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Abstract The relationships between materials processing and structure can vary between terrestrial and reduced gravity environments. As one case study, we compare the nonequilibrium melt processing of a rare-earth titanate, nominally 83TiO2-17Nd2O3, and the structure of its glassy and crystalline products. Density and thermal expansion for the liquid, supercooled liquid, and glass are measured over 300–1850 °C using the Electrostatic Levitation Furnace (ELF) in microgravity, and two replicate density measurements were reproducible to within 0.4%. Cooling rates in ELF are 40–110 °C s−1 lower than those in a terrestrial aerodynamic levitator due to the absence of forced convection. X-ray/neutron total scattering and Raman spectroscopy indicate that glasses processed on Earth and in microgravity exhibit similar atomic structures, with only subtle differences that are consistent with compositional variations of ~2 mol. % Nd2O3. The glass atomic network contains a mixture of corner- and edge-sharing Ti-O polyhedra, and the fraction of edge-sharing arrangements decreases with increasing Nd2O3 content. X-ray tomography and electron microscopy of crystalline products reveal substantial differences in microstructure, grain size, and crystalline phases, which arise from differences in the melt processes.

Disrupting a criminal organization requires a significant deployment of human resources, time, information, and financial investment. In the early stages of an investigation, details about a specific crime are typically scarce, often with no known suspect. The literature has shown that an effective approach for analyzing criminal organizations is social network analysis. This approach allows the use of traditional social network tools for analyzing criminal networks, as well as more sophisticated and recent tools. This article introduces a model called StPro, which enables the identification of members of a criminal organization starting from a single suspect. It utilizes linear optimization modeling based on Steiner trees. A suspect is used as the root node, and the resulting tree reveals a probable configuration of the criminal organization to which the suspect may belong. Its application to a real-world case demonstrates that there are no significant differences in effectiveness between the proposed model and the state-of-the-art in the literature, despite requiring less information. It also demonstrates how its application aided in the identification of a gang dedicated to violent crimes in Chile. These results highlight the strong capability of the proposed model to support criminal investigations.

Abstract Aluminosilicates (AS) are ubiquitous in ceramics, geology, and planetary science, and their glassy forms underpin vital technologies used in displays, waveguides, and lasers. In spite of this, the nonequilibrium behavior of the prototypical AS compound, mullite (40SiO2-60Al2O3, or AS60), is not well understood. By deeply supercooling mullite-composition liquid via aerodynamic levitation, we observe metastable liquid–liquid unmixing that yields a transparent two-phase glass, comprising a nanoscale mixture of AS7 and AS62. Extrapolations from X-ray scattering measurements show the AS7 phase is similar to vitreous SiO2 with a few Al species substituted for Si. The AS62 phase is built from a highly polymerized network of 4-, 5-, and 6-coordinated AlOx polyhedra. Polymerization of the AS62 network and the composite morphology provide essential mechanisms for toughening the glass.

Abstract Rare-earth titanates form very fragile liquids that can be made into glasses with useful optical properties. We investigate the atomic structure of 83TiO2-17Nd2O3 glass using pair distribution function (PDF) analysis of X-ray and neutron diffraction with double isotope substitutions for both Ti and Nd. Six total structure factors are analyzed (5 neutron + 1 X-ray) to obtain complementary sensitivities to O and Ti/Nd scattering, and an empirical potential structure refinement (EPSR) provides a structural model consistent with the experimental measurements. Glass density is estimated as 4.72(13) g cm−3, consistent with direct measurements. The EPSR model indicates nearest neighbor interactions for Ti-O at $$\overline{r}_{TiO}$$ r ¯ TiO = 1.984(11) Å with coordination of $$n_{TiO}$$ n TiO = 5.72(6) and for Nd-O at $$\overline{r}_{NdO}$$ r ¯ NdO = 2.598(22) Å with coordination of $$n_{NdO}$$ n NdO = 7.70(26), in reasonable agreement with neutron first order difference functions for Ti and Nd. The titanate glass network comprises a mixture of distorted Ti-O5 and Ti-O6 polyhedra connected via 71% corner-sharing and 23% edge-sharing. The O-Ti coordination environments include 15% nonbridging O-Ti1, 51% bridging O-Ti2, and 32% tricluster O-Ti3. This structure is highly unusual for oxide glasses melt-quenched at ambient pressure, as it consists of Ti-Ox predominantly in octahedral (with nearly no tetrahedral) coordination.

Rough-Fuzzy Support Vector Clustering (RFSVC) is a novel soft computing derivative of the classical Support Vector Clustering (SVC) algorithm, which has been used already in many real-world applications. RFSVC’s strengths are its ability to handle arbitrary cluster shapes, identify the number of clusters, and e?ectively detect outliers by the means of membership degrees. However, its current version uses only the closest support vector of each cluster to calculate outliers’ membership degrees, neglecting important information that remaining support vectors can contribute. We present a novel approach based on the ordered weighted average (OWA) operator that aggregates information from all cluster representatives when computing ?nal membership degrees and at the same time allows a better interpretation of the cluster structures found. Particularly, we propose the induced OWA using weights determined by the employed kernel function. The computational experiments show that our approach outperforms the current version of RFSVC as well as alternative techniques ?xing the weights of the OWA operator while maintaining the level of interpretability of membership degrees for detecting outliers.

To enhance the solubility of orally administered pharmaceuticals, liquid capsules or amorphous tablets are often preferred over crystalline drug products. However, little is known regarding the variation in bonding mechanisms between pharmaceutical molecules in their different disordered forms. In this study, liquid and melt-quenched glassy carbamazepine have been studied using high energy X-ray diffraction and modeled using Empirical Potential Structure Refinement. The results show significant structural differences between the liquid and glassy states. The liquid shows a wide range of structures; from isolated molecules, to aromatic ring correlations and NH-O hydrogen bonding. Upon quenching from the liquid to the glass the number of hydrogen bonds per molecule increases by ~50% at the expense of a ~30% decrease in the close contact (non-bonded) carbon-carbon interactions between aromatic rings. During the cooling process, there is an increase in both singly and doubly hydrogen-bonded adjacent molecules. Although hydrogen-bonded dimers found in the crystalline states persist in the glassy state, the absence of a crystalline lattice also allows small, hydrogen-bonded NH-O trimers and tetramers to form. This proposed model for the structure of glassy carbamazepine is consistent with the results from vibrational spectroscopy and nuclear magnetic resonance.

Demand forecasting and capacity management are complicated tasks for emergency healthcare services due to the uncertainty, complex relationships, and high public exposure involved. Published research does not show integrated solutions to these tasks. Thus, the objective of this paper is to present results from three hospitals that show the feasibility of routinely applying integrated forecasting and capacity management with advanced operations research tools.After testing several forecasting methods, neural networks and support vector regression provided the best results in terms of variance and accuracy. Based on this forecasting, a logic for managing hospital capacity was designed and implemented. This logic includes the comparison between the forecasted demand and the available medical resources and a stochastic simulation model to assess the performance of different configurations of facilities and resources. The logic also provides hospital managers with a decision tool for determining the number and distribution of medical resources on emergency services based on a cost/benefit analysis of resources and service improvement. Such results support the task of assigning doctors to different kinds of boxes, defining their work schedules, and considering additional doctors. The contribution of this paper consists of an integrated solution designed to implement the abovementioned logic. This solution combines forecasting, simulation for capacity management, process design, and IT support, facilitating the practical routine use of complex models. The integration explicitly considers a solution that also has adaptation capabilities to facilitate use under changing conditions.The solution is also general and admits adaptation and extension to other services. Thus, we have already performed similar work for ambulatory and surgical services.

The pressure-induced structural transformations in metasilicate MSiO3 glass (M = Mg or Ca) on cold-compression from ambient pressure to 17.5 GPa were investigated by neutron diffraction. The structure of the glass recovered to ambient conditions from a pressure of 8.2 or 17.5 GPa was also investigated by neutron or X-ray diffraction. The experimental work was complemented by molecular dynamics simulations using a newly-developed aspherical ion model. The results show network structures based predominantly on corner-sharing tetrahedral SiO4 units. At pressures up to ~8 GPa, there is little change to the network connectivity as described by the Qn speciation, where n denotes the number of bridging oxygen (BO) atoms per SiO4 tetrahedron. On compression of the glass to 17.5 GPa, the Mg–O coordination number increases from 4.5(1) to 6.2(1), and the Ca–O coordination number increases from 6.15(17) to 7.41(7). In both cases, the increased M-O coordination numbers are accompanied by an increased fraction of M-BO versus M-NBO connections, where NBO denotes a non-bridging oxygen atom. The results give the fraction of triple-bridging oxygen atoms as ~0.5% at 17.5 GPa, which does not support the formation of a substantial fraction of oxygen triclusters in either glass. The M-O coordination number of the recovered glass is larger than for the uncompressed material, which originates from an increased fraction of M-BO connections, and increases with the pressure from which the glass is recovered. The results suggest that the measured decrease in viscosity of molten MSiO3 on pressure increasing from ambient to ~8 GPa is not related to a large change in network polymerization, but to the appearance of higher-coordinated M-centred polyhedra that contain a larger fraction of weaker M-BO bonds. Keywords: Glass structure, Pressure, Neutron diffraction, X-ray diffraction, Molecular dynamics

The use of levitation (containerless) techniques can enable new scientific discoveries because deeply undercooled and metastable liquids can be achieved over a wide temperature range. This review article summarizes the state-of-art instrumentation for structure measurements at synchrotron radiation/neutron sources and for thermophysical property measurements not only on the ground but also in microgravity utilizing the International Space Station (ISS). Furthermore, we introduce recent scientific topics on high-temperature oxide liquids and oxide glasses synthesized from levitated undercooled liquids by the use of quantum beam measurements analyzed using advanced computation.

La gran mayoría de los proyectos de minería de datos que utilizan la metodología KDD en la vida real entregan solamente soluciones estáticas, que con el paso del tiempo pierden la capacidad de explicar los fenómenos para los que fueron construidos inicialmente. Presen-tamos un marco teórico-práctico que permite realizar un seguimiento cercano a los modelos para determinar el momento donde éstos deben ser actualizados, manteniendo un estricto control sobre la evolución de los mismos, las variables presentes en ellos y los cambios re-levantes que pueden ocurrir en la población desde que fueron inicialmente diseñados. Los tests estadísticos incluyen tests clásicos como las pruebas de Kolmogorov-Smirnov o la prue-ba de Chi-Cuadrado para medir los cambios en las medias de las variables en los modelos, más un test novedoso diseñado en base a la distribución de los coeficientes en los modelos y la desviación estándar observada de las variables, que permite medir cuándo la población ha cambiado más allá de los intervalos de confianza definidos por los parámetros iniciales. La metodología fue puesta a prueba utilizando las bases de datos reales de dos proyectos de Credit Scoring a microempresarios, realizados entre los años 2007 y 2008 con muy buenos resultados. Most data mining projects in real life applications give as a result only static solutions which, in time, lose their inherent capacity to explain the phenomena they were originally built for. We introduce an theoretical-practical framework that allows to closely follow up logistic regression models to determine the moment when they must be updated, maintaining an strict control over their evolution, the variables in them and relevant changes that can occur in the popula-tion since they were originally designed. The statistical test presented include classical tests such as Kolmogorov-Smirnov and Chi-Squared statistic to measure changes in means of the variables present in the models, plus a novel test designed from the distribution of the models coefficients that allows to measure the moment when a population has changed more than the confidence intervals defined from the original parameters. The methodology was tested using the databases from two real world micro-entrepreneurs credit scoring projects develo-ped between the years 2007 and 2008, with very good results.