The dependence of the conduction band edge of the alkali earth metal bismuthates on their composition

We present a comparative analysis of the conduction band edge of the alkali earth metal bismuthates containing Mg, Ca, Sr, and Ba. The conduction band edges were computed using the method suggested by Butler and Ginley. The calculations reveal that they depend on the bismuthate’s composition and vary over a wide range. We demonstrate that the energy of the conduction band increases in the series Ca?→?Sr?→?Ba. It also increases with an increase of the alkali earth metal content. The performed calculations help to determine the potential alkali earth metal bismuthate photocatalysts. The most promising compositions found in this study include strontium and barium bismuthates in which the number of the alkali earth metal atoms in the cationic sublattice exceeds the number of the bismuth atoms.     

Synthesis, characterization, and ion-exchange properties of colloidal zeolite nanocrystals

Here, we present physical–chemical properties of Linde type A (LTA) zeolite crystals synthesized via conventional hydrothermal and microwave heating methods. Both heating methods produced LTA crystals that were sub-micron in size, highly negatively charged, super-hydrophilic, and stable when dispersed in water. However, microwave heating produced relatively narrow crystal size distributions, required much shorter heating times, and did not significantly change composition, crystallinity, or surface chemistry. Moreover, microwave heating allowed systematic variation of crystal size by varying heating temperature and time during the crystallization reaction, thus producing a continuous gradient of crystal sizes ranging from about 90 to 300 nm. In ion-exchange studies, colloidal zeolites exhibited excellent sorption kinetics and capacity for divalent metal ions, suggesting their potential for use in water softening, scale inhibition, and scavenging of toxic metal ions from water.     

Ultrasonic technology for enhanced oil recovery from failing oil wells and the equipment for its implemention

A new method for the ultrasonic enhancement of oil recovery from failing wells is described. The technology involves lowering a source of power ultrasound to the bottom of the well either for a short treatment before removal or as a permanent placement for intermittent use. In wells where the permeability is above 20 mD and the porosity is greater than 15% ultrasonic treatment can increase oil production by up to 50% and in some cases even more. For wells of lower permeability and porosity ultrasonic treatment alone is less successful but high production rates can be achieved when ultrasound is applied in conjunction with chemicals. An average productivity increase of nearly 3 fold can be achieved for this type of production well using the combined ultrasound with chemical treatment technology.     

On a Question of Haskell P. Rosenthal Concerning a Characterization of c0 and lp

The following property of a normalized basis in a Banach spaceis considered: any normalized block sequence of the basis hasa subsequence equivalent to the basis. Under uniformity or othernatural assumptions, a basis with this property is equivalentto the unit vector basis of c₀ or l_p. An analogous problem concerningspreading models is also addressed. 2000 Mathematics SubjectClassification 46B20 (primary), 46B15 (secondary).     

Multivariate dynamic modeling for Bayesian forecasting of business revenue

Forecasting enterprise-wide revenue is critical to many companies and presents several challenges and opportunities for significant business impact. This case study is based on model developments to address these challenges for forecasting in a large-scale retail company. Focused on multivariate revenue forecasting across collections of supermarkets and product categories, hierarchical dynamic models are natural: these are able to couple revenue streams in an integrated forecasting model, while allowing conditional decoupling to enable relevant and sensitive analysis together with scalable computation. Structured models exploit multi-scale modeling to cascade information on price and promotion activities as predictors relevant across categories and groups of stores. With a context-relevant focus on forecasting revenue 12 weeks ahead, the study highlights product categories that benefit from multi-scale information, defines insights into when, how, and why multivariate models improve forecast accuracy, and shows how cross-category dependencies can relate to promotion decisions in one category impacting others. Bayesian modeling developments underlying the case study are accessible in custom code for interested readers.     

Information acquisition and disclosure by firms in the presence of additional available information

In this paper we analyze a model which addresses two stylized facts which have received little attention in disclosure theory. (a) Information that is acquired for internal decision-making can subsequently be disclosed to outside investors who can use it to update their assessment of the firm’s prospects. Thus, the decision to gather information in the first place does not only depend on the decision value of information. (b) Information disclosed by firms is only one element of the information environment upon which investors can draw. This setting creates an interaction between firms’ information gathering and disclosure decisions as well as alternative sources of information. We identify an equilibrium structure which we call a Countersignaling equilibrium in which only average firms acquire information whereas good and bad firms do not. We show that while several equilibria can coexist, a Countersignaling equilibrium is often the economically most efficient one.     

Characterisation of ancient Roman wall-painting fragments using non-destructive IBA and MA-XRF techniques

Scientific investigation is very important in studies addressing issues of archaeological and historical objects. Ion beam analysis (IBA) and macro X-ray fluorescence (MA-XRF) spectroscopy are remarkable tools to obtain information about elemental composition and imaging of historical artefacts with a non-invasive character. These investigation techniques were employed in the framework of a project aimed at supporting the characterization of materials and techniques related with the Roman wall painting. The archaeological excavations at Villa della Piscina in Rome have revealed a luxury building with a large pool (about 50 m long) and thermal baths and numerous fragments of plaster, coming from intentional demolitions referable to two distinct architectural contexts of the Villa during the imperial age, have been found. This work deals with studying the interesting wall pictorial apparatus of great cultural value of the heritage inherited from the Roman age in the area of the ancient city of Rome. The colour palette of the pigments investigated, in particular, by MA-XRF and particle-induced X-ray emission (PIXE) and has revealed Fe, Cu, Pb, Si and Hg as main elements. Traces of other constituents uncover the choice of the different colours chosen by the artists who had embellished the rooms of the Villa.     

Colloidal Analysis of Particles Extracted from Microalloyed Steels

Different colloidal particle characterization methods are examined for their suitability to determine the particle size distribution of particles extracted from steels. Microalloyed steels are dissolved to extract niobium and titanium carbonitride particles that are important for the mechanical properties of these steels. Such particles have sizes ranging from several nanometers to hundreds of nanometers depending on the precipitation stage during the thermomechanically controlled rolling process. The size distribution of the particles is analyzed by dynamic light scattering (DLS), analytical ultracentrifugation (AUC), and hollow fiber flow field-flow fractionation (HF5) and compared to data obtained for reference particles as well as data from electron microscopy, the standard sizing technique used in metallurgy today. AUC and HF5 provide high-quality size distributions, average over large particle numbers that enables statistical analysis, and yield useful insights for alloy design; however, DLS fails due to a lack of resolution. Important aspects in the conversion and comparison of size distributions obtained for broadly distributed particle systems with different measurement principles and the role of surfactants used in sample preparation are discussed.     

Opinion Polarization in Human Communities Can Emerge as a Natural Consequence of Beliefs Being Interrelated

The emergence of opinion polarization within human communities—the phenomenon that individuals within a society tend to develop conflicting attitudes related to the greatest diversity of topics—has been a focus of interest for decades, both from theoretical and modelling points of view. Regarding modelling attempts, an entire scientific field—opinion dynamics—has emerged in order to study this and related phenomena. Within this framework, agents’ opinions are usually represented by a scalar value which undergoes modification due to interaction with other agents. Under certain conditions, these models are able to reproduce polarization—a state increasingly familiar to our everyday experience. In the present paper, an alternative explanation is suggested along with its corresponding model. More specifically, we demonstrate that by incorporating the following two well-known human characteristics into the representation of agents: (1) in the human brain beliefs are interconnected, and (2) people strive to maintain a coherent belief system; polarization immediately occurs under exposure to news and information. Furthermore, the model accounts for the proliferation of fake news, and shows how opinion polarization is related to various cognitive biases.