Toward cognitive digital twins using a BIM-GIS asset management system for a diffused university

The integrated use of building information modeling (BIM) and geographic information system (GIS) is promising for the development of asset management systems (AMSs) for operation and maintenance (O & M) in smart university campuses. The combination of BIM-GIS with cognitive digital twins (CDTs) can further facilitate the management of complex systems such as university building stock. CDTs enable buildings to behave as autonomous entities, dynamically reacting to environmental changes. Timely decisions based on the actual conditions of buildings and surroundings can be provided, both in emergency scenarios or when optimized and adaptive performances are required. The research aims to develop a BIM-GIS-based AMS for improving user experience and enabling the optimal use of resources in the O & M phase of an Italian university. Campuses are complex assets, mainly diffused with buildings spread across the territory, managed with still document-based and fragmented databases handled by several subjects. This results in incomplete and asymmetrical information, often leading to ineffective and untimely decisions. The paper presents a methodology for the development of a BIM-GIS web-based platform (i.e., AMS-app) providing the real-time visualization of the asset in an interactive 3D map connected to analytical dashboards for management support. Two buildings of the University of Turin are adopted as demonstrators, illustrating the development of an easily accessible, centralized database by integrating spatial and functional data, useful also to develop future CDTs. As a first attempt to show the AMS app potential, crowd simulations have been conducted to understand the buildings' actual level of safety in case of fire emergency and demonstrate how CDTs could improve it. The identification of data needed, also gathered through the future implementation of suitable sensors and Internet of Things networks, is the core issue together with the definition of effective asset visualization and monitoring methods. Future developments will explore the integration of artificial intelligence and immersive technologies to enable space use optimization and real-time wayfinding during evacuation, exploiting digital tools to alert and drive users or authorities for safety improvement. The ability to easily optimize the paths with respect to the actual occupancy and conditions of both the asset and surroundings will be enabled

Hot gas flows on global and nuclear galactic scales

Since its discovery as an X-ray source with the Einstein Observatory, the hot X-ray emitting interstellar medium of early-type galaxies has been studied intensively, with observations of improving quality, and with extensive modeling by means of numerical simulations. The main features of the hot gas evolution are outlined here, focussing on the mass and energy input rates, the relationship between the hot gas flow and the main properties characterizing its host galaxy, the flow behavior on the nuclear and global galactic scales, and the sensitivity of the flow to the shape of the stellar mass distribution and the mean rotation velocity of the stars.Comment: 22 pages. Abbreviated version of chapter 2 of the book "Hot Interstellar Matter in Elliptical Galaxies", Springer 201

Functional Characterization of Cultured Keratinocytes after Acute Cutaneous Burn Injury

In addition to forming the epithelial barrier against the outside environment keratinocytes are immunologically active cells. In the treatment of severely burned skin, cryoconserved keratinocyte allografts gain in importance. It has been proposed that these allografts accelerate wound healing also due to the expression of a favourable--keratinocyte-derived--cytokine and growth factor milieu. In this study the morphology and cytokine expression profile of keratinocytes from skin after acute burn injury was compared to non-burned skin. Skin samples were obtained from patients after severe burn injury and healthy controls. Cells were cultured and secretion of selected inflammatory mediators was quantified using Bioplex Immunoassays. Immunohistochemistry was performed to analyse further functional and morphologic parameters. Histology revealed increased terminal differentiation of keratinocytes (CK10, CK11) in allografts from non-burned skin compared to a higher portion of proliferative cells (CK5, vimentin) in acute burn injury. Increased levels of IL-1α, IL-2, IL-4, IL-10, IFN-γ and TNFα could be detected in culture media of burn injury skin cultures. Both culture groups contained large amounts of IL-1RA. IL-6 and GM-CSF were increased during the first 15 days of culture of burned skin compared to control skin. Levels of VEGF, FGF-basic, TGF-ß und G-CSF were high in both but not significantly different. Cryoconservation led to a diminished mediator synthesis except for higher levels of intracellular IL-1α and IL-1ß. Skin allografts from non-burned skin show a different secretion pattern of keratinocyte-derived cytokines and inflammatory mediators compared to keratinocytes after burn injury. As these secreted molecules exert auto- and paracrine effects and subsequently contribute to healing and barrier restoration after acute burn injury therapies affecting this specific cytokine/growth factor micromilieu could be beneficial in burned patients

Dynamics of a Quantum Phase Transition and Relaxation to a Steady State

We review recent theoretical work on two closely related issues: excitation of an isolated quantum condensed matter system driven adiabatically across a continuous quantum phase transition or a gapless phase, and apparent relaxation of an excited system after a sudden quench of a parameter in its Hamiltonian. Accordingly the review is divided into two parts. The first part revolves around a quantum version of the Kibble-Zurek mechanism including also phenomena that go beyond this simple paradigm. What they have in common is that excitation of a gapless many-body system scales with a power of the driving rate. The second part attempts a systematic presentation of recent results and conjectures on apparent relaxation of a pure state of an isolated quantum many-body system after its excitation by a sudden quench. This research is motivated in part by recent experimental developments in the physics of ultracold atoms with potential applications in the adiabatic quantum state preparation and quantum computation.Comment: 117 pages; review accepted in Advances in Physic

Biochemical characterization and low-resolution SAXS shape of a novel GH11 exo-1,4-β-xylanase identified in a microbial consortium

Biotechnologies that aim to produce renewable fuels, chemicals, and bioproducts from residual ligno(hemi)cellulosic biomass mostly rely on enzymatic depolymerization of plant cell walls (PCW). This process requires an arsenal of diverse enzymes, including xylanases, which synergistically act on the hemicellulose, reducing the long and complex xylan chains to oligomers and simple sugars. Thus, xylanases play a crucial role in PCW depolymerization. Until recently, the largest xylanase family, glycoside hydrolase family 11 (GH11) has been exclusively represented by endo-catalytic β-1,4- and β-1,3-xylanases. Analysis of a metatranscriptome library from a microbial lignocellulose community resulted in the identification of an unusual exo-acting GH11 β-1,4-xylanase (MetXyn11). Detailed characterization has been performed on recombinant MetXyn11 including determination of its low-resolution small angle Xray scattering (SAXS) molecular envelope in solution. Our results reveal that MetXyn11 is a monomeric globular enzyme that liberates xylobiose from heteroxylans as the only product. MetXyn11 has an optimal activity in a pH range from 6 to 9 and an optimal temperature of 50 oC. The enzyme maintained above 65% of its original activity in the pH range 5 to 6 after being incubated for 72 h at 50 oC. Addition of the enzyme to a commercial enzymatic cocktail (CelicCtec3) promoted a significant increase of enzymatic hydrolysis yields of hydrothermally pretreated sugarcane bagasse (16% after 24 h of hydrolysis)

A CD8+ T cell transcription signature predicts prognosis in autoimmune disease.

Autoimmune diseases are common and debilitating, but their severe manifestations could be reduced if biomarkers were available to allow individual tailoring of potentially toxic immunosuppressive therapy. Gene expression-based biomarkers facilitating such tailoring of chemotherapy in cancer, but not autoimmunity, have been identified and translated into clinical practice. We show that transcriptional profiling of purified CD8(+) T cells, which avoids the confounding influences of unseparated cells, identifies two distinct subject subgroups predicting long-term prognosis in two autoimmune diseases, antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV), a chronic, severe disease characterized by inflammation of medium-sized and small blood vessels, and systemic lupus erythematosus (SLE), characterized by autoantibodies, immune complex deposition and diverse clinical manifestations ranging from glomerulonephritis to neurological dysfunction. We show that the subset of genes defining the poor prognostic group is enriched for genes involved in the interleukin-7 receptor (IL-7R) pathway and T cell receptor (TCR) signaling and those expressed by memory T cells. Furthermore, the poor prognostic group is associated with an expanded CD8(+) T cell memory population. These subgroups, which are also found in the normal population and can be identified by measuring expression of only three genes, raise the prospect of individualized therapy and suggest new potential therapeutic targets in autoimmunity

Global Analysis of DNA Methylation by Methyl-Capture Sequencing Reveals Epigenetic Control of Cisplatin Resistance in Ovarian Cancer Cell

Cisplatin resistance is one of the major reasons leading to the high death rate of ovarian cancer. Methyl-Capture sequencing (MethylCap-seq), which combines precipitation of methylated DNA by recombinant methyl-CpG binding domain of MBD2 protein with NGS, global and unbiased analysis of global DNA methylation patterns. We applied MethylCap-seq to analyze genome-wide DNA methylation profile of cisplatin sensitive ovarian cancer cell line A2780 and its isogenic derivative resistant line A2780CP. We obtained 21,763,035 raw reads for the drug resistant cell line A2780CP and 18,821,061reads for the sensitive cell line A2780. We identified 1224 hyper-methylated and 1216 hypomethylated DMRs (differentially methylated region) in A2780CP compared to A2780. Our MethylCap-seq data on this ovarian cancer cisplatin resistant model provided a good resource for the research community. We also found that A2780CP, compared to A2780, has lower observed to expected methylated CpG ratios, suggesting a lower global CpG methylation in A2780CP cells. Methylation specific PCR and bisulfite sequencing confirmed hypermethylation of PTK6, PRKCE and BCL2L1 in A2780 compared with A2780CP. Furthermore, treatment with the demethylation reagent 5-aza-dC in A2780 cells demethylated the promoters and restored the expression of PTK6, PRKCE and BCL2L1

Efficient Network Reconstruction from Dynamical Cascades Identifies Small-World Topology of Neuronal Avalanches

Cascading activity is commonly found in complex systems with directed interactions such as metabolic networks, neuronal networks, or disease spreading in social networks. Substantial insight into a system's organization can be obtained by reconstructing the underlying functional network architecture from the observed activity cascades. Here we focus on Bayesian approaches and reduce their computational demands by introducing the Iterative Bayesian (IB) and Posterior Weighted Averaging (PWA) methods. We introduce a special case of PWA, cast in nonparametric form, which we call the normalized count (NC) algorithm. NC efficiently reconstructs random and small-world functional network topologies and architectures from subcritical, critical, and supercritical cascading dynamics and yields significant improvements over commonly used correlation methods. With experimental data, NC identified a functional and structural small-world topology and its corresponding traffic in cortical networks with neuronal avalanche dynamics

Conserved and variable correlated mutations in the plant MADS protein network

<p>Abstract</p> <p>Background</p> <p>Plant MADS domain proteins are involved in a variety of developmental processes for which their ability to form various interactions is a key requisite. However, not much is known about the structure of these proteins or their complexes, whereas such knowledge would be valuable for a better understanding of their function. Here, we analyze those proteins and the complexes they form using a correlated mutation approach in combination with available structural, bioinformatics and experimental data.</p> <p>Results</p> <p>Correlated mutations are affected by several types of noise, which is difficult to disentangle from the real signal. In our analysis of the MADS domain proteins, we apply for the first time a correlated mutation analysis to a family of interacting proteins. This provides a unique way to investigate the amount of signal that is present in correlated mutations because it allows direct comparison of mutations in various family members and assessing their conservation. We show that correlated mutations in general are conserved within the various family members, and if not, the variability at the respective positions is less in the proteins in which the correlated mutation does not occur. Also, intermolecular correlated mutation signals for interacting pairs of proteins display clear overlap with other bioinformatics data, which is not the case for non-interacting protein pairs, an observation which validates the intermolecular correlated mutations. Having validated the correlated mutation results, we apply them to infer the structural organization of the MADS domain proteins.</p> <p>Conclusion</p> <p>Our analysis enables understanding of the structural organization of the MADS domain proteins, including support for predicted helices based on correlated mutation patterns, and evidence for a specific interaction site in those proteins.</p