Large photometric surveys require classification methods that retain sensitivity to sparsely represented periodic variable-star classes. We present a two-stage decoupled multimodal network (TDMN) for imbalanced periodic-variable-star classification u...
The classification of variable stars is essential for understanding stellar evolution and dynamics. With the growing volume of light curve data from extensive surveys, there is a need for automated and accurate classification methods. Traditional met...
The booming data volume of modern time-domain surveys demands fast, robust early classification of sparsely sampled light curves, as newly discovered transients typically have only a handful of observations. We compare classifiers for extremely spars...
The variability of B-type stars offers valuable insights into the interiors of stars and the processes that drive pulsation and rotation in massive stars. In this study, we present the classification of the variability of 197 B-type stars observed in...
The Optical Gravitational Lensing Experiment (OGLE) is one of the most productive and influential photometric sky surveys in the history of observational astronomy. Originally designed to detect dark matter through gravitational microlensing events,...
We present a comprehensive study of variable stars in the young open cluster NGC 663, combining ground-based 50BiN photometry, space-based TESS time-series observations, and astrometric measurements from Gaia DR3. A total of 60 variable candidates we...
Symbiotic stars, interacting binaries composed of a cool giant and a hot compact companion, exhibit complex variability across the electromagnetic spectrum. Over the past decades, large-scale photometric and spectroscopic surveys from ground- and spa...
Luminous Blue Variables are massive evolved stars, here we introduce this outstanding class of objects. Described are the specific characteristics, the evolutionary state and what they are connected to other phases and types of massive stars. Our cur...
In this article, we propose a robust star classification methodology leveraging light curves collected from 15 datasets within the Kepler field in the visible optical spectrum. By employing a Bagging neural network ensemble approach, specifically an...
Stellar evolution theory is most uncertain for massive stars. For reliable predictions of the evolution of massive stars and their final fate, solid constraints on the physical parameters, and their changes along the evolution and in different enviro...
This study was focused on the configuration design of a star grain by using machine learning in the optimal design process. The key to optimizing the grain design is aimed at obtaining a set of configuration variables that satisfy the requirements. T...
Background and Objectives: This prospective, comparative, double-cohort study aimed to compare the efficacy of silver diamine fluoride and potassium iodide (38% SDF+KI; Riva Star®) with sodium fluoride varnish (5% NaF; Duraphat®) in hypersens...
Systematic monitoring of specific targets in the optical regime was historically applied on a very narrow sample of known variable stars. The discovery of blazars in the 20th century brought to the foreground the need for new global sky surveys, cove...
The classification of agricultural products is of great importance for quality control, optimized marketing, efficient logistics, research progress, consumer satisfaction, and sustainability. Dragon fruit has many varieties that need to be identified...
The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) has produced massive medium-resolution spectra. Data mining for special and rare stars in massive LAMOST spectra is of great significance. Feature extraction plays an important ro...
Background/Objectives: Nursing staff turnover can adversely affect nursing home (NH) performance. To address staffing shortages, NHs are increasingly turning to agency nursing staff as a solution. This study examined the relationship between the use...
Background: Mechanical diagnosis and therapy (MDT) and the stratified approach using the Keele STarT Back Screening Tool (SBST) are examples of stratified low back pain (LBP) management. We investigated whether the medium–high risk in SBST can...
The Tsinghua University–Ma Huateng Telescopes for Survey (TMTS) started to monitor the LAMOST plates in 2020, leading to the discovery of numerous short-period eclipsing binaries, peculiar pulsators, flare stars, and other variable objects. Her...
The US food supply is dominated by highly-processed packaged food and beverage products that are high in energy, saturated fat, sugar, and salt. We report results of a cross-sectional assessment of the 2018 US packaged food and beverage supply by nut...
Current building energy benchmarking relies on annual Energy Use Intensity (EUI), which cannot detect temporal operational anomalies—such as after-hours equipment operation or irregular scheduling—that represent actionable efficiency oppo...
Understanding the movement, direction, and shape of sand dunes can contribute to reducing their impact on infrastructure and the environment. The Rub’ al Khali desert has a distribution of dune types. This study aims to identify and map the dif...
Objectives: Urinary tract infections (UTIs) are the most common healthcare-associated infections in Skilled Nursing Facilities (SNFs); they are associated with longer lengths of stay, higher levels of care, increased treatment costs, and higher morta...
With the increasing volume of collected Earth observation (EO) data, artificial intelligence (AI) methods have become state-of-the-art in processing and analyzing them. However, there is still a lack of high-quality, large-scale EO datasets for train...
An algorithm widely used in hotel companies for demand analysis is the so-called K-means. The aforementioned algorithm is based on the use of the Euclidean distance as a dissimilarity measure and this fact can cause a main handicap. Concretely, the E...
Most offshore wind farms built thus far are based on waters below 30 m deep, either using big diameter steel monopiles or a gravity base. Now, offshore windfarms are starting to be installed in deeper waters and the use of these structures—used...
Freezing of gait (FoG) in Parkinson’s disease is clinically heterogeneous, yet wearable-sensor studies predominantly focus on binary FoG detection. We investigated whether right-ankle inertial signals can characterize clinically meaningful FoG...
Buildings account for approximately one-third of global energy usage and associated carbon emissions, making energy benchmarking a crucial tool for advancing decarbonization. Current benchmarking studies have often been limited to mainly the annual s...