Correlation between the Bone Densities Jaws and Cervical Vertebrae through Computed Tomography with Multislice CT (Hounsfiled Scale). Osteoporosis Local or Systemic_ Crimson Publishers

 Correlation between the Bone Densities Jaws and Cervical Vertebrae through Computed Tomography with Multislice CT (Hounsfiled Scale). Osteoporosis Local or Systemic by Watanabe PCA* in Research in Medical & Engineering Sciences_ Journal of Medical Sciences

 

Abstract

In Brazil a Life expectancy at birth it’s almost 76 years old. With the increase of the average years lived by Brazilians, can we predict that in the future, gains in this indicator will not come as easily. More intervention will be necessary in the causes of death that affect the elderly, for example the osteoporosis, as well as more investments in prevention and treatment, becoming a public health concern. Osteoporosis is the most common metabolic bone disease, affecting one in two women and one in five men aged above 50 years in the world. It is a skeletal disorder characterized by compromises bone strength that predisposes individuals to an increased risk of fractures. This change is responsible for the imbalance of the mechanics of the skeleton, increased number of fractures, notably in the spine, femoral neck and distal of the radio. This can also be seen in the maxillomandibular region, most obviously in the mandible, with decreased cortical thinning and inferior mandibular body [1,2]. Dual X-ray absorptiometry (DXA) and quantitative computed tomography (QCT) have been standard examination protocols in the assessment of bone mineral densities.

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A Study on Dimocarpus longan Peel as Corrosion Inhibitor on Steel in Artificial Brine Solutions_ Crimson Publishers

A Study on Dimocarpus longan Peel as Corrosion Inhibitor on Steel in Artificial Brine Solutions by Gadang Priyotomo* in Research & Development in Material Science_ journal of materials science and technology

 

Abstract

The effect of Dimocarpus longan peel extract on the corrosion behavior of API 5L steel has been studied employing potentiodynamic polarization techniques and electrochemical impedance spectroscopy in an aqueous solution of artificial brine by injected CO2 gas. The addition of that extract decreases corrosion rate of API 5L steel, increasing corrosion inhibitor efficiency of that up to an extract concentration of 400ppm. On the basis of result, corrosion inhibitor of Dimocarpus longan peel extract is categorized as mixed inhibitor type where both the decrease of anodic and cathodic current take place with increasing the concentration of inhibitor. A shift of corrosion potential for steel is below ±85mV vs saturated standard calomel (SCE) which refers to the presence of mixed inhibitor. Furthermore, the addition Dimocarpus longan peel extract also increase charge transfer resistance which indicates the formation of film due to molecule adsorption on the metal surface.

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How Long Can an Ecological Model Predict?_ Crimson Publishers

How Long Can an Ecological Model Predict? by Maria Kuman* in Environmental Analysis & Ecology Studies_ Journal of Environmental Sciences

Abstract

Prediction of ecological phenomenon needs three components: a theoretical (or numerical) model based on the natural laws (physical, chemical, or biological), a sampling set of the reality, and a tolerance level. Comparison between the predicted and sampled values leads to the estimation of model error. In the error phase space, the prediction error is treated as a point; and the tolerance level (a prediction parameter) determines a tolerance ellipsoid. The prediction continues until the time when the error first exceeding the tolerance level (i.e., the error point first crossing the tolerance-ellipsoid). This time is called the first-passage time. Well-established theoretical framework such as the backward Fokker-Planck equation can be used to estimate the first-passage time-an up-time limit for any model prediction. A population dynamical system is used as an example to illustrate the concept and methodology and the dependence of the first-passage time on the model and prediction parameters.

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