On the Impact of Fast Failure Detectors on Real-Time Fault-Tolerant Systems

Abstract. We investigate whether fast failure detectors can be useful — and if so by how much — in the design of real-time fault-tolerant systems. Specifically, we show how fast failure detectors can speed up consensus and fault-tolerant broadcasts, by providing fast algorithms and deriving some matching lower bounds, for synchronous systems with crashes. These results show that a fast failure detector service (implemented using specialized hardware or expedited message delivery) can be an important tool in the design of real-time mission-critical systems.

Relatório de Revisão pela Gestão de 2014

We introduce the concept of cognitive design pattern to provide a design methodology for distributed multi-agent systems. A cognitive design pattern is a reusable solution to tackle problems requiring cognitive abilities (e.g. decision-making, attention, categorisation). It provides theoretical models and design guidelines to define the individual control rules in order to obtain a desired behaviour for the multiagent system as a whole. In this paper, we propose a cognitive design pattern for collective decision-making inspired by the nest-site selection behaviour of honeybee swarms. We illustrate how to apply the pattern to a case study involving spatial factors: the collective selection of the shortest path between two target areas. We analyse the dynamics of the multi-agent system and we show a very good agreement with the predictions of the macroscopic model.SCOPUS: ar.kinfo:eu-repo/semantics/publishe

Associations between polygenic risk score loading, psychosis liability, and clozapine use among individuals with schizophrenia

Importance: Predictors consistently associated with psychosis liability and course of illness in schizophrenia (SCZ) spectrum disorders (SSD), including the need for clozapine treatment, are lacking. Longitudinally ascertained medication use may empower studies examining associations between polygenic risk scores (PRSs) and pharmacotherapy choices. Objective: To examine associations between PRS-SCZ loading and groups with different liabilities to SSD (individuals with SSD taking clozapine, individuals with SSD taking other antipsychotics, their parents and siblings, and unrelated healthy controls) and between PRS-SCZ and the likelihood of receiving a prescription of clozapine relative to other antipsychotics. Design, Setting, and Participants: This genetic association study was a multicenter, observational cohort study with 6 years of follow-up. Included were individuals diagnosed with SSD who were taking clozapine or other antipsychotics, their parents and siblings, and unrelated healthy controls. Data were collected from 2004 until 2021 and analyzed between October 2021 and September 2022. Exposures: Polygenic risk scores for SCZ. Main Outcomes and Measures: Multinomial logistic regression was used to examine possible differences between groups by computing risk ratios (RRs), ie, ratios of the probability of pertaining to a particular group divided by the probability of healthy control status. We also computed PRS-informed odd ratios (ORs) for clozapine use relative to other antipsychotics. Results: Polygenic risk scores for SCZ were generated for 2344 participants (mean [SD] age, 36.95 years [14.38]; 994 female individuals [42.4%]) who remained after quality control screening (557 individuals with SSD taking clozapine, 350 individuals with SSD taking other antipsychotics during the 6-year follow-up, 542 parents and 574 siblings of individuals with SSD, and 321 unrelated healthy controls). All RRs were significantly different from 1; RRs were highest for individuals with SSD taking clozapine (RR, 3.24; 95% CI, 2.76-3.81; P = 2.47 × 10−46), followed by individuals with SSD taking other antipsychotics (RR, 2.30; 95% CI, 1.95-2.72; P = 3.77 × 10−22), parents (RR, 1.44; 95% CI, 1.25-1.68; P = 1.76 × 10−6), and siblings (RR, 1.40; 95% CI, 1.21-1.63; P = 8.22 × 10−6). Polygenic risk scores for SCZ were positively associated with clozapine vs other antipsychotic use (OR, 1.41; 95% CI, 1.22-1.63; P = 2.98 × 10−6), suggesting a higher likelihood of clozapine prescriptions among individuals with higher PRS-SCZ. Conclusions and Relevance: In this study, PRS-SCZ loading differed between groups of individuals with SSD, their relatives, and unrelated healthy controls, with patients taking clozapine at the far end of PRS-SCZ loading. Additionally, PRS-SCZ was associated with a higher likelihood of clozapine prescribing. Our findings may inform early intervention and prognostic studies of the value of using PRS-SCZ to personalize antipsychotic treatment