976 resultados para soil type


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Purpose To investigate longitudinal changes of subbasal nerve plexus (SNP) morphology and its relationship with conventional measures of neuropathy in individuals with diabetes. Methods A cohort of 147 individuals with type 1 diabetes and 60 age-balanced controls underwent detailed assessment of clinical and metabolic factors, neurologic deficits, quantitative sensory testing, nerve conduction studies and corneal confocal microscopy at baseline and four subsequent annual visits. The SNP parameters included corneal nerve fiber density (CNFD), branch density (CNBD) and fiber length (CNFL) and were quantified using a fully-automated algorithm. Linear mixed models were fitted to examine the changes in corneal nerve parameters over time. Results At baseline, 27% of the participants had mild diabetic neuropathy. All SNP parameters were significantly lower in the neuropathy group compared to controls (P<0.05). Overall, 89% of participants examined at baseline also completed the final visit. There was no clinically significant change to health and metabolic parameters and neuropathy measures from baseline to the final visit. Linear mixed model revealed a significant linear decline of CNFD (annual change rate, -0.9 nerve/mm2, P=0.01) in the neuropathy group compared to controls, which was associated with age (β=-0.06, P=0.04) and duration of diabetes (β=-0.08, P=0.03). In the neuropathy group, absolute changes of CNBD and CNFL showed moderate correlations with peroneal conduction velocity and cold sensation threshold, respectively (rs, 0.38 and 0.40, P<0.05). Conclusion This study demonstrates dynamic small fiber damage at the SNP, thus providing justification for our ongoing efforts to establish corneal nerve morphology as an appropriate adjunct to conventional measures of DPN.

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Improved glycemic control is the only treatment that has been shown to be effective for diabetic peripheral neuropathy in patients with type 1 diabetes (1). Continuous subcutaneous insulin infusion (CSII) is superior to multiple daily insulin injection (MDI) for reducing HbA1c and hypoglycemic events (2). Here, we have compared the benefits of CSII compared withMDI for neuropathy over 24months....

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The estimated one million Australians with type 2 diabetes face significant risks of morbidity and premature mortality. Inadequate diabetes self-management is associated with poor glycaemic control, which is further impaired by comorbid dysphoria. Regular access to ongoing self-management and psychological support is limited, especially in rural and regional locations. Web-based interventions can provide complementary support to patients’ usual care. Semi-structured interviews were undertaken with two samples that comprised (a) 13 people with type 2 diabetes and (b) 12 general practitioners (GPs). Interviews explored enablers and barriers to self-care, emotional challenges, needs for support, and potential web-based programme components. Patients were asked about the potential utility of a web-based support programme, and GPs were asked about likely circumstances of patient referral to it. Thematic analysis was used to summarise responses. Most perceived facilitators and barriers to self-management were similar across the groups. Both groups highlighted the centrality of dietary self-management, valued shared decision-making with health professionals, and endorsed the idea of web-based support. Some emotional issues commonly identified by patients varied to those perceived by GPs, resulting in different attributions for impaired self-care. A web-based programme that supported self-management and psychological/emotional needs appears likely to hold promise in yielding high acceptability and perceived utility.

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Background: The prevalence of type 2 diabetes is rising with the majority of patients practicing inadequate disease self-management. Depression, anxiety, and diabetes-specific distress present motivational challenges to adequate self-care. Health systems globally struggle to deliver routine services that are accessible to the entire population, in particular in rural areas. Web-based diabetes self-management interventions can provide frequent, accessible support regardless of time and location Objective: This paper describes the protocol of an Australian national randomized controlled trial (RCT) of the OnTrack Diabetes program, an automated, interactive, self-guided Web program aimed to improve glycemic control, diabetes self-care, and dysphoria symptoms in type 2 diabetes patients. Methods: A small pilot trial is conducted that primarily tests program functionality, efficacy, and user acceptability and satisfaction. This is followed by the main RCT, which compares 3 treatments: (1) delayed program access: usual diabetes care for 3 months postbaseline followed by access to the full OnTrack Diabetes program; (2) immediate program: full access to the self-guided program from baseline onward; and (3) immediate program plus therapist support via Functional Imagery Training (FIT). Measures are administered at baseline and at 3, 6, and 12 months postbaseline. Primary outcomes are diabetes self-care behaviors (physical activity participation, diet, medication adherence, and blood glucose monitoring), glycated hemoglobin A1c (HbA1c) level, and diabetes-specific distress. Secondary outcomes are depression, anxiety, self-efficacy and adherence, and quality of life. Exposure data in terms of program uptake, use, time on each page, and program completion, as well as implementation feasibility will be conducted. Results: This trial is currently underway with funding support from the Wesley Research Institute in Brisbane, Australia. Conclusions: This is the first known trial of an automated, self-guided, Web-based support program that uses a holistic approach in targeting both type 2 diabetes self-management and dysphoria. Findings will inform the feasibility of implementing such a program on an ongoing basis, including in rural and regional locations.

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Enlightened by the discovery of graphenes, a variety of inorganic analogues have been synthesized and characterized in recent years. Solvated Nb1-xWxS2 analogues of graphene-type sheets were prepared by lithiation and exfoliation of multistacked Nb1-xWxS2 coin roll nanowires (CRNWs), followed by in situ functionalization with gold nanoparticles to synthesize gold-loaded Nb1-xWxS2/Au nanocomposites. The Nb1-xWxS2 nanosheets and the corresponding Nb1-xWxS2/Au nanocomposites were characterized by high resolution electron microscopy (HRTEM), energy-dispersive X-ray spectroscopy (EDX), scanning transmission electron microscopy (STEM), dynamic light scattering (DLS) and scanning force microscopy (AFM). The graphene-type sheets are stable in water and other solvents and can be functionalized similarly as chalcogen-terminated surfaces (e.g. with Au nanoparticles).

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Aboveground–belowground interactions exert critical controls on the composition and function of terrestrial ecosystems, yet the fundamental relationships between plant diversity and soil microbial diversity remain elusive. Theory predicts predominantly positive associations but tests within single sites have shown variable relationships, and associations between plant and microbial diversity across broad spatial scales remain largely unexplored. We compared the diversity of plant, bacterial, archaeal and fungal communities in one hundred and forty-five 1 m2 plots across 25 temperate grassland sites from four continents. Across sites, the plant alpha diversity patterns were poorly related to those observed for any soil microbial group. However, plant beta diversity (compositional dissimilarity between sites) was significantly correlated with the beta diversity of bacterial and fungal communities, even after controlling for environmental factors. Thus, across a global range of temperate grasslands, plant diversity can predict patterns in the composition of soil microbial communities, but not patterns in alpha diversity.

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High-Order Co-Clustering (HOCC) methods have attracted high attention in recent years because of their ability to cluster multiple types of objects simultaneously using all available information. During the clustering process, HOCC methods exploit object co-occurrence information, i.e., inter-type relationships amongst different types of objects as well as object affinity information, i.e., intra-type relationships amongst the same types of objects. However, it is difficult to learn accurate intra-type relationships in the presence of noise and outliers. Existing HOCC methods consider the p nearest neighbours based on Euclidean distance for the intra-type relationships, which leads to incomplete and inaccurate intra-type relationships. In this paper, we propose a novel HOCC method that incorporates multiple subspace learning with a heterogeneous manifold ensemble to learn complete and accurate intra-type relationships. Multiple subspace learning reconstructs the similarity between any pair of objects that belong to the same subspace. The heterogeneous manifold ensemble is created based on two-types of intra-type relationships learnt using p-nearest-neighbour graph and multiple subspaces learning. Moreover, in order to make sure the robustness of clustering process, we introduce a sparse error matrix into matrix decomposition and develop a novel iterative algorithm. Empirical experiments show that the proposed method achieves improved results over the state-of-art HOCC methods for FScore and NMI.

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A new mesh adaptivity algorithm that combines a posteriori error estimation with bubble-type local mesh generation (BLMG) strategy for elliptic differential equations is proposed. The size function used in the BLMG is defined on each vertex during the adaptive process based on the obtained error estimator. In order to avoid the excessive coarsening and refining in each iterative step, two factor thresholds are introduced in the size function. The advantages of the BLMG-based adaptive finite element method, compared with other known methods, are given as follows: the refining and coarsening are obtained fluently in the same framework; the local a posteriori error estimation is easy to implement through the adjacency list of the BLMG method; at all levels of refinement, the updated triangles remain very well shaped, even if the mesh size at any particular refinement level varies by several orders of magnitude. Several numerical examples with singularities for the elliptic problems, where the explicit error estimators are used, verify the efficiency of the algorithm. The analysis for the parameters introduced in the size function shows that the algorithm has good flexibility.

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It is well understood that that there is variation inherent in all testing techniques, and that all soil and rock materials also contain some degree of natural variability. Less consideration is normally given to variation associated with natural material heterogeneity within a site, or the relative condition of the material at the time of testing. This paper assesses the impact of spatial and temporal variability upon repeated insitu testing of a residual soil and rock profile present within a single residential site over a full calendar year, and thus range of seasonal conditions. From this repeated testing, the magnitude of spatial and temporal variation due to seasonal conditions has demonstrated that, depending on the selected location and moisture content of the subsurface at the time of testing, up to a 35% variation within the test results can be expected. The results have also demonstrated that the completed insitu test technique has a similarly large measurement and inherent variability error and, for the investigated site, up to a 60% variation in normalised results was observed. From these results, it is recommended that the frequency and timing of insitu tests should be considered when deriving geotechnical design parameters from a limited data set.

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Hydrogeophysics is a growing discipline that holds significant promise to help elucidate details of dynamic processes in the near surface, built on the ability of geophysical methods to measure properties from which hydrological and geochemical variables can be derived. For example, bulk electrical conductivity is governed by, amongst others, interstitial water content, fluid salinity, and temperature, and can be measured using a range of geophysical methods. In many cases, electrical resistivity tomography (ERT) is well suited to characterize these properties in multiple dimensions and to monitor dynamic processes, such as water infiltration and solute transport. In recent years, ERT has been used increasingly for ecosystem research in a wide range of settings; in particular to characterize vegetation-driven changes in root-zone and near-surface water dynamics. This increased popularity is due to operational factors (e.g., improved equipment, low site impact), data considerations (e.g., excellent repeatability), and the fact that ERT operates at scales significantly larger than traditional point sensors. Current limitations to a more widespread use of the approach include the high equipment costs, and the need for site-specific petrophysical relationships between properties of interest. In this presentation we will discuss recent equipment advances and theoretical and methodological aspects involved in the accurate estimation of soil moisture from ERT results. Examples will be presented from two studies in a temperate climate (Michigan, USA) and one from a humid tropical location (Tapajos, Brazil).

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Electrical resistivity of soils and sediments is strongly influenced by the presence of interstitial water. Taking advantage of this dependency, electrical-resistivity imaging (ERI) can be effectively utilized to estimate subsurface soil-moisture distributions. The ability to obtain spatially extensive data combined with time-lapse measurements provides further opportunities to understand links between land use and climate processes. In natural settings, spatial and temporal changes in temperature and porewater salinity influence the relationship between soil moisture and electrical resistivity. Apart from environmental factors, technical, theoretical, and methodological ambiguities may also interfere with accurate estimation of soil moisture from ERI data. We have examined several of these complicating factors using data from a two-year study at a forest-grassland ecotone, a boundary between neighboring but different plant communities.At this site, temperature variability accounts for approximately 20-45 of resistivity changes from cold winter to warm summer months. Temporal changes in groundwater conductivity (mean=650 S/cm =57.7) and a roughly 100-S/cm spatial difference between the forest and grassland had only a minor influence on the moisture estimates. Significant seasonal fluctuations in temperature and precipitation had negligible influence on the basic measurement errors in data sets. Extracting accurate temporal changes from ERI can be hindered by nonuniqueness of the inversion process and uncertainties related to time-lapse inversion schemes. The accuracy of soil moisture obtained from ERI depends on all of these factors, in addition to empirical parameters that define the petrophysical soil-moisture/resistivity relationship. Many of the complicating factors and modifying variables to accurately quantify soil moisture changes with ERI can be accounted for using field and theoretical principles.

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One of the Department of Defense's most pressing environmental problems is the efficient detection and identification of unexploded ordnance (UXO). In regions of highly magnetic soils, magnetic and electromagnetic sensors often detect anomalies that are of geologic origin, adding significantly to remediation costs. In order to develop predictive models for magnetic susceptibility, it is crucial to understand modes of formation and the spatial distribution of different iron oxides. Most rock types contain iron and their magnetic susceptibility is determined by the amount and form of iron oxides present. When rocks weather, the amount and form of the oxides change, producing concomitant changes in magnetic susceptibility. The type of iron oxide found in the weathered rock or regolith is a function of the duration and intensity of weathering, as well as the original content of iron in the parent material. The rate of weathering is controlled by rainfall and temperature; thus knowing the climate zone, the amount of iron in the lithology and the age of the surface will help predict the amount and forms of iron oxide. We have compiled analyses of the types, amounts, and magnetic properties of iron oxides from soils over a wide climate range, from semi arid grasslands, to temperate regions, and tropical forests. We find there is a predictable range of iron oxide type and magnetic susceptibility according to the climate zone, the age of the soil and the amount of iron in the unweathered regolith.

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Magnetic properties of soils have been highlighted as a primary detrimental environmental effect on the performance of geophysical systems for detection of unexploded ordnance (UXO) and mine targets. A recent workshop at Cranfield University, U.K., aimed to identify knowledge gaps related to soil magnetism. Eight invited speakers from multidisciplinary areas provided briefings on state‐of‐the‐art research linked to soil magnetism and geophysical sensing. Contributions from other participants provided additional insights from a range of disciplines through case studies and applications. The workshop included break‐out sessions to identify current gaps in knowledge and to determine priority areas for investment in research to further developments in UXO and mine detection in magnetic soil environments. Key recommendations for future research investments have been grouped in categories including soils, theory and modeling, instrumentation, and communication.

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Introduction Research highlights patients with dual diagnoses of type 2 diabetes and acute coronary syndrome (ACS) have higher readmission rates and poorer health outcomes than patients with singular chronic conditions. Despite this, there is a lack of education programs targeted for this dual diagnosis population to improve self-management and decrease negative health outcomes. There is evidence to suggest that internet based interventions may improve health outcomes for patients with singular chronic conditions, however there is a need to develop an evidence base for ACS patients with comorbid diabetes. There is a growing awareness of the importance of a participatory model in developing effective online interventions. That is, internet interventions are more effective if end users’ perceptions of the intervention are incorporated in their final development prior to testing in large scale trials. Objectives This study investigated patients’ perspectives of the web-based intervention designed to promote self-management of the dual conditions in order to refine the intervention prior to clinical trial evaluation. Methods An interpretive approach with thematic analysis was used to obtain deeper understanding regarding participants’ experience when using web-application interventions for patients with ACS and type 2 diabetes. Semi-structured interviews were undertaken on a purposive sample of 30 patients meeting strict inclusion and exclusion criteria to obtain their perspectives on the program. Results Preliminary results indicate patients with dual diagnoses express more complex needs than those with a singular condition. Participants express a positive experience with the proposed internet intervention and emerging themes include that the web page is seen as easy to use and comforting as a support, in that patients know they are not alone. Further results will be reported as they become available. Conclusion The results indicate potential for patient acceptability of the newly developed internet intervention for patients with ACS and comorbid diabetes. Incorporation of patient perspectives into the final development of the intervention is likely to maximise successful outcomes of any future trials that utilise this intervention. Future quantitative evaluation of the effectiveness of the intervention is being planned.