Prefiltered component-based greedy (PreCoG) scan method.

The spatial distribution of disease cases can provide important insights into disease spread and its potential risk factors. Identifying disease clusters correctly can help us discover new risk factors and inform interventions to control and prevent the spread of disease as quickly as possible. In this study, we propose a novel scan method, the Prefiltered Component-based Greedy (PreCoG) scan method, which efficiently and accurately detects irregularly shaped clusters using a prefiltered component-based algorithm.

Utilizing logistic regression to compare risk factors in disease modeling with imbalanced data: a case study in vitamin D and cancer incidence.

Imbalanced data, a common challenge encountered in statistical analyses of clinical trial datasets and disease modeling, refers to the scenario where one class significantly outnumbers the other in a binary classification problem. This imbalance can lead to biased model performance, favoring the majority class, and affecting the understanding of the relative importance of predictive variables. Despite its prevalence, the existing literature lacks comprehensive studies that elucidate methodologies to handle imbalanced data effectively.

A comparative analysis and multi-objective optimization of replacing syngas from a downdraft gasifier in an ordinary 300 MW power plant to lessen the environmental effect.

Due to environmental issues, disposing of household garbage is a significant obstacle for life on Earth. Due to this, several sorts of research on biomass conversion into useable fuel technologies are carried out. Among the most popular and effective technologies is the gasification process, which transforms trash into a synthetic gas that can be used in industry.

Recent advances in tailoring and improving the properties of polyimide aerogels and their application.

With the rapid advancements in technology and growing aerospace applications, there is a need for effective low-weight and thermally insulating materials. Aerogels are known for their ultra-lightweight and they are highly porous materials with nanopores in a range of 2 to 50 nm with very low thermal conductivity values. However, due to hygroscopic nature and brittleness, aerogels are not used commercially and in daily life.

Estimating the optimal population upper bound for scan methods in retrospective disease surveillance.

Correctly and quickly identifying disease patterns and clusters is a vital aspect of public health and epidemiology so that disease outbreaks can be mitigated as effectively as possible. The circular scan method is one of the most commonly used methods for detecting disease outbreaks and clusters in retrospective and prospective disease surveillance. The circular scan method requires a population upper bound in order to construct the set of candidate zones to be scanned, which is usually set to 50% of the total population.