87 resultados para 310-M0011A


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The mechanical properties of microfilament networks are systematically summarized at different special scales in this paper. We have presented the mechanical models of single microfilaments and microfilament networks at microscale. By adopting a coarse-grained simulation strategy, the mechanical stability of microfilaments related cellular structures are analysed. Structural analysis is conducted to microfilament networks to understand the stress relaxation under compression. The nanoscale molecular mechanisms of the microfilaments deformation is also summarized from the viewpoint of molecular dynamics simulation. This paper provides the fundaments of multiscale modelling framework for the mechanical behaviours simulation of hierarchical microfilament networks.

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Bioremediation is a potential option to treat 1, 1, 1-trichloro-2, 2 bis (4-chlorophenyl) ethane (DDT) contaminated sites. In areas where suitable microbes are not present, the use of DDT resistant microbial inoculants may be necessary. It is vital that such inoculants do not produce recalcitrant breakdown products e.g. 1, 1-dichloro-2, 2-bis (4-chlorophenyl) ethylene (DDE). Therefore, this work aimed to screen DDT-contaminated soil and compost materials for the presence of DDT-resistant microbes for use as potential inoculants. Four compost amended soils, contaminated with different concentrations of DDT, were used to isolate DDT-resistant microbes in media containing 150 mg I -1 DDT at three temperatures (25, 37 and 55°C). In all soils, bacteria were more sensitive to DDT than actinomycetes and fungi. Bacteria isolated at 55°C from any source were the most DDT sensitive. However DDT-resistant bacterial strains showed more promise in degrading DDT than isolated fungal strains, as 1, 1-dichloro 2, 2-bis (4-chlorophenyl) ethane (DDD) was a major bacterial transformation product, while fungi tended to produce more DDE. Further studies on selected bacterial isolates found that the most promising bacterial strain (Bacillus sp. BHD-4) could remove 51% of DDT from liquid culture after 7 days growth. Of the amount transformed, 6% was found as DDD and 3% as DDE suggesting that further transformation of DDT and its metabolites occurred.

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The results of a study on the influence of the nonparabolicity of the free carriers dispersion law on the propagation of surface polaritons (SPs) located near the interface between an n-type semiconductor and a metal arc reported. The semiconductor plasma is assumed to be warm and nonisothermal. The nonparabolicity of the electron dispersion law has two effects. The first one is associated with nonlinear self-interaction of the SPs. The nonlinear dispersion equation and the nonlinear Schrodinger equation for the amplitude of the SP envelope are obtained. The nonlinear evolution of the SP is studied on the base of the above mentioned equations. The second effect results in third harmonics generation. Analysis shows that these third harmonics may appear as a pure surface polariton, a pseudosurface polariton, or a superposition of a volume wave and a SP depending on the wave frequency, electron density and lattice dielectric constant.

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Optical emission of reactive plasma species during the synthesis of functionally graded calcium phosphate-based bioactive films has been investigated. The coatings have been deposited on Ti-6Al-4V orthopedic alloy by co-sputtering of hydroxyapatite (HA) and titanium targets in reactive plasmas of Ar + H2O gas mixtures. The species, responsible for the Ca-P-Ti film growth have been non-intrusively monitored in situ by a high-resolution optical emission spectroscopy (OES). It is revealed that the optical emission originating from CaO species dominates throughout the deposition process. The intensities of CaO, PO and CaPO species are strongly affected by variations of the operating pressure, applied RF power, and DC substrate bias. The optical emission intensity (OEI) of reaction species can efficiently be controlled by addition of H2O reactant.

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Corporate social responsibility is imperative for manufacturing companies to achieve sustainable development. Under a strong environmental information disclosure system, polluting companies are disadvantaged in terms of market competitiveness, because they lack an environmentally friendly image. The objective of this study is to analyze productive inefficiency change in relation to toxic chemical substance emissions for the United States and Japan and their corresponding policies. We apply the weighted Russell directional distance model to measure companies productive inefficiency, which represents their production technology. The data encompass 330 US manufacturing firms observed from 1999 to 2007, and 466 Japanese manufacturing firms observed from 2001 to 2008. The article focuses on nine high-pollution industries (rubber and plastics; chemicals and allied products; paper and pulp; steel and non-ferrous metal; fabricated metal; industrial machinery; electrical products; transportation equipment; precision instruments) categorized into two industry groups: basic materials industries and processing and assembly industries. The results show that productive inefficiency decreased in all industrial sectors in the United States and Japan from 2001 to 2007. In particular, that of the electrical products industry decreased rapidly after 2002 for both countries, possibly because of the enforcement of strict environmental regulations for electrical products exported to European markets.

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Glassy carbon (GC) electrode modified with a self-assembled monolayer (SAM) of 1,8,15,22-tetraaminophthalocyanatocobalt(II) (4α-CoIITAPc) was used for the selective and highly sensitive determination of nitric oxide (NO). The SAM of 4α-CoIITAPc was formed on GC electrode by spontaneous adsorption from DMF containing 1 mM 4α-CoIITAPc. The SAM showed two pairs of well-defined redox peaks corresponding to CoIII/CoII and CoIIIPc−1/CoIIIPc−2 in 0.2 M phosphate buffer (PB) solution (pH 2.5). The SAM modified electrode showed excellent electrocatalytic activity towards the oxidation of nitric oxide (NO) by enhancing its oxidation current with 310 mV less positive potential shift when compared to bare GC electrode. In amperometric measurements, the current response for NO oxidation was linearly increased in the concentration range of 3×10−9 to 30×10−9 M with a detection limit of 1.4×10−10 M (S/N=3). The proposed method showed a better recovery for NO in human blood serum samples.

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Opioids are important endogenous ligands that exist in both invertebrates and vertebrates and signal by activation of opioid receptors to produce analgesia and reward or pleasure. The μ-opioid receptor is the best known of the opioid receptors and mediates the acute analgesic effects of opiates, while the δ-opioid receptor (DOR) has been less well studied and has been linked to effects that follow from chronic use of opiates such as stress, inflammation and anxiety. Recently, DORs have been shown to play an essential role in emotions and increasing evidence points to a role in learning actions and outcomes. The process of learning and memory in addiction has been proposed to involve strengthening of specific brain circuits when a drug is paired with a context or environment. The DOR is highly expressed in the hippocampus, amygdala, striatum and other basal ganglia structures known to participate in learning and memory. In this review, we will focus on the role of the DOR and its potential role in learning and memory underlying the development of addiction.

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In June 2007, the Australian federal government sent military and policy into Indigenous communities in the Northern Territory on the premise that sexual abuse of children was rampant and a national crisis. This article draws on Foucault’s work on sovereignty and rights to argue that patriarchal white sovereignty as a regime of power deploys a discourse of pathology in the exercising of sovereign right to subjugate and discipline Indigenous people as good citizens.

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Considering its many potentials in the tourism industry, Iran has constantly been among the leading countries seeking development in this industry. Iran is a country with many attractions in different tourism sections including cultural, urban, and monument tourism, and ancient places as well as ecotourism, and water tourism etc. for tourists. However, Iran has never economically prospered regarding its potentials in this industry as compared to its rivals. Thus, the main objective of this work is to list the main necessities of harnessing economic power and required instruments to fulfill this goal. In addition, the tourism industry is discussed as an important strategy for reaching this power, and the Iranian wildlife is introduced as an intact environment. It is also discussed that what economic benefits are obtained through using this tourism industry. It must be noted that the main emphasis of this work is on urban, monument tourism, ancient places, and ecotourism as a case study in two Iranian provinces. Finally, the required analyses are performed considering the affinity between these two sections and two provinces. Results indicated that while Iran having the highest percent of growth compared to the two other countries active in this area, however this advantage has not significantly affected the GDP in Iran, and Iran has not been able to improve its geo-economic capacity in this area.

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In recommender systems based on multidimensional data, additional metadata provides algorithms with more information for better understanding the interaction between users and items. However, most of the profiling approaches in neighbourhood-based recommendation approaches for multidimensional data merely split or project the dimensional data and lack the consideration of latent interaction between the dimensions of the data. In this paper, we propose a novel user/item profiling approach for Collaborative Filtering (CF) item recommendation on multidimensional data. We further present incremental profiling method for updating the profiles. For item recommendation, we seek to delve into different types of relations in data to understand the interaction between users and items more fully, and propose three multidimensional CF recommendation approaches for top-N item recommendations based on the proposed user/item profiles. The proposed multidimensional CF approaches are capable of incorporating not only localized relations of user-user and/or item-item neighbourhoods but also latent interaction between all dimensions of the data. Experimental results show significant improvements in terms of recommendation accuracy.

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The monoanionic ligand 1,1,3,3 tetracyano-2 ethoxypropenide (tcnoet) is reported with its Cu(II)–bpy complex of formula [Cu2(µ-tcnoet)2(tcnoet)2(bpy)2]. The structure has been determined using X-ray diffraction and features an alternating chain with bridging tcnoet ligands. One ligand acts as a bidentate, dinucleating ligand with one short Cu–N and one medium Cu–N bond, whereas the other tcnoet is largely monodentate, albeit with a very weak interdimer Cu–N bond. Despite the arrangement in dinuclear units, further arranged into linear chains through the non-bridging tcnoet ligand, the compound shows no significant magnetic exchange, as deduced from magnetic susceptibility down to 4 K. Ligand-field, IR and EPR spectra in the solid state and in frozen solution are reported and are consistent with the overall structure.

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Semantic priming occurs when a subject is faster in recognising a target word when it is preceded by a related word compared to an unrelated word. The effect is attributed to automatic or controlled processing mechanisms elicited by short or long interstimulus intervals (ISIs) between primes and targets. We employed event-related functional magnetic resonance imaging (fMRI) to investigate blood oxygen level dependent (BOLD) responses associated with automatic semantic priming using an experimental design identical to that used in standard behavioural priming tasks. Prime-target semantic strength was manipulated by using lexical ambiguity primes (e.g., bank) and target words related to dominant or subordinate meaning of the ambiguity. Subjects made speeded lexical decisions (word/nonword) on dominant related, subordinate related, and unrelated word pairs presented randomly with a short ISI. The major finding was a pattern of reduced activity in middle temporal and inferior prefrontal regions for dominant versus unrelated and subordinate versus unrelated comparisons, respectively. These findings are consistent with both a dual process model of semantic priming and recent repetition priming data that suggest that reductions in BOLD responses represent neural priming associated with automatic semantic activation and implicate the left middle temporal cortex and inferior prefrontal cortex in more automatic aspects of semantic processing.

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Classic identity negative priming (NP) refers to the finding that when an object is ignored, subsequent naming responses to it are slower than when it has not been previously ignored (Tipper, S.P., 1985. The negative priming effect: inhibitory priming by ignored objects. Q. J. Exp. Psychol. 37A, 571-590). It is unclear whether this phenomenon arises due to the involvement of abstract semantic representations that the ignored object accesses automatically. Contemporary connectionist models propose a key role for the anterior temporal cortex in the representation of abstract semantic knowledge (e.g., McClelland, J.L., Rogers, T.T., 2003. The parallel distributed processing approach to semantic cognition. Nat. Rev. Neurosci. 4, 310-322), suggesting that this region should be involved during performance of the classic identity NP task if it involves semantic access. Using high-field (4 T) event-related functional magnetic resonance imaging, we observed increased BOLD responses in the left anterolateral temporal cortex including the temporal pole that was directly related to the magnitude of each individual's NP effect, supporting a semantic locus. Additional signal increases were observed in the supplementary eye fields (SEF) and left inferior parietal lobule (IPL).

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This chapter extends the phenomenographical research method by arguing the merits of engineering the outcome space from these investigations to effectively communicate the outcomes to an audience in technology-based discipline areas. Variations discovered from the phenomenographical study are blended with pre and post tests and a frequency distribution. Outcomes are then represented in a visual statistical manner to suit the specific target audience. This chapter provides useful insights that will be of interest to researchers wishing to present findings from qualitative research methods, and particularly the outcomes of phenomenographic investigations, to an audience in technology-based discipline areas.