Conditions for describing triplet states in reduced density matrix functional theory

We consider necessary conditions for the one-body-reduced density matrix (1RDM) to correspond to a triplet wave-function of a two electron system. The conditions concern the occupation numbers and are different for the high spin projections, $S_z=\pm 1$, and the $S_z=0$ projection. Hence, they can be used to test if an approximate 1RDM functional yields the same energies for both projections. We employ these conditions in reduced density matrix functional theory calculations for the triplet excitations of two-electron systems. In addition, we propose that these conditions can be used in the calculation of triplet states of systems with more than two electrons by restricting the active space. We assess this procedure in calculations for a few atomic and molecular systems. We show that the quality of the optimal 1RDMs improves by applying the conditions in all the cases we studied

Mother-child histocompatibility and risk of rheumatoid arthritis and systemic lupus erythematosus among mothers.

The study objective was to test the hypothesis that having histocompatible children increases the risk of rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE), possibly by contributing to the persistence of fetal cells acquired during pregnancy. We conducted a case control study using data from the UC San Francisco Mother Child Immunogenetic Study and studies at the Inova Translational Medicine Institute. We imputed human leukocyte antigen (HLA) alleles and minor histocompatibility antigens (mHags). We created a variable of exposure to histocompatible children. We estimated an average sequence similarity matching (SSM) score for each mother based on discordant mother-child alleles as a measure of histocompatibility. We used logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals. A total of 138 RA, 117 SLE, and 913 control mothers were analyzed. Increased risk of RA was associated with having any child compatible at HLA-B (OR 1.9; 1.2-3.1), DPB1 (OR 1.8; 1.2-2.6) or DQB1 (OR 1.8; 1.2-2.7). Compatibility at mHag ZAPHIR was associated with reduced risk of SLE among mothers carrying the HLA-restriction allele B*07:02 (n = 262; OR 0.4; 0.2-0.8). Our findings support the hypothesis that mother-child histocompatibility is associated with risk of RA and SLE

Nemo: a computational tool for analyzing nematode locomotion

The nematode Caenorhabditis elegans responds to an impressive range of chemical, mechanical and thermal stimuli and is extensively used to investigate the molecular mechanisms that mediate chemosensation, mechanotransduction and thermosensation. The main behavioral output of these responses is manifested as alterations in animal locomotion. Monitoring and examination of such alterations requires tools to capture and quantify features of nematode movement. In this paper, we introduce Nemo (nematode movement), a computationally efficient and robust two-dimensional object tracking algorithm for automated detection and analysis of C. elegans locomotion. This algorithm enables precise measurement and feature extraction of nematode movement components. In addition, we develop a Graphical User Interface designed to facilitate processing and interpretation of movement data. While, in this study, we focus on the simple sinusoidal locomotion of C. elegans, our approach can be readily adapted to handle complicated locomotory behaviour patterns by including additional movement characteristics and parameters subject to quantification. Our software tool offers the capacity to extract, analyze and measure nematode locomotion features by processing simple video files. By allowing precise and quantitative assessment of behavioral traits, this tool will assist the genetic dissection and elucidation of the molecular mechanisms underlying specific behavioral responses.Comment: 12 pages, 2 figures. accepted by BMC Neuroscience 2007, 8:8

User experience evaluation of human representation in collaborative virtual environments

Human embodiment/representation in virtual environments (VEs) similarly to the human body in real life is endowed with multimodal input/output capabilities that convey multiform messages enabling communication, interaction and collaboration in VEs. This paper assesses how effectively different types of virtual human (VH) artefacts enable smooth communication and interaction in VEs. With special focus on the REal and Virtual Engagement In Realistic Immersive Environments (REVERIE) multi-modal immersive system prototype, a research project funded by the European Commission Seventh Framework Programme (FP7/2007-2013), the paper evaluates the effectiveness of REVERIE VH representation on the foregoing issues based on two specifically designed use cases and through the lens of a set of design guidelines generated by previous extensive empirical user-centred research. The impact of REVERIE VH representations on the quality of user experience (UX) is evaluated through field trials. The output of the current study proposes directions for improving human representation in collaborative virtual environments (CVEs) as an extrapolation of lessons learned by the evaluation of REVERIE VH representation

Radial Basis Function Artificial Neural Network for the Investigation of Thyroid Cytological Lesions

Objective. This study investigates the potential of an artificial intelligence (AI) methodology, the radial basis function (RBF) artificial neural network (ANN), in the evaluation of thyroid lesions. Study Design. The study was performed on 447 patients who had both cytological and histological evaluation in agreement. Cytological specimens were prepared using liquid-based cytology, and the histological result was based on subsequent surgical samples. Each specimen was digitized; on these images, nuclear morphology features were measured by the use of an image analysis system. The extracted measurements (41,324 nuclei) were separated into two sets: the training set that was used to create the RBF ANN and the test set that was used to evaluate the RBF performance. The system aimed to predict the histological status as benign or malignant. Results. The RBF ANN obtained in the training set has sensitivity 82.5%, specificity 94.6%, and overall accuracy 90.3%, while in the test set, these indices were 81.4%, 90.0%, and 86.9%, respectively. Algorithm was used to classify patients on the basis of the RBF ANN, the overall sensitivity was 95.0%, the specificity was 95.5%, and no statistically significant difference was observed. Conclusion. AI techniques and especially ANNs, only in the recent years, have been studied extensively. The proposed approach is promising to avoid misdiagnoses and assists the everyday practice of the cytopathology. The major drawback in this approach is the automation of a procedure to accurately detect and measure cell nuclei from the digitized images

MOOC as a Way of Dissemination, Training and Learning of Telecommunication Engineering

In this chapter, the use of massive open online courses (MOOCs) for the dissemination, training capabilities and learning of telecommunication engineering is described taking as example the successful MOOC ‘Ultra- Dense Networks for 5G and its Evolution’ developed under the European innovative training network (ITN) TeamUp5G. MOOCs are usually understood as a way of teaching or learning for massive potential students. Indeed, this is the main goal of any MOOC. However, we also propose its use for training and dissemination. The ITN TeamUp5G is a training network for 15 PhD students of seven different institutions (universities and companies) where the students make research on different interconnected topics for the common goal of Ultra dense networks for 5G. At the same time they researched, they prepared a MOOC to disseminate their most recent advances and their challenges. For the MOOC, they needed to collect their thoughts, organizse their knowledge and establish a common vision of the whole system. The cooperative work, the cross-related meetings and, the preparation of all the materials for the MOOC were very interesting and useful in their training process. The whole experience of designing and creating the MOOC is described in detail along with the challenges and lessons learned.info:eu-repo/semantics/acceptedVersio

Cell-Specific Monitoring of Protein Synthesis In Vivo

Analysis of general and specific protein synthesis provides important information, relevant to cellular physiology and function. However, existing methodologies, involving metabolic labelling by incorporation of radioactive amino acids into nascent polypeptides, cannot be applied to monitor protein synthesis in specific cells or tissues, in live specimens. We have developed a novel approach for monitoring protein synthesis in specific cells or tissues, in vivo. Fluorescent reporter proteins such as GFP are expressed in specific cells and tissues of interest or throughout animals using appropriate promoters. Protein synthesis rates are assessed by following fluorescence recovery after partial photobleaching of the fluorophore at targeted sites. We evaluate the method by examining protein synthesis rates in diverse cell types of live, wild type or mRNA translation-defective Caenorhabditis elegans animals. Because it is non-invasive, our approach allows monitoring of protein synthesis in single cells or tissues with intrinsically different protein synthesis rates. Furthermore, it can be readily implemented in other organisms or cell culture systems

Microscopic Optical Projection Tomography In Vivo

We describe a versatile optical projection tomography system for rapid three-dimensional imaging of microscopic specimens in vivo. Our tomographic setup eliminates the in xy and z strongly asymmetric resolution, resulting from optical sectioning in conventional confocal microscopy. It allows for robust, high resolution fluorescence as well as absorption imaging of live transparent invertebrate animals such as C. elegans. This system offers considerable advantages over currently available methods when imaging dynamic developmental processes and animal ageing; it permits monitoring of spatio-temporal gene expression and anatomical alterations with single-cell resolution, it utilizes both fluorescence and absorption as a source of contrast, and is easily adaptable for a range of small model organisms

Harmonized gap-filled datasets from 20 urban flux tower sites

A total of 20 urban neighbourhood-scale eddy covariance flux tower datasets are made openly available after being harmonized to create a 50 site-year collection with broad diversity in climate and urban surface characteristics. Variables needed as inputs for land surface models (incoming radiation, temperature, humidity, air pressure, wind and precipitation) are quality controlled, gap-filled and prepended with 10 years of reanalysis-derived local data, enabling an extended spin up to equilibrate models with local climate conditions. For both gap filling and spin up, ERA5 reanalysis meteorological data are bias corrected using tower-based observations, accounting for diurnal, seasonal and local urban effects not modelled in ERA5. The bias correction methods developed perform well compared to methods used in other datasets (e.g. WFDE5 or FLUXNET2015). Other variables (turbulent and upwelling radiation fluxes) are harmonized and quality controlled without gap filling Site description metadata include local land cover fractions (buildings, roads, trees, grass etc.), building height and morphology, aerodynamic roughness estimates, population density and satellite imagery. This open collection can help extend our understanding of urban environmental processes through observational synthesis studies or in the evaluation of land surface environmental models in a wide range of urban settings. These data can be accessed from https://doi.org/10.5281/zenodo.7104984 (Lipson et al., 2022).Peer reviewe