900 resultados para new keynesian models


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The past four decades have witnessed an explosive growth in the field of networkbased facility location modeling. This is not at all surprising since location policy is one of the most profitable areas of applied systems analysis in regional science and ample theoretical and applied challenges are offered. Location-allocation models seek the location of facilities and/or services (e.g., schools, hospitals, and warehouses) so as to optimize one or several objectives generally related to the efficiency of the system or to the allocation of resources. This paper concerns the location of facilities or services in discrete space or networks, that are related to the public sector, such as emergency services (ambulances, fire stations, and police units), school systems and postal facilities. The paper is structured as follows: first, we will focus on public facility location models that use some type of coverage criterion, with special emphasis in emergency services. The second section will examine models based on the P-Median problem and some of the issues faced by planners when implementing this formulation in real world locational decisions. Finally, the last section will examine new trends in public sector facility location modeling.

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Recognition systems play a key role in a range of biological processes, including mate choice, immune defence and altruistic behaviour. Social insects provide an excellent model for studying recognition systems because workers need to discriminate between nestmates and non-nestmates, enabling them to direct altruistic behaviour towards closer kin and to repel potential invaders. However, the level of aggression directed towards conspecific intruders can vary enormously, even among workers within the same colony. This is usually attributed to differences in the aggression thresholds of individuals or to workers having different roles within the colony. Recent evidence from the weaver ant Oecophylla smaragdina suggests that this does not tell the whole story. Here I propose a new model for nestmate recognition based on a vector template derived from both the individual's innate odour and the shared colony odour. This model accounts for the recent findings concerning weaver ants, and also provides an alternative explanation for why the level of aggression expressed by a colony decreases as the diversity within the colony increases, even when odour is well-mixed. The model makes additional predictions that are easily tested, and represents a significant advance in our conceptualisation of recognition systems.

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In this paper we propose a metaheuristic to solve a new version of the Maximum Capture Problem. In the original MCP, market capture is obtained by lower traveling distances or lower traveling time, in this new version not only the traveling time but also the waiting time will affect the market share. This problem is hard to solve using standard optimization techniques. Metaheuristics are shown to offer accurate results within acceptable computing times.

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A new method of measuring joint angle using a combination of accelerometers and gyroscopes is presented. The method proposes a minimal sensor configuration with one sensor module mounted on each segment. The model is based on estimating the acceleration of the joint center of rotation by placing a pair of virtual sensors on the adjacent segments at the center of rotation. In the proposed technique, joint angles are found without the need for integration, so absolute angles can be obtained which are free from any source of drift. The model considers anatomical aspects and is personalized for each subject prior to each measurement. The method was validated by measuring knee flexion-extension angles of eight subjects, walking at three different speeds, and comparing the results with a reference motion measurement system. The results are very close to those of the reference system presenting very small errors (rms = 1.3, mean = 0.2, SD = 1.1 deg) and excellent correlation coefficients (0.997). The algorithm is able to provide joint angles in real-time, and ready for use in gait analysis. Technically, the system is portable, easily mountable, and can be used for long term monitoring without hindrance to natural activities.

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A new algorithm called the parameterized expectations approach(PEA) for solving dynamic stochastic models under rational expectationsis developed and its advantages and disadvantages are discussed. Thisalgorithm can, in principle, approximate the true equilibrium arbitrarilywell. Also, this algorithm works from the Euler equations, so that theequilibrium does not have to be cast in the form of a planner's problem.Monte--Carlo integration and the absence of grids on the state variables,cause the computation costs not to go up exponentially when the numberof state variables or the exogenous shocks in the economy increase. \\As an application we analyze an asset pricing model with endogenousproduction. We analyze its implications for time dependence of volatilityof stock returns and the term structure of interest rates. We argue thatthis model can generate hump--shaped term structures.

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Summary One of the major goals of cancer immunotherapy is the induction of a specific and effective antitumor cytotoxic T lymphocyte (CTL) response. However, the downregulation of Class I Major Histocompatibility Complexes (MHC) expression and the low level of tumor peptide presentation on tumor cell surface, ás well as the low immunogenicity of tumor specific antigens, limit the effectiveness of anti-tumor CTL responses. On the other hand, monoclonal antibodies, which bind with high affinity to tumor cell surface markers, are powerful tumor targeting tools. However, their capacity to .kill cancer cells is limited and mAb cancer treatments usually require the addition of different form of chemotherapy. The new cancer immunotherapy strategy described herein combines the advantage of the high tumor targeting capacity of monoclonal antibodies (mAb) with the powerful cytotoxicity of CD8 T lymphocytes directed against highly antigenic peptide-MHC complexes. Monoclonal antibody Fab fragments directed against a cell surface tumor associated antigen (TAA) are chemically coupled to soluble MHC class I complexes carrying a highly antigenic peptide. Antibody guided targeting and oligomerization of numerous antigenic class IMHC/peptide complexes on tumor cell surfaces can redirect the cytotoxicity of peptide-specific CD8 T cells towards target cancer cells. After the description of the production of murine anti-tumor xMHC/peptide conjugates in the first part of this thesis, the therapeutic potential of such conjugates were sequentially investigated in different syngeneic tumor mouse models. As a first proof of principle, transgenic OT-1 mice and later CEA transgenic C57BL/6 (B6) mice, adoptively transferred with OT-1 spleen cells and immunized with ovalbumin, were used as a model of high frequency of ova peptide specific T cells. In these mice, growth inhibition and regression of palpable colon carcinoma expressing CEA, were obtained by systemic injection of anti-CEA Fab/H-2Kb/ova peptide conjugates. Next, LCMV virus and influenza virus infection of B6 mice were used as viral models to redirect natural antiviral CTL responses to tumors via conjugates loaded with viral peptides. We showed that in mice infected with the LCMV virus, subcutaneous CEA-expressing tumor cells were inhibited by the H2Db/GP33 restricted anti-viral CTL response when preincubated before grafting with anti-CEA Fab-H-2Db/GP33 peptide conjugates. In mice infected with the influenza virus, lung metastases expressing the HER2 antigen were inhibited by the H-2Db/NP366 restricted CTLs response when preincubated before injection with anti-Her2 Fab-H-2Db/NP366 peptide conjugates. In the last chapter, the stability of the peptide in the anti-CEA Fab-H-2Db/GP33 conjugates was improved by the covalent photocross-link of the GP33 peptide in the H-2Db MHC groove. Thus, LCMV immune mice could reject CEA expressing tumors when treated with systemic injections of anti-CEA FabH-2Db/GP33 cross-linked conjugates. These results are encouraging for the potential application of this strategy in clinic. Such conjugates could be used alone in patients boosted by the relevant virus, or used in combination with existing T cell based ìmmunotherapy. Résumé Une des principales approches utilisées dans l'immunothérapie contre le cancer consiste en l'induction d'une réponse T cytotoxique (CTL) spécifiquement dirigée contre la tumeur. Cependant, le faible niveau d'expression des complexes majeurs d'histocompatibilité de classe I (CMH I) et de présentation des peptides tumoraux à la surface des cellules cancéreuses ainsi que la faible immunogenicité des antigens tumoraux, limitent l'efficacité de la réponse CTL. D'autre part,. l'injection d'anticorps monoclonaux (mAb), se liant avec une haute affinité aux marqueurs de surface des cellules tumorales, a fourni des résultats cliniques encourageant. Cependant l'efficacité de ces mAbs contre des tumeur solides reste limitée et necessite souvent l'addition de chimiotherapie. La nouvelle stratégie thérapeutique décrite dans ce travail associe le fort pouvoir de localisation des anticorps monoclonaux et le fort pouvoir cytotoxique des lymphocytes T CD8+. Des fragments Fab d'anticorps monoclonaux, dirigés contre des antigènes surexprimés à la surface de cellules tumorales, ont été chimiquement couplés à des CMH I solubles, portant un peptide fortement antigénique. Le ciblage et l'oligomérisation à la surface des cellules tumorales de nombreux CMH I présentant un peptide antigénique, va réorienter la cytotoxicité des cellules T CD8+ spécifiques du peptide présenté, vers les cellules tumorales cibles. Après une description de la production de conjugé anti-tumeur x CMH Upeptide dans la première partie de cette thèse, le potentiel thérapeutique de tels conjugés a été successivement étudiés in vivo dans différents modèles de tumeur syngénéiques. Tout d'abord, des souris OT-1 transgéniques, puis des souris C57BL/6 (B6) transférées avec des cellules de rate OT-1 puis immunisées avec l'ovalbumine, ont été employées comme modèle de haute fréquence de cellules T CD8+ spécifiques du peptide ova. Chez ces souris, l'inhibition de la croissance et la régression de nodules palpables de carcinomes exprimant l'antigène caccino embryonaire (ACE), ont été obtenues par l'injection systémique de conjugés anti-ACE Fab/H-2Kb/ova. Par la suite, l'infection de souris B6 par le virus LCMV et par le virus de la grippe, ont été utilisés comme modèles viraux pour redirigées des réponses anti-virales naturelles vers les tumeurs, en utilisant des conjugés chargés avec des peptides viraux. Nous avons montré que .chez les souris infectées par le LCMV, la croissance de carcinome sous-cutané est empêchée par la réponse anti-virale, spécifique du complexe H2Db/GP33, lorsque les cellules tumorales greffées sont pré-incubées avec des conjugés anti-CEA Fab-H-2Db/GP33. Dans le cas de souris infectées par le virus de la grippe, la métastatisation de mélanomes pulmonaires exprimant l'antigène HER-2 est inhibée par la réponse anti-virale spécifique du complexe H-2Db/NP366, après pré-incubation des cellules tumorales avec des conjugés anti-Her2 FabxH-2Db/NP366. Dans le dernier chapitre, la liaison covalente du peptide GP33 dans le complexe H-2Db a amélioré la stabilité des conjugés correspondants et a permis le traitement systémique de souris greffées avec des tumeurs exprimant l'ACE et infectées par le LCMV. L'ensemble de ces résultats sont encourageant pour l'application de cette strategie en clinique. De tels conjugués pourraient être employés seuls ou en combinaison avec des protocols d'immunisation peptidique anti-tumoral. Résumé pour un large public Dans les pays industrialisés, le cancer se situe au deuxième rang des causes de mortalité après les maladies cardiovasculaires. Les principaux traitement de nombreux cancers sont la chirurgie, en association avec la radiothérapie et la chimiothérapie. L'immunothérapie est l'une des nouvelles approches mises en oeuvre pour la lutte contre le cancer. Elle peut être humorale, et s'appuyer alors sur la perfusion d'anticorps monoclonaux dirigés contre des antigènes tumoraux, par exemple les anticorps dirigés contre les protéines oncogéniques Her-2/neu dans le cancer du sein. Ces anticorps ont le grand avantage de spécifiquement se localiser à la tumeur et d'induire la lyse ou d'inhiber la proliferation des cellules tumorales exprimant l'antigène. Certains sont utilisés en clinique pour le traitement de lymphomes, de carcinomes de l'ovaire et du sein ou encore de carcinomes metastatiques du côlon. Cependant l'efficacité de ces anticorps contre des tumeurs solides reste limitée et les traitements exigent souvent d'être combiner avec de la chimiothérapie. L'immunothérapie spécifique peut également être cellulaire et reposer sur une démarche de type vaccinal, consistant à générer des lymphocytes T cytotoxiques (cytotoxic T lymphocytes :CTL) capables de détruire spécifiquement les cellules malignes. Pour obtenir une réponse lymphocytaire T cytotoxique antitumorale, la cellule T doit reconnaître un antigène associé à la tumeur, présenté sous forme de peptide dans un complexe majeur d'histocompatibilité de classe I. Or les cellules tumorales ne presentent pas efficacement les peptides antigèniques, car elles se caractérisent par une diminution ou une absence d'expression des antigènes d'histocompatibilité de classe I, des molécules d'adhésion et des cytokines costimulatrices, et par une faible expression des antigènes associés aux tumeurs. C'est en partie pourquoi, malgré l'induction de fortes réponses CTL specifiquement dirigés contre des antigens tumoraux, les régressions tumorales obtenus grace à ces vaccinations sont relativement rares. Alors que chez les personnes atteintes du cancer on observe l'instauration d'une tolérance immunitaire vis-à-vis de la tumeur, à l'inverse, notre systeme immunitaire reste parfaitement capable de combattre des infection virales classiques, tels que la grippe, qui font aussi appel à une réponse T cytotoxique. Notre groupe de recherche a donc eu l'idee de développer une nouvelle approche thérapeutique où une réponse immunitaire anti-virale très efficace serait redirigée vers les tumeurs par des anticorps monoclonaux. Concrètement, nous avons chimiquement couplés des fragments d'anticorps monoclonaux dirigés contre des antigènes surexprimés à la surface de cellules tumorales, à des CMH I portant un peptide viral antigénique. Les cellules tumorales, ciblées par le fragment anticorps et couvertes d' antigènes viraux présentés par des molécules de CMH I, peuvent ainsi tromper les lymphocytes cytotoxiques anti-viraux qui vont détruire les cellules tumorales comme si elles étaient infectées par le virus. Suite à des résultats prometteurs obtenus in vitro avec différents conjugués anticorps-CMH humain de type HLA.A2/peptide Flu, le but du projet était de tester in vivo des conjugués anticorps-CMH I murins sur des modèles expérimentaux de souris. Tout d'abord, des souris transgéniques pour un recepteur T specifique du peptide ova, puis des transferts adoptifs de ces cellules T specifiques dans des souris immunocompétentes, ont été choisi comme modèle de haute fréquence des cellules T spécifiques, et ont permi de valider le principe de la strategie in vivo. Puis, deux modèles viraux ont été elaboré avec le virus LCMV et le virus Influenza, pour réorienter des réponses antivirales naturelles vers les tumeurs grâce à des conjugés chargés avec des peptides viraux. Nous avons montré la grande capacité de nos conjugués à rediriger des réponses cytotoxiques vers les tumeurs et inhiber la croissance de tumeurs syngénéiques sous cutanés et pulmonaires. Ces résultats d'inhibition tumorales obtenus dans des souris immunocompétentes, grâce à l'injection de conjugués anticorps xCMH/peptide et réorientant deux réponses antivirales différentes vers deux modèles tumoraux syngeneiques, sont encourageant pour l'application de cette nouvelle stratégie en clinique.

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Despite the advancement of phylogenetic methods to estimate speciation and extinction rates, their power can be limited under variable rates, in particular for clades with high extinction rates and small number of extant species. Fossil data can provide a powerful alternative source of information to investigate diversification processes. Here, we present PyRate, a computer program to estimate speciation and extinction rates and their temporal dynamics from fossil occurrence data. The rates are inferred in a Bayesian framework and are comparable to those estimated from phylogenetic trees. We describe how PyRate can be used to explore different models of diversification. In addition to the diversification rates, it provides estimates of the parameters of the preservation process (fossilization and sampling) and the times of speciation and extinction of each species in the data set. Moreover, we develop a new birth-death model to correlate the variation of speciation/extinction rates with changes of a continuous trait. Finally, we demonstrate the use of Bayes factors for model selection and show how the posterior estimates of a PyRate analysis can be used to generate calibration densities for Bayesian molecular clock analysis. PyRate is an open-source command-line Python program available at http://sourceforge.net/projects/pyrate/.

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This Article breaks new ground toward contractual and institutional innovation in models of homeownership, equity building, and mortgage enforcement. Inspired by recent developments in the affordable housing sector and other types of public financing schemes, we suggest extending institutional and financial strategies such as time- and place-based division of property rights, conditional subsidies, and credit mediation to alleviate the systemic risks of mortgage foreclosure. Two new solutions offer a broad theoretical basis for such developments in the economic and legal institution of homeownership: a for-profit shared equity scheme led by local governments alongside a private market shared equity model, one of "bootstrapping home buying with purchase options".

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When dealing with the design of service networks, such as healthand EMS services, banking or distributed ticket selling services, thelocation of service centers has a strong influence on the congestion ateach of them, and consequently, on the quality of service. In this paper,several models are presented to consider service congestion. The firstmodel addresses the issue of the location of the least number of single--servercenters such that all the population is served within a standard distance,and nobody stands in line for a time longer than a given time--limit, or withmore than a predetermined number of other clients. We then formulateseveral maximal coverage models, with one or more servers per service center.A new heuristic is developed to solve the models and tested in a 30--nodesnetwork.

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Departures from pure self interest in economic experiments have recently inspired models of "social preferences". We conduct experiments on simple two-person and three-person games with binary choices that test these theories more directly than the array of games conventionally considered. Our experiments show strong support for the prevalence of "quasi-maximin" preferences: People sacrifice to increase the payoffs for all recipients, but especially for the lowest-payoff recipients. People are also motivated by reciprocity: While people are reluctant to sacrifice to reciprocate good or bad behavior beyond what they would sacrifice for neutral parties, they withdraw willingness to sacrifice to achieve a fair outcome when others are themselves unwilling to sacrifice. Some participants are averse to getting different payoffs than others, but based on our experiments and reinterpretation of previous experiments we argue that behavior that has been presented as "difference aversion" in recent papers is actually a combination of reciprocal and quasi-maximin motivations. We formulate a model in which each player is willing to sacrifice to allocate the quasi-maximin allocation only to those players also believed to be pursuing the quasi-maximin allocation, and may sacrifice to punish unfair players.

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Studies assessing skin irritation to chemicals have traditionally used laboratory animals; however, such methods are questionable regarding their relevance for humans. New in vitro methods have been validated, such as the reconstructed human epidermis (RHE) model (Episkin®, Epiderm®). The comparison (accuracy) with in vivo results such as the 4-h human patch test (HPT) is 76% at best (Epiderm®). There is a need to develop an in vitro method that better simulates the anatomo-pathological changes encountered in vivo. To develop an in vitro method to determine skin irritation using human viable skin through histopathology, and compare the results of 4 tested substances to the main in vitro methods and in vivo animal method (Draize test). Human skin removed during surgery was dermatomed and mounted on an in vitro flow-through diffusion cell system. Ten chemicals with known non-irritant (heptylbutyrate, hexylsalicylate, butylmethacrylate, isoproturon, bentazon, DEHP and methylisothiazolinone (MI)) and irritant properties (folpet, 1-bromohexane and methylchloroisothiazolinone (MCI/MI)), a negative control (sodiumchloride) and a positive control (sodiumlaurylsulphate) were applied. The skin was exposed at least for 4h. Histopathology was performed to investigate irritation signs (spongiosis, necrosis, vacuolization). We obtained 100% accuracy with the HPT model; 75% with the RHE models and 50% with the Draize test for 4 tested substances. The coefficients of variation (CV) between our three test batches were <0.1, showing good reproducibility. Furthermore, we reported objectively histopathological irritation signs (irritation scale): strong (folpet), significant (1-bromohexane), slight (MCI/MI at 750/250ppm) and none (isoproturon, bentazon, DEHP and MI). This new in vitro test method presented effective results for the tested chemicals. It should be further validated using a greater number of substances; and tested in different laboratories in order to suitably evaluate reproducibility.

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This paper evaluates new evidence on price setting practices and inflation persistence in the euro area with respect to its implications for macro modelling. It argues that several of the most commonly used assumptions in micro-founded macro models are seriously challenged by the new findings.

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The paper presents a new model based on the basic Maximum Capture model,MAXCAP. The New Chance Constrained Maximum Capture modelintroduces astochastic threshold constraint, which recognises the fact that a facilitycan be open only if a minimum level of demand is captured. A metaheuristicbased on MAX MIN ANT system and TABU search procedure is presented tosolve the model. This is the first time that the MAX MIN ANT system isadapted to solve a location problem. Computational experience and anapplication to 55 node network are also presented.

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Revenue management (RM) is a complicated business process that can best be described ascontrol of sales (using prices, restrictions, or capacity), usually using software as a tool to aiddecisions. RM software can play a mere informative role, supplying analysts with formatted andsummarized data who use it to make control decisions (setting a price or allocating capacity fora price point), or, play a deeper role, automating the decisions process completely, at the otherextreme. The RM models and algorithms in the academic literature by and large concentrateon the latter, completely automated, level of functionality.A firm considering using a new RM model or RM system needs to evaluate its performance.Academic papers justify the performance of their models using simulations, where customerbooking requests are simulated according to some process and model, and the revenue perfor-mance of the algorithm compared to an alternate set of algorithms. Such simulations, whilean accepted part of the academic literature, and indeed providing research insight, often lackcredibility with management. Even methodologically, they are usually awed, as the simula-tions only test \within-model" performance, and say nothing as to the appropriateness of themodel in the first place. Even simulations that test against alternate models or competition arelimited by their inherent necessity on fixing some model as the universe for their testing. Theseproblems are exacerbated with RM models that attempt to model customer purchase behav-ior or competition, as the right models for competitive actions or customer purchases remainsomewhat of a mystery, or at least with no consensus on their validity.How then to validate a model? Putting it another way, we want to show that a particularmodel or algorithm is the cause of a certain improvement to the RM process compared to theexisting process. We take care to emphasize that we want to prove the said model as the causeof performance, and to compare against a (incumbent) process rather than against an alternatemodel.In this paper we describe a \live" testing experiment that we conducted at Iberia Airlineson a set of flights. A set of competing algorithms control a set of flights during adjacentweeks, and their behavior and results are observed over a relatively long period of time (9months). In parallel, a group of control flights were managed using the traditional mix of manualand algorithmic control (incumbent system). Such \sandbox" testing, while common at manylarge internet search and e-commerce companies is relatively rare in the revenue managementarea. Sandbox testing has an undisputable model of customer behavior but the experimentaldesign and analysis of results is less clear. In this paper we describe the philosophy behind theexperiment, the organizational challenges, the design and setup of the experiment, and outlinethe analysis of the results. This paper is a complement to a (more technical) related paper thatdescribes the econometrics and statistical analysis of the results.

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A new direction of research in Competitive Location theory incorporatestheories of Consumer Choice Behavior in its models. Following thisdirection, this paper studies the importance of consumer behavior withrespect to distance or transportation costs in the optimality oflocations obtained by traditional Competitive Location models. To dothis, it considers different ways of defining a key parameter in thebasic Maximum Capture model (MAXCAP). This parameter will reflectvarious ways of taking into account distance based on several ConsumerChoice Behavior theories. The optimal locations and the deviation indemand captured when the optimal locations of the other models are usedinstead of the true ones, are computed for each model. A metaheuristicbased on GRASP and Tabu search procedure is presented to solve all themodels. Computational experience and an application to 55-node networkare also presented.