Academic Articles & Research Papers

How Progressive Hydrogenation Shapes the Optical Response of Carbon Clusters.

Hydrogenation of Uracil in Solid Para-Hydrogen: Infrared Spectra of Monohydrogenated Radicals (5H-C4H5N2O2, 6H-C4H5N2O2, and 4OH-C4H5N2O2) and Their Implications for RNA-Related Chemistry in the Interstellar Medium.

Two Novel ATP2C1 Mutations in Portuguese Patients with Hailey-Hailey Disease

Hailey-Hailey disease (HHD) is a rare autosomal dominant acantholytic dermatosis. It is characterized by a recurrent eruption of vesicles, erosions, and scaly erythematous plaques involving intertriginous areas and first occurring after pub...

A comparative empirical evaluation of semantic clustering algorithms on static word embeddings

Objective: This study conducts a comprehensive empirical evaluation of semantic clustering algorithms to identify the most effective approach for automatically organizing and extracting meaning from textual data. By systematically comparing...

Natural Language Processing

Natural language processing is a fast-evolving field with popular applications in language translation, speech recognition, text classification, and summarization of text, among others. The central aspect of NLP is vectorizing text data. Te...

Bridging the performance–efficiency gap: a resource-efficient hybrid DL-ML framework for jackfruit disease detection

Complex environment variability and limited computational resources in agricultural settings create challenges in automated detection in tropical regions, where jackfruit diseases pose major threats to harvest productivity and food security...

A comprehensive analytical assessment of dino-based architectures for sustainable automated potato inspection in the Al Kharj Region

Abstract Self-supervised learning (SSL) has emerged as a pivotal paradigm in computer vision, particularly for applications where labeled data are limited, costly, or labor-intensive to obtain. This paradigm is especially relevant to sustai...

Hierarchical Multimodal Sleep Staging with Optimized EEG, EOG, and PPG Features for Wearable Applications

Automatic sleep staging is fundamental for diagnosing sleep disorders and enabling long-term sleep monitoring with wearable devices. Although Deep Learning has significantly improved classification performance, balancing accuracy with compu...

Greedy Broad Learning System

In order to overcome the extremely time-consuming drawback of deep learning (DL), broad learning system (BLS) was proposed as an alternative method. This model is simple, fast, and easy to update. To ensure the fitting and generalization ab...

Single-cell spatial metabolomics with cell-type specific protein profiling for tissue systems biology

Abstract Metabolic reprogramming in cancer and immune cells occurs to support their increasing energy needs in biological tissues. Here we propose Single Cell Spatially resolved Metabolic (scSpaMet) framework for joint protein-metabolite pr...

A deep learning approach to predict blood-brain barrier permeability

The blood–brain barrier plays a crucial role in regulating the passage of 98% of the compounds that enter the central nervous system (CNS). Compounds with high permeability must be identified to enable the synthesis of brain medications for...

Machine learning in pain research

1. Introduction Pain and pain chronification are incompletely understood and unresolved medical problems that continue to have a high prevalence.14 It has been accepted that pain is a complex phenomenon.2,32,72 Contemporary methods of compu...

Evaluation of PCA with variable selection for cluster typological domains

Abstract The modeling of mineral deposits has been improved over the years with the incorporation of mineralogical and metallurgical information obtained from drilling samples that make up the pillars for the construction of resource models...

Semantic Interpretation for Convolutional Neural Networks: What Makes a Cat a Cat?

Abstract The interpretability of deep neural networks has attracted increasing attention in recent years, and several methods have been created to interpret the “black box” model. Fundamental limitations remain, however, that impede the pac...

Personalized ideological content recommendation via reinforcement learning as a digital therapeutic for anxiety reduction in youth

Abstract Adaptive digital therapies are needed with increasing rates of youth anxiety. However, existing systems lack personalization and dynamic learning. To solve this, the proposed research is to build a personalized ideological content ...

Tachyon: Enhancing stacked models using Bayesian optimization for intrusion detection using different sampling approaches

The integration of sensors in the monitoring of essential bodily measurements, air quality, and energy consumption in buildings demonstrates the importance of the Internet of Things (IoT) in everyday life. These security breaches are caused...