381 resultados para NPS
Resumo:
Shipboard power systems have different characteristics than the utility power systems. In the Shipboard power system it is crucial that the systems and equipment work at their peak performance levels. One of the most demanding aspects for simulations of the Shipboard Power Systems is to connect the device under test to a real-time simulated dynamic equivalent and in an environment with actual hardware in the Loop (HIL). The real time simulations can be achieved by using multi-distributed modeling concept, in which the global system model is distributed over several processors through a communication link. The advantage of this approach is that it permits the gradual change from pure simulation to actual application. In order to perform system studies in such an environment physical phase variable models of different components of the shipboard power system were developed using operational parameters obtained from finite element (FE) analysis. These models were developed for two types of studies low and high frequency studies. Low frequency studies are used to examine the shipboard power systems behavior under load switching, and faults. High-frequency studies were used to predict abnormal conditions due to overvoltage, and components harmonic behavior. Different experiments were conducted to validate the developed models. The Simulation and experiment results show excellent agreement. The shipboard power systems components behavior under internal faults was investigated using FE analysis. This developed technique is very curial in the Shipboard power systems faults detection due to the lack of comprehensive fault test databases. A wavelet based methodology for feature extraction of the shipboard power systems current signals was developed for harmonic and fault diagnosis studies. This modeling methodology can be utilized to evaluate and predicate the NPS components future behavior in the design stage which will reduce the development cycles, cut overall cost, prevent failures, and test each subsystem exhaustively before integrating it into the system.
Resumo:
The advancement of nanotechnology in the synthesis and characterisation of nanoparticles (NP's) has played an important role in the development of new technologies for various applications of nano-scale materials that have unique properties. The scientific development in the last decades in the field of nanotechnology has sought ceaselessly, the discovery of new materials for the most diverse applications, such as biomedical areas, chemical, optical, mechanical and textiles. The high bactericidal efficiency of metallic nanoparticles (Au and Ag), among other metals is well known, due to its ability to act in the DNA of fungi, viruses and bacteria, interrupting the process of cellular respiration, making them important means of study, in addition to its ability to protect UVA and UVB. The present work has as its main objective the implementation of an innovative method in the impregnation of nanoparticles of gold in textile substrate, functionalized with chitosan, by a dyeing process by exhaustion, with the control of temperature, time and velocity, thus obtaining microbial characteristics and UV protection. The exhausted substrates with colloidal solutions of NPAu's presented the colours, lilac and red (soybean knits) due to their surface plasmon peak around 520-540 nm. The NPAu's were synthesized chemically, using sodium citrate as a reducing agent and stabilizer. The material was previously cationised with chitosan, a natural polyelectrolyte, with the purpose of functionalising it to enhance the adsorption of colloid, at concentrations of 5, 7, 10 and 20 % of the bonding agent on the weight of the material (OWM). It was also observed, through an experimental design 23 , with 3 central points, which was the best process of exhaustion of the substrates, using the following factors: Time (min.), temperature (OC) and concentration of the colloid (%), having as a response to variable K/S (ABSORBÂNCIA/ Kubelka-Munk) of the fibres. Furthermore, it was evidenced as the best response, the following parameters: concentration 100%, temperature 70 ºC and time 30 minutes. The substrate with NPAu was characterised by XRD; thermal analysis using TGA; microstructural study using SEM/EDS and STEM, thus showing the NP on the surface of the substrate confirming the presence of the metal. The substrates showed higher washing fastness, antibacterial properties and UV radiation protection.
Resumo:
Nanoparticles are importante for the study of new phenomena and for the development of new applications. Metallic magnetic nanoparticles like Cobalt and Nickel are important for their applications in nanoscience and nanotechnology. In this work, we report on the synthesis and characterization of Ni and Co nanoparticles. The nanoparticles were prepared by the modi- ed sol-gel method and were formed in the pore-network of the biopolymer quitosan. The reduction occurred in absence of H2 ux. The metallic particles and their monoxides have a face-centered- cubic structure. The metallic particles sizes ranged from 59 to 77 nm and from 19 to 50 nm for Ni and Co, respectively. Their monoxides chemically passivated the metallic cores, and after several weeks we have not observed further increase in oxidation. The synthesis method was tuned to obtain mainly the ferromagnetic phase. The system behaves like a core/shell structure with a ferromagnetic core and an antiferromagnetic shell. Exchange bias e ect was observed at temperatures below the Néel temperature. Both systems were submitted to an alternated magnetic eld and the heat released by the particles increased the temperature to 140°C in an interval of 5 min. Similar studies in samples dispersed in water increased the temperatures to 40-59°C, these results suggest that these materials are candidates for magnetic hyperthermia.
Resumo:
Regional/global-scale information on coastline rates of change and trends is extremely valuable, but national-scale studies are scarce. A widely accepted standardized methodology for analysing long-term coastline change has been difficult to achieve, but is essential to conduct an integrated and holistic approach to coastline evolution and hence support coastal management actions. Additionally, databases providing knowledge on coastline evolution are of key importance to support both coastal management experts and users. The main objective of this work is to present the first systematic, global and consistent long-term coastline evolution data of Portuguese mainland low-lying sandy. The methodology used quantifies coastline evolution using an unique and robust coastline indicator (the foredune toe), which is independent of short-term changes. The dataset presented comprises: 1) two polyline sets, mapping the 1958 and 2010 sandy beach-dune systems coastline, both optimized for working at 1:50 000 scale or smaller, and 2) one polyline set representing long-term change rates between 1958 and 2010, estimated at each 250 m. Results show beach erosion as the dominant trend, with a mean change rate of -0.24 ± 0.01 m/year for all mainland Portuguese beach-dune systems. Although erosion is dominant, this evolution is variable in signal and magnitude in different coastal sediment cell and also within each cell. The most relevant beach erosion issues were found in the coastal stretches of Espinho - Torreira and Costa Nova - Praia da Mira, both at sub-cell 1b; Cova Gala - Leirosa, at sub-cell 1c and Cova do Vapor - Costa da Caparica, at cell 4. Cells 1 and 4 exhibit a history of major human interventions interfering with the coastal system, many of which originated and maintained a sediment deficit. In contrast, cells 5 and 6 have been less intervened and show stable or moderate accretion behaviour.
Resumo:
Gold nanoparticles (Au NPs) with diameters ranging between 5-60 nm have been synthesised in water, and further stabilized with polyethylene glycol-based thiol polymers (mPEG-SH). Successful PEGylation of the Au NPs was confirmed by Dynamic Light scattering (DLS) and Zeta potential measurements. PEG coating of the Au NPs is the key of their colloidal stabilty, and its successful applications. Catalytic efficiency testing of the PEG-AuNPs were carried out on homocoupling of boronic acid. PEG-Au NPs with AuNps diameter < 30 nm were useful as catalyst in water. Finally, the PEG-Au NPs were also shown to be stable in biological fluid and not cytotoxic on B16.F10 cell line, making them attractive for further studies.
Resumo:
The rapid development of nanotechnology and wider applications of engineered nanomaterials (ENMs) in the last few decades have generated concerns regarding their environmental and health risks. After release into the environment, ENMs undergo aggregation, transformation, and, for metal-based nanomaterials, dissolution processes, which together determine their fate, bioavailability and toxicity to living organisms in the ecosystems. The rates of these processes are dependent on nanomaterial characteristics as well as complex environmental factors, including natural organic matter (NOM). As a ubiquitous component of aquatic systems, NOM plays a key role in the aggregation, dissolution and transformation of metal-based nanomaterials and colloids in aquatic environments.
The goal of this dissertation work is to investigate how NOM fractions with different chemical and molecular properties affect the dissolution kinetics of metal oxide ENMs, such as zinc oxide (ZnO) and copper oxide (CuO) nanoparticles (NPs), and consequently their bioavailability to aquatic vertebrate, with Gulf killifish (Fundulus grandis) embryos as model organisms.
ZnO NPs are known to dissolve at relatively fast rates, and the rate of dissolution is influenced by water chemistry, including the presence of Zn-chelating ligands. A challenge, however, remains in quantifying the dissolution of ZnO NPs, particularly for time scales that are short enough to determine rates. This dissertation assessed the application of anodic stripping voltammetry (ASV) with a hanging mercury drop electrode to directly measure the concentration of dissolved Zn in ZnO NP suspensions, without separation of the ZnO NPs from the aqueous phase. Dissolved zinc concentration measured by ASV ([Zn]ASV) was compared with that measured by inductively coupled plasma mass spectrometry (ICP-MS) after ultracentrifugation ([Zn]ICP-MS), for four types of ZnO NPs with different coatings and primary particle diameters. For small ZnO NPs (4-5 nm), [Zn]ASV was 20% higher than [Zn]ICP-MS, suggesting that these small NPs contributed to the voltammetric measurement. For larger ZnO NPs (approximately 20 nm), [Zn]ASV was (79±19)% of [Zn]ICP-MS, despite the high concentrations of ZnO NPs in suspension, suggesting that ASV can be used to accurately measure the dissolution kinetics of ZnO NPs of this primary particle size.
Using the ASV technique to directly measure dissolved zinc concentration, we examined the effects of 16 different NOM isolates on the dissolution kinetics of ZnO NPs in buffered potassium chloride solution. The observed dissolution rate constants (kobs) and dissolved zinc concentrations at equilibrium increased linearly with NOM concentration (from 0 to 40 mg-C L-1) for Suwannee River humic acid (SRHA), Suwannee River fulvic acid and Pony Lake fulvic acid. When dissolution rates were compared for the 16 NOM isolates, kobs was positively correlated with certain properties of NOM, including specific ultraviolet absorbance (SUVA), aromatic and carbonyl carbon contents, and molecular weight. Dissolution rate constants were negatively correlated to hydrogen/carbon ratio and aliphatic carbon content. The observed correlations indicate that aromatic carbon content is a key factor in determining the rate of NOM-promoted dissolution of ZnO NPs. NOM isolates with higher SUVA were also more effective at enhancing the colloidal stability of the NPs; however, the NOM-promoted dissolution was likely due to enhanced interactions between surface metal ions and NOM rather than smaller aggregate size.
Based on the above results, we designed experiments to quantitatively link the dissolution kinetics and bioavailability of CuO NPs to Gulf killifish embryos under the influence of NOM. The CuO NPs dissolved to varying degrees and at different rates in diluted 5‰ artificial seawater buffered to different pH (6.3-7.5), with or without selected NOM isolates at various concentrations (0.1-10 mg-C L-1). NOM isolates with higher SUVA and aromatic carbon content (such as SRHA) were more effective at promoting the dissolution of CuO NPs, as with ZnO NPs, especially at higher NOM concentrations. On the other hand, the presence of NOM decreased the bioavailability of dissolved Cu ions, with the uptake rate constant negatively correlated to dissolved organic carbon concentration ([DOC]) multiplied by SUVA, a combined parameter indicative of aromatic carbon concentration in the media. When the embryos were exposed to CuO NP suspension, changes in their Cu content were due to the uptake of both dissolved Cu ions and nanoparticulate CuO. The uptake rate constant of nanoparticulate CuO was also negatively correlated to [DOC]×SUVA, in a fashion roughly proportional to changes in dissolved Cu uptake rate constant. Thus, the ratio of uptake rate constants from dissolved Cu and nanoparticulate CuO (ranging from 12 to 22, on average 17±4) were insensitive to NOM type or concentration. Instead, the relative contributions of these two Cu forms were largely determined by the percentage of CuO NP that was dissolved.
Overall, this dissertation elucidated the important role that dissolved NOM plays in affecting the environmental fate and bioavailability of soluble metal-based nanomaterials. This dissertation work identified aromatic carbon content and its indicator SUVA as key NOM properties that influence the dissolution, aggregation and biouptake kinetics of metal oxide NPs and highlighted dissolution rate as a useful functional assay for assessing the relative contributions of dissolved and nanoparticulate forms to metal bioavailability. Findings of this dissertation work will be helpful for predicting the environmental risks of engineered nanomaterials.
Resumo:
X-ray computed tomography (CT) imaging constitutes one of the most widely used diagnostic tools in radiology today with nearly 85 million CT examinations performed in the U.S in 2011. CT imparts a relatively high amount of radiation dose to the patient compared to other x-ray imaging modalities and as a result of this fact, coupled with its popularity, CT is currently the single largest source of medical radiation exposure to the U.S. population. For this reason, there is a critical need to optimize CT examinations such that the dose is minimized while the quality of the CT images is not degraded. This optimization can be difficult to achieve due to the relationship between dose and image quality. All things being held equal, reducing the dose degrades image quality and can impact the diagnostic value of the CT examination.
A recent push from the medical and scientific community towards using lower doses has spawned new dose reduction technologies such as automatic exposure control (i.e., tube current modulation) and iterative reconstruction algorithms. In theory, these technologies could allow for scanning at reduced doses while maintaining the image quality of the exam at an acceptable level. Therefore, there is a scientific need to establish the dose reduction potential of these new technologies in an objective and rigorous manner. Establishing these dose reduction potentials requires precise and clinically relevant metrics of CT image quality, as well as practical and efficient methodologies to measure such metrics on real CT systems. The currently established methodologies for assessing CT image quality are not appropriate to assess modern CT scanners that have implemented those aforementioned dose reduction technologies.
Thus the purpose of this doctoral project was to develop, assess, and implement new phantoms, image quality metrics, analysis techniques, and modeling tools that are appropriate for image quality assessment of modern clinical CT systems. The project developed image quality assessment methods in the context of three distinct paradigms, (a) uniform phantoms, (b) textured phantoms, and (c) clinical images.
The work in this dissertation used the “task-based” definition of image quality. That is, image quality was broadly defined as the effectiveness by which an image can be used for its intended task. Under this definition, any assessment of image quality requires three components: (1) A well defined imaging task (e.g., detection of subtle lesions), (2) an “observer” to perform the task (e.g., a radiologists or a detection algorithm), and (3) a way to measure the observer’s performance in completing the task at hand (e.g., detection sensitivity/specificity).
First, this task-based image quality paradigm was implemented using a novel multi-sized phantom platform (with uniform background) developed specifically to assess modern CT systems (Mercury Phantom, v3.0, Duke University). A comprehensive evaluation was performed on a state-of-the-art CT system (SOMATOM Definition Force, Siemens Healthcare) in terms of noise, resolution, and detectability as a function of patient size, dose, tube energy (i.e., kVp), automatic exposure control, and reconstruction algorithm (i.e., Filtered Back-Projection– FPB vs Advanced Modeled Iterative Reconstruction– ADMIRE). A mathematical observer model (i.e., computer detection algorithm) was implemented and used as the basis of image quality comparisons. It was found that image quality increased with increasing dose and decreasing phantom size. The CT system exhibited nonlinear noise and resolution properties, especially at very low-doses, large phantom sizes, and for low-contrast objects. Objective image quality metrics generally increased with increasing dose and ADMIRE strength, and with decreasing phantom size. The ADMIRE algorithm could offer comparable image quality at reduced doses or improved image quality at the same dose (increase in detectability index by up to 163% depending on iterative strength). The use of automatic exposure control resulted in more consistent image quality with changing phantom size.
Based on those results, the dose reduction potential of ADMIRE was further assessed specifically for the task of detecting small (<=6 mm) low-contrast (<=20 HU) lesions. A new low-contrast detectability phantom (with uniform background) was designed and fabricated using a multi-material 3D printer. The phantom was imaged at multiple dose levels and images were reconstructed with FBP and ADMIRE. Human perception experiments were performed to measure the detection accuracy from FBP and ADMIRE images. It was found that ADMIRE had equivalent performance to FBP at 56% less dose.
Using the same image data as the previous study, a number of different mathematical observer models were implemented to assess which models would result in image quality metrics that best correlated with human detection performance. The models included naïve simple metrics of image quality such as contrast-to-noise ratio (CNR) and more sophisticated observer models such as the non-prewhitening matched filter observer model family and the channelized Hotelling observer model family. It was found that non-prewhitening matched filter observers and the channelized Hotelling observers both correlated strongly with human performance. Conversely, CNR was found to not correlate strongly with human performance, especially when comparing different reconstruction algorithms.
The uniform background phantoms used in the previous studies provided a good first-order approximation of image quality. However, due to their simplicity and due to the complexity of iterative reconstruction algorithms, it is possible that such phantoms are not fully adequate to assess the clinical impact of iterative algorithms because patient images obviously do not have smooth uniform backgrounds. To test this hypothesis, two textured phantoms (classified as gross texture and fine texture) and a uniform phantom of similar size were built and imaged on a SOMATOM Flash scanner (Siemens Healthcare). Images were reconstructed using FBP and a Sinogram Affirmed Iterative Reconstruction (SAFIRE). Using an image subtraction technique, quantum noise was measured in all images of each phantom. It was found that in FBP, the noise was independent of the background (textured vs uniform). However, for SAFIRE, noise increased by up to 44% in the textured phantoms compared to the uniform phantom. As a result, the noise reduction from SAFIRE was found to be up to 66% in the uniform phantom but as low as 29% in the textured phantoms. Based on this result, it clear that further investigation was needed into to understand the impact that background texture has on image quality when iterative reconstruction algorithms are used.
To further investigate this phenomenon with more realistic textures, two anthropomorphic textured phantoms were designed to mimic lung vasculature and fatty soft tissue texture. The phantoms (along with a corresponding uniform phantom) were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Scans were repeated a total of 50 times in order to get ensemble statistics of the noise. A novel method of estimating the noise power spectrum (NPS) from irregularly shaped ROIs was developed. It was found that SAFIRE images had highly locally non-stationary noise patterns with pixels near edges having higher noise than pixels in more uniform regions. Compared to FBP, SAFIRE images had 60% less noise on average in uniform regions for edge pixels, noise was between 20% higher and 40% lower. The noise texture (i.e., NPS) was also highly dependent on the background texture for SAFIRE. Therefore, it was concluded that quantum noise properties in the uniform phantoms are not representative of those in patients for iterative reconstruction algorithms and texture should be considered when assessing image quality of iterative algorithms.
The move beyond just assessing noise properties in textured phantoms towards assessing detectability, a series of new phantoms were designed specifically to measure low-contrast detectability in the presence of background texture. The textures used were optimized to match the texture in the liver regions actual patient CT images using a genetic algorithm. The so called “Clustured Lumpy Background” texture synthesis framework was used to generate the modeled texture. Three textured phantoms and a corresponding uniform phantom were fabricated with a multi-material 3D printer and imaged on the SOMATOM Flash scanner. Images were reconstructed with FBP and SAFIRE and analyzed using a multi-slice channelized Hotelling observer to measure detectability and the dose reduction potential of SAFIRE based on the uniform and textured phantoms. It was found that at the same dose, the improvement in detectability from SAFIRE (compared to FBP) was higher when measured in a uniform phantom compared to textured phantoms.
The final trajectory of this project aimed at developing methods to mathematically model lesions, as a means to help assess image quality directly from patient images. The mathematical modeling framework is first presented. The models describe a lesion’s morphology in terms of size, shape, contrast, and edge profile as an analytical equation. The models can be voxelized and inserted into patient images to create so-called “hybrid” images. These hybrid images can then be used to assess detectability or estimability with the advantage that the ground truth of the lesion morphology and location is known exactly. Based on this framework, a series of liver lesions, lung nodules, and kidney stones were modeled based on images of real lesions. The lesion models were virtually inserted into patient images to create a database of hybrid images to go along with the original database of real lesion images. ROI images from each database were assessed by radiologists in a blinded fashion to determine the realism of the hybrid images. It was found that the radiologists could not readily distinguish between real and virtual lesion images (area under the ROC curve was 0.55). This study provided evidence that the proposed mathematical lesion modeling framework could produce reasonably realistic lesion images.
Based on that result, two studies were conducted which demonstrated the utility of the lesion models. The first study used the modeling framework as a measurement tool to determine how dose and reconstruction algorithm affected the quantitative analysis of liver lesions, lung nodules, and renal stones in terms of their size, shape, attenuation, edge profile, and texture features. The same database of real lesion images used in the previous study was used for this study. That database contained images of the same patient at 2 dose levels (50% and 100%) along with 3 reconstruction algorithms from a GE 750HD CT system (GE Healthcare). The algorithms in question were FBP, Adaptive Statistical Iterative Reconstruction (ASiR), and Model-Based Iterative Reconstruction (MBIR). A total of 23 quantitative features were extracted from the lesions under each condition. It was found that both dose and reconstruction algorithm had a statistically significant effect on the feature measurements. In particular, radiation dose affected five, three, and four of the 23 features (related to lesion size, conspicuity, and pixel-value distribution) for liver lesions, lung nodules, and renal stones, respectively. MBIR significantly affected 9, 11, and 15 of the 23 features (including size, attenuation, and texture features) for liver lesions, lung nodules, and renal stones, respectively. Lesion texture was not significantly affected by radiation dose.
The second study demonstrating the utility of the lesion modeling framework focused on assessing detectability of very low-contrast liver lesions in abdominal imaging. Specifically, detectability was assessed as a function of dose and reconstruction algorithm. As part of a parallel clinical trial, images from 21 patients were collected at 6 dose levels per patient on a SOMATOM Flash scanner. Subtle liver lesion models (contrast = -15 HU) were inserted into the raw projection data from the patient scans. The projections were then reconstructed with FBP and SAFIRE (strength 5). Also, lesion-less images were reconstructed. Noise, contrast, CNR, and detectability index of an observer model (non-prewhitening matched filter) were assessed. It was found that SAFIRE reduced noise by 52%, reduced contrast by 12%, increased CNR by 87%. and increased detectability index by 65% compared to FBP. Further, a 2AFC human perception experiment was performed to assess the dose reduction potential of SAFIRE, which was found to be 22% compared to the standard of care dose.
In conclusion, this dissertation provides to the scientific community a series of new methodologies, phantoms, analysis techniques, and modeling tools that can be used to rigorously assess image quality from modern CT systems. Specifically, methods to properly evaluate iterative reconstruction have been developed and are expected to aid in the safe clinical implementation of dose reduction technologies.
Resumo:
Gold nanoparticles (Au NPs) with diameters ranging between 15 and 150 nm have been synthesised in water. 15 and 30 nm Au NPs were obtained by the Turkevich and Frens method using sodium citrate as both a reducing and stabilising agent at high temperature (Au NPs-citrate), while 60, 90 and 150 nm Au NPs were formed using hydroxylamine-o-sulfonic acid (HOS) as a reducing agent for HAuCl4 at room temperature. This new method using HOS is an extension of the approaches previously reported for producing Au NPs with mean diameters above 40 nm by direct reduction. Functionalised polyethylene glycol-based thiol polymers were used to stabilise the pre-synthesised Au NPs. The nanoparticles obtained were characterised using uv-visible spectroscopy, dynamic light scattering (DLS) and transmission electron microscopy (TEM). Further bioconjugation on 15, 30 and 90 nm PEGylated Au NPs were performed by grafting Bovine Serum Albumin, Transferrin and Apolipoprotein E (ApoE).
Resumo:
The ability to tune the structural and chemical properties of colloidal nanoparticles (NPs), make them highly advantageous for studying activity and selectivity dependent catalytic behaviour. Incorporating pre-synthesized colloidal NPs into porous supports materials remains a challenge due to poor wetting and pore permeability. In this report monodisperse, composition controlled AgPd alloy NPs were synthesised and embedded into SBA-15 using supercritical carbon dioxide and hexane. Supercritical fluid impregnation resulted in high metal loading without the requirement for surface pre-treatments. The catalytic activity, reaction profiles and recyclability of the alloy NPs embedded in SBA-15 and immobilised on non-porous SiO2 are evaluated. The NPs incorporated within the SBA-15 porous network showed significantly greater recyclability performance compared to non-porous SiO2.
Resumo:
Recent developments in tailoring the structural and chemical properties of colloidal metal nanoparticles (NPs) have led to significant enhancements in catalyst performance. Controllable colloidal synthesis has also allowed tailor-made NPs to serve as mechanistic probes for catalytic processes. The innovative use of colloidal NPs to gain fundamental insights into catalytic function will be highlighted across a variety of catalytic and electrocatalytic applications. The engineering of future heterogenous catalysts is also moving beyond size, shape and composition considerations. Advancements in understanding structure-property relationships have enabled incorporation of complex features such as tuning surface strain to influence the behavior of catalytic NPs. Exploiting plasmonic properties and altering colloidal surface chemistry through functionalization are also emerging as important areas for rational design of catalytic NPs. This news article will highlight the key developments and challenges to the future design of catalytic NPs.
Resumo:
The majority of electrode materials in batteries and related electrochemical energy storage devices are fashioned into slurries via the addition of a conductive additive and a binder. However, aggregation of smaller diameter nanoparticles in current generation electrode compositions can result in non-homogeneous active materials. Inconsistent slurry formulation may lead to inconsistent electrical conductivity throughout the material, local variations in electrochemical response, and the overall cell performance. Here we demonstrate the hydrothermal preparation of Ag nanoparticle (NP) decorated α-AgVO3 nanowires (NWs) and their conversion to tunnel structured β-AgVO3 NWs by annealing to form a uniform blend of intercalation materials that are well connected electrically. The synthesis of nanostructures with chemically bound conductive nanoparticles is an elegant means to overcome the intrinsic issues associated with electrode slurry production, as wire-to-wire conductive pathways are formed within the overall electrode active mass of NWs. The conversion from α-AgVO3 to β-AgVO3 is explained in detail through a comprehensive structural characterization. Meticulous EELS analysis of β-AgVO3 NWs offers insight into the true β-AgVO3 structure and how the annealing process facilitates a higher surface coverage of Ag NPs directly from ionic Ag content within the α-AgVO3 NWs. Variations in vanadium oxidation state across the surface of the nanowires indicate that the β-AgVO3 NWs have a core–shell oxidation state structure, and that the vanadium oxidation state under the Ag NP confirms a chemically bound NP from reduction of diffused ionic silver from the α-AgVO3 NWs core material. Electrochemical comparison of α-AgVO3 and β-AgVO3 NWs confirms that β-AgVO3 offers improved electrochemical performance. An ex situ structural characterization of β-AgVO3 NWs after the first galvanostatic discharge and charge offers new insight into the Li+ reaction mechanism for β-AgVO3. Ag+ between the van der Waals layers of the vanadium oxide is reduced during discharge and deposited as metallic Ag, the vacant sites are then occupied by Li+.
Resumo:
Planktonic foraminifera populations were studied throughout the top 25 meters of the IODP ACEX 302 Hole 4C from the central Arctic Ocean at a resolution varying from 5cm (at the top of the record) to 10cm. Planktonic foraminifera occur in high absolute abundances only in the uppermost fifty centimetres and are dominated by the taxa Neogloboquadrina pachyderma. Except for a few intermittent layers below this level,most samples are barren of calcareous microfossils.Within the topmost sediments, Neogloboquadrina pachyderma specimens present large morphological variability in the shape and number of chambers in the finalwhorl, chamber sphericity, size, and coiling direction. Five morphotypeswere identified among the sinistral (sin.) population (Nps-1 to Nps-5), including a small form (Nps-5) that is similar to a non-encrusted normal form also previously identified in the modern Arctic Ocean watermasses. Twenty five percent of the sinistral population is made up by large specimens (Nps-2, 3, 4), with a maximal mean diameter larger than 250µm. Following observations made in peri-Arctic seas (Hillaire-Marcel et al. 2004, doi:10.1016/j.quascirev.2003.08.006), we propose that occurrence of these large-sized specimens of N. pachyderma (sin.) in the central Arctic Ocean sediments could sign North Atlantic water sub-surface penetration.
Resumo:
Current treatment strategies for the treatment of brain tumor have been hindered primarily by the presence of highly lipophilic insurmountable blood-brain barrier (BBB). The purpose of current research was to investigate the efficiency of engineered biocompatible polymeric nanoparticles (NPs) as drug delivery vehicle to bypass the BBB and enhance biopharmaceutical attributes of anti-metabolite methotrexate (MTX) encapsulated NPs. The NPs were prepared by solvent diffusion method using cationic bovine serum albumin (CBA), and characterized for physicochemical parameters such as particle size, polydispersity index, and zeta-potential; while the surface modification was confirmed by FTIR, and NMR spectroscopy. Developed NPs exhibited zestful relocation of FITC tagged NPs across BBB in albino rats. Further, hemolytic studies confirmed them to be non-toxic and biocompatible as compared to free MTX. In vitro cytotoxicity assay of our engineered NPs on HNGC1 tumor cells proved superior uptake in tumor cells; and elicited potent cytotoxic effect as compared to plain NPs and free MTX solution. The outcomes of the study evidently indicate the prospective of CBA conjugated poly (D,L-lactide-co-glycolide) (PLGA) NPs loaded with MTX in brain cancer bomber with amplified capability to circumvent BBB.
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The aim of this paper is to explore the role and activities of nurse practitioners (NPs) working in long-term care (LTC) to understand concepts of access to primary care for residents. Utilizing the "FIT" framework developed by Penchanksy and Thomas, we used a directed content analysis method to analyze data from a pan-Canadian study of NPs in LTC. Individual and focus group interviews were conducted at four sites in western, central and eastern regions of Canada with 143 participants, including NPs, RNs, regulated and unregulated nursing staff, allied health professionals, physicians, administrators and directors and residents and family members. Participants emphasized how the availability and accessibility of the NP had an impact on access to primary and urgent care for residents. Understanding more about how NPs affect access in Canadian LTC will be valuable for nursing practice and healthcare planning and policy and may assist other countries in planning for the introduction of NPs in LTC settings to increase access to primary care.
Resumo:
To minimize the side effects and the multidrug resistance (MDR) arising from daunorubicin (DNR) treatment of malignant lymphoma, a chemotherapy formulation of cysteamine-modified cadmium tellurium (Cys-CdTe) quantum dots coloaded with DNR and gambogic acid (GA) nanoparticles (DNR-GA-Cys-CdTe NPs) was developed. The physical property, drug-loading efficiency and drug release behavior of these DNR-GA-Cys-CdTe NPs were evaluated, and their cytotoxicity was explored by 3-[4,5-dimethylthiazol-2-y1]-2,5-diphenyltetrazolium bromide assay. These DNR-GA-Cys-CdTe NPs possessed a pH-responsive behavior, and displayed a dose-dependent antiproliferative activity on multidrug-resistant lymphoma Raji/DNR cells. The accumulation of DNR inside the cells, revealed by flow cytometry assay, and the down-regulated expression of P-glycoprotein inside the Raji/DNR cells measured by Western blotting assay indicated that these DNR-GA-Cys-CdTe NPs could minimize the MDR of Raji/DNR cells. This multidrug delivery system would be a promising strategy for minimizing MDR against the lymphoma.