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Jul 01, 2025Open Access
This study investigates the impact of personalized AI-generated video advertisements on consumer click-through rates (CTR), aiming to understand the effectiveness of personalized content in the digital advertising landscape. Utilizing a mixed-methods approach, including quantitative analysis and qualitative feedback, we examined the correlation between ad personalization, emotional engagement, and consumer behavior across various demographics. Data collected through a structured questionnaire re...
Jun 30, 2025Open Access
In this paper, a novel multilingual OCR (Optical Character Recognition) method for scanned papers is provided. Current open-source solutions, like Tesseract, offer extremely high accuracy when it comes to Latin letters. Nonetheless, multilingual texts using Asian characters typically have less accuracy than ones that are simply in Latin. The challenges for OCR increase when handling the logographic Chinese and Korean scripts because these languages feature complex multi-stroke characters. Text s...
Jun 27, 2025Open Access
This research paper delves into the tactical integration of Artificial Intelligence (AI) within the framework of Human Resource Management (HRM), with a specific focus on a case study that revolves around Microsoft Corporation. Microsoft is, without a doubt, a premier global player when it comes to digital transformation and innovation, thus, it serves as a fascinating point of reference for understanding how various AI technologies can be effectively embedded into core HR operations and functio...
Jun 26, 2025Open Access
This study explores the psychological impacts of artificial intelligence (AI) exposure to job insecurity and employee morale, with a specific focus on the moderating role of emotional intelligence (EI). The integration of AI technologies in the workplace has drastically altered job dynamics, leading to heightened fears of job loss among employees. This research aims to understand how these changes affect employees’ emotional and psychological states, particularly in terms of perceived job insecu...
Jun 24, 2025Open Access
The rapid advancement of Artificial Intelligence (AI) has fundamentally transformed marketing strategies, offering unprecedented opportunities for personalization, particularly in the diverse landscape of the European market. This article investigates the theme “Think Global, Advertise Local”, focusing on how AI technologies empower businesses to craft personalized advertisements that are finely tuned to local cultural contexts and consumer preferences. By employing principles of glocalization, ...
Jun 23, 2025Open Access
Neuroleptic Malignant Syndrome (NMS) and severe anticholinergic adverse drug reactions (ADRs) are rare but life-threatening complications associated with antipsychotic pharmacotherapy. These conditions often arise unpredictably, posing significant challenges in psychiatric clinical practice. Current risk stratification approaches lack the granularity to account for complex interplays between genetic predispositions, pharmacological profiles, and individual patient characteristics. In this study,...
Jun 19, 2025Open Access
In view of the control problem of hydrogen pressure and flow coupling in the anode subsystem of the Proton Exchange Membrane Fuel Cell (PEMFC) under dynamic load conditions, this paper proposes an intelligent control framework based on the deep deterministic policy gradient (DDPG) algorithm. Firstly, a dynamic model of the fuel cell anode system is established to transform the multivariable coupling control problem into a reinforcement learning state space; secondly, a multi-objective reward fun...
Jun 13, 2025Open Access
Evaluating drug safety during pregnancy remains an ongoing clinical and pharmacological challenge due to ethical, practical, and regulatory barriers, resulting in scarce human clinical trial data. Consequently, healthcare providers must frequently rely on limited observational data and incomplete safety profiles when prescribing medications, especially psychiatric and neurological drugs, whose discontinuation could lead to significant maternal health risks. This research addresses these critical...
Jun 13, 2025Open Access
Psychiatric and neurological disorders often exhibit overlapping symptomatology and shared neurobiological mechanisms, yet pharmacological treatments are typically developed and administered in isolation. This research proposes a machine learning (ML) framework to identify potential “dual-use” drugs—compounds that may be therapeutically effective across both domains—by analysing drug-target interaction data. Drug-target profiles were curated from ChEMBL and Drug Bank, with each drug categorized ...
Jun 13, 2025Open Access
Background: Treatment-resistant depression (TRD) poses significant clinical challenges, with many patients inadequately responding to augmentation strategies like aripiprazole. Pramipexole, a dopamine agonist, has emerged as a promising alternative, though predictors of response remain unclear. This study applies machine learning (ML) to identify predictors and subgroups influencing pramipexole augmentation (PA) effectiveness in TRD, especially among patients previously failing ...
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