Face recognition is one of the most ubiquitous examples of pattern recognition in machine learning, with numerous applications in security, access control, and law enforcement, among many others. Pattern recognition with classical algorithms requires significant computational resources, especially when dealing with high-resolution images in an extensive database. Quantum algorithms have been shown to improve the efficiency and speed of many computational tasks, and as such, they could also potentially improve the complexity of the face recognition process.
View Article and Find Full Text PDFProtonated azobenzene (AB), H(CHNCH), has been studied using threshold collision-induced dissociation in a guided ion beam tandem mass spectrometer. Product channels observed are CHN + CH and CH + N + CH. The experimental kinetic energy-dependent cross sections were analyzed using a statistical model that accounts for internal and kinetic energy distributions of the reactants, multiple collisions, and kinetic shifts.
View Article and Find Full Text PDFChemical bonding and the electronic structure of the trans 2,2',6,6'-tetrafluoroazobenzene negative ion have been studied using collision-induced dissociation as well as photodetachment-photoelectron spectroscopy and the experimental results for different properties were compared with the corresponding values calculated using ab initio quantum chemistry methods. The trans 2,2',6,6'-tetrafluoroazobenzene anion was prepared by atmospheric pressure chemical ionization for the collision induced dissociation (CID) experiment and through thermal electron attachment in the photodetachment-photoelectron spectroscopy experiments. The adiabatic electron affinity of trans 2,2',6,6'-tetrafluoroazobenzene was measured to be 1.
View Article and Find Full Text PDFBackground: Staphylococcus aureus, the major virulence factor of hospital and community acquired infections, secretes numerous exotoxins (super antigens), which may affect immunological and inflammatory status in psoriatic skin lesion.
Objectives: This study is designed to compare the S. aureus super antigens level in sera of psoriatic patients with normal cases (nevus).