Robust Gravitational Wave Burst Detection and Source Localization in a Network of Interferometers Using Cross Wigner Spectra

We discuss a fast cross-Wigner transform based technique for detecting gravitational wave bursts, and estimating the direction of arrival, using a network of (three) non co-located interferometric detectors. The performances of the detector as a function of signal strength and source location, and the accuracy of the direction of arrival estimation are investigated by numerical simulations.Comment: accepted in Class. Quantum Gravit

Statistical Parameters of Steel Rebars of Reinforced Concrete Existing Structures

Historical and cognitive investigations supported by in-situ and/or laboratory tests are needed for a robust reliability assessment of existing structures. Indeed, an adequate knowledge of material properties and their statistical description is the basis for carrying out accurate reliability analyses and verifications on the investigated structures. In this paper, a procedure for the definition of pdfs of mechanical parameters of steel rebars is proposed based on secondary experimental test data. This information is very helpful for the reliability assessment of existing r.c. buildings, where estimation of statistical parameters of mechanical properties of steel reinforcement is very difficult. In fact. It must be highlighted on the one hand that direct information about the examined structure are commonly not sufficient, on the other hand that the number of rebar samples extracted from the structure, if available, is so limited that it does not allow a complete statistical analysis. The first step has been the collection of experimental acceptance tests carried out by Department of Civil and Industrial Engineering of University of Pisa on steel rebars of reinforced concrete (r.c.) structures during the 1960s. The yield strength and the tensile strength are extrapolated for each sample defining a significant database of experimental test results for existing r.c. structures. Then, probability distribution models for the mechanical properties of steel reinforcement have been defined as already done by the authors for concrete strength. A cluster analysis has been carried out based on the Gaussian Mixture Model applying the Expectation-Maximization algorithm to identify homogeneous material classes and their associated pdfs of material mechanical parameters. The main advantage of proposed procedure consists in its “blindness”, In fact, not requiring subjective information like pre-classification of data, the methodology is not sensitive to alterations caused by engineering judgement or by inexact identification of declared strength class of the tested samples, due for example to downgraded materials

Influence of pore water chemistry on hydaulic conductivity of kaolinite suspensions

The role of pore water chemistry on particle aggregation and soil formation during sedimentation process has been investigated for a kaolinite clay suspensions. The modification of surfaces charge properties of clay minerals induced by different pore water chemistry rules the particles arrangement. As a consequence, at volume scale the sedimentation behaviour and in turn the physical, mechanical and hydraulic behaviour of the formed soil skeleton are changed. Sedimentation tests on several suspensions showed the influence of different aggregation on settling and self-weight consolidation stages. Hydraulic conductivity of kaolin suspensions has been estimated from the settling velocity recorded in sedimentation tests. Test results showed the relevant dependency of the hydraulic conductivity of the clay suspensions on the particle arrangement induced by the pore water chemistry

Combining Machine Learning Analysis and Incentive-Based Genetic Algorithms to Optimise Energy District Renewable Self-Consumption in Demand-Response Programs

The recent rise of renewable energy sources connected to the distribution networks and the high peak consumptions requested by electric vehicle-charging bring new challenges for network operators. To operate smart electricity grids, cooperation between grid-owned and third-party assets becomes crucial. In this paper, we propose a methodology that combines machine learning with multi-objective optimization to accurately plan the exploitation of the energy district&rsquo s flexibility with the objective of reducing peak consumption and avoiding reverse power flow. Using historical data, acquired by the smart meters deployed on the pilot district, the district&rsquo s power profile can be predicted daily and analyzed to identify potentially critical issues on the network. District&rsquo s resources, such as electric vehicles, charging stations, photovoltaic panels, buildings energy management systems, and energy storage systems, have been modeled by taking into account their operational constraints and the multi-objective optimization has been adopted to identify the usage pattern that better suits the distribution operator&rsquo s (DSO) needs. The district is subject to incentives and penalties based on its ability to respond to the DSO request. Analysis of the results shows that this methodology can lead to a substantial reduction of both the reverse power flow and peak consumption. Document type: Articl

Mas Mahal sa UP Kaysa DLSU: Isang Alternatibong Pagsusukat sa Gastos ng Edukasyon

May saysay ang pagsusukat sa gastos ng edukasyon upang matantiya ang kinakailangang yaman ng mga pamilya at ng pamahalaan sa pagpopondo ng lalong mataas na edukasyon. Sinuri ang normatibong pagpopondo bilang pamantayan sa alokasyon ng pondo sa mga pampublikong pamantasan at kolehiyo. Nagbalik tanaw sa mga pag-aaral sa pagsusukat ng gastos sa edukasyon sa loob at labas ng bansa. Dahil sa hirap ng paglikom ng datos nagpanukala ng isang modelo ng pagsukat sa gastos ng edukasyon batay sa konsepto ng pangkaraniwang guro. Ayon sa mga tinantiyang sukat mula sa modelong binalangkas, ang gastos bawat yunit ay halos kapantay ng tuition na sinisingil ng mga pribadong pamantasan at kolehiyo. Samantala, sa mga pampublikong institusyon, ang binabayarang tuition ng mga estudyante ay maliit na proporsyon lamang ng gastos na pinopondohan ng pamahalaan. May pagkakataon na mas mahal ang pampublikong pamantasan kaysa pribadong institusyon. Dahil dito dapat pag-isipan ng pamahalaan ang mga alternatibo sa tuwirang pagpapatakbo ng mga pampublikong pamantasan at kolehiyo sa harap ng pagiging episyente ng mga pribadong pamantasan at kolehiyo

Oxidative Stress in Non-Alcoholic Fatty Liver Disease

Non-alcoholic fatty liver disease (NAFLD) is a challenging disease caused by multiple factors, which may partly explain why it still remains an orphan of adequate therapies. This review highlights the interaction between oxidative stress (OS) and disturbed lipid metabolism. Several reactive oxygen species generators, including those produced in the gastrointestinal tract, contribute to the lipotoxic hepatic (and extrahepatic) damage by fatty acids and a great variety of their biologically active metabolites in a “multiple parallel-hit model”. This leads to inflammation and fibrogenesis and contributes to NAFLD progression. The alterations of the oxidant/antioxidant balance affect also metabolism-related organelles, leading to lipid peroxidation, mitochondrial dysfunction, and endoplasmic reticulum stress. This OS-induced damage is at least partially counteracted by the physiological antioxidant response. Therefore, modulation of this defense system emerges as an interesting target to prevent NAFLD development and progression. For instance, probiotics, prebiotics, diet, and fecal microbiota transplantation represent new therapeutic approaches targeting the gut microbiota dysbiosis. The OS and its counter-regulation are under the influence of individual genetic and epigenetic factors as well. In the near future, precision medicine taking into consideration genetic or environmental epigenetic risk factors, coupled with new OS biomarkers, will likely assist in noninvasive diagnosis and monitoring of NAFLD progression and in further personalizing treatments

Discovering Genotype Variants in an Infant with VACTERL through Clinical Exome Sequencing: A Support for Personalized Risk Assessment and Disease Prevention

Abstract: Congenital anomalies may have an increased risk of noncommunicable diseases (NCDs) We performed a clinical exome analysis in an infant affected by “Vertebral, Anorectal, Cardiac, Tracheoesophageal, Genitourinary, and Limb” (VACTERL) malformation association to identify potential biomarkers that may be helpful for preventing malignancy risk or other chronic processes. Among the variants, six variants that may be linked with VACTERL were identified in the exome analysis. The variants c.501G>C on OLR1 and c.-8C>G on PSMA6 were previously associated with myocardial infarction. The variants c.1936A>G on AKAP10 and c.575A>G on PON1 are linked to defects in cardiac conduction and artery disease, respectively. Alterations in metabolism were also suggested by the variants c.860G>A on EPHX2 and c.214C>A on GHRL. In addition, three variants associated with colon cancer were discovered. Specifically, the reported variants were c.723G>A on CCND1 and c.91T>A on AURKA proto-oncogenes as well as c.827A>C in the tumor suppressor PTPRJ. A further inspection identified 15 rare variants carried by cancer genes. Specifically, these mutations are located on five tumor suppressors (SDHA, RB1CC1, PTCH1, DMBT1, BCR) and eight proto-oncogenes (MERTK, CSF1R, MYB, ROS1, PCM1, FGFR2, MYH11, BRCC3) and have an allele frequency lower than 0.01 in the Genome Aggregation Database (GnomAD).We observed that the cardiac and metabolic phenotypic traits are linked with the genotype of the patient. In addition, the risk of developing neoplasia cannot be excluded a priori. Long-term surgical issues of patients with VATER syndrome could benefit from the clinical exome sequencing of a personalized risk assessment for the appearance of further disease in pubertal timing and adult age