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Purpose: To explore the soil heavy metal pollution around Wangchun Industrial Park and its health effects on people of different ages. Methods: In this study, pollution assessment methods such as the I geo and the Nemero Comprehensive Pollution Index were used to assess the pollution status of six heavy metals Cd, Ni, Pb, Cu, Hg and As in 32 soil samples collected from Wangchun Industrial Park. Results: Observed the average concentrations of the six heavy metals exceeded the background values of Ningshao Plain in four heavy metals, As, Ni, Cu, and Hg, but none of them exceeded the screening values of construction land. According to the analysis of local accumulation index and Nemero index, the order of soil pollution and heavy metal concentration is as follows: As > Ni > Cu > Pb > Cd > Hg. The The results of human health risk assessment, adult men, women, and children are at a higher risk of non-carcingenic from ingestion of HMs that are exposed to the route, children are the group at highest risk of As cancer. Conclusions: Contamination of As, Ni and Cu in the soil of the study area has been primarily influenced by the mixing of nearby industrial activities and other human activities. The appropriate concentration ranges of As, Ni and Cu are as follows: As: 5.4–6 mg/kg, Ni: 21.51–32 mg/kg, Cu: 20.98–31.62 mg/kg, which have little impact on human health. [ABSTRACT FROM AUTHOR]

Accurate identification of Seriola dumerili (SD) offers crucial technical support for aquaculture practices and behavioral research of this species. However, the task of discerning S. dumerili from complex underwater settings, fluctuating light conditions, and schools of fish presents a challenge. This paper proposes an intelligent recognition model based on the YOLOv8 network called SD-YOLOv8. By adding a small object detection layer and head, our model has a positive impact on the recognition capabilities for both close and distant instances of S. dumerili, significantly improving them. We construct a convenient S. dumerili dataset and introduce the deformable convolution network v2 (DCNv2) to enhance the information extraction process. Additionally, we employ the bottleneck attention module (BAM) and redesign the spatial pyramid pooling fusion (SPPF) for multidimensional feature extraction and fusion. The Inner-MPDIoU bounding box regression function adjusts the scale factor and evaluates geometric ratios to improve box positioning accuracy. The experimental results show that our SD-YOLOv8 model achieves higher accuracy and average precision, increasing from 89.2% to 93.2% and from 92.2% to 95.7%, respectively. Overall, our model enhances detection accuracy, providing a reliable foundation for the accurate detection of fishes. [ABSTRACT FROM AUTHOR]

We herein report a novel, reliable and inexpensive method for detecting esophageal cancer using blood plasma resonance Raman spectroscopy combined with multivariate analysis methods. The blood plasma samples were divided into late stage cancer group (n = 164), early stage cancer group (n = 35) and normal group (n = 135) based on clinical pathological diagnosis. Using a specially designed quartz capillary tube as sample holder, we obtained higher quality resonance Raman spectra of blood plasma than existing method. The study demonstrated that the carotenoids levels in blood plasma were reduced in esophageal cancer patients. The area under the receiver operating characteristic curve (and 95% confidence interval) calculated by wavenumber selection and principal component analysis combined with linear discriminant analysis (PC‐LDA) algorithm were 0.894 (0.858‐0.929), 0.901 (0.841‐0.960) and 0.871 (0.799‐0.942) for differentiating late cancer from normal, late cancer from early cancer, and early cancer from normal respectively. The contribution from the two carotenoids wavenumber regions of 1155 and 1515 cm−1 were more than 84.2%. The results show that the plasma carotenoids could be a potential biomarker for screening esophageal cancer using resonance Raman spectroscopy combined with wavenumber selection and PC‐LDA algorithms. [ABSTRACT FROM AUTHOR]

This study aims to reveal the distribution of topics, and the associations among them, in information behavior research from 2009 to 2018. Working with a collection of 6744 publications from the Web of Science database, co-word analysis is used to investigate the overall topic structure, the associations among the topics, and their evolution in different years, which is supplemented by visualization with science maps. The results uncovered an unbalanced distribution of topics, and that the topics cluster into six communities representing subdivisions of this field: information behavior in patient-centered studies; information interaction in the digital environment; information literacy in health and academic contexts; health literacy on the Internet; information behavior in child-centered studies; and information behavior in medical informatics. The findings supplement and provide refinements to work on the state of this field, and help researchers obtain an overview of the past decade to guide their future work. [ABSTRACT FROM AUTHOR]

Children's books involve a large number of topics. Research on them has been paid much attention to by both scholars and practitioners. However, the existing achievements do not focus on China, which is the fastest growing market for children's books in the world. Studies using quantitative analysis are low in number, especially on the intellectual structure, evolution patterns, and development trends of topics of children's bestsellers in China. Dangdang.com, the biggest Chinese online bookstore, was chosen as a data source to obtain children's bestsellers, and topic words in them were extracted from brief introductions. With the aid of co-occurrence theory and tools of social network analysis and visualization, the distribution, correlation structures, and evolution patterns of topics were revealed and visualized. This study shows that topics of Chinese children's bestsellers are broad and relatively concentrated, but their distribution is unbalanced. There are four distinguished topic communities (Living, Animal, World, and Child) in terms of centrality and maturity, and they all establish their individual systems and tend to be mature. The evolution of these communities tends to be stable with powerful continuity. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to identify the leading topics and developmental trends of archival information resource research in China by visualizing the intellectual structure and evolution patterns of archival information resource research. Design/methodology/approach: This study took China National Knowledge Infrastructure (CNKI) as the data source and extracted keywords from relevant articles in archival information resource research as the sample. First, the frequency and co-occurrence of keywords were calculated by using SCI2. Second, this study analyzed the co-word network indicators by using Pajek. Then, topic community detection was conducted by using a VOS viewer, as well as the visualization of intellectual structures. Next, this study developed a graphical mapping of the evolution of research topics over time by using Cortext. Findings: The research topics of archival information resources in China were unbalanced but distinct. Researchers focus on the construction and utilization of archival information resource, which consist of five evident research directions. The phenomena of fusion and differentiation coexist in research topic evolution. There were both continuities of traditional research and innovations in emerging research. The archival information resource research tended to be systematized and extended, reflecting the vertical and horizontal extension of the research content. Originality/value: Based on a large number of previous studies, this study adopted quantitative methods to reveal the intellectual structure and evolution patterns of archival information resource research in China, providing guidance for researchers and institutions to grasp research status and developmental trends. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to measure the degree of interdisciplinary collaboration in Big Data research based on the co-occurrences of subject categories using Stirling’s diversity index and specialization index.Design/methodology/approach Interdisciplinarity was measured utilizing the descriptive statistics of disciplines, network indicators showing relationships between disciplines and within individual disciplines, interdisciplinary communities, Stirling’s diversity index and specialization index, and a strategic diagram revealing the development status and trends of discipline communities.Findings Comprehensively considering all results, the degree of interdisciplinarity of Big Data research is increasing over time, particularly, after 2013. There is a high level of interdisciplinarity in Big Data research involving a large number of disciplines, but it is unbalanced in distribution. The interdisciplinary collaborations are not intensive on the whole; most disciplines are aggregated into a few distinct communities with computer science, business and economics, mathematics, and biotechnology and applied microbiology as the core. Four major discipline communities in Big Data research represent different directions with different development statuses and trends. Community 1, with computer science as the core, is the most mature and central to the whole interdisciplinary network. Accounting for all network indicators, computer science, engineering, business and economics, social sciences, and mathematics are the most important disciplines in Big Data research.Originality/value This study deepens our understanding of the degree and trend of interdisciplinary collaboration in Big Data research through a longitudinal study and quantitative measures based on two indexes. It has practical implications to study and reveal the interdisciplinary phenomenon and characteristics of related developments of a specific research area, or to conduct comparative studies between different research areas. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to visualize the collaboration network among regions in library science (LS) in China. Using various methods and tools of social network analysis and geographical visualization, results were obtained, showing the structure and patterns of research collaborations in topological and geographical views, as well as the geographical distributions of contribution.Design/methodology/approach The sample includes all studies published in the top journal in library science in China from 2006 to 2015. First, co-occurrence data representing collaborations among regions was extracted from author affiliations. Second, the topological network of collaboration was generated by applying social network analysis tools and descriptive statistics, network indicators of the collaboration network and research communities were calculated. Third, the topological network was projected into a geographical map with corresponding coordinates and distances using geographical tools. Finally, the topological network maps and the geographical maps were produced for visualization.Findings The levels of contribution are very unbalanced between regions, and overall research collaboration is low. Beijing, Hubei and several other areas are central and significant regions in China; other regions are mostly connected with central ones through direct collaborations. Research collaborations in LS research in China are mostly distributed in the east and south of China, being centralized in the “Beijing–Hubei–Shanghai” triangle zone, as well as within the triangle’s extending zones. Finally, there are three distinct research communities that connect closely within themselves and loosely between them. The Beijing community is relatively centralized in geography, while other communities are scattered.Originality/value This study applied various methods and tools of social network analysis and geographical mapping analysis to reveal the collaboration structure and patterns among regions in LS research in China. Visualized maps in topological and geographical views help shed new light on research efforts. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to reveal the structure and patterns of cross-national collaborations in Big Data research through application of various social network analysis and geographical visualization methods.Design/methodology/approach The sample includes articles containing Big Data research, covering all years, in the Web of Science Core Collection as of December 2015. First, co-occurrence data representing collaborations among nations were extracted from author affiliations. Second, the descriptive statistics, network indicators of collaborations, and research communities were calculated. Third, topological network maps, geographical maps integrated with topological network projections, and proportional maps were produced for visualization.Findings The results show that the scope of international collaborations in Big Data research is broad, but the distribution among nations is unbalanced and fragmented. The USA, China, and the UK were identified as the major contributors to this research area. Five research communities are identified, led by the USA, China, Italy, South Korea, and Brazil. Collaborations within each community vary, reflecting different levels of research development. The visualizations show that nations advance in Big Data research are centralized in North America, Europe, and Asia-Pacific.Originality/value This study applied various informetric methods and tools to reveal the collaboration structure and patterns among nations in Big Data research. Visualized maps help shed new light on global research efforts. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to analyze the research status and outputs of information behavior in China in order to reveal its in-depth research pattern and trends.Design/methodology/approach The author collected literature during the past 29 years from China Academic Journal Network Publishing Database. Bibliometric analysis, including publication growth analysis, core authors and collaborative degree analysis, core journals analysis, and institutions distribution, was performed. The temporal visualization map of burst term was drawn, and the co-occurrence matrix of these keywords was analyzed by the hierarchical cluster analysis, strategic diagram, and social network analysis.Findings The earliest article on information behavior in China was published in 1987. And the number of articles has risen continually since then, which follows the logical growth law of literature. The collaborative degree of authors is on the rise in general. The distribution of these articles obeys the Bradford’s Law of Scattering. School of Information Management of Wuhan University remarkably ranks the top in most publications. In all, ten important research directions were identified, which are in the imbalanced development. And a newly appearing topic with great potential for further development, namely information seeking and information security, is identified.Originality/value This study provides important insights into the research status and trends on information behavior in China, which might provide a potential guide for the future research. [ABSTRACT FROM AUTHOR]

Big Data is a research field involving a large number of collaborating disciplines. Based on bibliometric data downloaded from the Web of Science, this study applies various social network analysis and visualization tools to examine the structure and patterns of interdisciplinary collaborations, as well as the recently evolving overall pattern. This study presents the descriptive statistics of disciplines involved in publishing Big Data research; and network indicators of the interdisciplinary collaborations among disciplines, interdisciplinary communities, interdisciplinary networks, and changes in discipline communities over time. The findings indicate that the scope of disciplines involved in Big Data research is broad, but that the disciplinary distribution is unbalanced. The overall collaboration among disciplines tends to be concentrated in several key fields. According to the network indicators, Computer Science, Engineering, and Business and Economics are the most important contributors to Big Data research, given their position and role in the research collaboration network. Centering around a few important disciplines, all fields related to Big Data research are aggregated into communities, suggesting some related research areas, and directions for Big Data research. An ever-changing roster of related disciplines provides support, as illustrated by the evolving graph of communities. [ABSTRACT FROM AUTHOR]

Herein we propose a hybridization chain reaction based kinetics competition strategy able to recognize the combination/sequence of input signals. Further, a DNA priority encoder and a keypad lock were constructed. This strategy allowed us to develop a one-pot assay that can automatically and smartly respond to multiple inputs. [ABSTRACT FROM AUTHOR]

A new fluorescence sensor is developed for simultaneous detection of Hg and Ag. During the detection process, Hg forms complexes with the fluorescent dye rhodamine B isothiocyanate (RBITC) modified onto the surface of gold nanoparticles(AuNPs), resulting in RBITC's displacement from the surface of AuNPs and the recovery of fluorescence. Meanwhile, Ag forms 'C-Ag-C' complex with C-rich 5-carboxyfluorescein (FAM)-ssDNA modified onto the surface of AuNPs, which keeps the fluorescent dye FAM close to the AuNPs and results in quench of fluorescence. The experimental results show a wide linear range and a good sensitivity. The limit of detection is 1.06 nmol/L for Ag and 0.48 nmol/L for Hg. This detection method is not only easy to operate but also efficient. [ABSTRACT FROM AUTHOR]

We report the design of a high-performance asymmetric supercapacitor (ASC) based on manganese monoxide/carbon aerogel (MnO/NCA) composites as the positive electrode and iron oxide/carbon aerogel (Fe2O3/NCA) composites as the negative electrode. The prepared MnO/NCA hybrid composites display a highly interconnected network structure with ultrathin MnO nanoparticles uniformly embedded into the 3D nitrogen-doped carbon matrix. Because of the synergistic effects of the highly conductive carbon aerogel and highly pseudocapacitive metal oxides, the hybrid MnO/NCA electrode exhibits highly effective surface area, greatly enhanced ion transportation, and excellent electrochemical performance, in comparison with other MnOx-based electrode materials. Matching it with the Fe2O3/NCA cathode, the novel ASC devices can achieve a high voltage window of 2.0 V, delivering a remarkable energy density of 48.67 W h kg−1 at a power density of 1000 W kg−1 and still retains 27.39 W h kg−1 at a high power density of 10 kW kg−1, consequently giving rise to stable cycling performance. These encouraging results will provide a fresh route for the design and fabrication of metal oxide@carbon aerogel materials for application in next-generation storage systems. [ABSTRACT FROM AUTHOR]

Purpose The purpose of this paper is to examine behavior intention of Chinese university students toward mobile library (m-library) applications (apps) and to explore the determinants of their perceptions of m-library apps.Design/methodology/approach Based on previous research, this study first proposed an integrated model and hypothesized the relationships between constructs while exploring the significance of the effects of education level and discipline. In all, 466 undergraduate and graduate students from various disciplines participated in a survey for this study. A structural equation modeling approach was applied for analysis.Findings Attitude is the main predictor of behavior intention toward m-library apps, and it is significantly affected by perceived usefulness, self-efficacy, and subjective norm. The quality of m-library apps determines students’ perception of usefulness. In addition, education level and discipline have significant effects on behavior intention toward m-library apps, which may reflect students’ different focuses and purposes of use.Originality/value This study deepens understanding of the continuance usage of m-library apps and has practical implications on related developments and services. [ABSTRACT FROM AUTHOR]

Nitrites (NO2− ions) in food and drink play an important role in human health but require complicated operations before detection. Herein, we present a rationally designed SERS-enabled micro-chamber that comprised a drawn glass capillary with a tiny orifice (∼50 μm) at the distal tip, wherein the gold nanoparticles (Au NPs) are compactly coated on the inner wall surface. In this chamber, nitrites specifically trigger a pH and laser irradiance-dependent diazotization starting from p-aminothiophenol (PATP) absorbed onto the surface of Au NPs to form p,p′-dimercaptoazobenzene (DMAB) molecules, in which the presence of NO2− ions above 30.7 μM (1.38 ppm) in the siphoned liquid sample can be identified relying on SERS peak (1141 cm−1) intensity of the emerging azo moiety. Except for pH conditions, laser irradiance is more important but easily neglected in previous studies, which is capable of preventing generation of errors when the detection sensitivity was pursued through increasing the laser power. In this case, several real samples (rather than simple water samples), including honey, pickled vegetable and fermented bean curd, had been successfully detected accurately through such a convenient sampling micro-chamber. The SERS-enabled device could potentially be facilely incorporated with portable Raman instruments for a special application of food inspection in rapid and field analysis of NO2− ions. [ABSTRACT FROM AUTHOR]

We report on a continuous and non-invasive approach in vivo to monitor arterial blood pH based on the laser trapping and Raman detection of single live erythrocytes. A home-built confocal laser tweezers Raman system (LTRS) is applied to trace the live erythrocytes at different pH values of the extracellular environment to record their corresponding Raman changes in vitro and in vivo. The analysis results in vitro show that when the extracellular environment pH changes from 6.5 to 9.0, the Raman intensity ratio (R1603, 1616 = I1603/I1616) of single erythrocytes decrease regularly; what is more, there is a good linear relationship between these two variables, and the linearity is 0.985, which is also verified successfully via in vivo Raman measurements. These results demonstrate that the Raman signal of single live erythrocytes is possible as a marker of the extracellular pH value. This in vivo and quantitative Raman-pH sensor of arterial blood will be an important candidate for monitoring the acid–base status during the treatment of ill patients and in some major surgeries because of its continuous and non-invasive characters. [ABSTRACT FROM AUTHOR]

This review (with 139 refs.) gives a fundamental introduction into the sensors and logic gates based on G-quadruplexes (G4s). G4 characterizes vibrant binding activities and topology diversity, which contribute to the multiple signal output modes (including labeled moieties based on distance changes, label-free outputs by employing fluorescent ligands, G4/hemin DNAzyme with catalyzing activity and colorimetric readout using gold nanoparticles) and versatile design strategies (including target-induced G4 formation/disruption, liberation of blocked G4, split G4 probes, polymerase-assisted amplification and G4/hemin enrichment on sensor surface) of G4s-based methods. Following two important trends in logic gates (application of intelligent detection schemes and logic circuit constructions), specific sections review logic sensors and logic circuits based on G4s with several representative examples. We close this review with conclusions and give a perspective that employment of DNA technologies (such as aptamers, DNA junctions/origami, toehold-mediated strand displacement, enzyme-assisted amplification, metal ion-dependent DNAzymes) and various nanomaterials in G4s-based methods results in quite a large potential in terms of logic detection and construction of logic circuits. [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

Herein, we presented a novel logic gate based on an INHIBITION gate that performs parallel readouts. Logic gates performing INHIBITION and YES/OR were constructed using surface-enhanced Raman scattering as optical outputs for the first time. The strategy allowed for simultaneous reading of outputs in one tube. The applicability of this strategy has been successfully exemplified in the construction of half-adder using the two-output logic gates as reporting gates. This reporting strategy provides additional design flexibility for dynamic DNA devices. [ABSTRACT FROM AUTHOR]

Anisotropic metallic nanoparticles (NPs) possess unique optical properties, which lend them to applications such as surface-enhanced Raman scattering (SERS). However, their preparation by an efficient, biocompatible and high yield synthetic method is still challenging. In this work, we demonstrate a simple and reproducible way to produce chitosan (CS) encapsulated gold–silver nanoflowers by sequentially adding chitosan, chloroauric acid, silver nitrate, and ascorbic acid to water at room temperature. This is a one-pot, seed- and surfactant-free synthetic method, which is simple and credible. CS is used to modulate the size of NPs, while AgNO3 is introduced to improve the monodispersity and homogeneity of NPs. Highly sensitive, spectrally and physically stable SERS tags are developed in virtue of the cooperative effect of CS and Ag+. Cresyl violet (CV) is applied as a Raman reporter to test the SERS property of NPs, and the results demonstrated that the nanoflowers exhibited stronger and more stable SERS signals than those of spherical gold nanoparticles. Importantly, after being modified by tumor cell-specific targeting ligands (folic acid), the sensitive and stable labeled nanoflowers are applied for cancer cell targeting and SERS imaging. [ABSTRACT FROM AUTHOR]

The precisely controlled synthesis of a specific morphology is proved to be highly effective for enhancing sensing performance of functional micro- and nano-materials. Thus, a comprehensive understanding of the effect of synthesis conditions on morphology evolution is of great importance. In this paper, by using In2O3 as an example, we demonstrate the great effect of supersaturation on the morphology evolution during the growth process. Under vapour-phase synthesis, by varying positions of product collection, the amount of the starting materials, and reaction temperatures, a continuous two-step route consisting of ammonolysis and re-oxidation processes was developed for the morphology evolution of several kinds of In2O3, including octahedron strings, nanowires, crystal chains, lollipop-like structures, and particles. The controlled supersaturation of the In2O3 vapour was eventually proved to be a decisive factor for the formation of various In2O3 morphologies. Furthermore, we evaluated the gas-sensing properties of the three kinds of one-pot synthesized In2O3, indicating a shape-dependent relationship with sensing performance. The present work not only offers a unique strategy to control supersaturation in vapour-phase synthesis, but also provides an opportunity to deeply understand the morphology-dependent sensing performance. [ABSTRACT FROM AUTHOR]

Novel three-dimensional (3D) nano-assemblies of noble metal nanoparticle (NP)–infinite coordination polymers (ICPs) are conveniently fabricated through the infiltration of HAuCl4 into hollow Au@Ag@ICPs core–shell nanostructures and its replacement reaction with Au@Ag NPs. The present 3D nano-assemblies exhibit highly efficient and specific intrinsic oxidase-like activity even without adding any cosubstrate. [ABSTRACT FROM AUTHOR]

A simple, versatile, and label-free DNA computing strategy was designed by using toehold-mediated strand displacement and stem-loop probes. A full set of logic gates (YES, NOT, OR, NAND, AND, INHIBIT, NOR, XOR, XNOR) and a two-layer logic cascade were constructed. The probes contain a G-quadruplex domain, which was blocked or unfolded through inputs initiating strand displacement and the obviously distinguishable light-up fluorescent signal of G-quadruplex/NMM complex was used as the output readout. The inputs are the disease-specific nucleotide sequences with potential for clinic diagnosis. The developed versatile computing system based on our label-free and modular strategy might be adapted in multi-target diagnosis through DNA hybridization and aptamer-target interaction. [ABSTRACT FROM AUTHOR]

We report a new and efficient protocol for rapid electrodeposition of a gold–Prussian blue ((Au–PB)REd) nanocomposite with ultrahigh electroactivity on an Au electrode by cyclic voltammetry in 0.1 M aqueous K2SO4 containing 1 mM K3Fe(CN)6, 1 mM HAuCl4, and 0.1 mM Fe2(SO4)3, and an electrochemical quartz crystal microbalance and scanning electron microscopy were utilized to investigate the electrodeposition. The (Au–PB)REd/Au electrode was then cast-coated with a urate oxidase (UOx)–poly(anilineboronic acid) (PABA)–Pt nanoparticle (PtNP) bionanocomposite and chitosan (CS) for high-performance amperometric biosensing of uric acid (UA) in the dual-potential mode. The UOx–PABA–PtNP bionanocomposite was prepared through chemical oxidation of anilineboronic acid (ABA) by sodium chloroplatinate in the presence of UOx. The thus-fabricated CS/UOx–PABA–PtNP/(Au–PB)REd/Au enzyme electrode worked well under optimized conditions through both oxidation and reduction determination of enzyme-generated H2O2, which responded linearly to UA concentrations from 0.3 μM to 0.65 mM with a sensitivity of 223 μA mM−1 cm−2 and a limit of detection (LOD) of 0.2 μM (0.7 V vs. SCE), and from 0.2 μM to 0.25 mM with a sensitivity of 247 μA mM−1 cm−2 and a LOD of 0.1 μM (−0.05 V vs. SCE), being superior to most analogues hitherto reported for biosensing of UA. [ABSTRACT FROM AUTHOR]

We describe a highly sensitive and spectrally stable surface-enhanced Raman scattering (SERS) tag for live cell imaging based on carbon-encapsulated gold nano-aggregates (CEGNAs). Our findings reveal that controlling the synthesis of the gold nano-aggregate core can be achieved under the mediation of cetyltrimethylammonium bromide (CTAB) through electrostatic forces and hydrophobic interactions, and as the number of particles in the aggregates increase, the relative SERS activity also increases hugely. [ABSTRACT FROM AUTHOR]

In this paper, the sampled-data state estimation problem is investigated for a class of recurrent neural networks with time-varying delay. Instead of the continuous measurement, the sampled measurement is used to estimate the neuron states, and a sampled-data estimator is constructed. By converting the sampling period into a bounded time-varying delay, the error dynamics of the considered neural network is derived in terms of a dynamic system with two different time-delays. Subsequently, by choosing an appropriate Lyapunov functional and using the Jensen's inequality, a sufficient condition depending on the sampling period is obtained under which the resulting error system is exponentially stable. Then a sampled-data estimator is designed in terms of the solution to a set of linear matrix inequalities (LMIs) which can be solved by using available software. Finally, a numerical example is employed to demonstrate the effectiveness of the proposed sampled-data estimation approach. [ABSTRACT FROM AUTHOR]

Self-replication, an important concept abstracted from reproduction, the key feature of life, remains vague in definition and lacking in clear interpretation in terms of its chemical mechanism. Mentioned frequently in discussions concerning the essence of life and its origin, the vague concept has caused a lot of uncertain statements, confusable references, and malposed debates, and has seriously held back efforts in this field. In this article, we try to improve the situation by a conceptual analysis in a more fundamental and clearer background. Self-replication in the substantial world could not mean anything but that 'an entity favors the production of its own.' The major chemical mechanism for such favoring is catalysis, which can be classified into speed- and direction-favoring types (the template-directing function is actually a type of direction-favoring catalysis). Molecular self-replication could be based on autocatalysis or self-metabolism; the self-replication of a complex entity could be based on autocatalytic and/or self-metabolic sets, and should involve a mechanism of self-division. This conceptual clarification sheds light on the dim areas concerning the essence of life and its origin. [ABSTRACT FROM AUTHOR]

The paper describes an energy-dispersive X-ray spectrometer for a scanning electron microscope (SEM-EDXS). It was constructed using the new architecture of a virtual instrument (VI), which is low-cost, space-saving, fast and flexible way to develop the instrument. Computer-aided teaching (CAT) was used to develop the instrument and operation rather than a traditional instrument technique. The VI was designed using the object-oriented program language C++ and compact programmable logical devices (CPLD). These include spectra collection and processing, quantitative analysis and X-ray-intensity distribution analysis. The procedure is described in detail. The VI system gives an effective and user-friendly human interface for the whole analytical task. Some examples are described. [ABSTRACT FROM AUTHOR]

A simple method of fabricating shape-tunable Au nanopeanuts from Au–Ag core–shell nanoparticles based on both galvanic replacement and reagent reduction is described. [ABSTRACT FROM AUTHOR]