An enhanced concave program relaxation for choice network revenue management

The network choice revenue management problem models customers as choosing from an offer-set, andthe firm decides the best subset to offer at any given moment to maximize expected revenue. The resultingdynamic program for the firm is intractable and approximated by a deterministic linear programcalled the CDLP which has an exponential number of columns. However, under the choice-set paradigmwhen the segment consideration sets overlap, the CDLP is difficult to solve. Column generation has beenproposed but finding an entering column has been shown to be NP-hard. In this paper, starting with aconcave program formulation based on segment-level consideration sets called SDCP, we add a class ofconstraints called product constraints, that project onto subsets of intersections. In addition we proposea natural direct tightening of the SDCP called ?SDCP, and compare the performance of both methodson the benchmark data sets in the literature. Both the product constraints and the ?SDCP method arevery simple and easy to implement and are applicable to the case of overlapping segment considerationsets. In our computational testing on the benchmark data sets in the literature, SDCP with productconstraints achieves the CDLP value at a fraction of the CPU time taken by column generation and webelieve is a very promising approach for quickly approximating CDLP when segment consideration setsoverlap and the consideration sets themselves are relatively small.

Validation procedures in radiological diagnostic models. Neural network and logistic regression

The objective of this paper is to compare the performance of twopredictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validation methods did not reveal statistically significant differences between LR and NN rules. The neural network classifier performs better than the one based on logistic regression. This advantage is well detected by three-fold cross-validation, but remains unnoticed when leave-one-out or bootstrap algorithms are used.

Hybrid risk adjustment for pharmaceutical benefits

This paper analyses the application of hybrid risk adjustment versus either prospective orconcurrent risk adjustment formulae in the context of funding pharmaceutical benefits for thepopulation of an integrated healthcare delivery organization in Catalonia during years 2002 and2003. We apply a mixed formula and find that a hybrid risk adjustment model increasesincentives for efficiency in the provision of low risk individuals at health organizations not only asa whole but also at each internal department compared to only prospective models by reducingwithin-group variation of drug expenditures.

Socio-economic benefits of using space technologies to monitor and respond to earthquakes

Earthquakes represent a major hazard for populations around the world, causing frequent loss of life,human suffering and enormous damage to homes, other buildings and infrastructure. The Technology Resources forEarthquake Monitoring and Response (TREMOR) Team of 36 space professionals analysed this problem over thecourse of the International Space University Summer Session Program and published their recommendations in the formof a report. The TREMOR Team proposes a series of space- and ground-based systems to provide improved capabilityto manage earthquakes. The first proposed system is a prototype earthquake early-warning system that improves theexisting knowledge of earthquake precursors and addresses the potential of these phenomena. Thus, the system willat first enable the definitive assessment of whether reliable earthquake early warning is possible through precursormonitoring. Should the answer be affirmative, the system itself would then form the basis of an operational earlywarningsystem. To achieve these goals, the authors propose a multi-variable approach in which the system will combine,integrate and process precursor data from space- and ground-based seismic monitoring systems (already existing andnew proposed systems) and data from a variety of related sources (e.g. historical databases, space weather data, faultmaps). The second proposed system, the prototype earthquake simulation and response system, coordinates the maincomponents of the response phase to reduce the time delays of response operations, increase the level of precisionin the data collected, facilitate communication amongst teams, enhance rescue and aid capabilities and so forth. It isbased in part on an earthquake simulator that will provide pre-event (if early warning is proven feasible) and post-eventdamage assessment and detailed data of the affected areas to corresponding disaster management actors by means of ageographic information system (GIS) interface. This is coupled with proposed mobile satellite communication hubs toprovide links between response teams. Business- and policy-based implementation strategies for these proposals, suchas the establishment of a non-governmental organisation to develop and operate the systems, are included.

Nets: Network estimation for time series

This work proposes novel network analysis techniques for multivariate time series.We define the network of a multivariate time series as a graph where verticesdenote the components of the process and edges denote non zero long run partialcorrelations. We then introduce a two step LASSO procedure, called NETS, toestimate high dimensional sparse Long Run Partial Correlation networks. This approachis based on a VAR approximation of the process and allows to decomposethe long run linkages into the contribution of the dynamic and contemporaneousdependence relations of the system. The large sample properties of the estimatorare analysed and we establish conditions for consistent selection and estimation ofthe non zero long run partial correlations. The methodology is illustrated with anapplication to a panel of U.S. bluechips.

The evolution of recent research on Catalan literature through the production of PhD theses: a bibliometric and social network analysis

Introduction. This paper studies the situation of research on Catalan literature between 1976 and 2003 by carrying out a bibliometric and social network analysis of PhD theses defended in Spain. It has a dual aim: to present interesting results for the discipline and to demonstrate the methodological efficacy of scientometric tools in the humanities, a field in which they are often neglected due to the difficulty of gathering data. Method. The analysis was performed on 151 records obtained from the TESEO database of PhD theses. The quantitative estimates include the use of the UCINET and Pajek software packages. Authority control was performed on the records. Analysis. Descriptive statistics were used to describe the sample and the distribution of responses to each question. Sex differences on key questions were analysed using the Chi-squared test. Results. The value of the figures obtained is demonstrated. The information obtained on the topic and the periods studied in the theses, and on the actors involved (doctoral students, thesis supervisors and members of defence committees), provide important insights into the mechanisms of humanities disciplines. The main research tendencies of Catalan literature are identified. It is observed that the composition of members of the thesis defence committees follows Lotka's Law. Conclusions. Bibliometric analysis and social network analysis may be especially useful in the humanities and in other fields which are lacking in scientometric data in comparison with the experimental sciences.

Gp74 a membrane glycoprotein of the cis-Golgi network that cycles through the endoplasmic reticulum and intermediate compartment

A monoclonal antibody CC92 (IgM), raised against a fraction of rat liver enriched in Golgi membranes, recognizes a novel Endo H-resistant 74-kD membrane glycoprotein (gp74). The bulk of gp74 is confined to the cis-Golgi network (CGN). Outside the Golgi gp74 is found in tubulovesicular structures and ER foci. In cells incubated at 37 degrees C the majority of gp74 is segregated from the intermediate compartment (IC) marker p58. However, in cells treated with organelle perturbants such as low temperature, BFA, and [AIF4]- the patterns of the two proteins become indistinguishable. Both proteins are retained in the Golgi complex at 20 degrees C and in the IC at 15 degrees C. Incubation of cells with BFA results in relocation of gp74 to p58 positive IC elements. [AIF4]- induces the redistribution of gp74 from the Golgi to p58-positive vesicles and does not retard the translocation of gp74 to IC elements in cells treated with BFA. Disruption of microtubules by nocodazol results in the rapid disappearance of the Golgi elements stained by gp74 and redistribution of the protein into vesicle-like structures. The responses of gp74 to cell perturbants are in sharp contrast with those of cis/middle and trans-Golgi resident proteins whose location is not affected by low temperatures or [AIF4]-, are translocated to the ER upon addition of BFA, and stay in slow disintegrating Golgi elements in cells treated with nocodazol. The results suggest that gp74 is an itinerant protein that resides most of the time in the CGN and cycles through the ER/IC following the pathway used by p58.

An investment social network beside the Banco de Barcelona, an unusual case?

[cat] L’extensió de les activitats bancàries al segle XIX va ser liderat per alguns grups socials connectats amb el comerç, que van treure profit de la seva experiència i coneixement per estendre la seva influència al voltant del món del crèdit. A la historiografia espanyola, hi ha un conjunt de treballs que s’han centrat en aquesta gent, però en molts pocs casos s’ha fet una classificació que permeti detectar el conjunt de grups econòmics que han liderat el procés de modernització financera de l’Espanya de mitjans del segle XIX. El principal objectiu del treball és l’anàlisi dels grups socials que van formar el Banco de Barcelona entre 1844 i 1854. Aquesta institució va ser important per a la història financera i bancària d’Espanya per ser pionera en la seva activitat creditícia i d’emissió: a més, la seva experiència va servir com a base en la constitució d’un sistema financer modern a Espanya. En una societat com la catalana de mitjans del segle XIX, la confiança era un factor important per explicar la decisió d’invertir. L’aparició de noves companyies i les seves necessitats d’inversió van transformar el comportaments previs. Quin va ser el comportament dels inversors potencials? Va ser el grup que hi havia al voltant del banc el que va ascendir econòmicament en els anys centrals del segle XIX? La resposta és prou clara, els membres del consell d’administració del Banc de Barcelona formaven un grup apart dins dels grups que sorgeixen a l’economia catalana en el seu conjunt.

Hay competencia en el mercado europeo de transporte aéreo?: el caso español

La liberalización del transporte aéreo que se llevó a término en la Unión Europea a principios de los años noventa ha tenido efectos positivos sobre el bienestar del viajero. No obstante, existe un consenso en la literatura académica que estos efectos dependen de la existencia de una competencia efectiva en el nivel de la ruta. En este sentido, se plantea el problema que puede llegar a suponer las ventajas de escalera de las compañías dominantes en cada mercado interior. Además, se pretende capturar la diferenciación de productos como característica esencial de la industria del transporte aéreo. El análisis de estas cuestiones se realiza de la forma siguiente. En primer lugar, se hace referencia a los principales aspectos económicos que condicionan la competencia en el transporte aéreo. Y en segundo lugar, se implementa un modelo empírico basado en un sistema de tres ecuaciones, que se estima mediante la técnica de las variables instrumentales. La muestra utilizada hace referencia al año 2001 para la mayoría de las rutas del mercado interior español de vuelos regulares en dónde hay competencia. Los resultados de la estimación muestran la existencia de unas condiciones de competencia diferentes según el segmento del mercado al cual se dirigen las compañías aéreas. Efectivamente, la competencia en precios (calidad) parece ser predominante en el segmento de viajeros por motivos personales (negocios). Adicionalmente, el dominio que la compañía dominante tiene sobre la mayoría de las rutas parece descansar en las ventajas competitivas, tanto en términos de costes como en términos de demanda, que le proporciona el control de la red aeroportuaria nacional. De todo esto se puede inferir que el mantenimiento y/o aumento de los beneficios de la liberalización de los servicios de transporte aéreo exige extender la liberalización al uso del aeropuertos así como descentralizar su gestión.

Optimal network topologies for local search with congestion

The problem of searchability in decentralized complex networks is of great importance in computer science, economy, and sociology. We present a formalism that is able to cope simultaneously with the problem of search and the congestion effects that arise when parallel searches are performed, and we obtain expressions for the average search cost both in the presence and the absence of congestion. This formalism is used to obtain optimal network structures for a system using a local search algorithm. It is found that only two classes of networks can be optimal: starlike configurations, when the number of parallel searches is small, and homogeneous-isotropic configurations, when it is large.

Self-similar community structure in a network of human interactions

We propose a procedure for analyzing and characterizing complex networks. We apply this to the social network as constructed from email communications within a medium sized university with about 1700 employees. Email networks provide an accurate and nonintrusive description of the flow of information within human organizations. Our results reveal the self-organization of the network into a state where the distribution of community sizes is self-similar. This suggests that a universal mechanism, responsible for emergence of scaling in other self-organized complex systems, as, for instance, river networks, could also be the underlying driving force in the formation and evolution of social networks.

Hierarchical neural network with high storage capacity

A recent method used to optimize biased neural networks with low levels of activity is applied to a hierarchical model. As a consequence, the performance of the system is strongly enhanced. The steps to achieve optimization are analyzed in detail.

Modelling diffusion of innovations in a social network

A simple model of diffusion of innovations in a social network with upgrading costs is introduced. Agents are characterized by a single real variable, their technological level. According to local information, agents decide whether to upgrade their level or not, balancing their possible benefit with the upgrading cost. A critical point where technological avalanches display a power-law behavior is also found. This critical point is characterized by a macroscopic observable that turns out to optimize technological growth in the stationary state. Analytical results supporting our findings are found for the globally coupled case.