Multi-scale Modelling of Natural Composites Using Thermodynamics-Based Artificial Neural Networks and Dimensionality Reduction Techniques

Modelling natural composites, as the majority of real geomaterials, requires facing their intrinsic multiscale nature. This allows to consider multiphysics coupling occurring at the microscale, then reflected onto the macroscopic behavior. Geotechnics is constantly requiring reliable constitutive models of natural compolve large-scale engineering problems accurately and efficiently. This need motivates the contribution. To capture in detail the macroscopic effects of microssites to socopic processes, many authors have developed multi-scale numerical schemes. A common drawback of such methods is the prohibitive computational cost. Recently,Machine Learning based approaches have raised as promising alternatives to traditional methods. Artificial Neural Networks – ANNs – have been used to predict the constitutive behaviour of complex, heterogeneous materials, with reduced calculation costs. However, a major weakness of ANN is the lack of a rigorous framework based on principles of physics. This often implies a limited capability to extrapolate values ranging outside the training set and the need of large, high-quality datasets, on which performing the training. This work focuses on the use of Thermodynamics-based Artificial Neural Networks – TANN – to predict the constitutive behaviour of natural composites. Dimensionality reduction techniques – DRTs – are used to embed information of microscopic processes into a lower dimensional manifold. The obtained set of variables is used to characterize the state of the material at the macroscopic scale. Entanglement of DRTs with TANN allows to reproduce the complex nonlinear material response with reduced computational costs and guarantying thermodynamic admissibility. To demonstrate the method capabilities an application to a heterogeneous material model is presented

Combinazioni di parole parzialmente riempite. Formati e rappresentazione lessicografica

Questo contributo intende analizzare le proprietà di alcune combinazioni di parole della lingua italiana, rappresentate da strutture riempite solo parzialmente da unità lessicali. Attraverso l’analisi di dati estratti da corpora, il contributo si propone di a) identificare e analizzare alcuni formati parzialmente riempiti dell’italiano emersi durante la stesura del dizionario combinatorio CombiNet, b) classificare tali unità sulla base di specifiche proprietà sintattiche o semantiche, c) mostrare una possibile rappresentazione lessicografica di tali formati di parola

Expert Knowledge Base Development for an Industrial Energy Assessment System

Industrial energy management is critical to achieve and monitor industrial energy efficiency. Decision support systems enable energy managers to form effective strategies to increase profitability by eliminating wasteful practices. A well formulated knowledge base is essential for a decision support system to function. Expert knowledge must be acquired and coded into a knowledge base to be accessible to a decision support system. The primary objective is to devise a methodology to extract expert knowledge acquired through field work or archived in manually generated energy analysis reports. Once the knowledge is extracted it can be codified and stored in a knowledge base that is validated to be usable by an energy management assistant decision support system. The acquisition and codification method is demonstrated by its implementation in the REACTOR energy management software system

Application of 3D printing to prototype and develop novel plant tissue culture systems

Additional file 6. STL (StereoLithography) file was designed for an accessory lid without fan slot using SketchUp or Fusion 360 (Autodesk) software and the STL file was processed using MatterControl 3D printing software and exported as gcode files

Immune dyscrasia in adult growth hormone deficiency: Evaluation of hemolytic complement activity (CH50) and IgG subclasses.

CH50 is a screening assay for the activation of the classical complement pathway, the immunoglobulins-mediated one, activated in several inflammatory diseases. Adult growth hormone deficiency (aGHD) is recognized as a chronic inflammatory condition, although poorly evaluated under the profile of inflammatory biomarkers. The aim of this case-control observational study is to analyze CH50 and immunoglobulins G (IgG) subclasses production in aGHD, comparing this condition to healthy controls.38 subjects were included and divided as follows: aGHD (n = 18, 6 females and 12 males); healthy controls (n = 20, 10 females and 10 males). GHD was diagnosed with dynamic test using Growth Hormone-Releasing Hormone (GHRH 50 μg i.v. + arginine 0,5 g/Kg), with a peak GH response 30 kg/m2. The two groups were evaluated for hormonal and metabolic parameters, CH50 and IgG subtypes.IgG1 and IgG2 were significantly higher in controls than in aGHD, while IgG3 and IgG4 showed a trend to higher levels in controls, although not significant. Furthermore, CH50 levels were significantly higher in aGHD.These data substantiate the hypothesis of a dyscrasia in IgG subclasses production in aGHD. As IgG levels decrease, CH50 levels do not

Immune dyscrasia in adult growth hormone deficiency: Evaluation of hemolytic complement activity (CH50) and IgG subclasses

CH50 is a screening assay for the activation of the classical complement pathway, the immunoglobulins-mediated one, activated in several inflammatory diseases. Adult growth hormone deficiency (aGHD) is recognized as a chronic inflammatory condition, although poorly evaluated under the profile of inflammatory biomarkers. The aim of this case-control observational study is to analyze CH50 and immunoglobulins G (IgG) subclasses production in aGHD, comparing this condition to healthy controls. 38 subjects were included and divided as follows: aGHD (n = 18, 6 females and 12 males); healthy controls (n = 20, 10 females and 10 males). GHD was diagnosed with dynamic test using Growth Hormone-Releasing Hormone (GHRH 50 \u3bcg i.v. + arginine 0,5 g/Kg), with a peak GH response < 9 \u3bcg/L when BMI was <30 kg/m2 or < 4 \u3bcg/L when BMI was >30 kg/m2. The two groups were evaluated for hormonal and metabolic parameters, CH50 and IgG subtypes. IgG1 and IgG2 were significantly higher in controls than in aGHD, while IgG3 and IgG4 showed a trend to higher levels in controls, although not significant. Furthermore, CH50 levels were significantly higher in aGHD. These data substantiate the hypothesis of a dyscrasia in IgG subclasses production in aGHD. As IgG levels decrease, CH50 levels do not

Photonic Biosensor Assays to Detect and Distinguish Subspecies of Francisella tularensis

The application of photonic biosensor assays to diagnose the category-A select agent Francisella tularensis was investigated. Both interferometric and long period fiber grating sensing structures were successfully demonstrated; both these sensors are capable of detecting the optical changes induced by either immunological binding or DNA hybridization. Detection was made possible by the attachment of DNA probes or immunoglobulins (IgG) directly to the fiber surface via layer-by-layer electrostatic self-assembly. An optical fiber biosensor was tested using a standard transmission mode long period fiber grating of length 15 mm and period 260 μm, and coated with the IgG fraction of antiserum to F. tularensis. The IgG was deposited onto the optical fiber surface in a nanostructured film, and the resulting refractive index change was measured using spectroscopic ellipsometry. The presence of F. tularensis was detected from the decrease of peak wavelength caused by binding of specific antigen. Detection and differentiation of F. tularensis subspecies tularensis (type A strain TI0902) and subspecies holarctica (type B strain LVS) was further accomplished using a single-mode multi-cavity fiber Fabry-Perot interferometric sensor. These sensors were prepared by depositing seven polymer bilayers onto the fiber tip followed by attaching one of two DNA probes: (a) a 101-bp probe from the yhhW gene unique to type-A strains, or (b) a 117-bp probe of the lpnA gene, common to both type-A and type-B strains. The yhhW probe was reactive with the type-A, but not the type-B strain. Probe lpnA was reactive with both type-A and type-B strains. Nanogram quantities of the target DNA could be detected, highlighting the sensitivity of this method for DNA detection without the use of PCR. The DNA probe reacted with 100% homologous target DNA, but did not react with sequences containing 2-bp mismatches, indicating the high specificity of the assay. These assays will fill an important void that exists for rapid, culture-free, and field-compatible diagnosis of F. tularensis

Biofunctionalized Zinc Oxide Field Effect Transistors for Selective Sensing of Riboflavin with Current Modulation

Zinc oxide field effect transistors (ZnO-FET), covalently functionalized with single stranded DNA aptamers, provide a highly selective platform for label-free small molecule sensing. The nanostructured surface morphology of ZnO provides high sensitivity and room temperature deposition allows for a wide array of substrate types. Herein we demonstrate the selective detection of riboflavin down to the pM level in aqueous solution using the negative electrical current response of the ZnO-FET by covalently attaching a riboflavin binding aptamer to the surface. The response of the biofunctionalized ZnO-FET was tuned by attaching a redox tag (ferrocene) to the 3′ terminus of the aptamer, resulting in positive current modulation upon exposure to riboflavin down to pM levels