Constitutive Activation of the Thyroid-Stimulating Hormone Receptor (TSHR) by Mutating Ile691 in the Cytoplasmic Tail Segment

/inositol phosphate (IP) pathways, which stimulate thyroid hormone production and thyroid proliferation./IP signaling pathway./IP cascade

A Visualization Approach to Air Pollution Data Exploration—A Case Study of Air Quality Index (PM2.5) in Beijing, China

In recent years, frequent occurrences of significant air pollution events in China have routinely caused panic and are a major topic of discussion by the public and air pollution experts in government and academia. Therefore, this study proposed an efficient visualization method to represent directly, quickly, and clearly the spatio-temporal information contained in air pollution data. Data quality check and cleansing during a preliminary visual analysis is presented in tabular form, heat matrix, or line chart, upon which hypotheses can be deduced. Further visualizations were designed to verify the hypotheses and obtain useful findings. This method was tested and validated in a year-long case study of the air quality index (AQI of PM2.5) in Beijing, China. We found that PM2.5, PM10, and NO2 may be emitted by the same sources, and strong winds may accelerate the spread of pollutants. The average concentration of PM2.5 in Beijing was greater than the AQI value of 50 over the six-year study period. Furthermore, arable lands exhibited considerably higher concentrations of air pollutants than vegetation-covered areas. The findings of this study showed that our visualization method is intuitive and reliable through data quality checking and information sharing with multi-perspective air pollution graphs. This method allows the data to be easily understood by the public and inspire or aid further studies in other fields

An algorithm for highway vehicle detection based on convolutional neural network

Abstract In this paper, we present an efficient and effective framework for vehicle detection and classification from traffic surveillance cameras. First, we cluster the vehicle scales and aspect ratio in the vehicle datasets. Then, we use convolution neural network (CNN) to detect a vehicle. We utilize feature fusion techniques to concatenate high-level features and low-level features and detect different sizes of vehicles on different features. In order to improve speed, we naturally adopt fully convolution architecture instead of fully connection (FC) layers. Furthermore, recent complementary advances such as batch-norm, hard example mining, and inception have been adopted. Extensive experiments on JiangSuHighway Dataset (JSHD) demonstrate the competitive performance of our method. Our framework obtains a significant improvement over the Faster R-CNN by 6.5% mean average precision (mAP). With 1.5G GPU memory at test phase, the speed of the network is 15 FPS, three times faster than the Faster R-CNN

Construction of dual heterogeneous interface between zigzag-like Mo–MXene nanofibers and small CoNi@NC nanoparticles for electromagnetic wave absorption

Two-dimensional (2D) transition metal carbides (MXene) possess attractive conductivity and abundant surface functional groups, providing immense potential in the field of electromagnetic wave (EMW) absorption. However, high conductivity and spontaneous aggregation of MXene suffer from limited EMW response. Inspired by dielectric–magnetic synergy effect, the strategy of decorating MXene with magnetic elements is expected to solve this challenge. In this work, zigzag-like Mo2TiC2–MXene nanofibers (Mo-based MXene (Mo–MXene) NFs) with cross-linked networks are fabricated by hydrofluoric acid (HF) etching and potassium hydroxide (KOH) shearing processes. Subsequently, Co-metal–organic framework (MOF) and derived CoNi layered double hydroxide (LDH) ultrathin nanosheets are grown inside Mo–MXene NFs, and the N-doped carbon matrix anchored by CoNi alloy nanoparticles formed by pyrolysis is firmly embedded in the Mo–MXene NFs network. Benefiting from synergistic effect of highly dispersed small CoNi alloy nanoparticles, a three-dimensional (3D) conductive network assembled by zigzag-like Mo–MXene NFs, numerous N-doped hollow carbon vesicles, and abundant dual heterogeneous interface, the designed Mo–MXene/CoNi–NC heterostructure provides robust EMW absorption ability with a reflection loss (RL) value of −68.45 dB at the thickness (d) of 4.38 mm. The robust EMW absorption performance can be attributed to excellent dielectric loss, magnetic loss, impedance matching (Z), and multiple scattering and reflection triggered by the unique 3D network structure. This work puts up great potential in developing advanced MXene-based EMW absorption devices.</p

Distribution of Cu Ions in Lanthanum-Modified CuHY Zeolite and Its Influence on Adsorption Desulfurization Performance

The Cu-loaded CuHY and CuLaHY zeolites were prepared by an incipient wetness method under nitrogen gas atmosphere. The samples were characterized by X-ray diffraction (XRD), N(2) adsorption, NH(3) temperature-programmed desorption, and X-ray photoelectron spectroscopy. The crystalline structure and the distribution of Cu(2+) cations in the cages of Y zeolite were determined by XRD. The adsorption desulfurization performance of the zeolites was investigated for model diesel containing dibenzothiophene (DBT). The results showed that most of Cu species from the precursor CuCl(2) was ion-exchanged with the HY and LaHY zeolites. For the La(3+)-modified CuHY zeolite (Cu-LaHY), the Cu(2+) cations entering the supercages of the zeolite coordinated with both skeleton-oxygen atoms and water molecules, and thus being firmly situated at the sites Sri and Sill in the supercages. For the CuHY zeolite, however, Cu(2+) cations entering the supercages were only near the sites S(II) and S(III) in the supercages. A very small percentage of CuCl molecules was highly scattered in the cages of the Y zeolite, with no definite position. The Cu(2+) cations at the sites S(II) and S(III) in the supercages adsorbed DBT molecules in the model diesel were the centers of adsorption desulfurization. The desulfurization capacity of the CuLaHY zeolite was better as compared with the CuHY zeolite. However, naphthalene molecules will result in competitive adsorption with DBT molecules if there are naphthalene molecules in the model diesel