Using Tolerance Bounds for Estimation of Characteristic Fatigue Curves for Composites with Confidence

Fatigue S–N curves provide the number of stress cycles that result in fatigue failure at stress range S and need to be measured for new engineering materials where data are not as readily available as they are for well-characterized and widely used metals. A simple statistical method for the estimation of characteristic fatigue curves defined in terms of lower-tail quantiles in probability distributions of dependent variables is presented. The method allows for the estimation of such quantiles with a specified confidence level, taking account of the statistical uncertainty caused by a limited number of experimental test results available for the estimation. The traditional general approach for estimating characteristic S–N curves by tolerance bounds is complicated and is not much used by engineers. The presented approach allows for calculating the curves with a simple spreadsheet. The only requirement is that the experimental log S data for the S–N curve are fairly uniformly distributed over a finite logS interval, where S denotes the stress range. Experimental fatigue test programs are often designed such that test data fulfil this assumption. Although developed with fatigue of composite laminates in mind, the presented statistical procedure and the presented associated charts are valid for fatigue curve estimation for any material.

Being Uncertain in Chromatographic Calibration—Some Unobvious Details in Experimental Design

This is an introductory tutorial and review about the uncertainty problem in chromatographic calibration. It emphasizes some unobvious, but important details influencing errors in the calibration curve estimation, uncertainty in prediction, as well as the connections and dependences between them, all from various perspectives of uncertainty measurement. Nonuniform D-optimal designs coming from Fedorov theorem are computed and presented. As an example, all possible designs of 24 calibration samples (3–8, 4–6, 6–4, 8–3 and 12–2, both uniform and D-optimal) are compared in context of many optimality criteria. It can be concluded that there are only two independent (orthogonal, but slightly complex) trends in optimality of these designs. The conclusions are important, as the uniform designs with many concentrations are not the best choices, contrary to some intuitive perception. Nonuniform designs are visibly better alternative in most calibration cases.

The Research of Small Wave Basis ANN Algorithm and 5-Class Decision Factor AI

The accuracy and reliability of continuous space curve estimation is the key to global exploration. An improved artificial intelligence algorithm is proposed for the analysis of continuous space. First, small wave basis ANN algorithm is proposed to solve discretization strategy in continuous space: The hidden layer node transfer function in BP neural network is substituted with wavelet basis function, while the replaced BP neural network is composed of wavelet neural network. Secondly, improved wolf algorithm is set up. The core wolf system ensures the precision of whole exploration. Finally, the main and auxiliary double cores and five-class decision factor is used to establish a population classification model to solve the convergence of the algorithm.

Mesh Size Selectivity of Tie-Down Gillnets for the Blackfin Flounder (Glyptocephalus stelleri) in Korea

Although gillnet fisheries are increasingly common in Korea, few studies have conducted sea trials using tie-down gillnets. Here, we analyzed the mesh size selectivity using tie-down gillnets with four different mesh sizes (84, 90, 105, and 120 mm) to catch blackfin flounders. A total of 10 sea trials were conducted at depths of 100–140 m in the waters of Yangyang County, Gangwon Province, Korea, and the catching efficiency and mesh size selectivity were comparatively analyzed. The net with a mesh size of 84 mm showed the highest number of catches (373), followed by the 90-mm (363) and 105-mm (307) meshes. The results of the master curve estimation showed that the larger the mesh size, the higher the total length representing the same retention probability. Therefore, the catch rate of small fish decreased with the increasing mesh size. For the 84-mm net, the 50% selection length for small fish (total length ≤ 170 mm) was estimated at 186.9 mm, which was approximately 17 mm larger than the length limit. The results show that when using tie-down gillnets, the size of the fish caught changed according to the changes in the mesh size.

Malaria Cases in a Tertiary Hospital in Kuala Lumpur, Malaysia: A 16-Year (2005–2020) Retrospective Review

While there has been a tremendous decline in malaria disease burden in the remote parts of Malaysia, little is known about malaria incidence in its urban localities. This study aimed to analyze trends of malaria cases in urban Kuala Lumpur, Malaysia. All suspected cases presented to a university hospital in Kuala Lumpur from January 2005 to December 2020 were examined by microscopy. Infection status was analyzed using descriptive statistics and curve estimation analysis. Of 3105 blood films examined, 92 (3%) were microscopically confirmed malaria cases. Plasmodium vivax infections accounted for the majority (36.9%) of all malaria cases. Nearly half (47.8%) of cases were found among foreign cases (p < 0.001). The majority of foreign cases were male (86.4%) and came from Southeast Asian countries (65.9%). The curve estimation analysis showed significant decreases in malaria cases due to P. vivax (R2 = 0.598; p < 0.001) and Plasmodium falciparum (R2 = 0.298, p = 0.029), but increases for Plasmodium knowlesi (R2 = 0.325, p = 0.021) during the 16 years. This study showed that malaria incidence in urban Kuala Lumpur is low and has remained stable since 2005. However, P. knowlesi has played a significant role in the increase in overall malaria in the area, highlighting the importance of continued vigilance and improved surveillance.

Incidence of Malaria in Kuala Lumpur, Malaysia: A Single-Institution Retrospective Review from 2005 to 2020

While there has been a tremendous decline in malaria disease burden in the remote parts of the Malaysia, little is known about malaria incidence in its urban localities. This study aimed to analyse trends of malaria cases in urban Kuala Lumpur, Malaysia. All suspected cases presented to a university hospital in Kuala Lumpur from January 2005 to December 2020 were examined by microscopy. Infection status was analysed using descriptive statistics and curve estimation analysis. Of 3105 blood films examined, 92 (3%) were microscopically confirmed malaria cases. Plasmodium vivax infections accounted for the majority (36.9%) of all malaria cases. Nearly half (47.8%) of cases were found among foreign cases (P&amp;lt;0.001). The majority of foreign cases were males (86.4%) and came from Southeast Asian countries (65.9%). Curve estimation analysis showed significant decreases of malaria cases due to P. vivax (R2 = 0.598; P&amp;lt;0.001) and Plasmodium falciparum (R2 = 0.0259, P = 0.029), but increase for Plasmodium knowlesi (R2 = 0.325, P = 0.021) during the 16 years. This study revealed that malaria incidence in urban Kuala Lumpur is low and has remained stable since 2005. However, P. knowlesi played a significant role in the increase of overall malaria in the area, highlighting the importance of continued vigilance and improved surveillance.