Simulation of Shaking Table Tests to Study Soil-Structure Interaction by Means of Two Different Constitutive Models

The paper presents the main results of a FEM 3-D model reproducing a physical model subjected to shaking table tests. The tests, performed at the EERC laboratory of Bristol University, have been simulated by means of a new numerical model based on a recent constitutive model characterized by isotropic and kinematic hardening and devoted to granular soil. The shaking table tests have been performed using: a six-degree of freedom shaking table; a shear-stack; a scaled one-storey steel frame; the Leigthon Buzzard Sand. The tests have been characterized by 11 shaking runs. As regards the 3-D numerical modeling, the linear elastic material has been considered for the structure, instead the soil has been modeled both with a cap-hardening Drucker-Prager model, often implemented in commercial codes, and with the above mentioned new constitutive model, implemented in the utilized FEM code by the Research Group of Catania University. Thanks to the great quantity of experimental data, the power of the proposed numerical model in simulation/prediction of dynamic soil-structure interaction can be verified and compared with the capability of other numerical models based on simpler constitutive models

Probabilistic Timed Automata with Clock-Dependent Probabilities

Probabilistic timed automata are classical timed automata extended with discrete probability distributions over edges. We introduce clock-dependent probabilistic timed automata, a variant of probabilistic timed automata in which transition probabilities can depend linearly on clock values. Clock-dependent probabilistic timed automata allow the modelling of a continuous relationship between time passage and the likelihood of system events. We show that the problem of deciding whether the maximum probability of reaching a certain location is above a threshold is undecidable for clock-dependent probabilistic timed automata. On the other hand, we show that the maximum and minimum probability of reaching a certain location in clock-dependent probabilistic timed automata can be approximated using a region-graph-based approach.Comment: Full version of a paper published at RP 201

Insulin Resistance and Body Fat Distribution in South Asian Men Compared to Caucasian Men

South Asians are susceptible to insulin resistance even without obesity. We examined the characteristics of body fat content, distribution and function in South Asian men and their relationships to insulin resistance compared to Caucasians.Twenty-nine South Asian and 18 Caucasian non-diabetic men (age 27+/-3 and 27+/-3 years, respectively) underwent euglycemic-hyperinsulinemic clamp for insulin sensitivity, underwater weighing for total body fat, MRI of entire abdomen for intraperitoneal (IP) and subcutaneous abdominal (SA) fat and biopsy of SA fat for adipocyte size.Compared to Caucasians, in spite of similar BMI, South Asians had higher total body fat (22+/-6 and 15+/-4% of body weight; p-value<0.0001), higher SA fat (3.5+/-1.9 and 2.2+/-1.3 kg, respectively; p-value = 0.004), but no differences in IP fat (1.0+/-0.5 and 1.0+/-0.7 kg, respectively; p-value = 0.4). SA adipocyte cell size was significantly higher in South Asians (3491+/-1393 and 1648+/-864 microm2; p-value = 0.0001) and was inversely correlated with both glucose disposal rate (r-value = -0.57; p-value = 0.0008) and plasma adiponectin concentrations (r-value = -0.71; p-value<0.0001). Adipocyte size differences persisted even when SA was matched between South Asians and Caucasians.Insulin resistance in young South Asian men can be observed even without increase in IP fat mass and is related to large SA adipocytes size. Hence ethnic excess in insulin resistance in South Asians appears to be related more to excess truncal fat and dysfunctional adipose tissue than to excess visceral fat

Screen-Printed Biosensors for the Early Detection of Biomarkers Related to Alzheimer Disease: Preliminary Results

Abstract Alzheimer disease (AD), despite representing the most common type of dementia in elderly, is still lacking reliable methodologies for early diagnosis. A potential biomarker associated to AD development has been recently identified in the open isoform of p53, redox sensitive protein, currently quantified using a specific blood-based enzyme-linked immunosorbent assay (ELISA). In order to overcome ELISA limitations (level of detection, standardization and reliability), this study aimed to realize a low cost highly sensitive portable point-of-care (PoC) testing system based on screen printed electrochemical sensors (SPES). The study specifically reported the design of the platform, including the sensing probe and the electronic circuit devoted to the conditioning of the electric signal. Preliminary results were obtained from circuit testing by using controlled concentrations of electrolytic solutions and from an initial calibration stage by using Anodic Stripping Voltammetry (ASV) measurements. Future works will address the quantification of unknown concentration of unfolded p53 in peripheral blood samples, thus to validate the here-presented low cost, easy to use and highly precise platform

Hybrid lipid self-assembling nanoparticles for brain delivery of microRNA

Hybrid self-assembling nanoparticles (SANPs) have been previously designed as novel drug delivery system that overcomes stability issues following long-term storage and with an easy scale-up. This system has been successfully used to deliver anionic-charged agents, e.g. bisphosphonates, in different types of tumors, such glioblastoma (GBM). Here, SANPs were tested and optimized for the delivery of nucleic acids, in particular of a specific microRNA, e.g. miR603, used for its potential role in controlling the chemoresistance in different forms of cancer, e.g. (GBM). To this aim, SANPs with different lipids were prepared and characterized, in terms of size, polydispersity index, zeta potential, miRNA encapsulation, stability in BSA, serum and hemolytic activity. Then, SANPs were tested in vitro on two different cell lines of GBM. Finally, miRNA biodistribution was tested in vivo in an orthotopic model of GBM. The majority of the formulations showed good technological characteristics and were stable in BSA and serum with a low hemolytic activity. The intracellular uptake studies on GBM cell lines showed that SANPs allow to achieve a higher miRNA delivery compared to others transfection agents, e.g. lipofectamine. Finally, in vivo biodistribution studies in an orthotopic of GBM demonstrated that the optimized SANP formulations, were able to deliver miRNA in different organs, e.g. the brain

Blastic plasmacytoid dendritic cell neoplasm: Genomics mark epigenetic dysregulation as a primary therapeutic target

Blastic plasmacytoid dendritic cell neoplasm (BPDCN) is a rare and aggressive hematologic malignancy for which there is still no effective B therapy. In order to identify genetic alterations useful for a new treatment design, we used whole-exome sequencing to analyze 14 BPDCN patients and the patient-derived CAL-1 cell line. The functional enrichment analysis of mutational data reported the epigenetic regulatory program to be the most significantly undermined (P&lt;0.0001). In particular, twenty-five epigenetic modifiers were found mutated (e.g. ASXL1, TET2, SUZ12, ARID1A, PHF2, CHD8); ASXL1 was the most frequently affected (28.6% of cases). To evaluate the impact of the identified epigenetic mutations at the gene-expression and Histone H3 lysine 27 trimethylation/acetylation levels, we performed additional RNA and pathology tissue-chromatin immunoprecipitation sequencing experiments. The patients displayed enrichment in gene signatures regulated by methylation and modifiable by decitabine administration, shared common H3K27-acetylated regions, and had a set of cell-cycle genes aberrantly up-regulated and marked by promoter acetylation. Collectively, the integration of sequencing data showed the potential of a therapy based on epigenetic agents. Through the adoption of a preclinical BPDCN mouse model, established by CAL-1 cell line xenografting, we demonstrated the efficacy of the combination of the epigenetic drugs 5’-azacytidine and decitabine in controlling disease progression in vivo

Experimental Biological Protocols with Formal Semantics

Both experimental and computational biology is becoming increasingly automated. Laboratory experiments are now performed automatically on high-throughput machinery, while computational models are synthesized or inferred automatically from data. However, integration between automated tasks in the process of biological discovery is still lacking, largely due to incompatible or missing formal representations. While theories are expressed formally as computational models, existing languages for encoding and automating experimental protocols often lack formal semantics. This makes it challenging to extract novel understanding by identifying when theory and experimental evidence disagree due to errors in the models or the protocols used to validate them. To address this, we formalize the syntax of a core protocol language, which provides a unified description for the models of biochemical systems being experimented on, together with the discrete events representing the liquid-handling steps of biological protocols. We present both a deterministic and a stochastic semantics to this language, both defined in terms of hybrid processes. In particular, the stochastic semantics captures uncertainties in equipment tolerances, making it a suitable tool for both experimental and computational biologists. We illustrate how the proposed protocol language can be used for automated verification and synthesis of laboratory experiments on case studies from the fields of chemistry and molecular programming

Abstract basins of attraction

Abstract basins appear naturally in different areas of several complex variables. In this survey we want to describe three different topics in which they play an important role, leading to interesting open problems

Transition probabilities for general birth-death processes with applications in ecology, genetics, and evolution

A birth-death process is a continuous-time Markov chain that counts the number of particles in a system over time. In the general process with $n$ current particles, a new particle is born with instantaneous rate $\lambda_n$ and a particle dies with instantaneous rate $\mu_n$. Currently no robust and efficient method exists to evaluate the finite-time transition probabilities in a general birth-death process with arbitrary birth and death rates. In this paper, we first revisit the theory of continued fractions to obtain expressions for the Laplace transforms of these transition probabilities and make explicit an important derivation connecting transition probabilities and continued fractions. We then develop an efficient algorithm for computing these probabilities that analyzes the error associated with approximations in the method. We demonstrate that this error-controlled method agrees with known solutions and outperforms previous approaches to computing these probabilities. Finally, we apply our novel method to several important problems in ecology, evolution, and genetics

Distribution-based bisimulation for labelled Markov processes

In this paper we propose a (sub)distribution-based bisimulation for labelled Markov processes and compare it with earlier definitions of state and event bisimulation, which both only compare states. In contrast to those state-based bisimulations, our distribution bisimulation is weaker, but corresponds more closely to linear properties. We construct a logic and a metric to describe our distribution bisimulation and discuss linearity, continuity and compositional properties.Comment: Accepted by FORMATS 201