A compositional Semantics for CHR

Constraint Handling Rules (CHR) are a committed-choice declarative language which has been designed for writing constraint solvers. A CHR program consists of multi-headed guarded rules which allow one to rewrite constraints into simpler ones until a solved form is reached. CHR has received a considerable attention, both from the practical and from the theoretical side. Nevertheless, due the use of multi-headed clauses, there are several aspects of the CHR semantics which have not been clarified yet. In particular, no compositional semantics for CHR has been defined so far. In this paper we introduce a fix-point semantics which characterizes the input/output behavior of a CHR program and which is and-compositional, that is, which allows to retrieve the semantics of a conjunctive query from the semantics of its components. Such a semantics can be used as a basis to define incremental and modular analysis and verification tools

Constraint programming for flexible service function chaining deployment

Network Function Virtualization (NFV) and Software Defined Networking (SDN) are technologies that recently acquired a great momentum thanks to their promise of being a flexible and cost-effective solution for replacing hardware-based, vendor-dependent network middleboxes with software appliances running on general purpose hardware in the cloud. Delivering end-to-end networking services across multiple NFV/SDN network domains by implementing the so-called Service Function Chain (SFC) i.e., a sequence of Virtual Network Functions (VNF) that composes the service, is a challenging task. In this paper we address two crucial sub-problems of this task: i) the language to formalize the request of a given SFC to the network and ii) the solution of the SFC design problem, once the request is received. As for i) in our solution the request is built upon the intent-based approach, with a syntax that focuses on asking the user "what" she needs and not "how" it should be implemented, in a simple and high level language. Concerning ii) we define a formal model describing network architectures and VNF properties that is then used to solve the SFC design problem by means of Constraint Programming (CP), a programming paradigm which is often used in Artificial Intelligence applications. We argue that CP can be effectively used to address this kind of problems because it provides very expressive and flexible modeling languages which come with powerful solvers, thus providing efficient and scalable performance. We substantiate this claim by validating our tool on some typical and non trivial SFC design problems

Patterns of Long COVID Symptoms: A Multi-Center Cross Sectional Study

Background: Long COVID has become a burden on healthcare systems worldwide. Research into the etiology and risk factors has been impeded by observing all diverse manifestations as part of a single entity. We aimed to determine patterns of symptoms in convalescing COVID-19 patients. Methods: Symptomatic patients were recruited from four countries. Data were collected regarding demographics, comorbidities, acute disease and persistent symptoms. Factor analysis was performed to elucidate symptom patterns. Associations of the patterns with patients’ characteristics, features of acute disease and effect on daily life were sought. Results: We included 1027 symptomatic post-COVID individuals in the analysis. The majority of participants were graded as having a non-severe acute COVID-19 (N = 763, 74.3%). We identified six patterns of symptoms: cognitive, pain-syndrome, pulmonary, cardiac, anosmia-dysgeusia and headache. The cognitive pattern was the major symptoms pattern, explaining 26.2% of the variance; the other patterns each explained 6.5–9.5% of the variance. The cognitive pattern was higher in patients who were outpatients during the acute disease. The pain-syndrome pattern was associated with acute disease severity, higher in women and increased with age. The pulmonary pattern was associated with prior lung disease and severe acute disease. Only two of the patterns (cognitive and cardiac) were associated with failure to return to pre-COVID occupational and physical activity status. Conclusion: Long COVID diverse symptoms can be grouped into six unique patterns. Using these patterns in future research may improve our understanding of pathophysiology and risk factors of persistent COVID, provide homogenous terminology for clinical research, and direct therapeutic interventions