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Background: Recent lifestyle changes have increased the prevalence of dyslipidemia in Korea. Young men are known to have a low awareness of dyslipidemia and a lack of motivation to maintain their weight. However, the association between weight change and dyslipidemia in young adults has not been thoroughly examined. Methods: Data from the Armed Forces Medical Command Defense Medical Information System database were used. In this study, 15,068 soldiers who underwent private and corporal health examinations between May 2020 and April 2022 were included. The difference in weights between the two different health examinations was used to quantify weight change. Four components of the lipid profile were used to assess dyslipidemia during the corporal health examination. Results: After adjusting for relevant covariates, weight gain was associated with increased risk of dyslipidemia (adjusted odds ratio [OR], 1.38 [95% confidence interval, CI, 1.15 to 1.64] for the 5% to 10% weight gain group; and OR, 2.02 [95% CI, 1.59 to 2.55] for the ≥10% weight gain group), whereas weight loss was associated with decreased risk (adjusted OR, 0.82 [95% CI, 0.68 to 0.98] for the 5% to 10% weight loss group; and OR, 0.38 [95% CI, 0.27 to 0.53] for the ≥10% weight loss group). In subgroup analysis based on the participants’ baseline body mass index, smoking status, regular exercise habits, and hypertension status, there were no significant differences between the subgroups. Conclusion: Weight change was associated with dyslipidemia in Korean male soldiers. The findings suggest that limiting weight gain in young adults by encouraging a healthy lifestyle may help prevent dyslipidemia. [ABSTRACT FROM AUTHOR]

The purpose of this study is to propose a method for rapidly assessing the hit locations and extent of damage to a naval ship attacked by threatening weapons. An integrated method is presented for assessing the vulnerability to the hull and systems caused by the blast or penetrating effects of a weapon at multiple possible impact locations.The proposed method enables the assessment of vulnerability changes for design alternatives during the early design phase of naval vessels. To predict the extent of damage and to visualize the damaged hull and equipment, it is first assumed that a weapon has multiple hit locations.It is shown that a set of possible hit locations was generated by assuming the trajectory for air-explosion (AIREX) weapons by dividing the trajectory into an air-to-ship trajectory and a ship-to-ship trajectory. To account for the non-deterministic nature of weapon hits, a probability distribution approach was used to generate random multiple hit locations for each trajectory while the hit locations of AIREX in all directions were predicted using a multivariate probability distribution that generates three-dimensional random hit points. The extent of damage was then calculated, taking into account the topology of the hull structure and the equipment installed within the hull compartment, along with the damage volume associated with the weapon at each hit point. To identify the damage volume, axis-aligned bounding box (AABB) components were used, which provide a simplified representation of the ship’s geometry, as well as the relative position and dimensions of the hull structure and installed equipment. The damage compartment was defined as the portion of the hull that overlapped the damaged volume. While AABB’s overlap detection algorithm was applied to the damaged hull compartments, the algorithm identified the equipment that overlapped the damaged volume of the hull. Finally, the geometric modeling module, the probabilistic multiple hit location prediction module, and the damage analysis module were developed for damage visualization and vulnerability assessment. [ABSTRACT FROM AUTHOR]

Background: There are many models for predicting diabetes mellitus (DM), but their clinical implication remains vague. Therefore, we aimed to create various DM prediction models using easily accessible health screening test parameters. Methods: Two sets of variables were used to develop eight DM prediction models. One set comprised 62 easily accessible examination results of commonly used variables from a tertiary university hospital. The second set comprised 27 of the 62 variables included in the national routine health checkups. Gradient boosting and random forest algorithms were used to develop the models. Internal validation was performed using the stratified 10-fold cross-validation method. Results: The area under the receiver operating characteristic curve (ROC-AUC) for the 62-variable DM model making 12-month predictions for subjects without diabetes was the largest (0.928) among those of the eight DM prediction models. The ROC-AUC dropped by more than 0.04 when training with the simplified 27-variable set but still showed fairly good performance with ROCAUCs between 0.842 and 0.880. The accuracy was up to 11.5% higher (from 0.807 to 0.714) when fasting glucose was included. Conclusion: We created easily applicable diabetes prediction models that deliver good performance using parameters commonly assessed during tertiary university hospital and national routine health checkups. We plan to perform prospective external validation, hoping that the developed DM prediction models will be widely used in clinical practice. [ABSTRACT FROM AUTHOR]

In this work we report on the photoluminescence (PL) characteristics of porous silicon (PS) prepared by electrochemical anodization of a p-type Si wafer using chemically metal-dissolved hydrofluoric solutions. Various solid metals, oxidative (Al, Fe, Sn, Ni, Cr) and reductive (Cu), were used for this work. The effects of metals on the PL properties in as-grown, illuminated, and aged states have been studied. It is found that for the as-grown state the PL intensity is reduced by the addition of metal. In particular, the Cu-doped PS reveals a PL intensity lower by one order of magnitude as compared to that of normal PS. The improvement of stability in the PL intensity under illumination was only observed for the Cu-doped PS sample, which is more stable by a factor of 2 as compared to that of normal PS. On the other hand, the improved stability of the PL intensity in the aged state was observed for metal-doped PS samples other than for the Cu-doped sample. From the results, it is suggested that reductive metals are more effective in reducing the PL degradation caused by illumination while oxidative metals are more effective in reducing the PL degradation caused by ageing. [ABSTRACT FROM AUTHOR]