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Deep neural network-based prediction of tsunami wave attenuation by mangrove forests

Didit Adytia, Dede Tarwidi, Deni Saepudin, Semeidi Husrin et al. • MethodsX (2024)

The goal of this research is to develop a model employing deep neural networks (DNNs) to predict the effectiveness of mangrove forests in attenuating the impact of tsunami waves. The dataset for the DNN model is obtained by simulating tsuna...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.mex.2024.102791

Evaluating the Suitability of the Simplified Pairs Trading Strategy for Short-term Equity Market Trading

Julija Mosina, Grigorij Žilinskij • Comparative Economic Research (2025)

Pairs trading has been a successful tool for traders since its inception in the 1980s and has evolved significantly with the introduction of algorithmic, machine, and AI trading. This evolution has compli­cated the implementation of this st...

DOAJ Open Access (DOAJ) DOI: 10.18778/1508-2008.28.20

Integrating ayurvedic eye care into primary health practice: an exploratory study on the combined effect of pratimarsha nasya, avagundana, and aschyotana in meibomian gland dysfunction

Sreelekha P, Sushma Naranappa Salethoor, Shanti K • Frontiers in Medicine (2026)

BackgroundMeibomian Gland Dysfunction (MGD) has become increasingly common in community practice, often presenting as dryness, irritation, and ocular fatigue. Factors such as prolonged screen exposure, environmental irritants, and advancing...

DOAJ Open Access (DOAJ) DOI: 10.3389/fmed.2025.1732091

Colonic stenting as bridge to surgery versus emergency surgery for management of acute left-sided malignant colonic obstruction: a multicenter randomized trial (Stent-in 2 study)

Scholten Pieter, Grubben Marina JAL, Timmer Robin, van Berkel Anne-Marie et al. • BMC Surgery (2007)

Abstract Background Acute left-sided colonic obstruction is most often caused by malignancy and the surgical treatment is associated with a high mortality and morbidity rate. Moreover, these operated patients end up with a temporary or perm...

DOAJ Open Access (DOAJ) DOI: 10.1186/1471-2482-7-12