Uterine natural killer cell heterogeneity: Lessons from mouse models

Natural killer (NK) cells are the most abundant lymphocytes at the maternal-fetal interface. Epidemiological data implicate NK cells in human pregnancy outcomes. Discoveries using mouse NK cells have guided subsequent advances in human NK cell biology. However, it remains challenging to identify mouse and human uterine NK (uNK) cell function(s) because of the dynamic changes in the systemic-endocrinological and local uterine structural microenvironments during pregnancy. This review discusses functional similarities and differences between mouse and human NK cells at the maternal-fetal interface

Gait Recognition from Motion Capture Data

Gait recognition from motion capture data, as a pattern classification discipline, can be improved by the use of machine learning. This paper contributes to the state-of-the-art with a statistical approach for extracting robust gait features directly from raw data by a modification of Linear Discriminant Analysis with Maximum Margin Criterion. Experiments on the CMU MoCap database show that the suggested method outperforms thirteen relevant methods based on geometric features and a method to learn the features by a combination of Principal Component Analysis and Linear Discriminant Analysis. The methods are evaluated in terms of the distribution of biometric templates in respective feature spaces expressed in a number of class separability coefficients and classification metrics. Results also indicate a high portability of learned features, that means, we can learn what aspects of walk people generally differ in and extract those as general gait features. Recognizing people without needing group-specific features is convenient as particular people might not always provide annotated learning data. As a contribution to reproducible research, our evaluation framework and database have been made publicly available. This research makes motion capture technology directly applicable for human recognition.Comment: Preprint. Full paper accepted at the ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), special issue on Representation, Analysis and Recognition of 3D Humans. 18 pages. arXiv admin note: substantial text overlap with arXiv:1701.00995, arXiv:1609.04392, arXiv:1609.0693

Dynamics explorer guest investigator

The use of Dynamics Explorer (DE) data sets to model the auroral inputs for the time dependent ionospheric model (TDIM) is reported. The modelling requires DE-1 SAI images and simultaneous DE-2 LAPI particle data. The data sets allow the large scale relative auroral variations and local absolute energy flexes and characteristics energies to be defined. The images enabled global scale auroral modelling with 12 min. time resolution and the LAPI data presented a detailed energy flux and characteristic energy calibration of the image model. The auroral model is used as an input to the TDIM and studies ionospheric storms

Dynamics Explorer guest investigator

The research has focused on using the SAI auroral images as a high resolution auroral precipitation input to the USU global scale ionospheric model. From the global scale modeling viewpoint, these images offer unique spatial and temporal resolution since all prior studies have used empirical auroral models. These latter models are devoid of storm, substorm, or discrete oval features. The research focused on the problems in converting images to energy flux; using LAPU data to calibrate these energy fluxes; using the USU Time Dependent Ionospheric Model (TDIM) to look at the ionospheric consequences of this structure; and then using DE-2 in-situ observations to compare with the TDIM ionospheric parameters. In carrying out these studies, several additional investigations cropped up which were pursued to help meet the overall goals. The foremost difficulty in carrying out the TDIM modeling in conjunction with the high resolution DE auroral model was that of defining an appropriate ionospheric convection pattern. Under northward conditions this pattern is very complex. In order to study Theta aurora or in general northward IMF conditions, a new model was required. Hence, a study was completed to supply this new model to drive the TDIM as a function of the IMF. With the DE auroral model having adequate resolution to show structure on the 100's of km and all model electric fields being devoid of such structure, an investigation was pursued to find out the effects of structures in the electric field on the F-region

Global Scale, Physical Models of the \u3ci\u3eF\u3c/i\u3e Region Ionosphere

During the last decade, ionospheric F region modeling has reached an accurate climatological level. We now have global computer models of the F region which simulate the interactions between physical processes in the ionosphere. Because of their complexity, these climatological models are confined to modern day supercomputers. This review focuses on the development and verification of these physical ionospheric models. Such models are distinct from local models, steady state models, and empirical models of the ionosphere, which are, by their conception, unable to represent physically the range of F region variability or storm dynamics. This review examines the limitations of the physical models, which are at the present time mainly associated with inputs to the ionospheric system. Of these, the magnetospheric electric field and auroral precipitation are by far the most dominant and yet the least well-defined dynamic inputs. Several developments are currently under way which could well lead to meteorological modeling capabilities in the next decade. For this the use of higher-resolution inputs, both temporal and spatial (for example, auroral imagery), is critical. Coupling the ionospheric models with thermospheric and magnetospheric models will lead to self-consistency and probably a predictive capability. Coupling to thermospheric models is currently under way; however, coupling with the magnetosphere must await the development of a magnetospheric model

New Czechoslovak Hyphenation Patterns, Word Lists, and Workflow

Space- and time-effective segmentation and hyphenation of natural languages stay at the core of every document preparation system, web browser, or mobile rendering system. We use the unreasonable effectiveness of pattern generation with patgen. It is possible to use hyphenation patterns to solve the dictionary problem also for close languages without compromise. In this article, we show how we applied the marvelous effectiveness of patgen for the generation of the new Czechoslovak hyphenation patterns that cover both Czech and Slovak languages. We show that developing universal, up-to-date, high-coverage and high-generalization hyphenation patterns is feasible, generated from semi-automatically prepared word lists from actual language usage. We evaluate the new approach and argue that the new Czechoslovak hyphenation patterns bring significant coverage and generalization improvements, and space savings. We share all the data, word lists, and workflow for reproducibility and usage

Foreigners on the labour market in Poland

The goal of the paper is the analysis of the scale and structure of the phenomenon of labour immigration in Poland after its accession to the European Union. Gradual liberalisation of legal regulations concerning immi-grants on Polish labour market that occurred after 2004 has had an impact on continuous increase in the number of immigrants who work legally in Poland. Citizens of Ukraine are a predominant group of foreigners. Ukrainians have dominated labour market in Poland mainly in construction sector, services in households, agriculture and also in the sector of transport services and warehousing