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A hypophosphorous acid-based ionic liquid [Bmim]H2PO2 (BMP) was synthesized and characterized by FTIR, 1HNMR, 13CNMR and 31PNMR. Moreover, a new intumescent flame-retardant system composed of BMP and expandable graphite (EG) was used to improve the flame retardancy of high-density polyethylene-based wood–plastic composites (WPC). The retardant properties and thermal decomposition behaviors were investigated by the limiting oxygen index (LOI) test, UL-94 vertical burning test, thermogravimetric analysis (TGA) and cone calorimeter test, respectively. When the mass ratio of BMP to EG was 1:2 and the total amount was kept at 30 mass%, WPC/EG-BMP composite passed UL-94 V-0 rating, and its LOI value increased to 31.5% from 21.4% for neat WPC. In addition, both the peak heat release rate and the total heat release of WPC/BMP-EG composite decreased significantly relative to WPC and WPC/EG composites according to cone calorimeter analysis. The TGA results suggested that BMP had good ability of char formation, and when combined with EG, it could greatly promote the formation of the protective char layer. The surface morphology and chemical structure of char residues were examined using scanning electron microscope–energy-dispersive spectrometer and Raman spectroscopy. It revealed that a compact and thick char layer was formed with the combination of BMP and EG, which hinder the transfer of heat flow and combustible gases in the condensed phase, thus exhibiting excellent flame retardancy. This study demonstrated that BMP and EG had a synergistic effect on the flame retardancy of WPC.

In this study, three carbazole-coumarin hybrid dyes were successfully synthesized, and their UV-vis absorption spectra, fluorescence spectra, and structural properties were investigated. The results indicated that diethyl 12-hexyl-2,9-dioxo-9,12-dihydro-2H-dipyrano[2,3-b:3',2'-h]-carbazole-3,8-dicarboxylate showed a slight red shift of the maximum absorption wavelength, and its fluorescence intensity was above 4000 arb units, about 22 times higher than that of ethyl 10-hexyl-8-hydroxy-2-oxo-2,10-dihydropyrano[2,3-b]carbazole-3-carboxylate and ethyl 10-hexyl-8-(hexyloxy)-2-oxo-2,10-dihydropyrano[2,3-b]carbazole-3-carboxylate in CHCl3. The fluorescence intensity of the three compounds first increases and then decreases with the rise of concentration, and the maximum emission wavelength shows a slight red shift. The stability pH range of diethyl 12-hexyl-2,9-dioxo-9,12-dihydro-2H-dipyrano[2,3-b:3',2'-h]carbazole-3,8-dicarboxylate in THF was 2–10.

In this study, we designed and synthesized a simple probe 2-(8-((8-methoxyquinolin-2-yl)methoxy)quinolin-2-yl)benzo[d]thiazole (DQT) for detection of Ag+ and Cd2+ in a CH3OH/HEPES (9 : 1 v/v, pH = 7.30) buffer system. Its structure was characterized by NMR, ESI-HR-MS and DFT calculations, and its fluorescence performance was also investigated. Probe DQT showed fluorescence quenching in response to Ag+ and Cd2+ with low detection limits of 0.42 μM and 0.26 μM, respectively. Importantly, the complexation of the probe with Cd2+ resulted in a red shift from blue to green, making it possible to detect Ag+ and Cd2+ by the naked eye under an ultraviolet lamp. The DQT-Cd2+ complex could be used for sequential recognition of S2−. The recovery response could be repeated 3 times by alternate addition of Cd2+ and S2−. A filter paper strip test further demonstrated the potential of probe DQT as a convenient and rapid assay.

Computer modeling and simulation is fast-moving towards clinical applications to advance cardiac diagnosis and aid treatment planning. As cardiac models become more popular and useful, the need to tailor these models for individual subjects has grown. Therefore, model identification becomes an important step of cardiac modeling. Cardiac model identification is a challenging task, particularly for simulation in high organizational scales such as tissue and organ scales, as the models are nonlinear and involve hidden ion channel gating variables. In this study, we proposed a two-stage model calibration algorithm to estimate the parameters of cardiac tissue model using membrane potential data. Specifically, an ensemble Kalman Filter (EnKF) is used in the first stage to track the membrane potentials and the hidden ion channel gating variables; the outputs from the EnKF are used as the initial values to calculate forward prediction in the second stage. The optimization algorithm minimizes the sum of squared errors in both stages through a coarse and a fine optimization. The proposed method is validated through multiple simulation designs, which shows good accuracy and efficiency.

In this study, a BODIPY-based water-soluble fluorescent chemosensor BBP has been synthesized using BODIPY as the fluorescence group and quinoline as the recognition group. BBP can be used for naked eye detection of pH in complete aqueous solution and it shows high specificity in a wide range of cations. The pKa value is determined to be 2.94 and the fluorescence intensity is linearly related to pH in the range of 2.4-3.6.

A Ru-catalyzed selective and atom-economic ortho-C–H allylation of aromatic acids with vinylcyclopropanes is reported. The reaction proceeds with selective cleavage of both a C–H and a C–C bond. A ...

A catalytic annulation is presented that provides straightforward, modular synthetic access to 3-substituted indanones from benzoic acids and α,β-unsaturated ketones. It is catalyzed by a bimetalli...

Statistical modeling using ground-based PM2.5 observations and satellite-derived aerosol optical depth (AOD) data is a promising means of obtaining spatially and temporally continuous PM2.5 estimations to assess population exposure to PM2.5. However, the vast amount of AOD data that is missing due to retrieval incapability above bright reflecting surfaces such as cloud/snow cover and urban areas challenge this application. Furthermore, most previous studies cannot directly account for the spatiotemporal autocorrelations in PM2.5 distribution, impacting the associated estimation accuracy. In this study, fixed rank smoothing was adopted to fill the data gaps in a semifinished 3 km AOD dataset, which was a combination of the Moderate Resolution Imaging Spectroradiometer (MODIS) 3 km Dark Target AOD data and MODIS 10 km Deep Blue AOD data from the Terra and Aqua satellites. By matching the gap-filled 3 km AOD data, ground-based PM2.5 observations, and auxiliary variable data, sufficient samples were screened to develop a spatiotemporal regression kriging (STRK) model for PM2.5 estimation. The STRK model achieved notable performance in a cross-validation experiment, with a R square of 0.87 and root-mean-square error of 16.55 μg/m3 when applied to estimate daily ground-level PM2.5 concentrations over East China from March 1, 2015 to February 29, 2016. Using the STRK model, daily PM2.5 concentrations with full spatial coverage at a resolution of 3 km were generated. The PM2.5 distribution pattern over East China can be identified at a relatively fine spatiotemporal scale. Thus, the STRK model with gap-filled high-resolution AOD data can provide reliable full-coverage PM2.5 estimations over large areas for long-term exposure assessment in epidemiological studies.

Cytoplasmic effects (CEs) have been discovered to influence a diverse array of agronomic traits in crops, and understanding the underlying mechanisms can help accelerate breeding programs. Seed oil content (SOC) is of great agricultural, nutritional, and economic importance. However, the genetic basis of CEs on SOC (CE-SOC) remains enigmatic. In this study, we use an optimized approach to sequence the cytoplasmic (plastid and mitochondrial) genomes of allotetraploid oilseed rape (Brassica napus) cultivars, 51218 and 56366, that bear contrasting CE-SOC. By combining comparative genomics and genome-wide transcriptome analysis, we identify mitochondria-encoded orf188 as a potential CE-SOC determinant gene. Functional analyses in the model system Arabidopsis thaliana and rapeseed demonstrated that orf188 governs CE-SOC and could significantly increase SOC, strikingly, through promoting the yield of ATP. Consistent with this finding, transcriptional profiling with microarray and RNA sequencing revealed that orf188 affects transcriptional reprogramming of mitochondrial energy metabolism to facilitate ATP production. Intriguingly, orf188 is a previously uncharacterized chimeric gene, and the presence of this genetic novelty endows rapeseed with positive CE-SOC. Our results shed light on the molecular basis of CEs on a key quantitative trait in polyploid crops and enrich the theory of maternal control of oil content, providing new scientific guidance for breeding high-oil rapeseed germplasms.

Polychlorinated biphenyls (PCBs) found in marine molluscs could be a serious threat to the health of consumers; however, studies on this subject are limited. To understand this threat, the indicator PCBs (PCB-28, PCB-52, PCB-101, PCB-118, PCB-138, PCB-153 and PCB-180) found in six different kinds of molluscs were determined, and the associated cancer risk for consumers that intake these indicator PCBs via molluscs was assessed. The total concentrations of PCBs in molluscs ranged from 17.51 to 47.43 ng/g (d.w.). The order of contamination levels for indicator PCBs in molluscs was Perna viridis > Ruditapes philippinarum > Crassostrea gigas > Mimachlamys nobilis > Glossaulax didyma > Anadara antiquata. Tri-, tetra- and penta-PCBs were the dominant congeners in molluscs from Haikou City. Tetra-PCBs are the most common PCB, accounting for 38.49% of total PCBs. Compared with previous global studies on PCBs in molluscs, the pollution level of indicator PCBs in the molluscs from Haikou City was lower than most of reports in Europe and China, but higher than those from France and Korea, suggesting a moderate pollution level. The 50% and 95% cancer risks of indicator PCBs in molluscs for adult consumers were 2.75 × 10-7 and 4.32 × 10-7, indicating that the cancer risk was at an acceptable level. Since the dioxin like-PCBs were not analyzed in this study, the cancer risk of PCBs to human health might be underestimated; therefore, more studies on PCB pollution in molluscs are required.

In this study, a highly selective chemosensor ML based on a BODIPY fluorescent chromophore was synthesized for sequential recognition of Cu2+ and HSO3− in a CH3OH/H2O (99 : 1 v/v) system, which contained three recognition sites and its structure characterized by 1H NMR, 13C NMR and ESI-HR-MS. The sensor ML showed an obvious “on–off” fluorescence quenching response toward Cu2+ and the ML-Cu2+ complex showed an “off–on” fluorescence enhancement response toward HSO3−. The detection limit of the sensor ML was 0.36 μM to Cu2+ and 1.4 μM to HSO3−. In addition, the sensor ML showed a 1 : 3 binding stoichiometry to Cu2+ and the recovery rate of ML-Cu2+ complex identifying HSO3− could be over 70%. Sensor ML showed remarkable detection ability in a pH range of 4–8.

The variety of sensors embedded in smartphones makes it possible to develop indoor navigation and localization systems on mobile terminals. However, these cheap sensors are plagued by bias and noise, leading to unbounded system drifts. Inspired by Expectation-Maximization algorithm, this paper proposes to combine zero-velocity detection with gated recurrent unit (GRU) neural networks, make full use of pedestrian motion characteristics, and naturally and accurately split the raw measurements into multiple weakly correlated windows step by step. The GRU is used to exploit dynamic context and predict the polar vector of each window. Several experiments were conducted to test the performance of proposed model, and IONet, a deep learning based inertial odometry model using fixed-size sliding window, was taken as a reference. The results show that the proposed model is able to generate smooth trajectories with high precision. Compared with IONet, the performance of proposed model in turning is better.

Fully Convolutional Network (FCN), which can adopt various Convolutional Neural Networks (CNN), are now increasingly being used in remote sensing communities. CNN are improved constantly either in accuracy or by reducing parameters for a given equivalent accuracy. This paper investigates five widely used CNNs (AlexNet, VGG16, ResNet, SqueezeNet, and a pruned VGG16) in the context of FCN for coastal beach classification of imagery acquired by Unmanned Aerial Vehicles (UAV). Our experiments show that (1) not every CNN is suitable to FCN for semantic segmentations of images though each CNN approximately achieved an equivalent accuracy for image labeling; (2) band reduced pruning of existing CNN has the least impact on implementation and accuracy. To examine the capability of convolutional layers capturing semantic features, this paper also carries out beach classification experiments using hypercolumn methods with VGG16.

The predicted wind power in coastal waters is an important factor when planning and developing offshore wind farms. The stochastic wind field challenges the accuracy of these predictions. Using single-point wind measurements, most previous studies have focused on the prediction of short-term wind power, ranging from minutes to several days. Longer-term wind power predictions would better support decision-making related to offshore wind power balance management and reserve capacities. In addition, larger-scale wind power predictions, based on gridded wind field data, would provide a more comprehensive understanding of the spatiotemporal variations of wind energy resources. In this study, a spatiotemporal ordinary kriging model was developed to predict the offshore wind power density on a monthly basis using the cross-calibrated multiplatform gridded wind field data. The spatiotemporal variations of wind power density were directly quantified through the development of spatiotemporal variograms that integrated spatial and temporal distances. The proposed model achieved a notable performance with an overall R2 of 0.94 and a relative prediction error of 16.35% in the validation experiment of predicting the monthly wind power density from 2013 in the coastal waters of China’s Guangdong Province. Using this model, the spatial distributions of wind power density along Guangdong’s coastal waters at monthly, seasonal, and annual time-scales from 2013 were accurately predicted. The experiment results demonstrated the remarkable potential of the spatiotemporal ordinary kriging model to provide reliable long-term prediction for offshore wind energy resources.

Triclocarban (TCC) is an antibacterial agent commonly found in environmental, wildlife, and human samples. However, with in-depth study of TCC, its negative effects are increasingly presented. Toxicological studies of TCC at environmentally relevant concentrations have been conducted in zebrafish embryos and indicated that TCC leads to deformity of development causes developmental deformities. However, the molecular mechanisms underlying the toxicity of TCC in zebrafish embryos have not been entirely elucidated. We investigated whether exposure to TCC at environmentally relevant concentrations induces endoplasmic reticulum (ER) stress and unfolded protein response (UPR) in zebrafish. Zebrafish embryos were grown to 32 hours post fertilization and exposed to 2.5, 5, and 10 μg/L TCC and used in whole-mount in situ hybridization to visualize the expression of ER chaperone hspa5 and ER stress-related apoptosis factor chop. Zebrafish livers were exposed to different concentrations of TCC to elaborate the relationships between fatty degeneration and ER stress. Then, a human hepatic cell line (HL-7702) was used to test whether TCC induced ER stress in human livers similar to those of zebrafish. In zebrafish embryos, TCC induced high hspa5 expression, which could defend against external stimulations. Furthermore, hapa5, hsp90b1, and chop exhibited ectopic expressions in the neuromast, intestinal tract, and tail tip of zebrafish embryos. On the one hand, significant differences were observed in the mRNA and protein expressions of the ER stress molecular chaperone pPERK-pEIF2a-ATF4 and ATF6 pathways in HL-7702 cells exposed to TCC. On the other hand, lipid droplet accumulation slightly increased in zebrafish livers exposed to 10 μg/L TCC in vitro. These results demonstrate that TCC not only damages the development of zebrafish embryos and structure of zebrafish liver but also influences human hepatic cells by activating ER stress and the UPR signaling pathway.

Surfactants are often required to reduce emulsion viscosity and heavy-oil flow resistance in pipelines, thereby forming a stable oil-in-water emulsion under shear stress. This study aimed to quanti...

Background: Metal organic compounds have attracted considerable attention since the advent of Salvarsan, a metal organic compound for the treatment of syphilis. Ferrocene as an effective phenyl bioisostere is becoming a viable platform for drug design by virtue of its redox properties, high lipophilicity and three-dimensional metallocene unit, which may lead to some changes in selectivity toward biological targets compared with phenyl or alkyl groups. Therefore, ferrocene seems to an appropriate candidate for improving the antioxidant activity of drugs. Methods: We synthesized four ferrocenyl-containing curcumin analogues by introducing ferrocenyl groups into the active methylene groups to obtain higher antioxidant activity than the parent ferrocene- substituted curcumin analogues, and their antioxidant activities were evaluated in 2, 2′- azobis (2-amidinopropane hydrochloride) (AAPH) and Cu2+/glutathione(GSH) -induced oxidation of DNA, and in trapping 2, 2′-diphenyl-1-picrylhydrazyl (DPPH), 2, 2′-azinobis(3-ethylbenzothiazoline- 6-sulfonate) cationic radicals (ABTS+•) and galvinoxyl radicals. Results: These ferrocenyl-containing curcumin analogues can protect DNA against Cu2+/GSHinduced oxidation, and scavenge 5.7, 6.9, 5.5 and 5.3 radicals in protecting DNA against AAPHinduced oxidation. Compounds (3)~(5) can trap more DPPH, ABTS+• and galvinoxyl radicals than compound (6). The substituents and iron atoms play an antioxidant role in ferrocenyl-containing curcumin analogues. Conclusion: The introduction of ferrocenyl group results in a higher antioxidant activity than the traditional hydroxyl-involved curcumin analogues. The ferrocenyl group is a powerful antioxidative group that could be used to modify natural antioxidants. The electron-accepting group attaching to the phenyl-group could further increase the antioxidant activity. Ferrocene-containing curcumin analogues show higher activities in quenching radicals and protecting DNA against radical-induced oxidation. Therefore, the introduction of ferrocenyl group into the natural antioxidant may contribute to increase the antioxidant activity.

In this study, we have successfully synthesized a new coumarin based fluorescent chemosensor 1, in which tren and quinolone are introduced as receptors for sequential recognition of Cu2+ and PPi. The structure of chemosensor 1 was characterized by 1H NMR, 13C NMR and ESI-HR-MS. Sensor 1 showed an obvious “on-off” fluorescence quenching response toward Cu2+, and the quenching efficiency reached a maximum of 99.6% with the addition of 20 equiv. of Cu2+. The 1-Cu2+ complex showed an “off-on” fluorescence enhancement response toward PPi over many competitive anions, especially HPO42− and H2PO4−. The detection limit of sensor 1 was 1.9 × 10−6 M to Cu2+ and 5.96 × 10−8 M to PPi. In addition, sensor 1 showed a 1:1 binding stoichiometry to Cu2+ and sensor 1-Cu2+ showed a 2: 1 binding stoichiometry to PPi in CH3CN/HEPES buffer medium (9:1 v/v, pH = 7.4). The stable pH range of sensor 1 to Cu2+ and 1-Cu2+ to PPi was from 4 to 8.

Triclocarban (TCC) is used in many household and personal hygiene products. TCC has been widely detected in wastewater around the world. The present study reveals that TCC can activate oxidative stress, induce total antioxidant capacity expression and lipid peroxidation, and increase the activities of superoxide dismutase and other antioxidant enzymes to resist oxidative damage. A significant induction of concentrations of proinflammatory mediator and nitric oxide (NO), accompanied by an upregulated expression of inducible NO synthase gene, was detected in zebrafish embryos exposed to TCC. The transcription of immune-response-related genes, including tnf-α, il-1β, il-4, il-8, and cxcl-clc, was significantly upregulated on exposure to TCC. Furthermore, we found that the exposure of zebrafish embryos to TCC decreased immune cell recruiting in the head. Expressions of nf-κb, trif, myd88, irak4, and traf6 were altered on exposure to TCC. These results demonstrated that exposure to TCC at environmental concentrations significantly affects the expression of immune-response-related genes in zebrafish embryos following oxidative stress and the release of proinflammatory mediators through Toll-like receptor signaling pathway. Thus, we assumed that the ecological risk of TCC on aquatic organisms could not be ignored.

Two novel chiral crystals were prepared by utilizing the spatial distortions of achiral ligands under the same coordination environment. We find that in the same coordination environment, as the radius of halogen atoms decreases, the number of hydrogen bonds decreases, which in turn affects the spatial distortion and leads to chirality. Experiments showed that they have good photophysical properties and stability, which was further proved by theoretical calculations. Additionally, the bioimaging was performed to extend their application in biological development.

Artificial lighting at night has becoming a new type of pollution posing an important anthropogenic environmental pressure on organisms. The objective of this research was to examine the potential association between nighttime artificial light pollution and nest densities of the three main sea turtle species along Florida beaches, including green turtles, loggerheads, and leatherbacks. Sea turtle survey data was obtained from the “Florida Statewide Nesting Beach Survey program”. We used the new generation of satellite sensor “Visible Infrared Imaging Radiometer Suite (VIIRS)” (version 1 D/N Band) nighttime annual average radiance composite image data. We defined light pollution as artificial light brightness greater than 10% of the natural sky brightness above 45° of elevation (>1.14 × 10−11 Wm−2sr−1). We fitted a generalized linear model (GLM), a GLM with eigenvectors spatial filtering (GLM-ESF), and a generalized estimating equations (GEE) approach for each species to examine the potential correlation of nest density with light pollution. Our models are robust and reliable in terms of the ability to deal with data distribution and spatial autocorrelation (SA) issues violating model assumptions. All three models found that nest density is significantly negatively correlated with light pollution for each sea turtle species: the higher light pollution, the lower nest density. The two spatially extended models (GLM-ESF and GEE) show that light pollution influences nest density in a descending order from green turtles, to loggerheads, and then to leatherbacks. The research findings have an implication for sea turtle conservation policy and ordinance making. Near-coastal lights-out ordinances and other approaches to shield lights can protect sea turtles and their nests. The VIIRS DNB light data, having significant improvements over comparable data by its predecessor, the DMSP-OLS, shows promise for continued and improved research about ecological effects of artificial light pollution.

A facile insertion of ruthenium into aromatic C–H and allylic C–N bonds are the key steps in a [Ru(p-cymene)Cl2]2-catalyzed ortho-C–H allylation of benzoic acids. This protocol allows drawing on the large pool of allylic amines for state-of-the-art ortho-functionalizations of arenes, turning neutral amines into leaving groups. Concise syntheses of biologically active compounds provide further evidence of the synthetic potential of this methodology.

In this study, a highly selective fluorescence chemosensor N-(2-(bis(2-((4-methylphenyl)sulfonamido)ethyl)amino)ethyl)-7-(diethylamino)-2-oxo-2H-chromene-3-carboxamide(1) was synthesized and characterized by 1H NMR, 13C NMR and ESI-MS. This tren-based chemosensor 1 showed an “on-off-on” fluorescence response toward Cu2+ and H2PO4− with a 1:1 binding stoichiometry in CH3CN/HEPES buffer medium (9:1 v/v) by UV/vis and fluorescence spectroscopies. The detection limits of sensor 1 to Cu2+ was determined to be 0.37 μM, while that of 1-Cu2+ complex to H2PO4− was 1.6 μM, respectively. The sequential recognition behavior can be repeated four times with little fluorescence efficiency loss using Cu2+ and H2PO4−. The stable pH range for Cu2+ and H2PO4− determination was from 4 to 7.5.

Three novel coordination polymers, [Zn(μ2-HTCA)(Phen)]n (1), {[Cd(μ3-HTCA)(Phen)]·2H2O}n (2), [Mn(μ2-HTCA)(Phen)(H2O)]n (3) were prepared by hydrothermal synthesis from the 4, 4', 4''-nitrilotribenzoicacid (H3TCA) and 1, 10-phenanthroline monohydrate (Phen) with different transition metal salts, which were characterized by elemental analysis, IR spectra, powder and single-crystal X-ray diffraction and thermogravimetric analysis. The photophysical properties of the complexes were investigated by solid-state diffuse reflectance spectra, photoluminescent properties, lifetime and quantum yield. For these complexes, it was found that the band gaps follow the order: 3 ＜ 2 ＜ 1 ＜ 2.80 eV, fluorescence intensity order: 1 ＞ H3TCA ＞ 2 ＞ 3; quantum yield order: H3TCA ＞ 1 ＞ 2 ＞ 3; while the lifetime order: 1 ＞ 2 ＞ H3TCA ＞ 3.

A [Ru(p-cymene)Cl2]2 catalyst activates allyl alcohols and ethers for the regioselective ortho-C-H allylation of aromatic and heteroaromatic carboxylates. The reaction is orthogonal to most C-H functionalisations with allyl alcohols in that allyl arenes rather than carbonyl compounds are obtained. A wide range of substrates are thus smoothly transformed to allylarenes at 50 °C in phosphate-buffered 2,2,2-trichloroethanol. The reaction concept combines the use of abundant reagents and directing groups in a sustainable, waste-minimised method for C-C bond formation.

In this study, a highly sensitive and selective fluorescent chemosensor, ethyl(E)-2-((2-((2-(7-(diethylamino)-2-oxo-2H-chromene-3-carbonyl)hydrazono)methyl)quinolin-8-yl)oxy)acetate (1), was synthesized and characterized by 1H NMR, 13C NMR and ESI-MS. Sensor 1 showed an “on–off” fluorescence response to Pb2+ with a 1 : 1 binding stoichiometry in CH3CN/HEPES buffer medium (9 : 1 v/v). The detection limit of sensor 1 to Pb2+ was determined to be 0.5 μM, and the stable pH range for Pb2+ detection was from 4 to 8.

Triclocarban (TCC), considered an endocrine-disrupting, persistent, and bioaccumulating organic matter, has attracted a great deal of attention for its pollution and health risks. However, studies on its toxicological mechanism, especially for embryo development are limited. This article explores the cardiac developmental toxicity induced in zebrafish embryos after exposure to different TCC concentrations. First, liquid chromatography-tandem mass spectrometry was used in detecting TCC in embryos in vivo after exposure to various TCC. Results showed that embryonic TCC content reached 9.23 ng after exposure to 300 μg/L TCC, the heart rates of the embryos markedly decreased, heart abnormalities significantly increased. In addition, obvious pericardial effusion was observed in the larvae. Through transcriptome sequencing, 200 differential gene expression (DGE) patterns were detected in the TCC (300 μg/L) experimental and control groups. The results of GO function analysis and KEGG pathway of DGE showed that aryl hydrocarbon receptor (AhR) activation and cyp-related genes (cyp1a, cyp1b1 and cyp1c) were significantly up-regulated. these affected the normal development of zebrafish embryonic heart, tissue edema, and hemorrhage. TCC exhibited strong cardiac teratogenic effects and developmental toxicity, which is partly related to AhR activation. Transcriptome-based results are helpful in precisely determining the risk of TCC exposure. The potential mechanism between TCC and AhR should be further investigated.

SRB is one of the main bacteria causing marine microbial corrosion. In order to reduce the loss of microbial corrosion, a Gemini surfactant (12-B-12) containing semi-rigid spacer was used to investigate the anti-bacterial and anti-corrosion performances of carbon steel in simulated seawater by weight-loss test, electrochemical method and surface morphology analysis. The results showed that the inhibition efficiency of 0.01 mM 12-B-12 was as high as 98.3% after 30 days of incubation in simulated seawater with SRB, and the planktonic and sessile SRB on the carbon steel surface can be reduced to undetectable level. Quantum chemical calculation and molecular dynamics simulation were used to study the structure–activity relationship.

The bearings fault diagnosis is essential for the maintenance and reliability of rotating machinery. Bearings pitting is one of the most common fault types of rotating machinery. However, due to the complex working conditions of bearings, it is challenging to diagnose the pitting faults in bearings inner and outer rings at different speeds. In this paper, an improved one-dimensional inception capsule network (IICN) is proposed to solve the problem of bearing pitting fault diagnosis under complex working conditions. Firstly, the raw bearing vibration signal is processed using the improved Inception network. The function of the stage is to approximate an optimal local sparse structure with a simple dense substructure for bearing healthy state feature extraction. And then inputs concatenated features to the primary capsule layer and the routing capsule layer. The inputs are mapped to feature vector space and weighted by the dynamic routing algorithm. The dynamic routing algorithm encodes the significant spatial relationship between low-level features and upper-level features. The Euclidean length of each capsule vector is the probability of belonging to this bearing healthy condition. In order to validate the effectiveness of the IICN method, bearings pitting experiments at different speeds were designed. The raw bearings vibration signal data under six different health conditions are collected, and the effectiveness of the IICN method is verified. Experimental results show that the IICN method can effectively distinguish different degrees of bearing pitting fault at different speeds, and its diagnostic accuracy is superior to other advanced deep learning methods.

Developing novel probe for Copper (Cu 2+ ) in living system is still of great importance and challenge work for researchers. However, it is rarely reported that a probe for Cu 2+ with remarkable two-photon absorption properties, well biocompatibility and excellent water solubility. Herein, a novel water-soluble Schiff-base compound ( HL ) was confirmed by single crystal X-ray diffraction analysis, which can specifically coordinates with Cu 2+ ，giving an obvious fluorescence quenching and a significant change of the absorption band in HEPES buffer. The mechanism of HL for sensing Cu 2+ was proposed relying on 1 H NMR titration, mass spectra and theoretical calculations. Furthermore, the UV-vis absorption and emission spectra exhibit a multi-recovery by the subsequent addition of histidine (His). Importantly, the copper complex ( L -Cu- L ) formed from the probe was still water-soluble and biocompatible. Then the probe was successfully applied to two-photon fluorescent imaging in cellular mitochondria as well as in the intestine and liver of a larval zebrafish. These results imply promising applications of using such probe in physiological systems.

Streambank erosion is a major source of fluvial sediment, but few large-scale, spatially distributed models exist to quantify streambank erosion rates. We introduce a spatially distributed model for streambank erosion applicable to sinuous, single-thread channels. We argue that such a model can adequately characterize streambank erosion rates, measured at the outsides of bends over a 2-year time period, throughout a large region. The model is based on the widely-used excess-velocity equation and comprised three components: a physics-based hydrodynamic model, a large-scale 1-dimensional model of average monthly discharge, and an empirical bank erodibility parameterization. The hydrodynamic submodel requires inputs of channel centerline, slope, width, depth, friction factor, and a scour factor A; the large-scale watershed submodel utilizes watershed-averaged monthly outputs of the Noah-2.8 land surface model; bank erodibility is based on tree cover and bank height as proxies for root density. The model was calibrated with erosion rates measured in sand-bed streams throughout the northern Gulf of Mexico coastal plain. The calibrated model outperforms a purely empirical model, as well as a model based only on excess velocity, illustrating the utility of combining a physics-based hydrodynamic model with an empirical bank erodibility relationship. The model could be improved by incorporating spatial variability in channel roughness and the hydrodynamic scour factor, which are here assumed constant. A reach-scale application of the model is illustrated on ∼1 km of a medium-sized, mixed forest-pasture stream, where the model identifies streambank erosion hotspots on forested and non-forested bends.

A cationic Pd(II)-catalyzed redox neutral arylative cyclization of enynes by using β-acetoxy elimination as the quenching step has been developed. The reaction offers an efficient method to access a variety of carbocycles and N-heterocycles bearing an exocyclic double bond.

A cationic palladium(II) complex catalyzed reductive coupling of N-tosyl-tethered alkynones for the synthesis of functionalized piperidines was successfully developed. This reaction was initiated by hydropalladation of the alkyne and quenched by addition to the intramolecular carbonyl group. The substituent on the alkyne is key to the reaction.

An efficient rhodium(III)-catalyzed coupling reaction of N-aryloxyacetamides with 6-diazo-2-cyclohexenones through a cascade redox-neutral C–H functionalization and aromatization has been developed. This novel and scalable transformation provides a straightforward way to construct unsymmetrical ortho-biphenols with broad substrate scope under mild and redox-neutral conditions. The synthetic utility of this approach is demonstrated in the late-stage functionalization of bioactive compounds and the synthesis of an optically active ortho-biphenol.

In oil pipeline leak detection and location, noise in the pressure signal collected at the end of the pipeline affects the accuracy of leak detection and the error of leakage location. To reduce the noise interference, an improved local mean decomposition signal analysis method is proposed. The production functions (PFs) that are related to the leak signal can be exacted, and it is necessary to know the characteristics of leak signals or noise in advance. According to the cross-correlation function, there is a significant peak between the measured signals, which are decomposed into a number of PFs. These reconstructed principal PF components are obtained, and a wavelet analysis is used to remove the noise in the reconstructed signal. On this basis, the signal features are extracted according to the time-domain feature and the waveform feature, which are input into the least squares twin support vector machine (LSTSVM), to recognize pipeline leaks. According to the reconstructed signal after wavelet denoising, the time-delay estimate of the negative pressure signal at the end of the pipeline is obtained by the cross-correlation function, and the leak location is ultimately calculated by combining the time delay with the leak signal propagation velocity. A flow model for pipeline leakage is proposed based on the Flowmaster software, where the collected data of the different working conditions are processed. The experimental results show that the proposed method can effectively identify different working conditions and accurately locate the leakage point.

Exposure to particulate matter with an aerodynamic diameter of less than 2.5 μm (PM2.5) may increase risk of lung cancer. The repetitive and broad-area coverage of satellites may allow atmospheric remote sensing to offer a unique opportunity to monitor air quality and help fill air pollution data gaps that hinder efforts to study air pollution and protect public health. This geographical study explores if there is an association between PM2.5 and lung cancer mortality rate in the conterminous USA. Lung cancer (ICD-10 codes C34- C34) death count and population at risk by county were extracted for the period from 2001 to 2010 from the U.S. CDC WONDER online database. The 2001-2010 Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth dataset was used to calculate a 10 year average PM2.5 pollution. Exploratory spatial data analyses, spatial regression (a spatial lag and a spatial error model), and spatially extended Bayesian Monte Carlo Markov Chain simulation found that there is a significant positive association between lung cancer mortality rate and PM2.5. The association would justify the need of further toxicological investigation of the biological mechanism of the adverse effect of the PM2.5 pollution on lung cancer. The Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth dataset provides a continuous surface of concentrations of PM2.5 and is a useful data source for environmental health research.

Modeling and simulation have been widely used in both cardiac research and clinical study to investigate cardiac disease mechanism and develop new treatment design. Electrical conduction among cardiac tissue is commonly modeled with a partial differential equation, i.e., reaction-diffusion equation, where the reaction term describes cellular excitation and diffusion term describes electrical propagation. Cellular excitation can be modeled by either detailed human cellular models or simplified models such as the FitzHugh-Nagumo model; electrical propagation can be simulated using either biodomain or mono-domain tissue model. However, existing cardiac models have a great level of complexity, and the simulation is often time-consuming. This paper develops a new spatiotemporal model as a surrogate model of the timeconsuming cardiac model. Specifically, we propose to investigate the auto-regressive convolutional neural network (AR-CNN) and convolutional long short-term memory (Conv-LSTM) to model the spatial and temporal structure for the metamodeling. Model predictions are compared to the one-dimensional simulation data to validate the prediction accuracy. The metamodel can accurately capture the properties of the individual cardiac cell, as well as the electrical wave morphology in cardiac fiber at different simulation scenarios, which demonstrates its superior performance in modeling and the long-term prediction.

In the presence of a [Cp*RhCl2 ]2 catalyst, the Lewis acid In(OTf)3 , and the mild base Na2 CO3 , aromatic carboxylates and α,β-unsaturated ketones undergo a unique hydroarylation/Claisen/retro-Claisen process to give the corresponding indanones. In this carboxylate-directed ortho-C-H annelation, the C-COR bond of the ketone and the CO-OH group of the aromatic carboxylate are cleaved, and the hydroxy group is transferred from the aromatic to the aliphatic acyl residue. This reactivity is synthetically useful, particularly when starting from cyclic ketones, which are converted into indanones bearing aliphatic carboxylate side chains, thus greatly increasing the molecular complexity of aromatic carboxylates in a single step.

In this study, by employing mixed organic ligands through rational design and metal ions as the initial reactants, a series of novel metal-organic frameworks (AHU-TW1 to 6) were synthesized by a solvothermal method. Herein, accessible Lewis base sites originating from organic ligands within MOFs act as functional sites that can interact with the analyte possessing protons and then lead to obvious variations in the fluorescence spectra. Due to their superiority, AHU-TW1, 3, 4 and 6 are able to recognize trinitrophenol (TNP) with high sensitivity and a low detection limit.

Two benzothiazole derivatives, namely 2-(n-hexylamino)-4-(3′-N,N-dimethylamino-propyl)amino-6-(benzothiazol-2-yl)thio-1,3,5-s-triazine (BTC6T) and 2-(n-octylamino)-4-(3′-N,N-dimethylamino-propyl)amino-6-(benzothiazol-2-yl)thio-1,3,5-s-triazine (BTC8T), were synthesized to study their corrosion inhibiting effect against steel in a 1 M HCl solution. The corrosion inhibition efficiency was measured using electrochemical impedance spectroscopy (EIS), potentiodynamic polarization, and weight loss methods. Both inhibitors offered extra stability and higher inhibition efficiencies again steel corrosion than previously reported benzothiazole family inhibitors. These inhibitors can be adsorbed onto surfaces by both physical and chemical means. Finally, quantum chemical parameters were calculated using the density functional theory method (DFT) and the correlation between the theoretical and experimental results are discussed.

The bearing fault diagnosis is of vital significance in maintaining the safety of rotation machine. Among various fault detection techniques, the diagnosis based on vibration signal is widely applied in monitoring the condition of rotation machine. Variational mode decomposition (VMD) is a novel signal analysis method, which can decompose a multi-component signal into a certain number of band-limited intrinsic mode functions (BLIMFs) nonrecursively. VMD could overcome some problems such as mode mixing, the inference of noise, the determination of wavelet base, which exist in empirical mode decomposition, ensemble empirical mode decomposition, wavelet transform, respectively. However, the empirical selection of the parameters for VMD would affect the result of the decomposition. This paper presents an adaptive VMD method with parameter optimization for detecting the localized faults of rolling bearing. Kurtosis, sensitive to transient impulsive components, is employed as optimization index to evaluate the performance of the VMD. Two parameters in the VMD, namely the number of decomposition modes and data-fidelity constraint, are optimized synchronously based on the kurtosis index through artificial fish swarm algorithm. Executing VMD with the acquired parameters, the optimal BLIMF is obtained. The spectrum analysis of the optimal BLIMF could identify the characteristic frequency caused by the localized crack effectually. The validity of the proposed method is proved by means of a cyclic transient impulse response signal and two experiments with practical vibration signals of rolling bearings. Compared to several existing methods, the proposed method demonstrates reinforced results.

Aggregation behavior and thermodynamics of micellization of diester-bonded cationic gemini surfactants (12-Z1-12, 14-Z1-14, 12-Z2-12, 14-Z2-14) have been studied in ethylene glycol–water (EG–water) binary mixtures by conductometric method in the temperatures ranging from 298.15 to 313.15 K. With increasing length of hydrophobic chain and spacer, the values of critical micelle concentration (CMC) decrease, and degree of counterion association (β) increases. While with increasing temperature and concentration of ethylene glycol, the values of CMC increase, and β decrease. The thermodynamic parameters of micellization were determined from the temperature dependence of CMC values. The Gibbs energy values were found to be negative, and the negative values increased with the increase in the length of hydrophobic chain and spacer of surfactant, and with the decrease in temperature and volume fraction of ethylene glycol.

The efficiency and enantioselectivity of polyoxometalate (POM) in the oxidation of styrene with H 2 O 2 could be improved via simply combined the POM with the chiral ionic liquids (CILs), which consist of the quaternized alkyl bromide salts (with lengths of C-8, C-12, and C-16) derived from natural chiral S -nicotine. The hybrids showed synergistic advantages between POM and CILs, achieving a complete conversion of styrene after 1 h of mild reaction and a relatively high selectivity for R- (−)-1-phenylethane-1, 2-diol with 72% yield and 96% ee. Further fluorescence analysis illustrated that CILs might serve for the enantiomeric recognition of R- than S- enantiomers.

Sodium 4,6-(2-(N,N-bis-ethylhexylamino)-1,3,5-triazine-4,6-yl-amino) ethane sulfonate (IXC8), Sodium 4,6-(2-(N,N-bis-octylamino)-1,3,5-Triazine-4,6-yl-amino) ethane sulfonate (XC8) and 2,2′-(6,6′-(ethane-1,2-diylbis(azanediyl) bis(4-(octylamino)-1,3,5-triazine-6,2-diyl)) bis(azanediyl))diethane sulfonate (C8-2-C8) were synthesized from cyanuric chloride. The surface activity and application properties of these surfactants (XC8, IXC8 and C8-2-C8) were discussed. The values of CMC, γ CMC, pC20, Γmax, and Amin calculated from surface tension measurement at 30 °C indicate that the surface activity of IXC8, which has two branched hydrophobic carbon chains, has lower γ CMC (26.8 mN m−1) than the other investigated surfactants and excellent wetting ability.

Four cationic gemini surfactants featuring semi-rigid spacers were synthesized via a two-step process. The surface-active properties of these surfactants were investigated through surface tension and electrical conductivity measurement. The thermodynamic parameters of micellization were evaluated from electrical conductivity measurements at temperatures ranging from 293 to 313 K. The aggregation behavior of these synthesized gemini surfactants in water were investigated using dynamic light scattering and transmission electron microscopy. Further, the antimicrobial activities of these synthesized gemini surfactants against both Gram-positive and Gram-negative bacteria were also investigated.

Framework-forming scleractinian (FFS) corals provide structurally complex habitats to support abundant and diverse benthic communities but are vulnerable to environmental changes and anthropogenic disturbances. Scientific modeling of suitable habitat provides important insights into the impact of the environmental conditions and fills the gap in the knowledge on habitat suitability. This study presents predictive habitat suitability modeling for deep-sea (depth > 50 m) FFS corals in the GoM. We first conducted a nonparametric estimate of the observed coral point process intensity as a function of each numeric environmental variable. Next, we performed species distribution modeling (SDM) using an assemble of four machine learning models - maximum entropy (ME), support vector machine (SVM), random forest (RF), and deep neural network (DNN). We found that most important variables controlling the coral distribution are super-dominant gravel and rock substrata, SW and SE aspects, slope steepness, salinity, depth, temperature, acidity, dissolved oxygen, and chlorophyll-a. Highly suitable habitats are predicted to be on the continental slope off Texas, Louisiana, and Mississippi and the shelf and slope of the West Florida Escarpment. All the four models have outstanding prediction performances with AUC values over 0.95. DNN model performs best (AUC = 0.987). The study contributes to coral habitat modeling research by presenting unique methods including nonparametric function of coral point process intensity, DNN and SVM models that have not been used in coral SDM, post-classification model assembling, and percentile approach to determine a threshold value for classifying a suitability score map into a binary map. Our findings would help support conservation prioritization, management and planning, and guide new field exploration.

Two triazine derivatives were synthesized and characterized by HR-MS and 1H NMR spectroscopy. Melamine (S1), S2 and S3 were examined as corrosion inhibitors for medium carbon steel in 1 M HCl solution using electrochemical measurement, weight loss and surface analysis. The theoretical studies combining with experimental results revealed a same inhibition order S3 > S2 > S1. This study proved that the synergistic effect of surface active functional groups and corrosion inhibition functional groups on corrosion inhibition performance and sufficiently comprehensive and detailed to explain the effects and mechanism of triazine inhibitors.

In this study, a highly selective fluorescent sensor (E)-2-((2-(benzo[d]thiazol-2-yl)quinolin-8-yl)oxy)-N′-((7-(diethylamino)-2-oxo-2H-chromen-3-yl)methylene)acetohydrazide (TQC) was synthesized from 2-methylquinolin-8-ol and 4-(diethylamino)-2-hydroxybenzaldehyde and its structure was characterized by 1H NMR, 13C NMR, ESI-HR-MS and density functional theory (DFT) calculation. Sensor TQC showed an obvious “on-off-on” fluorescence response to Cu2+ and PPi in a DMSO/HEPES (3:2 v/v, pH = 7.4) buffer system. The detection limits of sensor TQC were 0.06 μM to Cu2+ and 0.01 μM to PPi. In addition, sensor TQC showed a 1:1 binding stoichiometry to Cu2+ and TQC-Cu2+ complex showed a 2:1 binding stoichiometry to PPi. The optimum pH range of sensor TQC and TQC-Cu2+ was 3–8. Further studies demonstrated that sensor TQC could be made into test paper strips for the qualitative of Cu2+ and PPi and showed sequentially “on-off-on” fluorescent bio-imaging of Cu2+ and PPi in HeLa cells.

In this study, a novel schiff base fluorescent probe (E)-N'-(3-(benzo[d]thiazol-2-yl)-2-hydroxy-5-methylbenzylidene)-7-(diethylamino)-2-oxo-2H-chromene-3-carbohydrazide (CHS) was synthesized for sequential detection of Al3+ and pyrophosphate ions (PPi) in a DMSO/HEPES (4:1 v/v, pH = 7.4) buffer system and characterized by 1H NMR, 13C NMR, ESI-HR-MS and DFT calculation. Its detection limit was determined to be 0.16 μM for Al3+ and 0.18 μM for PPi in a pH range of 4∼8, respectively. The Job’ s plot showed that the stoichiometric ratio to Al3+ was 1:1, and CHS-Al3+ showed highly selective recognition of PPi. The sensor CHS could also recognize Al3+ and PPi and exhibited fluorescence enhancement and quenching properties in HeLa cells.