207 resultados para HOMOGENEOUS COPOLYMERS


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We investigated the influence of different gas environments on the fabrication of surfaces, homogeneously covered with equally sized and spaced micro-structures. Two types of structures have been successfully micro-machined with a femtosecond laser on titanium surfaces in various atmospheres. The surface chemistry of samples machined in oxygen and helium shows TiO2, while machining in nitrogen leads to an additional share of TiN. The actual surface structure was found to vary significantly as a function of the gas environment. We found that the ablated particles and their surface triggered two consecutive events: The optical properties of the gas environment became non-isotropic which then led to the pulse intensity being redistributed throughout the cross section of the laser beam. Additionally, the effective intensity was further reduced for TiN surfaces due to TiN's high reflectivity. Thus, the settings for the applied raster-scanning machining method had to be adjusted for each gas environment to produce comparable structures. In contrast to previous studies, where only noble gases were found suitable to produce homogeneous patches, we obtained them in an oxygen environment.

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Extracellular matrix (ECM) materials are widely used in cartilage tissue engineering. However, the current ECM materials are unsatisfactory for clinical practice as most of them are derived from allogenous or xenogenous tissue. This study was designed to develop a novel autologous ECM scaffold for cartilage tissue engineering. The autologous bone marrow mesenchymal stem cell-derived ECM (aBMSC-dECM) membrane was collected and fabricated into a three-dimensional porous scaffold via cross-linking and freeze-drying techniques. Articular chondrocytes were seeded into the aBMSC-dECM scaffold and atelocollagen scaffold, respectively. An in vitro culture and an in vivo implantation in nude mice model were performed to evaluate the influence on engineered cartilage. The current results showed that the aBMSC-dECM scaffold had a good microstructure and biocompatibility. After 4 weeks in vitro culture, the engineered cartilage in the aBMSC-dECM scaffold group formed thicker cartilage tissue with more homogeneous structure and higher expressions of cartilaginous gene and protein compared with the atelocollagen scaffold group. Furthermore, the engineered cartilage based on the aBMSC-dECM scaffold showed better cartilage formation in terms of volume and homogeneity, cartilage matrix content, and compressive modulus after 3 weeks in vivo implantation. These results indicated that the aBMSC-dECM scaffold could be a successful novel candidate scaffold for cartilage tissue engineering.

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Rupture of vulnerable atheromatous plaque in the carotid and coronary arteries often leads to stroke and heart attack respectively. The mechanism of blood flow and plaque rupture in stenotic arteries is still not fully understood. A three dimensional rigid wall model was solved under steady state conditions and unsteady conditions by assuming a time-varying inlet velocity profile to investigate the relative importance of axial forces and pressure drops in arteries with asymmetric stenosis. Flow-structure interactions were investigated for the same geometry and the results were compared with those retrieved with the corresponding 2D cross-section structural models. The Navier-Stokes equations were used as the governing equations for the fluid. The tube wall was assumed hyperelastic, homogeneous, isotropic and incompressible. The analysis showed that the three dimensional behavior of velocity, pressure and wall shear stress is in general very different from that predicted by cross-section models. Pressure drop across the stenosis was found to be much higher than shear stress. Therefore, pressure may be the more important mechanical trigger for plaque rupture other than shear stress, although shear stress is closely related to plaque formation and progression.

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Ordinal qualitative data are often collected for phenotypical measurements in plant pathology and other biological sciences. Statistical methods, such as t tests or analysis of variance, are usually used to analyze ordinal data when comparing two groups or multiple groups. However, the underlying assumptions such as normality and homogeneous variances are often violated for qualitative data. To this end, we investigated an alternative methodology, rank regression, for analyzing the ordinal data. The rank-based methods are essentially based on pairwise comparisons and, therefore, can deal with qualitative data naturally. They require neither normality assumption nor data transformation. Apart from robustness against outliers and high efficiency, the rank regression can also incorporate covariate effects in the same way as the ordinary regression. By reanalyzing a data set from a wheat Fusarium crown rot study, we illustrated the use of the rank regression methodology and demonstrated that the rank regression models appear to be more appropriate and sensible for analyzing nonnormal data and data with outliers.

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Based on the non-equilibrium molecular dynamics simulations, we have studied the thermal conductivities of a novel ultra-thin one-dimensional carbon nanomaterial - diamond nanothread (DNT). Unlike single-wall carbon nanotube (CNT), the existence of the Stone-Wales transformations in DNT endows it with richer thermal transport characteristics. There is a transition from wave-dominated to particle-dominated transport region, which depends on the length of poly-benzene rings. However, independent of the transport region, strong length dependence in thermal conductivity is observed in DNTs with different lengths of poly-benzene ring. The distinctive SW characteristic in DNT provides more degrees of freedom to tune the thermal conductivity not found in the homogeneous structure of CNT. Therefore, DNT is an ideal platform to investigate various thermal transport mechanisms at the nanoscale. Its high tunability raises the potential to design DNTs for different applications, such as thermal connection and temperature management.

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The application of mesoporous silica nanospheres (MSNs) loaded with drugs/growth factors to induce osteogenic differentiation of stem cells has been trialed by a number of researchers recently. However, limitations such as high cost, complex fabrication and unintended side effects from supraphysiological concentrations of the drugs/growth factors represent major obstacles to any potential clinical application in the near term. In this study we reported an in situ one-pot synthesis strategy of MSNs doped with hypoxia-inducing copper ions and systematically evaluated the nanospheres by in vitro biological assessments. The Cu-containing mesoporous silica nanospheres (Cu-MSNs) had uniform spherical morphology (∼100 nm), ordered mesoporous channels (∼2 nm) and homogeneous Cu distribution. Cu-MSNs demonstrated sustained release of both silicon (Si) and Cu ions and controlled degradability. The Cu-MSNs were phagocytized by immune cells and appeared to modulate a favorable immune environment by initiating proper pro-inflammatory cytokines, inducing osteogenic/angiogenic factors and suppressing osteoclastogenic factors by the immune cells. The immune microenvironment induced by the Cu-MSNs led to robust osteogenic differentiation of bone mesenchymal stem cells (BMSCs) via the activation of Oncostation M (OSM) pathway. These results suggest that the novel Cu-MSNs could be used as an immunomodulatory agent with osteostimulatory capacity for bone regeneration/therapy application. Statement of significance In order to stimulate both osteogenesis and angiogenesis of stem cells for further bone regeneration, a new kind of hypoxia-inducing copper doped mesoporous silica nanospheres (Cu-MSNs) were prepared via one-pot synthesis. Biological assessments under immune environment which better reflect the in vivo response revealed that the nanospheres possessed osteostimulatory capacity and had potential as immunomodulatory agent for bone regeneration/therapy application. The strategy of introducing controllable amount of therapeutic ions instead of loading expensive drugs/growth factors in mesoporous silica nanosphere provides new options for bioactive nanomaterial functionalization.

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This article examines whether cluster analysis can be used to identify groups of Finnish residents with similar housing preferences. Because homebuilders in Finland have been providing relatively homogeneous products to an increasingly diverse population, current housing may not represent the occupiers' preferences so a segmentation approach relying on socioeconomic characteristics and expressed preferences may not be sufficient. We use data collected via questionnaire in a principal component analysis followed by a hierarchical cluster analysis to determine whether different combinations of housing attributes are important to groups of residents. We can identify four clusters of housing residents based on important characteristics when looking for a house. The clusters describe Finnish people in different phases of the life cycle and with different preferences based on their recreational activities and financial expenditures. Mass customization of housing could be used to better appeal to these different clusters of consumers who share similar preferences, increasing consumer satisfaction and improving profitability.

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Context: Identifying susceptibility genes for schizophrenia may be complicated by phenotypic heterogeneity, with some evidence suggesting that phenotypic heterogeneity reflects genetic heterogeneity. Objective: To evaluate the heritability and conduct genetic linkage analyses of empirically derived, clinically homogeneous schizophrenia subtypes. Design: Latent class and linkage analysis. Setting: Taiwanese field research centers. Participants: The latent class analysis included 1236 Han Chinese individuals with DSM-IV schizophrenia. These individuals were members of a large affected-sibling-pair sample of schizophrenia (606 ascertained families), original linkage analyses of which detected a maximum logarithm of odds (LOD) of 1.8 (z = 2.88) on chromosome 10q22.3. Main Outcome Measures: Multipoint exponential LOD scores by latent class assignment and parametric heterogeneity LOD scores. Results: Latent class analyses identified 4 classes, with 2 demonstrating familial aggregation. The first (LC2) described a group with severe negative symptoms, disorganization, and pronounced functional impairment, resembling “deficit schizophrenia.” The second (LC3) described a group with minimal functional impairment, mild or absent negative symptoms, and low disorganization. Using the negative/deficit subtype, we detected genome-wide significant linkage to 1q23-25 (LOD = 3.78, empiric genome-wide P = .01). This region was not detected using the DSM-IV schizophrenia diagnosis, but has been strongly implicated in schizophrenia pathogenesis by previous linkage and association studies.Variants in the 1q region may specifically increase risk for a negative/deficit schizophrenia subtype. Alternatively, these results may reflect increased familiality/heritability of the negative class, the presence of multiple 1q schizophrenia risk genes, or a pleiotropic 1q risk locus or loci, with stronger genotype-phenotype correlation with negative/deficit symptoms. Using the second familial latent class, we identified nominally significant linkage to the original 10q peak region. Conclusion: Genetic analyses of heritable, homogeneous phenotypes may improve the power of linkage and association studies of schizophrenia and thus have relevance to the design and analysis of genome-wide association studies.

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We included six trials with 2524 participants. Capnography reduced hypoxaemic episodes, relative risk (95% CI) 0.71 (0.56-0.91), but the quality of evidence was poor due to high risks of performance bias and detection bias and substantial statistical heterogeneity. The reduction in hypoxaemic episodes was statistically homogeneous in the subgroup of three trials of 1823 adults sedated for colonoscopy, relative risk (95% CI) 0.59 (0.48-0.73), although the risks of performance and detection biases were high. There was no evidence that capnography affected other outcomes, including assisted ventilation, relative risk (95% CI) 0.58 (0.26-1.27), p = 0.17.

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As long as population growth continues, policies for urban consolidation closer to city centres fail, and there is land available, Australians will continue to build in new Greenfield suburbs. However, the 50-year legacy of the homogeneous one-size-fits-all approach to suburbia beyond the sticks and sometimes hours away from where one can find a job, is proving unsustainable, the commute alone a significant contributor to greenhouse gas emissions across the globe. The ‘creative suburb’ was inspired by the possibility to create new, innovative and entrepreneurial suburbs, places which are more self-sufficient and self-contained than the ‘product’ perpetuated down under even today. The ‘creative suburb’ draws on significant primary research with suburban home-based creative industries workers, vernacular architecture, and town planning in the Toowoomba region, in the state of Queensland, Australia, as inspiration for a series of new building and urban designs available for innovators operating in new suburban greenfield situations in Queensland and possibly further a field. This paper considers the role ‘creative reflective practice’ played in the process of developing the building and urban designs presented in a book and showcased in a building as creative outputs of this practice-led and property development industry embedded inquiry.

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The ability to test large arrays of cell and biomaterial combinations in 3D environments is still rather limited in the context of tissue engineering and regenerative medicine. This limitation can be generally addressed by employing highly automated and reproducible methodologies. This study reports on the development of a highly versatile and upscalable method based on additive manufacturing for the fabrication of arrays of scaffolds, which are enclosed into individualized perfusion chambers. Devices containing eight scaffolds and their corresponding bioreactor chambers are simultaneously fabricated utilizing a dual extrusion additive manufacturing system. To demonstrate the versatility of the concept, the scaffolds, while enclosed into the device, are subsequently surface-coated with a biomimetic calcium phosphate layer by perfusion with simulated body fluid solution. 96 scaffolds are simultaneously seeded and cultured with human osteoblasts under highly controlled bidirectional perfusion dynamic conditions over 4 weeks. Both coated and noncoated resulting scaffolds show homogeneous cell distribution and high cell viability throughout the 4 weeks culture period and CaP-coated scaffolds result in a significantly increased cell number. The methodology developed in this work exemplifies the applicability of additive manufacturing as a tool for further automation of studies in the field of tissue engineering and regenerative medicine.

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Solving large-scale all-to-all comparison problems using distributed computing is increasingly significant for various applications. Previous efforts to implement distributed all-to-all comparison frameworks have treated the two phases of data distribution and comparison task scheduling separately. This leads to high storage demands as well as poor data locality for the comparison tasks, thus creating a need to redistribute the data at runtime. Furthermore, most previous methods have been developed for homogeneous computing environments, so their overall performance is degraded even further when they are used in heterogeneous distributed systems. To tackle these challenges, this paper presents a data-aware task scheduling approach for solving all-to-all comparison problems in heterogeneous distributed systems. The approach formulates the requirements for data distribution and comparison task scheduling simultaneously as a constrained optimization problem. Then, metaheuristic data pre-scheduling and dynamic task scheduling strategies are developed along with an algorithmic implementation to solve the problem. The approach provides perfect data locality for all comparison tasks, avoiding rearrangement of data at runtime. It achieves load balancing among heterogeneous computing nodes, thus enhancing the overall computation time. It also reduces data storage requirements across the network. The effectiveness of the approach is demonstrated through experimental studies.