Quantum face recognition protocol with ghost imaging.

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. Here, we propose a quantum machine learning algorithm for pattern recognition based on quantum principal component analysis, and quantum independent component analysis. A novel quantum algorithm for finding dissimilarity in the faces based on the computation of trace and determinant of a matrix (image) is also proposed. The overall complexity of our pattern recognition algorithm is [Formula: see text]-N is the image dimension. As an input to these pattern recognition algorithms, we consider experimental images obtained from quantum imaging techniques with correlated photons, e.g. "interaction-free" imaging or "ghost" imaging. Interfacing these imaging techniques with our quantum pattern recognition processor provides input images that possess a better signal-to-noise ratio, lower exposures, and higher resolution, thus speeding up the machine learning process further. Our fully quantum pattern recognition system with quantum algorithm and quantum inputs promises a much-improved image acquisition and identification system with potential applications extending beyond face recognition, e.g., in medical imaging for diagnosing sensitive tissues or biology for protein identification.

Phosphenes, retinal discrete dark noise, negative afterimages and retinogeniculate projections: A new explanatory framework based on endogenous ocular luminescence.

Cellular luminescence is the emission of photons by living cells due to various biophysical and biochemical processes, mostly associated with cellular metabolism. In this review paper we summarize today's understanding of four luminescence-dependent phenomena in the eye, i.e., phosphenes, retinal discrete dark noise, negative afterimages and the development of retinogeniculate projections in the brain. We review the phenomena above in the context of knowledge gained from experimental and theoretical works. Finally, we discuss this knowledge in terms of its physiological significance.

Concurrent macular corneal dystrophy and keratoconus.

A 21-year-old female presented with progressive bilateral visual loss for the past 8 years. The patient had no history of systemic disease, surgery or medications. Complete ophthalmologic examination and topography were performed. On ophthalmic examination, uncorrected visual acuity was counting fingers at 2.5 m (20/50 with pinhole) in the right and left eyes. Both corneas appeared hazy on gross examination. On slit-lamp biomicroscopy, focal grayish-white opacities with indistinct borders were noted in the superficial and deep corneal stroma of both eyes. Both corneas were thin and bulging. Corneal topography showed a pattern consistent with keratoconus. The patient underwent penetrating keratoplasty (PKP). Histopathologic studies after PKP confirmed the diagnosis of macular corneal dystrophy and keratoconus in the same eye. The patient was clinically diagnosed as a case of concurrent macular dystrophy and keratoconus, which is a very rare presentation.

Molecular detection and antimicrobial resistance of diarrheagenic Escherichia coli strains isolated from diarrheal cases.

OBJECTIVE: To identify and classify Iranian isolates of diarrheagenic Escherichia coli (E. coli) on the basis of presence of virulence genes and to determine antibiotic susceptibility of isolated strains. METHODS: The current cross-sectional study was conducted in 2005 at the Pasteur Institute, Tehran, Iran. One hundred and ninety-three diarrheagenic E. coli isolated from diarrheal patients in different regions of Iran were included in current study. Virulence factor genes for diarrheagenic E. coli were detected by polymerase chain reaction. RESULTS: Of the 193 diarrheagenic E. coli detected by PCR, 86 (44.5%) were Shiga toxin-producing E. coli STEC, 74 (38.4%) enteropathogenic E. coli EPEC, 19 (9.8%) enteroaggregative E. coli, and 14 (7.3%) enterotoxigenic E. coli isolates. Susceptibility to 12 clinically important antimicrobial agents was determined for 193 strains of diarrheagenic E. coli. A high incidence of resistance to tetracycline (63%), ampicillin (62%), streptomycin (56%), amoxicillin/clavulanic acid (44.5%), trimethoprim/sulfamethoxazole (39.5%), and cephalothin (37%) was observed. CONCLUSION: The STEC and EPEC strains with high resistance to tetracycline and ampicillin, but highly susceptible to quinolones are among the most important causative agent of diarrhea in Iran. This study suggests that antimicrobial resistance is widespread among E. coli strains colonizing Iranian patients. Guidelines for appropriate use of antibiotics in developing countries require updating.