877 resultados para next generation matrix


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Fe–Cr based alloys are the leading structural material candidates in the design of next generation reactors due to their high resistance to swelling and corrosion. Despite these good properties there are others, such as embrittlement, which require a higher level of understanding in order to improve aspects such as safety or lifetime of the reactors. The addition of Cr improves the behavior of the steels under irradiation, but not in a monotonic way. Therefore, understanding the changes in the Fe–Cr based alloys microstructure induced by irradiation and the role played by the alloying element (Cr) is needed in order to predict the response of these materials under the extreme conditions they are going to support. In this work we perform a study of the effect of Cr concentration in a bcc Fe–Cr matrix on formation and binding energies of vacancy clusters up to 5 units. The dependence of the calculated formation and binding energy is investigated with two empirical interatomic potentials specially developed to study radiation damage in Fe–Cr alloys. Results are very similar for both potentials showing an increase of the defect stability with the cluster size and no real dependence on Cr concentration for the binding energy.

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Buffered crossbar switches have recently attracted considerable attention as the next generation of high speed interconnects. They are a special type of crossbar switches with an exclusive buffer at each crosspoint of the crossbar. They demonstrate unique advantages over traditional unbuffered crossbar switches, such as high throughput, low latency, and asynchronous packet scheduling. However, since crosspoint buffers are expensive on-chip memories, it is desired that each crosspoint has only a small buffer. This dissertation proposes a series of practical algorithms and techniques for efficient packet scheduling for buffered crossbar switches. To reduce the hardware cost of such switches and make them scalable, we considered partially buffered crossbars, whose crosspoint buffers can be of an arbitrarily small size. Firstly, we introduced a hybrid scheme called Packet-mode Asynchronous Scheduling Algorithm (PASA) to schedule best effort traffic. PASA combines the features of both distributed and centralized scheduling algorithms and can directly handle variable length packets without Segmentation And Reassembly (SAR). We showed by theoretical analysis that it achieves 100% throughput for any admissible traffic in a crossbar with a speedup of two. Moreover, outputs in PASA have a large probability to avoid the more time-consuming centralized scheduling process, and thus make fast scheduling decisions. Secondly, we proposed the Fair Asynchronous Segment Scheduling (FASS) algorithm to handle guaranteed performance traffic with explicit flow rates. FASS reduces the crosspoint buffer size by dividing packets into shorter segments before transmission. It also provides tight constant performance guarantees by emulating the ideal Generalized Processor Sharing (GPS) model. Furthermore, FASS requires no speedup for the crossbar, lowering the hardware cost and improving the switch capacity. Thirdly, we presented a bandwidth allocation scheme called Queue Length Proportional (QLP) to apply FASS to best effort traffic. QLP dynamically obtains a feasible bandwidth allocation matrix based on the queue length information, and thus assists the crossbar switch to be more work-conserving. The feasibility and stability of QLP were proved, no matter whether the traffic distribution is uniform or non-uniform. Hence, based on bandwidth allocation of QLP, FASS can also achieve 100% throughput for best effort traffic in a crossbar without speedup.

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Burn injuries in the United States account for over one million hospital admissions per year, with treatment estimated at four billion dollars. Of severe burn patients, 30-90% will develop hypertrophic scars (HSc). Current burn therapies rely upon the use of bioengineered skin equivalents (BSEs), which assist in wound healing but do not prevent HSc. HSc contraction occurs of 6-18 months and results in the formation of a fixed, inelastic skin deformity, with 60% of cases occurring across a joint. HSc contraction is characterized by abnormally high presence of contractile myofibroblasts which normally apoptose at the completion of the proliferative phase of wound healing. Additionally, clinical observation suggests that the likelihood of HSc is increased in injuries with a prolonged immune response. Given the pathogenesis of HSc, we hypothesize that BSEs should be designed with two key anti-scarring characterizes: (1) 3D architecture and surface chemistry to mitigate the inflammatory microenvironment and decrease myofibroblast transition; and (2) using materials which persist in the wound bed throughout the remodeling phase of repair. We employed electrospinning and 3D printing to generate scaffolds with well-controlled degradation rate, surface coatings, and 3D architecture to explore our hypothesis through four aims.

In the first aim, we evaluate the impact of elastomeric, randomly-oriented biostable polyurethane (PU) scaffold on HSc-related outcomes. In unwounded skin, native collagen is arranged randomly, elastin fibers are abundant, and myofibroblasts are absent. Conversely, in scar contractures, collagen is arranged in linear arrays and elastin fibers are few, while myofibroblast density is high. Randomly oriented collagen fibers native to the uninjured dermis encourage random cell alignment through contact guidance and do not transmit as much force as aligned collagen fibers. However, the linear ECM serves as a system for mechanotransduction between cells in a feed-forward mechanism, which perpetuates ECM remodeling and myofibroblast contraction. The electrospinning process allowed us to create scaffolds with randomly-oriented fibers that promote random collagen deposition and decrease myofibroblast formation. Compared to an in vitro HSc contraction model, fibroblast-seeded PU scaffolds significantly decreased matrix and myofibroblast formation. In a murine HSc model, collagen coated PU (ccPU) scaffolds significantly reduced HSc contraction as compared to untreated control wounds and wounds treated with the clinical standard of care. The data from this study suggest that electrospun ccPU scaffolds meet the requirements to mitigate HSc contraction including: reduction of in vitro HSc related outcomes, diminished scar stiffness, and reduced scar contraction. While clinical dogma suggests treating severe burn patients with rapidly biodegrading skin equivalents, these data suggest that a more long-term scaffold may possess merit in reducing HSc.

In the second aim, we further investigate the impact of scaffold longevity on HSc contraction by studying a degradable, elastomeric, randomly oriented, electrospun micro-fibrous scaffold fabricated from the copolymer poly(l-lactide-co-ε-caprolactone) (PLCL). PLCL scaffolds displayed appropriate elastomeric and tensile characteristics for implantation beneath a human skin graft. In vitro analysis using normal human dermal fibroblasts (NHDF) demonstrated that PLCL scaffolds decreased myofibroblast formation as compared to an in vitro HSc contraction model. Using our murine HSc contraction model, we found that HSc contraction was significantly greater in animals treated with standard of care, Integra, as compared to those treated with collagen coated-PLCL (ccPLCL) scaffolds at d 56 following implantation. Finally, wounds treated with ccPLCL were significantly less stiff than control wounds at d 56 in vivo. Together, these data further solidify our hypothesis that scaffolds which persist throughout the remodeling phase of repair represent a clinically translatable method to prevent HSc contraction.

In the third aim, we attempt to optimize cell-scaffold interactions by employing an anti-inflammatory coating on electrospun PLCL scaffolds. The anti-inflammatory sub-epidermal glycosaminoglycan, hyaluronic acid (HA) was used as a coating material for PLCL scaffolds to encourage a regenerative healing phenotype. To minimize local inflammation, an anti-TNFα monoclonal antibody (mAB) was conjugated to the HA backbone prior to PLCL coating. ELISA analysis confirmed mAB activity following conjugation to HA (HA+mAB), and following adsorption of HA+mAB to the PLCL backbone [(HA+mAB)PLCL]. Alican blue staining demonstrated thorough HA coating of PLCL scaffolds using pressure-driven adsorption. In vitro studies demonstrated that treatment with (HA+mAB)PLCL prevented downstream inflammatory events in mouse macrophages treated with soluble TNFα. In vivo studies using our murine HSc contraction model suggested positive impact of HA coating, which was partiall impeded by the inclusion of the TNFα mAB. Further characterization of the inflammatory microenvironment of our murine model is required prior to conclusions regarding the potential for anti-TNFα therapeutics for HSc. Together, our data demonstrate the development of a complex anti-inflammatory coating for PLCL scaffolds, and the potential impact of altering the ECM coating material on HSc contraction.

In the fourth aim, we investigate how scaffold design, specifically pore dimensions, can influence myofibroblast interactions and subsequent formation of OB-cadherin positive adherens junctions in vitro. We collaborated with Wake Forest University to produce 3D printed (3DP) scaffolds with well-controlled pore sizes we hypothesized that decreasing pore size would mitigate intra-cellular communication via OB-cadherin-positive adherens junctions. PU was 3D printed via pressure extrusion in basket-weave design with feature diameter of ~70 µm and pore sizes of 50, 100, or 150 µm. Tensile elastic moduli of 3DP scaffolds were similar to Integra; however, flexural moduli of 3DP were significantly greater than Integra. 3DP scaffolds demonstrated ~50% porosity. 24 h and 5 d western blot data demonstrated significant increases in OB-cadherin expression in 100 µm pores relative to 50 µm pores, suggesting that pore size may play a role in regulating cell-cell communication. To analyze the impact of pore size in these scaffolds on scarring in vivo, scaffolds were implanted beneath skin graft in a murine HSc model. While flexural stiffness resulted in graft necrosis by d 14, cellular and blood vessel integration into scaffolds was evident, suggesting potential for this design if employed in a less stiff material. In this study, we demonstrate for the first time that pore size alone impacts OB-cadherin protein expression in vitro, suggesting that pore size may play a role on adherens junction formation affiliated with the fibroblast-to-myofibroblast transition. Overall, this work introduces a new bioengineered scaffold design to both study the mechanism behind HSc and prevent the clinical burden of this contractile disease.

Together, these studies inform the field of critical design parameters in scaffold design for the prevention of HSc contraction. We propose that scaffold 3D architectural design, surface chemistry, and longevity can be employed as key design parameters during the development of next generation, low-cost scaffolds to mitigate post-burn hypertrophic scar contraction. The lessening of post-burn scarring and scar contraction would improve clinical practice by reducing medical expenditures, increasing patient survival, and dramatically improving quality of life for millions of patients worldwide.

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Lung cancer diagnostics have progressed greatly in the previous decade. Development of molecular testing to identify an increasing number of potentially clinically actionable genetic variants, using smaller samples obtained via minimally invasive techniques, is a huge challenge. Tumour heterogeneity and cancer evolution in response to therapy means that repeat biopsies or circulating biomarkers are likely to be increasingly useful to adapt treatment as resistance develops. We highlight some of the current challenges faced in clinical practice for molecular testing of EGFR, ALK, and new biomarkers such as PDL1. Implementation of next generation sequencing platforms for molecular diagnostics in non-small-cell lung cancer is increasingly common, allowing testing of multiple genetic variants from a single sample. The use of next generation sequencing to recruit for molecularly stratified clinical trials is discussed in the context of the UK Stratified Medicine Programme and The UK National Lung Matrix Trial.

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International audience

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Magnesium (Mg) battery is considered as a promising candidate for the next generation battery technology that could potentially replace the current lithium (Li)-ion batteries due to the following factors. Magnesium possesses a higher volumetric capacity than commercialized Li-ion battery anode materials. Additionally, the low cost and high abundance of Mg compared to Li makes Mg batteries even more attractive. Moreover, unlike metallic Li anodes which have a tendency to develop a dendritic structure on the surface upon the cycling of the battery, Mg metal is known to be free from such a hazardous phenomenon. Due to these merits of Mg as an anode, the topic of rechargea¬ble Mg batteries has attracted considerable attention among researchers in the last few decades. However, the aforementioned advantages of Mg batteries have not been fully utilized due to the serious kinetic limitation of Mg2+ diffusion process in many hosting compounds which is believed to be due to a strong electrostatic interaction between divalent Mg2+ ions and hosting matrix. This serious kinetic hindrance is directly related to the lack of cathode materials for Mg battery that provide comparable electrochemical performances to that of Li-based system. Manganese oxide (MnO2) is one of the most well studied electrode materials due to its excellent electrochemical properties, including high Li+ ion capacity and relatively high operating voltage (i.e., ~ 4 V vs. Li/Li+ for LiMn2O4 and ~ 3.2 V vs. Mg/Mg2+). However, unlike the good electrochemical properties of MnO2 realized in Li-based systems, rather poor electrochemical performances have been reported in Mg based systems, particularly with low capacity and poor cycling performances. While the origin of the observed poor performances is believed to be due to the aforementioned strong ionic interaction between the Mg2+ ions and MnO2 lattice resulting in a limited diffusion of Mg2+ ions in MnO2, very little has been explored regarding the charge storage mechanism of MnO2 with divalent Mg2+ ions. This dissertation investigates the charge storage mechanism of MnO2, focusing on the insertion behaviors of divalent Mg2+ ions and exploring the origins of the limited Mg2+ insertion behavior in MnO2. It is found that the limited Mg2+ capacity in MnO2 can be significantly improved by introducing water molecules in the Mg electrolyte system, where the water molecules effectively mitigated the kinetic hindrance of Mg2+ insertion process. The combination of nanostructured MnO2 electrode and water effect provides a synergic effect demonstrating further enhanced Mg2+ insertion capability. Furthermore, it is demonstrated in this study that pre-cycling MnO2 electrodes in water-containing electrolyte activates MnO2 electrode, after which improved Mg2+ capacity is maintained in dry Mg electrolyte. Based on a series of XPS analysis, a conversion mechanism is proposed where magnesiated MnO2 undergoes a conversion reaction to Mg(OH)2 and MnOx and Mn(OH)y species in the presence of water molecules. This conversion process is believed to be the driving force that generates the improved Mg2+ capacity in MnO2 along with the water molecule’s charge screening effect. Finally, it is discussed that upon a consecutive cycling of MnO2 in the water-containing Mg electrolyte, structural water is generated within the MnO2 lattice, which is thought to be the origin of the observed activation phenomenon. The results provided in this dissertation highlight that the divalency of Mg2+ ions result in very different electrochemical behaviors than those of the well-studied monovalent Li+ ions towards MnO2.

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Over the last decade, graphene and related materials (GRM) have drawn significant interest and resources for their development into the next generation of composite materials. This is because these nanoparticles have the ability to operate as reinforcing additives capable of imparting considerable mechanical property increases while also embedding multi-functional advantages on the host matrix. Because graphene and 2D materials are still in their early stages, the relative maturity of different types of composite systems varies. As a result, certain nanocomposite systems are currently commercially accessible, while others are not yet sufficiently developed to enter the market. A substantial emphasis has been placed on developing thermoplastic and thermosetting materials that combine a variety of mechanical and functional qualities. These include higher strength and stiffness, increased thermal and electrical conductivity, improved barrier properties, fire retardancy, and others, with the ultimate goal of providing multifunctionality to already employed composites. The work presented in this thesis investigates the use and benefits that GRM could bring to composites for a variety of applications, with the goal of realizing multifunctional components with improved properties that leads to lightweight and, as a result, energy and cost savings and pollution reduction in the environment. In particular, we worked on the following topics: • Benchmarking of commercial GRM-based master batches; • GRM-coatings for water uptake reduction; • GRM as thermo-electrical anti-icing /de-icing system; • GRM for Out of Oven curing of composites.

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As a consequence of the diffusion of next generation sequencing techniques, metagenomics databases have become one of the most promising repositories of information about features and behavior of microorganisms. One of the subjects that can be studied from those data are bacteria populations. Next generation sequencing techniques allow to study the bacteria population within an environment by sampling genetic material directly from it, without the needing of culturing a similar population in vitro and observing its behavior. As a drawback, it is quite complex to extract information from those data and usually there is more than one way to do that; AMR is no exception. In this study we will discuss how the quantified AMR, which regards the genotype of the bacteria, can be related to the bacteria phenotype and its actual level of resistance against the specific substance. In order to have a quantitative information about bacteria genotype, we will evaluate the resistome from the read libraries, aligning them against CARD database. With those data, we will test various machine learning algorithms for predicting the bacteria phenotype. The samples that we exploit should resemble those that could be obtained from a natural context, but are actually produced by a read libraries simulation tool. In this way we are able to design the populations with bacteria of known genotype, so that we can relay on a secure ground truth for training and testing our algorithms.

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This article aimed at comparing the accuracy of linear measurement tools of different commercial software packages. Eight fully edentulous dry mandibles were selected for this study. Incisor, canine, premolar, first molar and second molar regions were selected. Cone beam computed tomography (CBCT) images were obtained with i-CAT Next Generation. Linear bone measurements were performed by one observer on the cross-sectional images using three different software packages: XoranCat®, OnDemand3D® and KDIS3D®, all able to assess DICOM images. In addition, 25% of the sample was reevaluated for the purpose of reproducibility. The mandibles were sectioned to obtain the gold standard for each region. Intraclass coefficients (ICC) were calculated to examine the agreement between the two periods of evaluation; the one-way analysis of variance performed with the post-hoc Dunnett test was used to compare each of the software-derived measurements with the gold standard. The ICC values were excellent for all software packages. The least difference between the software-derived measurements and the gold standard was obtained with the OnDemand3D and KDIS3D (-0.11 and -0.14 mm, respectively), and the greatest, with the XoranCAT (+0.25 mm). However, there was no statistical significant difference between the measurements obtained with the different software packages and the gold standard (p> 0.05). In conclusion, linear bone measurements were not influenced by the software package used to reconstruct the image from CBCT DICOM data.

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Background: Alternative splicing (AS) is a central mechanism in the generation of genomic complexity and is a major contributor to transcriptome and proteome diversity. Alterations of the splicing process can lead to deregulation of crucial cellular processes and have been associated with a large spectrum of human diseases. Cancer-associated transcripts are potential molecular markers and may contribute to the development of more accurate diagnostic and prognostic methods and also serve as therapeutic targets. Alternative splicing-enriched cDNA libraries have been used to explore the variability generated by alternative splicing. In this study, by combining the use of trapping heteroduplexes and RNA amplification, we developed a powerful approach that enables transcriptome-wide exploration of the AS repertoire for identifying AS variants associated with breast tumor cells modulated by ERBB2 (HER-2/neu) oncogene expression. Results: The human breast cell line (C5.2) and a pool of 5 ERBB2 over-expressing breast tumor samples were used independently for the construction of two AS-enriched libraries. In total, 2,048 partial cDNA sequences were obtained, revealing 214 alternative splicing sequence-enriched tags (ASSETs). A subset with 79 multiple exon ASSETs was compared to public databases and reported 138 different AS events. A high success rate of RT-PCR validation (94.5%) was obtained, and 2 novel AS events were identified. The influence of ERBB2-mediated expression on AS regulation was evaluated by capillary electrophoresis and probe-ligation approaches in two mammary cell lines (Hb4a and C5.2) expressing different levels of ERBB2. The relative expression balance between AS variants from 3 genes was differentially modulated by ERBB2 in this model system. Conclusions: In this study, we presented a method for exploring AS from any RNA source in a transcriptome-wide format, which can be directly easily adapted to next generation sequencers. We identified AS transcripts that were differently modulated by ERBB2-mediated expression and that can be tested as molecular markers for breast cancer. Such a methodology will be useful for completely deciphering the cancer cell transcriptome diversity resulting from AS and for finding more precise molecular markers.

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Insect societies are well known for their high degree of cooperation, but their colonies can potentially be exploited by reproductive workers who lay unfertilized, male eggs, rather than work for the good of the colony. Recently, it has also been discovered that workers in bumblebees and Asian honeybees can succeed in entering and parasitizing unrelated colonies to produce their own male offspring. The aim of this study was to investigate whether such intraspecific worker parasitism might also occur in stingless bees, another group of highly social bees. Based on a large-scale genetic study of the species Melipona scutellaris, and the genotyping of nearly 600 males from 45 colonies, we show that similar to 20% of all males are workers` sons, but that around 80% of these had genotypes that were incompatible with them being the sons of workers of the resident queen. By tracking colonies over multiple generations, we show that these males were not produced by drifted workers, but rather by workers that were the offspring of a previous, superseded queen. This means that uniquely, workers reproductively parasitize the next-generation workforce. Our results are surprising given that most colonies were sampled many months after the previous queen had died and that workers normally only have a life expectancy of similar to 30 days. It also implies that reproductive workers greatly outlive all other workers. We explain our results in the context of kin selection theory, and the fact that it pays workers more from exploiting the colony if costs are carried by less related individuals.

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This paper presents a free software tool that supports the next-generation Mobile Communications, through the automatic generation of models of components and electronic devices based on neural networks. This tool enables the creation, training, validation and simulation of the model directly from measurements made on devices of interest, using an interface totally oriented to non-experts in neural models. The resulting model can be exported automatically to a traditional circuit simulator to test different scenarios.

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The TCP/IP architecture was consolidated as a standard to the distributed systems. However, there are several researches and discussions about alternatives to the evolution of this architecture and, in this study area, this work presents the Title Model to contribute with the application needs support by the cross layer ontology use and the horizontal addressing, in a next generation Internet. For a practical viewpoint, is showed the network cost reduction for the distributed programming example, in networks with layer 2 connectivity. To prove the title model enhancement, it is presented the network analysis performed for the message passing interface, sending a vector of integers and returning its sum. By this analysis, it is confirmed that the current proposal allows, in this environment, a reduction of 15,23% over the total network traffic, in bytes.

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Urbanization and the ability to manage for a sustainable future present numerous challenges for geographers and planners in metropolitan regions. Remotely sensed data are inherently suited to provide information on urban land cover characteristics, and their change over time, at various spatial and temporal scales. Data models for establishing the range of urban land cover types and their biophysical composition (vegetation, soil, and impervious surfaces) are integrated to provide a hierarchical approach to classifying land cover within urban environments. These data also provide an essential component for current simulation models of urban growth patterns, as both calibration and validation data. The first stages of the approach have been applied to examine urban growth between 1988 and 1995 for a rapidly developing area in southeast Queensland, Australia. Landsat Thematic Mapper image data provided accurate (83% adjusted overall accuracy) classification of broad land cover types and their change over time. The combination of commonly available remotely sensed data, image processing methods, and emerging urban growth models highlights an important application for current and next generation moderate spatial resolution image data in studies of urban environments.