Plasma lipids are affected similarly by dietary lauric or palmitic acid in gerbils and monkeys

To compare the relative impact of dietary lauric acid (12∶0) and palmitic acid (16∶0) on plasma lipids, two fat-sensitive species, Mongolian gerbils and cebus monkeys, were fed cholesterol-free, purified diets enriched with either 12∶0-rich or 16∶0-rich fats, while all other fatty acids were held constant by selective blending of up to five natural fats or oils. The two gerbil diets (40 en% from fat) allowed for an 8 en% exchange between 12∶0 and 16∶0, and the monkey diets (31 en% from fat) allowed for 6 en% exchange beteen these two fatty acids. Eight gerbils received the diets for eight weeks, and 12 cebus monkeys were fed each diet in a cross-over design for up to 22 wk. Both diets resulted in similar plasma cholesterol, triglyceride, and high density lipoprotein cholesterol concentrations within each species. Additionally, separation of cebus lipoproteins by discontinuous density-gradient ultracentrifugation failed to show any dietary differences in concentration or composition of the three major lipoprotein classes (d<1.019, 1.019–1.055, and 1.055–1.168 g/mL). Thus, in two species sensitive to manipulations in dietary fat while consuming cholesterol-free diets, 16∶0 was not hypercholesterolemic relative to 12∶0. Based on a paper presented at the PORIM International Palm Oil Congress (PIPOC) held in Kuala Lumpur, Malaysia, September 1993.     

Nondestructive NMR determination of oil composition in transformed canola seeds

Magic-angle spinning (MAS) ¹³C nuclear magnetic resonance (NMR) spectroscopy is a convenient method for nondestructive, quantitative characterization of seed oil composition. We describe results for intact hybrid and transformed canola seeds. The MAS ¹³C NMR technique complements and agrees with gas chromatography results. The spectral resolution approaches that of neat, liquid oils. MAS ¹³C NMR data allow quantitative analysis of major oil components, including saturates and oleic, linoleic, and linolenic acyl chains. ¹³C NMR directly and quantitatively elucidates, triglyceride regiochemistry and acyl chain cis-trans isomers that cannot be quickly detected by other methods. MAS ¹³C NMR can serve as the primary method for development of near-infrared seed oil calibrations. These NMR methods are nondestructive and attractive for plant-breeding programs or other studies (e.g., functional genomics) where loss of seed viability is inconvenient.     

Relations among categorization, induction, recognition, and similarity: Comment on Sloutsky and Fisher (2004).

V. M. Sloutsky and A. V. Fisher (see record 2004-14313-002) reported 5 experiments documenting relations among categorization, induction, recognition, and similarity in children as well as adults and proposed a new model of induction, SINC (similarity, induction, categorization). Those authors concluded that induction depends on perceptual similarity rather than conceptual knowledge. Despite the useful contributions of this work, there are some important limitations. The experimental designs examined a limited range of phenomena that are not the most revealing about the use of nonperceptual information. The main results involved a simple triad task, for which the SINC model's predictions are equivalent to the predictions of previous models of inductive reasoning. It is also unclear whether the SINC model can account for the observed relations between similarity and recognition. Implications for future work on induction and related cognitive activities are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Simulator-mediated acquisition of a dynamic control skill

Uses of stored skill-models to accelerate simulator-based real-time training in a control skill are discussed. A real-time coach must deliver advice at three levels: (1) what to do next, (2) what to watch for, and (3) what went wrong. Human learning and machine learning results are presented using different screen representations of a pole-and-cart balancing task.     

OWL-QL—a language for deductive query answering on the Semantic Web

This paper discusses the issues involved in designing a query language for the Semantic Web and presents the OWL query language (OWL-QL) as a candidate standard language and protocol for query–answering dialogues among Semantic Web computational agents using knowledge represented in the W3Cs ontology web language (OWL). OWL-QL is a formal language and precisely specifies the semantic relationships among a query, a query answer, and the knowledge base(s) used to produce the answer. Unlike standard database and Web query languages, OWL-QL supports query–answering dialogues in which the answering agent may use automated reasoning methods to derive answers to queries, as well as dialogues in which the knowledge to be used in answering a query may be in multiple knowledge bases on the Semantic Web, and/or where those knowledge bases are not specified by the querying agent. In this setting, the set of answers to a query may be of unpredictable size and may require an unpredictable amount of time to compute.     

Low-temperature X-ray microanalysis of the differentiating vascular tissue in root tips of Lemna minor L

The fracture faces of bulk-frozen tissue offer a number of advantages for the analysis of diffusible elements. They are easy to prepare, remain uncontaminated, and, unlike most frozen-hydrated sections, can be shown to exist in a fully hydrated state throughout examination and analysis. Root tips of Lemna minor briefly treated with a polymeric cryoprotectant are quench frozen in melting nitrogen. Fractures are prepared using the AMRAY Biochamber, lightly etched if necessary to reveal surface detail and carbon coated while maintaining the specimen at 110 K. The frozen-hydrated fracture faces are analysed at 110 K using the P/B ratio method which is less sensitive to changes in surface geometry and variations in beam current. The method has been used to investigate the distribution of seven elements (Na+, Mg⁺⁺, P, S, Cl^?, K+ and Ca⁺⁺) in the developing vascular tissue of the root tip. The microprobe can measure relative elemental ratios at the cellular level and the results from this present study reveal important variations in different parts of the root. The younger, more actively dividing cells, appear to have a slightly higher concentration of diffusible ions in comparison to the somewhat older tissues which have begun to differentiate into what are presumed to be functional vascular elements.     

Microfluidic switchboards with integrated inertial pumps

Arrays of H-shaped microfluidic channels connecting two different fluidic reservoirs have been built with silicon/SU8 microfabrication technologies utilized in production of thermal inkjet printheads. The fluids are delivered to the channels via slots etched through the silicon wafer. Every H-shaped channel comprises four thermal inkjet resistors, one in each of the four legs. The resistors vaporize water and generate drive bubbles that pump the fluids from the bulk reservoirs into and out of the channels. By varying relative frequencies of the four pumps, input fluids can be routed to any part of the network in any proportion. Several fluidic operations including dilution, mixing, dynamic valving, and routing have been demonstrated. Thus, a fully integrated microfluidic switchboard that does not require external sources of mechanical power has been achieved. A matrix formalism to describe flow in complex switchboards has been developed and tested.     

Investigation of Freeze Lining in Copper-Containing Slag Systems: Part III. High-Temperature Experimental Investigation of the Effect of Bath Agitation

Freeze-lining technologies have been employed to protect the cooling walls of reactors from chemically aggressive molten reactants. To date, the designs of freeze linings for pyrometallurgical reactors have been based on the basic assumption that the interface between the deposit and the bath remains at the liquidus temperature of the bulk liquid. There is, however, increasing evidence that interface temperature between stagnant deposit and bath is less than the liquidus of the bulk liquid. A previous study also demonstrated that the effects of bath chemistry need to be taken into account in freeze-lining designs. To investigate the fundamental processes involved in the formation and stability of the deposit, experimental laboratory studies have been undertaken in the Cu-Fe-Si-Al-O slag system in equilibrium with metallic copper using an air-cooled probe technique. In the current study, the effects of bath agitation on the microstructure, morphologies of the phases, and formation of various layers across the freeze-lining deposit were studied at steady-state conditions. It appears that the changes in the fluid flow pattern through changes in shear intensities result in corresponding changes in the deposit microstructure, formation of the sealing primary phase layer, thus influencing the interface temperature between freeze-lining deposit and the liquid bath.     

Cryptocurrency value formation: An empirical study leading to a cost of production model for valuing bitcoin

This paper aims to identify the likely determinants for cryptocurrency value formation, including for that of bitcoin. Due to Bitcoin’s growing popular appeal and merchant acceptance, it has become increasingly important to try to understand the factors that influence its value formation. Presently, the value of all bitcoins in existence represent approximately $7 billion, and more than $60 million of notional value changes hands each day. Having grown rapidly over the past few years, there is now a developing but vibrant marketplace for bitcoin, and a recognition of digital currencies as an emerging asset class. Not only is there a listed and over-the-counter market for bitcoin and other digital currencies, but also an emergent derivatives market. As such, the ability to value bitcoin and related cryptocurrencies is becoming critical to its establishment as a legitimate financial asset.Using cross-sectional empirical data examining 66 of the most widely used cryptocurrencies, a regression model was estimated that points to three main drivers of cryptocurrency value: the level of competition in the network of producers, the rate of unit production, and the difficulty of algorithm used to “mine” for the cryptocurrency. These amount to relative differences in the cost of production of one digital currency over another at the margin, pointing to differences in relative cost of production – electricity goes in, cryptocurrency comes out. Using that as a starting point, a no-arbitrage situation is established for Bitcoin-like cryptocurrencies followed by the formalization of a cost of production model to determine the fair value of a bitcoin.