Possible and Guaranteed Concurrency in CSP

In this paper we recast the classical Darondeau---Degano's causal semantics of concurrency in a coalgebraic setting, where we derive a compact model. Our construction is inspired by the one of Montanari and Pistore yielding causal automata, but we show that it is instance of an existing categorical framework for modeling the semantics of nominal calculi, whose relevance is further demonstrated. The key idea is to represent events as names, and the occurrence of a new event as name generation. We model causal semantics as a coalgebra over a presheaf, along the lines of the Fiore---Turi approach to the semantics of nominal calculi. More specifically, we take a suitable category of finite posets, representing causal relations over events, and we equip it with an endofunctor that allocates new events and relates them to their causes. Presheaves over this category express the relationship between processes and causal relations among the processes' events. We use the allocation operator to define a category of well-behaved coalgebras: it models the occurrence of a new event along each transition. Then we turn the causal transition relation into a coalgebra in this category, where labels only exhibit maximal events with respect to the source states' poset, and we show that its bisimilarity is essentially Darondeau---Degano's strong causal bisimilarity. This coalgebra is still infinite-state, but we exploit the equivalence between coalgebras over a class of presheaves and History Dependent automata to derive a compact representation, where states only retain the poset of the most recent events for each atomic subprocess, and are isomorphic up to order-preserving permutations. Remarkably, this reduction of states is automatically performed along the equivalence.

Causationin written natural language can express a strong relationship between events and facts. Causation in the written form can be referred to as a causal relation where a cause event entails the occurrence of an effect event. A cause and effect relationship is stronger than a correlation between events, and therefore aggregated causal relations extracted from large corpora can be used in numerous applications such as question-answering and summarisation to produce superior results than traditional approaches. Techniques like logical consequence allow causal relations to be used in niche practical applications such as event prediction which is useful for diverse domains such as security and finance. Until recently, the use of causal relations was a relatively unpopular technique because the causal relation extraction techniques were problematic, and the relations returned were incomplete, error prone or simplistic. The recent adoption of language models and improved relation extractors for natural language such as Transformer-XL (Daiet al. (2019).Transformer-xl: Attentive language models beyond a fixed-length context. arXiv preprintarXiv:1901.02860) has seen a surge of research interest in the possibilities of using causal relations in practical applications. Until now, there has not been an extensive survey of the practical applications of causal relations; therefore, this survey is intended precisely to demonstrate the potential of causal relations. It is a comprehensive survey of the work on the extraction of causal relations and their applications, while also discussing the nature of causation and its representation in text.

Learning commonsense causal and temporal relation between events is one of the major steps towards deeper language understanding. This is even more crucial for understanding stories and script learning. A prerequisite for learning scripts is a semantic framework which enables capturing rich event structures. In this paper we introduce a novel semantic annotation framework, called Causal and Temporal Relation Scheme (CaTeRS), which is unique in simultaneously capturing a comprehensive set of temporal and causal relations between events. By annotating a total of 1,600 sentences in the context of 320 five-sentence short stories sampled from ROCStories corpus, we demonstrate that these stories are indeed full of causal and temporal relations. Furthermore, we show that the CaTeRS annotation scheme enables high inter-annotator agreement for broad-coverage event entity annotation and moderate agreement on semantic link annotation.

The goal that the authors of the article set for themselves is to specify causal relationships between the systemic determinant of a linguistic type and its particular specific features at the levels of phonetics, morphology and syntax. The object of study is the agglutinative and inflectional types of languages that lie between the limiting manifestations of proximity and remoteness of individual consciousnesses. In their work, the authors rely on the systemic methodology of determinant typological analysis, developed in the 1960s - 70s by the founder of modern systems linguistics, Professor Gennady P. Melnikov.

Monitoring real-time concurrent systems is a challenging task. In this paper we formulate (model-based) supervision by means of hidden state history reconstruction, from event (e.g. alarm) observations. We follow a so-called true concurrency approach using time Petri nets: the model defines explicitly the causal and concurrency relations between the observable events, produced by the system under supervision on different points of observation, and constrained by time aspects.

Since the behavior is the essential characteristic of business process models, and ordering relations between execution of tasks can be used to describe the behavior of process models, we need to compute the ordering relations between tasks in process models. This computation can be used for compliance checking and querying process models based on behavior. There are three basic types of ordering relations between two events in a concurrent system, i.e., causal, conflict, and concurrency. In this paper, we refine the causal and concurrency relations with uncertainty according to whether one task is always executed with the other task in the same instance. To compute the refined ordering relations with uncertainty efficiently, we propose some rules for adjacent tasks and some transitive laws for nonadjacent tasks together with their proofs. Based on these rules and laws, we propose an algorithm to compute the refined ordering relations for acyclic process models based on unfolding technology. The algorithm has a biquadrate time to the size of complete prefix unfolding of the original model.

Monitoring real-time concurrent systems is a challenging task. In this paper we formulate (model-based) supervision by means of hidden state history reconstruction, from event (e.g. alarm) observations. We follow a so-called true concurrency approach using time Petri nets: the model defines explicitly the causal and concurrency relations between the observable events, produced by the system under supervision on different points of observation, and constrained by time aspects. The problem is to compute on-the-fly the different partial order histories, which are the possible explanations of the observable events. We do not impose that time is observable: the aim of supervision is to infer the partial ordering of the events and their possible firing dates. This is achieved by considering a model of the system under supervision, given as a time Petri net, and the on-the-fly construction of an unfolding, guided by the observations. Using a symbolic representation, this paper presents a new definition of the unfolding of time Petri nets with dense time.KeywordsPartial StateExtended ProcessConcurrent SystemExtended EventInput PlaceThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Introduction. Drinking water includes a multitude of natural elements, with a strong connection between them, which through the dynamics of their modification in many cases influence the health of the population.
 Material and methods. The quality of drinking water from the Prut river ecosystem was studied (water from aqueducts fed from the river, water from artesian wells, water from adjacent wells), health status of the population from riparian localities (Lipcani, Ungheni and Cahul). The correlations between these two indicators and the risk of population disease caused by water quality were calculated. Hygienic, epidemiological, sanitary-chemical and statistical methods of investigation were used.
 Results. Following the study, the existence of small and medium correlative dependencies between the water quality indices from the aqueduct fed from the Prut River and the prevalence of the main groups of nosology of morbidity was highlighted. High direct correlative dependencies of health indices on water quality in artesian wells and wells were quantified. The values of the risk of genito-urinary, osteo-articular, digestive system, blood diseases/anemia, etc. were determined.
 Conclusions. Finally, there was a causal relationship between the factors investigated and the health of the population, highlighting the risk of developing nosological forms.

In Hong Kong, a multidisciplinary team consisting of a pharmacist, a chemical pathologist, a scientific officer, and a physician has jointly provided an advisory service on herbal safety to healthcare professionals of all public hospitals since August 2000. This paper reports the first 2 years of experience of this team to emphasize the importance of a multidisciplinary approach to herbal poisoning. Twenty referrals received from the public hospitals from August 2000 to June 2002 were reviewed. The diagnosis of herbal toxicity was made after consideration of the temporal relationship between exposure to the herb and the occurrence of the adverse event and the exclusion of other causes. The causal relationship was seen as much stronger if the herb's pharmacological effects could fully explain the adverse event, if there were similar previous reports, and if the toxicological analysis findings were supportive. In 10 patients, the adverse events were deemed unlikely to be related to the use of herbal medicines. In 3 patients, it was concluded that the adverse events were possibly related to the use of herbal medicines. In 7 patients, the causal relationship was seen to be much stronger because the adverse events in these patients simply reflected the pharmacological effects of the herbs consumed and specific toxic ingredients were isolated from herbal residues and patients' urine or serum. The clinical problems arising from the use of herbal medicines included the Aristolochia species causing acute renal failure (n = 1), aconite roots causing aconitine poisoning (n = 2), the Datura species causing anticholinergic poisoning (n = 1), and "yulan" (Stephania sinica) causing tetrahydropalmatine poisoning (n = 3). The 4 patients with acute renal failure and tetrahydropalmatine poisoning received these toxic herbs, which were not listed in the prescriptions, as a result of poor dispensing practice or for other reasons. Toxicological problems associated with the use of herbal medicines are complex and may be easily overlooked. A multidisciplinary team of experts should be made available to provide advice to frontline healthcare professionals.

International audience

A logical characterization of well branching event structures

The classical experiment of Howard and Pelc (1) showed that the reproductive cycle of plant root cells was divisible into four periods of time: G1, S, G2, and M. This organization of cell reproductive events has come to serve as a conceptual foundation for the study of cell reproduction in a wide variety of unicellular and multicellular organisms. It is generally accepted that the cell cycle is a sequence of events that is based in turn on a set of specific genes termed the cell cycle genes. Presumably, the sequential occurrence of these cell cycle events is established by causal relationships between successively functioning products of cell cycle genes, e.g. in the simplest sense the occurrence of one event triggers the next, and so on. Thus, the orderliness of the events by which a cell progresses from division to division resides in underlying causal relationships among these events based on the cell cycle genes.

The relationship between Pacific blocking and large-scale circulation regimes is investigated. The large-scale circulation regimes are obtained by cluster analysis using the k-means method and tested against significance and reproducibility. Pacific blocking is described using two different methods. In a direct approach, blocking is described by a recently developed blocking index, which is defined in terms of potential temperature anomaly on a surface of constant potential vorticity. In an indirect approach, the occurrence of extreme events is used as a proxy for blockings. Between the two methods there is a causal relationship; the direct one is an indication of the occurrence of the blocking, while the indirect one is a measure of some of the effects caused by the blocking. The results indicate that large-scale circulation regimes are related to but not necessarily tightly coupled to blocking and weather extremes in the Pacific–North America region.

Immunization is the process whereby a person is made immune or resistant to an infectious disease, typically by the administration of a vaccine. However, like other medicinal products, vaccines are not free from adverse reactions. AEFI is any untoward medical occurrence which follows immunization and which does not necessarily have a causal relationship with the usage of the vaccine. The reporting of AEFI’s from the routine system is inadequate due to many reasons. Hence this study was conducted to throw some light and provide the baseline data. To find out the incidence of adverse events following immunization among infants in District Srinagar. It was a prospective study in which parents of infants receiving vaccines were contacted telephonically after specified time intervals to verify the occurrence of adverse events. The children were followed till 30 days of the administration of vaccines up to measles rubella vaccine. The incidence of AEFI reported in this study was 23.03% with 95% CI (22.24% to 23.85%). The most frequently reported AEFI was Fever (54.90%, n=1322), followed by Diarrhea (8.30%, n=200) and Vomiting (8.14%, n=196). AEFI were more in frequency during first week of receiving vaccine and most of the parents of children did not report AEFI after 7 days after vaccination. This study reveals that most of the vaccines associated adverse reactions were of mild and non-serious type and rarely of serious nature, yet proper monitoring of vaccine associated adverse reactions; is too essential. Proper and complete reporting of AEFI’s by field workers needs to be encouraged.

GFR is the accepted metric for evaluating renal function but measuring it directly (mGFR) can be cumbersome, time-consuming, and costly. The constant infusion method using inulin as the filtration marker, introduced in 1934 by Richards and Smith (1), has undergone many revisions that have now made mGFR easier to perform, although not widely available (2,3). A simple, reliable, unbiased, precise, and accurate estimation of mGFR, without reliance on constant infusions or timed urinary collections, would be welcome; however, as illustrated by the extensive compendium of comparisons of mGFR (using classical inulin clearance methods) to eGFR by Botev et al. (4) in this issue of CJASN , this objective is far from being realized. Although formulaic methods to approximate the values of mGFR from serum creatinine (Scr) levels have been used for many decades, the seminal description of the Modification of Diet in Renal Disease (MDRD) equation (eGFR-MDRD) in 1999 galvanized interest in this common and important clinical issue (5). The often used Cockcroft-Gault equation (6) was never intended to be an approximation of GFR but rather was designed to estimate endogenous creatinine clearance, which is not equivalent to GFR because of the effects of tubular secretion of creatinine (TScr). In normal individuals, this can be compensated for by a correction factor, because TScr is relatively constant (at approximately 22 to 24% of GFR) (7); however, TScr can vary markedly in disease states, particularly those associated with heavy proteinuria (8). Compared with mGFR, the current widely used eGFR-MDRD formulas (original and reexpressed [5,9]) have limitations because of variable degrees of bias, imprecision, and inaccuracy (10). The studies of Botev et al. (4) in this issue of CJASN provide additional quantitative data on the ranges of bias, precision, and accuracy of eGFR-MDRD according to the levels …