Luminescence of sapphire single crystals irradiated with high-power ion beams

Optical absorption, photo- and cathodoluminescence of a sapphire single crystal (α-Al 2 O 3 ) exposed to pulsed nanosecond radiation with high-power ion beams C + /H + with an energy of 300 keV and energy density 0.5-1.5 J/cm 2 were first investigated in this work. It was found that under ion irradiation accompanied by heating of sapphire up to melting, the formation of F-type centers and their aggregates associated with oxygen vacancies was observed in the crystals under study. These centers have luminescence bands at 330, 410 and 500 nm which depend on the type and wavelength of the optical excitation. The appearance of a new PL emission at 435 nm, presumably associated with a complex vacancy-impurity defect, was also observed in the photoluminescence spectra. © Published under licence by IOP Publishing Ltd.The work was supported by the initiative scientific project № 16.5186.2017/8.9 of the Ministry of Education and Science of the Russian Federation. Experiments on ion irradiation of sapphire was done at the KIPT as a part of the state task

Anomalous Transient Current in Nonuniform Semiconductors

Nonequilibrium processes in semiconductors are considered with highly nonuniform initial densities of charge carriers. It is shown that there exist such distributions of charge densities under which the electric current through a sample displays quite abnormal behaviour flowing against the applied voltage. The appearance of this negative electric current is a transient phenomenon occurring at the initial stage of the process. After this anomalous negative fluctuation, the electric current becomes normal, i.e. positive as soon as the charge density becomes more uniform. Several possibilities for the practical usage of this effect are suggested.Comment: 1 file, 11 pages, RevTex, no figure

Luminescent Properties of Nanostructured Al2O3 Ceramics Irradiated with C+/H+ Pulsed Ion Beams

The luminescent properties of nanostructured α-Al2O3 ceramics irradiated with C+/H+ pulsed ion beams have been studied. The relationship between changes in the TL properties of ceramics and the formation of radiation defects under irradiation is discussed

Dynamics of Multiple Trafficking Behaviors of Individual Synaptic Vesicles Revealed by Quantum-Dot Based Presynaptic Probe

Although quantum dots (QDs) have provided invaluable information regarding the diffusive behaviors of postsynaptic receptors, their application in presynaptic terminals has been rather limited. In addition, the diffraction-limited nature of the presynaptic bouton has hampered detailed analyses of the behaviors of synaptic vesicles (SVs) at synapses. Here, we created a quantum-dot based presynaptic probe and characterized the dynamic behaviors of individual SVs. As previously reported, the SVs exhibited multiple exchanges between neighboring boutons. Actin disruption induced a dramatic decrease in the diffusive behaviors of SVs at synapses while microtubule disruption only reduced extrasynaptic mobility. Glycine-induced synaptic potentiation produced significant increases in synaptic and inter-boutonal trafficking of SVs, which were NMDA receptor- and actin-dependent while NMDA-induced synaptic depression decreased the mobility of the SVs at synapses. Together, our results show that sPH-AP-QD revealed previously unobserved trafficking properties of SVs around synapses, and the dynamic modulation of SV mobility could regulate presynaptic efficacy during synaptic activity

Machine learning with different digital images classification in laparoscopic surgery

The evaluation of the effectiveness of the automatic computer diagnostic (ACD) systems developed based on two classifiers – HAAR features cascade and AdaBoost for the laparoscopic diagnostics of appendicitis and ovarian cysts in women with chronic pelvic pain is presented. The training of HAAR features cascade, and AdaBoost classifiers were performed with images/ frames, which have been extracted from video gained in laparoscopic diagnostics. Both gamma-corrected RGB and RGB converted into HSV frames were used for training. Descriptors were extracted from images with the method of Local Binary Pattern (LBP), which includes both data on color characteristics («modified color LBP» - MCLBP) and textural characteristics, which have been used later on for AdaBoost classifier training. Classification of test video images revealed that the highest recall for appendicitis diagnostics was achieved after training of AdaBoost with MCLBP descriptors extracted from RGB images – 0.708, and in the case of ovarian cysts diagnostics – for MCLBP gained from RGB images – 0.886. Developed AdaBoost-based ACD system achieved a 73.6% correct classification rate (accuracy) for appendicitis and 85.4% for ovarian cysts. The accuracy of the HAAR features classifier was highest in the case of ovarian cysts identification and achieved 0.653 (RGB) – 0.708 (HSV) values. It was concluded that the HAAR feature-based cascade classifier turned to be less effective when compared with the AdaBoost classifier trained with MCLBP descriptors. Ovarian cysts were better diagnosed when compared with appendicitis with the developed ACD

Digital images classification in automatic laparoscopic diagnostics

The aim: To evaluate the automatic computer diagnostic (ACD) systems, which were developed, based on two classi!ers–HAAR features cascade and AdaBoost for the laparoscopic diagnostics of appendicitis and ovarian cysts in women with chronic pelvic pain. Materials and methods: The training of HAAR features cascade, and AdaBoost classi!ers were performed with images/ frames of laparoscopic diagnostics. Both gamma-corrected RGB and RGB converted into HSV frames were used for training. Descriptors were extracted from images with the method of Local Binary Pattern (LBP), which includes both data on color characteristics («modi!ed color LBP»-MCLBP) and textural features. Results: Classi!cation of test video images revealed that the highest recall for appendicitis diagnostics was achieved after training of AdaBoost with MCLBP descriptors extracted from RGB images – 0.708, and in the case of ovarian cysts diagnostics – for MCLBP gained from RGB images – 0.886 (P<0.05). Developed AdaBoost-based ACD system achieved a 73.6% correct classi!cation rate (accuracy) for appendicitis and 85.4% for ovarian cysts. The accuracy of the HAAR features classi!er was highest in the case of ovarian cysts identi!cation and achieved 0,653 (RGB) – 0,708 (HSV) values (P<0.05). Conclusions: The HAAR feature-based cascade classi!er turned out to be less e"ective when compared with the AdaBoost classi!er trained with MCLBP descriptors. Ovarian cysts were better diagnosed when compared with appendicitis with the developed ACD