Purpose: The purpose of this study was to identify from the International Classification of Functioning model, factors influencing quality of life in elderly persons and to describe the concrete pathway of influence and the power of each variable. Methods: The sample included 334 elders who lived in 5 districts of D Metropolitan City. A structured questionnaire was used and the collected data were analyzed for fitness, using the AMOS 18.0 program. Results: This model was concise and extensive in predicting the quality of life of elders. The research verified the factors influencing quality of life for elders as direct factors such as activity of daily living (ADL) (${\beta}$=.13, t=2.47), leisure activity (${\beta}$=.55, t=5.04), social disengagement (${\beta}$=-.25, t=-2.25), and depression (${\beta}$=-.62, t=-10.86). Indirect factors including economic status (${\gamma}$=.17, p=.009), type of residence (${\gamma}$=.19, p=.004), ADL (${\gamma}$=.12, p=.027) were important factors in predicting quality of life for elders. These variables explained 75.6% of variance in the prediction model. Conclusion: The findings indicate a need for the nursing scientific community to develop intervention programs considering these variables to improve the quality of life for elders.
Analysis and evaluation of uncertainty is adopting the advanced methodology among the methods for greenhouse gas emission assessment that was defined in GPS2000 (Good practice guideline 2000) and GPG-LULUCF (GPG Land Use, Land-Use Change and Forestry). In 2006 IPCC guideline, two approaches are suggested to explain the uncertainty for each section with a national net emission and a prediction value on uncertainty as follows; 1) Spread sheet calculation based on the error propagation algorithm that was simplified with some assumptions, and 2) Monte carlo simulation that can be utilized in general purposes. There are few researches on the agricultural field including greenhouse gas emission that is generated from livestock and cultivation lands due to lack of information for statistic data, emission coefficient, and complicated emission formula. The main objective of this study is to suggest an evaluation method for the uncertainty of greenhouse gas emission in agricultural field by means of intercomparison of the prediction value on uncertainties which were estimated by spread sheet calculation and monte carlo simulation. A statistic analysis for probability density function for uncertainty of emission rate was carried out by targeting livestock intestinal fermentation, excrements treatment, and direct/indirect emission from agricultural lands and rice cultivation. It was suggested to minimize uncertainty by means of extraction of emission coefficient according to each targeting section.
It takes quite a long time for an analyzer, such as gas chromatography, to measure a bulk property of a system, which prevents on-line measurements. Also, the cost of installation and maintenance is very high. Consequently, some other means is needed for on-line measurements of properties and the development of soft sensors based on process variables like temperature and pressure is of great interest. In the field of gas industry, the development of a soft sensor which makes indirect on-line measurements of gas compositions and flow rate, is in progress. In this paper, we proposed a hybrid inner model PLS which improved the prediction performance by taking into account the data structure, as an empirical modeling algorithm. When applied to a design of a soft sensor of a distillation tower, the hybrid inner model PLS showed better prediction performance than other methods.
At both international and national levels, such as in the Rio Declaration and the EU's Fifth Environmental Action Plan, governments have committed themselves to the adoption of the precautionary principle (UNCED 1992, CEC 1992). These commitments mean that the existence of uncertainty in appraising policies and proposals for development should be acknowledged. Uncertainty arise in both the prediction of impacts and in the evaluation of their significance, particularly of those cumulative impacts which are individually insignificant but cumulatively damaging. The EC network of EIA experts, stated at their last meeting in Athens that indirect effects and the treatment of uncertainty are one of the main deficiencies of current EIA practice. Uncertainties in decision-making arise where choices have been made in the development of the policy or proposal, such as the selection of options, the justification for that choice, and the selection of different indicators to comply with different regulatory regimes. It is also likely that a weighting system for evaluating significance will have been used which may be implicit rather than explicit. Those involved in decision-making may employ different tolerances of uncertainty than members of the public, for instance over the consideration of the worst-case scenario. Possible methods for dealing with these uncertainties include scenarios, sensitivity analysis, showing points of view, decision analysis, postponing decisions and graphical methods. An understanding of the development of cumulative environmental impacts affords not only ecologic but also socio-economic investigations. Since cumulative impacts originate mainly in centres of urban or industrial development, in particular an analysis of future growth effects that might possibly be induced by certain development impacts. Not least it is seen as an matter of sustainability to connect this issue with ecological research. The serious attempt to reduce the area of uncertainty in environmental planning is a challenge and an important step towards reliable planning and sustainable development.
Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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2010.05a
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pp.49-49
/
2010
The most commonly used numerical modelling techniques for acoustics and vibration are based on element based techniques, such as the nite element and boundary element method. Due to the huge computational eorts involved, the use of these deterministic techniques is practically restricted to low-frequency applications. For high-frequency modelling, probabilistic techniques such as SEA are well established. However, there is still a wide mid-frequency range, for which no adequate and mature prediction techniques are available. In this frequency range, the computational eorts of conventional element based techniques become prohibitively large, while the basic assumptions of the probabilistic techniques are not yet valid. In recent years, a vast amount of research has been initiated in a quest for an adequate solution for the current midfrequency problem. One family of research methods focuses on novel deterministic approaches with an enhanced convergence rate and computational eciency compared to the conventional element based methods in order to shift the practical frequency limitation towards the mid-frequency range. Amongst those techniques, a wave based prediction technique using an indirect Tretz approach is being developed at the K.U.Leuven - Noise and Vibration Research group. This paper starts with an outline of the major features of the mid-frequency modelling challenge and provides a short overview of the current research activities in response to this challenge. Next, the basic concepts of the wave based technique and its hybrid coupling with nite element schemes are described. Various validations on two- and threedimensional acoustic, elastic, poro-elastic and vibro-acoustic examples are given to illustrate the potential of the method and its benecial performance as compared to conventional element based methods. A closing part shares some views on the open issues and future research directions.
Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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2001.06a
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pp.1273-1273
/
2001
The efficiency of the luminal fermentation process influences overall efficiency of luminal production, animal health and reproduction. Ruminant production systems have a significant impact on the global environment, as well. Animal wastes contribute to pollution of the environment as ammonia volatilized to the air and nitrate leached to ground water. Microbial protein synthesis in the rumen satisfies a large proportion of the protein requirements of animals. Quantifying the microbial synthesis is possible by using markers for lumen bacteria and protozoa such as nucleic acids, purine bases, some specific amino acids, or by isotopic $^{15}N,^{32}P,\;and\;^{35}S$ labelled feeds. All those methods require cannulated animals, they are time-consuming and some methods are very expensive as well. Many attempts have been made to find an alternative method for indirect measurement of microbial synthesis in intact animals. The present investigations aimed to assess possibilities of NIRS for prediction of purine nitrogen excretion and ruminal microbial nitrogen synthesis by NIR spectra of urine. Urine samples were collected from 12 growing sheep,6 of them male, and 6- female. The sheep were included in feeding experiment. The ration consisted of sorghum silage and protein supplements -70:30 on dry matter basis. The protein supplements were chosen to differ in protein degradability. The urine samples were collected daily in a vessel containing $60m{\ell}$ 10% sulphuric acid to reduce pH below 3 and diluted with tap water to 4 liters. Samples were stored in plastic bottles and frozen at $-20^{\circ}C$ until chemical and NIRS analysis. The urine samples were analyzed for purine derivates - allantoin, uric acid, xantine and hypoxantine content. Microbial nitrogen synthesis in the lumen was calculated according to Chen and Gomes, 1995. Transmittance urine spectra with sample thickness 1mm were obtained by NIR System 6500 spectrophotometer in the spectral range 1100-2500nm. The calibration was performed using ISI software and PLS regression, respectively. The following statistical results of NIRS calibration for prediction of purine derivatives and microbial protein synthesis were obtained.(Table Omitted). The result of estimation of purine nitrogen excretion and microbial protein synthesis by NIR spectra of urine showed accuracy, adequate for rapid evaluation of microbial protein synthesis for a large number of animals and different diets. The results indicate that the advantages of the NIRS technology can be extended into animal physiological studies. The fast and low cost NIRS analyses could be used with no significant loss of accuracy when microbial protein synthesis in the lumen and the microbial protein flow in the duodenum are to be assessed by NIRS.
Background: ASF was first reported in Kenya in 1910 in 1921. In China, ASF spread to 31 provinces including Henan and Jiangsu within six months after it was first reported on August 3, 2018. The epidemic almost affected the whole China, causing direct economic losses of tens of billions of yuan. Cause great loss to our pig industry. As ELISA is cheap and easy to operate, OIE regards it as the preferred serological method for ASF detection. P54 protein has good antigenicity and is an ideal antigen for detection. Objective: To identify a conservative site in the African swine fever virus (ASFV) p54 protein and perform a Cloth-enzyme-linked immunosorbent assay (ELISA) for detecting the ASFV antibody in order to reduce risks posed by using the live virus in diagnostic assays. Method: We used bioinformatics methods to predict the antigen epitope of the ASFV p54 protein in combination with the antigenic index and artificially synthesized the predicted antigen epitope peptides. Using ASFV-positive serum and specific monoclonal antibodies (mAbs), we performed indirect ELISA and blocking ELISA to verify the immunological properties of the predicted epitope polypeptide. Results: The results of our prediction revealed that the possible antigen epitope regions were A23-29, A36-45, A72-94, A114-120, A124-130, and A137-150. The indirect ELISA showed that the peptides A23-29, A36-45, A72-94, A114-120, and A137-150 have good antigenicity. Moreover, the A36-45 polypeptide can react specifically with the mAb secreted by hybridoma cells, and its binding site contains a minimum number of essential amino acids in the sequence 37DIQFINPY44. Conclusions: Our study confirmed a conservative antigenic site in the ASFV p54 protein and its amino acid sequence. A competitive ELISA method for detecting ASFV antibodies was established based on recombinant p54 and matching mAb. Moreover, testing the protein sequence alignment verified that the method can theoretically detect antibodies produced by pigs affected by nearly all ASFVs worldwide.
Proceedings of the Korean Radioactive Waste Society Conference
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2003.11a
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pp.534-538
/
2003
Final disposal of radioactive waste generated from Nuclear Power Plant (NPP) requires the detailed knowledge of the natures and quantities of radionuclides in waste package. Many of these radionuclides are difficult to measure and expensive to assay. Thus it is suggested to the Indirect method by which the concentrations of DTM (Difficult-to-Measure) nuclide is decided using the relation of concentrations (Scaling Factor) between Key (Easy-to-Measure) nuclide and DTM nuclide with measured concentrations of Key nuclide. In general, scaling factor is determined by using of log mean average (LMA) and regression. These methods are adequate to apply most corrosion product nuclides. But in case of fission product nuclides and some corrosion product nuclides, the predicted values aren't well matched with the original values. In this study, the models using artificial neural network (ANN) for C-14 and Sr-90 are compared with those using LMA and regression. The assessment of models is executed in the two parts divided by a training part and a validation part. For all of two nuclides in the training part, the predicted values using ANN are well matched with the measured values compared with those using LMA and regression. In the validation part, the accuracy of the predicted values using ANN is better than that using LMA and is similar to or better than that using regression. It is concluded that the predicted values using ANN model are better than those using conventional model in some nuclides and ANN model can be used as the complement of LMA and regression model.
Objectives : The purpose of this study is to examine accuracy of predicted resting energy expenditure (REE), relationship fat free mass (FFM) and REE. Methods : 60 normal, obese women $(body\;mass\;index\;{\geq}25kg/m^2)$ were recruited for this study, they had low calorie diet for 8 weeks. At week 0, 4, and 8, REE was measured by MedGem (indirect calorimeter), Bioelectrical impedance analysis (BIA) using Cunningham equation, and Harris-Benedict (H-B) equation, FFM was also measured by BIA. Results : The REE predicted by BIA was lower than the REE measured by MedGem (MG) in every measurement. The REE predicted by H-B equation predicted REE was lower than that of MG in the second measurement (p<0.01). The REE measured by MedGem was declined after 8 weeks, BIA and H-B equation predicted REE were declined after 4 weeks (p<0.01). H-B equation predicted REE had more significant correlation with the REE measured by MedGem than that of BIA. There was significant correlation between measured REE and FFM, but measured REE declined after 8 weeks, FFM declined after 4 weeks (p<0.01). We derived a prediction equation as follows : REE = 108.36+31.42 (FFM), $R^2=0.23$.
PURPOSES : This study primarily focused on evaluating the performance characteristics of 4.75-mm nominal maximum aggregate size (NMAS) asphalt mixtures for their more effective implementation to a layered flexible pavement system. METHODS : The full-scale pavements in the FDOT's accelerated pavement testing (APT) program, including 4.75-mm mixtures at the top with different thicknesses and asphalt binder types, were considered for the faster and more realistic evaluation of the rutting performance. The results of superpave indirect tensile (IDT) tests and hot-mix asphalt fracture mechanics (HMA-FM) based model predictions were used for cracking performance assessments. RESULTS : The results indicated that the rutting performance of pavement structures with 4.75-mm mixtures may not be as good as to those with the typical 12.5-mm mixtures, and pavement rutting was primarily confined to the top layer of 4.75-mm mixtures. This was likely due to the relatively higher mixture instability and lower shear resistance compared to 12.5-mm mixtures. The energy ratio (ER) and HMA-FM based model performance prediction results showed a potential benefit of 4.75-mm mixtures in enhanced cracking resistance. CONCLUSIONS : In relation to their implementation, the best use of 4.75-mm mixtures seem to be as a surface course for low-traffic-volume applications. These mixtures can also be properly used as a preservation treatment that does not necessarily last as long as 12.5-mm NMAS structural mixes. It is recommended that adequate thicknesses and binder types be considered for the proper application of a 4.75-mm mixture in asphalt pavements to effectively resist both rutting and cracking.
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