Micro-expressions play an essential part in understanding non-verbal communication and deceit detection. They are involuntary, brief facial movements that are shown when a person is trying to conceal something. Automatic analysis of micro-expression is challenging due to their low amplitude and to their short duration (they occur as fast as 1/15 to 1/25 of a second). We propose a fully micro-expression analysis system consisting of a high-speed image acquisition setup and a software framework which can detect the frames when the micro-expressions occurred as well as determine the type of the emerged expression. The detection and classification methods use fast and simple motion descriptors based on absolute image differences. The recognition module it only involves the computation of several 2D Gaussian probabilities. The software framework was tested on two publicly available high speed micro-expression databases and the whole system was used to acquire new data. The experiments we performed show that our solution outperforms state of the art works which use more complex and computationally intensive descriptors.
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http://dx.doi.org/10.3390/s17122913 | DOI Listing |
Int J Pharm Pract
January 2025
School of Pharmacy and Biomolecular Sciences, Liverpool John Moores University, Liverpool, United Kingdom.
Objectives: To explore the perspectives of stakeholders on the General Pharmaceutical Council's revised Standards for the Initial Education and Training of Pharmacists that enable pharmacists to prescribe at the point of registration, from 2026.
Methods: This qualitative study used the Theoretical Domains Framework (TDF) to develop schedules for structured interviews that were conducted with various stakeholders and recorded via Microsoft Teams. Recordings were transcribed verbatim, checked for accuracy, and then analysed using the Framework approach, facilitated by NVIVO® software.
BMC Genomics
January 2025
College of Software, Nankai University, TianJin, China.
Background: Mining functional gene modules from genomic data is an important step to detect gene members of pathways or other relations such as protein-protein interactions. This work explores the plausibility of detecting functional gene modules by factorizing gene-phenotype association matrix from the phenotype ontology data rather than the conventionally used gene expression data. Recently, the hierarchical structure of phenotype ontologies has not been sufficiently utilized in gene clustering while functionally related genes are consistently associated with phenotypes on the same path in phenotype ontologies.
View Article and Find Full Text PDFMed Biol Eng Comput
January 2025
Faculty of Medicine and University Hospital Cologne, Institute for Medical Cologne, Cologne, Germany.
Recently, research on blockchain applications in the healthcare research domain has attracted increasing attention due to its strong potential. However, the existing literature reveals limited studies on defining use cases of blockchain in clinical research, categorizing and comparing available studies. Therefore, this study aims to explore the significant potential and use cases of blockchain in clinical research through a comprehensive systematic literature review (SLR).
View Article and Find Full Text PDFZhong Nan Da Xue Xue Bao Yi Xue Ban
August 2024
Center of Clinical Pharmacology, Third Xiangya Hospital, Central South University, Changsha 410013.
Objectives: Software for pharmacological modeling and statistical analysis is essential for drug development and individualized treatment modeling. This study aims to develop a pharmacokinetic analysis cloud platform that leverages cloud-based benefits, offering a user-friendly interface with a smoother learning curve.
Methods: The platform was built using Rails as the framework, developed in Julia language, and employs PostgreSQL 14 database, Redis cache, and Sidekiq for asynchronous task management.
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