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The selective orientation of grains during laser powder bed fusion (L-PBF) leads to anisotropy in mechanical properties. The current understanding of the evolution between the different morphologies of the grains is still limited. The present work is aimed at revealing the grain evolution process through the development of a coupled discrete elemental method-computational fluid dynamics-metacellular automata model. The results show that most of the grains observed through characterization experiments are irregularly shaped columnar grains and exhibit anisotropy in mechanical property tests. The grains observed in the simulations can be generalized into four types: V-shaped grain, slanted grain, vertical grain, and equiaxial grain. During the overlapping of interlayer and intertrack, some of the slanted grains are retained and others grow into V-shaped grains. In addition, some of the V-shaped grains coarsen during remelting and resolidification and subsume the slanted grains in the direction in which they grow, eventually developing into coarse vertical grain. Therefore, an appropriate increase in hatch distance is beneficial to reduce anisotropy. This study contributes to an in-depth understanding of grain transformation during remelting and resolidification and guides the design of specific microstructures. [ABSTRACT FROM AUTHOR]

The New Third Board (NTB) market is a non-publicly traded stock exchange in the Chinese securities market and is an essential component of the Chinese capital market. The distinctive features of the NTB market are its low entry barriers, high flexibility, and relatively minimal information disclosure requirements, which, in turn, introduce higher levels of risk. In order to effectively predict the financial risks of NTB-listed companies, a predictive model based on data mining and machine learning technologies needs to be developed. The purpose of this research is to construct a financial risk prediction model for NTB-listed companies, based on integrated feature engineering and learning models, to enhance risk warning capabilities and accuracy. In this study, 15 predictive indicators were formed based on collected financial data of listed companies, and the F-score was used to calculate risk prediction ground truth. Subsequently, through supervised learning, an ensemble learning model, Catboost, was trained for risk assessment and prediction in different time periods. The results of the study indicate that this framework aligns with professional scoring trends, and the mean squared error (MSE) and mean absolute error (MAE) metrics outperform traditional machine learning methods significantly. Notably, the MAE metric is as low as 0.124, suggesting a high level of precision in intelligent risk prediction, offering new perspectives for financial risk assessment of NTB-listed companies in the future. [ABSTRACT FROM AUTHOR]

Integrating new technology in medical diagnostics presents significant potential for improving precision and productivity. To detect oral tumor cells, this study presents a unique method that uses carbon/graphene dot (CGD) and a Customized Dual Deep Neural Network (CDDNN), known as CGD-CDDNN. Given their distinct electrical and optical characteristics, graphene quantum dots (GQDs) are used as quantum dots in quantum optics to simulate the behaviour of carbon and graphene. The proposed CDDNN architecture has two routes for processing various characteristics associated with tumor cells and is specifically designed to detect oral tumors. This customized deep-learning model's goal is to recognize complex relationships and patterns in a variety of data sources. Because the network is dual, information may be processed in parallel, and complimentary aspects can be integrated more quickly. To take advantage of the unique qualities of CGDs, quantum optics concepts are incorporated into the model, offering a quantum-level comprehension of light-matter interactions in the context of oral cancer cell identification. The CGD-CDDNN system is trained on a dataset of labelled pictures of oral cancer cells using quantum-inspired embeddings and sophisticated optimisation methods. The validation of the proposed model demonstrates its effectiveness in detecting oral tumour cells, showcasing superior performance compared to conventional methods. The study emphasises the potential of quantum optics with carbon/graphene dot models and customised dual deep neural networks in revolutionising the landscape of medical imaging and tumour diagnostics. The CGD-CDDNN framework enhances accuracy and provides valuable insights into the quantum-level interactions within biological systems, paving the way for innovative applications in precision medicine. [ABSTRACT FROM AUTHOR]

The development of Industrial Internet of Things, big data, and multi-domain modeling, led to the emergence of digital twin (DT), providing a new approach to the cyber-physical production systems. In the traditional shipbuilding industry, a large number of hull parts are often tracked and transferred. During the hull parts picking and processing, the uncertainty from parts transfer tasks and logistics information often leads to low resource utilization. Therefore, a real-time resource allocation method based on DT for hull part smart picking and processing system (SPPS) is proposed. Firstly, a multi-agent model of the multi-gantry crane system is established in virtual space to achieve real-time task allocation, hence minimizing the transport time. Next, a real-time picking and processing scheduling policy is proposed to reduce the idle time of all workstations by estimating the time of parts arriving at target station and processing completion time. Finally, the services available in the DT platform can be applied to optimize the system performance, taking the number of devices and the takt time optimization as examples. Several experiments in case study are carried out to verify the proposed method. The average utilization rate of all workstations is increased by 17.39%, and the standard deviation is reduced by 83.31%. The results have shown that the proposed method can effectively improve the workstation utilization rate and load balance. The maximum average number of parts in the station buffer, which is limited to 0.33, is kept at a low level. [ABSTRACT FROM AUTHOR]

To evaluate the impact of zinc sulfate (ZnSO4) concentration on the structural properties of the films, Cd1−xZnxS thin films were formed on glass substrates using chemical bath deposition (CBD) in this study. The effect of ZnSO4 precursor concentration on the surface morphology, optical properties, and morphological structure of the Cd1−xZnxS films was investigated. To study the impact of zinc doping content on the performance metrics of Cu(In1−xGax)Se2 (CIGS) cells in the experimental group and to improve the buffer layer thickness, simulations were run using one-dimensional solar cell capacitance simulator (SCAPS-1D) software. [ABSTRACT FROM AUTHOR]

Fluorescent lateral flow immunoassay (LFA), one tool in point of care testing (POCT) systems for breast cancer, has attracted attention because it is quick, simple, and convenient. However, samples and the constituent material exhibit autofluorescence in the visible region, which is a very large obstacle in the development of fluorescent LFAs. The autofluorescence of biological samples is scarcely found in the second near-infrared (NIR-II) range and samples scatter and absorb less NIR-II light than visible light. Here, we report an NIR-II QD-LFA platform using the NIR-II fluorescent Ag2Se quantum dots (QDs) with 1020 nm emission encapsulated into polystyrene beads as fluorescent probes. The NIR-II LFA platform was established to detect breast cancer tumour markers (CEA and CA153) within 15 min with a low limit of detection (CEA: 0.768 ng mL−1, CA153: 1.192 U mL−1), high recoveries (93.7% ~ 108.8%), and relative standard deviations (RSDs) of less than 10%. This study demonstrated the potential of NIR-II Ag2Se polystyrene beads as a fluorescent probe in LFA for rapid and accurate identification of biomarkers. They are suited for use in professional situations. [ABSTRACT FROM AUTHOR]

The digital twin workshop is a new workshop operation paradigm that enables precise decision-making by fusing virtual and physical space. As a complex manufacturing system, the digital twin model of the workshop must integrate models from different domains in order to provide personalized services. The interoperability of multi-domain models and the dynamic update of parameters become obstacles. In this paper, a knowledge graph (KG)-based multi-domain model integration method for digital twin workshops is proposed. The multi-domain model integration architecture based on KG is consisted of model element, model ontology, model data, semantic integration, and network connection. Then, the KG of multi-domain model for design, manufacturing, and simulation is constructed through ontology modeling and knowledge extraction. On this basis, multi-domain model integration is realized through semantic inference and knowledge query. The model parameters are updated through file exchange during the dynamic simulation. Finally, multiple scenarios in the subassembly workshop for hull construction are used to verify the efficacy of the proposed method. During the assembly and welding of hull parts, the integration of the product model, equipment model, and simulation model is realized, which assists in meeting the service requirements of multiple business scenarios. [ABSTRACT FROM AUTHOR]

Tool breakage in manufacturing procedures can damage machined surfaces and machine tools. It is crucial to detect tool breakage in time and promptly respond to it. Due to the safety restrictions imposed in production, failure samples are significantly scarcer than normal samples, and this disequilibrium results in difficulty of failure detection. Therefore, we propose a new imbalanced data learning method for tool breakage detection. The key strategy is to balance the data distribution by producing valuable artificial samples for the minority class using an adversarial generative oversampling model based on a generative adversarial network (GAN). Unlike previous studies using GAN, we use the discriminator to screen samples generated by the generator and achieve effective oversampling. Multiple classifiers are adopted as the decision-making models to perform tool breakage detection. The proposed method is applied to a set of imbalanced experimental tool breakage data collected in a workshop. Compared with the best results of other oversampling solutions, the proposed method improves the breakage detection rate from 93.6% to 100%, which shows its practicability and validity. Additionally, evaluations are performed based on 12 imbalanced benchmark datasets. The results further substantiate the superiority of the proposed method to existing sampling methods. [ABSTRACT FROM AUTHOR]

Gate-channel electron low-field transport characteristic is obtained from measured current–voltage and capacitance–voltage curves for the AlGaN/GaN heterostructure field-effect transistors (HFETs) with drain Schottky contact and drain Ohmic contact. The electron mobility curve of the HFET with drain Schottky contact shows larger value and slower rising trend, comparing with that of traditional drain Ohmic contact. This phenomenon is investigated qualitatively and quantificationally, in the view of polarization scattering effect. In addition, it is found that different transport characteristics originate from different polarization charge distributions near drain electrode. Since drain Schottky contact does not suffer from thermal annealing process, there is no polarization charge variation, inducing weaker scattering intensity and thus larger electron mobility. It offers a special perspective for the future optimization of AlGaN/GaN HFETs. [ABSTRACT FROM AUTHOR]

Effective cutting tool life prediction is significant for ensuring processing quality and improving production efficiency. Data-driven prediction methods have been widely used. However, traditional methods assume that there are high-quality sensor data, whereas, in practice, factors such as poor installation of sensors and environmental interference often lead to poor-quality data, leading to unreliable analysis results and incorrect decisions. Thus, in this paper, a sensor data anomaly detection and correction method is proposed. It mainly includes four parts: data preprocessing, abnormal data detection, correction of detected abnormal data, and tool life prediction and evaluation. First, the raw condition monitoring data are preprocessed for feature extraction and health index (HI) construction. Second, the HIs of historical training samples are clustered based on the dynamic time warping (DTW) algorithm, and the abnormal data are detected based on error calculation with a preset error threshold. Third, the detected abnormal data are optimized via similarity matching using k-nearest neighbors with dynamic time warping (KNN-DTW). Finally, the optimized data are used for tool life prediction and evaluation. The proposed method has been tested on real data acquired from a turbine factory. The comparison results show that the prediction effect can be significantly improved after adopting the proposed method, which verifies the necessity of sensor data anomaly detection and correction. [ABSTRACT FROM AUTHOR]

Periodically ordered arrays of vertically aligned Si nanowires (Si NWs) are successfully fabricated with controllable diameters and lengths. Their photoconductive properties are investigated by photoconductive atomic force microscopy (PCAFM) on individual nanowires. The results show that the photocurrent of Si NWs increases significantly with the laser intensity, indicating that Si NWs have good photoconductance and photoresponse capability. This photoenhanced conductance can be attributed to the photoinduced Schottky barrier change, confirmed by I–V curve analyses. On the other hand, electrostatic force microscopy (EFM) results indicate that a large number of photogenerated charges are trapped in Si NWs under laser irradiation, leading to the lowering of barrier height. Moreover, the size dependence of photoconductive properties is studied on Si NWs with different diameters and lengths. It is found that the increasing magnitude of photocurrent with laser intensity is greatly relevant to the nanowires' diameter and length. Si NWs with smaller diameters and shorter lengths display better photoconductive properties, which agrees well with the size-dependent barrier height variation induced by photogenerated charges. With optimized diameter and length, great photoelectrical properties are achieved on Si NWs. Overall, in this study the photoelectrical properties of individual Si NWs are systematically investigated by PCAFM and EFM, providing important information for the optimization of nanostructures for practical applications. [ABSTRACT FROM AUTHOR]

To simultaneously detect two metabolites of Aspergillus flavus, namely, cyclopiazonic acid (CPA) and aflatoxin (AFT), an ultrasensitive monoclonal antibody (mAb) YTT-2 against CPA was developed and characterized, with sensitivity to CPA of 1.32 ng mL−1. Along with the previously homemade mAb 1C11 against AFT, two mAbs were used to develop time-resolved fluorescence immunoprobes or gold immunoprobes. We developed two multiple-analyte paper immunosensors including time-resolved fluorescent immunochromatographic assay (TRFICA) and gold immunochromatographic assay (GICA) for the simultaneous determination of CPA and AFT. The TRFICA showed limits of determination (LODs) of 0.21 and 0.004 ng mL−1, while the GICA showed LODs of 0.33 and 0.01 ng mL−1 for CPA and AFT, respectively. To validate the specificity of the two rapid immunoassays, rice, corn and peanut samples were spiked with different concentrations of CPA and AFT. The two methods showed satisfactory recoveries (76.39~90.82% for CPA and 84.60~94.45% for AFT) and coefficients of variation of 3.50~7.80% for CPA and 4.12~13.90% for AFT. The results indicated that the TRFICA could complete the test within 5 min and had lower LODs and linear ranges, compared with that of GICA. The method developed in this work can be widely applied to the rapid and quantitative simultaneous determination of multiple harmful metabolites in fungi for food safety and health care. [ABSTRACT FROM AUTHOR]

Excessive tool wear leads to the damage and eventual breakage of the tool, workpiece, and machining center. Therefore, it is crucial to monitor the condition of tools during processing so that appropriate actions can be taken to prevent catastrophic tool failure. This paper presents a hybrid information system based on a long short-term memory network (LSTM) for tool wear prediction. First, a stacked LSTM is used to extract the abstract and deep features contained within the multi-sensor time series. Subsequently, the temporal features extracted are combined with process information to form a new input vector. Finally, a nonlinear regression model is designed to predict tool wear based on the new input vector. The proposed method is validated on both NASA Ames milling data set and the 2010 PHM Data Challenge data set. Results show the outstanding performance of the hybrid information model in tool wear prediction, especially when the experiments are run under various operating conditions. [ABSTRACT FROM AUTHOR]

Catastrophic tool failure (CTF) in milling process can cause damage to the product's machined surface and the machine tools, leading to huge financial losses. It is therefore critical to detect CTF in advance and promptly respond to it. Because of the safety and quality requirements imposed in practice, there are far fewer failure samples than normal samples, and this disequilibrium makes it difficult to detect failures. The aim of this study is to develop a new, easy, and practical automatic system for tool breakage detection using the acoustic emission (AE) technique. Components of AE raw data are analysed to locate the moments of tool breakages and to screen the corresponding AE feature samples. A support vector machine-based cost-sensitive breakage detection model is established and optimized. The proposed model is applied and validated by experiments conducted on a factory's milling machine. The model achieves an accuracy of 91.18% in the detection of breakages. The results show the practicability and validity of the proposed method. [ABSTRACT FROM AUTHOR]

The authors describe a novel electrochemical determination method for bisphenol A (BPA) based on the electrosynthesised Cu-BTC (H3BTC: trimesic acid) films. Using H3BTC as the ligand, Cu(NO3)2 as the precursor of copper ions, and triethylamine hydrochloride (Et3NHCl) as the probase source, Cu-BTC films were directly deposited on glassy carbon electrode (GCE) surface via cathodic electrochemical reduction under −1.30 V. Considering the electrocatalytic activity of metal center Cu2+, Cu-BTC films were applied to construct the electrochemical determination platform for BPA. Chronocoulometry and electrochemical impedance spectroscopy were used to study the signal enhancement mechanism. The determination conditions were optimized. As a result, a sensitive electrochemical method was constructed for BPA. The peak currents, best measured at voltage of 0.496 V vs. SCE (KCl saturated calomel reference electrode), increase linearly in the range from 5.0 to 2000 nM. The value of determination limit is 0.72 nM. The proposed method was successfully applied to determine BPA in spiked urine, spiked waste water samples and plastic products. The results were in good agreement with those obtained for the same samples by high-performance liquid chromatography (HPLC). [ABSTRACT FROM AUTHOR]

Tool wear degradation and working status of slotting cutter have a great effect on the surface quality of rotor slot; therefore, tool condition monitoring and its degradation estimation are needed for guaranteeing slot machining quality. This paper proposes a two-phase method based on acoustic emission (AE) signal classification and logistic regression model for slotting cutter condition monitoring and its degradation estimation. In the first phase, the failure reliability estimation models corresponding to different machining processes are established considering the variability of process system like tool regrinding times and material randomness of workpiece. In the second phase, the most appropriate estimation model corresponding to the optimum cluster is selected and used for failure reliability estimation and status determination of slotting cutter. This approach has been validated on a CNC rotor slot machine in a factory. Experimental results show that the proposed method can be effectively used for cutting tool degradation estimation and status determination of slotting cutter with high accuracy. [ABSTRACT FROM AUTHOR]

Previous studies investigating the relation between heat stress and crime incidents often focus on violent crimes. In this study, the impacts of heat stress on two types of robbery (violent and nonviolent) in China are compared using crime statistics collected in Beijing and heat stress indices that consider the combined effects of temperature and humidity. The results indicate that the abrupt change in the trend of robbery rates is affected by the 2008 Beijing Olympic Games. The nonviolent robbery rates have a more pronounced seasonality and are better correlated with heat stress at daily scales, especially during the period from 2009 to 2014 when no trend exists. The results also demonstrate that both violent and nonviolent robbery rates significantly increase with heat stress in spring. The nonviolent robbery rates also significantly increase with heat stress in summer. The influence of heat stress on violent robbery rate is more complicated and nonlinear. [ABSTRACT FROM AUTHOR]

The relationship between ground deposition of radionuclides and wind fields from the Fukushima Daiichi accident was investigated using the weather research and forecasting/chemistry model with the improvements by adding the radioactive decay process, dry and wet deposition parameterizations. To examine this correlation, wind fields near Fukushima Daiichi nuclear power plant (FDNPP) were defined as four different types mainly based on the wind direction, and the contaminated land areas were classified to five levels. The results showed that the distribution of the ground deposition of the radionuclides is mainly determined by the wind field rather than the precipitation distribution; Northeast wind has the largest contaminated land areas, and it is considered to much more easily accelerate the transport of radionuclides than any other wind direction near the FDNPP. It was also indicated by the results that in terms of high contaminated land area (>100 Bq/m), total ground deposition is dominated by dry deposition for I, and by wet deposition for Cs. [ABSTRACT FROM AUTHOR]

A sensitive and specific immunoaffinity column to clean up and isolate multiple mycotoxins was developed along with a rapid one-step sample preparation procedure for ultra-performance liquid chromatography-tandem mass spectrometry analysis. Monoclonal antibodies against aflatoxin B1, aflatoxin B2, aflatoxin G1, aflatoxin G2, zearalenone, ochratoxin A, sterigmatocystin, and T-2 toxin were coupled to microbeads for mycotoxin purification. We optimized a homogenization and extraction procedure as well as column loading and elution conditions to maximize recoveries from complex feed matrices. This method allowed rapid, simple, and simultaneous determination of mycotoxins in feeds with a single chromatographic run. Detection limits for these toxins ranged from 0.006 to 0.12 ng mL, and quantitation limits ranged from 0.06 to 0.75 ng mL. Concentration curves were linear from 0.12 to 40 μg kg with correlation coefficients of R > 0.99. Intra-assay and inter-assay comparisons indicated excellent repeatability and reproducibility of the multiple immunoaffinity columns. As a proof of principle, 80 feed samples were tested and several contained multiple mycotoxins. This method is sensitive, rapid, and durable enough for multiple mycotoxin determinations that fulfill European Union and Chinese testing criteria. [ABSTRACT FROM AUTHOR]

A toxin-free enzyme-linked immunosorbent assay (ELISA) for aflatoxins was developed using an anti-idiotype nanobody VHH 2-5 as surrogate standard. Anti-idiotype nanobody VHH 2-5 was generated by immunizing an alpaca with anti-aflatoxin monoclonal antibody 1C11. This assay was used to detect aflatoxins in agro-products after a simple extraction with 75 % methanol/HO. Aflatoxin concentration was calculated by a two-step approach: the concentration of VHH 2-5 was first obtained by a four-parameter logistic regression from the detected absorbance value at 450 nm, and then converted to aflatoxin concentration by a linear equation. The assay exhibits a limit of detection (LOD) of 0.015 ng mL, which is better than or comparable with conventional immunoassays. The performance of our VHH surrogate-based ELISA was further validated with a high-performance liquid chromatography (HPLC) method for total aflatoxins determination in 20 naturally contaminated peanut samples, displaying a good correlation ( R = 0.988). In conclusion, the proposed assay represents a first example applying an anti-idiotype VHH antibody as a standard surrogate in ELISA. With the advantages of high stability and ease of production, the VHH antibody-based standard surrogate can be extended in the future to immunoassays for other highly toxic compounds. [ABSTRACT FROM AUTHOR]

In order to develop an efficient system for deleting genomic segment in Agrobacterium tumefaciens to analyze gene functions and construct marker gene-free recombinant strains, a Cre recombinase expression plasmid was constructed by placing its encoding gene under the control of Ptet promoter and cloning into the plasmid replicable in both A. tumefaciens and E. coli. Triple recombineering was applied to efficiently construct integrative vectors which were used to introduce loxP sites and selection markers into the chromosome of A. tumefaciens. Cre recombinase could be properly induced by anhydrotetracycline in A. tumefaciens, which was revealed by the fact that kanamycin resistance gene flanked by two parallel loxP sites was excised from the genome of A. tumefaciens with virtually 100 % efficiency. And what is more, an A. tumefaciens mutant carrying large-deletion (~85 kb) in genome was successfully constructed by Cre/loxP system. Here, we described the application of combination of Cre/loxP system and triple recombineering to efficiently excise genomic segment in A. tumefaciens, which also would facilitate efficient construction of multiple gene disruptions in A. tumefaciens. [ABSTRACT FROM AUTHOR]

As a case study, the Meihe Basin, a typical Cenozoic faulted basin, was divided into and identified as five three-order sequences by utilizing core, well logging, and seismic data, as well as palaeontological and geochemical data. Field measurements of sections, core observations, and a comprehensive analysis revealed that the basin is mainly composed of deposits of alluvial fan, fan delta, lacustrine facies, and gravity flows, and oil shale is mainly developed in semi-deep and deep lacustrine environments. The comprehensive study of the sediment-sequence stratigraphy indicates that Sequence I was formed in the initial rifting stage of the basin, dominated by coarse clastic sediments of alluvial fan and fan delta. Sequence II was formed in the rifting expansion stage of the basin, with more developed sediments of fan delta and lacustrine. Sequence III was formed in the largest expansion stage of the basin, dominated by mudstone of deep lacustrine facies and gravity flow deposits. Sequence IV was formed in the shrinking stage of the basin, dominated by sediments of delta and lacustrine fan. Oil shale are mainly developed in the transgressive system tract (TST) and highstand system tract (HST) of Sequence III (Mudstone Member of lacustrine facies). The lake flooding effect of TST can reduce the decomposition amount of organic matter, increase in organic matter production, and reduce the amount of dilution, thus forming oil shale with a thin consistency but high quality. In the period of the HST, the larger accommodation space and excellent organic matter preservation conditions are conducive to developing stable oil shale with a greater consistency. During the high water level period, however, due to the oxygen brought in by turbidites, the decomposition of organic matter is often increased, resulting in the formation of low-quality oil shale. [ABSTRACT FROM AUTHOR]

Current link state routing is based on routing decisions made through distributed interactions among routers. Link state is disseminated by means of flooding, which possesses a few limitations, such as excessive message overhead and network-wide computation. Thus, we propose LSC, an extended link state routing protocol with centralized control, in this paper to address this problem. In LSC, link state advertisements (LSAs) are communicated between a centralized element (CE) and a forwarding engine (FE) rather than traditional flooding. Multiple CEs form a separate control network as a representation of the control plane. Through this control network, LSAs are disseminated to FEs in a determinate manner. We also propose a signaling protocol for independent path convergence in the control network, as well as a routing control algorithm to prevent unnecessary routing updates in the forwarding network. We implement a prototype LSC and evaluate its performance. Our experiments show that with the use of real topologies, LSC can accelerate network convergence and reduce message overhead compared with OSPF. Moreover, LSC is robust because having multiple CEs can prevent the occurrence of a single point of failure. LSC also scales well with network size by adding additional CEs to share in the processing load. [ABSTRACT FROM AUTHOR]

A 4-month field experiment was conducted in an organic vegetable production system; two crops, Brassica chinensis and Cichorium endivia L., were cultivated successively and treated with 0 (CKC), 30 (PC1), 60 (PC2), or 120 (PC3) t ha of pig manure-based compost. The replicated and heavy application of pig manure-based compost increased the total amounts of some heavy metals (Zn, Cu, Pb, and Cd) in the short term in soil. Despite the Shannon (bacterial diversity), Chao1 (richness), and evenness indices of different samples calculated after pyrosequencing analysis were similar, changes occurred in the bacterial community composition in soils amended with different rates of compost. The joint cluster and principal component analysis (PCA) indicated that heavy rates of compost may not change bacterial diversity in the short term and, in some cases, even produce a lower genetic diversity. The optimum rate, as well as the period, for compost application should be evaluated to promote the sustainable development of organic agriculture. [ABSTRACT FROM AUTHOR]

In this paper, we propose and demonstrate a 2 × 2 optical Benes switching unit based on two nested silicon microring resonators (MRRs) monolithically integrated on a silicon-on-insulator (SOI) wafer. High extinction ratios (ERs) of about 44.7/38.0 dB and low crosstalk values of about −37.5/−45.2 dB at cross/bar states are obtained with the fabricated device. The operation principle is theoretically studied and the switching function is verified by system demonstration experiments with 10 and 12.5 Gb/s non-return-to-zero (NRZ) signals. The switching speed on the order of gigahertz based on free carrier effect in silicon is also experimentally demonstrated. [ABSTRACT FROM AUTHOR]

A series of nanocapsules with carboxymethyl cellulose (CMC)-modified melamine-formaldehyde as the shell material and phase change paraffin as the core material were prepared by in situ polymerization. The modified capsules were examined using Fourier transform infrared spectra, scanning electronic microscope, differential scanning calorimeter, and optical microscopy, and two factors that influence paraffin emulsion preparation (emulsifier type and stirring rate) were investigated. The effects of the synthesis conditions used for the prepolymer on the surface morphology of the capsules were also studied. We found that phase change capsules prepared with both anionic and nonionic emulsifiers were superior to those prepared with a simple emulsifier. The best performance of the paraffin emulsion was obtained when the emulsion was stirred at 8,000 rpm during preparation. The optimal prepolymer reaction conditions to give smooth capsules with good dispersibility and complete morphology were reaction temperature 72.5 °C, reaction time 75 min, and pH 8.5. The CMC-modified nanocapsules have a phase change enthalpy of 83.46 J/g, are fully encased, and are uniform, with an average particle size of 50 nm. [ABSTRACT FROM AUTHOR]

With the analysis of the element geochemistry characteristics, the ancient lake information evolution history of the argillaceous source rocks in Lucaogou (芦草沟) Formation in Sangonghe (三工河) area is reconstructed. According to the ancient lake information and total organic matter (TOC) characteristics of argillaceous source rocks, the study section is divided into 6 Subsections. Subsection I mainly developed low-quality source rocks. This is because of the arid climate, high salinity, low lake productivity, unstable preservation conditions in this Subsection. Subsection II mainly developed high-quality source rocks. This is because of the humid climate, low salinity, high lake productivity, stable preservation conditions in this Subsection. Though the paleoclimate was humid and preservation conditions were stable. Lake productivity and the water salinity changed frequently. So Subsection III mainly developed medium-quality source rocks. Because of the humid climate, high lake productivity, medium sedimentary rate and stable preservation conditions, high-quality source rocks were developed in Subsection IV. The preservation conditions were stable, but other ancient lake information changed frequently. Therefore, the quality of the formed source rocks in Subsection V was different. Subsection VI mainly developed high-quality source rocks because of the humid climate, medium sedimentary rate, high lake productivity, low salinity and good preservation conditions. In summary, the ancient lake information parameters and TOC characteristics of each Subsection are different from each other. [ABSTRACT FROM AUTHOR]

A triple recombineering technique was used with plasmid pHT315 to produce pHTEC, a construct carrying chitinase and cry2Aa genes from Bacillus thuringiensis subsp. kurstaki 4.0718. Transformation of wild-type B. thuringiensis strain HD73 and the acrystalliferous strain Cry-B with pHTEC resulted in the recovery of recombinant strains that expressed Cry2Aa as cubic crystals in the cell pellet and soluble chitinase protein. The toxicity of HD73 (pHTEC) against Helicoverpa armigera larvae increased sevenfold when compared with HD73 (pHT315) harboring pHT315 vector. The triple recombineering protocol was optimized by comparing recombination efficacy mediated by RecE/RecT and Redα/Redβ and by using single-strand DNA as substrate. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel and flexible 16-quadrature amplitude modulation (16QAM) transmitter based on cascaded dual-parallel Mach-Zehnder modulator (DPMZM) and phase modulator (PM). The proposed transmitter is able to generate three types of 16QAM signals: square 16QAM, star 16QAM and four-amplitude-four-phase-16-QAM (FAFP-16QAM). The feasibility of the transmitter is verified through experiment, 20-Gb/s eye diagrams of the 16QAM signals are obtained. In order to evaluate the performances of the 16QAM signals, simulations are also conducted using VPI Transmission Maker, clear constellations of 40-Gb/s 16QAM signals are achieved by coherent detection. [ABSTRACT FROM AUTHOR]

Many scholars carried out large quantity of researches on oil and gas preservative conditions of marine carbonate rocks from the aspects of cap rocks, faults, formation water, hydrodynamic, and tectonism. This article gives dynamic evaluation on oil and gas preservative conditions of marine stratum in Jianghan (江汉) plain of multiphase tectonic disturbance from the view of paleofluid geochemistry. The conclusion shows that there mainly existed fluid filling of two periods in the reservoir of Lower-Middle Triassic to Permian. The fluid filled in the earlier period came from Lower Palaeozoic. The interchange of fluid in Lower-Middle Triassic to Permian suggested the oil and gas in Lower Palaeozoic had been broken up. The fluid filled in the later period (Lower-Middle Triassic to Permian) came from the same or adjacent strata and lacked anatectic fluidogenous features coming from Palaeozoic. With good preservative conditions of bulk fluid at the time, the fluid of Lower-Middle Triassic to Permian and that of Lower Palaeozoic did not connect with each other. However, the hydrocarbon generation peak of marine source rocks had passed or the paleo-oil and gas reservoirs had been destroyed at that time and the marine stratum of Palaeozoic to Triassic in the research area did not put out commercial oil and gas flow. [ABSTRACT FROM AUTHOR]

Based on the characteristics of the complex system, this paper presents a novel method, the monotonic indexes space method, for the effectiveness analysis of the complex system. First, it presents some basic concepts and assumption such as the monotonic indexes space, monotonic indexes requirement locus, etc. Second, based on the assumption that indexes are monotonic for the requirements, an algorithm is proposed and applied to numerical approximation of monotonic indexes requirement locus with hyperboxes. Third, this paper proposes two algorithms for acquiring intersection of several monotonic indexes requirement locus. Fourth, this paper proposes the monotonic-index-space based system analysis model such as the system evaluation model, the sensitivity analysis model for indexes. Based on the practical requirement, the concept of fuzzy monotonic indexes requirement locus and the corresponding analysis model are introduced. Finally, this paper applies the above-mentioned models to analyze the effectiveness of a notional anti-stealth-air-defense information system. And the outputs show that the method is promising. [ABSTRACT FROM AUTHOR]

Pseudoxanthoma elasticum (PXE) is a hereditary disease characterized by progressive dystrophic mineralization of the elastic fibres. PXE patients frequently present with skin lesions and visual acuity loss. Recently, we and others showed that PXE is caused by mutations in the ABCC6/MRP6 gene. However, the molecular pathology of PXE is complicated by yet unknown factors causing the variable clinical expression of the disease. In addition, the presence of ABCC6/MRP6 pseudogenes and multiple ABCC6/MRP6- associated deletions complicate interpretation of molecular genetic studies. In this study, we present the mutation spectrum of ABCC6/MRP6 in 59 PXE patients from the Netherlands. We detected 17 different mutations in 65 alleles. The majority of mutations occurred in the NBF1 (nucleotide binding fold) domain, in the eighth cytoplasmatic loop between the 15th and 16th transmembrane regions, and in NBF2 of the predicted ABCC6/MRP6 protein. The R1141X mutation was by far the most common mutation identified in 19 (32.2%) patients. The second most frequent mutation, an intragenic deletion from exon 23 to exon 29 in ABCC6/MRP6, was detected in 11 (18.6%) of the patients. Our data include 11 novel ABCC6/MRP6 mutations, as well as additional segregation data relevant to the molecular pathology of PXE in a limited number of patients and families. The consequences of our data for the molecular pathology of PXE are discussed. [ABSTRACT FROM AUTHOR]

In this work, a novel soft-hard template method towards the direct fabrication of graphene films on silicon/silica substrate is developed via a tri-constituent self-assembly route. Using cetyl trimethyl ammonium bromide (CTAB) as a soft template, silica (SiO2) from tetramethoxysilane as a hard template, and pyrene as a carbon source, the self-assembly process allows the formation of a sandwich-like SiO2/CTAB/pyrene composite, which can be further converted to high quantity graphene films with a thickness of ~1 nm and a size of over 5 μm by thermal treatment. The morphology and thickness of the graphene films can be effectively controlled through the adjustment of the ratio of pyrene to CTAB. Furthermore, a high nonlinear refractive index n2 of ~10−12 m2 W−1 is measured from graphene/silica hybrid film, which is six orders of magnitude larger than that of silicon and comparable to the graphene from chemical vapor deposition process. [ABSTRACT FROM AUTHOR]