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Among the wide range of materials used for remediating environmental contaminants, modified and functionalised nanoclays show particular promise as advanced sorbents, improved dispersants, or biodegradation enhancers. However, many chemically modified nanoclay materials are incompatible with living organisms when they are used in natural systems with detrimental implications for ecosystem recovery. Here we critically review the pros and cons of functionalised nanoclays and provide new perspectives on the synthesis of environmentally friendly varieties. Particular focus is given to finding alternatives to conventional surfactants used in modified nanoclay products, and to exploring strategies in synthesising nanoclay-supported metal and metal oxide nanoparticles. A large number of promising nanoclay-based sorbents are yet to satisfy environmental biocompatibility in situ but opportunities are there to tailor them to produce “biocompatible” or regenerative/reusable materials. [ABSTRACT FROM AUTHOR]

The surface normal estimation from photometric stereo becomes less reliable when the surface reflectance deviates from the Lambertian assumption. The non-Lambertian effect can be explicitly addressed by physics modeling to the reflectance function, at the cost of introducing highly nonlinear optimization. This paper proposes a numerical compensation scheme that attempts to minimize the angular error to address the non-Lambertian photometric stereo problem. Due to the multifaceted influence in the modeling of non-Lambertian reflectance in photometric stereo, directly minimizing the angular errors of surface normal is a highly complex problem. We introduce an alternating strategy, in which the estimated reflectance can be temporarily regarded as a known variable, to simplify the formulation of angular error. To reduce the impact of inaccurately estimated reflectance in this simplification, we propose a numerical compensation scheme whose compensation weight is formulated to reflect the reliability of estimated reflectance. Finally, the solution for the proposed numerical compensation scheme is efficiently computed by using cosine difference to approximate the angular difference. The experimental results show that our method can significantly improve the performance of the state-of-the-art methods on both synthetic data and real data with small additive costs. Moreover, our method initialized by results from the baseline method (least-square-based) achieves the state-of-the-art performance on both synthetic data and real data with significantly smaller overall computation, i.e., about eight times faster compared with the state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Social media like Twitter have become globally popular in the past decade. Thanks to the high penetration of smartphones, social media users are increasingly going mobile. This trend has contributed to foster various location based services deployed on social media, the success of which heavily depends on the availability and accuracy of users' location information. However, only a very small fraction of tweets in Twitter are geo-tagged. Therefore, it is necessary to infer locations for tweets in order to attain the purpose of those location based services. In this paper, we tackle this problem by scrutinizing Twitter user timelines in a novel fashion. First of all, we split each user's tweet timeline temporally into a number of clusters, each tending to imply a distinct location. Subsequently, we adapt two machine learning models to our setting and design classifiers that classify each tweet cluster into one of the pre-defined location classes at the city level. The Bayes based model focuses on the information gain of words with location implications in the user-generated contents. The convolutional LSTM model treats user-generated contents and their associated locations as sequences and employs bidirectional LSTM and convolution operation to make location inferences. The two models are evaluated on a large set of real Twitter data. The experimental results suggest that our models are effective at inferring locations for non-geotagged tweets and the models outperform the state-of-the-art and alternative approaches significantly in terms of inference accuracy. [ABSTRACT FROM AUTHOR]

Abstract The traditional degradation of organic pollutants is based on the sacrifice of chemical or biological reagents. In this study, a purely physical technique was developed to break the chemical bonds and consequently decompose macromolecules in aqueous solution. Assisted with a high-speed mechanical blade, refined quartz sand grains with particularly sharp nano-scale edges can act as 'nano-knives', which are able to cut the long chain of carboxymethyl cellulose (CMC, as a model molecule). High performance size exclusion chromatography measurements evidenced that the original CMC molecules (41,000 Da) were decomposed into a series of smaller molecules (460, 1000, 2200, 21,000, 27,000 and 31,000 Da). Consequently, the initial viscosity of the CMC solution (2 g/L) rapidly decreased by approximately 50% after 3 min treatment by the nano-knife materials along with the mechanical blade. Fourier transform infrared (FTIR) spectra indicated that the original functional groups were still present and new functional groups were not produced after shearing. The intensity of the main functional group β-1-4-glycosidic bond (wavenumber 1062 cm− 1) was observed to markedly decrease after shearing. These results indicated that the long-chain CMC was cleaved into short-chain CMC. A degradation mechanism was proposed whereby the cutting force generated by the rapid motion of the nano-knives may be responsible for the breakage of β-1-4-glycosidic bonds in the macromolecular cellulose backbone. These results provide support for a potentially more affordable and environment-friendly strategy for physical-based decomposition of recalcitrant organic pollutants from aqueous solution without the need of chemical or biological reagents. Graphical abstract Unlabelled Image [ABSTRACT FROM AUTHOR]

Abstract Synthesis and application of reliable nanoscale materials is a progressive domain and the limelight of modern nanotechnology. Conventional physicochemical approaches for the synthesis of metal nanoparticles have become obsolete owing to costly and hazardous materials. There is a need to explore alternative, cost-effective and eco-friendly strategies for fabrication of nanoparticle (NPs). Green synthesis of noble metal nanoparticles has emerged as a promising approach in the last decade. Elucidation of the molecular mechanism is highly essential in the biological synthesis of noble metal nanoparticles (NPs) for the controlled size, shape, and monodispersity. Moreover, mechanistic insights will help to scale up the facile synthesis protocols and will enable biotransformation of toxic heavy metals hence also providing the detoxification effects. Therefore, the current review article has primarily targeted the mechanisms involved in the green synthesis of metal NPs, which have been reported during the last few years. Detailed mechanistic pathways have highlighted nitrate reductase as a principle reducing agent in the bacterial mediated synthesis and stabilization of NPs. Furthermore, we have highlighted the potential implications of these mechanisms in bioremediation and biomineralization processes, which can play a critical role in biogeochemical cycling and environmental impacts of heavy metals. We anticipate that this review article will help researchers to address the challenges of bioremediation and modern nanotechnology. Highlights • Various mechanisms of noble metal nanoparticles green synthesis were analyzed • Nitrate reductase as a principle reducing agent in the transformation of metals to nanoparticles • Potential implications of these mechanisms in bioremediation and biomineralization for biogeochemical cycles. [ABSTRACT FROM AUTHOR]

Abstract Many arsenic-bearing freshwaters are facing with eutrophication and consequent algae-induced anoxia/hypoxia events. However, arsenic cycling in eutrophic waters and its impact on public health are poorly understood. Laboratory simulation experiments are performed in this study to investigate the effect of algal blooms on the cycling of arsenic in a sediment–water–air system. We found that the anoxia induced by the degradation of algal biomass promoted an acute arsenic (mostly As(III)) release within two days from sediment to both the water and atmosphere, and the release effluxes were proportional to the algae dosage. The reduction and methylation of arsenic were enhanced at the sediment–water interface, owing to the significant increase in arsenate reductase genes (arr A and ars C), and arsenite methyltransferase genes (ars M) caused by increased anoxia. The analysis of synchrotron-based X-ray absorption spectroscopy indicated that the concomitantly released natural organic matter (NOM) and sulfur (S) at the sediment–water interface reduced the As(III) release to a certain extent in the later reducing period of incubation, by forming As 2 S 3 (43–51%) and As(III)-Fe-NOM (28–35%). Our results highlight the needs for the in-situ assessment of volatile arsenic in eutrophic freshwaters with its risk to human and animal health. Graphical abstract Image 1 Highlights • Algal blooms degradation increases arsenic toxic impact to public health. • Organic matter is a sequestrator of arsenic in anoxic sediments. • Hypoxia/anoxia induced microbial changes contribute to arsenic speciation. • Volatile arsenic in algal water-sediment systems is assessed i n-situ. [ABSTRACT FROM AUTHOR]

Abstract Hazardous outdoor air pollution has severely affected indoor air quality, threatening the health of billions of people. However, existing indoor air purification technologies are unsatisfactory due to some inherent limitations such as poor efficiency, limited target pollutants, the need to frequently replace filters or adsorbents, or the generation of harmful by-products. Here, we studied the effect and mechanism of cryogenic circulation for indoor air purification. Experimental results show that up to 99% of indoor PM 2.5 from ambient air was removed at −18 °C. The morphological measurements indicate that micrometer-sized particles are formed concomitantly with the reduction of nanometer- or submicron-sized particles, suggesting that condensational growth of fine particles is responsible for the removal. Applying the method to gaseous pollutant purification demonstrates that 98% of NO 2 is condensed and removed from the ambient air at −50 °C, implying that the method would be effective for multiple indoor pollutants with higher boiling points. Cryogenic condensation may provide a principle for continuous indoor air purification via modified air conditioners and humidifiers in cases where health benefits outweigh energy consumption concerns. Graphical abstract Unlabelled Image Highlights • Cryogenic condensation can remove indoor fine particulate and gaseous pollutants. • Phase transition of gaseous components induces haze pollutants removal. • Obtain clean indoor air for health through reasonable energy consumption. [ABSTRACT FROM AUTHOR]

Abstract Deep learning, especially Convolutional Neural Networks (CNNs), has been widely applied in many domains. The large number of parameters in a CNN allow it to learn complex features, however, they may tend to hinder generalization by over-fitting training data. Despite many previously proposed regularization methods, over-fitting is still a problem in training a robust CNN. Among many factors that lead to over-fitting, the numerous parameters of fully-connected layers (FCLs) of a typical CNN should be taken into account. This paper proposes the SparseConnect, a simple idea which alleviates over-fitting by sparsifying connections to FCLs. Experimental results on three benchmark datasets MNIST, CIFAR10 and ImageNet show that the SparseConnect outperforms several state-of-the-art regularization methods. [ABSTRACT FROM AUTHOR]

Neurons communicate nonlinearly through spike activities. Generalized linear models (GLMs) describe spike activities with a cascade of a linear combination across inputs, a static nonlinear function, and an inhomogeneous Bernoulli or Poisson process, or Cox process if a self-history term is considered. This structure considers the output nonlinearity in spike generation but excludes the nonlinear interaction among input neurons. Recent studies extend GLMs by modeling the interaction among input neurons with a quadratic function, which considers the interaction between every pair of input spikes. However, quadratic effects may not fully capture the nonlinear nature of input interaction. We therefore propose a staged point-process model to describe the nonlinear interaction among inputs using a few hidden units, which follows the idea of artificial neural networks. The output firing probability conditioned on inputs is formed as a cascade of two linear-nonlinear (a linear combination plus a static nonlinear function) stages and an inhomogeneous Bernoulli process. Parameters of this model are estimated by maximizing the log likelihood on output spike trains. Unlike the iterative reweighted least squares algorithm used in GLMs, where the performance is guaranteed by the concave condition, we propose a modified Levenberg-Marquardt (L-M) algorithm, which directly calculates the Hessian matrix of the log likelihood, for the nonlinear optimization in our model. The proposed model is tested on both synthetic data and real spike train data recorded from the dorsal premotor cortex and primary motor cortex of a monkey performing a center-out task. Performances are evaluated by discrete-time rescaled Kolmogorov-Smirnov tests, where our model statistically outperforms a GLM and its quadratic extension, with a higher goodness-of-fit in the prediction results. In addition, the staged point-process model describes nonlinear interaction among input neurons with fewer parameters than quadratic models, and the modified L-M algorithm also demonstrates fast convergence. [ABSTRACT FROM AUTHOR]

Combating hypoxia/anoxia is an increasingly common need for restoring natural waters suffering from eutrophication. Oxygen nanobubble modified natural particles were investigated for mitigating hypoxia/anoxia at the sediment-water interface (SWI) in a simulated column experiment. By adding oxygen nanobubble modified zeolites (ONMZ) and local soils (ONMS), the oxygen nanobubble concentrations (10 5 –10 7  particles/mL) were several orders of magnitude higher in the water than the original water solution (10 4  particles/mL) within 24 h. In the column experiment, an oxygen-locking surface sediment layer was formed after capping with ONMZ and ONMS particles. The synergy of diffusion of oxygen nanobubbles and retention of oxygen in this layer contributes to both the increase of DO and reversal of hypoxic conditions. The overlying water had significantly higher dissolved oxygen (DO) values (4–7.5 mg/L) over the experimental period of 127 days in ONMZ and ONMS compared with the control systems (around 1 mg/L). Moreover, the oxidation-reduction potential (ORP) was reversed from −200 mV to 180–210 mV and maintained positive values for 89 days in ONMZ systems. In the control systems, ORP was consistently negative and decreased from −200 mV to −350 mV. The total phosphorus (TP) flux from sediment to water across the SWI was negative in the ONMZ and ONMS treated systems, but positive in the control system, indicating the sediment could be switched from TP source to sink. The oxygen-locking capping layer was crucial in preventing oxygen consumption caused by the reduced substances released from the anoxic sediment. The study outlines a potentially promising technology for mitigating sediment anoxia and controlling nutrient release from sediments, which could contribute significantly to addressing eutrophication and ecological restoration. [ABSTRACT FROM AUTHOR]

Objective: Computer-aided estimation of brain connectivity aims to reveal information propagation in brain automatically, which has great potential in clinical applications, e.g., epilepsy foci diagnosis. Granger causality is an effective tool for directional connection analysis in multivariate time series. However, most existing methods based on Granger causality assume fixed time lags in information transmission, while the propagation delay between brain signals is usually changing constantly. Methods: We propose a Granger causality estimator based on the recurrent neural network, called RNN-GC, to deal with the multivariate brain connectivity detection problem. Our model takes input of time-series signals with arbitrary length of transmission time lags and learns the information flow from the data using the gated RNN model, i.e., long short-term memory (LSTM). The LSTM model can sequentially update the gates in memory cells to determine how many preceding points should be considered for prediction. Therefore, the LSTM-based RNN-GC estimator works well on varying-length time lags and shows effectiveness even on very long transmission delays. Results: Experiments are carried out in comparison with other methods using both simulation data and epileptic electroencephalography signals. The RNN-GC estimator achieves superior performance in brain connectivity estimation and shows robustness in modeling multivariate connections with varying-length time lags. Conclusion: The RNN-GC method is capable of modeling nonlinear and varying-length lagged information transmission and effective in directional brain connectivity estimation. Significance: The proposed method is promising to serve as a robust brain connection analysis tool in clinical applications. [ABSTRACT FROM AUTHOR]

Type 2 diabetes (T2D) mellitus is a complex metabolic disease commonly caused by insulin resistance in several tissues. We performed a matched two-dimensional metabolic screening in tissue samples from 43 multi-organ donors. The intra-individual analysis was assessed across five key metabolic tissues (serum, visceral adipose tissue, liver, pancreatic islets and skeletal muscle), and the inter-individual across three different groups reflecting T2D progression. We identified 92 metabolites differing significantly between non-diabetes and T2D subjects. In diabetes cases, carnitines were significantly higher in liver, while lysophosphatidylcholines were significantly lower in muscle and serum. We tracked the primary tissue of origin for multiple metabolites whose alterations were reflected in serum. An investigation of three major stages spanning from controls, to pre-diabetes and to overt T2D indicated that a subset of lysophosphatidylcholines was significantly lower in the muscle of pre-diabetes subjects. Moreover, glycodeoxycholic acid was significantly higher in liver of pre-diabetes subjects while additional increase in T2D was insignificant. We confirmed many previously reported findings and substantially expanded on them with altered markers for early and overt T2D. Overall, the analysis of this unique dataset can increase the understanding of the metabolic interplay between organs in the development of T2D. [ABSTRACT FROM AUTHOR]

In this study, a novel data-driven model is proposed for efficient spatial–temporal forecasting of the significant wave height (S W H), mean wave period (M W P), and mean wave direction (M W D) in the Pearl River Estuary, located in Southern China, using machine learning. The model utilizes machine learning techniques and employs a multi-layer perceptron (M L P) and decision tree (D T) based architecture following a matrix-to-matrix mapping strategy to establish the underlying spatial–temporal relationship between the wind and wave fields for four-day and ocean-scale forecasts. The training and testing of the model were carried out using long-term hindcast wave and wind datasets released by ERA5. A rectangular sea region covering an area of 5° × 5°in the Pearl River Estuary was regarded as the modeling domain. The data-driven model was validated against a 10 years of historical hindcast data, and the global errors were analyzed. The forecasting performance of the established model for tropical cyclone wave events was investigated in terms of both the spatial pattern and temporal variance of the SWH, MWP, and MWD. Extreme waves were generated using the proposed model and compared with the original hindcast results. The data-driven model showed promising potential for accurately capturing ambiguous patterns and features that are variant in both spatial and temporal dimensions, and exhibited obvious superiority over numerical wave modeling in terms of computational efficiency. • Machine-learning model for wave condition (SWH, MWP, MWD) forecasting is proposed. • Hindcast wave and wind datasets are used to train and test the model. • Spatial–temporal relationships between wind and wave fields are derived. • MLP and DT models with matrix-to-matrix mapping strategy are applied. • Model was validated against 11 years of historical hindcast typhoon data. [ABSTRACT FROM AUTHOR]

Heavy metal ions coexisting with salts in the contaminant water are difficult to remove due to the interference of salts. Herein, biochars were pyrolyzed by corn straw at different temperatures, aiming to remove Cr(VI) in the presence of salts. Results show that biochars had surprisingly selective adsorption of Cr(VI). X-ray photoelectron and X-ray absorption near edge spectra revealed that Cr(VI) was reduced to Cr(III). All the adsorption was conducted at pH ∼ 7, which differed from the previous studies that Cr(VI) could only be reduced at pH 2–4. Environmental persistent free radicals (EPFRs) on biochars were found to play the role in reducing Cr(VI) in neutral solutions, which was confirmed by electron spin resonance and free radical quenching. The biochar with EPFRs reveals a highly selective removal of Cr(VI), which has implications for the remediation of contaminated water. This work provides a new insight into biochar’s properties and potential environmental applications. [ABSTRACT FROM AUTHOR]

Key message: HT-induced ROS burst in developing anther is closely related to the lowered CAT activity as the result of the markedly suppressed OsCATB transcript, thereby causing severe fertility injury for rice plants exposed to HT at meiosis stage.Abstract: The reproductive stage of rice plants is highly sensitive to heat stress. In this paper, different rice cultivars were used to investigate the relationship of HT-induced floret sterility with reactive oxygen species (ROS) detoxification in rice anthers under well-controlled climatic conditions. Results showed that high temperature (HT) exposure significantly enhanced the ROS level and malondialdehyde (MDA) content in developing anther, and the increase in ROS amount in rice anther under HT exposure was closely associated with HT-induced decline in the activities of several antioxidant enzymes. For various antioxidant enzymes, SOD and CAT were more susceptible to the ROS burst in rice anther induced by HT exposure than APX and POD, in which SOD and CAT activity in developing anther decreased significantly by HT exposure, whereas APX activity was relatively stable among different temperature regimes. HT-induced decrease in CAT activity was attributable to the suppressed transcript of OsCATB. This occurrence was strongly responsible for HT-induced increase in ROS level and oxidative-damage in rice anther, thereby it finally caused significant reduction in pollen viability and floret fertility for the rice plants exposed to HT during meiosis. Exogenous application of 1000 µM salicylic acid (SA) may alleviate HT-induced reduction in pollen viability and floret fertility, concomitantly with the increased CAT activity and reduced ROS level in rice anther. [ABSTRACT FROM AUTHOR]

Repetitive transcranial magnetic stimulation (rTMS) has been proposed as an experimental approach for the treatment of disorders of consciousness (DOC). To date, there has been little research into the use of rTMS in DOC and the therapeutic effects have been variously documented. This study aimed to examine the effects of 20 Hz rTMS on the electroencephalography (EEG) reactivity and clinical response in patients with DOC and to explore the neuromodulatory effects of high-frequency rTMS. In this randomized, sham-controlled, crossover study, real or sham 20 Hz rTMS was applied to the left primary motor cortex (M1) of patients with DOC for 5 consecutive days. Evaluations were blindly performed at the baseline (T0), immediately after the end of the 5 days of treatment (T1) and 1 week after the treatment (T2) using the JFK coma recovery scale-revised (CRS-R) and resting-state EEG. Only one patient, with a history of 2 months of traumatic brain injury, showed long-lasting (T1, T2) behavioral and neurophysiological modifications after the real rTMS stimulation. The 5 remaining patients presented brain reactivity localized at several electrodes, and the EEG modification was not significant. rTMS stimulation may improve awareness and arousal of DOC. Additionally, EEG represents a potential biomarker for the therapeutic efficacy of rTMS. This trial is registered with (NCT03385278). [ABSTRACT FROM AUTHOR]

High temperature (HT) at meiosis stage is one of most important environment constraint affecting spikelet fertility and rice yield. In this paper, the effects of HT exposure at meiosis stage on the ROS (reactive oxygen species) accumulation, various superoxide dismutase (SOD, EC1.15.1.11) isozymes in developing anther, and its relationship with HT-induced decline in pollen viability and floret fertility were investigated by using four rice cultivars differing in heat tolerance under well-controlled climatic condition. Results showed that HT exposure significantly increased ROS level and malondialdehyde (MDA) content in rice anther, and this occurrence was strongly responsible for the HT-induced decline in pollen viability and harmful effect of HT adversity on floret fertility. However, the increased extent of ROS concentration in rice anther under HT exposure was greatly variable, depending on both the intensity and duration of HT exposure and different rice cultivars used. The SOD and CAT activities of HT-sensitive cultivars decreased more profoundly than those of HT-tolerant cultivars under the same HT regimes. Among various types of SOD enzymes, Cu/Zn–SODa expressed highly in rice anther and responded sensitively to HT exposure, while Cu/Zn–SODb expressed weakly in rice anther and preferentially in rice leaves. HT exposure suppressed the expression of Cu/Zn–SODa in developing anther, which was closely associated with the down-regulated transcripts of cCu/Zn – SOD1 gene. Hence, Cu/Zn–SODa may play a central role in the regulation of total SOD activity and ROS detoxification in rice anther as affected by HT exposure at meiosis stage. [ABSTRACT FROM AUTHOR]

[Display omitted] • Design aromatic amide derivatives based on BCR-ABL1 inhibitor. • The new compounds were evaluated for antitumor activities. • Effects of compounds on tumor cell proliferation, apoptosis, and migration. • Molecular docking analysis of compound 4j interact with BCR-ABL1 kinase. BCR-ABL1 kinase is a key driver of the pathophysiology of chronic myeloid leukemia (CML). Current treatments need to broaden the chemical diversity of BCR-ABL1 kinase inhibitors to overcome drug resistance. We designed and synthesized a series of aromatic amide derivatives based on several generations of BCR-ABL1 kinase inhibitors. Biological studies showed that compared with Imatinib, these compounds showed significant proliferation inhibitory activities of HL-60 and K562 in cell activity assay. Compounds 4g and 4j exhibited significant anti-tumor activity against the K562 cells with IC 50 values of 6.03 ± 0.49 μM and 5.66 ± 2.06 μM respectively. Compounds 4g and 4j , as potential BCR-ABL1 inhibitors, inhibit the phosphorylation of ABL1 and CRKL in a dose-dependent manner. Therefore, compounds 4g and 4j can be used as a starting point for further optimization. [ABSTRACT FROM AUTHOR]

Spiking Neural Network (SNN) is a type of biologically-inspired neural networks that perform information processing based on discrete-time spikes, different from traditional Artificial Neural Network (ANN). Hardware implementation of SNNs is necessary for achieving high-performance and low-power. We present the Darwin Neural Processing Unit (NPU), a highly-configurable neuromorphic hardware co-processor based on SNN implemented with digital logic, supporting a configurable number of neurons, synapses and synaptic delays. The Darwin NPU was fabricated by standard 180 nm CMOS technology with area size of 5 × 5 mm 2 and 70 MHz clock frequency at the worst case. It consumes 0.84 mW/MHz with 1.8 V power supply for typical applications. Two prototype applications are used to demonstrate the performance and efficiency of the Darwin NPU. [ABSTRACT FROM AUTHOR]

Microalgae are often used as feedstock for renewable biofuel production and as pollutant up-takers for wastewater treatment; however, biomass harvesting still remains a challenge in field applications. In this study, electro-flocculation using aluminium electrolysis was tested as a method to collect Chlorella vulgaris . The electrolysis products were positively charged over a wide pH range below 9.5, which gave them a flocculation potential for negatively charged microalgae. As flocculants were in-situ generated and gradually released, microalgae flocs formed in a snowballing mode, resulting in the compaction of large flocs. When higher current density was applied, microalgae could be harvested more rapidly, although there was a trade-off between a higher energy use and more residual aluminium in the culture medium. Benefits of this flocculation method are twofold: the phosphate decrease in post-harvesting could improve nutrient removal in microalgae based wastewater treatment, while the ammonium increase may favor microalgae recovery for medium recycling. [ABSTRACT FROM AUTHOR]

Algae as an abundant natural biomass, more attention has been paid to explore its potential application in environmental pollutants treatment. This work prepared the algae-TiO 2 /Ag bionano hybrid material by loading algae cells on the ultrafine TiO 2 /Ag chitosan hybrid nanofiber mat. For the first time, the synergistic photocatalytic effect of fresh algae and TiO 2 /Ag nanomaterial was investigated by removal of Cr(VI). The addition of algae significantly improved the photo-removal of Cr(VI) in the system with TiO 2 /Ag hybrid nanomaterial under visible light irradiation. Meanwhile, the photocatalytic mechanism was studied. The photogenerated reactive oxygen species were quantified and the addition of algae apparently decreased the yields of OH to 31.0 μM, while improved the yields of 1 O 2 and O 2 − in the reaction system with TiO 2 /Ag hybrid nanofiber mats. The change of superoxide dismutase activity and malondialdehyde content in algae indicated that TiO 2 /Ag could impose oxidative stress and cause lipid peroxidation in algae cells. During the course of irradiation, algae released substances could act as scavenger for holes, thus inhibited the recombination of hole/electron and enhanced the photocatalytic reduction of Cr(VI) by electrons on TiO 2 surface. Algae was simultaneously photodegraded in the system and the resulting O 2 − , organic free radicals could promote the reduction of Cr(VI). This functional hybrid nanofiber mat was easily recovered and maintained a great photocatalytic activity on the five successive cycles. This algae-photocatalyst hybrid material has promising applications potential in heavy metal removal and organic pollutants treatment. [ABSTRACT FROM AUTHOR]

With the explosion of healthcare information, there has been a tremendous amount of heterogeneous textual medical knowledge (TMK), which plays an essential role in healthcare information systems. Existing works for integrating and utilizing the TMK mainly focus on straightforward connections establishment and pay less attention to make computers interpret and retrieve knowledge correctly and quickly. In this paper, we explore a novel model to organize and integrate the TMK into conceptual graphs. We then employ a framework to automatically retrieve knowledge in knowledge graphs with a high precision. In order to perform reasonable inference on knowledge graphs, we propose a contextual inference pruning algorithm to achieve efficient chain inference. Our algorithm achieves a better inference result with precision and recall of 92% and 96%, respectively, which can avoid most of the meaningless inferences. In addition, we implement two prototypes and provide services, and the results show our approach is practical and effective. [ABSTRACT FROM AUTHOR]

Graphene-based membranes have great potential for seawater desalination and water treatment, although it is still a great challenge to find an effective solution for the dilemma between water flux through the membrane and removal rate of salt ions. In this study, a novel strategy of coating polyelectrolytes on holey graphene oxide was designed in order to modify the surface charge on a graphene oxide membrane, aiming to simultaneously improve water flux and desalination performance. The resultant highly-charged graphene oxide membrane presents excellent opportunity to connect sheets together by the formation of chemical bonds, subsequently effectively enhancing the stability, surface potential and hydrophilicity of the membrane in water, improving the water flux and desalination performance. The nano-pores of holey graphene oxide, formed by H 2 O 2 etching, can improve the structure of two-dimensional nano-channels between slices and shorten the transport distance of water molecules, thus leading to a higher water flux. Moreover, coating the holey graphene oxide membrane with charged polyelectrolytes enhances excellent ion rejection by the combination of interlayer size screening and electrostatic repulsion. The cationic polyelectrolyte-coated composite membrane can achieve a water flux of 268.49 L m−2·h−1·MPa−1 and the desalination rate of 87.86% for 0.5 g L−1 NaCl, achieving an increase of 3.44 times and 37.65%, respectively, as compared with untreated graphene oxide film. The facile and scalable surface modification of this graphene oxide-based membrane produces a promising application prospect in desalination of wastewater with a high salinity. [Display omitted] • A novel strategy of coating polyelectrolytes on HGO was designed for desalination. • Water flux and desalination performance were simultaneously improved. • H 2 O 2 etching treatment shortened the transport distance of water molecules. • Coating HGO films with charged polyelectrolytes enhanced excellent ion rejection. [ABSTRACT FROM AUTHOR]

• The quantitative input of MWCNTs dispersion solution with the concrete flow is realized. • The distribution characteristics of MWCNTs in recycled aggregate shotcrete is revealed. • The influence of MWCNTs content on the flow properties and mechanical properties of recycled aggregate concrete is analyzed. • The microscopic mechanism of MWCNTs improving the mechanical properties of shotcrete is discussed. This study aimed to investigate the spatial distribution characteristics of multi-walled carbon nanotubes (MWCNTs) in recycled coarse aggregate shotcrete (RCAS) and the influence of the dosage of MWCNTs on flow characteristic, mechanical properties and its microscopic mechanism. In this paper, 100% of natural coarse aggregate (NCA) was replaced by recycled coarse aggregate (RCA). Multiple nano-characterization techniques were adopted, and the wet-mix shotcrete technology and a combined device for variable addition of MWCNTs suspension were used. The experimental results showed that with the increase of the dosage of MWCNTs, the flow characteristic of RCAS in fresh state decreased. In terms of mechanical properties, the compressive strength, splitting tensile strength and flexural strength of RCAS all showed a trend of increasing first and then decreasing, when MWCNTs was 0.09 wt%, the flexural strength and splitting strength of RCAS reached the peak value. When the dosage of MWCNTs was 0.03 wt%, 0.06 wt% and 0.09 wt%, the quantity distribution of MWCNTs in the RCAS was average and centered. Appropriate dosage of MWCNTs (0.06 wt% or 0.09 wt%) had a positive effect on improving the compactness of interface transition zone (ITZ) of the RCA, optimizing the internal pore size distribution of RCAS, accelerating the hydration reaction rate and increasing the yield of hydration products. [ABSTRACT FROM AUTHOR]

High temperature (HT) at meiosis induces heat injury to pollen viability and floret fertility, which is closely associated with HT-induced endoplasmic reticulum (ER) stress and ROS damage in developing anthers. Disulfide isomerase like proteins (PDILs) play an essential role in the formation, reduction, and isomerization of disulfide bonds in nascent secretory proteins for the maintenance of cell viability and ER homeostasis. However, the underlying mechanism by which HT induces ROS burst in rice anthers and its relation to ER stress for the varying existence of PDILs is largely unknown. In this paper, we investigated the action of PDILs in the regulation of heat injury to floret fertility and its association with HT-induced ROS generation in developing anthers under well-controlled climatic conditions. Results showed that knock-down of OsPDIL1–1 by RNAi enhanced the activity of NADPH oxidase and caused the excessive ROS accumulation in developing anthers, consequently the up-grading sensitivity of pollen viability and floret fertility to heat stress. RBOHb is the primary site where HT exposure affected NADPH oxidase activity and triggered ROS generation in rice anthers because OsPDIL1–1 was found to interact with RBOHb in the ER-PM junction. Furthermore, HT exposure triggered the RBOHb-mediated ROS generation in a Ca2+-dependent manner, while the induction of HT exposure to ER stress was not necessarily associated with ROS generation derived from NADPH oxidase. • PDIL1-1 was essential for maintaining floret fertility at elevated temperatures. • PDIL1-1 directly interacts with RBOHb to modulate ROS generation in rice anthers. • HT triggered the RBOHb-mediated ROS generation in a Ca2+-dependent manner. • HT-induced ER stress was not associated with NADPH oxidase-derived ROS. • PDIL1-1 was found to interact with RBOHb in the ER-PM junction. [ABSTRACT FROM AUTHOR]

Prediction of memory performance (remembered or forgotten) has various potential applications not only for knowledge learning but also for disease diagnosis. Recently, subsequent memory effects (SMEs)—the statistical differences in electroencephalography (EEG) signals before or during learning between subsequently remembered and forgotten events—have been found. This finding indicates that EEG signals convey the information relevant to memory performance. In this paper, based on SMEs we propose a computational approach to predict memory performance of an event from EEG signals. We devise a convolutional neural network for EEG, called ConvEEGNN, to predict subsequently remembered and forgotten events from EEG recorded during memory process. With the ConvEEGNN, prediction of memory performance can be achieved by integrating two main stages: feature extraction and classification. To verify the proposed approach, we employ an auditory memory task to collect EEG signals from scalp electrodes. For ConvEEGNN, the average prediction accuracy was 72.07% by using EEG data from pre-stimulus and during-stimulus periods, outperforming other approaches. It was observed that signals from pre-stimulus period and those from during-stimulus period had comparable contributions to memory performance. Furthermore, the connection weights of ConvEEGNN network can reveal prominent channels, which are consistent with the distribution of SME studied previously. [ABSTRACT FROM AUTHOR]

To clarify the interaction between different antioxidant enzymes for monitoring oxidative stress and ROS burst in rice senescent leaves, we investigated the genotype-dependent alteration in temporal patterns of the O 2 •− production rate, H 2 O 2 content, and ROS–scavenging enzyme activities during leaf senescence in two rice genotypes, namely, the premature senescence of flag leaf ( psf ) mutant and its wild type. Results showed that the psf mutant differed obviously from its wild type in leaf O 2 •− generation rate and H 2 O 2 content accumulation, and the decreased activities of SOD, CAT, and APX in the psf leaves were strongly responsible for the increased ROS level and the accelerated leaf senescence. By contrast, the increase in POD activity was positively correlated with the senescence-related enhancement in O 2 •− generation in rice leaves. Among various SOD isoforms, Mn–SOD responded sensitively to the increasing O 2 •− generation rate, whereas Cu/Zn–SOD remained stable with the progression of leaf senescence. These findings suggest that the senescence-related decline in total SOD activity was mostly attributable to the downregulation of both the translation and transcription of Mn – SOD isoform. This occurrence finally resulted in the collapse of SOD defense system and accelerated leaf senescence for the psf mutant. Furthermore, we presented the possible contribution of several Cu/Zn – SOD expression patterns to the senescence-related O 2 •− detoxification in different cell compartments. [ABSTRACT FROM AUTHOR]

High-frequency oscillations (HFOs) are promising biomarkers for epileptic foci; however, their characteristic changes during the preictal period remain unclear. Here, the preictal HFOs were recorded and detected by an automated HFOs detection method in the mouse pilocarpine model as well as in patients with mesial temporal lobe epilepsy (mTLE) and neocortical epilepsy. A total of sixteen low-voltage fast (LVF) and fifty-three hypersynchronous-onset (HYP) seizures were recorded in ten mice. The rate of ripples (80–250 Hz) decreased during 1 min before the onset of LVF and HYP seizures, which was primarily due to the reduction of type II (independent of epileptiform discharges) rather than type I ripples (superimposed on epileptiform activities). The ripple rate decreased until 30 s before HYP seizure, whereas it increased with a peak at 40 s during the 1 min preictal period of LVF seizures. Furthermore, the “ripple reduction” phenomenon was also observed in all twelve seizures from nine patients with mTLE but not in neocortical epilepsy. These results indicate that ripples may potentially be helpful for understanding the mechanisms of ictogenesis in mTLE, and the different modes of ripple changes during the minute before LVF and HYP seizures might also be beneficial for the diagnosis of seizure types. [ABSTRACT FROM AUTHOR]

D1 protein in the PSII reaction center is the major target of photodamage, and it exhibits the highest turnover rate among all the thylakoid proteins. In this paper, rice psf (premature senescence of flag leaves) mutant and its wild type were used to investigate the genotype-dependent alteration in PSII photo-damage and D1 protein turnover during leaf senescence and its relation to ABA accumulation in senescent leaves. The symptom and extent of leaf senescence of the psf mutant appeared to be sunlight-dependent under natural field condition. The psf also displayed significantly higher levels of ABA accumulation in senescent leaves than the wild type. However, the premature senescence lesion of psf leaves could be alleviated by shaded treatment, concomitantly with the strikingly suppressed ABA level in the shaded areas of flag leaves. The change in ABA concentration contributed to the regulation of shade-delayed leaf senescence. The participation of ABA in the timing of senescence initiation and in the subsequent rate of leaf senescence was closely associated with PSII photodamage and D1 protein turnover during leaf senescence, in which the transcriptional expression of several key genes (psbA, psbB, psbC and OsFtsH2) involved in D1 protein biosynthesis and PSII repair cycle was seriously suppressed by the significantly increased ABA level. This response resulted in the low rate of D1 protein synthesis and impaired repair recovery in the presence of ABA. The psf showed evidently decreased D1 protein amount in the senescent leaves. Both the inhibition of de novo synthesized D1 protein and the slow rate of proteolytic removal for the photodamaged D1 protein was among the most crucial steps for the linkage between light-dependent leaf senescence and the varying ABA concentration in psf mutant leaves. OsFtsH2 transcriptional expression possibly played an important role in the regulation of D1 protein turnover and PSII repair cycle in relation to ABA mediated leaf senescence. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to determine the effects of highfrequency repetitive transcranial magnetic stimulation (rTMS) on cerebral hemodynamics in patients with disorders of consciousness (DOC). Methods: In this sham-controlled study, 20-Hz and sham rTMS were applied over the left primary motor cortex (M1) of 5 patients in a vegetative state (VS) and 5 patients in a minimally conscious state (MCS). The clinical behavior and cerebral blood flow (CBF) velocity in the bilateral middle cerebral artery (MCA) of the patients were evaluated before and after rTMS. Results: Compared with the VS group, the MCS group exhibited significant increases in peak systolic velocity (PSV; p = 0.024) and mean flow velocity (MFV) of the left MCA that were temporally related to the rTMS (p = 0.042). There were no significant effects on CBF velocity in the sham-stimulation group or the right MCA. Conclusions: High-frequency rTMS exerts different effects on CBF depending on the level of consciousness in patients with DOC such that it increased PSV and MFV in patients in a MCS. These effects may be related to the varying degrees of disrupted neurovascular coupling and the autonomic control of the cerebral hemodynamics in patients in a VS or MCS. [ABSTRACT FROM AUTHOR]

Wet shotcrete can reduce dust and improve supporting strength, however, safe and efficient pipage is a key technical part of wet shotcrete process. The paper studied the pipe flow law of wet shotcrete based on lubrication layer by build the experimental pumping circuit of wet shotcrete that can carry out a number of full-scale pumping tests. The experimental results show there was a linear relationship between pressure loss and flow rate. Combined with the Buckingham rheological equation, the computing equations of the yield shear stress and plastic viscosity were deduced through linear regression. A simple analytical method allowing for a rough estimation of the pumping pressure was proposed and used when considering the lubrication layer of wet shotcrete in pipes. In addition, two kinds of particulate distributive models were established along the time axial to analyze the formation of lubrication layer which is related with particles migration. By computational fluid dynamics simulation, the lubrication layer thickness of different mix proportions was estimated. A new method for measuring the thickness of lubrication layer was proposed to verify it by binarization processing. Finally, according to the comparative analysis of experiments, simulation and computed value, it can be seen that the lubrication layer plays a key role in the process of wet shotcrete flow and with the increase of lubrication layer thickness pipe pressure declines gradually. [ABSTRACT FROM AUTHOR]

A rat cyborg system refers to a biological rat implanted with microelectrodes in its brain, via which the outer electrical stimuli can be delivered into the brain in vivo to control its behaviors. Rat cyborgs have various applications in emergency, such as search and rescue in disasters. Prior to a rat cyborg becoming controllable, a lot of effort is required to train it to adapt to the electrical stimuli. In this paper, we build a vision-based automatic training system for rat cyborgs to replace the time-consuming manual training procedure. A hierarchical framework is proposed to facilitate the colearning between rats and machines. In the framework, the behavioral states of a rat cyborg are visually sensed by a camera, a parameterized state machine is employed to model the training action transitions triggered by rat’s behavioral states, and an adaptive adjustment policy is developed to adaptively adjust the stimulation intensity. The experimental results of three rat cyborgs prove the effectiveness of our system. To the best of our knowledge, this study is the first to tackle automatic training of animal cyborgs. [ABSTRACT FROM AUTHOR]

A cheap and biodegradable modifier, cationic starch (CS), was used to turn local soils into effective flocculants for Microcystis aeruginosa ( M. aeruginosa ) removal. The isoelectric point of soil particles was remarkably increased from pH 0.5 to 11.8 after modification with CS, which made CS modified soil particles positively charged and obtain algal flocculation ability. At the soil concentration of 100 mg/L, when the CS modifier was 10 mg/L, 86% of M. aeruginosa cells were removed within 30 min. Lower or higher CS dosage led to limited algal removal. About 71% and 45% of M. aeruginosa cells were removed within 30 min when CS was 5 mg/L and 80 mg/L, respectively. This is because only part of algal cells combined with CS modified soil particles through charge neutralization at low dosage, while flocs formed at high CS dosage were positively charged which prevents further aggregation among the flocs. The floc stability was quantified by a floc breakage index under applied shear force. Algal flocs formed at acid and alkaline conditions were more prone to be broken than those at the neutral condition. The cost and biodegradability concerns may be largely reduced through the use of CS modified local soils. For field applications, other practical issues (e.g., re-suspension) should be further studied by jointly using other methods. [ABSTRACT FROM AUTHOR]

Concentration and salinity conditions are the dominant environmental factors affecting the behavior of perfluorinated compounds (PFCs) on the surfaces of a variety of solid matrices (suspended particles, sediments, and natural minerals). However, the mechanism has not yet been examined at molecular scales. Here, the structural transformation of perfluorooctane sulfonate (PFOS) at water/rutile interfaces induced by changes of the concentration level of PFOS and salt condition was investigated using molecular dynamics (MD) simulations. At low and intermediate concentrations all PFOS molecules directly interacted with the rutile (1 1 0) surface mainly by the sulfonate headgroups through electrostatic attraction, yielding a typical monolayer structure. As the concentration of PFOS increased, the molecules aggregated in a complex multi-layered structure, where an irregular assembling configuration was adsorbed on the monolayer structure by the van der Waals interactions between the perfluoroalkyl chains. When adding CaCl 2 to the system, the multi-layered structure changed to a monolayer again, indicating that the addition of CaCl 2 enhanced the critical concentration value to yield PFOS multilayer assemblies. The divalent Ca 2+ substituted for monovalent K + as the bridging counterion in PFOS adsorption. MD simulation may trigger wide applications in study of perfluorinated compounds (PFCs) from atomic/molecular scale. [ABSTRACT FROM AUTHOR]

To clarify the complex relationship between ascorbate–glutathione (AsA–GSH) cycle and H 2 O 2 -induced leaf senescence, the genotype-dependent difference in some senescence-related physiological parameters and the transcript levels and the temporal patterns of genes involved in the AsA–GSH cycle during leaf senescence were investigated using two rice genotypes, namely, the early senescence leaf ( esl ) mutant and its wild type. Meanwhile, the triggering effect of exogenous H 2 O 2 on the expression of OsAPX genes was examined using detached leaves. The results showed that the esl mutant had higher H 2 O 2 level than its wild type at the initial stage of leaf senescence. At transcriptional level, the association of expression of various genes involved in the AsA–GSH cycle with leaf senescence was isoform dependent. For OsAPXs , the transcripts of two cytosolic OsAPX genes ( OsAPX1 and OsAPX2 ), thylakoid-bound OsAPX8 , chloroplastic OsAPX7 and peroxisomal OsAPX4 exhibited remarkable genotype-dependent variation in their expression levels and temporal patterns during leaf senescence, there were significantly increasing transcripts of OsAXP1 and OsAPX7 , severely repressed transcripts of OsAPX4 and OsAPX8 for the esl rice at the initial leaf senescence. In contrast, the repressing transcript of OsAPX8 was highly sensitive to the increasing H 2 O 2 level in the senescing rice leaves, while higher H 2 O 2 concentration resulted in the enhancing transcripts of two cytosolic OsAPX genes, OsAPX7 transcript was greatly variable with different H 2 O 2 concentrations and incubating duration, suggesting that the different OsAPXs isoforms played a complementary role in perceiving and scavenging H 2 O 2 accumulation at various H 2 O 2 concentrations during leaf senescence. Higher H 2 O 2 level, increased AsA level, higher activities of APX and glutathione reductase (GR), and relatively stable GSH content during the entire sampling period in the leaves of esl mutant implied that a close interrelationship existed between AsA level and APX activity in the ongoing senescence of rice leaves. The GSH supply in rice leaves was not the limiting factor for the efficient maintenance of AsA–GSH cycle, despite the senescence-related change in GR activity between the two rice genotypes. [ABSTRACT FROM AUTHOR]

A four-vane continuous wave (CW) RFQ has been designed for the injector II LINAC of China ADS project. To acquire the experience of a CW RFQ on design, tuning, conditioning, running, etc., a 1-m-long RFQ accelerator prototype has been built. Working at 162.5 MHz, the RFQ prototype accelerates protons of 10 mA from 20 keV to 560 keV in one meter length with a low inter-vane voltage of 65 kV and a safe Kilpatric factor of 1.3. Conditioning and beam test of the accelerator prototype have been completed, and it shows the transmission efficiency can reach 90% with a 10 mA CW proton beam. Design, fabrication and tests of the RFQ prototype will be presented in detail in the paper. [ABSTRACT FROM AUTHOR]

This paper presents the first report of a system of human's speech interaction with rats via integration of brain-machine interfaces and automatic speech recognition technologies. We propose a novel human-rat speech interaction paradigm by incorporating speech translator module, which translates human's speech commands into suitable electrical brain stimulation to steer the rat to induce expected locomotor behaviors. The preliminary results show that we can guide a rat's movement by speech commands. We further look into the future application scenarios together with forthcoming challenges facing this newly evolved cyborg intelligent system. This work will pave the way for natural interaction with animal robots. [ABSTRACT FROM AUTHOR]

Background: While more and more open procedures now routinely performed using laparoscopy, minimally invasive pancreaticoduodenectomy (MIPD) remains one of the most challenging abdominal procedures. Therefore, we carried out this meta-analysis to evaluate whether MIPD is safe, feasible and worthwhile. Methods: PubMed, EMBASE, and Cochrane Library were searched to identify studies published between January 1994 and November 2013 comparing MIPD with open pancreaticoduodenectomy (OPD). Intraoperative outcomes, oncologic safety, postoperative complications, and postoperative recovery were evaluated. Results: 11 retrospective studies representing 869 patients (327 MIPDs, 542 OPDs) were included. MIPD was associated with a reduction in estimated blood loss (MD −361.93 ml, 95% CI −519.22 to −204.63 ml, p<0.001, I2 = 94%), wound infection (OR 0.41, 95% CI 0.22 to 0.78, p = 0.007, I2 = 0%), and hospital stay (MD −2.64 d, 95% CI −4.23 to −1.05 d, p = 0.001, I2 = 78%). However, it brings longer operative time (MD 105 min, 95% CI 49.73 to 160.26 min, p<0.001, I2 = 93%). There were no significant differences between the two procedures in likelihood of overall complications (p = 0.05), pancreatic fistula (PF) (p = 0.86), delayed gastric empting (DGE) (p = 0.96), positive surgical margins (p = 0.07), retrieval of lymph nodes (p = 0.48), reoperation (p = 0.16) and mortality (p = 0.64). Conclusions: Our results suggest that MIPD is currently safe, feasible and worthwhile. But considering the selection bias, complexity of MIPD and lack of long-term oncologic outcomes, we suggest it be performed in a high-volume pancreatic surgery center in selected patients. [ABSTRACT FROM AUTHOR]

• Algal migration in water column manipulates DNF in bed sediments. • DNF rate is low but positively correlated with C hl-a in algae left zone. • DNF rate is high but negatively correlated with C hl-a in algae concentrated zone. Driven by winds, the distribution of algae is often noticeably patchy at kilometer scales in shallow lakes. The decomposition of the settled algal biomass may affect nitrogen (N) biogeochemical cycles and thereby N loss in sediments. In this study, we investigated sediment denitrification N-loss patterns along algal migration pathway in Taihu Lake, a shallow and eutrophic lake in China, and found that wind-induced algal migration in the overlying water manipulated the temporal and spatial patterns of denitrification N-loss in sediments. A N loss hotspot in sediments was created in the algae concentrated zone, where N loss was, however, temporarily inhibited during algal bloom seasons and generally exhibited a negative relationship with algal biomass. In the zone where algae have left, sediment N loss rate was relatively low and positively correlated with algal biomass. The decay of algal biomass generated organic carbon and created anoxia, favoring denitrification, while excessive algal biomass could deplete oxygen and inhibit nitrification, causing nitrate limitation for denitrification. Piecewise linear regression analysis indicated that algal biomass of Chl-a > 73.0 μg/L in the overlying water could inhibit denitrification N-loss in sediments. This study adds to our understanding of N biogeochemical cycles in shallow eutrophic lakes. [Display omitted] [ABSTRACT FROM AUTHOR]

An introduction is presented, in which the author discusses various topics including growing role of big data to enable a smarter word scenarios, data segmentation in human activity recognition within the Ambient-Assisted Living, and developing orchestrating applications for masses of sensors.

Two novel metal-organic coordination complexes [Cd(Zalto profen)2(H2O)3](H2O) (1), [Zn(Zaltoprofen)(H2O)]n(2) (where zaltoprofen = 5-(1-carboxyethyl)-2-(phenylthio)phenylacetic acid) have been synthesized under normal conditions and hydrothermal conditions, respectively. And characterized by single crystal X-ray diffraction, elemental analysis, spectral method (IR), powder X-ray diffraction (XRD), and fluorescent properties. Compound 1 crystallizes in the monoclinicCcspace group while compound 2 in the monoclinic system with space groupP21/c. [Cd(Zaltoprofen)2(H2O)3](H2O) (1) features 0-D structural, the hydrogen-bonds play a vital role in determining the crystal packing and construction of the extended 3-D supramolecular network. [Zn(Zaltoprofen)(H2O)]n(2) displays a 2D net with alternately arranged left- and right-handed helical chains. The O–H···O hydrogen bonding play an important role in stabilizing the structure. Supplemental materials are available for this article. Go to the publisher's online edition ofSynthesis and Reactivity in Inorganic, Metal-Organic, and Nano-Metal Chemistryto view the supplemental file. [ABSTRACT FROM PUBLISHER]

In order to explore new coordination frameworks with novel designed 3-nitrophthalic acid and N–donor ancillary ligands, three novel coordination complexes, namely, [Co2(3-NPA)2(2,2′-bipy)2(H2O)2]•2H2O (1), [Mn2(3-NPA)2(4,4′-bipy)3(H2O)6]•(4,4′-bipy) (2), and [Pb2O(3-NPA)]n(3) (where 3-NPAH2= 3-nitrophthalic acid, 2,2′-bipy = 2,2′-bipyridine, 4,4′-bipy = 4,4′-bipyridine), have been hydrothermally synthesized. X-ray structure analysis reveals that1and2are dinuclear structures, while3is a two-dimensional (2D) network polymer. And the hydrogen bonds and π–π stacking also play important roles in affecting the final structure where complexes1-2have 3D and 2D supramolecular architectures, respectively. These complexes have been characterized by powder X-ray diffractions (PXRD) and thermal gravimetric analyses (TGA). In addition, their photochemical properties have also been investigated. [ABSTRACT FROM PUBLISHER]

Two novel binuclear metal-organic coordination complexes [Zn2(dpa)2(phen)2(H2O)2] (1), [Cd2(dpa)2(btz)2(H2O)2] (2) (where H2dpa = diphenic acid, phen = 1,10-phenanthroline, btz = thiabendazole) have been synthesized under hydrothermal conditions and characterized by single-crystal X-ray diffraction, spectral method (IR), elemental analysis, and fluorescent properties. Compound 1 crystallizes in the triclinicP-1space group while compound 2 in the monoclinic system with space groupP2(1)/n. The binuclear cluster are stabilized by O‒HO hydrogen bond and further fitted together into 3-D supramolecular network by π–π stacking interactions and hydrogen bonds. The luminescence measurements reveal that two complexes exhibit strong fluorescent emissions in the solid state at room temperature. [ABSTRACT FROM AUTHOR]

Policy-based management is a very effective method to protect sensitive information. However, the overclaim of privileges is widespread in emerging applications, including mobile applications and social network services, because the applications' users involved in policy administration have little knowledge of policy-based management. The overclaim can be leveraged by malicious applications, then lead to serious privacy leakages and financial loss. To resolve this issue, this paper proposes a novel policy administration mechanism, referred to as collaborative policy administration (CPA for short), to simplify the policy administration. In CPA, a policy administrator can refer to other similar policies to set up their own policies to protect privacy and other sensitive information. This paper formally defines CPA and proposes its enforcement framework. Furthermore, to obtain similar policies more effectively, which is the key step of CPA, a text mining-based similarity measure method is presented. We evaluate CPA with the data of Android applications and demonstrate that the text mining-based similarity measure method is more effective in obtaining similar policies than the previous category-based method. [ABSTRACT FROM AUTHOR]

Reutilization of the waste by-products from industrial and agricultural activities is crucially important towards attainment of environmental sustainability and the 'circular economy'. In this study, we have developed and evaluated a sustainably-sourced adsorbent from coal fly ash, which was modified by a small amount of lanthanum (La-FA), for the recapture of phosphorous (P) from both synthetic and real natural waters. The prepared La-FA adsorbent possessed typical characteristic diffraction peaks similar to zeolite type Na–P1, and the BET surface area of La-FA was measured to be 10.9 times higher than that of the original FA. Investigation of P adsorption capability indicated that the maximum adsorption (10.8 mg P g−1) was 6.14 times higher than that (1.8 mg P g−1) of the original fly ash material. The ζ potentials measurement and P K-edge X-ray Absorption Near Edge Structure (XANES) spectra demonstrated that P was bonded on La-FA surfaces via an adsorption mechanism. After applying the proposed adsorbent to real lake water with La/P molar ratios in the range from 0.5:1 to 3:1, the La-FA adsorbent showed the highest phosphate removal ability with a La/P molar ratio 1:1, and the P adsorption was similar to that performance with the synthetic solution. Moreover, the La-FA absorbent produced a negligible effect on the concentrations of total dissolved nitrogen (TDN), NH 4 +-N and NO 3 −-N in water. This study thus provides a potential material for effective P recapture and details of its operation. [Display omitted] • Lanthanum modified fly ash (La-FA) was proven to act as a sustainable-sourced P absorbent. • La-FA showed 6 times higher P adsorption ability compared with the original material. • P removal performance from natural water was similar to that of synthetic solution. • Surface P adsorption was deemed the main mechanism via XANES spectral analyses. [ABSTRACT FROM AUTHOR]