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Geochemical compositions can be used to determine the tectonic setting of sedimentary basins, while where the link of source to sink is no longer preserved, detrital zircon age patterns can aid in resolving the original basin setting. The metasedimentary Legoupil Formation, located at Cape Legoupil and the Schmidt Peninsula, could give a hint for the tectonic evolution of Antarctic Peninsula. In this contribution, we constrain the sedimentary provenance of the Legoupil Formation through geochemistry and detrital zircon U-Pb geochronology. The petrography and geochemical features indicate that the provenance of the Legoupil Formation could be felsic rocks. Detrital zircon grains record a steady supply of Permian and Ordovician material into the Legoupil Formation. The youngest concordant zircon ages of 262 Ma suggest that the depositional time of Legoupil Formation is no older than Late Permian. The detrital zircon age spectrum of Legoupil Formation suggests that the Legoupil Formation sediments should be derived from regional sources endemic to western Gondwana prior to its breakup. Together with the previous studies, geochemistry and detrital zircons reflect an active continental margin tectonic setting and the detrital zircon spectra of Legoupil Formation are similar to the ones deposited in forearc tectonic setting. [ABSTRACT FROM AUTHOR]

Acoustic scene classification (ASC) is the process of identifying the acoustic environment or scene from which an audio signal is recorded. In this work, we propose an encoder-decoder-based approach to ASC, which is borrowed from the SegNet in image semantic segmentation tasks. We also propose a novel feature normalization method named Mixup Normalization, which combines channel-wise instance normalization and the Mixup method to learn useful information for scene and discard specific information related to different devices. In addition, we propose an event extraction block, which can extract the accurate semantic segmentation region from the segmentation network, to imitate the effect of image segmentation on audio features. With four data augmentation techniques, our best single system achieved an average accuracy of 71.26% on different devices in the Detection and Classification of Acoustic Scenes and Events (DCASE) 2020 ASC Task 1A dataset. The result indicates a minimum margin of 17% against the DCASE 2020 challenge Task 1A baseline system. It has lower complexity and higher performance compared with other state-of-the-art CNN models, without using any supplementary data other than the official challenge dataset. [ABSTRACT FROM AUTHOR]

We report here the synthesis and structural characterization of the first binary iron arsenide cluster anion, [Fe3(As3)3(As4)]3−, present in both [K([2.2.2]crypt)]3[Fe3(As3)3(As4)] (1) and [K(18‐crown‐6)]3[Fe3(As3)3(As4)]⋅en (2). The cluster contains an Fe3 triangle with three short Fe−Fe bond lengths (2.494(1) Å, 2.459(1) Å and 2.668(2) Å for 1, 2.471(1) Å, 2.473(1) Å and 2.660(1) Å for 2), bridged by a 2‐butene‐like As4 unit. An analysis of the electronic structure using DFT reveals a triplet ground state with direct Fe−Fe bonds stabilizing the Fe3 core. [ABSTRACT FROM AUTHOR]

We report here the synthesis and structural characterization of the first binary iron arsenide cluster anion, [Fe3(As3)3(As4)]3−, present in both [K([2.2.2]crypt)]3[Fe3(As3)3(As4)] (1) and [K(18‐crown‐6)]3[Fe3(As3)3(As4)]⋅en (2). The cluster contains an Fe3 triangle with three short Fe−Fe bond lengths (2.494(1) Å, 2.459(1) Å and 2.668(2) Å for 1, 2.471(1) Å, 2.473(1) Å and 2.660(1) Å for 2), bridged by a 2‐butene‐like As4 unit. An analysis of the electronic structure using DFT reveals a triplet ground state with direct Fe−Fe bonds stabilizing the Fe3 core. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) is empowering personalized online news delivery to accommodate people's information needs and combat information overload. However, AI models learned from user data are inheriting and amplifying some underlying human prejudice such as the sentiment bias of news reading, which may lead to potential negative societal effects and ethical concerns. Here, substantial evidence shows that AI is manipulating the sentiment orientation of news displayed to users by promoting the presence chance of negative news, even if there is no human interference. To mitigate this manipulation, a sentiment-debiasing method based on a decomposed adversarial learning framework is proposed, which can reduce 97.3% of sentiment bias with only 2.9% accuracy sacrifice. Our work provides the potential in improving AI's responsibility in many human-centered applications such as online journalism and information spread. [ABSTRACT FROM AUTHOR]

Comprehensive Summary: Polyarsenides containing coinage metals, [As7Cu(PPh3)]2– (1) and [M2As14]4– (M = Cu, 2; Ag, 3), were synthesized by reactions of the nominal composition K3As7 with Group 11 metal complexes. The possible intermediate, cluster 1, was isolated from the solution phase through subtle changes in reaction conditions in the formation process of complex 2. Hence, we establish the pathway of the bimetallic bridged clusters [Cu2As14]4– by the oxidation of the [As7Cu(PPh3)]2–. Quantum chemical calculations reveal the presence of metallophilic interaction in clusters 2 and 3. [ABSTRACT FROM AUTHOR]

Acid rain is a global environmental issue and causes serious adverse impacts on natural ecosystems and human health. The acid rain and its subsequent impacts have been extensively studied in temperate regions and in big cities globally, but the monitoring of acid rain in non-urban areas in subtropical region is still limited. Here, we analyze 18 years of water acidity observations from a non-urban site in western Pearl River Delta region, south China. From 2000 to 2018, annual mean precipitation pH values in the study site showed a marked increase (P<0.0001) from 4.96 in 2000 to 6.88 in 2018. This 18-year dataset of precipitation acidity shows a clear recovery from acid deposition over the annual period, dry seasons and wet seasons. Within a year, precipitation pH was relatively lower in dry seasons (5.46±0.95) than in wet seasons (5.80±0.89) during the whole study period, and the seasonal pattern of precipitation pH was amplified during drier years as a strong dilution effect was detected between precipitation amount and its acidity. The pH of surface runoff water (4.74±0.70) was significantly lower than that of precipitation as a result of the regulating effects of the highly acidified soil and the rich humus on the forest floor. The groundwater pH (6.32±0.63) was significantly higher than the precipitation pH especially during dry seasons. The results of the present study indicated that the groundwater has a strong acid buffer and neutralizing effects and thus plays an important role in supplies of clean water. [ABSTRACT FROM AUTHOR]

Many end-to-end approaches have been proposed to detect predefined keywords. For scenarios of multi-keywords, there are still two bottlenecks that need to be resolved: (1) the distribution of important data that contains keyword(s) is sparse, and (2) the timestamps of the detected keywords are inaccurate. In this paper, to alleviate the first issue and further improve the performance of the end-to-end ASR front-end, we propose the biased loss function for guiding the recognizer to pay more attention to the speech segments containing the predefined keywords. As for the second issue, we solve this problem by modifying the force alignment applied to the end-to-end ASR front-end. To get the frame-level alignment, we utilize a Gaussian Mixture Model-Hidden Markov Model (GMM-HMM) based acoustic model (AM) for auxiliary. The proposed system is evaluated in the OpenSAT20 held by the National Institute of Standards and Technology (NIST). The performance of our end-to-end KWS system is comparable to the conventional hybrid KWS system, sometimes even slightly better. With fusion results of the end-to-end and conventional KWS systems, we won the first prize in the KWS track. On the dev dataset (a part of SAFE-T corpus), the system outperforms the baseline by a large margin, i.e., our system with GMM-HMM aligner has a lower segmentation-aware word error rates (relatively 7.9–19.2% decrease) and higher overall Actual term-weighted values (relatively 3.6–11.0% increase), which demonstrates the effectiveness of the proposed method. For more precise alignments, we can use DNN-based AM as alignmentor at the cost of more computation. [ABSTRACT FROM AUTHOR]

Many end-to-end approaches have been proposed to detect predefined keywords. For scenarios of multi-keywords, there are still two bottlenecks that need to be resolved: (1) the distribution of important data that contains keyword(s) is sparse, and (2) the timestamps of the detected keywords are inaccurate. In this paper, to alleviate the first issue and further improve the performance of the end-to-end ASR front-end, we propose the biased loss function for guiding the recognizer to pay more attention to the speech segments containing the predefined keywords. As for the second issue, we solve this problem by modifying the force alignment applied to the end-to-end ASR front-end. To get the frame-level alignment, we utilize a Gaussian Mixture Model-Hidden Markov Model (GMM-HMM) based acoustic model (AM) for auxiliary. The proposed system is evaluated in the OpenSAT20 held by the National Institute of Standards and Technology (NIST). The performance of our end-to-end KWS system is comparable to the conventional hybrid KWS system, sometimes even slightly better. With fusion results of the end-to-end and conventional KWS systems, we won the first prize in the KWS track. On the dev dataset (a part of SAFE-T corpus), the system outperforms the baseline by a large margin, i.e., our system with GMM-HMM aligner has a lower segmentation-aware word error rates (relatively 7.9–19.2% decrease) and higher overall Actual term-weighted values (relatively 3.6–11.0% increase), which demonstrates the effectiveness of the proposed method. For more precise alignments, we can use DNN-based AM as alignmentor at the cost of more computation. [ABSTRACT FROM AUTHOR]

Soil pollution is one of the most important issues in environmental governance at present. Using scientific and reasonable methods to estimate the economic losses caused by soil pollution is the basis for maximizing the effectiveness of governance resources. This study combines the methods of mixed group discussion and literature analysis to establish preliminary soil pollution value loss measurement indicators. The Delphi method is used to modify, add, and delete indicators to obtain a set of feasible soil pollution value loss measurement indicator systems. It laid a method foundation for further quantifying the loss of soil pollution value and provided support to related government decisions such as land resource management and soil pollution control. The response coefficients of the two rounds of expert consultations were 81.2% and 77.8%; the degree of expert authority was 0.647 and 0.708; the coordination coefficients were 0.155 and 0.194; the final indicator system included three dimensions of economic, social, and environmental, a total of eight indicators. The experts in the soil pollution value loss measurement index system established in this study have unified final opinions and a good degree of coordination, which can be used to measure soil pollution value loss. [ABSTRACT FROM AUTHOR]

A simple and efficient system was developed for the ligand‐free Pd‐catalyzed Suzuki–Miyaura reaction in water under mild conditions. Quaternary ammonium hydroxides with long chains were found to be very suitable bases. This ligand‐free Pd‐catalyzed Suzuki–Miyaura reaction showed improved durability in water with Pd loadings decreased to ppm level. Bases were shown to stabilize active palladium species in addition to acting as a base during the catalytic process. In the catalytic system with a strong base, the soluble active PdII ion exhibited anti‐reduction properties, which prevented aggregation and deactivation of Pd species. The entire catalytic system could be recycled after separating the product by simple filtration. The water‐compatible and air‐stable effective catalytic protocol described herein represents an attractive and green synthetic advance in Suzuki–Miyaura couplings. [ABSTRACT FROM AUTHOR]

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An efficient iodine‐mediated aza‐Michael addition/C−H functionalization procedure for the synthesis of indoles was achieved in one pot. By simple aza‐Michael addition between anilines and α,β‐ynones, a series of N‐aryl enaminones intermediate was generated, followed by iodine‐mediated C−H functionalization, a wide variety of indole derivatives were obtained in moderate to excellent yields under transition‐metal‐free conditions. Control experiments and in situ ESI‐MS analysis indicated the reaction occurred via a radical mechanism. Tandem bike: A highly efficient iodine‐mediated aza‐Michael addition/C−H functionalization procedure for the synthesis of indoles from aniline and α,β‐ynones was achieved. The reaction provides access to a wide variety of indole derivatives, in moderate to excellent yields under transition‐metal‐free conditions. [ABSTRACT FROM AUTHOR]

End-to-end speech recognition systems have been successfully implemented and have become competitive replacements for hybrid systems. A common loss function to train end-to-end systems is connectionist temporal classification (CTC). This method maximizes the log likelihood between the feature sequence and the associated transcription sequence. However there are some weaknesses with CTC training. The main weakness is that the training criterion is different from the test criterion, since the training criterion is log likelihood, while the test criterion is word error rate. In this work, we introduce a new lattice based transcription loss function to address this deficiency of CTC training. Compared to the CTC function, our new method optimizes the model directly using the transcription loss. We evaluate this new algorithm in both a small speech recognition task, the Wall Street Journal (WSJ) dataset, a large vocabulary speech recognition task, the Switchboard dataset and a low resource speech recognition task, OpenKWS16. Results demonstrate that our algorithm outperforms a traditional CTC criterion, and achieves 7% WER relative reduction. In addition, we compare our new algorithm to some discriminative training algorithms, such as state-level minimum Bayes risk (SMBR) and minimum word error (MWE), with results supporting the benefits of the new algorithm. [ABSTRACT FROM AUTHOR]

A novel, hydrophilic and recyclable methoxypolyethylene glycol (PEG)-modulated s-triazine-based multifunctional Schiff base/N,P-ligand L9 was prepared and used in Pd-catalyzed Heck-type carbonylative coupling reactions, affording diverse chalcone derivatives and 1,4-dicarbonyl esters in good yields. [ABSTRACT FROM AUTHOR]

Secondary forests account for a large amount of subtropical forest due to persistent anthropogenic disturbance in China. The interaction between vegetation and soil during recovery process is rather complex and dependent on forest conditions. Understanding how vegetation and soil properties changes and how their relationship develops in secondary forests is key to effective forest restoration and management. Here we explored the patterns of vegetation and soil properties as well as their correlations during forest recovery process in a subtropical forest in south China. Plots of three forest types, i.e., broadleaf-conifer mixed forest, broadleaved forest and old growth stand, were established to represent the recovery stages. The results showed that diversity patterns in the tree, shrub and herb layers were different: in the tree layer the species diversity peaked at the intermediate stage, while in the understory layers it decreased chronologically. Most of the soil factors showed an increasing trend, and different effects of soil factors were found for the three layers as well as for the two spatial scales. Together, our results suggested that vegetation and soil might be interdependent during the recovery course. Further studies are needed on exploring how vegetation interplays with soil at different scales and how nutrient limitations affects the vegetation development in a chronosequence. [ABSTRACT FROM AUTHOR]

It is still a changing problem of choosing the most relevant ones from multiple features for their specific machine learning tasks. However, feature selection provides an effective solution to it, which aims to choose the most relevant and least redundant features for data analysis. In this paper, we present a feature selection algorithm termed as semi-supervised minimum redundancy maximum relevance. The relevance is measured by a semi-supervised filter score named constraint compensated Laplacian score, which takes advantage of the local geometrical structures of unlabeled data and constraint information from labeled data. The redundancy is measured by a semi-supervised Gaussian mixture model-based Bhattacharyya distance. The optimal feature subset is selected by maximizing feature relevance and minimizing feature redundancy simultaneously. We apply our algorithm in audio classification task and compare it with other known feature selection methods. Experimental results further prove that our algorithm can lead to promising improvements. [ABSTRACT FROM AUTHOR]

This paper proposes a branch-and-bound algorithm for solving the unit-modulus constrained complex quadratic programming problems (CQPP). We study the convex hull of a unit-modulus complex variable with argument constraints, derive new valid linear inequalities from the convex hull, construct an improved semidefinite relaxation of CQPP, and then design an efficient algorithm for solving CQPP globally. The proposed algorithm branches on the sets of argument constraints and derives new valid inequalities from the partitioned sets of arguments. Numerical results are included to support the effectiveness of the proposed algorithm for finding a global solution to CQPP. [ABSTRACT FROM AUTHOR]

Multicomponent ring-opening/Huisgen cycloaddition reactions combined with CO2 capture with a polyurea-encapsulated copper salt as a catalyst that in situ formed from simple CuCl and soluble polyurea during the reaction were carried out successfully for the synthesis of β-hydroxytriazoles under exceptionally mild conditions, in which the polyurea-encapsulated copper(i) chloride proved to be a robust and recyclable catalyst system with high yields as well as excellent chemoselectivity in this reaction. [ABSTRACT FROM AUTHOR]

It was found that catalytic allylation of various cyanoacetamides proceeded smoothly and efficiently in environmentally benign PEG-400 (PEG=poly(ethylene glycol)) in the presence of Pd(OAc)2 and novel triazine-derived multifunctional ligand L1, with which this reaction could afford the structurally diverse mono- and double allylated adducts in good to excellent yields as well as good chemo- and regioselectivity. In addition, this Pd/ L1/PEG-400 catalyst system could be recycled for five runs with good yield and high efficiency, which supported the notion that the triazine-containing Schiff base based phosphine ligand could be a multifunctional and reusable ligand encapsulated in PEG-400. [ABSTRACT FROM AUTHOR]

Tunable organometallic Lewis acid catalysts were developed by combining salicylic acid (H-Sal) with benzoic acid (H-Ben), 4-fluorobenzoic acid (H-BenF) and 3-thiophenic acid (H-Th), as coligands for mixed bis-carboxylate titanocene complexes. Three air-stable complexes [CpTi(η-HSal)(η-Ben)] ( 1), [CpTi(η-HSal)(η-BenF)] ( 2) and [CpTi[η-HSal][(η-Th)] ( 3) were prepared in high yields by the reaction of salicylato titanocene chelate with carboxylate ligands. The mixed bis-carboxylate titanocene complexes were fully characterized by physicochemical and spectroscopic methods. Single-crystal X-ray diffraction studies revealed Ti-O bond distances in 1, 2 and 3 of 1.972(3), 1.9245(18) and 1.912(5) Å, respectively, while the bond distances involving the coligands of 1, 2 and 3 are 1.908(3) Å (Ti-O), 1.9296(19) Å (Ti-O) and 1.945(5) Å (Ti-O), respectively. These bis-carboxylate titanocene complexes showed satisfactory activities and selectivities in Mannich and cross-aldol reactions. Notably, complex 3 bearing the labile thiophene carboxylate ligand gave high yields with a diastereomer ratio (d.r.) as high as 1:99 for the direct Mannich reactions of benzaldehyde, cyclohexanone and aniline. In cross-aldol reaction of benzaldehyde and cyclohexanone, 1 and 2 successfully catalyzed the formation of double-aldol products in up to 99 % yield. [ABSTRACT FROM AUTHOR]

A new voice activity detection algorithm based on long-term pitch divergence is presented. The long-term pitch divergence not only decomposes speech signals with a bionic decomposition but also makes full use of long-term information. It is more discriminative comparing with other feature sets, such as long-term spectral divergence. Experimental results show that among six analyzed algorithms, the proposed algorithm is the best one with the highest non-speech hit rate and a reasonably high speech hit rate. [ABSTRACT FROM AUTHOR]

Image segmentation and image denoising are two important and fundamental topics in the field of image processing. Geometric active contour model based on level set method can deal with the problem of image segmentation, but it does not consider the problem of image denoising. In this paper, a new diffusion equation model for noisy image segmentation is proposed by incorporating some classical diffusion equation denoising models into the segmental process. An assumption about the connection between the image intensity and level set function is given firstly. Some classical denoising models are employed to describe the evolution of level set function secondly. The final nonlinear diffusion equation model for noisy image segmentation is built thirdly. Then image segmentation and image denoising are combined in a united framework. The segmental results can be presented by level set function. Experimental results show that the new model has the advantage of noise resistance and is superior to traditional segmentation model. [ABSTRACT FROM AUTHOR]

In addition to ammonia-oxidizing bacteria (AOB) the more recently discovered ammonia-oxidizing archaea (AOA) can also oxidize ammonia, but little is known about AOA community structure and abundance in subtropical forest soils. In this study, both AOA and AOB were investigated with molecular techniques in eight types of forests at surface soils (0-2 cm) and deep layers (18-20 cm) in Nanling National Nature Reserve in subtropical China. The results showed that the forest soils, all acidic (pH 4.24-5.10), harbored a wide range of AOA phylotypes, including the genera Nitrosotalea, Nitrososphaera, and another 6 clusters, one of which was reported for the first time. For AOB, only members of Nitrosospira were retrieved. Moreover, the abundance of the ammonia monooxygenase gene ( amoA) from AOA dominated over AOB in most soil samples (13/16). Soil depth, rather than forest type, was an important factor shaping the community structure of AOA and AOB. The distribution patterns of AOA and AOB in soil layers were reversed: AOA diversity and abundances in the deep layers were higher than those in the surface layers; on the contrary, AOB diversity and abundances in the deep layers were lower than those in the surface layers. Interestingly, the diversity of AOA was positively correlated with pH, but negatively correlated with organic carbon, total nitrogen and total phosphorus, and the abundance of AOA was negatively correlated with available phosphorus. Our results demonstrated that AOA and AOB were differentially distributed in acidic soils in subtropical forests and affected differently by soil characteristics. [ABSTRACT FROM AUTHOR]

Currently, phonotactic spoken language recognition (SLR) and acoustic SLR systems are widely used language recognition systems. Parallel phone recognition followed by vector space modeling (PPRVSM) is one typical phonotactic system for spoken language recognition. To achieve better performance, researchers assumed to extract more complementary information of the training data using phone recognizers trained for multiple language-specific phone recognizers, different acoustic models and acoustic features. These methods achieve good performance but usually compute at high computational cost and only using complementary information of the training data. In this paper, we explore a novel approach to discriminative vector space model (VSM) training by using a boosting framework to use the discriminative information of test data effectively, in which an ensemble of VSMs is trained sequentially. The effectiveness of our boosting variation comes from the emphasis on working with the high confidence test data to achieve discriminatively trained models. Our variant of boosting also includes utilizing original training data in VSM training. The discriminative boosting algorithm (DBA) is applied to the National Institute of Standards and Technology (NIST) language recognition evaluation (LRE) 2009 task and show performance improvements. The experimental results demonstrate that the proposed DBA shows 1.8 %, 11.72 % and 15.35 % relative reduction for 30s, 10s and 3s test utterances in equal error rate (EER) than baseline system. [ABSTRACT FROM AUTHOR]

Ligand-mediated targeting of anticancer therapeutic agents is a useful strategy for improving anti-tumor efficacy. It has been reported that co-administration of a tumor-penetrating peptide iRGD (CRGDK/RGPD/EC) enhances the efficacy of anticancer drugs. Here, we designed an experiment involving co-administration of iRGD-SSL-DOX with free iRGD to B16-F10 tumor bearing mice to examine the action of free iRGD. We also designed an experiment to investigate the location of iRGD-modified SSL when co-administered with free iRGD or free RGD to B16-F10 tumor bearing nude mice. Considering the sequence of iRGD, we selected the GPDC, RGD and CRGDK as targeting ligands to investigate the targeting effect of these peptides compared with iRGD on B16-F10 and MCF-7 cells, with or without enzymatic degradation. Finally, we selected free RGD, free CRGDK and free iRGD as ligand to investigate the inhibitory effect on RGD-, CRGDK- or iRGD-modified SSL on B16-F10 or MCF-7 cells. Our results indicated that iRGD targeting to tumor cells was ligand–receptor mediated involving RGD to αv-integrin receptor and CRGDK to NRP-1 receptor. Being competitive effect, the administration of free iRGD would not be able to further enhance the anti-tumor activity of iRGD-modified SSL. There is no need to co-administrate of free iRGD with the iRGD-modified nanoparticles for further therapeutic benefit. [ABSTRACT FROM PUBLISHER]

Five chiral metal-organic coordination compounds (CMOCCs), {[Cu4O(Lvcz)2Br4] ·H2O} n ( 1), {[Cd(HLvcz)2(NO3)2] ·0.25H2O} n ( 2), {[Cu2(HLvcz)2I2] ·H2O} n ( 3), {[Ag(HLvcz)2]CF3SO3} n ( 4), and {[Co2(HLvcz)(bdc)2(dmf)2] ·dmf ·3H2O} n ( 5; HLvcz = voriconazole, bdc = terephthalic acid), have been successfully prepared and structurally characterized. The chiral drug ligand voriconazole exhibits diverse modes of coordination in the five complexes, resulting in the formation of various architectures and properties. Complex 1 is a tetranuclear cluster, complex 2 exhibits a 1D double-strand chain structure in which hydrogen-bonding interactions lead to a 3D supramolecular network, complex 3 is a 1D chain structure with two different types of rings based on the rhombic dimer Cu2I2, complex 4 is a 2D structure with 63 topology that contains four types of C-H ···F hydrogen bonds, and complex 5 affords a 3D framework with sxa topology. Their properties, such as chirality, second-order nonlinear optical (NLO) effects, ferroelectric behavior and dielectric anomalies, have been investigated in the solid state. [ABSTRACT FROM AUTHOR]

Support vector machines (SVMs) have played an important role in the state-of-the-art language recognition systems. The recently developed extreme learning machine (ELM) tends to have better scalability and achieve similar or much better generalization performance at much faster learning speed than traditional SVM. Inspired by the excellent feature of ELM, in this paper, we propose a novel method called regularized minimum class variance extreme learning machine (RMCVELM) for language recognition. The RMCVELM aims at minimizing empirical risk, structural risk, and the intra-class variance of the training data in the decision space simultaneously. The proposed method, which is computationally inexpensive compared to SVM, suggests a new classifier for language recognition and is evaluated on the 2009 National Institute of Standards and Technology (NIST) language recognition evaluation (LRE). Experimental results show that the proposed RMCVELM obtains much better performance than SVM. In addition, the RMCVELM can also be applied to the popular i-vector space and get comparable results to the existing scoring methods. [ABSTRACT FROM AUTHOR]

The facile synthesis of the starch hydrogel with anisotropic microstructure and dynamic behaviors was developed in the presence (A-gel) and absence of DC electric field (B-gel). The microstructures of hydrogels were characterized by environmental scanning electron microscope. Their electro-responsive property of hydrogels was investigated with their storage modulus (G′). The result demonstrates that theG′ ofA-gel is greater than that ofB-gel, and the modulus ofA-gel increases along with the external field, which signifies positive electroresponse. In addition, theG′ ofA-gel andB-gel (and) also continuously increases with increasing starch concentration, whereas both the maximum of modulus increment (ΔG′ =  − ) and that of modulus increment sensitivity (ΔG′/) occur with the starch weight fraction at around 36.5%. To enhance the electro-responsive effects of the hydrogels, dielectric particles were dispersed in the hydrogel. It is found that BaTiO3/chitosan core-shell composite particles significantly enhance the electroresponse of the hydrogel. The mechanism of the electro-response mode is proposed. [ABSTRACT FROM AUTHOR]

The synthesis of a new pyrene-containing Fischer carbene complex is described. The complex has a broad absorbance spectrum between 300 and 400 nm and, on excitation at 345 nm in CH2Cl2 solution, emission is observed at 395 and 415 nm. Emission is also observed in PBS buffer, but in this case the resulting spectra are much broader. Confocal and fluorescence lifetime imaging indicate that emission occurs on treating HeLa cells with the complex and co-localisation studies demonstrate that this is from the mitochondria and lipid-rich regions of the cell. [ABSTRACT FROM AUTHOR]