Selective External Oxidation of the Intermetallic Compound, BaAg_5

The selective oxidation of BaAg_5 has been examined at 650–680°C in flowing 3%H2/Ar (po2 ≤ 1.1×x×10^–19atm). Under these conditions, a continuous external barium oxide scale formed. Depletion of Ba from the underlying BaAg_5 led to the formation of a continuous Ag layer between the oxide scale and the BaAg_5. Ba was only detected along grain boundaries in the continuous Ag layer, which was consistent with the negligible solubility reported for Ba in bulk Ag. The local thickness of the continuous Ag layer was inversely correlated to the local Ag grain size. Subsequent experiments with Ag-clad BaAg_5 revealed that surface oxide formation commenced at exposed Ag grain boundaries. BaAg_5 specimens clad with fine grained Ag foil exhibited more extensive oxide formation in a given time than specimens clad with coarse grained Ag foil. These observations confirmed that outward Ba migration through the continuous Ag layer occurred preferentially along Ag grain boundaries. This work demonstrates that an intermetallic compound may undergo external oxidation even when a continuous metallic (or intermetallic) layer, that possesses a low solubility for the oxidizable element, forms under the oxide scale

Online Linear Optimization with Inventory Management Constraints

This paper considers the problem of online linear optimization with inventory management constraints. Specifically, we consider an online scenario where a decision maker needs to satisfy her timevarying demand for some units of an asset, either from a market with a time-varying price or from her own inventory. In each time slot, the decision maker is presented a (linear) price and must immediately decide the amount to purchase for covering the demand and/or for storing in the inventory for future use. The inventory has a limited capacity and can be used to buy and store assets at low price and cover the demand when the price is high. The ultimate goal of the decision maker is to cover the demand at each time slot while minimizing the cost of buying assets from the market. We propose ARP, an online algorithm for linear programming with inventory constraints, and ARPRate, an extended version that handles rate constraints to/from the inventory. Both ARP and ARPRate achieve optimal competitive ratios, meaning that no other online algorithm can achieve a better theoretical guarantee. To illustrate the results, we use the proposed algorithms in a case study focused on energy procurement and storage management strategies for data centers

Online Linear Optimization with Inventory Management Constraints

This paper considers the problem of online linear optimization with inventory management constraints. Specifically, we consider an online scenario where a decision maker needs to satisfy her time-varying demand for some units of an asset, either from a market with a time-varying price or from her own inventory. In each time slot, the decision maker is presented a (linear) price and must immediately decide the amount to purchase for covering the demand and/or for storing in the inventory for future use. The inventory has a limited capacity and can be used to buy and store assets at low price and cover the demand when the price is high. The ultimate goal of the decision maker is to cover the demand at each time slot while minimizing the cost of buying assets from the market. We propose ARP, an online algorithm for linear programming with inventory constraints, and ARPRate, an extended version that handles rate constraints to/from the inventory. Both ARP and ARPRate achieve optimal competitive ratios, meaning that no other online algorithm can achieve a better theoretical guarantee. To illustrate the results, we use the proposed algorithms in a case study focused on energy procurement and storage management strategies for data centers

Income and Poverty in a Developing Economy

We present a stochastic agent-based model for the distribution of personal incomes in a developing economy. We start with the assumption that incomes are determined both by individual labour and by stochastic effects of trading and investment. The income from personal effort alone is distributed about a mean, while the income from trade, which may be positive or negative, is proportional to the trader's income. These assumptions lead to a Langevin model with multiplicative noise, from which we derive a Fokker-Planck (FP) equation for the income probability density function (IPDF) and its variation in time. We find that high earners have a power-law income distribution while the low income groups have a Levy IPDF. Comparing our analysis with the Indian survey data (obtained from the world bank website) taken over many years we obtain a near-perfect data collapse onto our model's equilibrium IPDF. The theory quantifies the economic notion of "given other things". Using survey data to relate the IPDF to actual food consumption we define a poverty index, which is consistent with traditional indices, but independent of an arbitrarily chosen "poverty line" and therefore less susceptible to manipulation

The Radish Gene Reveals a Memory Component with Variable Temporal Properties

Memory phases, dependent on different neural and molecular mechanisms, strongly influence memory performance. Our understanding, however, of how memory phases interact is far from complete. In Drosophila, aversive olfactory learning is thought to progress from short-term through long-term memory phases. Another memory phase termed anesthesia resistant memory, dependent on the radish gene, influences memory hours after aversive olfactory learning. How does the radish-dependent phase influence memory performance in different tasks? It is found that the radish memory component does not scale with the stability of several memory traces, indicating a specific recruitment of this component to influence different memories, even within minutes of learning

Blockade of adenosine A2B receptors ameliorates murine colitis

Background and purpose: The adenosine 2B (A2B) receptor is the predominant adenosine receptor expressed in the colon. Acting through the A2B receptor, adenosine mediates chloride secretion, as well as fibronectin and interleukin (IL)-6 synthesis and secretion in intestinal epithelial cells. A2B receptor mRNA and protein expression are increased during human and murine colitis. However, the effect of the A2B receptor in the activation of the intestinal inflammatory response is not known. In this study, we examined the effect of A2B receptor antagonism on murine colitis. Experimental approach: Dextran sodium sulphate (DSS)-treated mice and piroxicam-treated IL-10/ mice were used as animal models of colitis. The A2B receptor-selective antagonist, ATL-801, was given in the diet. Key results: Mice fed ATL-801 along with DSS showed a significantly lower extent and severity of colitis than mice treated with DSS alone, as shown by reduced clinical symptoms, histological scores, IL-6 levels and proliferation indices. The administration of ATL-801 prevented weight loss, suppressed the inflammatory infiltrate into colonic mucosa and decreased epithelial hyperplasia in piroxicam-treated IL-10/ mice. IL-6 and keratinocyte-derived chemokine (KC) concentrations in the supernatants of colonic organ cultures from colitic mice were significantly reduced by ATL-801 administration. Conclusions and implications: Taken together, these data demonstrate that the intestinal epithelial A2B receptor is an important mediator of pro-inflammatory responses in the intestine and that A2B receptor blockade may be an effectiv

Protein Microarray On-Demand: A Novel Protein Microarray System

We describe a novel, simple and low-cost protein microarray strategy wherein the microarrays are generated by printing expression ready plasmid DNAs onto slides that can be converted into protein arrays on-demand. The printed expression plasmids serve dual purposes as they not only direct the synthesis of the protein of interest; they also serve to capture the newly synthesized proteins through a high affinity DNA-protein interaction. To accomplish this we have exploited the high-affinity binding (∼3–7×10 −13 M) of E. coli Tus protein to Ter, a 20 bp DNA sequence involved in the regulation of E. coli DNA replication. In our system, each protein of interest is synthesized as a Tus fusion protein and each expression construct directing the protein synthesis contains embedded Ter DNA sequence. The embedded Ter sequence functions as a capture reagent for the newly synthesized Tus fusion protein. This “all DNA” microarray can be converted to a protein microarray on-demand without need for any additional capture reagent.