The Portrayal of Indonesian Image in 2007 Kompas Selected Short Stories: Social Problems, Criticisms and Hopes

Article aimed at exploring social problems reflected in 15 selected short stories printed in Kompas during 2007 both explicitly and implicitly. Specifically, this research is focused on the mapping of dominant social problems raised by the short stories, the social criticisms strongly voiced by the authors and the hopes of a better situation implicitly reflected in these interesting short stories. This study applies the Defamiliarization Effect promoted by Bertolt Brecht and Negative Dialectics or Negative Knowledge by Theodor Adorno, specifically in analyzing the literary works as a criticism tool. The result of the research shows that phenomena of social problems current lately in Indonesian context like identity, poverty, corruption, religious tensions, moral degradation, politics dirtiness, minority group problems, social security, natural disasters and the like are clearly seen and teased in these writings

DataSheet1_Potential causal associations of PM2.5 and osteoporosis: a two-sample mendelian randomization study.docx

Background: Observational studies suggest a potential association between atmospheric particulate matter 2.5 (PM2.5) and osteoporosis, but a causal association is unclear due to the presence of confounding factors.Methods: We utilized bone mineral density indices at four specific sites to represent osteoporosis: femoral neck (FN-BMD), lumbar spine (LS-BMD), forearm (FA-BMD), and heel (HE-BMD). The PM2.5 data was obtained from the UK Biobank database, while the datasets for FN-BMD, LS-BMD, and FA-BMD were obtained from the GEFOS database, and the dataset for HE-BMD was obtained from the EBI database. A two-sample Mendelian randomization analysis was conducted using mainly the inverse variance weighted method, horizontal pleiotropy and heterogeneity were also assessed.Results: The results indicated that PM2.5 was not correlated with a decrease in FN-BMD (β: −0.305, 95%CI: −0.762, 0.153), LS-BMD (β: 0.134, 95%CI: −0.396, 0.666), FA-BMD (β: -0.056, 95%CI: −1.172,1.060), and HE-BMD (β: −0.084, 95%CI: −0.261,0.093). Additionally, acceptable levels of horizontal pleiotropy and heterogeneity were observed.Conclusion: In contrast to most observational studies, our research did not discover a potential causal relationship between PM2.5 and the development of osteoporosis.</p

Establishment and Assessment of New Formulas for Energy Consumption Estimation in Adult Burn Patients

<div><p>Objective</p><p>An accurate knowledge of energy consumption in burn patients is a prerequisite for rational nutrition therapy. This study sought to create a formula that accounts for the metabolic characteristics of adult burn patients to accurately estimate energy consumption of patients with different areas and extents of burn and at different times after injury.</p><p>Methods</p><p>Resting energy expenditure (REE) data on 66 burn patients, with total body surface area (TBSA) of burns ranging from 4% to 96%, were evaluated at different times after injury. REE values were determined in patients using indirect calorimetry at days 1, 2, 3, 7, 14, 21, and 28 after injury. We then constructed a mathematical model of REE changes post-burn. Next, established two new formulas (one non-linear and the other linear) for energy consumption estimation using model-based analytical solution and regression analysis. The new formulas were compared with measured REE and commonly used formulas including those of Carlson, Xie, Curreri, and Milner to determine accuracy and reliability.</p><p>Results</p><p>Comparative analysis showed that the new formulas offered significantly higher accuracy and reliability than the Milner formula, which is considered the most accurate of commonly used burn energy consumption estimate formulas. The accuracy of the new nonlinear formula (94.29%) and that of the linear formula (91.43%) were significantly higher than that of Milner formula (72.86%) when compared to measured REE (χ2  =  11.706, P  =  0.001; χ2  =  8.230, P  =  0.004, respectively). The reliabilities of the new estimation formulas were both 100% and that of Milner formula was 74.24% (χ2  =  19.513, P  =  0.000).</p><p>Conclusion</p><p>The new formulas constructed in this study provide reliable simulation of the impact of the degree of burn and post-burn days on energy consumption and offer notably higher accuracy and reliability than other formulas. These formulas will help determine nutritional needs of burn patients.</p><p>Trial Registration</p><p>The study was registered on Chinese Clinical Trial Registry as ChiCTR-TRC-13003806.</p></div

Results of the multiple linear regression for energy consumption estimation.

<p>Results of the multiple linear regression for energy consumption estimation.</p

Resting energy expenditures of burn patients grouped based on extent TBSA at indicated post-burn day (PBD).

<p>Resting energy expenditures of burn patients grouped based on extent TBSA at indicated post-burn day (PBD).</p

Comparison of estimates from energy consumption estimation formulas and experimental data.

<p>(A) Non-linear estimation formula (4) and (B) linear estimation formula (5). The circles represent average REE measurements for each patient.</p

Subject characteristics (n = 66, M = 48, F = 18).

<p>Subject characteristics (n = 66, M = 48, F = 18).</p

Comparisons between the newly built formula and commonly used formulas with different combinations of PBD and TBSA.

<p><b>Note:</b> Data are presented as means ± SD. MEE, measured resting energy expenditure. The letter “a” is used to indicate the results of the comparisons between MEE and non-linear, linear or Milner estimating formula, the letter “b” is used to indicate the results of the comparisons between mean MEE and Carlson, Xie, or Curreri formulas. * indicates that the result does not lie in the range of ±20% for MEE.</p><p>Comparisons between the newly built formula and commonly used formulas with different combinations of PBD and TBSA.</p

Comparison of accuracy and reliability of different formulas.

<p>“*” denotes comparison with the new non-linear estimation formula; “+” indicates comparison with the new linear estimation formula; “*” or “+” indicates P <0.05; “**” or “+ +” indicates P <0.01.</p

Definitions and units of the parameters in equations (1) and (2).

<p>Definitions and units of the parameters in equations (1) and (2).</p