The dynamic structure factor S(Q,omega) of both associated (water and ammonia) and simple fluids (nitrogen and neon) has been determined by high-resolution inelastic x-ray scattering in the 2-14 nm(-1) momentum transfer range. A line-shape analysis with a generalized hydrodynamic model was used to study the involved relaxation process and to characterize its strength and time scale. We observe that in the liquid phase such a process is governed by rearrangements of intermolecular bonds, whereas in the supercritical region it assumes a collisional nature.

Breast lesion detection employing state of the art microwave systems provide a safe, non-ionizing technique that can differentiate healthy and non-healthy tissues by exploiting their dielectric properties. In this paper, a microwave apparatus for breast lesion detection is used to accumulate clinical data from subjects undergoing breast examinations at the Department of Diagnostic Imaging, Perugia Hospital, Perugia, Italy. This paper presents the first ever clinical demonstration and comparison of a microwave ultra-wideband (UWB) device augmented by machine learning with subjects who are simultaneously undergoing conventional breast examinations. Non-ionizing microwave signals are transmitted through the breast tissue and the scattering parameters (S-parameter) are received via a dedicated moving transmitting and receiving antenna set-up. The output of a parallel radiologist study for the same subjects, performed using conventional techniques, is taken to pre-process microwave data and create suitable data for the machine intelligence system. These data are used to train and investigate several suitable supervised machine learning algorithms nearest neighbour (NN), multi-layer perceptron (MLP) neural network, and support vector machine (SVM) to create an intelligent classification system towards supporting clinicians to recognise breasts with lesions. The results are rigorously analysed, validated through statistical measurements, and found the quadratic kernel of SVM can classify the breast data with 98% accuracy.

This paper presents preliminary results of an innovative microwave imaging apparatus for breast lesions detection. Specifically, a Huygens Principle based method is employed to process the microwave signals and to build the respective microwave images. The apparatus has been first tested on phantoms. Next, its performance has been verified through clinical examinations on 22 healthy breasts and on 29 breast having lesions, using as gold standard the output of the radiologist study review obtained using conventional techniques. Specifically, we introduce a metric, which is the ratio between maximum and average of the image intensity (MAX/AVG). We found that MAX/AVG of microwave images can be used for classifying breasts containing lesions. In addition, using MAX/AVG as classification parameter, receiver operating characteristic curves have been empirically determined. Furthermore, for one randomly selected breast having lesion, we have demonstrated that the localization of the inclusion acquired through microwave imaging is compatible with mammography images.

We present a dynamic and thermodynamic study of the orientational glass former Freon 113 (1,1,2-trichloro-1,2,2-trifluoroethane, CCl 2 F-CClF 2 ) in order to analyze its kinetic and thermodynamic fragilities. Freon 113 displays internal molecular degrees of freedom that promote a complex energy landscape. Experimental specific heat and its microscopic origin, the vibrational density of states from inelastic neutron scattering, together with the orientational dynamics obtained by means of dielectric spectroscopy have revealed the highest fragility value, both thermodynamic and kinetic, found for this orientational glass former. The excess in both Debye-reduced specific heat and density of states (boson peak) evidences the existence of glassy low-energy excitations. We demonstrate that early proposed correlations between the boson peak and the Debye specific heat value are elusive as revealed by the clear counterexample of the studied case. DOI: 10.1103/PhysRevLett.118.105701 When a structurally disordered system is rapidly cooled to avoid crystallization, some properties, such as viscosity, show a dramatic increase down to the glass transition where the material reaches viscosity values comparable to those of a solid (10 12 Pa s), i.e., relaxation times of ≈100 s. Such behavior contrasts with that typical for most liquids at high temperatures, which usually exhibit a simple Arrhenius behavior of the relaxation time, τ ¼ τ 0 expðE a =k B TÞ, where the activation energy is temperature independent.Decreasing temperature relaxation time shows a stronger increase, faster than that of the Arrhenius law and accompanied with an increase of some characteristic cooperativity relaxation length. The viscosity (or τ) increase is generally characterized by recourse to the concept of the kinetic fragility [1,2], m ¼ fð∂ log τÞ=½∂ðT g =TÞg T¼T g , which accounts for the deviation of the Arrhenius temperature dependence.In terms of fragility index m, materials for which τ follow an Arrhenius law are known as "strong" glass formers, whereas "fragile" glass formers are those exhibiting super-Arrhenius behavior. For such cases, the temperature dependence of τ is given through the Vogel-FulcherTammann (VFT) expression,where the temperature T 0 is associated with an ideal glass transition and even with the so-called Kauzmann temperature [3], and the fragility strength parameter D is linked to the fragility parameter by. Typical strong glass formers (m ≈ 16, or D ≥ 100) are tetrahedral network liquids as SiO 2 or GeO 2 . The highest values of fragility for organic materials (exception made of polymers) have been found in cis-or trans-decahydronaphthalene (m ¼ 147 [4]). Another group of materials exhibiting glasslike properties is that of crystals with positional order and orientational disorder [5]. Such plastic phases are formed from the liquid and can be supercooled, giving rise to the so-called orientational glasses (OG) or "glassy crystals" [6][7][8][9]. They show typically low fragility, as cyclooctanol (m ¼ 33) [10,11]

Microwave imaging has received increasing attention in the last decades, motivated by its application in diagnostic imaging. Such effort has been encouraged by the fact that, at microwave frequencies, it is possible to distinguish between tissues with different dielectric properties. In such framework, a novel microwave device is presented here. The apparatus, consisting of two antennas operating in air, is completely safe and non-invasive since it does not emit any ionizing radiation and it can be used for breast lesion detection without requiring any breast crushing. We use Huygens Principle to provide a novel understanding into microwave imaging; specifically, the algorithm based on this principle provides images which represent homogeneity maps of the dielectric properties (dielectric constant and/or conductivity). The experimental results on phantoms having inclusions with different dielectric constants are presented here. In addition, the capability of the device to detect breast lesions has been verified through clinical examinations on 51 breasts.We introduce a metric to measure the non-homogenous behaviour of the image, establishing a modality to detect the presence of inclusions inside phantoms and, similarly, the presence of a lesion inside a breast.

MammoWave is a microwave imaging device for breast lesions detection, which operates using two (azimuthally rotating) antennas without any matching liquid. Images, subsequently obtained by resorting to Huygens Principle, are intensity maps, representing the homogeneity of tissues’ dielectric properties. In this paper, we propose to generate, for each breast, a set of conductivity weighted microwave images by using different values of conductivity in the Huygens Principle imaging algorithm. Next, microwave images’ parameters, i.e. features, are introduced to quantify the non-homogenous behaviour of the image. We empirically verify on 103 breasts that a selection of these features may allow distinction between breasts with no radiological finding (NF) and breasts with radiological findings (WF), i.e. with lesions which may be benign or malignant. Statistical significance was set at p<0.05. We obtained single features Area Under the receiver operating characteristic Curves (AUCs) spanning from 0.65 to 0.69. In addition, an empirical rule-of-thumb allowing breast assessment is introduced using a binary score S operating on an appropriate combination of features. Performances of such rule-of-thumb are evaluated empirically, obtaining a sensitivity of 74%, which increases to 82% when considering dense breasts only.

We use Bayesian inference methods to provide fresh insights into the sub-nanosecond dynamics of glycerol, a prototypical glass-forming liquid. To this end, quasielastic neutron scattering data as a function of temperature have been analyzed using a minimal set of underlying physical assumptions. On the basis of this analysis, we establish the unambiguous presence of three distinct dynamical processes in glycerol, namely, translational diffusion of the molecular centre of mass and two additional localized and temperature-independent modes.The neutron data also provide access to the characteristic length scales associated with these motions in a model-independent manner, from which we conclude that the faster (slower) localized motions probe longer (shorter) length scales. Careful Bayesian analysis of the entire scattering law favors a heterogeneous scenario for the microscopic dynamics of glycerol, where molecules undergo either the faster and longer or the slower and shorter localized motions.

The determination of special molecular arrangements in disordered phases such as liquids is inherently difficult due to its lack of periodicity, in contrast to the crystalline solids. We have already settled a general method to study molecular liquids capable to unveil the details of the molecular ordering from small molecules to systems as big as a protein. However it would be desirable to extract some general features of a liquid phase without going into such details. In this work we propose a method to achieve this challenge by analyzing the probability distributions describing position and orientational molecular ordering within the framework of information theory.