Non-centrosymmetric metal chalcogenides such as AgGaS2 and AgGaSe2 are two of the commercial nonlinear optical (NLO) crystals widely used in the infrared (IR) region. Nevertheless, the inherent incompatibility between the wide energy gap (Eg) and large second-harmonic generation (SHG) efficiency (dij) hinders their high-power laser applications. Recently, the development of salt-inclusion chalcogenides with non-centrosymmetric structures has attracted more and more attention and interest owing to their intensive potential applications originating from their wide Eg, strong dij, ultrahigh laser-induced damage thresholds (LIDTs) and large IR transmission range. In this frontier paper, we review the recent progress of salt-inclusion chalcogenides (including 28 related compounds) as favourable candidates for IR-NLO materials, which can be divided into 3 types according to their chemical compositions and structural characteristics (i) the [RaXb][GanQ2n] type and its derivatives, (ii) [NaBa4Cl][Ge3S10] and its derivatives, and (iii) the [A3X][MB12(MQ4)3] type. The relationships between the non-centrosymmetric structures and NLO properties of these 3 types of compounds are summarized and briefly remarked. In addition, the present challenges of creating new IR-NLO salt-inclusion chalcogenides and future perspectives in this field are discussed.Natural estrogens such as 17α-estradiol (E2α), 17β-estradiol (E2β), estrone (E1), and estriol (E3), released to surface waters from both urban and agricultural sources, are endocrine disrupting for fish. Here, we assess the prevalence of livestock farming derived natural estrogens in tributaries and ponds in the agriculturally dominated catchment of Lake Baldegg, Switzerland.  https://www.selleckchem.com/products/dn02.html  Passive samplers were deployed in the main tributary and daily time-proportional water samples were collected in five tributaries for 30 days at the beginning of the vegetation period. Furthermore, we took grab samples of 12 ponds in the catchment. Aqueous samples were liquid-liquid extracted, derivatized, and analysed with LC-MS/MS and stream water samples additionally with ERα-CALUX, a bioassay for assessing total estrogenic activity. Natural estrogens were regularly detected, with mean concentrations ranging from below the limit of detection to 0.55 ng L-1 for E2β and E1, respectively, and passive sampling and bioassay results largely confirmed these findings. Monte Carlo simulated mean natural estrogen concentrations underestimated measured ones by a factor of three to 11. An agricultural area's hydrological contribution and connectivity to surface waters seemed to be more important for the development of estrogen concentrations in streams than livestock densities in a catchment or the actual loads of slurry applied. Pond water occasionally contained natural estrogens in concentrations up to 8.6 ng L-1 for E2α. The environmental quality standards of the European Union (0.4 ng L-1 for E2β and 3.6 ng L-1 for E1) were never exceeded for longer than a day in tributaries, but E1 reached critical concentrations for aquatic organisms in ponds.Using two different action spectroscopic techniques, a high-resolution quantum cascade laser operating around 1300 cm-1 and a cryogenic ion trap machine, the proton shuttle motion of the cations HHe2+ and HHe3+ has been probed at a nominal temperature of 4 K. For HHe3+, the loosely bound character of this complex allowed predissociation spectroscopy to be used, and the observed broad features point to a lifetime of a few ps in the vibrationally excited state. For He-H+-He, a fundamental linear molecule consisting of only three nuclei and four electrons, the method of laser-induced inhibition of complex growth (LIICG) enabled the measurement of three accurate rovibrational transitions, pinning down its molecular parameters for the first time.Incorporating poly(lactic-co-glycolic) acid (PLGA) microparticles into human mesenchymal stem cells (hMSC) aggregates has shown promising application prospects. However, the acidic degradation products and burst release of PLGA microparticles still need to be ameliorated. In this study, the PLGA/chitosan-heparin (P/C-h) composite microparticles were successfully fabricated by integrating the double emulsion and microfluidic technology through the precise manipulation of the emulsion composition and flow rate of the two-phase in a flow-focusing chip. The P/C-h microparticles were highly monodispersed with a diameter of 23.45 ± 0.25 μm and shell-core structure of the PLGA encapsulated C-h complex, which were suitable for the fabrication of hMSC aggregates. When the mass ratio of PLGA to the C-h complex was optimized to 2  1, the pH of the leach liquor of P/C-h microparticles remained neutral. Compared with those of PLGA microparticles, the cytotoxicity and the initial burst release (loaded FGF-2 and VEGF) were both significantly reduced in P/C-h microparticles. Furthermore, the survival, stemness, as well as secretion and migration abilities of cells in hMSC aggregates incorporating P/C-h microparticles were also enhanced. In summary, the P/C-h composite microparticles prepared by the droplet microfluidic technique support the optimal biological and functional profile of the hMSC aggregates, which may facilitate the clinical applications of MSC-based therapy.Although good performance has been reported in shallow neural networks, the application of memristor synapses towards realistic deep neural networks has met more stringent requirements on the synapse properties, particularly the high precision and linearity of the synaptic analog weight tuning. In this study, a LiAlOX memristor synapse was fabricated and optimized to address these demands. By delicately tuning the initial conductance states, 120-level continuously adjustable conductance states were obtained and the nonlinearity factor was substantially reduced from 8.96 to 0.83. The significant enhancements were attributed to the reduced Schottky barrier height (SBH) between the filament tip and the electrode, which was estimated from the measured I-V curves. Furthermore, a deep neural network for realistic action recognition task was constructed, and the recognition accuracy was found to be increased from 15.1% to 91.4% on the Weizmann video dataset by adopting the above-described device optimization method.