. mRNA level of Sj29 was the highest at the 32nd day post-infection. CONCLUSION: The recombinant protein rSj29 induces certain degree of protective immunity in mice.