970 resultados para Strength prediction
Resumo:
In order to predict compressive strength of geopolymers prepared from alumina-silica natural products, based on the effect of Al 2 O 3 /SiO 2, Na 2 O/Al 2 O 3, Na 2 O/H 2 O, and Na/[Na+K], more than 50 pieces of data were gathered from the literature. The data was utilized to train and test a multilayer artificial neural network (ANN). Therefore a multilayer feedforward network was designed with chemical compositions of alumina silicate and alkali activators as inputs and compressive strength as output. In this study, a feedforward network with various numbers of hidden layers and neurons were tested to select the optimum network architecture. The developed three-layer neural network simulator model used the feedforward back propagation architecture, demonstrated its ability in training the given input/output patterns. The cross-validation data was used to show the validity and high prediction accuracy of the network. This leads to the optimum chemical composition and the best paste can be made from activated alumina-silica natural products using alkaline hydroxide, and alkaline silicate. The research results are in agreement with mechanism of geopolymerization.
Read More: http://ascelibrary.org/doi/abs/10.1061/(ASCE)MT.1943-5533.0000829
Resumo:
The Short Term Assessment of Risk and Treatability is a structured judgement tool used to inform risk estimation for multiple adverse outcomes. In research, risk estimates outperform the tool's strength and vulnerability scales for violence prediction. Little is known about what its’component parts contribute to the assignment of risk estimates and how those estimates fare in prediction of non-violent adverse outcomes compared with the structured components. START assessment and outcomes data from a secure mental health service (N=84) was collected. Binomial and multinomial regression analyses determined the contribution of selected elements of the START structured domain and recent adverse risk events to risk estimates and outcomes prediction for violence, self-harm/suicidality, victimisation, and self-neglect. START vulnerabilities and lifetime history of violence, predicted the violence risk estimate; self-harm and victimisation estimates were predicted only by corresponding recent adverse events. Recent adverse events uniquely predicted all corresponding outcomes, with the exception of self-neglect which was predicted by the strength scale. Only for victimisation did the risk estimate outperform prediction based on the START components and recent adverse events. In the absence of recent corresponding risk behaviour, restrictions imposed on the basis of START-informed risk estimates could be unwarranted and may be unethical.
Resumo:
Background: Body composition is affected by diseases, and affects responses to medical treatments, dosage of medicines, etc., while an abnormal body composition contributes to the causation of many chronic diseases. While we have reliable biochemical tests for certain nutritional parameters of body composition, such as iron or iodine status, and we have harnessed nuclear physics to estimate the body’s content of trace elements, the very basic quantification of body fat content and muscle mass remains highly problematic. Both body fat and muscle mass are vitally important, as they have opposing influences on chronic disease, but they have seldom been estimated as part of population health surveillance. Instead, most national surveys have merely reported BMI and waist, or sometimes the waist/hip ratio; these indices are convenient but do not have any specific biological meaning. Anthropometry offers a practical and inexpensive method for muscle and fat estimation in clinical and epidemiological settings; however, its use is imperfect due to many limitations, such as a shortage of reference data, misuse of terminology, unclear assumptions, and the absence of properly validated anthropometric equations. To date, anthropometric methods are not sensitive enough to detect muscle and fat loss. Aims: The aim of this thesis is to estimate Adipose/fat and muscle mass in health disease and during weight loss through; 1. evaluating and critiquing the literature, to identify the best-published prediction equations for adipose/fat and muscle mass estimation; 2. to derive and validate adipose tissue and muscle mass prediction equations; and 3.to evaluate the prediction equations along with anthropometric indices and the best equations retrieved from the literature in health, metabolic illness and during weight loss. Methods: a Systematic review using Cochrane Review method was used for reviewing muscle mass estimation papers that used MRI as the reference method. Fat mass estimation papers were critically reviewed. Mixed ethnic, age and body mass data that underwent whole body magnetic resonance imaging to quantify adipose tissue and muscle mass (dependent variable) and anthropometry (independent variable) were used in the derivation/validation analysis. Multiple regression and Bland-Altman plot were applied to evaluate the prediction equations. To determine how well the equations identify metabolic illness, English and Scottish health surveys were studied. Statistical analysis using multiple regression and binary logistic regression were applied to assess model fit and associations. Also, populations were divided into quintiles and relative risk was analysed. Finally, the prediction equations were evaluated by applying them to a pilot study of 10 subjects who underwent whole-body MRI, anthropometric measurements and muscle strength before and after weight loss to determine how well the equations identify adipose/fat mass and muscle mass change. Results: The estimation of fat mass has serious problems. Despite advances in technology and science, prediction equations for the estimation of fat mass depend on limited historical reference data and remain dependent upon assumptions that have not yet been properly validated for different population groups. Muscle mass does not have the same conceptual problems; however, its measurement is still problematic and reference data are scarce. The derivation and validation analysis in this thesis was satisfactory, compared to prediction equations in the literature they were similar or even better. Applying the prediction equations in metabolic illness and during weight loss presented an understanding on how well the equations identify metabolic illness showing significant associations with diabetes, hypertension, HbA1c and blood pressure. And moderate to high correlations with MRI-measured adipose tissue and muscle mass before and after weight loss. Conclusion: Adipose tissue mass and to an extent muscle mass can now be estimated for many purposes as population or groups means. However, these equations must not be used for assessing fatness and categorising individuals. Further exploration in different populations and health surveys would be valuable.
Resumo:
Ionic liquids (ILs) have attracted great attention, from both industry and academia, as alternative fluids for very different types of applications. The large number of cations and anions allow a wide range of physical and chemical characteristics to be designed. However, the exhaustive measurement of all these systems is impractical, thus requiring the use of a predictive model for their study. In this work, the predictive capability of the conductor-like screening model for real solvents (COSMO-RS), a model based on unimolecular quantum chemistry calculations, was evaluated for the prediction water activity coefficient at infinite dilution, gamma(infinity)(w), in several classes of ILs. A critical evaluation of the experimental and predicted data using COSMO-RS was carried out. The global average relative deviation was found to be 27.2%, indicating that the model presents a satisfactory prediction ability to estimate gamma(infinity)(w) in a broad range of ILs. The results also showed that the basicity of the ILs anions plays an important role in their interaction with water, and it considerably determines the enthalpic behavior of the binary mixtures composed by Its and water. Concerning the cation effect, it is possible to state that generally gamma(infinity)(w) increases with the cation size, but it is shown that the cation-anion interaction strength is also important and is strongly correlated to the anion ability to interact with water. The results here reported are relevant in the understanding of ILs-water interactions and the impact of the various structural features of its on the gamma(infinity)(w) as these allow the development of guidelines for the choice of the most suitable lLs with enhanced interaction with water.
Resumo:
Abstract Objective: Evidence shows an association between muscular strength (MS) and health among youth, however low muscular strength cut-points for the detection of high metabolic risk in Latin-American populations are scarce. The aim of this study was two-fold: to explore potential age- and sex-specific thresholds of MS, for optimal cardiometabolic risk categorization among Colombian children and adolescents; and to investigate if cardiometabolic risk differed by MS group by applying the receiver operating characteristic curve (ROC) cut point. Methods: This is a secondary analysis of a cross-sectional study (the FUPRECOL study), published elsewhere. The FUPRECOL study assessments were conducted during the 2014– 2015 school year. MS was estimated by a handle dynamometer on 1,950 children and adolescents from Colombia, using the MS relative to weight (handgrip strength/body mass). A metabolic risk score was computed from the following components: waist circumference, triglycerides, HDL-c, glucose, systolic and diastolic blood pressure. ROC analysis showed a significant discriminatory accuracy of MS in identifying the low/high metabolic risk in children and adolescents and both gender. Results: In children, handgrip strength/body mass level for a low metabolic risk were 0.359 and 0.376 in girls and boys, respectively. In adolescents, these points were 0.440 and 0.447 in girls and boys, respectively. Conclusion: In conclusion, the results suggest a hypothetical MS level relative to weight for having a low metabolic risk, which could be used to identify youths at risk.
Resumo:
Aims: To compare the physical activity, sedentary activity and health-related quality of life (HRQoL) in institutionalized vs. non-institutionalized elderly, and to establish a pattern of relationship and prediction of physical and sedentary activity with physical and mental components of HRQoL. Methods: The sample consisted of 383 elderly with ≥ 75 years old (n=187 institutionalized and n=196 non-institutionalized). Were administered the International Physical Activity Questionnaire (IPAQ) and Short Form 36 Health Survey (SF-36) for evaluated the physical and sedentary activity and HRQoL. Also was used the Mini Mental State Examination (MMSE) as exclusion criteria for cognitive problems in the elderly. Results: Differences between institutionalized and non-institutionalized elderly were found in moderate-intensity activities and walking, a favour of non-institutionalized. The institutionalized elderly remain more minutes in sedentary activity. Also, were observed differences between both groups in physical component of HRQoL, a favour of non-institutionalized elderly. The mental component remained unchanged. The multivariate regression analyses showed that physical activity predicted the physical (8 to 12%) and mental (5 to 8%) components of HRQoL for institutionalized and non-institutionalized elderly. Conclusions: Non-institutionalized elderly were more physically active, spent less time in sedentary activity and showed better perception physical component of HRQoL that institutionalized elderly. An important and encouraging result of this study was that physical activity is a predictor of improved physical and mental component of HRQoL for institutionalized and non-institutionalized elderly.
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Purpose: In the present study, we consider mechanical properties of phosphate glasses under high temperatureinduced and under friction-induced cross-linking, which enhance the modulus of elasticity. Design/methodology/approach: Two nanomechanical properties are evaluated, the first parameter is the modulus of elasticity (E) (or Young's modulus) and the second parameter is the hardness (H). Zinc meta-, pyro - and orthophosphates were recognized as amorphous-colloidal nanoparticles were synthesized under laboratory conditions and showed antiwear properties in engine oil. Findings: Young's modulus of the phosphate glasses formed under high temperature was in the 60-89 GPa range. For phosphate tribofilm formed under friction hardness and the Young's modulus were in the range of 2-10 GPa and 40-215 GPa, respectively. The degree of cross-linking during friction is provided by internal pressure of about 600 MPa and temperature close to 1000°C enhancing mechanical properties by factor of 3 (see Fig 1). Research limitations/implications: The addition of iron or aluminum ions to phosphate glasses under high temperature - and friction-induced amorphization of zinc metaphosphate and pyrophosphate tends to provide more cross-linking and mechanically stronger structures. Iron and aluminum (FeO4 or AlO4 units), incorporated into phosphate structure as network formers, contribute to the anion network bonding by converting the P=O bonds into bridging oxygen. Future work should consider on development of new of materials prepared by solgel processes, eg., zinc (II)-silicic acid. Originality/value: This paper analyses the friction pressure-induced and temperature–induced the two factors lead phosphate tribofilm glasses to chemically advanced glass structures, which may enhance the wear inhibition. Adding the coordinating ions alters the pressure at which cross-linking occurs and increases the antiwear properties of the surface material significantly.