Mechanical-physical experimental tests on lime mortars and bricks reinforced with hemp

Hemp is an agricultural product used for various applications. In the Civil Engineering field, only a limited use of this natural material, called the “green pig” since exploitation of all its constituent parts is allowed, has been done. For this reason, in the paper an experimental activity on lime mortars and bricks reinforced with hemp components has been performed. Compression and bending tests have been carried out on specimens manufactured with hemp shives and fibres, respectively. The achieved results have shown that hemp products change the failure modes from brittle to ductile, leaving basically unaltered the strength capacity of reinforced specimens with respect to unreinforced ones

Calibrating chemical multisensory devices for real world applications: An in-depth comparison of quantitative Machine Learning approaches

Chemical multisensor devices need calibration algorithms to estimate gas concentrations. Their possible adoption as indicative air quality measurements devices poses new challenges due to the need to operate in continuous monitoring modes in uncontrolled environments. Several issues, including slow dynamics, continue to affect their real world performances. At the same time, the need for estimating pollutant concentrations on board the devices, espe- cially for wearables and IoT deployments, is becoming highly desirable. In this framework, several calibration approaches have been proposed and tested on a variety of proprietary devices and datasets; still, no thorough comparison is available to researchers. This work attempts a benchmarking of the most promising calibration algorithms according to recent literature with a focus on machine learning approaches. We test the techniques against absolute and dynamic performances, generalization capabilities and computational/storage needs using three different datasets sharing continuous monitoring operation methodology. Our results can guide researchers and engineers in the choice of optimal strategy. They show that non-linear multivariate techniques yield reproducible results, outperforming lin- ear approaches. Specifically, the Support Vector Regression method consistently shows good performances in all the considered scenarios. We highlight the enhanced suitability of shallow neural networks in a trade-off between performance and computational/storage needs. We confirm, on a much wider basis, the advantages of dynamic approaches with respect to static ones that only rely on instantaneous sensor array response. The latter have been shown to be best choice whenever prompt and precise response is needed

Independent component analysis of interictal fMRI in focal epilepsy: comparison with general linear model-based EEG-correlated fMRI

The general linear model (GLM) has been used to analyze simultaneous EEG–fMRI to reveal BOLD changes linked to interictal epileptic discharges (IED) identified on scalp EEG. This approach is ineffective when IED are not evident in the EEG. Data-driven fMRI analysis techniques that do not require an EEG derived model may offer a solution in these circumstances. We compared the findings of independent components analysis (ICA) and EEG-based GLM analyses of fMRI data from eight patients with focal epilepsy. Spatial ICA was used to extract independent components (IC) which were automatically classified as either BOLD-related, motion artefacts, EPI-susceptibility artefacts, large blood vessels, noise at high spatial or temporal frequency. The classifier reduced the number of candidate IC by 78%, with an average of 16 BOLD-related IC. Concordance between the ICA and GLM-derived results was assessed based on spatio-temporal criteria. In each patient, one of the IC satisfied the criteria to correspond to IED-based GLM result. The remaining IC were consistent with BOLD patterns of spontaneous brain activity and may include epileptic activity that was not evident on the scalp EEG. In conclusion, ICA of fMRI is capable of revealing areas of epileptic activity in patients with focal epilepsy and may be useful for the analysis of EEG–fMRI data in which abnormalities are not apparent on scalp EEG

Thermal stability and aggregation of sulfolobus solfataricus b-glycosidase are dependent upon the N-e-methylation of specific lysyl residues: critical role of in vivo post-translational modifications.

Methylation in vivo is a post-translational modification observed in several organisms belonging to eucarya, bacteria, and archaea. Although important implications of this modification have been demonstrated in several eucaryotes, its biological role in hyperthermophilic archaea is far from being understood. The aim of this work is to clarify some effects of methylation on the properties of β-glycosidase from Sulfolobus solfataricus, by a structural comparison between the native, methylated protein and its unmethylated counterpart, recombinantly expressed in Escherichia coli. Analysis by Fourier transform infrared spectroscopy indicated similar secondary structure contents for the two forms of the protein. However, the study of temperature perturbation by Fourier transform infrared spectroscopy and turbidimetry evidenced denaturation and aggregation events more pronounced in recombinant than in native β-glycosidase. Red Nile fluorescence analysis revealed significant differences of surface hydrophobicity between the two forms of the protein. Unlike the native enzyme, which dissociated into SDS-resistant dimers upon exposure to the detergent, the recombinant enzyme partially dissociated into monomers. By electrospray mapping, the methylation sites of the native protein were identified. A computational analysis of β-glycosidase three-dimensional structure and comparisons with other proteins from S. solfataricus revealed analogies in the localization of methylation sites in terms of secondary structural elements and overall topology. These observations suggest a role for the methylation of lysyl residues, located in selected domains, in the thermal stabilization of β-glycosidase from S. solfataricu

Short Gamma Ray Bursts as possible electromagnetic counterpart of coalescing binary systems

Coalescing binary systems, consisting of two collapsed objects, are among the most promising sources of high frequency gravitational waves signals detectable, in principle, by ground-based interferometers. Binary systems of Neutron Star or Black Hole/Neutron Star mergers should also give rise to short Gamma Ray Bursts, a subclass of Gamma Ray Bursts. Short-hard-Gamma Ray Bursts might thus provide a powerful way to infer the merger rate of two-collapsed object binaries. Under the hypothesis that most short Gamma Ray Bursts originate from binaries of Neutron Star or Black Hole/Neutron Star mergers, we outline here the possibility to associate short Gamma Ray Bursts as electromagnetic counterpart of coalescing binary systems.Comment: 4 pages, 1 figur

Comment on "Are periodic solar wind number density structures formed in the solar corona?" by N. M. Viall et al., 2009, Geophys. Res. Lett., 36, L23102, doi:10.1029/2009GL041191

Location of formation of periodic solar wind number density structures is discussed. Observation of proton and alpha anticorrelation in these structures [Viall et al., 2009] indicates that taking into account that bulk velocity of aplha-particles is higher than that of proton the place of formation for these structures should be located at distance less 0.002 AU from place of observation.Comment: 6 pages, submitted in GR

Three-body interactions in colloidal systems

We present the first direct measurement of three-body interactions in a colloidal system comprised of three charged colloidal particles. Two of the particles have been confined by means of a scanned laser tweezers to a line-shaped optical trap where they diffused due to thermal fluctuations. Upon the approach of a third particle, attractive three-body interactions have been observed. The results are in qualitative agreement with additionally performed nonlinear Poissson-Boltzmann calculations, which also allow us to investigate the microionic density distributions in the neighborhood of the interacting colloidal particles

Anatomic & metabolic brain markers of the m.3243A>G mutation: A multi-parametric 7T MRI study

One of the most common mitochondrial DNA (mtDNA) mutations, the A to G transition at base pair 3243, has been linked to changes in the brain, in addition to commonly observed hearing problems, diabetes and myopathy. However, a detailed quantitative description of m.3243A>G patients' brains has not been provided so far. In this study, ultra-high field MRI at 7T and volume- and surface-based data analyses approaches were used to highlight morphology (i.e. atrophy)-, microstructure (i.e. myelin and iron concentration)- and metabolism (i.e. cerebral blood flow)-related differences between patients (N = 22) and healthy controls (N = 15). The use of quantitative MRI at 7T allowed us to detect subtle changes of biophysical processes in the brain with high accuracy and sensitivity, in addition to typically assessed lesions and atrophy. Furthermore, the effect of m.3243A>G mutation load in blood and urine epithelial cells on these MRI measures was assessed within the patient population and revealed that blood levels were most indicative of the brain's state and disease severity, based on MRI as well as on neuropsychological data. Morphometry MRI data showed a wide-spread reduction of cortical, subcortical and cerebellar gray matter volume, in addition to significantly enlarged ventricles. Moreover, surface-based analyses revealed brain area-specific changes in cortical thickness (e.g. of the auditory cortex), and in T1, T2* and cerebral blood flow as a function of mutation load, which can be linked to typically m.3243A>G-related clinical symptoms (e.g. hearing impairment). In addition, several regions linked to attentional control (e.g. middle frontal gyrus), the sensorimotor network (e.g. banks of central sulcus) and the default mode network (e.g. precuneus) were characterized by alterations in cortical thickness, T1, T2* and/or cerebral blood flow, which has not been described in previous MRI studies. Finally, several hypotheses, based either on vascular, metabolic or astroglial implications of the m.3243A>G mutation, are discussed that potentially explain the underlying pathobiology. To conclude, this is the first 7T and also the largest MRI study on this patient population that provides macroscopic brain correlates of the m.3243A>G mutation indicating potential MRI biomarkers of mitochondrial diseases and might guide future (longitudinal) studies to extensively track neuropathological and clinical changes