Modeling the performance of distributed fiber optical sensor based on spontaneous Brillouin scattering

An optical model to simulate the distributed fiber optical sensor based on spontaneous Brillouin spectrum is derived. The reliability of this model is validated with experimental measurements. Using this analytical expression, parametric studies are conducted to investigate impacts of key factors including fiber loss, signal to noise ratio, bandwidth and scanning step on the optical fiber sensor measurement error. The simulation results exhibit good agreement with previous published calculation results. Applying this novel model into the data interpretation, measurement error of distributed fiber optical sensor based on spontaneous Brillouin scattering can be better controlled

Comparison theorems for multi-dimensional BSDEs with jumps and applications to constrained stochastic linear-quadratic control

In this paper, we, for the first time, establish two comparison theorems for multi-dimensional backward stochastic differential equations with jumps. Our approach is novel and completely different from the existing results for one-dimensional case. Using these and other delicate tools, we then construct solutions to coupled two-dimensional stochastic Riccati equation with jumps in both standard and singular cases. In the end, these results are applied to solve a cone-constrained stochastic linear-quadratic and a mean-variance portfolio selection problem with jumps. Different from no jump problems, the optimal (relative) state processes may change their signs, which is of course due to the presence of jumps

Constrained monotone mean-variance problem with random coefficients

This paper studies the monotone mean-variance (MMV) problem and the classical mean-variance (MV) problem with convex cone trading constraints in a market with random coefficients. We provide semiclosed optimal strategies and optimal values for both problems via certain backward stochastic differential equations (BSDEs). After noting the links between these BSDEs, we find that the two problems share the same optimal portfolio and optimal value. This generalizes the result of Shen and Zou $[$ SIAM J. Financial Math., 13 (2022), pp. SC99-SC112$]$ from deterministic coefficients to random ones

Spatial origin analysis on atmospheric bulk deposition of polycyclic aromatic hydrocarbons in Shanghai

Atmospheric deposition of polycyclic aromatic hydrocarbons (PAHs) onto soil threatens terrestrial ecosystem. To locate potential source areas geographically, a total of 139 atmospheric bulk deposition samples were collected during 2012–2019 at eight sites in Shanghai and its surrounding areas. A multisite joint location method was developed for the first time to locate potential source areas of atmospheric PAHs based on an enhanced three dimensional concentration weighted trajectory model. The method considered spatial and temporal variations of atmospheric boundary layer height and homogenized all results over the eight sites via geometric mean. Regional transport was an important contributor of PAH atmospheric deposition while massive local emissions may disturb the identification of potential source areas. Northwesterly winds were associated with elevated deposition fluxes. Potential source areas were identified by the multisite joint location method and included Hebei, Tianjin, Shandong and Jiangsu to the north, and Anhui to the west of Shanghai. PM and SO2 data from the national ground monitoring stations confirmed the identified source areas of deposited PAHs in Shanghai

sTarPicker: A Method for Efficient Prediction of Bacterial sRNA Targets Based on a Two-Step Model for Hybridization

Bacterial sRNAs are a class of small regulatory RNAs involved in regulation of expression of a variety of genes. Most sRNAs act in trans via base-pairing with target mRNAs, leading to repression or activation of translation or mRNA degradation. To date, more than 1,000 sRNAs have been identified. However, direct targets have been identified for only approximately 50 of these sRNAs. Computational predictions can provide candidates for target validation, thereby increasing the speed of sRNA target identification. Although several methods have been developed, target prediction for bacterial sRNAs remains challenging.Here, we propose a novel method for sRNA target prediction, termed sTarPicker, which was based on a two-step model for hybridization between an sRNA and an mRNA target. This method first selects stable duplexes after screening all possible duplexes between the sRNA and the potential mRNA target. Next, hybridization between the sRNA and the target is extended to span the entire binding site. Finally, quantitative predictions are produced with an ensemble classifier generated using machine-learning methods. In calculations to determine the hybridization energies of seed regions and binding regions, both thermodynamic stability and site accessibility of the sRNAs and targets were considered. Comparisons with the existing methods showed that sTarPicker performed best in both performance of target prediction and accuracy of the predicted binding sites.sTarPicker can predict bacterial sRNA targets with higher efficiency and determine the exact locations of the interactions with a higher accuracy than competing programs. sTarPicker is available at http://ccb.bmi.ac.cn/starpicker/

Study of GaN LED ITO nano-gratings with standing wave analysis

This study reveals the effect of nanoscale ITO transmission gratings on light emission from the top, sides, and bottom of a GaN light-emitting diode (LED), based on the substrate standing wave analysis. First, we show that sapphire substrate thickness affects the standing wave pattern in the LED and find the best- and worst-case sapphire thicknesses. Second, we find that adding nanoscale ITO transmission gratings can improve light extraction by 222% or 253%, depending on the reference chosen. Third, we observe that maximizing top light emission with the nano-grating can significantly reduce bottom and side light emissions. Finally, we study grating performance over different wavelengths and generate the LED spectrum

An All-Solid-State Phosphate Electrode with H3PO4 Doped Polyaniline as the Sensitive Layer

We here describe the construction of a highly sensitive and selective all-solid-state phosphate electrode based on polyaniline and H3PO4 doped polyaniline. The polyaniline layer was electroplated on the gold substrate with Chronoamperometry method and was in-situ doped by H3PO4. The Scanning Electron Microscopy-Energy Dispersive X-ray Spectroscopy (SEM, EDS) and contact angle measurement was taken to explain the difference of the two layers. This electrode can be used in both freshwater and seawater systems. In both of the two systems, the electrode exhibits linear response in the concentration range 10-1 to 10-6 M with detection limit of 10-6 M. and response time of <1 seconds. The selectivity of the electrodes was also studied in 10-1-10-5 M KH2PO4 solutions containing either 0.01 M sulfate, nitrate, chloride as the interference ions. During 12 hours continuous monitoring in 10-3 M KH2PO4 with 3.5% NaCl the potential drift was 0.05 mV/h and the lifetime of the electrode was over 40 days when preserved in this solutionpublishersversionPeer reviewe