Budget feasible mechanisms on matroids

Motivated by many practical applications, in this paper we study budget feasible mechanisms where the goal is to procure independent sets from matroids. More specifically, we are given a matroid =(,) where each ground (indivisible) element is a selfish agent. The cost of each element (i.e., for selling the item or performing a service) is only known to the element itself. There is a buyer with a budget having additive valuations over the set of elements E. The goal is to design an incentive compatible (truthful) budget feasible mechanism which procures an independent set of the matroid under the given budget that yields the largest value possible to the buyer. Our result is a deterministic, polynomial-time, individually rational, truthful and budget feasible mechanism with 4-approximation to the optimal independent set. Then, we extend our mechanism to the setting of matroid intersections in which the goal is to procure common independent sets from multiple matroids. We show that, given a polynomial time deterministic blackbox that returns -approximation solutions to the matroid intersection problem, there exists a deterministic, polynomial time, individually rational, truthful and budget feasible mechanism with (3+1) -approximation to the optimal common independent set

On-demand or Spot? Selling the cloud to risk-averse customers

In Amazon EC2, cloud resources are sold through a combination of an on-demand market, in which customers buy resources at a fixed price, and a spot market, in which customers bid for an uncertain supply of excess resources. Standard market environments suggest that an optimal design uses just one type of market. We show the prevalence of a dual market system can be explained by heterogeneous risk attitudes of customers. In our stylized model, we consider unit demand risk-averse bidders. We show the model admits a unique equilibrium, with higher revenue and higher welfare than using only spot markets. Furthermore, as risk aversion increases, the usage of the on-demand market increases. We conclude that risk attitudes are an important factor in cloud resource allocation and should be incorporated into models of cloud markets.Comment: Appeared at WINE 201

Welfare and Revenue Guarantees for Competitive Bundling Equilibrium

We study equilibria of markets with $m$ heterogeneous indivisible goods and $n$ consumers with combinatorial preferences. It is well known that a competitive equilibrium is not guaranteed to exist when valuations are not gross substitutes. Given the widespread use of bundling in real-life markets, we study its role as a stabilizing and coordinating device by considering the notion of \emph{competitive bundling equilibrium}: a competitive equilibrium over the market induced by partitioning the goods for sale into fixed bundles. Compared to other equilibrium concepts involving bundles, this notion has the advantage of simulatneous succinctness ($O(m)$ prices) and market clearance. Our first set of results concern welfare guarantees. We show that in markets where consumers care only about the number of goods they receive (known as multi-unit or homogeneous markets), even in the presence of complementarities, there always exists a competitive bundling equilibrium that guarantees a logarithmic fraction of the optimal welfare, and this guarantee is tight. We also establish non-trivial welfare guarantees for general markets, two-consumer markets, and markets where the consumer valuations are additive up to a fixed budget (budget-additive). Our second set of results concern revenue guarantees. Motivated by the fact that the revenue extracted in a standard competitive equilibrium may be zero (even with simple unit-demand consumers), we show that for natural subclasses of gross substitutes valuations, there always exists a competitive bundling equilibrium that extracts a logarithmic fraction of the optimal welfare, and this guarantee is tight. The notion of competitive bundling equilibrium can thus be useful even in markets which possess a standard competitive equilibrium

Pricing Multi-Unit Markets

We study the power and limitations of posted prices in multi-unit markets, where agents arrive sequentially in an arbitrary order. We prove upper and lower bounds on the largest fraction of the optimal social welfare that can be guaranteed with posted prices, under a range of assumptions about the designer's information and agents' valuations. Our results provide insights about the relative power of uniform and non-uniform prices, the relative difficulty of different valuation classes, and the implications of different informational assumptions. Among other results, we prove constant-factor guarantees for agents with (symmetric) subadditive valuations, even in an incomplete-information setting and with uniform prices

Distributed Scheduling of Recording Tasks with Interconnected Servers

We consider a system with multiple interconnected video servers storing TV programs that are received through satellite antennas. Users, equipped with set-top boxes, submit requests for TV programs, to each of which they assign a utility value according to their preferences. We develop a distributed scheduling algorithm that selects the programs to be recorded and the servers to store them, so that a high total utility is generated to the users' population. Our scheduling algorithm is based on the programs' broadcasting information, the users' preferences, the constraints regarding the capabilities of simultaneous recordings and storage, and the system's topology. In fact, servers belonging to the same cluster co-operate in order to attain increased e#ciency by exchanging content through streaming or replication. The e#cient performance of our scheduling algorithm is shown by means of experiments. The algorithm constitutes a practically applicable solution, already implemented and integrated in the testbed of the IST project UP-TV

Revealed Preference Dimension via Matrix Sign Rank

Given a data-set of consumer behaviour, the Revealed Preference Graph succinctly encodes inferred relative preferences between observed outcomes as a directed graph. Not all graphs can be constructed as revealed preference graphs when the market dimension is fixed. This paper solves the open problem of determining exactly which graphs are attainable as revealed preference graphs in $d$-dimensional markets. This is achieved via an exact characterization which closely ties the feasibility of the graph to the Matrix Sign Rank of its signed adjacency matrix. The paper also shows that when the preference relations form a partially ordered set with order-dimension $k$, the graph is attainable as a revealed preference graph in a $k$-dimensional market.Comment: Submitted to WINE `1

Aggregated impact of allowance allocation and power dispatching on emission reduction

Climate change has become one of the most important issues for the sustainable development of social well-being. China has made great efforts in reducing CO2 emissions and promoting clean energy. Pilot Emission Trading Systems (ETSs) have been launched in two provinces and five cities in China, and a national level ETS will be implemented in the third quarter of 2017, with preparations for China’s national ETS now well under way. In the meantime, a new round of China’s electric power system reform has entered the implementation stage. Policy variables from both electricity and emission markets will impose potential risks on the operation of generation companies (GenCos). Under this situation, by selecting key variables in each domain, this paper analyzes the combined effects of different allowance allocation methods and power dispatching models on power system emission. Key parameters are set based on a provincial power system in China, and the case studies are conducted based on dynamic simulation platform for macro-energy systems (DSMES) software developed by the authors. The selected power dispatching models include planned dispatch, energy saving power generation dispatch and economic dispatch. The selected initial allowance allocation methods in the emission market include the grandfathering method based on historical emissions and the benchmarking method based on actual output. Based on the simulation results and discussions, several policy implications are highlighted to help to design an effective emission market in China

Methods designed for the identification and characterization of in vitro and in vivo chromatin assembly mutants in Saccharomyces cerevisiae

Assembly of DNA into chromatin allows for the formation of a barrier that protects naked DNA from protein and chemical agents geared to degrade or metabolize DNA. Chromatin assembly occurs whenever a length of DNA becomes exposed to the cellular elements, whether during DNA synthesis or repair. This report describes tools to study chromatin assembly in the model system Saccharomyces cerevisiae. Modifications to an in vitro chromatin assembly assay are described that allowed a brute force screen of temperature sensitive (ts) yeast strains in order to identify chromatin assembly defective extracts. This screen yielded mutations in genes encoding two ubiquitin protein ligases (E3s): RSP5, and a subunit of the Anaphase Promoting Complex (APC), APC5. Additional modifications are described that allow for a rapid analysis and an in vivo characterization of yeast chromatin assembly mutants, as well as any other mutant of interest. Our analysis suggests that the in vitro and in vivo chromatin assembly assays are responsive to different cellular signals, including cell cycle cues that involve different molecular networks

Interrater reliability of the mind map assessment rubric in a cohort of medical students

<p>Abstract</p> <p>Background</p> <p>Learning strategies are thinking tools that students can use to actively acquire information. Examples of learning strategies include mnemonics, charts, and maps. One strategy that may help students master the tsunami of information presented in medical school is the mind map learning strategy. Currently, there is no valid and reliable rubric to grade mind maps and this may contribute to their underutilization in medicine. Because concept maps and mind maps engage learners similarly at a metacognitive level, a valid and reliable concept map assessment scoring system was adapted to form the mind map assessment rubric (MMAR). The MMAR can assess mind map depth based upon concept-links, cross-links, hierarchies, examples, pictures, and colors. The purpose of this study was to examine interrater reliability of the MMAR.</p> <p>Methods</p> <p>This exploratory study was conducted at a US medical school as part of a larger investigation on learning strategies. Sixty-six (<it>N </it>= 66) first-year medical students were given a 394-word text passage followed by a 30-minute presentation on mind mapping. After the presentation, subjects were again given the text passage and instructed to create mind maps based upon the passage. The mind maps were collected and independently scored using the MMAR by 3 examiners. Interrater reliability was measured using the intraclass correlation coefficient (<it>ICC</it>) statistic. Statistics were calculated using SPSS version 12.0 (Chicago, IL).</p> <p>Results</p> <p>Analysis of the mind maps revealed the following: concept-links <it>ICC </it>= .05 (95% CI, -.42 to .38), cross-links <it>ICC </it>= .58 (95% CI, .37 to .73), hierarchies <it>ICC </it>= .23 (95% CI, -.15 to .50), examples <it>ICC </it>= .53 (95% CI, .29 to .69), pictures <it>ICC </it>= .86 (95% CI, .79 to .91), colors <it>ICC </it>= .73 (95% CI, .59 to .82), and total score <it>ICC </it>= .86 (95% CI, .79 to .91).</p> <p>Conclusion</p> <p>The high <it>ICC </it>value for total mind map score indicates strong MMAR interrater reliability. Pictures and colors demonstrated moderate to strong interrater reliability. We conclude that the MMAR may be a valid and reliable tool to assess mind maps in medicine. However, further research on the validity and reliability of the MMAR is necessary.</p