624 research outputs found
Frustration driven structural distortion in VOMoO4
Nuclear magnetic resonance (NMR), electron paramagnetic resonance (EPR),
magnetization measurements and electronic structure calculations in VOMoO4 are
presented. It is found that VOMoO4 is a frustrated two-dimensional
antiferromagnet on a square lattice with competing exchange interactions along
the side J1 and the diagonal J2 of the square. From magnetization measurements
J1+J2 is estimated around 155 K, in satisfactory agreement with the values
derived from electronic structure calculations. Around 100 K a structural
distortion, possibly driven by the frustration, is evidenced. This distortion
induces significant modifications in the NMR and EPR spectra which can be
accounted for by valence fluctuations. The analysis of the spectra suggests
that the size of the domains where the lattice is distorted progressively grows
as the temperature approaches the transition to the magnetic ground state at
Tc=42 K
Prediction-based classification for longitudinal biomarkers
Assessment of circulating CD4 count change over time in HIV-infected subjects
on antiretroviral therapy (ART) is a central component of disease monitoring.
The increasing number of HIV-infected subjects starting therapy and the limited
capacity to support CD4 count testing within resource-limited settings have
fueled interest in identifying correlates of CD4 count change such as total
lymphocyte count, among others. The application of modeling techniques will be
essential to this endeavor due to the typically nonlinear CD4 trajectory over
time and the multiple input variables necessary for capturing CD4 variability.
We propose a prediction-based classification approach that involves first stage
modeling and subsequent classification based on clinically meaningful
thresholds. This approach draws on existing analytical methods described in the
receiver operating characteristic curve literature while presenting an
extension for handling a continuous outcome. Application of this method to an
independent test sample results in greater than 98% positive predictive value
for CD4 count change. The prediction algorithm is derived based on a cohort of
HIV-1 infected individuals from the Royal Free Hospital, London who
were followed for up to three years from initiation of ART. A test sample
comprised of individuals from Philadelphia and followed for a similar
length of time is used for validation. Results suggest that this approach may
be a useful tool for prioritizing limited laboratory resources for CD4 testing
after subjects start antiretroviral therapy.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS326 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Atmospheric nitrogen deposition in a highly human impacted area in northern Italy
Nitrogen can enter the water cycle through atmospheric depositions on ground and water surfaces, leakages from point and diffuse sources (i.e., sewage treatment plants or sewage systems, fertilizer and manure applications), and erosion processes affecting nitrogen rich soils (EEA, 2005). However, integrating all nitrogen forms, processes and scales is still a major challenge for the understanding and the management of the nitrogen cycle
Post-Depositional Biodegradation Processes of Pollutants on Glacier Surfaces
Glaciers are important fresh-water reservoirs for our planet. Although they are often
located at high elevations or in remote areas, glacial ecosystems are not pristine, as many pollutants
can undergo long-range atmospheric transport and be deposited on glacier surface, where they
can be stored for long periods of time, and then be released into the down-valley ecosystems.
Understanding the dynamics of these pollutants in glaciers is therefore important for assessing their
environmental fate. To this aim, it is important to study cryoconite holes, small ponds filled with
water and with a layer of sediment, the cryoconite, at the bottom, which occur on the surface of
most glaciers. Indeed, these environments are hotspots of biodiversity on glacier surface as they host
metabolically active bacterial communities that include generalist taxa able to degrade pollutants.
In this work, we aim to review the studies that have already investigated pollutant (e.g., chlorpyrifos
and polychlorinated-biphenyls (PCBs)) degradation in cryoconite holes and other supraglacial
environmental matrices. These studies have revealed that bacteria play a significant role in pollutant
degradation in these habitats and can be positively selected in contaminated environments. We will
also provide indication for future research in this field
Modeling an Industrial Revolution: How to Manage Large-Scale, Complex IoT Ecosystems?
Advancements around the modern digital industry gave birth to a number of closely interrelated concepts: in the age of the Internet of Things (IoT), System of Systems (SoS), Cyber-Physical Systems (CPS), Digital Twins and the fourth industrial revolution, everything revolves around the issue of designing well-understood, sound and secure complex systems while providing maximum flexibility, autonomy and dynamics.The aim of the paper is to present a concise overview of a comprehensive conceptual framework for integrated modeling and management of industrial IoT architectures, supported by actual evidence from the Arrowhead Tools project; in particular, we adopt a three-dimensional projection of our complex engineering space, from modeling the engineering process to SoS design and deployment.In particular, we start from modeling principles of the the engineering process itself. Then, we present a design-time SoS representation along with a toolchain concept aiding SoS design and deployment. This brings us to reasoning about what potential workflows are thinkable for specifying comprehensive toolchains along with their data exchange interfaces. We also discuss the potential of aligning our vision with RAMI4.0, as well as the utilization perspectives for real-life engineering use-cases
Poorly differentiated clusters (PDC) in colorectal cancer: Does their localization in tumor matter?
Poorly differentiated clusters (PDC) are aggregates of at least five neoplastic cells lacking evidence of glandular differentiation. By definition, they can be present at the invasive front (peripheral PDC or pPDC) and within the tumor stroma (central PDC or cPDC). In colorectal cancer (CRC), PDC are considered adverse prognosticators and seem to reflect epithelial mesenchymal transition (EMT). In this study, we have investigated the immuno-expression of two EMT-related proteins, E-cadherin and β-catenin, in PDC of primary CRCs and matched liver metastases. pPDC always showed nuclear β-catenin staining and diffusely reduced/absence of E-cadherin expression as opposed cPDC which showed nuclear β-catenin immunoreactivity and E-cadherin expression in about 50% of cases. In addition, the pattern of β-catenin and E-cadherin expression differed between PDC and the main tumor, and between primary CRC and liver metastasis (LM), in a percentage of cases. A discordant pattern of β-catenin and E-cadherin expression between pPDC and cPDC, between main tumor and cPDC, and between primary CRC and LM, confirms that EMT is a dynamic and reversible process in CRC. On the overall, this suggests that pPDC and cPDC are biologically different. We may advocate that PDC develop at the tumor center (cPDC) and then some of them migrate towards the tumor periphery while progressively completing EMT process (pPDC). Based on these results, PDC presence and counting may have different prognostic relevance if the assessment is done at the invasive front of the tumor or in the intratumor stroma
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