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ABSTRACT Background Tuberculosis (TB) remains a significant public health challenge, necessitating accurate forecasting methodologies to support effective control and prevention strategies. This paper explores the applic...

Abstract Faculty hiring shapes the flow of ideas, resources, and opportunities in academia, influencing not only individual career trajectories but also broader patterns of institutional prestige and scientific progress....

Carbon allowances constitute a foundational component of national carbon emission control frameworks, as they govern the equitable distribution of subsequent allocations and directly shape the overall effectiveness of gr...

INTRODUCTION: With the rapid growth of offshore wind power integration and increasing wind power penetration, accurate power forecasting has become essential for maintaining grid stability and supporting economic dispatc...

BackgroundThe COVID-19 pandemic has reshaped the global epidemiology of respiratory infectious diseases, posing new challenges for influenza forecasting. Existing studies are often limited by reliance on single data sour...

Abstract Air pollution, particularly Nitrogen Dioxide ( $$\text {NO}_2$$ ) and ground-level ozone ( $$\text {O}_3$$ ), poses major risks to human health and the environment, making accurate forecasting essential for effe...

Accurate traffic flow prediction is of great significance for urban planning and traffic management. Among existing methods, researchers have shown remarkable progress by utilizing spatiotemporal networks. Unfortunately,...

Abstract River water quality forecasting on directed river networks requires jointly modeling temporal dynamics and directional spatial dependencies among monitoring sites. Existing spatio-temporal models often emphasize...

Forecasting vaccine demand and determining inventory policies are critical challenges in healthcare supply chains, where uncertainty poses significant operational risks. This study proposes a two-step data-driven framewo...

INTRODUCTION: High renewable energy penetration introduces significant uncertainties in distribution networks, posing challenges for source-load power forecasting and voltage management. OBJECTIVES: This study aims to e...

Abstract Financial time series forecasting is traditionally based on historical price patterns, often overlooking exogenous and behavioral variables that can significantly affect market movements. In this study, we enhan...

BackgroundInfluenza poses a significant global public health threat, with its pandemic potential and seasonal variability presenting formidable challenges to prediction accuracy. This study leverages high-quality weekly ...

Abstract Air-conditioning load forecasting is important for building energy scheduling and control. The task is difficult because load data show clear periodic patterns, and sudden changes caused by events such as holida...

Abstract Bunker fuel prices constitute a major component of maritime transport costs, representing 30–70% of total operating expenses and critically influencing competitiveness, planning, and regulatory compliance in g...

Abstract Carbon markets play a critical role in emission reduction and sustainable economic transition; however, carbon price series exhibit high volatility, nonlinear dynamics, and complex cross-feature interactions, ma...

Presents corrections to the paper, (Demand Forecasting in Data-Scarce and Resource-Restricted Environments).

This research focuses on developing a neural network model in the Python programming language to solve the technological problem of forecasting potato yields with limited agroclimatic data. The developed program is consi...

The article considers strategic modeling of the competitive capabilities of tourism companies in a dynamic market. The purpose is to design an effective model for assessing competitiveness, using materials from the case ...

Thermoelectric generators offer a promising solution for sustainable, low-maintenance energy harvesting in smart agriculture, especially for powering off-grid sensor nodes and microgrid systems. However, their inherently...

Background: Latent tuberculosis infection (LTBI) remains a critical reservoir for the global tuberculosis (TB) epidemic, particularly in South Asia, where high population density and socioeconomic disparities amplify its...

Objective To characterise temporal trends in antiretroviral therapy (ART) utilisation and forecast short-term changes in regimen distribution within a provincial HIV treatment programme.Design Population-level longitudin...

Unmanned surface vehicles (USVs) operating in open-sea environments experience significant roll motion due to wave-induced excitation. The dynamic roll response depends on various factors, including vessel speed, wave en...

Abstract Accurate prediction of terrestrial water cycle variables like soil moisture (SM) and evapotranspiration (ET) is crucial, yet existing Deep Learning (DL) models face limitations. Many adopt Single-Task Learning (...

Subsurface temperature uncertainty represents a major risk in geothermal drilling, particularly in volcanic systems where permeability, lithology, and fluid circulation create highly heterogeneous thermal regimes. This s...