122 resultados para visible spectra


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Vehicle traffic through roadwork sites creates a hazardous work environment, with speed limit noncompliance a major contributor to the high risk and high severity of roadwork crashes. This paper examines responses to an online survey to better understand the factors underlying drivers’ work zone speed choices. Drivers’ stated speed choice was compared between two photographs of the same work zone section – one with workers and machinery present and another with no visible activity. Drivers also provided comments on any aspect of roadwork safety they thought was important. A paired t-test of stated speed choice revealed that significantly lower mean speeds were nominated when workers and machinery were clearly present and active (41.7 vs 53.5 km/h, p<0.01). Participants expressed concern about roadwork signage and reduced speed limits being left in place when there was no apparent work activity. Driver perceptions, and thus compliance, may be improved through technological and operational changes.

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Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. HRV analysis is an important tool to observe the heart’s ability to respond to normal regulatory impulses that affect its rhythm. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. A computer-based arrhythmia detection system of cardiac states is very useful in diagnostics and disease management. In this work, we studied the identification of the HRV signals using features derived from HOS. These features were fed to the support vector machine (SVM) for classification. Our proposed system can classify the normal and other four classes of arrhythmia with an average accuracy of more than 85%.

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A new era of visible and sharable electricity information is emerging. Where eco-feedback is installed, households can now visualise many aspects of their energy consumption and share this information with others through Internet platforms such as social media. Despite providing users with many affordances, eco-feedback information can make public previously private actions from within the intimate setting of the family home. This paper represents a study focussing specifically on the privacy aspects of nascent ways for viewing and sharing this new stream of personal information. It explores the nuances of privacy related to eco-feedback both within and beyond the family home. While electricity consumption information may not be considered private itself, the household practices which eco-feedback systems makes visible may be private. We show that breaches of privacy can occur in unexpected ways and have the potential to cause distress. The paper concludes with some suggestions for how to realise the benefits of sharing energy consumption information whist effectively maintaining individuals’ conceptions of adequate privacy.

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Diagnosis of articular cartilage pathology in the early disease stages using current clinical diagnostic imaging modalities is challenging, particularly because there is often no visible change in the tissue surface and matrix content, such as proteoglycans (PG). In this study, we propose the use of near infrared (NIR) spectroscopy to spatially map PG content in articular cartilage. The relationship between NIR spectra and reference data (PG content) obtained from histology of normal and artificially induced PG-depleted cartilage samples was investigated using principal component (PC) and partial least squares (PLS) regression analyses. Significant correlation was obtained between both data (R2 = 91.40%, p<0.0001). The resulting correlation was used to predict PG content from spectra acquired from whole joint sample, this was then employed to spatially map this component of cartilage across the intact sample. We conclude that NIR spectroscopy is a feasible tool for evaluating cartilage contents and mapping their distribution across mammalian joint

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This study shows that there is positive regulatory effect of feedback from pupils to teachers on Assessment for Learning (AfL), classroom proactiveness, and on visible and progressive learning but not on behaviour. This research finding further articulates feedback from pupil to teacher as a paradigm shift from the classical paradigm of feedback from teacher to pupil. Here, the emphasis is geared towards pupils understanding of objectives built from previous knowledge. These are then feedback onto the teachers by the pupils in the form of discrete loops of cues and questions, where they are with their learning. This therefore enables them to move to the next level of understanding, and thus acquired independence, which in turn is reflected by their success in both formative and summative assessments. This study therefore shows that when feedback from pupil to teacher is used in combination with teacher to pupil feedback, AfL is ameliorated and hence, visible and accelerated learning occurs in a gender, nor subject non-dependent manner.

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The structural characteristics of raw coal and hydrogen peroxide (H2O2)-oxidized coals were investigated using scanning electron microscopy, X-ray diffraction (XRD), Raman spectra, and Fourier transform infrared (FT-IR) spectroscopy. The results indicate that the derivative coals oxidized by H2O2 are improved noticeably in aromaticity and show an increase first and then a decrease up to the highest aromaticity at 24 h. The stacking layer number of crystalline carbon decreases and the aspect ratio (width versus stacking height) increases with an increase in oxidation time. The content of crystalline carbon shows the same change tendency as the aromaticity measured by XRD. The hydroxyl bands of oxidized coals become much stronger due to an increase in soluble fatty acids and alcohols as a result of the oxidation of the aromatic and aliphatic C‐H bonds. In addition, the derivative coals display a decrease first and then an increase in the intensity of aliphatic C‐H bond and present a diametrically opposite tendency in the aromatic C‐H bonds with an increase in oxidation time. There is good agreement with the changes of aromaticity and crystalline carbon content as measured by XRD and Raman spectra. The particle size of oxidized coals (<200 nm in width) shows a significant decrease compared with that of raw coal (1 μm). This study reveals that the optimal oxidation time is ∼24 h for improving the aromaticity and crystalline carbon content of H2O2-oxidized coals. This process can help us obtain superfine crystalline carbon materials similar to graphite in structure.

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This project was a step forward in developing new recyclable photocatalysts for chemical reactions. These new photocatalysts can facilitate reactions by using visible light under moderate reaction conditions which is suitable for a sustainable, green and eco-friendly modern chemical industry. The outcome of the study greatly extended our understanding in metal nanoparticle photocatalysis, which reveals new photocatalytic mechanisms for the controlled transformation of chemical reactions. The prospect of sunlight irradiation driving chemical reactions may provide opportunity for the organic synthesis via a more controlled, simplified, and greener process in the future.

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Diabetic macular edema (DME) is one of the most common causes of visual loss among diabetes mellitus patients. Early detection and successive treatment may improve the visual acuity. DME is mainly graded into non-clinically significant macular edema (NCSME) and clinically significant macular edema according to the location of hard exudates in the macula region. DME can be identified by manual examination of fundus images. It is laborious and resource intensive. Hence, in this work, automated grading of DME is proposed using higher-order spectra (HOS) of Radon transform projections of the fundus images. We have used third-order cumulants and bispectrum magnitude, in this work, as features, and compared their performance. They can capture subtle changes in the fundus image. Spectral regression discriminant analysis (SRDA) reduces feature dimension, and minimum redundancy maximum relevance method is used to rank the significant SRDA components. Ranked features are fed to various supervised classifiers, viz. Naive Bayes, AdaBoost and support vector machine, to discriminate No DME, NCSME and clinically significant macular edema classes. The performance of our system is evaluated using the publicly available MESSIDOR dataset (300 images) and also verified with a local dataset (300 images). Our results show that HOS cumulants and bispectrum magnitude obtained an average accuracy of 95.56 and 94.39 % for MESSIDOR dataset and 95.93 and 93.33 % for local dataset, respectively.

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Iron species are one of the least toxic and least expensive substances that are photocatalytic in the visible region of the spectrum. Therefore, this article focuses on iron-based photocatalysts sensitive to visible light. Photo-Fenton reactions are considered with respect to those assisted by and involve the in situ production of H2O2. The possible role that photoactive iron species play by interacting with natural organic matter in water purification in the natural environment is considered. The review also considered photosensitization by phthalocyanines and the potential role that layered double hydroxides may have not only as catalyst supports but also as photosensitizers themselves. Finally, photocatalytic disinfection of water is discussed, and the desirability of standardized metrics and experimental conditions to assist in the comparative evaluation of photocatalysts is highlighted.

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A rapid and catalyst-free cycloaddition system for visible-light-induced click chemistry is reported. A readily accessible photoreactive 2H-azirine moiety was designed to absorb light at wavelengths above 400 nm. Irradiation with low-energy light sources thus enables efficient small-molecule synthesis with a diverse range of multiple-bond-containing compounds. Moreover, in order to demonstrate the efficiency of the current approach, quantitative ligation of the photoactivatable chromophore with functional polymeric substrates was performed and full conversion with irradiation times of only 1 min at ambient conditions was achieved. The current report thus presents a highly efficient method for applications involving selective cycloaddition to electron-deficient multiple-bond-containing materials.

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Palladium (Pd)-catalyzed cross-coupling reactions are among the most important methods in organic synthesis. We report the discovery of highly efficient and green photocatalytic processes by which cross-coupling reactions, including Sonogashira, Stille, Hiyama, Ullmann, and Buchwald–Hartwig reactions, can be driven with visible light at temperatures slightly above room temperature using alloy nanoparticles of gold and Pd on zirconium oxide, thus achieving high yields. The alloy nanoparticles absorb visible light, and their conduction electrons gain energy, which is available at the surface Pd sites. Results of the density functional theory calculations indicate that transfer of the light excited electrons from the nanoparticle surface to the reactant molecules adsorbed on the nanoparticle surface activates the reactants. When the light intensity was increased, a higher reaction rate was observed, because of the increased population of photoexcited electrons. The irradiation wavelength also has an important impact on the reaction rates. Ultraviolet irradiation can drive some reactions with the chlorobenzene substrate, while visible light irradiation failed to, and substantially improve the yields of the reactions with the bromobenzene substrate. The discovery reveals the possibility of using low-energy and -density sources such as sunlight to drive chemical transformations.