Analysis of the role of the p47 GTPase IIGP1 in Resistance against Intracellular Pathogens

IIGP1 is a member of the p47 GTPase family of IFNγ-induced proteins, which are among the most potent presently known mediators of cell-autonomous resistance against intracellular bacterial and protozoan pathogens in the mouse. From all studied members of this family IIGP1 is the best characterized with respect to biochemical characteristics and enzymatic activity in vitro, as well as membrane binding properties and dynamic behavior in cells. The role of the protein in intracellular defense was however, unknown and this study was set as an initial attempt to reveal it. This thesis describes the generation of an IIGP1 deficient mouse and analysis of the susceptibility of this animal to pathogens from protozoan and bacterial origin, which employ diverse strategies for host cell invasion and intracellular survival and replication. Despite having intact adaptive immune system, the IIGP1 deficient mice showed higher incidence of development of cerebral malaria after infection with Plasmodium berghei sporozoites. In addition, IIGP1 deficient astrocytes exhibited a partial loss of IFNγ-induced inhibition of Toxoplasma gondii growth. IIGP1 deficient animals were not susceptible to infection with Leishmania major, Listeria monocytogenes, Chlamydia trachomatis and Anaplasma phagocytophilum. From the analysis of the obtained data in the context of the intracellular lifestyle of the pathogens involved in this study, we concluded that IIGP1 seems to be specifically involved in defense against protozoan parasites, which like Pl. berghei and T. gondii reside in non-fusigenic parasitophorous vacuoles after entering cells. The mechanisms of IIGP1-dependent protection of cells against these pathogens remain to be studied

Algebraic Approach to Molecular thermodynamics

An algebraic model based on Lie-algebraic and discrete symmetry techniques is applied to the analysis of thermodynamic vibrational properties of molecules. The local anharmonic effects are described by a Morse-like potential and the corresponding anharmonic bosons are associated with the SU(2) algebra. A vibrational high-temperature partition function and the related thermodynamic functions are derived and studied in terms of the parameters of the model. The idea of a critical temperature is introduced in relation with the specific heat. A physical interpretation of a quantum deformation associated with the model is given.Comment: 18 pages, 6 figures, submitted to J Physics: Condensed Matte

Real-Time Grasp Detection Using Convolutional Neural Networks

We present an accurate, real-time approach to robotic grasp detection based on convolutional neural networks. Our network performs single-stage regression to graspable bounding boxes without using standard sliding window or region proposal techniques. The model outperforms state-of-the-art approaches by 14 percentage points and runs at 13 frames per second on a GPU. Our network can simultaneously perform classification so that in a single step it recognizes the object and finds a good grasp rectangle. A modification to this model predicts multiple grasps per object by using a locally constrained prediction mechanism. The locally constrained model performs significantly better, especially on objects that can be grasped in a variety of ways.Comment: Accepted to ICRA 201

Developments in the Agricultural and Rural Capital Market of the Former Yugoslav Republic of Macedonia

The undeveloped rural capital market in the Former Yugoslav Republic of Macedonia is constrained by an urban–rural development gap, with limited capacities for rural development and imperfections in the rural capital market. Among the most striking hindrances are the illegal status of a large share of agricultural buildings and other real estate in rural areas, particularly on the individual family farms that prevail in the country, and the insufficient knowledge and abilities of individual farmers in applying for credit. National, EU and other donor funds are being used to improve knowledge, skills and other human resources, and to address the illegal status of buildings and facilities. During the most recent years, government support for agricultural, rural and regional development has been introduced to promote good agricultural practices, production and economic activity in rural areas. The elimination of imperfections and improvements to the functioning of the capital market – making access to credit and funds easier, especially for small-scale family farms and for rural development – are seen as measures contributing to agriculture and more balanced rural and regional development.

Geometry-Based Next Frame Prediction from Monocular Video

We consider the problem of next frame prediction from video input. A recurrent convolutional neural network is trained to predict depth from monocular video input, which, along with the current video image and the camera trajectory, can then be used to compute the next frame. Unlike prior next-frame prediction approaches, we take advantage of the scene geometry and use the predicted depth for generating the next frame prediction. Our approach can produce rich next frame predictions which include depth information attached to each pixel. Another novel aspect of our approach is that it predicts depth from a sequence of images (e.g. in a video), rather than from a single still image. We evaluate the proposed approach on the KITTI dataset, a standard dataset for benchmarking tasks relevant to autonomous driving. The proposed method produces results which are visually and numerically superior to existing methods that directly predict the next frame. We show that the accuracy of depth prediction improves as more prior frames are considered.Comment: To appear in 2017 IEEE Intelligent Vehicles Symposiu