Earthquake Early Warning System for Structural Drift Prediction Using Machine Learning and Linear Regressors

In this work, we explored the feasibility of predicting the structural drift from the first seconds of P-wave signals for On-site Earthquake Early Warning (EEW) applications. To this purpose, we investigated the performance of both linear least square regression (LSR) and four non-linear machine learning (ML) models: Random Forest, Gradient Boosting, Support Vector Machines and K-Nearest Neighbors. Furthermore, we also explore the applicability of the models calibrated for a region to another one. The LSR and ML models are calibrated and validated using a dataset of ∼6,000 waveforms recorded within 34 Japanese structures with three different type of construction (steel, reinforced concrete, and steel-reinforced concrete), and a smaller one of data recorded at US buildings (69 buildings, 240 waveforms). As EEW information, we considered three P-wave parameters (the peak displacement, Pd, the integral of squared velocity, IV2, and displacement, ID2) using three time-windows (i.e., 1, 2, and 3 s), for a total of nine features to predict the drift ratio as structural response. The Japanese dataset is used to calibrate the LSR and ML models and to study their capability to predict the structural drift. We explored different subsets of the Japanese dataset (i.e., one building, one single type of construction, the entire dataset. We found that the variability of both ground motion and buildings response can affect the drift predictions robustness. In particular, the predictions accuracy worsens with the complexity of the dataset in terms of building and event variability. Our results show that ML techniques perform always better than LSR models, likely due to the complex connections between features and the natural non-linearity of the data. Furthermore, we show that by implementing a residuals analysis, the main sources of drift variability can be identified. Finally, the models trained on the Japanese dataset are applied the US dataset. In our application, we found that the exporting EEW models worsen the prediction variability, but also that by including correction terms as function of the magnitude can strongly mitigate such problem. In other words, our results show that the drift for US buildings can be predicted by minor tweaks to models

A Collaborative Workflow for the Digitization of Unique Materials

This paper examines the experience of one institution, the University of Maryland Libraries, as it made organizational efforts to harness existing workflows and to capture digitization done in the course of responding to patron requests. By examining the way this organization adjusted its existing workflows to put in place more systematic methods for digital capture of unique collections, the authors hope to provide insight into the benefits and pitfalls of one model for scaling up digitization

A new algorithm for brown and black carbon identification and organic carbon detection in fine atmospheric aerosols by a multi-wavelength Aethalometer

A novel approach for the analysis of aerosol absorption coefficient measurements is presented. A 7-wavelenghts aethalometer has been employed to identify brown carbon (BrC) and black carbon (BC) and to detect organic carbon (OC) in fine atmospheric aerosols (PM2.5). The Magee Aethalometer estimates the BC content in atmospheric particulate by measuring the light attenuation in the aerosols accumulated on a quartz filter, at the standard wavelength λ = 0.88 μm. The known Magee algorithm is based on the hypothesis of a mass absorption coefficient inversely proportional to the wavelength. The new algorithm has been developed and applied to the whole spectral range; it verifies the spectral absorption behavior and, thus, it distinguishes between black and brown carbon. Moreover, it allows also to correct the absorption estimation at the UV wavelength commonly used to qualitatively detect the presence of mixed hydrocarbons. The algorithm has been applied to data collected in Agri Valley, located in Southern Italy, where torched crude oil undergoes a pre-treatment process. The Magee Aethalometer has been set to measure Aerosol absorption coefficients τaer (λ, t) every 5 min. Wavelength dependence of τaer (λ, t) has been analyzed by a best-fit technique and, excluding UV-wavelengths, both the absorption Angstrom coefficient α and the BC (or BrC) concentration have been determined. Finally, daily histograms of α provide information on optical properties of carbonaceous aerosol, while the extrapolation at UV-wavelengths gives information on the presence of semivolatile organic carbon (OC) particles

Transcriptional frameshifting rescues Citrobacter rodentium Type VI secretion by the production of two length variants from the prematurely interrupted tssM gene

The Type VI secretion system (T6SS) mediates toxin delivery into both eukaryotic and prokaryotic cells. It is composed of a cytoplasmic structure resembling the tail of contractile bacteriophages anchored to the cell envelope through a membrane complex composed of the TssL and TssM inner membrane proteins and of the TssJ outer membrane lipoprotein. The C-terminal domain of TssM is required for its interaction with TssJ, and for the function of the T6SS. In Citrobacter rodentium, the tssM1 gene does not encode the C-terminal domain. However, the stop codon is preceded by a run of 11 consecutive adenosines. In this study, we demonstrate that this poly-A tract is a transcriptional slippery site that induces the incorporation of additional adenosines, leading to frameshifting, and hence the production of two TssM1 variants, including a full-length canonical protein. We show that both forms of TssM1, and the ratio between these two forms, are required for the function of the T6SS in C. rodentium. Finally, we demonstrate that the tssM gene associated with the Yersinia pseudotuberculosis T6SS-3 gene cluster is also subjected to transcriptional frameshifting

Kinetics of DNA methylation inheritance by the Dnmt1-including complexes during the cell cycle

<p>Abstract</p> <p>Background</p> <p>The clonal transmission of lineage-specific DNA methylation patterns in a mammalian genome during the cellular division is a crucial biological process controlled by the DNA methyltransferase Dnmt1, mainly. To investigate possible dynamic mechanisms of DNA methylation inheritance during the cell cycle, we used a Proximity Ligation <it>In Situ </it>Assay (P-LISA) to analyze the kinetic of formation and DNA recruitment of Dnmt1-including complexes.</p> <p>Results</p> <p>P-LISA, sequential chromatin immunoprecipitation and quantitative methylation specific PCR revealed that the Dnmt1/PCNA/UHRF1-including complexes are mainly formed and recruited on DNA during the S-phase of cell cycle, while the formation and the DNA recruitment of several Dnmt1/transcription factors-including complexes are not S-phase dependent but are G0/G1 and/or G2/M phases dependent.</p> <p>Conclusion</p> <p>Our data confirm that DNA methylation inheritance occurs in S-phase, and demonstrate that DNA methylation inheritance can also occur in G0/G1 and G2/M phases of the cell cycle.</p

Estrogenic regulation of claudin 5 and tight junction protein 1 gene expression in zebrafish: A role on blood-brain barrier?

The blood-brain barrier (BBB) is a physical interface between the blood and the brain parenchyma, playing key roles in brain homeostasis. In mammals, the BBB is established thanks to tight junctions between cerebral endothelial cells, involving claudin, occludin, and zonula occludens proteins. Estrogens have been documented to modulate BBB permeability. Interestingly, in the brain of zebrafish, the estrogen-synthesizing activity is strong due to the high expression of Aromatase B protein, encoded by the cyp19a1b gene, in radial glial cells (neural stem cells). Given the roles of estrogens in BBB function, we investigated their impact on the expression of genes involved in BBB tight junctions. We treated zebrafish embryos and adult males with 17β-estradiol and observed an increased cerebral expression of tight junction and claudin 5 genes in adult males only. In females, treatment with the nuclear estrogen receptor antagonist (ICI182,780 ) had no impact. Interestingly, telencephalic injuries performed in males decreased tight junction gene expression that was partially reversed with 17β-estradiol. This was further confirmed by extravasation experiments of Evans blue showing that estrogenic treatment limits BBB leakage. We also highlighted the intimate links between endothelial cells and neural stem cells, suggesting that cholesterol and peripheral steroids could be taken up by endothelial cells and used as precursors for estrogen synthesis by neural stem cells. Together, our results show that zebrafish provides an alternative model to further investigate the role of steroids on the expression of genes involved in BBB integrity, both in constitutive and regenerative physiological conditions. The link we described between capillaries endothelial cells and steroidogenic neural cells encourages the use of this model in understanding the mechanisms by which peripheral steroids get into neural tissue and modulate neurogenic activity

Comparison of spheroids formed by rat glioma stem cells and neural stem cells reveals differences in glucose metabolism and promising therapeutic applications

Cancer stem cells (CSCs) are thought to be partially responsible for cancer resistance to current therapies and tumor recurrence. Dichloroacetate (DCA), a compound capable of shifting metabolism from glycolysis to glucose oxidation, via an inhibition of pyruvate dehydrogenase kinase was used. We show that DCA is able to shift the pyruvate metabolism in rat glioma CSCs but has no effect in rat neural stem cells. DCA forces CSCs into oxidative phosphorylation but does not trigger the production of reactive oxygen species and consecutive anti-cancer apoptosis. However, DCA, associated with etoposide or irradiation, induced a Bax-dependent apoptosis in CSCs in vitro and decreased their proliferation in vivo. The former phenomenon is related to DCA-induced Foxo3 and p53 expression, resulting in the overexpression of BH3-only proteins (Bad, Noxa, and Puma), which in turn facilitates Bax-dependent apoptosis. Our results demonstrate that a small drug available for clinical studies potentiates the induction of apoptosis in glioma CSCs

Novel transcriptomic panel identifies histologically active eosinophilic oesophagitis.

Eosinophilic oesophagitis (EoE) is characterised by symptoms of esophageal dysfunction and oesinophil tissue infiltration. The EoE Diagnostic Panel (EDP) can distinguish between active and non-active EoE using a set of 77 genes. Recently, the existence of distinct EoE variants featuring symptoms similar to EoE, such as oesophageal dysfunction but lacking eosinophil infiltration, had been determined. We used oesophageal biopsies from patients with histologically active (n=10) and non-active EoE (n=9) as well as from healthy oesophageal controls (n=5) participating in the Swiss Eosinophilic Esophagitis Cohort Study (SEECS) and analysed the gene expression profile in these biopsies by total RNA-sequencing (RNA-seq). Moreover, we employed the publicly accessible RNA-seq dataset (series GSE148381) as reported by Greuter et al, encompassing a comprehensive genomic profile of patients presenting with EoE variants. A novel, diagnostic gene expression panel that can effectively distinguish patients with histologically active conventional EoE from patients with EoE in histological remission and control individuals, and from three newly discovered EoE variants was identified. Histologically Active EoE Diagnostic Panel (HAEDP) consists of 53 genes that were identified based on differential expression between histologically active EoE, histological remission and controls (p≤0.05). By combining the HAEDP with EDP, we expanded our knowledge about factors that may contribute to the inflammation in EoE and improved our understanding of the underlying mechanisms of the disease. Conversely, we suggested a compact group of genes common to both HAEDP and EDP to create a reliable diagnostic tool that might enhance the accuracy of EoE diagnosis. We identified a novel set of 53 dysregulated genes that are closely associated with the histological inflammatory activity of EoE. In combination with EDP, our new panel might be a valuable tool for the accurate diagnosis of patients with EoE as well as for monitoring their disease course