17 research outputs found

    Statistical Inferences In Material Selection Of A Polymer Matrix For Natural Fiber Composites

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    In this paper, statistical inferences in material selection of polymer matrix for natural fiber composite are presented. Hypothesis testing and confidence interval were used to evaluate the suitability of the sample for use as a matrix in natural fiber reinforced composites. The screening process for material selection was carried out using a stepwise regression method. Then, the ranking process in material selection was conducted using an estimation of performance score (PS) for mechanical properties such as impact strength (IS), elongation at break (E) and tensile strength (TS). Ten types of polymer were involved in the study. The final selection revealed that polyamide (PA6), polyurethanes (PUR) and polypropylene (PP) are the potential candidates to manufacture handbrake levers according to IS, E and TS, respectively. Here, it was found that the score for Tp (thermoplastic) is better than Ts (thermoset) in terms of IS. In contrast, the Ts offered a better score result than, Tp, with respect to E and TS. The results of statistical measurements using statistical modelling prove that the data analysis can be used as a part of the decision making in material selection

    Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

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    Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat

    Variation Trend of Leaf Area Index, Yield and Yield Components of Green Beans (Phaseolous vulgaris L.) by Using Zinc Sulfate and Nitrogen

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    Proper nutrition of plant is one of the most important factors to improve both quality and quantiy of crop yields. Accordingly, the effect of different levels of zinc and nitrogen on leaf area index, yield and yield components of green beans investigated in the summer of 2012. The experiment used was a split plot in randomized complete block design with three replications in the Dezful. In this study, the main plots consisted of four nitrogen rates of urea (0, 30, 60 and 90 kgha-1), and sub plots of four levels of zinc sulfate (0, 10, 20 and 30 kg.ha-1). The results showed that application of 90 N kg.ha-1 increased leaf area index, plant dry matter, grain yield, biological yield, harvest index and protein content. Use of zinc sulfate at the rate of 20 kg.ha-1 was superior in grain yield and yield components. The highest leaf area index, grain and biological yields harvest index and protein content were achieved by application of 90 kg nitrogen and 20 kg of zinc sulfate per hectare. It seems that the use of zinc with appropriate rates, through its involvement in physiological processes and nitrogen metabolism in plants as an essential element, accelerates green beans growth processes and increases green bean yield

    Wnioskowanie statystyczne w wyborze materiału osnowy polimerowej kompozytów z włóknami naturalnymi

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    In this paper, statistical inferences in material selection of polymer matrix for natural fiber composite are presented. Hypothesis testing and confidence interval were used to evaluate the suitability of the sample for use as a matrix in natural fiber reinforced composites. The screening process for material selection was carried out using a stepwise regression method. Then, the ranking process in material selection was conducted using an estimation of performance score (PS) for mechanical properties such as impact strength (IS), elongation at break (E) and tensile strength (TS). Ten types of polymer were involved in the study. The final selection revealed that polyamide (PA6), polyurethanes (PUR) and polypropylene (PP) are the potential candidates to manufacture hand-brake levers according to IS, E and TS, respectively. Here, it was found that the score for Tp (thermoplastic) is better than Ts (thermoset) in terms of IS. In contrast, the Ts offered a better score result than, Tp, with respect to E and TS. The results of statistical measurements using statistical modelling prove that the data analysis can be used as a part of the decision making in material selection.Opisano wnioskowanie statystyczne dotyczące wyboru materiału osnowy polimerowej kompozytu z włóknami naturalnymi. Testy hipotez statystycznych i przyjęte przedziały ufności służyły do oceny próbki pod względem przydatności do zastosowania w charakterze osnowy polimerowej w kompozycie wzmocnionym włóknem naturalnym. Selekcji materiałów dokonano przy użyciu metody regresji krokowej, następnie uszeregowano wybrane materiały z wykorzystaniem rankingu oceny (PS) właściwości mechanicznych, takich jak: udarność (IS), wydłużenie przy zerwaniu (E) i wytrzymałość na rozciąganie (TS). Wyselekcjonowano wstępnie 10 rodzajów polimerów zaliczanych do grup polimerów termoplastycznych (Tp) i termoutwardzalnych (Ts). Wnioskowanie statystyczne wykazało, że poliamid (PA6), poliuretany (PUR) i polipropylen (PP) są potencjalnie korzystnymi osnowami polimerowymi do wytwarzania dźwigni hamulca ręcznego. Stwierdzono, że polimery z grupy Tp wykazują lepszą udarność niż polimery z grupy Ts. Natomiast materiały Ts charakteryzują korzystniejsze wartości wydłużenia przy zerwaniu i wytrzymałości na rozciąganie niż ich odpowiedniki z grupy Tp. Wyniki przeprowadzonej analizy danych z zastosowaniem modelowania statystycznego dowodzą, że metoda ta może być pomocna przy wyborze materiału odpowiedniego do planowanej aplikacji

    Statistical inferences in material selection of a polymer matrix for natural fibre composites

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    In this paper, statistical inferences in material selection of polymer matrix for natural fiber composite are presented. Hypothesis testing and confidence interval were used to evaluate the suitability of the sample for use as a matrix in natural fiber reinforced composites. The screening process for material selection was carried out using a stepwise regression method. Then, the ranking process in material selection was conducted using an estimation of performance score (PS) for mechanical properties such as impact strength (IS), elongation at break (E) and tensile strength (TS). Ten types of polymer were involved in the study. The final selection revealed that polyamide (PA6), polyurethanes (PUR) and polypropylene (PP) are the potential candidates to manufacture hand-brake levers according to IS, E and TS, respectively. Here, it was found that the score for Tp (thermoplastic) is better than Ts (thermoset) in terms of IS. In contrast, the Ts offered a better score result than, Tp, with respect to E and TS. The results of statistical measurements using statistical modelling prove that the data analysis can be used as a part of the decision making in material selection

    Material Selection Of A Natural Fibre Reinforced Polymer Composites Using An Analytical Approach

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    Material selection has become a critical part of design for engineers, due to availability of diverse choice of materials that have similar properties and meet the product design specification. Implementation of statistical analysis alone makes it difficult to identify the ideal composition of the final composite. An integrated approach between statistical model and micromechanical model is desired. In this paper, resultant natural fibre and polymer matrix from previous study is used to estimate the mechanical properties such as density, Young’s modulus and tensile strength. Four levels of fibre loading are used to compare the optimum natural fibre reinforced polymer composite (NFRPC). The result from this analytical approach revealed that kenaf/polystyrene (PS) with 40% fibre loading is the ideal composite in automotive component application. It was found that the ideal composite score is 1.156 g/cm3, 24.2 GPa and 413.4 MPa for density, Young’s modulus and tensile strength, respectively. A suggestion to increase the properties on Young’s modulus are also presented. This work proves that the statistical model is well incorporated with the analytical approach to choose the correct composite to use in automotive applicatio
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