1,721,080 research outputs found
Multiscale Modelling of Microtubules and Actin Microfilaments
No full text9th International Fröhlich's Symposium ELECTRODYNAMIC ACTIVITY OF LIVING CELLS Including Microtubule Coherent Modes and Cancer Cell Physics Prague, July 1-3, 201
Electric field generated by longitudinal axial microtubule vibration modes with high spatial resolution microtubule model
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Mediapipe based Preprocessed VGGFace2 Dataset
No full textVGGFace2 Dataset and Face Mesh PreprocessingIntroductionThe VGGFace2 dataset is a large-scale face recognition dataset containing over 3.31 million images of 9,131 identities, with an average of 362 images per identity. The dataset is designed to include extensive variations in pose, age, illumination, ethnicity, and profession, making it one of the most diverse and challenging face recognition datasets available. For more details, please refer to the original publication:VGGFace2: A dataset for recognizing faces across pose and age - DOI: 10.48550/arXiv.1710.08092
Preprocessing Using MediaPipe 3D Face MeshOn this dataset, we applied the MediaPipe-based 3D face mesh algorithm to accurately detect faces while removing all background elements, including hair. Our preprocessing strictly retained facial landmarks, ensuring that only the essential facial features were preserved. This approach significantly enhanced the accuracy and generalization of our model, as the model was trained exclusively on landmark-based facial data.
Training and PerformanceThe preprocessed data was utilized to train Xception model, which resulted in remarkably accurate outcomes due to the strictly landmark-based facial representation. The model demonstrated robust performance including explainable-AI, proving that eliminating unnecessary background elements contributed positively to its efficiency and reliability.
CitationIf you use this dataset or the preprocessed version in your work, please cite both of the following:
VGGFace2 Dataset:
@article{Cao2018VGGFace2, title={VGGFace2: A dataset for recognizing faces across pose and age}, author={Cao, Qiong and Shen, Li and Xie, Weidi and Parkhi, Omkar M and Zisserman, Andrew}, journal={arXiv preprint arXiv:1710.08092}, year={2018}}
DOI: [10.48550/arXiv.1710.08092](https://doi.org/10.48550/arXiv.1710.08092) Preprocessed Dataset using MediaPipe:@dataset{Shah2025_MediaPipe_FaceMesh, title={MediaPipe-based 3D Face Mesh Preprocessed VGGFace2 Dataset}, author={Shah, Syed Taimoor Hussain and Shah, Syed Adil Hussain and Zamir, Ammara and Qayyum, Kainat and Shah, Syed Baqir Hussain and Fatima, Syeda Maryam and Deriu, Marco Agostino}, year={2025}, doi={10.5281/zenodo.15078557}} DOI: [10.5281/zenodo.15078557](https://doi.org/10.5281/zenodo.15078557)
ContactFor any questions or further details, please feel free to contact us.Syed Taimoor Hussain ShahPolitoBIOMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, ItalyEmail: [email protected]: 0000-0002-6010-677
A computational multilevel approach to study the effects of biodegradable metals on subcellular structures
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In silico investigation of Alsin RLD conformational dynamics and phosphoinositides binding mechanism
Full text linkAlsin is a protein known for its major role in neuronal homeostasis and whose mutation is associated with early-onset neurodegenerative diseases. It has been shown that its relocalization from the cytoplasm to the cell membrane is crucial to induce early endosomes maturation. In particular, evidences suggest that the N-terminal regulator of chromosome condensation 1 like domain (RLD) is necessary for membrane association thanks to its affinity to phosphoinositides, membrane lipids involved in the regulation of several signaling processes. Interestingly, this domain showed affinity towards phosphatidylinositol 3-phosphate [PI(3)P], which is highly expressed in endosomes membrane. However, Alsin structure has not been experimentally resolved yet and molecular mechanisms associated with its biological functions are mostly unknown. In this work, Alsin RLD has been investigated through computational molecular modeling techniques to analyze its conformational dynamics and obtain a representative 3D model of this domain. Moreover, a putative phosphoinositide binding site has been proposed and PI(3)P interaction mechanism studied. Results highlight the substantial conformational stability of Alsin RLD secondary structure and suggest the role of one highly flexible region in the phosphoinositides selectivity of this domain
Multiscale Modelling of entire Microtubules and Actin Microfilaments
No full text4th International Conference on the Mechanics of Biomaterials and Tissues Marriott Waikola Beach Resort and Spa, Hawai'i, USA, 11-14 December 201
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