Superconductivity in the η\eta-carbide-type oxides Zr4Rh2Ox

We report on the synthesis and the superconductivity of Zr$_4$Rh$_2$O$_{x}$ ($x$ = 0.4, 0.5, 0.6, 0.7, 1.0). These compounds crystallize in the $\eta$-carbide structure, which is a filled version of the complex intermetallic Ti$_2$Ni structure. We find that in the system Zr$_4$Rh$_2$O$_{x}$, already a small amount ($x$ $\geq$ 0.4) of oxygen addition stabilizes the $\eta$-carbide structure over the more common intermetallic CuAl$_2$ structure-type, in which Zr$_2$Rh crystallizes. We show that Zr$_4$Rh$_2$O$_{0.7}$ and Zr$_4$Rh$_2$O are bulk superconductors with critical temperatures of $T_c \approx$ 2.8 K and 4.7 K in the resistivity, respectively. Our analysis of the superconducting properties reveal both compounds to be strongly type-II superconductors with critical fields up to $\mu_0 H_{c1}$(0) $\approx$ 8.8 mT and $\mu_0 H_{c2}$(0) $\approx$ 6.08 T. Our results support that the $\eta$-carbides are a versatile family of compounds for the investigation of the interplay of interstitial doping on physical properties, especially for superconductivity

Superconductivity in the η-carbide-type oxides Zr4Rh2Ox

We report on the synthesis and the superconductivity in (x = 0.4, 0.5, 0.6, 0.7, 1.0). These compounds crystallize in the η-carbide structure, which is a filled version of the complex intermetallic structure. We find that in the system , already a small amount (x 0.4) of oxygen addition stabilizes the η-carbide structure over the more common intermetallic structure-type, in which crystallizes. We show that and are bulk superconductors with critical temperatures of 2.8 K and 4.7 K in the resistivity, respectively. Our analysis of the superconducting properties reveal both compounds to be strongly type-II superconductors with critical fields up to (0) 8.8 mT and (0) 6.08 T. Our results support that the η-carbides are a versatile family of compounds for the investigation of the interplay of interstitial doping on physical properties, especially for superconductivity

Influencia de los modelos intuitivos en la comprensión de la multiplicación y la división

Since the stdy by Fischbein et al. (1985) which suggested that children develop intuitive models about multiplication and division early, much research has offered data that corroborate these models. In this study we analyze the differential weight of the models in three kid of task: algorithms, problem solving, and problem posing. We included two age groups (1st of ESO and 8th of EGB), and three kid of quantities (whole numbers, decimals and fractions). The results indicated that the intuitive models did not have the same differential weight for the different tasks. For instance, the problem posing task did not seem suited to the conditions under which the intuitive models act. Likewise, the presence of quantities that failed to observe one or more restrictions of the models did not have a negative influence. In contrast, the errors committed in the two remaining tasks were almost exclusively due to the application of the intuitive rules.A partir del trabajo de Fischbein et al. (1985) que sugiere que los niños construyen tempranamente modelos intuitivos sobre la multiplicación y división, numerosas investigaciones han ofrecido datos consistentes con estos modelos. En este estudio analizamos el peso diferencial de los modelos en tres tipos de tareas: resolver algoritmes, resolver problemas y plantear problemas. Hemos incluido también dos grupos de edad (1º de ESO y 8º de EGB), asi como tres tipos de cantidades (enteros, decimales y fracciones). LoS resultados indicaron que los modelos intuitivos no tuvieron el mismo peso diferencial en las diferentes tareas. Por ejemplo, la tarea de plantear problemas no parecía reunir las condiciones bajo las que actúan los modelos intuitivos. Asimismo, la presencia de cantidades que alteraban una o más imposiciones de los modelos no influyó negativamente. Por el contrario, los errores de las dos tareas restantes se debieron a la aplicación de las reglas intuitivas

The stochastic digital human is now enrolling for in silico imaging trials -- Methods and tools for generating digital cohorts

Randomized clinical trials, while often viewed as the highest evidentiary bar by which to judge the quality of a medical intervention, are far from perfect. In silico imaging trials are computational studies that seek to ascertain the performance of a medical device by collecting this information entirely via computer simulations. The benefits of in silico trials for evaluating new technology include significant resource and time savings, minimization of subject risk, the ability to study devices that are not achievable in the physical world, allow for the rapid and effective investigation of new technologies and ensure representation from all relevant subgroups. To conduct in silico trials, digital representations of humans are needed. We review the latest developments in methods and tools for obtaining digital humans for in silico imaging studies. First, we introduce terminology and a classification of digital human models. Second, we survey available methodologies for generating digital humans with healthy and diseased status and examine briefly the role of augmentation methods. Finally, we discuss the trade-offs of four approaches for sampling digital cohorts and the associated potential for study bias with selecting specific patient distributions

Two-gap to single-gap superconducting transition on a honeycomb lattice in Ca1−xSrxAlSi

We report on the structural and microscopic superconducting properties of the Ca1−xSrxAlSi solid solution. Specifically, we have realized the continuous solid solution, which for all members, other than x=0 (CaAlSi), crystallizes in the AlB2-type structure. For CaAlSi, we present an improved structural model where all Al/Si layers are buckled, leading to a 6-folded structure along the crystallographic c direction. We, furthermore, find indications for the structural instability in the parent compound CaAlSi to enhance the superconductivity across the solid solution. Our investigation of the magnetic penetration depths by means of muon-spin rotation experiments reveals that CaAlSi is a two-gap superconductor, that SrAlSi is a single-gap superconductor, and that there is a continuous transition from one electronic state to the other across the solid solution. Hence, we show that the Ca1−xSrxAlSi solid solution is a highly tunable two-gap to single-gap superconducting system on a honeycomb lattice, where the superconductivity is strongly connected to a structural instability, i.e., the buckling of the Al/Si layers

Progranulin as a biomarker and potential therapeutic agent

Progranulin is a cysteine-rich secreted protein with diverse pleiotropic actions and participates in several processes, such as inflammation or tumorigenesis. Progranulin was first identified as a growth factor and, recently, it was characterised as an adipokine implicated in obesity, insulin resistance and rheumatic disease. At a central level, progranulin acts as a neurotropic and neuroprotective factor and protects from neural degeneration. In this review, we summarise the most recent research advances concerning the potential role of progranulin as a therapeutic target and biomarker in cancer, neurodegenerative and inflammatory diseases

Ambient Oxygen Promotes Tumorigenesis

Oxygen serves as an essential factor for oxidative stress, and it has been shown to be a mutagen in bacteria. While it is well established that ambient oxygen can also cause genomic instability in cultured mammalian cells, its effect on de novo tumorigenesis at the organismal level is unclear. Herein, by decreasing ambient oxygen exposure, we report a ∼50% increase in the median tumor-free survival time of p53−/− mice. In the thymus, reducing oxygen exposure decreased the levels of oxidative DNA damage and RAG recombinase, both of which are known to promote lymphomagenesis in p53−/− mice. Oxygen is further shown to be associated with genomic instability in two additional cancer models involving the APC tumor suppressor gene and chemical carcinogenesis. Together, these observations represent the first report directly testing the effect of ambient oxygen on de novo tumorigenesis and provide important physiologic evidence demonstrating its critical role in increasing genomic instability in vivo

Probability distributed time delays: integrating spatial effects into temporal models

Background: In order to provide insights into the complex biochemical processes inside a cell, modelling approaches must find a balance between achieving an adequate representation of the physical phenomena and keeping the associated computational cost within reasonable limits. This issue is particularly stressed when spatial inhomogeneities have a significant effect on system's behaviour. In such cases, a spatially-resolved stochastic method can better portray the biological reality, but the corresponding computer simulations can in turn be prohibitively expensive.Results: We present a method that incorporates spatial information by means of tailored, probability distributed time-delays. These distributions can be directly obtained by single in silico or a suitable set of in vitro experiments and are subsequently fed into a delay stochastic simulation algorithm (DSSA), achieving a good compromise between computational costs and a much more accurate representation of spatial processes such as molecular diffusion and translocation between cell compartments. Additionally, we present a novel alternative approach based on delay differential equations (DDE) that can be used in scenarios of high molecular concentrations and low noise propagation.Conclusions: Our proposed methodologies accurately capture and incorporate certain spatial processes into temporal stochastic and deterministic simulations, increasing their accuracy at low computational costs. This is of particular importance given that time spans of cellular processes are generally larger (possibly by several orders of magnitude) than those achievable by current spatially-resolved stochastic simulators. Hence, our methodology allows users to explore cellular scenarios under the effects of diffusion and stochasticity in time spans that were, until now, simply unfeasible. Our methodologies are supported by theoretical considerations on the different modelling regimes, i.e. spatial vs. delay-temporal, as indicated by the corresponding Master Equations and presented elsewhere

Supramolecular assemblies involving metal organic ring interactions: Heterometallic Cu(II)-Ln(III) two dimensional coordination polymers

Three isostructural two-dimensional coordination polymers of the general formula [Ln2(CuL)3(H2O)9]$5.5H2O, where Ln is La (1), Nd (2), and Gd (3), have been synthesized and isolated from aqueous solutions and their single-crystal structures determined by X-ray diffraction. The supramolecular interaction between the non-aromatic metallorings plays an important role in stabilizing the structure of these compounds. The thermal stability, reversible solvent uptake, electronic properties and magnetic studies of these compounds are also reported

Network 'small-world-ness': a quantitative method for determining canonical network equivalence

Background: Many technological, biological, social, and information networks fall into the broad class of 'small-world' networks: they have tightly interconnected clusters of nodes, and a shortest mean path length that is similar to a matched random graph (same number of nodes and edges). This semi-quantitative definition leads to a categorical distinction ('small/not-small') rather than a quantitative, continuous grading of networks, and can lead to uncertainty about a network's small-world status. Moreover, systems described by small-world networks are often studied using an equivalent canonical network model-the Watts-Strogatz (WS) model. However, the process of establishing an equivalent WS model is imprecise and there is a pressing need to discover ways in which this equivalence may be quantified. Methodology/Principal Findings: We defined a precise measure of 'small-world-ness' S based on the trade off between high local clustering and short path length. A network is now deemed a 'small-world' if S. 1-an assertion which may be tested statistically. We then examined the behavior of S on a large data-set of real-world systems. We found that all these systems were linked by a linear relationship between their S values and the network size n. Moreover, we show a method for assigning a unique Watts-Strogatz (WS) model to any real-world network, and show analytically that the WS models associated with our sample of networks also show linearity between S and n. Linearity between S and n is not, however, inevitable, and neither is S maximal for an arbitrary network of given size. Linearity may, however, be explained by a common limiting growth process. Conclusions/Significance: We have shown how the notion of a small-world network may be quantified. Several key properties of the metric are described and the use of WS canonical models is placed on a more secure footing