Facebook users are exposed to diverse news and political content; this means that Facebook is a significant tool for the enhancement of civic participation and engagement in politics. However, it has been argued that Facebook, through its algorithmic...
Artificial intelligence (AI) is transforming how news is produced, curated, and consumed, challenging traditional gatekeeping theories rooted in human editorial control. We develop a robust theoretical framework to reconceptualize gatekeeping in the...
Digital gatekeeping is increasingly performed by adaptive systems that rank, sequence, package, moderate, and sometimes generate news across repeated interactions. This conceptual analysis asks two questions: how should researchers analyze these syst...
The rise of algorithm-driven virtual museums presents a philosophical challenge for how cultural meaning is constructed and critiqued in digital curation. Prevailing approaches highlight important but partial aspects: the loss of aura and authenticit...
An adequate visualization form is required to gain an overview and ultimately understand the complex and diverse biological mechanisms of diseases. Recently, disease maps have been introduced for this purpose. A disease map is defined as a systems bi...
The increasing number and complexity of structures containing RNA chains in the Protein Data Bank (PDB) have led to the need for automated structure annotation methods to replace or complement expert visual curation. This is especially true when sear...
This article is an overview of preliminary research undertaken for the creation of a framework for collecting and distributing new media art within regional art galleries in the U.K. From the 1960s, artists have experimented using computers and softw...
Museums in Dispute: Artificial Intelligence, Digital Culture, and Critical Curation analyzes contemporary debates in the museum field through the lens of tensions between technology, digital culture, and political and epistemological disputes. Struct...
Digital capitalism has generated new forms of extractivism that extend beyond natural resources to encompass data, attention, affect, and planetary materials. This article examines how exhibition practices can function as forms of algorithmic resista...
Development of new agricultural fungicides requires reliable computational tools to screen candidate molecules before investing time, money, and effort in experimental assays. In this study, curated datasets of fungicidal and non-fungicidal compounds...
This paper investigates the post-hoc calibration of confidence for “exploratory” machine learning classification problems. The difficulty in these problems stems from the continuing desire to push the boundaries of which categories have e...
Pupylation is a type of reversible post-translational modification of proteins, which plays a key role in the cellular function of microbial organisms. Several proteomics methods have been developed for the prediction and analysis of pupylated protei...
Antibiotic resistance (AR) is a naturally occurring phenomenon with the capacity to render useless all known antibiotics in the fight against bacterial infections. Although bacterial resistance appeared before any human life form, this process has ac...
The curation design of cultural heritage sites, such as museums, influence the level of visitor satisfaction and the possibility of revisitation; therefore, an efficient exhibit layout is critical. The difficulty of determining the behavior of visito...
Most of the dam structures around the world are approaching the end of their economic life of 50 to 70 years, especially due to sediment accumulation in reservoir areas. This situation necessitates the development of proactive infrastructure manageme...
The huge amount of data produced by the Internet of Things need to be validated and curated to be prepared for the selection of relevant data in order to prototype models, train them, and serve the model. On the other side, blockchains and open data...
Deep learning is a convenient method for doctors to classify pulmonary diseases such as COVID-19, viral pneumonia, bacterial pneumonia, and tuberculosis. However, such a task requires a dataset including samples of all these diseases and a more effec...
Traditional agenda-setting theory, which is centered on legacy news outlets, now operates in a fragmented ecosystem shaped by platforms, algorithms, and networked intermediaries. Existing agenda-setting models only partially integrate algorithmic gat...
Background and Aim: In the era of deep learning, numerous models have emerged in the literature and various application domains. Transformer architectures, particularly, have gained popularity in deep learning, with diverse transformer-based computer...
Organic solar cells are widely recognized for their flexibility, light weight and semitransparency, all relevant for niche applications. A significant challenge in their development lies in the accurate prediction of their power conversion efficiency...
Background: Electroencephalography (EEG) signal-based machine learning models are among the most cost-effective methods for information retrieval. In this context, we aimed to investigate the cortical activities of psychotic criminal subjects by depl...
Machine learning is a crucial tool for both academic and real-world applications. Classification problems are often used as the preferred showcase in this space, which has led to a wide variety of datasets being collected and utilized for a myriad of...
Individual gene expression and molecular pathway activation profiles were shown to be effective biomarkers in many cancers. Here, we used the human interactome model to algorithmically build 7470 molecular pathways centered around individual gene pro...
In this paper, we propose a new sensor for the detection and analysis of dusts (seen as powders and fibers) in indoor environments, especially designed for applications in the field of Cultural Heritage or in other contexts where the presence of dust...
In the last decades, the development of interconnectivity, pervasive systems, citizen sensors, and Big Data technologies allowed us to gather many data from different sources worldwide. This phenomenon has raised privacy concerns around the globe, co...
This paper investigates digital comics—particularly webcomics and webtoons—as emerging forms of cultural heritage, analyzing their exponential global influence alongside the limitations of traditional heritage frameworks in systematically...
(1) Background: Machine learning algorithms are finding fruitful applications in predicting the ADME profile of new molecules, with a particular focus on metabolism predictions. However, the development of comprehensive metabolism predictors is hampe...
With the continuously accelerating genome sequencing from diverse groups of archaea and bacteria, accurate identification of gene orthology and availability of readily expandable clusters of orthologous genes are essential for the functional annotati...
S2R overexpression is associated with various forms of cancer as well as both neuropsychiatric disorders (e.g., schizophrenia) and neurodegenerative diseases (Alzheimer’s disease: AD). In the present study, three ligand-based methods (QSAR modeling,...
Self-compacting concrete (SCC) has been developed as a type of concrete capable of filling narrow gaps in highly reinforced areas of a mold without internal or external vibration. Bleeding and segregation in SCC can be prevented by the addition of su...
Horizontal gene transfer (HGT) is a fast-track mechanism that allows genetically unrelated organisms to exchange genes for rapid environmental adaptation. We developed a new phyletic distribution-based software, HGT-Finder, which implements a novel b...
In 2007, an outbreak of African swine fever (ASF), a deadly disease of domestic swine and wild boar caused by the African swine fever virus (ASFV), occurred in Georgia and has since spread globally. Historically, ASFV was classified into 25 different...
Rheumatoid arthritis (RA) is a chronic autoimmune disorder that has a significant impact on quality of life and work capacity. Treatment of RA aims to control inflammation and alleviate pain; however, achieving remission with minimal toxicity is freq...
A code MolecGeom, based on algorithms for stepwise distortions of bond lengths, bond angles and dihedral angles of polyatomic molecules, is presented. Potential energy surfaces (PESs) are curated in terms of the energy for each molecular geometry. PE...
Digital capitalism is often described either as a clean break with the past or as a continuation of older markets. This article takes a third position: digital capitalism is a reorganisation of capitalist accumulation around platforms, data, attentio...
This study examines how the relationship between perceived financial accounting disclosures (FAD) and investor reactions to negative financial news (IRNFN) is conditioned by two individual-level moderators among 310 retail investors holding shares in...
(1) Background: Data accuracy plays a key role in determining the model performances and the field of metabolism prediction suffers from the lack of truly reliable data. To enhance the accuracy of metabolic data, we recently proposed a manually curat...
Protein phase separation is increasingly understood to be an important mechanism of biological organization and biomaterial formation. Intrinsically disordered protein regions (IDRs) are often significant drivers of protein phase separation. A number...
The National Oceanic and Atmospheric Administration’s (NOAA) Center for Satellite Applications and Research (STAR) facilitates and enables societal benefits from satellite oceanography, supporting operational and experimental satellite missions...
License plate recognition is a pivotal challenge in surveillance applications, predominantly due to the low resolution and diminutive size of license plates, which impairs recognition accuracy. The advent of AI-based super-resolution techniques offer...
Background/Objectives: Leishmaniasis is a group of diseases caused by obligate intracellular parasites of the Leishmania genus and is classified by the World Health Organization as a category I neglected tropical disease. Leishmania infantum predomin...
The sustainability of human existence is in dire danger and this threat applies to our environment, societies, and economies. Smartization of cities and societies has the potential to unite individuals and nations towards sustainability as it require...
In recent years we have been experiencing an ever-increasing number of Building Modeling Modeling (BIM) and Visual Programming Language (VPL) approaches in the architectural design field. These experiments have inspired new research strictly focused...
Background: Electronic and electrical waste (e-waste) production has emerged to be of global environmental public health concern. E-waste workers, who are frequently exposed to hazardous chemicals through occupational activities, face considerable he...
Artificial intelligence (AI) is gaining increasing interest in the field of medicine because of its capacity to process big data and pattern recognition. Cardiotocography (CTG) is widely used for the assessment of foetal well-being and uterine contra...
Diabetic retinopathy (DR), a leading cause of vision loss worldwide, poses a critical challenge to healthcare systems due to its silent progression and the reliance on labor-intensive, subjective manual screening by ophthalmologists, especially amid...
Machine Learning models, more specifically Artificial Neural Networks, are transforming medical imaging by enabling precise liver segmentation, a crucial task for diagnosing and treating liver diseases. However, these models often face challenges in...
Cancer remains one of the most formidable challenges to human health; hence, developing effective treatments is critical for saving lives. An important strategy involves reactivating tumor suppressor genes, particularly p53, by targeting their negati...
It is necessary to understand the complicated interplay between diseases and medicinal plants to find new curing agents that may be used in natural sources. Nevertheless, the state of interaction between diseases and plants today is not fully develop...
This scoping review synthesizes 35 studies on sensor technologies and artificial intelligence for fruit detection, classification, and quality assessment, contrasting Latin American and international research traditions. The analysis suggests notable...
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