Neighborhood and Efficiency in Manufacturing in Brazilian Regions: A Spatial Markov Chain Analysis

This paper analyzes the geography of regional competitiveness in manufacturing in Brazil. The authors estimate stochastic frontiers to calculate regional efficiency of representative firms in 137 regions in the period 2000-2006, in four sectors defined by technological intensity. The efficiency results are analyzed using Markov Spatial Transition Matrices to provide insights into the transition of regions between efficiency levels, considering their local spatial context. The results indicate that geography plays an important role in manufacturing competitiveness. In particular, regions with more competitive neighbors are more likely to improve their relative efficiency (pull effect) over time, and regions with less competitive neighbors are more likely to lose relative efficiency (drag effect). The authors find that the pull effect is stronger than the drag effect.

Efficient simulation of a Tandem Jackson Network

The two-node tandem Jackson network serves as a convenient reference model for the analysis and testing of different methodologies and techniques in rare event simulation. In this paper we consider a new approach to efficiently estimate the probability that the content of the second buffer exceeds some high level L before it becomes empty, starting from a given state. The approach is based on a Markov additive process representation of the buffer processes, leading to an exponential change of measure to be used in an importance sampling procedure. Unlike changes of measures proposed and studied in recent literature, the one derived here is a function of the content of the first buffer. We prove that when the first buffer is finite, this method yields asymptotically efficient simulation for any set of arrival and service rates. In fact, the relative error is bounded independent of the level L; a new result which is not established for any other known method. When the first buffer is infinite, we propose a natural extension of the exponential change of measure for the finite buffer case. In this case, the relative error is shown to be bounded (independent of L) only when the second server is the bottleneck; a result which is known to hold for some other methods derived through large deviations analysis. When the first server is the bottleneck, experimental results using our method seem to suggest that the relative error is bounded linearly in L.

The use of stochastic dynamic programming in optimal landscape reconstruction for metapopulations

A decision theory framework can be a powerful technique to derive optimal management decisions for endangered species. We built a spatially realistic stochastic metapopulation model for the Mount Lofty Ranges Southern Emu-wren (Stipiturus malachurus intermedius), a critically endangered Australian bird. Using diserete-time Markov,chains to describe the dynamics of a metapopulation and stochastic dynamic programming (SDP) to find optimal solutions, we evaluated the following different management decisions: enlarging existing patches, linking patches via corridors, and creating a new patch. This is the first application of SDP to optimal landscape reconstruction and one of the few times that landscape reconstruction dynamics have been integrated with population dynamics. SDP is a powerful tool that has advantages over standard Monte Carlo simulation methods because it can give the exact optimal strategy for every landscape configuration (combination of patch areas and presence of corridors) and pattern of metapopulation occupancy, as well as a trajectory of strategies. It is useful when a sequence of management actions can be performed over a given time horizon, as is the case for many endangered species recovery programs, where only fixed amounts of resources are available in each time step. However, it is generally limited by computational constraints to rather small networks of patches. The model shows that optimal metapopulation, management decisions depend greatly on the current state of the metapopulation,. and there is no strategy that is universally the best. The extinction probability over 30 yr for the optimal state-dependent management actions is 50-80% better than no management, whereas the best fixed state-independent sets of strategies are only 30% better than no management. This highlights the advantages of using a decision theory tool to investigate conservation strategies for metapopulations. It is clear from these results that the sequence of management actions is critical, and this can only be effectively derived from stochastic dynamic programming. The model illustrates the underlying difficulty in determining simple rules of thumb for the sequence of management actions for a metapopulation. This use of a decision theory framework extends the capacity of population viability analysis (PVA) to manage threatened species.

Equilibrium distributions of discrete non-autonomous graphs

We introduce the notions of equilibrium distribution and time of convergence in discrete non-autonomous graphs. Under some conditions we give an estimate to the convergence time to the equilibrium distribution using the second largest eigenvalue of some matrices associated with the system.

Topological entropy of catalytic sets: Hypercycles revisited

The dynamics of catalytic networks have been widely studied over the last decades because of their implications in several fields like prebiotic evolution, virology, neural networks, immunology or ecology. One of the most studied mathematical bodies for catalytic networks was initially formulated in the context of prebiotic evolution, by means of the hypercycle theory. The hypercycle is a set of self-replicating species able to catalyze other replicator species within a cyclic architecture. Hypercyclic organization might arise from a quasispecies as a way to increase the informational containt surpassing the so-called error threshold. The catalytic coupling between replicators makes all the species to behave like a single and coherent evolutionary multimolecular unit. The inherent nonlinearities of catalytic interactions are responsible for the emergence of several types of dynamics, among them, chaos. In this article we begin with a brief review of the hypercycle theory focusing on its evolutionary implications as well as on different dynamics associated to different types of small catalytic networks. Then we study the properties of chaotic hypercycles with error-prone replication with symbolic dynamics theory, characterizing, by means of the theory of topological Markov chains, the topological entropy and the periods of the orbits of unimodal-like iterated maps obtained from the strange attractor. We will focus our study on some key parameters responsible for the structure of the catalytic network: mutation rates, autocatalytic and cross-catalytic interactions.

Algorithms and methodologies for decision support in energy efficiency on buildings

Dissertação apresentada na faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

Comparing impact and cost-effectiveness of primary prevention strategies for lipid-lowering.

BACKGROUND: Lipid-lowering therapy is costly but effective at reducing coronary heart disease (CHD) risk. OBJECTIVE: To assess the cost-effectiveness and public health impact of Adult Treatment Panel III (ATP III) guidelines and compare with a range of risk- and age-based alternative strategies. DESIGN: The CHD Policy Model, a Markov-type cost-effectiveness model. DATA SOURCES: National surveys (1999 to 2004), vital statistics (2000), the Framingham Heart Study (1948 to 2000), other published data, and a direct survey of statin costs (2008). TARGET POPULATION: U.S. population age 35 to 85 years. Time Horizon: 2010 to 2040. PERSPECTIVE: Health care system. INTERVENTION: Lowering of low-density lipoprotein cholesterol with HMG-CoA reductase inhibitors (statins). OUTCOME MEASURE: Incremental cost-effectiveness. RESULTS OF BASE-CASE ANALYSIS: Full adherence to ATP III primary prevention guidelines would require starting (9.7 million) or intensifying (1.4 million) statin therapy for 11.1 million adults and would prevent 20,000 myocardial infarctions and 10,000 CHD deaths per year at an annual net cost of $3.6 billion ($42,000/QALY) if low-intensity statins cost $2.11 per pill. The ATP III guidelines would be preferred over alternative strategies if society is willing to pay $50,000/QALY and statins cost $1.54 to $2.21 per pill. At higher statin costs, ATP III is not cost-effective; at lower costs, more liberal statin-prescribing strategies would be preferred; and at costs less than $0.10 per pill, treating all persons with low-density lipoprotein cholesterol levels greater than 3.4 mmol/L (>130 mg/dL) would yield net cost savings. RESULTS OF SENSITIVITY ANALYSIS: Results are sensitive to the assumptions that LDL cholesterol becomes less important as a risk factor with increasing age and that little disutility results from taking a pill every day. LIMITATION: Randomized trial evidence for statin effectiveness is not available for all subgroups. CONCLUSION: The ATP III guidelines are relatively cost-effective and would have a large public health impact if implemented fully in the United States. Alternate strategies may be preferred, however, depending on the cost of statins and how much society is willing to pay for better health outcomes. FUNDING: Flight Attendants' Medical Research Institute and the Swanson Family Fund. The Framingham Heart Study and Framingham Offspring Study are conducted and supported by the National Heart, Lung, and Blood Institute.

Adaptive Continuous time Markov Chain Approximation Model to General Jump-Diusions

We propose a non-equidistant Q rate matrix formula and an adaptive numerical algorithm for a continuous time Markov chain to approximate jump-diffusions with affine or non-affine functional specifications. Our approach also accommodates state-dependent jump intensity and jump distribution, a flexibility that is very hard to achieve with other numerical methods. The Kolmogorov-Smirnov test shows that the proposed Markov chain transition density converges to the one given by the likelihood expansion formula as in Ait-Sahalia (2008). We provide numerical examples for European stock option pricing in Black and Scholes (1973), Merton (1976) and Kou (2002).

trEST, trGEN and Hits: access to databases of predicted protein sequences.

High throughput genome (HTG) and expressed sequence tag (EST) sequences are currently the most abundant nucleotide sequence classes in the public database. The large volume, high degree of fragmentation and lack of gene structure annotations prevent efficient and effective searches of HTG and EST data for protein sequence homologies by standard search methods. Here, we briefly describe three newly developed resources that should make discovery of interesting genes in these sequence classes easier in the future, especially to biologists not having access to a powerful local bioinformatics environment. trEST and trGEN are regularly regenerated databases of hypothetical protein sequences predicted from EST and HTG sequences, respectively. Hits is a web-based data retrieval and analysis system providing access to precomputed matches between protein sequences (including sequences from trEST and trGEN) and patterns and profiles from Prosite and Pfam. The three resources can be accessed via the Hits home page (http://hits. isb-sib.ch).

MAMOT: hidden Markov modeling tool.

Hidden Markov models (HMMs) are probabilistic models that are well adapted to many tasks in bioinformatics, for example, for predicting the occurrence of specific motifs in biological sequences. MAMOT is a command-line program for Unix-like operating systems, including MacOS X, that we developed to allow scientists to apply HMMs more easily in their research. One can define the architecture and initial parameters of the model in a text file and then use MAMOT for parameter optimization on example data, decoding (like predicting motif occurrence in sequences) and the production of stochastic sequences generated according to the probabilistic model. Two examples for which models are provided are coiled-coil domains in protein sequences and protein binding sites in DNA. A wealth of useful features include the use of pseudocounts, state tying and fixing of selected parameters in learning, and the inclusion of prior probabilities in decoding. AVAILABILITY: MAMOT is implemented in C++, and is distributed under the GNU General Public Licence (GPL). The software, documentation, and example model files can be found at http://bcf.isb-sib.ch/mamot

The cost-effectiveness and public health benefit of nalmefene added to psychosocial support for the reduction of alcohol consumption in alcohol-dependent patients with high/very high drinking risk levels: a Markov model.

OBJECTIVES: To determine whether nalmefene combined with psychosocial support is cost-effective compared with psychosocial support alone for reducing alcohol consumption in alcohol-dependent patients with high/very high drinking risk levels (DRLs) as defined by the WHO, and to evaluate the public health benefit of reducing harmful alcohol-attributable diseases, injuries and deaths. DESIGN: Decision modelling using Markov chains compared costs and effects over 5 years. SETTING: The analysis was from the perspective of the National Health Service (NHS) in England and Wales. PARTICIPANTS: The model considered the licensed population for nalmefene, specifically adults with both alcohol dependence and high/very high DRLs, who do not require immediate detoxification and who continue to have high/very high DRLs after initial assessment. DATA SOURCES: We modelled treatment effect using data from three clinical trials for nalmefene (ESENSE 1 (NCT00811720), ESENSE 2 (NCT00812461) and SENSE (NCT00811941)). Baseline characteristics of the model population, treatment resource utilisation and utilities were from these trials. We estimated the number of alcohol-attributable events occurring at different levels of alcohol consumption based on published epidemiological risk-relation studies. Health-related costs were from UK sources. MAIN OUTCOME MEASURES: We measured incremental cost per quality-adjusted life year (QALY) gained and number of alcohol-attributable harmful events avoided. RESULTS: Nalmefene in combination with psychosocial support had an incremental cost-effectiveness ratio (ICER) of £5204 per QALY gained, and was therefore cost-effective at the £20,000 per QALY gained decision threshold. Sensitivity analyses showed that the conclusion was robust. Nalmefene plus psychosocial support led to the avoidance of 7179 alcohol-attributable diseases/injuries and 309 deaths per 100,000 patients compared to psychosocial support alone over the course of 5 years. CONCLUSIONS: Nalmefene can be seen as a cost-effective treatment for alcohol dependence, with substantial public health benefits. TRIAL REGISTRATION NUMBERS: This cost-effectiveness analysis was developed based on data from three randomised clinical trials: ESENSE 1 (NCT00811720), ESENSE 2 (NCT00812461) and SENSE (NCT00811941).

Evaluation of adding a second marker to overcome Staphylococcus aureus spa typing homoplasies.

The utility of sequencing a second highly variable locus in addition to the spa gene (e.g., double-locus sequence typing [DLST]) was investigated to overcome limitations of a Staphylococcus aureus single-locus typing method. Although adding a second locus seemed to increase discriminatory power, it was not sufficient to definitively infer evolutionary relationships within a single multilocus sequence type (ST-5).

Cost-effectiveness analysis of a European primary-care physician training in smoking cessation counseling.

BACKGROUND: Physician training in smoking cessation counseling has been shown to be effective as a means to increase quit success. We assessed the cost-effectiveness ratio of a smoking cessation counseling training programme. Its effectiveness was previously demonstrated in a cluster randomized, control trial performed in two Swiss university outpatients clinics, in which residents were randomized to receive training in smoking interventions or a control educational intervention. DESIGN AND METHODS: We used a Markov simulation model for effectiveness analysis. This model incorporates the intervention efficacy, the natural quit rate, and the lifetime probability of relapse after 1-year abstinence. We used previously published results in addition to hospital service and outpatient clinic cost data. The time horizon was 1 year, and we opted for a third-party payer perspective. RESULTS: The incremental cost of the intervention amounted to US$2.58 per consultation by a smoker, translating into a cost per life-year saved of US$25.4 for men and 35.2 for women. One-way sensitivity analyses yielded a range of US$4.0-107.1 in men and US$9.7-148.6 in women. Variations in the quit rate of the control intervention, the length of training effectiveness, and the discount rate yielded moderately large effects on the outcome. Variations in the natural cessation rate, the lifetime probability of relapse, the cost of physician training, the counseling time, the cost per hour of physician time, and the cost of the booklets had little effect on the cost-effectiveness ratio. CONCLUSIONS: Training residents in smoking cessation counseling is a very cost-effective intervention and may be more efficient than currently accepted tobacco control interventions.

Stochastic models and numerical algorithms for a class of regulatory gene networks.

Regulatory gene networks contain generic modules, like those involving feedback loops, which are essential for the regulation of many biological functions (Guido et al. in Nature 439:856-860, 2006). We consider a class of self-regulated genes which are the building blocks of many regulatory gene networks, and study the steady-state distribution of the associated Gillespie algorithm by providing efficient numerical algorithms. We also study a regulatory gene network of interest in gene therapy, using mean-field models with time delays. Convergence of the related time-nonhomogeneous Markov chain is established for a class of linear catalytic networks with feedback loops.

Distribution asymptotique du nombre de diviseurs premiers distincts inférieurs ou égaux à m

Le sujet principal de ce mémoire est l'étude de la distribution asymptotique de la fonction f_m qui compte le nombre de diviseurs premiers distincts parmi les nombres premiers $p_1,...,p_m$. Au premier chapitre, nous présentons les sept résultats qui seront démontrés au chapitre 4. Parmi ceux-ci figurent l'analogue du théorème d'Erdos-Kac et un résultat sur les grandes déviations. Au second chapitre, nous définissons les espaces de probabilités qui serviront à calculer les probabilités asymptotiques des événements considérés, et éventuellement à calculer les densités qui leur correspondent. Le troisième chapitre est la partie centrale du mémoire. On y définit la promenade aléatoire qui, une fois normalisée, convergera vers le mouvement brownien. De là, découleront les résultats qui formeront la base des démonstrations de ceux chapitre 1.