A Compositional Semantics for Stochastic Reo Connectors

In this paper we present a compositional semantics for the channel-based coordination language Reo which enables the analysis of quality of service (QoS) properties of service compositions. For this purpose, we annotate Reo channels with stochastic delay rates and explicitly model data-arrival rates at the boundary of a connector, to capture its interaction with the services that comprise its environment. We propose Stochastic Reo automata as an extension of Reo automata, in order to compositionally derive a QoS-aware semantics for Reo. We further present a translation of Stochastic Reo automata to Continuous-Time Markov Chains (CTMCs). This translation enables us to use third-party CTMC verification tools to do an end-to-end performance analysis of service compositions.Comment: In Proceedings FOCLASA 2010, arXiv:1007.499

A Formal and Tool-Equipped Approach for the Integration of State Diagrams and Formal Datatypes

International audienceSeparation of concerns or aspects is a way to deal with the increasing complexity of systems. The separate design of models for different aspects also promotes a better reusability level. However, an important issue is then to define means to integrate them into a global model. We present a formal and tool-equipped approach for the integration of dynamic models (behaviors expressed using state diagrams) and static models (formal data types) with the benefit to share advantages of both: graphical user-friendly models for behaviors, formal and abstract models for data types. Integration is achieved in a generic way so that it can deal with both different static specification languages (algebraic specifications, Z, B) and different dynamic specification semantic

Impact of changing US cigarette smoking patterns on incident cancer: Risks of 20 smoking-related cancers among the women and men of the NIH-AARP cohort

Background: Historically, US women started smoking at a later age than men and had lower relative risks for smoking-related cancers. However, more recent birth cohorts of women and men have similar smoking histories and have now reached the high-risk age for cancer. The impact of these changes on cancer incidence has not been systematically examined. Methods: Relative risks (RR), 95% confidence intervals (CI) and attributable fractions were calculated for cigarette smoking and incidence of 20 smoking-related cancers in 186 057 women and 266 074 men of the National Institutes of Health-AARP cohort, aged 50 to 71 years in 1995 and followed for 11 years. Results: In the cohort, which included participants born between 1924 and 1945, most women and men started smoking as teenagers. RRs for current vs never smoking were similar in women and men for the following cancers: lung squamous-cell (RR women: 121.4, 95% CI: 57.3–257.4; RR men:114.6, 95% CI: 61.2–214.4), lung adenocarcinoma (RR women: 11.7, 95% CI: 9.8–14.0; RR men: 15.6, 95% CI: 12.5–19.6), laryngeal (RR women: 37.0, 95% CI: 14.9–92.3; RR men: 13.8, 95% CI: 9.3–20.2), oral cavity-pharyngeal (RR women:4.4, 95% CI: 3.3–6.0; RR men: 3.8, 95% CI: 3.0–4.7), oesophageal squamous cell (RR women: 7.3, 95% CI: 3.5–15.5; RR men: 6.2, 95% CI: 2.8–13.7), bladder (RR women: 4.7, 95% CI: 3.7–5.8; RR men: 4.0, 95% CI: 3.5–4.5), colon (RR women: 1.3, 95% CI: 1.2–1.5; RR men: 1.3, 95% CI: 1.1–1.4), and at other sites, with similar attributable fractions. Conclusions: RRs for current smoking and incidence of many smoking-related cancers are now similar in US women and men, likely reflecting converging smoking patterns

The economic trade-offs of large language models: A case study

Contacting customer service via chat is a common practice. Because employing customer service agents is expensive, many companies are turning to NLP that assists human agents by auto-generating responses that can be used directly or with modifications. Large Language Models (LLMs) are a natural fit for this use case; however, their efficacy must be balanced with the cost of training and serving them. This paper assesses the practical cost and impact of LLMs for the enterprise as a function of the usefulness of the responses that they generate. We present a cost framework for evaluating an NLP model's utility for this use case and apply it to a single brand as a case study in the context of an existing agent assistance product. We compare three strategies for specializing an LLM - prompt engineering, fine-tuning, and knowledge distillation - using feedback from the brand's customer service agents. We find that the usability of a model's responses can make up for a large difference in inference cost for our case study brand, and we extrapolate our findings to the broader enterprise space.Comment: Paper to be published at the Association for Computational Linguistics in the Industry Track 202

Multilevel Contracts for Trusted Components

This article contributes to the design and the verification of trusted components and services. The contracts are declined at several levels to cover then different facets, such as component consistency, compatibility or correctness. The article introduces multilevel contracts and a design+verification process for handling and analysing these contracts in component models. The approach is implemented with the COSTO platform that supports the Kmelia component model. A case study illustrates the overall approach.Comment: In Proceedings WCSI 2010, arXiv:1010.233

Key Data Elements in Myeloid Leukemia

Data standards consisting of key data elements for clinical routine and trial documentation harmonize documentation within and across different health care institutions making documentation more efficient and improving scientific data analysis. This work focusses on the field of myeloid leukemia (ML), where a semantic core of common data elements (CDEs) in routine and trial documentation is established by automatic UMLS-based form analysis of existing documentation models. These CDEs (n=227) were initially reviewed and commented by leukemia experts before they were systematically surveyed by an international voting process through seven hematologists of four countries. The total agreement score was 86%. 116 elements (51%) of these share an agreement score of 100%. This work generated CDEs with language-independent semantic codes and international clinical expert review to build a first approach towards an international data standard for ML. A first version of the CDE list is implemented in the data standard Operational Data Model and additional other data formats for reuse in different medical information systems

COVID-19 Vaccination in those with mental health difficulties: A guide to assist decision-making in England, Scotland, and Wales

There is currently no specific guidance addressing vaccine hesitancy in those with mental health difficulties in the United Kingdom. This is particularly problematic when one considers that individuals with serious mental illnesses are at greater risk of infection and have poorer health outcomes for a range of reasons. There are also many individual and system level barriers to vaccination in this group. When an affected adult lacks the capacity to make a decision for themselves, it often falls to healthcare professionals to make a decision on that person's behalf and in their best interests. This article explores this matter with regard to the law in practice in the English and Welsh, and Scottish, jurisdictions and consider this with relevance to the safest approach that doctors and other healthcare professionals should take in working with patients for whom mental disorder may impact on decision-making capacity. The article focuses on psychiatric inpatients, including those who are detained involuntarily, to consider whether, and in what circumstances, COVID-19 vaccination should be given to individuals who cannot or do not consent

The PedAL/EuPAL Project:A Global Initiative to Address the Unmet Medical Needs of Pediatric Patients with Relapsed or Refractory Acute Myeloid Leukemia

The prognosis of children with acute myeloid leukemia (AML) has improved incrementally over the last few decades. However, at relapse, overall survival (OS) is approximately 40–50% and is even lower for patients with chemo-refractory disease. Effective and less toxic therapies are urgently needed for these children. The Pediatric Acute Leukemia (PedAL) program is a strategic global initiative that aims to overcome the obstacles in treating children with relapsed/refractory acute leukemia and is supported by the Leukemia and Lymphoma Society in collaboration with the Children’s Oncology Group, the Innovative Therapies for Children with Cancer consortium, and the European Pediatric Acute Leukemia (EuPAL) foundation, amongst others. In Europe, the study is set up as a complex clinical trial with a stratification approach to allocate patients to sub-trials of targeted inhibitors at relapse and employing harmonized response and safety definitions across sub-trials. The PedAL/EuPAL international collaboration aims to determine new standards of care for AML in a first and second relapse, using biology-based selection markers for treatment stratification, and deliver essential data to move drugs to front-line pediatric AML studies. An overview of potential treatment targets in pediatric AML, focused on drugs that are planned to be included in the PedAL/EuPAL project, is provided in this manuscript.</p

The PedAL/EuPAL Project:A Global Initiative to Address the Unmet Medical Needs of Pediatric Patients with Relapsed or Refractory Acute Myeloid Leukemia

The prognosis of children with acute myeloid leukemia (AML) has improved incrementally over the last few decades. However, at relapse, overall survival (OS) is approximately 40–50% and is even lower for patients with chemo-refractory disease. Effective and less toxic therapies are urgently needed for these children. The Pediatric Acute Leukemia (PedAL) program is a strategic global initiative that aims to overcome the obstacles in treating children with relapsed/refractory acute leukemia and is supported by the Leukemia and Lymphoma Society in collaboration with the Children’s Oncology Group, the Innovative Therapies for Children with Cancer consortium, and the European Pediatric Acute Leukemia (EuPAL) foundation, amongst others. In Europe, the study is set up as a complex clinical trial with a stratification approach to allocate patients to sub-trials of targeted inhibitors at relapse and employing harmonized response and safety definitions across sub-trials. The PedAL/EuPAL international collaboration aims to determine new standards of care for AML in a first and second relapse, using biology-based selection markers for treatment stratification, and deliver essential data to move drugs to front-line pediatric AML studies. An overview of potential treatment targets in pediatric AML, focused on drugs that are planned to be included in the PedAL/EuPAL project, is provided in this manuscript.</p