k-Same-Siamese-GAN: k-Same Algorithm with Generative Adversarial Network for Facial Image De-identification with Hyperparameter Tuning and Mixed Precision Training

For a data holder, such as a hospital or a government entity, who has a privately held collection of personal data, in which the revealing and/or processing of the personal identifiable data is restricted and prohibited by law. Then, "how can we ensure the data holder does conceal the identity of each individual in the imagery of personal data while still preserving certain useful aspects of the data after de-identification?" becomes a challenge issue. In this work, we propose an approach towards high-resolution facial image de-identification, called k-Same-Siamese-GAN, which leverages the k-Same-Anonymity mechanism, the Generative Adversarial Network, and the hyperparameter tuning methods. Moreover, to speed up model training and reduce memory consumption, the mixed precision training technique is also applied to make kSS-GAN provide guarantees regarding privacy protection on close-form identities and be trained much more efficiently as well. Finally, to validate its applicability, the proposed work has been applied to actual datasets - RafD and CelebA for performance testing. Besides protecting privacy of high-resolution facial images, the proposed system is also justified for its ability in automating parameter tuning and breaking through the limitation of the number of adjustable parameters

Effective reduction of CSF partial volume effect in DTI by acquiring additional DWIs with smaller β-value

Diffusion: ADC & DTI Methods - Poster presentationOne of the major limitations of DTI is its vulnerability to CSF contamination. To remove such effect, FLAIR preparation and the two-compartment tensor model have been proposed. However, they require substantially increased scan time (and lead to reduced brain tissue SNR in the former case). A simple and effective approach is proposed in the current study. Diffusion tensor (DT) was computed from diffusion-weighted images acquired with b-value=500 and 1000s/mm2. Experiments were performed in volunteers and rodents to compare this approach and conventional DTI, demonstrating effective reduction of CSF contamination.published_or_final_versionThe 17th Scientific Meeting & Exhibition of the International Society of Magnetic Resonance in Medicine (ISMRM), Honolulu, HI., 18-24 April 2009. In Proceedings of ISMRM 17th Scientific Meeting & Exhibition, 2009, p. 357

Characterization and evaluation of Ni/SiO catalysts for hydrogen production and tar reduction from catalytic steam pyrolysis-reforming of refuse derived fuel

A series of Ni/SiO catalysts have been prepared and investigated for their suitability for hydrogen production and tar reduction in a two-stage pyrolysis-reforming system, using refuse derived fuel (RDF) as the raw material. Experiments were conducted at a pyrolysis temperature of 600°C, and a reforming temperature of 800°C. The product gases were analysed by gas chromatography (GC) and the condensed fraction was collected and quantified using gas chromatography-mass spectrometry (GC-MS). The effects of the catalyst preparation method, nickel content and the addition of metal promoters (Ce, Mg, Al), were investigated. Catalysts were characterised using BET surface area analysis, temperature programmed oxidation (TPO), and scanning electron microscopy (SEM). The TPO and SEM analysis of the reacted catalysts showed that amorphous type carbons tended to be deposited over the Ni/SiO catalysts prepared by impregnation, while filamentous type carbons were favoured with the sol-gel prepared catalysts. The influence of catalyst promoters (Ce, Mg, Al) added to the Ni/SiO catalyst prepared by the sol-gel method was found not to be significant, as the H production was not increased and the tar formation was not reduced with the metal-added catalyst. The highest H concentration of 57.9vol.% and lower tar amount produced of 0.24mg/g; were obtained using the 20wt.% Ni/SiO catalyst prepared by sol-gel. On the other hand a low catalytic activity for H production and higher tar produced were found for the impregnated series of catalysts, which might be due to the smaller surface area, pore size and due to the formation of amorphous carbons on the catalyst surface. Alkenes and alcohol functional groups were mainly found in the analysed tar samples, with major concentrations of styrene, phenol, indene, cresols, naphthalene, fluorene, and phenanthrene

Exploring Flaring Behaviour on Low Mass Stars, Solar-type Stars and the Sun

We report on our project to study the activity in both the Sun and low mass stars. Utilising high cadence, Hα observations of a filament eruption made using the CRISP spectropolarimeter mounted on the Swedish Solar Telescope has allowed us to determine 3D velocity maps of the event. To gain insight into the physical mechanism which drives the event we have qualitatively compared our observation to a 3D MHD reconnection model. Solar-type and low mass stars can be highly active producing flares with energies exceeding erg. Using K2 and TESS data we find no correlation between the number of flares and the rotation phase which is surprising. Our solar flare model can be used to aid our understanding of the origin of flares in other stars. By scaling up our solar model to replicate observed stellar flare energies, we investigate the conditions needed for such high energy flares

Coordination of metronidazole to Cu(II): Structural characterization of a mononuclear square-planar compound Joshua H.

The reaction between metronidazole [1-(2-hydroxyethyl)-2-methyl-5-nitroimidazole, MET] and CuCl2•2H2O in methanol solution has allowed isolation of blue crystals of composition Cu(MET)2Cl2•MeOH. These crystals have been shown by X-ray diffraction to consist of mononuclear square-planar trans-Cu(MET)2Cl2 molecules in which the metronidazole ligands are trans to each other, as are the Cl ligands. The structure of this compound is very different from other compounds that have been obtained from the reaction between CuCl2•2H2O and metronidazole, namely [Cu(MET)2(μ-Cl)Cl]2 and [Cu(MET)2(μ-Cl)(OH2)]2[Cl]2, which are dimers featuring bridging chloride ligands

Chemokine control of HIV-1 infection: Beyond a binding competition

A recent paper by Cameron et al. demonstrated that certain chemokines such as CCL19 activate cofilin and actin dynamics, promoting HIV nuclear localization and integration into resting CD4 T cells. Apparently, these chomokines synergize with the viral envelope protein, triggering cofilin and actin dynamics necessary for the establishment of viral latency. This study opens a new avenue for understanding chemokine interaction with HIV. Traditionally, chemokine control of HIV infection focuses on competitive binding and down-modulation of the corecptors, particularly CCR5. This new study suggests that a diverse group of chemokines may also affect HIV infection through synergistic or antagonistic interaction with the viral coreceptor signaling pathways

Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking

Discriminative Correlation Filters (DCF) have demonstrated excellent performance for visual object tracking. The key to their success is the ability to efficiently exploit available negative data by including all shifted versions of a training sample. However, the underlying DCF formulation is restricted to single-resolution feature maps, significantly limiting its potential. In this paper, we go beyond the conventional DCF framework and introduce a novel formulation for training continuous convolution filters. We employ an implicit interpolation model to pose the learning problem in the continuous spatial domain. Our proposed formulation enables efficient integration of multi-resolution deep feature maps, leading to superior results on three object tracking benchmarks: OTB-2015 (+5.1% in mean OP), Temple-Color (+4.6% in mean OP), and VOT2015 (20% relative reduction in failure rate). Additionally, our approach is capable of sub-pixel localization, crucial for the task of accurate feature point tracking. We also demonstrate the effectiveness of our learning formulation in extensive feature point tracking experiments. Code and supplementary material are available at http://www.cvl.isy.liu.se/research/objrec/visualtracking/conttrack/index.html.Comment: Accepted at ECCV 201