Workshop on Magmatic Processes of Early Planetary Crusts: Magma Oceans and Stratiform Layered Intrusions

The significance of the lunar highland pristine cumulate samples were reevaluated with the aid of the additional insights provided by geologically constrained terrestrial investigations. This exercise involved a review of the state of knowledge about terrestrial and lunar cumulate rocks as well as an enumeration and reevaluation of the processes hypothesized to have been responsible for their formation, both classically and at present

Theoretical analysis of the demand of money

The paper summarizes current mainstream views concerning the theory of money demand. A utility maximizing household chooses to hold money because it facilitates transactions, allowing it to economize on shopping time. Two types of implied money demand functions are derived: a “proper” demand function with arguments exogenous to the household and a conventional “portfolio balance” relationship. The historical evolution of ideas pertaining to money demand is reviewed. A final section considers ongoing controversies concerning the role of uncertainty, the use of overlapping generations and cash-in-advance models, and the interpretation of empirical results suggestive of extremely slow portfolio adjustment.Money ; Interest rates

Panel discussion I: what have we learned since October 1979?

Monetary policy ; Federal Reserve System - History

Correlation Clustering with Low-Rank Matrices

Correlation clustering is a technique for aggregating data based on qualitative information about which pairs of objects are labeled 'similar' or 'dissimilar.' Because the optimization problem is NP-hard, much of the previous literature focuses on finding approximation algorithms. In this paper we explore how to solve the correlation clustering objective exactly when the data to be clustered can be represented by a low-rank matrix. We prove in particular that correlation clustering can be solved in polynomial time when the underlying matrix is positive semidefinite with small constant rank, but that the task remains NP-hard in the presence of even one negative eigenvalue. Based on our theoretical results, we develop an algorithm for efficiently "solving" low-rank positive semidefinite correlation clustering by employing a procedure for zonotope vertex enumeration. We demonstrate the effectiveness and speed of our algorithm by using it to solve several clustering problems on both synthetic and real-world data

Optimizing ethanol and bioelectricity production in sugarcane biorefineries in Brazil

In sugarcane biorefineries, the lignocellulosic portion of the sugarcane biomass (i.e. bagasse and cane trash) can be used as fuel for electricity production and/or feedstock for second generation (2G) ethanol. This study presents a techno-economic analysis of upgraded sugarcane biorefineries in Brazil, aiming at utilizing surplus bagasse and cane trash for electricity and/or ethanol production. The study investigates the trade-off on sugarcane biomass use for energy production: bioelectricity versus 2G ethanol production. The BeWhere mixed integer and spatially explicit model is used for evaluating the choice of technological options. Different scenarios are developed to find the optimal utilization of sugarcane biomass. The study finds that energy prices, type of electricity substituted, biofuel support and carbon tax, investment costs, and conversion efficiencies are the major factors influencing the technological choice. At the existing market and technological conditions applied in the upgraded biorefineries, 300 PJy^12G ethanol could be optimally produced and exported to the EU, which corresponds to 2.5% of total transport fuel demand in the EU. This study provides a methodological framework on how to optimize the alternative use of agricultural residues and industrial co-products for energy production in agro-industrie

Universal schema for entity type prediction

Categorizing entities by their types is useful in many applications, including knowledge base construction, relation extraction and query intent prediction. Fine-grained entity type ontologies are especially valuable, but typically difficult to design because of unavoidable quandaries about level of detail and boundary cases. Automatically classifying entities by type is challenging as well, usually involving hand-labeling data and training a supervised predictor. This paper presents a universal schema approach to fine-grained entity type prediction. The set of types is taken as the union of textual surface patterns (e.g. appositives) and pre-defined types from available databases (e.g. Freebase) - yielding not tens or hundreds of types, but more than ten thousands of entity types, such as financier, criminologist, and musical trio. We robustly learn mutual implication among this large union by learning latent vector embeddings from probabilistic matrix factorization, thus avoiding the need for hand-labeled data. Experimental results demonstrate more than 30% reduction in error versus a traditional classification approach on predicting fine-grained entities types. © 2013 ACM

Clay as Thermoluminescence Dosemeter in diagnostic Radiology applications

As part of efforts to isolate and utilize local and naturally occurring materials for development of thermoluminescece dosemeters and other technologies, an earlier report had shown that Nigerian clay showedprospects of utility as a thermoluminescence dosemeter (TLD). This paper reports the investigation of the basic thermoluminescence properties of clay at x-rays in the diagnostic radiology range, including dose monitoring in abdominal radiography. Clay sourced from Calabar, Nigeria, was tested for thermoluminescence response after irradiation at diagnostic radiology doses, including application in abdominal radiography dose monitoring in a clinical setting.Results show that thermoluminescence (TL) output in natural clay is very low, but demonstrates enhanced performance with the addition of common salt. Specific TL characteristics of good repeatability for individual and batched pellets (variability index of 3.08%) and a high degree of trap emptying were observed. It had a glow curve peak at 275 C; with traces of spurious thermoluminescence emission at the reader anneal temperature. There was evidence of good batch homogeneity (< 30%) and a similar pattern of dose absorption in abdominal radiography with commercialLithium Fluoride (LiF TLD-100). A high fading rate (over 30% in twelve hours) and low sensitivity (12 times less than LiF TLD-100) however, signal the unacceptability of clay as aTLD in diagnostic radiology in the forms studied. Clay demonstrates poor TL response at diagnostic radiology doses. However, it's water absorbing property offers a means of overcoming the hygroscopic nature of common salt. This could beexplored to improve the use of sodium chloride as a radiation detector.Keywords: Clay, Thermoluminescence, Dosemeter, Detector, Radiology, x-rays