Multiple-Emitting Luminescent Metal-Organic Framework as an Array-on-a-MOF for Rapid Screening and Discrimination of Nitroaromatics.

Fluorescence array technologies have attracted great interest in the sensing field because of their high sensitivity, low cost, and capability of multitarget detection. However, traditional array sensing relies on multiple independent sensors and thus often requires time-consuming and laborious measurement processes. Herein, we introduce a novel fluorescence array strategy of the array-on-a-metal-organic framework (MOF), which integrates multiple array elements into a single MOF matrix to achieve facile sensing and discrimination of multiple target analytes. As a proof-of-concept system, we constructed a luminescent MOF containing three different emitting channels, including a lanthanide ion (europium/Eu3+, red emission), a fluorescent dye (7-hydroxycoumarin-4-acetic acid/HCAA, blue emission), and the MOF itself (UiO-66-type MOF, blue-violet emission). Five structurally similar nitroaromatic compounds (NACs) were chosen as the targets. All three channels of the array-on-a-MOF displayed rapid and stable fluorescence quenching responses to NACs (response equilibrium achieved within 30 s). Different responses were generated for each channel against each NAC due to the various quenching mechanisms, including photoinduced electron transfer, energy competition, and the inner filter effect. Using linear discriminant analysis, the array-on-a-MOF successfully distinguished the five NACs and their mixtures at varying concentrations and demonstrated good sensitivity to quantify individual NACs (detect limit below the advisory concentration in drinking water). Moreover, the array also showed feasibility in the sensing and discrimination of multiple NACs in real water samples. The proposed "array-on-a-MOF" strategy simplifies multitarget discrimination procedures and holds great promise for various sensing applications.

Revealing Molecular Structures of Nitrogen-Containing Compounds in Dissolved Black Carbon Using Ultrahigh-Resolution Mass Spectrometry Combined with Thermodynamic Calculations.

Landscape wildfires generate a substantial amount of dissolved black carbon (DBC) annually, yet the molecular nitrogen (N) structures in DBC are poorly understood. Here, we systematically compared the chemodiversity of N-containing molecules among three different DBC samples from rice straw biochar pyrolyzed at 300, 400, and 500 °C, one leached dissolved organic carbon (LDOC) sample from composted rice straw, and one fire-affected soil dissolved organic matter (SDOMFire) sample using Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS). N-Containing molecules contributed 20.0%, 36.1%, and 43.7% of total compounds in Combined DBC (pooling together the three DBC), LDOC, and SDOMFire, respectively, and molecules with fewer N atoms had higher proportions (i.e., N1 > N2 > N3). The N-containing molecules in Combined DBC were dominated by polycyclic aromatic (62.2%) and aromatic (14.4%) components, while those in LDOC were dominated by lignin-like (50.4%) and aromatic (30.1%) components. The composition and structures of N-containing molecules in SDOMFire were more similar to those in DBC than in LDOC. As the temperature rose, the proportion of the nitrogenous polycyclic aromatic component in DBC significantly increased with concurrent enhanced oxidation and unsaturation of N. As indicated by density functional theory (DFT)-based thermodynamic calculations, the proportion of aliphatic amide N decreased from 23.2% to 7.9%, whereas that of nitroaromatic N increased from 10.0% to 39.5% as the temperature increased from 300 to 500 °C; alternatively, the proportion of aromatic N in the 5/6 membered ring remained relatively stable (∼31%) and that of aromatic amide N peaked at 400 °C (32.7%). Our work first provides a comprehensive and thorough description of molecular N structures of DBC, which helps to better understand and predict their fate and biogeochemical behavior.

Efficient Catalytic Oxidation of Ethylene at 0 °C on an in Situ Carbon Modified Pt Catalyst Supported on SBA-15.

The design of efficient catalysts for catalytic ethylene (C2H4) oxidation is of crucial importance for extending the shelf life of fruits and vegetables. Herein, a carbon modified SBA-15 supported Pt catalyst (Pt/CSBA-15) was prepared in situ by a facile solid phase grinding-infiltration-inert atmosphere calcination method. Characterization results reveal that in the Pt/CSBA-15 catalysts thin carbon layers are successfully formed in the hexagonal pores of SBA-15. Additionally, Pt particles are well dispersed in the channels of SBA-15, and Pt/CSBA-15 has a smaller Pt particle size than the catalyst without carbon modification (i.e., Pt/SBA-15). O2 is more feasibly adsorbed and activated on small-sized Pt particles, and in situ formed carbon species enhance the hydrophobicity of catalysts. As a result, both 3Pt/CSBA-15 and 5Pt/CSBA-15 are able to maintain 100% conversion of 50 ppm of C2H4 for more than 7 h at 0 °C. 3Pt/CSBA-15 even achieves 81.5% C2H4 conversion and 71.6% CO2 yield after 20 h, exhibiting much more prominent catalytic performances than 3Pt/SBA-15. DFT calculations and in situ FTIR measurements confirm that small-sized Pt particles possess strong O2 affinity to promote O2 adsorption, and in situ formed hydrophobic carbon layers efficiently suppress competitive H2O adsorption. Such a unique one-step catalyst preparation method for regulating the size of metal particles and the hydrophobicity of catalysts can be perfectly utilized to develop simple and efficient hydrophobic catalysts applied in low-temperature oxidation of C2H4.

Benzenepoly(carboxylic acid)s as Exclusive Intrinsic Markers to Assess Riverine Export of Dissolved Black Carbon.

Landscape fires annually generate large quantities of black carbon. The water-soluble fraction of black carbon (i.e., dissolved black carbon/DBC) is an important constituent of the dissolved organic carbon (DOC) pool, playing a crucial role in the global budget of refractory carbon and climate change. A key challenge in constraining the flux and fate of riverine DBC is to develop targeted and accurate quantification methods. Herein, we report that benzenepentacarboxylic acid (B5CA) intrinsically present in DBC can be used as an exclusive and holistic marker (representing both condensed aromatics and less-/nonaromatic fractions) for DBC quantification. B5CA was universally detected in water extractions of biochar and fire-affected soils with relatively large abundance but not produced by nonthermogenic processes. It has good mobility in the environment as it is not readily precipitated by cations or adsorbed by common geosorbents. B5CA also represents the recalcitrant components of DBC with excellent stability against photodegradation and biodegradation. Applying B5CA as the DBC marker in surface waters of the Changjiang River (i.e., the third largest river in the world), we calculate the DBC concentration in the downstream Changjiang River to be 4.8 ± 5.5% of the DOC flux. Our work provides a simple and reliable approach for the accurate quantification and source tracking of DBC in the soil and aquatic carbon pools.

An evaluation of cervical maturity for Chinese women with labor induction by machine learning and ultrasound images.

BACKGROUND: To evaluate the improvement of evaluation accuracy of cervical maturity for Chinese women with labor induction by adding objective ultrasound data and machine learning models to the existing traditional Bishop method. METHODS: The machine learning model was trained and tested using 101 sets of data from pregnant women who were examined and had their delivery in Peking University Third Hospital in between December 2019 and January 2021. The inputs of the model included cervical length, Bishop score, angle, age, induced labor time, measurement time (MT), measurement time to induced labor time (MTILT), method of induced labor, and primiparity/multiparity. The output of the model is the predicted time from induced labor to labor. Our experiments analyzed the effectiveness of three machine learning models: XGBoost, CatBoost and RF(Random forest). we consider the root-mean-squared error (RMSE) and the mean absolute error (MAE) as the criterion to evaluate the accuracy of the model. Difference was compared using t-test on RMSE between the machine learning model and the traditional Bishop score. RESULTS: The mean absolute error of the prediction result of Bishop scoring method was 19.45 h, and the RMSE was 24.56 h. The prediction error of machine learning model was lower than the Bishop score method. Among the three machine learning models, the MAE of the model with the best prediction effect was 13.49 h and the RMSE was 16.98 h. After selection of feature the prediction accuracy of the XGBoost and RF was slightly improved. After feature selection and artificially removing the Bishop score, the prediction accuracy of the three models decreased slightly. The best model was XGBoost (p = 0.0017). The p-value of the other two models was < 0.01. CONCLUSION: In the evaluation of cervical maturity, the results of machine learning method are more objective and significantly accurate compared with the traditional Bishop scoring method. The machine learning method is a better predictor of cervical maturity than the traditional Bishop method.

Current and Future Trends of Low and High Molecular Weight Polycyclic Aromatic Hydrocarbons in Surface Water and Sediments of China: Insights from Their Long-Term Relationships between Concentrations and Emissions.

In this study, we analyzed the temporal trend of polycyclic aromatic hydrocarbons (PAHs) in China using data reported over the past 20 years. We found that the total concentrations of low molecular weight PAHs (CΣLPAHs) in surface water and sediments were positively correlated with their total emissions (EΣLPAHs), which increased between 2000 and 2008, then decreased until 2017. Additionally, the total concentrations of high molecular weight PAHs (C∑HPAHs) in surface water and sediments were positively correlated with their total emissions (EΣHPAHs), which increased significantly from 2000 to 2014 and then plateaued. Two future scenarios were assessed to explore C∑LPAHs and C∑HPAHs in surface water and sediments. PAH emissions were reduced by technological improvement in 2030 for coal consumption in Scenario 1 and for control of biomass burning in Scenario 2. Scenario 1 was more efficient than Scenario 2 in reducing C∑HPAHs in the surface water and sediments of China for the areas where CΣHPAHs in surface water exceeded the annual average standard (i.e., 30 ng L-1), with reductions of 38 and 24% in Scenarios 1 and 2, respectively. The observed relationships in this study can provide tools for emission reduction policies in the future.

Comparing Photoactivities of Dissolved Organic Matter Released from Rice Straw-Pyrolyzed Biochar and Composted Rice Straw.

Here, we systematically compared the photoactivity and photobleaching behavior between dissolved black carbon (DBC) from rice straw biochar and leached dissolved organic carbon (LDOC) from rice straw compost using complementary techniques. The Fourier transform-ion cyclotron resonance mass spectrometry (FT-ICR MS) analysis showed that DBC was dominated by polycyclic aromatic (55.1%) and tannin-like molecules (24.1%), while LDOC was dominated by lignin-like (58.9%) and tannin-like molecules (19.7%). Under simulated sunlight conditions, DBC had much higher apparent quantum yields for 3DOM* and 1O2 but much lower apparent quantum yields for •OH than LDOC. After a 168 h irradiation, the total number of LDOC formulas identified by FT-ICR MS decreased by 40.1% with concurrent increases in O/C and H/C ratios and also decreases in double bond equivalence minus oxygen (DBE - O) and average molecular weight identified by gel permeation chromatography. However, despite the large decreases in UVA254 and DOC, the total number of DBC formulas decreased only by 12.0% with nearly unchanged O/C ratio, DBE - O values, molecular weight distribution, and benzenepolycarboxylic aromatic condensation (BACon) index regardless of the decreased percentage of condensed aromatic carbon (ConAC %). Compared with LDOC, the photolysis of DBC was much less oxidative and destructive mainly via breakup of a small portion of the highly condensed aromatic rings, probably accompanied by photodecarboxylation.

High-Throughput Method for Natural Organic Matter Hydrophobicity Assessment Using an Ionic Liquid-Based Aqueous Two-Phase System.

Hydrophobicity of natural organic matter (NOM) is one of its fundamental properties that influence the environmental fate of pollutants and the performance of many water treatment unit processes. In this study, a high-throughput method was developed for NOM hydrophobicity measurement based on the phase separation technique in the 96-well format. It measures the partition coefficients of NOM (KATPS,IL) in an ionic liquid (IL)-based aqueous two-phase system (ATPS). The ATPS was made of 1-butyl-3-methylimidazole bromide solution and a salt solution containing potassium phosphate monobasic and potassium phosphate dibasic. The partition of NOM in IL-based ATPS is mainly affected by its hydrophobicity. log KATPS,IL linearly correlated with the commonly used NOM hydrophobicity scales, including (O + N)/C, O/C, and aromatic carbons. KATPS,IL provided a more accurate assessment of NOM hydrophobicity than spectroscopic indices. Furthermore, KATPS,IL can predict the organic carbon-water partition coefficients for hydrophobic organic chemical sorption to NOM based on the two-phase system model. The high-throughput KATPS,IL measurement and the two-phase system model can be applied to real surface water samples. Our results suggest that the proposed high-throughput method has great potential to be applied to monitor NOM hydrophobicity for environmental risk assessment and water treatment purposes.

Circ-AKT3 inhibits the accumulation of extracellular matrix of mesangial cells in diabetic nephropathy via modulating miR-296-3p/E-cadherin signals.

Diabetic nephropathy is a leading cause of end-stage renal disease globally. The vital role of circular RNAs (circRNAs) has been reported in diabetic nephropathy progression, but the molecular mechanism linking diabetic nephropathy to circRNAs remains elusive. In this study, we investigated the significant function of circ-AKT3/miR-296-3p/E-cadherin regulatory network on the extracellular matrix accumulation in mesangial cells in diabetic nephropathy. The expression of circ-AKT3 and fibrosis-associated proteins, including fibronectin, collagen type I and collagen type IV, was assessed via RT-PCR and Western blot analysis in diabetic nephropathy animal model and mouse mesangial SV40-MES13 cells. Luciferase reporter assays were used to investigate interactions among E-cadherin, circ-AKT3 and miR-296-3p in mouse mesangial SV40-MES13 cells. Cell apoptosis was evaluated via flow cytometry. The level of circ-AKT3 was significantly lower in diabetic nephropathy mice model group and mouse mesangial SV40-MES13 cells treated with high-concentration (25 mmol/L) glucose. In addition, circ-AKT3 overexpression inhibited the level of fibrosis-associated protein, such as fibronectin, collagen type I and collagen type IV. Circ-AKT3 overexpression also inhibited the apoptosis of mouse mesangial SV40-MES13 cells treated with high glucose. Luciferase reporter assay and bioinformatics tools identified that circ-AKT3 could act as a sponge of miR-296-3p and E-cadherin was the miR-296-3p direct target. Moreover, circ-AKT3/miR-296-3p/E-cadherin modulated the extracellular matrix of mouse mesangial cells in high-concentration (25 mmol/L) glucose, inhibiting the synthesis of related extracellular matrix protein. In conclusion, circ-AKT3 inhibited the extracellular matrix accumulation in diabetic nephropathy mesangial cells through modulating miR-296-3p/E-cadherin signals, which might offer novel potential opportunities for clinical diagnosis targets and therapeutic biomarkers for diabetic nephropathy.

Loss of lncRNA MIAT ameliorates proliferation and fibrosis of diabetic nephropathy through reducing E2F3 expression.

Diabetic nephropathy (DN) is a serious kidney disease resulted from diabetes. Dys-regulated proliferation and extracellular matrix (ECM) accumulation in mesangial cells contribute to DN progression. In this study, we tested expression level of MIAT in DN patients and mesangial cells treated by high glucose (HG). Up-regulation of MIAT was observed in DN. Then, functional assays displayed that silence of MIAT by siRNA significantly repressed the proliferation and cycle progression in mesangial cells induced by HG. Meanwhile, we found that collagen IV, fibronectin and TGF-ß1 protein expression was obviously triggered by HG, which could be rescued by loss of MIAT. Then, further assessment indicated that MIAT served as sponge harbouring miR-147a. Moreover, miR-147a was decreased in DN, which exhibited an antagonistic effect of MIAT on modulating mesangial cell proliferation and fibrosis. Moreover, bioinformatics analysis displayed that E2F transcription factor 3 (E2F3) could act as direct target of miR-147a. We demonstrated that E2F3 was greatly increased in DN and the direct binding association between miR-147a and E2F3 was evidenced using luciferase reporter assay. In summary, our data explored the underlying mechanism of DN pathogenesis validated that MIAT induced mesangial cell proliferation and fibrosis via sponging miR-147a and regulating E2F3.

Downregulation of XIST ameliorates acute kidney injury by sponging miR-142-5p and targeting PDCD4.

Acute kidney injury (AKI) is a common kidney disease that markedly affects public health. To date, the roles of long noncoding RNA XIST in AKI are poorly understood. Here, we investigated the biological functions of XIST in AKI. We observed that XIST expression increased in patients with AKI and HK-2 cells stimulated by CoCl2 . In addition, a rat AKI model induced by ischemia-reperfusion was established. Tumor necrosis factor-α, interleukin-6, and cyclooxygenase-2 messenger RNA expression were induced in vivo; moreover, XIST expression was upregulated. Knockdown of XIST significantly repressed CoCl2 -triggered injury in HK-2 cells. However, microRNA (miR)-142-5p, a downstream target of XIST, was downregulated in AKI. miR-142-5p was repressed by XIST and miR-142-5p could inhibit CoCl2 -induced injury in HK-2 cells. Moreover, PDCD4 expression was significantly increased in AKI. PDCD4 was predicted to be the target of miR-142-5p. Subsequently, loss of PDCD4 was able to retard injury in HK-2 cells exposed to CoCl2. Thus, we suggest that XIST regulates miR-142-5p and PDCD4, and it has the potential to function as a biomarker in therapeutic strategies for AKI.

Two-Phase System Model to Assess Hydrophobic Organic Compound Sorption to Dissolved Organic Matter.

The equilibrium partition of organic compounds to dissolved organic matter (DOM) is an essential process that affects their environmental risks. Traditional models cannot accurately assess this process as the variability of DOM is not properly accounted for. The two-phase system (TPS) model was developed with the consideration of the variability that stems from both organic compounds and DOM. In this study, we examined the applicability of the TPS model for the prediction of the organic carbon-water partition coefficient (KOC) of hydrophobic organic compound (HOC) sorption to aquatic and sediment DOM using a diverse set of 17 organic compounds and 53 DOM samples. The TPS model showed good predictive power (RMSE < 0.20) without calibration, outperforming currently used linear free energy relationship models (RMSE > 0.28). The significance of DOM properties in the sorption behavior was quantitatively analyzed based on the TPS model. The spatial pattern of KOC for HOC sorption to aquatic DOM in Lake Taihu, the third largest freshwater lake in China, was assessed using the TPS model. Our results suggest that the TPS model has great potential to facilitate the routine assessment of the partition behavior of HOCs in aquatic systems for environmental risk assessment.

Dissolved Black Carbon Facilitates Photoreduction of Hg(II) to Hg(0) and Reduces Mercury Uptake by Lettuce (Lactuca sativa L.).

Here, we investigated the photoreduction of Hg(II) (Hg(NO3)2) mediated by dissolved black carbon (DBC, <0.45 µm size fraction) collected from water extracts of biochar derived by pyrolyzing crop residues (rice, soybean, and peanut). Under simulated sunlight conditions, the presence of 5 mg C/L DBC significantly facilitated the production of Hg(0) from Hg(II) (initially at 10 nmol/L) with a reduction ratio of 73 ± 4% in 5.3 h. Inhibition of photolysis-induced reactive oxygen species by a quencher or removal of dissolved oxygen indicated that Hg(II) was mainly reduced by superoxide anion (O2•-). Reduction by electrons transferred from photoexcited DBC components or by organic free radicals produced from photo-Fenton-like reactions was also proposed to play a role. Contrary to dissolved humic substances, the DBC-mediated photoreduction of Hg(II) led to unique positive mass-independent isotopic fractionation (MIF) of Hg(0) (Δ199Hg = 1.8 ± 0.3‰), which was attributed to the dominance of secondary Hg(II) reduction by O2•-. The leachate from soil amended with rice biochar at 1-5% mass ratios exhibited significantly higher photocatalytic efficiency than that from unamended soil (wherein the reduced Hg(0) increased from 27 ± 1 to 63 ± 2% in maximum), and the efficiency positively correlated with the percentage of amended biochar. Under natural illumination conditions, the total mercury and/or methylmercury uptake by roots, shoots, and leaves of lettuce (Lactuca sativa L.) grown in water extracts of rice biochar-amended soil was consistently lower (up to 70 ± 20%) than that without the biochar amendment. The findings highlight that DBC might play an important and previously unrecognized role in the biogeochemical cycle and the environmental impact of mercury.

Role of Extracellular Polymeric Substances in Microbial Reduction of Arsenate to Arsenite by Escherichia coli and Bacillus subtilis.

We show that arsenate can be readily reduced to arsenite on cell surfaces of common bacteria (E. coli or B. subtilis) or in aqueous dissolved extracellular polymeric substances (EPS) extracted from different microorganisms (E. coli, B. subtilis, P. chrysosporium, D. gigas, and a natural biofilm) in the absence of exogenous electron donors. The efficiency of arsenate reduction by E. coli after a 7-h incubation was only moderately reduced from 51.3% to 32.7% after knocking out the arsenic resistance genes (arsB and arsC). Most (>97%) of the reduced arsenite was present outside the bacterial cells, including for the E. coli blocked mutant lacking arsB and arsC. Thus, extracellular processes dominated arsenate reduction. Arsenate reduction was facilitated by removing EPS attached to E. coli or B. subtilis, which was attributed to enhanced access to reduced extracellular cytochromes. This highlights the role of EPS as a permeability barrier to arsenate reduction. Fourier-transform infrared (FTIR) combined with other chemical analyses implicated some low-molecular weight (<3 kDa) molecules as electron donors (reducing saccharides) and electron transfer mediators (quinones) in arsenate reduction by dissolved EPS alone. These results indicate that EPS act as both reducing agent and permeability barrier for access to reduced biomolecules in bacterial reduction of arsenate.

Impact of the Three Gorges Dam on the Quality of Riverine Dissolved Organic Matter.

The Three Gorges Dam (TGD) is the largest hydropower facility in the world, influencing the riverine hydrology and mass flux in the Yangtze River. Little is known about its impact on the riverine dissolved organic matter (DOM) quality. In this work, the water quality and DOM quality for water samples collected from the upstream and downstream sites of TGD were investigated. The presence of TGD significantly affects the quantity and quality of DOM but has no pronounced effect on nutrient concentrations. Upstream DOM had higher concentration but lower average molecular weight and aromaticity than the downstream DOM. The biological processes in the dam reservoir contribute significantly to upstream DOM. In the downstream sites, terrestrial DOM input raises the average molecular weight and aromaticity of the overall DOM pool. These results suggest that TGD will influence not only the mass flux of organic carbon but also its quality and lability, which has both environmental and ecological significance.

Prediction of Apolar Compound Sorption to Aquatic Natural Organic Matter Accounting for Natural Organic Matter Hydrophobicity Using Aqueous Two-Phase Systems.

The equilibrium partitioning of organic compounds to natural organic matter (NOM) plays a key role in their environmental fate as well as bioavailability. In this study, a prediction model for organic compound sorption to NOM was theoretically derived based on two-phase systems. In this model, the hydrophobicity of NOM was scaled by their partition coefficients in an aqueous two-phase system (KATPS) and that of organics was scaled by their octanol-water partition coefficients (KOW). The model uses only KATPS and KOW as variables. Coefficients in the model were determined using a data set including the organic carbon-water partition coefficient (KOC) of four polycyclic aromatic hydrocarbons (PAHs) sorption to 10 NOM samples collected from surface waters. The resulting model was validated using additional NOM samples and reference NOM, which suggested good prediction power for PAH sorption to aquatic NOM. The model performance was compared with commonly used linear free energy relationship models, and its applicability was discussed. Sorption behavior unexpected by this model is attributed to additional sorption mechanisms other than partitioning. Overall, this approach allows prediction of KOC for apolar organic compound sorption to aquatic NOM simply using their respective partition coefficients in two-phase systems based on a specific model.

Sunlight-Mediated Lead and Chromium Release from Commercial Lead Chromate Pigments in Aqueous Phase.

Lead chromate pigments are included in a group of the most widely used pigments, which account for 3% of worldwide lead consumption. This study reports the photoactivity of commercial lead chromate pigment (i.e., chrome yellow) under simulated sunlight. It underwent photodissolution in the presence of organic acid and dissolved organic matter in the aqueous phase, releasing Pb(II) and Cr(III). Pb(II) was released more readily than Cr(III) which mainly formed hydroxides and oxides. The photodissolution can be activated by light with a wavelength <514 nm. The reaction is mediated by the reduction of Cr(VI) in the pigment by self-generated electrons. The kinetics were mainly affected by the electron-hole separation efficiency which can be enhanced by electron donors. The reaction rate decreases with increasing solution pH as the photodissolution process consumes protons. The photodissolution of the chrome yellow pigment was further confirmed in a river water sample under natural sunlight, with 11.28% of lead and 2.56% of chromium released in 7 h. This study highlights the importance of considering photochemical processes in risk assessments and regulations of commercial semiconductor pigments, which are currently based on their solubility.

High Three-Dimensional Detection Accuracy in Piezoelectric-Based Touch Panel in Interactive Displays by Optimized Artificial Neural Networks.

High detection accuracy in piezoelectric-based force sensing in interactive displays has gained global attention. To achieve this, artificial neural networks (ANN)-successful and widely used machine learning algorithms-have been demonstrated to be potentially powerful tools, providing acceptable location detection accuracy of 95.2% and force level recognition of 93.3% in a previous study. While these values might be acceptable for conventional operations, e.g., opening a folder, they must be boosted for applications where intensive operations are performed. Furthermore, the relatively high computational cost reported prevents the popularity of ANN-based techniques in conventional artificial intelligence (AI) chip-free end-terminals. In this article, an ANN is designed and optimized for piezoelectric-based touch panels in interactive displays for the first time. The presented technique experimentally allows a conventional smart device to work smoothly with a high detection accuracy of above 97% for both location and force level detection with a low computational cost, thereby advancing the user experience, and serviced by piezoelectric-based touch interfaces in displays.

Investigation of Multi-Plane Scheme for Compensation of Fringe Effect of Electrical Resistance Tomography Sensor.

Conventional electrical resistance tomography (ERT) sensors suffer from the fringe effect, i.e., severe distortion of the electric field on both ends of the measurement electrodes, leading to a 3D sensing region for a 2D sensor. As a result, the objects outside an ERT sensor plane affect the sensing and hence image, i.e., deteriorating the image quality. To address this issue, a multiple-plane ERT sensor scheme is proposed in this paper. With this scheme, auxiliary sensor planes are used to provide references for the fringe effect of the measurement plane, for compensation by subtracting the weighed influence of the fringe effect. Simulation results show that the proposed scheme, either three-plane or two-plane sensor, can compensate for the fringe effect induced by objects outside the measurement plane with a variety of axial object distributions, i.e., several non-conductive bars or conductive bars placed at different cross-sectional and axial positions inside the sensor. Experiments were carried out. Images obtained with single-plane and multiple-plane ERT sensors are compared, and the proposed compensation scheme has been hence verified.

Dissolved Black Carbon as an Efficient Sensitizer in the Photochemical Transformation of 17ß-Estradiol in Aqueous Solution.

Dissolved black carbon (DBC) is an important component of the dissolved organic matter (DOM) pool. Nonetheless, little is known about its role in the photochemical processes of organic contaminants. This study investigated the effect of DBC on the phototransformation of 17ß-estradiol in aqueous solutions under simulated sunlight. Four well-studied dissolved humic substances (DHS) were included as comparisons. DBC acted as a very effective sensitizer to facilitate the phototransformation of 17ß-estradiol. The apparent quantum yield for 17ß-estradiol phototransformation mediated by DBC was approximately six times higher than that by DHS at the same carbon concentration. Quenching experiments suggested that direct reaction with triplet-excited state DBC (3DBC*) was the predominant pathway of 17ß-estradiol phototransformation. The higher mediation efficiency of DBC than DHS is likely due to the higher contents of aromatic groups and smaller molecular sizes, which facilitated the generation of 3DBC*. The apparent quantum yield of triplet-excited states production for DBC was 4-8 times higher than that for DHS. The results suggest that 3DBC* may have a considerable contribution to the overall photoreactivity of triplet-excited state DOM in aquatic systems. Our findings also imply that DBC can play an important role in the phototransformation of organic contaminants in the environments.